University of Iowa
Iowa Research Online
Theses and Dissertations
Fall 2013
Microrna regulation of central nervous system
development and their species-specific role in
evolution
Hayley Sarah McLoughlin
University of Iowa
Copyright 2013 Hayley Sarah McLoughlin
This dissertation is available at Iowa Research Online: http://ir.uiowa.edu/etd/5024
Recommended Citation
McLoughlin, Hayley Sarah. "Microrna regulation of central nervous system development and their species-specific role in evolution."
PhD (Doctor of Philosophy) thesis, University of Iowa, 2013.
http://ir.uiowa.edu/etd/5024.
Follow this and additional works at: http://ir.uiowa.edu/etd
Part of the Neuroscience and Neurobiology Commons
MICRORNA REGULATION OF CENTRAL NERVOUS SYSTEM DEVELOPMENT
AND THEIR SPECIES-SPECIFIC ROLE IN EVOLUTION
by
Hayley Sarah McLoughlin
A thesis submitted in partial fulfillment
of the requirements for the Doctor of
Philosophy degree in Neuroscience
in the Graduate College of
The University of Iowa
December 2013
Thesis Supervisor: Professor Beverly L. Davidson
Graduate College
The University of Iowa
Iowa City, Iowa
CERTIFICATE OF APPROVAL
_______________________
PH.D. THESIS
_______________
This is to certify that the Ph.D. thesis of
Hayley Sarah McLoughlin
has been approved by the Examining Committee
for the thesis requirement for the Doctor of Philosophy
degree in Neuroscience at the December 2013 graduation.
Thesis Committee: ___________________________________
Beverly L. Davidson, Thesis Supervisor
___________________________________
Pedro Gonzalez-Alegre
___________________________________
Gloria Lee
___________________________________
Robert Cornell
___________________________________
Yi Xing
To my beloved husband, James, infinitely supportive
ii
ACKNOWLEDGMENTS
This project would not have been possible without the support of many people.
Many thanks to my advisor, Bev Davidson, who has shown me over the past four and a
half years how a women can thrive as a scientist by cultivating a scientific sagacity,
adding lot of hard work, staying diligent, and remembering to maintain a home-life
balance. Much appreciation to Luis Tecedor for his technical training and guidance
throughout my first research project. Thanks to Mark Schultz, Edgar Rodriguez, Ryan
Spengler, Pavi Ramachandran, and all other lab members for their assistance and advice
on all things research. Also thank you to my committee members, Yi Xing, Rob Cornell,
Pedro Gonzalez-Alegre, and Gloria Lee, who offered guidance and support these past few
years. Much gratitude to the University of Iowa Neuroscience program for the
opportunity to transform my scientific interests into a career. Finally many thanks to my
family, whose encouragement and love have been a constant in all I have pursued. Most
importantly, I am infinitely grateful to my husband James, the love of my life, for being
my unwavering and unconditional cornerstone throughout my graduate career.
iii
ABSTRACT
Genetic dissection of loci important in the control of neurogenesis has improved
our understanding of both the evolutionarily conserved and divergent processes in
neurodevelopment. These loci include not only protein coding genes [1, 2], but also
noncoding RNAs [3-5]. One important family of non-coding RNAs is miRNAs, which
control gene expression fundamental in developmental regulation and mature cell
maintenance [3, 5-9].
Here, we will first focus our efforts by surveying miRNA regulation in the
developing brain. We hypothesize a strong regulatory role of miRNAs during
proliferation, cell death, migration and differentiation in the developing mammalian
forebrain that has yet to be adequately described in the literature. Second, we will assess
miRNA’s role in the evolutionary divergence of brain-related gene expression. We
hypothesize that a human specific single nucleotide change(s) in the miRNA recognition
element of transcription factors 3’ untranslated regions contributes to species-specific
differences in transcription factor expression and ultimately alters regulatory function.
iv
TABLE OF CONTENTS
LIST OF TABLES ............................................................................................................ vii
LIST OF FIGURES ......................................................................................................... viii
LIST OF ABBREVIATIONS ............................................................................................. x
CHAPTER I: INTRODUCTION ........................................................................................ 1
MiRNA Regulation ................................................................................................. 1
MiRNA Biogenesis ..................................................................................... 1
MiRNA Post-Transcriptional Regulation ................................................... 2
MRE Prediction .......................................................................................... 3
MiRNA Regulation in Neural Development .............................................. 4
Conditional Dicer Depletion and Mouse Models ........................... 5
Alternative Functions of Dicer........................................................ 6
Benefits of MiRNAs for Therapeutic Interventions ....................... 7
Proposed Mechanisms for MiRNA Regulatory Diversity .......................... 7
Gene Regulatory Networks ..................................................................................... 9
Transcription Factor Regulation ................................................................. 9
TF:MiRNA Circuitry .................................................................................. 9
TF:MiRNA Circuitry Evolutionary Impact .............................................. 10
Summary ............................................................................................................... 10
Published Work..................................................................................................... 11
CHAPTER II: DICER IS REQUIRED FOR PROLFIERATION, VIABILITY,
MIGRATION AND DIFFERENTIATION IN CORTICONEUROGENESIS ................ 15
Abstract ................................................................................................................. 15
Introduction ........................................................................................................... 16
Results ................................................................................................................... 18
Gross Cortical Abnormalities of Dicer Depleted Mice............................. 19
Dicer Inactivation Reduces Cell Division................................................. 20
Dicer Depletion Induces Increased Apoptosis in Late Corticogenesis ..... 21
Dicer Deficient Mice Have Dysregulated Neuronal Migration and
Differentiation ........................................................................................... 22
Discussion ............................................................................................................. 23
Dicer Depletion Impacts Proliferating Cells and Induces Cell Death ...... 24
Effect of MiRNA Depltion in Migration and Differentiation in
Developing Cortex .................................................................................... 25
Dicer Depletion Leads to a Precocious Induction of Astrocyte
Differentiation ........................................................................................... 27
Materials and Methods .......................................................................................... 28
Animal Care and Use ................................................................................ 28
Embryo Collection .................................................................................... 38
Immunohistochemistry ............................................................................. 29
RNA In Situ Hybridization ....................................................................... 30
Microscopy and Statistics ......................................................................... 31
v
RNA Isolation and RT-qPCR Analysis .................................................... 32
CHAPTER III: HUMAN-SPECIFIC MIRNA REGULATION OF FOXO1:
IMPLICATIONS FOR MIRNA RECOGNITION ELEMENT EVOLUTION ............. 44
Abstract ................................................................................................................. 44
Introduction ........................................................................................................... 45
Results ................................................................................................................... 47
Selection of Candidate Human-Specific MRE ......................................... 47
Human FOXO1 Contains Predicted MiR-183 Regulatory Sites .............. 48
MiR-183 Targets Endogenous FOXO1 at the Human-Specific MRE...... 50
Functional Implications of Human FOXO1 Regulation by MiR-183:
Cellular Invasion ....................................................................................... 52
Functional Implications of Human FOXO1 Regulation by MiR-183:
Cellular Proliferation ................................................................................ 53
Discussion ............................................................................................................. 53
Materials and Methods .......................................................................................... 56
Bioinformatic Analysis ............................................................................. 56
PITA Target Site Predictions .................................................................... 57
Cell Cultures ............................................................................................. 58
PsiCHECKTM-2 Dual Luciferase 3’UTR Plasmids .................................. 58
Perfect Target Luciferase Controls ........................................................... 58
PsiCHECKTM-2 Dual Luciferase Assay ................................................... 59
Site Directed Mutagenesis ........................................................................ 59
Overexpression In Vitro Studies ............................................................... 60
Target Site Protectors Transfections ......................................................... 60
RNA Isolation and RT-qPCR Analysis .................................................... 60
Western Blot Assay................................................................................... 61
Invasion Assay .......................................................................................... 61
PI Flow Cytometric Analysis for DNA Content ....................................... 62
Statistics .................................................................................................... 63
CHAPTER IV: CONCLUSIONS AND FUTURE DIRECTIONS .................................. 82
Cell Specific Regulation and Transcriptome Wide Mapping of MREs ............... 82
HITS-CLIP ................................................................................................ 82
PAR-CLIP ................................................................................................. 83
CLASH ..................................................................................................... 83
Identification of MiRNAs that Cause Dicer Phenotypes .......................... 85
Evolutionary Prospective of TF MRE regulation ................................................. 86
Analysis of the Human-Specific FOXO1 MRE In Vivo ........................... 86
Investigate Additional Gain of Human-Specific TF MREs Functional
Implications............................................................................................... 86
Summary ............................................................................................................... 88
REFERENCES ................................................................................................................. 90
vi
LIST OF TABLES
Table 1:
List of MiRNA Target Prediction Tools. ........................................................ 13
Table 2:
List of Functional Impairment After Conditional Dicer Elimination. ............ 14
Table 3:
Bioinformatic Predictions of Human-Specific MREs in TF 3'UTR ............... 89
vii
LIST OF FIGURES
Figure 1: MiRNA Biogenesis ......................................................................................... 12
Figure 2: Transgenic Breeding Scheme ......................................................................... 33
Figure 3: Nestin and MAP2 Dysregulation in Nestin-Cre Dicer Depleted Cerebral
Cortices. .......................................................................................................... 34
Figure 4: Decreased in Progenitor Cell Proliferation in Dicer Depleted Cortical
Tissue. ............................................................................................................. 35
Figure 5: Reduction in Proliferation and Cell Cycle Kinetics in Dicer Depleted
Brains. ............................................................................................................. 36
Figure 6: Increased Apoptotic Cell Death in Dicer Depleted Cortical Tissues. ............. 37
Figure 7: Impaired Migration of C-R Neurons in the Dicer Depleted Cerebral
Cortex.............................................................................................................. 38
Figure 8: Overexpression of Reelin in Dicer Depleted Cerebral Cortices. .................... 39
Figure 9: Reduced Immature Migrating Neurons in Dicer Depleted Cortices. .............. 40
Figure 10: Overexpression of Rnd2, a Multipolar to Bipolar Transition Regulator
in Dicer Depleted Cortical Tissue. .................................................................. 41
Figure 11: The Astrocytic Marker GFAP is Overexpressed in Dicer Depleted
Cortices. .......................................................................................................... 42
Figure 12: Dicer Depletion Summary of Results ............................................................. 43
Figure 13: Schematic Representation for Human-Specific MRE Detection .................... 64
Figure 14: Human Gain of Target Candidate Validation of MRE in 3'UTR ................... 65
Figure 15: FOXO1 3’UTR Schematic of MiR-183 MRE ................................................ 66
Figure 16: Validation of Pre-miR-183 Processing and Targeting Capacity..................... 67
Figure 17: Human FOXO1 3’UTR Targeted by MiR-183 ............................................... 68
Figure 18: Human-Specific MiR-183 MRE is Functional on Human FOXO1 3’UTR ... 69
Figure 19: Pre-miR-183 Modulates FOXO1 Transcript Levels in Hsa ONS-76 Cells
but not Mmu C17-2 Cells ............................................................................... 70
viii
Figure 20: Pre-miR-183 Modulates FOXO1 Protein Expression Levels in Hsa
ONS-76 Cells but not Mmu C17-2 Cells ........................................................ 71
Figure 21: TSP of FOXO1 3’UTR d
oes not Change FOXO1 Transcript Levels ..................................................... 72
Figure 22: TSP of FOXO1 3’UTR Regulates Expression Levels at Human-Specific
MRE in Hsa ONS-76 Cells ............................................................................. 73
Figure 23: SiRNA Against FOXO1 Decreases RNA Transcript Levels .......................... 74
Figure 24: SiRNA Against FOXO1 Decreases Protein Expression Levels ..................... 75
Figure 25: SiRNA Against FOXO1 Induces Cell Invasion in ONS-76 Cells and
C17-2 Cells ..................................................................................................... 76
Figure 26: Pre-miR-183 Induces Cell Invasion in Hsa ONS-76 Cells but not Mmu
C17-2 Cells ..................................................................................................... 77
Figure 27: TSP of Human-Specific MiR-183 MRE Impedes Cell Invasion in Hsa
ONS-76 Cells but not Mmu C17-2 Cells ........................................................ 78
Figure 28: SiRNA Against FOXO1 Impedes S-Phase Progression in ONS-76 Cells
and C17-2 Cells............................................................................................... 79
Figure 29: Pre-miR-183 Impedes S-Phase Progression in both Hsa ONS-76 and Mmu
C17-2 Cells ..................................................................................................... 80
Figure 30: TSP of Human-Specific MiR-183 MRE Induces S-Phase Progression
Only in Hsa ONS-76 Cells but not in Mmu C17-2 Cells ............................... 81
ix
LIST OF ABBREVIATIONS
3’UTR
3’ untranslated region
Ago
Argonaute
BrdU
5′-bromo-2′-deoxyuridine
C17-2
Mouse cerebellar stem cells
CLASH
crosslinking, ligating, and sequencing of hybrids
CLIP
crosslinking and immunoprecipitation
C–R
Cajal–Retzius
CP
cortical plate
DCX
Doublecortin
DMEM
Dulbecco’s modified Eagle’s medium
DNA
deoxyribonucleic acid
E7.5
embryonic day 7.5
fd
floxed Dicer
FOXO1
Forkhead Box O1, FKHR
FBS
fetal bovine serum
HEK293
Human Embryonic Kidney 293 Cells
HITS-CLIP
high-throughput sequencing of RNA isolated by CLIP
hsa
Homo sapiens, human
IdU
5′-iodo-2′-deoxyuridine
IHC
immunohistochemistry
ISH
in situ hybridization
miRNA
miR, microRNA
x
miRISC
miRNA loaded into a RISC complex
mmu
Mus musculus, mouse
MRE
miRNA recognition element
mRNA
messenger RNA
MZ
marginal zone
NPC
neural progenitor cell
nCre
Nestin-Cre
ONS-76
human medulloblastoma cell line
P21
postnatal day 21
PAR-CLIP
photoactivatable-ribonucleoside-enhanced CLIP
pan
Pan troglodytes, chimpanzee
PFA
paraformaldehyde
PH3
phosphohistone 3
PI
propidium iodide
pre-miR
artificial precursor miRNA
PT
perfect target
RBPJ
recombining binding protein suppressor of hairless
RISC
RNA-induced silencing complex
RLU
relative luciferase units
RNA
ribonucleic acid
RREB
ras responsive element binding protein 1
RT
room temperature
RT-qPCR
reverse transcription quantitative polymerase chain reaction
xi
siRNA
small (short) interfering RNA
SP1
specific protein 1
SVZ
subventricular zone
TF
transcription factor
TSP
target site protector
VZ
ventricular zone
xii
1
CHAPTER I:
INTRODUCTION
MiRNA Regulation
Gene expression can be regulated at many levels: DNA, RNA and protein.
MicroRNAs (miRNAs) are one class of noncoding RNAs that provide a mechanism for
post-transcriptional gene silencing upon base pairing with target mRNAs to induce
translational repression or transcript degradation. MiRNAs are encoded across the
genomes of vertebrates, invertebrates and plants and notably once a miRNA gene
emerges in a particular lineage, it is rarely lost in the descendant lineage. This conserved
emergence of particular miRNAs creates a strong environment for evolutionary diversity.
In this chapter, I present key background information for my studies on the role of
miRNA regulation in the developing central nervous system and as a rich resource for
human evolutionary divergence.
MiRNA Biogenesis
The majority of primary miRNA (pri-miRNA) transcripts in the miRNA
biogenesis pathway are intergenically or intragenically transcribed by RNA polymerase II
and in some cases RNA polymerase III [10]. Pri-miRNA length can vary from hundreds
to thousands of nucleotides in length and contains at least one hairpin structure. Once
transcribed, the pri-miRNA remains in the nucleus, where the hairpin structure is excised
via a Drosha/DGCR8 complex [11, 12] resulting in ~70 basepairs long precursor
miRNAs (pre-miRNAs). The pre-miRNA is transported to the cytoplasm, via Exportin-5
and processed by a RNaseIII family ribonuclease called Dicer, which cleaves the loop
region of the hairpin, creating a 21-22 base pair mature miRNA:miRNA* duplex [13,
2
14]. The most favorable duplex strand, largely based on 3’ end stability, is loaded into
the effector complex RISC (RNA-induced silencing complex) [15]. The single-stranded
mature miRNA within RISC (miRISC) forms imperfect complementary contacts on
target mRNAs, typically in the 3’ untranslated region (3’UTR). The miRISC binding
contacts, known as miRNA recognition elements (MREs) are complementarity to the
miRNA seed region, basepairs 2-7 at the 5’ end of the miRNA strand. Once bound to
target mRNAs, miRISC has all the necessary components to regulate mRNA expression
(Figure 1).
MiRNA Post-Transcriptional Regulation
MiRNA regulation of gene expression generally occurs by one of three main
mechanisms: i) A miRNA may bind to a target transcript to sterically interfere with
translational initiation, thus prohibiting protein generation. Evidence for this mechanism
has shown that the main protein of the RISC complex, Argonaute (Ago), can either
compete with the eIF4E binding to the mRNA 5’cap structure to inhibit the first step in
the translational initiation complex assembly or recruit the translational repressor eIF6 to
target mRNAs [16-18]. ii) If translation initiation has commenced, a miRNA may bind
to a target mRNA and impede translational progression, ultimately causing ribosomal
drop-off [19, 20]. This inhibition by miRNAs post-initiation was first observed for lin-14
and lin-28 mRNAs, targeted by lin-4 miRNA [21, 22]. iii) MiRNAs may also affect
mRNA stability causing rapid target degradation. This process occurs generally when the
miRNA has perfect complementarity to the target mRNA, while in the presence of deadenylating and de-capping enzymes [23-25]. Interestingly, there are a few studies of
3
select miRNAs functioning as translational activators, generally observed under
conditions of cell stress [26-28].
MRE Prediction
The majority of miRNA regulation occurs in the 3’UTR, but there is growing
evidence of MREs located in coding and 5’UTR regions, although these less common
sites generally have minimal regulatory capacity [29]. Additionally, the same target site
sequence does not always mediate efficient regulation in different UTRs. This
divergence in miRNA regulation can be partially attributed to the variance in
alternatively polyadenylated or spliced 3’UTRs and the local context of the MRE [29].
From a combinatorial prospective, different MREs for different miRNAs within the same
mRNA may act independently of each other, providing an additive effect of simultaneous
repression by several miRNAs [30-32]. Additionally, any one miRNA has the potential
to target hundreds of mRNAs. Many of these miRNA properties parallel transcription
factor activity [33], which will be discussed later in this chapter.
To understand the potential role of miRNA regulation, MRE prediction
algorithms were developed to identify evolutionarily conserved MREs [34, 35].
Predicted MREs are shown to be approximately 3.5 times more conserved than control
sequences [36] and depleted in single nucleotide polymorphisms (SNPs) [37], indicating
evolutionary protection for functionally consequential sites. From the past two decades,
many of the experimentally validated MRE sites were chosen based on conserved seed
region criteria leaving many non-conserved and non-canonical sites under-represented in
miRNA literature. In hopes of determining non-conserved MREs, prediction algorithms
also incorporate targeting biology, with prediction scores considering site location,
4
accessibility, and miRNA:mRNA pairing. For more information on miRNA
computational prediction tools refer to Table 1.
It is important to note that while target site predictability is improved by more
advanced algorithms, miRNA regulation still requires an understanding of both spatial
and temporal co-expression of a miRNA and its predicted target that can be manipulated
by both internal and external cues [38]. A significant precedence must be placed on highthroughput mRNA sequencing of tissue-, development-, and disease-specific gene
expression that can be combined with miRNA profiling to identify candidate miRNA
targets.
MiRNA Regulation in Neural Development
MiRNA control of gene expression has been implicated in developmental
regulation and mature cell maintenance. In the nervous system, gross evaluation of total
miRNA expression profiling revealed strong miRNA enrichment in developing and
mature neuronal tissue and at least 60% of known miRNA species detected in the adult
brain in which many are drastically regulated during embryonic brain development [3941]. Since Dicer is the key enzyme in canonical miRNA processing, several studies have
reported the global effects of miRNAs in CNS development by ablating Dicer and in turn
blocking the biogenesis of all miRNAs in specific regions and at different developing
stages in the CNS using tissue-specific Cre lines. The complete knockout of the Dicer
gene resulted in early embryonic lethality at embryonic day 7.5 (E7.5), which is prior to
neurulation [42]. This suggested that miRNAs are involved in cellular differentiation and
maintenance of cell identity. It is well accepted that noncoding RNAs, in particular
miRNAs, play a critical role in neural development and function, with additional
5
implications in CNS disorders where miRNA expression can be altered, thus affecting
downstream protein targets that may contribute to underlying disease phenotypes [3].
Conditional Dicer Depletion and Mouse Models
Over the past six years conditional knockouts of Dicer have been used extensively
to examine the collective roles of miRNAs in specific tissues and cell types in the
developing mouse CNS by utilizing the Cre-LoxP system. LoxP/Cre systems utilize
homologous recombination to create conditional gene knockouts [43]. Cre is an enzyme
isolated from bacteriophage P1 and functions as a site specific DNA recombinase [44].
Cre specifically recognizes 34 bp LoxP sites, consisting of two inverted repeats separated
by a small spacer [44]. When two LoxP sites are oriented in the same direction, a Cre
enzyme will excise the intervening DNA and leave one LoxP site intact. For the
purposes of conditional Dicer depletion models, engineered LoxP sites flank exon 23,
which contains the ribonuclease RNaseIII domain. Thus, when a mouse expressing Cre
recombinase under a tissue-specific promoter is crossed with a LoxP-Dicer model, the
Dicer gene is floxed leading to Dicer depletion in specific cells of interest.
One of the first functional studies of Dicer ablation in the brain was completed
using a FoxG1 promoter to drive Cre expression throughout the telencephalon beginning
at E8. Makeyev et al. showed reduced forebrain size by E13.5 due to decreased and
mislocalized neuronal differentiation markers, along with increased cellular apoptosis
[45]. A follow-up study in this same Dicer knockout model focused on the role of
miRNA regulation in olfactory neurogenesis [46]. In that work, FoxG1-Cre Dicer
depletion led to reduced olfactory progenitor cell markers, as well as a reduction in the
neuroepithelium by E13.5 [46]. Forebrain Dicer depletion beginning at ~E9.5 was also
6
tested by crossing LoxP Dicer mice to mice driving Cre under either the Emx1 or Nestin
promoters. The Emx1-Cre Dicer model specifically ablates Dicer in neuroepithelial cells
in the dorsal telencephalon by E13.5, differing from the less restrictive Nestin-Cre Dicer
model of Dicer ablation in the entire CNS by E15.5. Studies using both the Nestin-Cre
and Emx1-Cre Dicer models concluded that miRNAs were required for neuronal
maturation, but these models diverged when assessing differentiation. In the Emx1-Cre
Dicer model, the differentiation of neural progenitors and ectopic early-born neurons is
detected around E13.5, whereas Nestin-Cre Dicer models exhibited delayed neurogenesis
later at ~E18.5 [47, 48].
Another important model of Dicer depletion in the developing forebrain utilized
the calmodulin kinase II (CaMK11-alpha) promoter to drive Cre expression. In this
setting, Dicer depletion occurs in the cortex and hippocampus around E15.5, with
resulting gross brain malformations such as microcephaly, enlarged ventricles, and
reduced white matter tracks evident at postnatal day 21 (P21).
Together, these studies
illustrate the broad role of Dicer and miRNAs in mammalian CNS development, with
functional implications for miRNA controlled cellular functions that when misregulated
may contribute to neurological disorders, such as lissencephaly and microcephaly [3].
For a complete list of functional impairment after conditional Dicer elimination of
neuronal tissue refer to Table 2.
Alternative Functions of Dicer
Conditional ablation of Dicer in specific regions in the CNS and in distinct cell
lineages has demonstrated the importance of the miRNA-mediated pathway in CNS
development and in the differentiation of different cell types. However, because Dicer is
7
also involved in maintaining heterochromatin assembly, likely by the short interfering
RNA (siRNA) pathway, the CNS defects in Dicer knockout mice should be carefully
interpreted [49, 50]. In the future, examining how individual miRNAs and/or miRNA
families function will help reveal their precise roles in CNS development.
Benefits of MiRNAs for Therapeutic Interventions
Importantly, misregulation of miRNAs has been implicated in human
neurological diseases [3], however many of these findings still require comprehensive
investigation to better understand their biological contributions to the disease state.
Nonetheless, miRNAs are now being proposed as potential biomarkers, either for the
effects of therapy or as a disease indicator [51, 52]. Additionally, from a more direct
therapeutic standpoint, miRNAs can be rapidly synthesized and easily delivered, making
them a promising option for novel treatment tools. But to effectively utilize miRNAs as
a treatment tool we also need an extensive assessment of function, particularly how
miRNAs interface with other master regulators, such as transcription factors to control
cell function or fate.
Proposed Mechanisms for MiRNA Regulatory Diversity
Evolutionary research is aimed around delineating the alterations, expansions, and
contractions of cellular diversity and function that leads to the emergent success of
biological systems. On a small scale, research can be strung together to understand
specific evolutionary links between individual molecular mechanisms, but the key to
unlocking the bigger picture is to first understand the broad mechanisms by which such
diversity is generated. With the advancements in sequencing technology, it is now
known that alterations to the protein-coding genetic repertoire inadequately account for
8
the levels of evolutionary change between species. Research has pointed toward the
evolution of gene expression regulators and their targets as one of the major
distinguishing factor between us and our primate cousins [53].
A recent review by Li et al. highlight four mechanisms by which genetic diversity
can affect miRNA regulatory pathways, ranging from biogenesis to target recognition
[54]. They are : i) MiRNA expression may be altered by SNPs on the miRNA promoter
region. ii) Processing of pri-miRNAs and pre-miRNA by Drosha and Dicer, respectively,
may be affected by SNPs located on or near the enzyme cleavage sites. iii) SNPs in the
miRNA seed region (nucleotides 2-8 from 5’ end) may result in complete re-targeting of
miRNA regulation to novel MREs. iv) MREs and surrounding sequence are susceptible
to SNPs that could alter localized miRNA targeting. In most cases, the SNP will be
selected against, but some MRE mutations can be neutral or even advantageous and be
fixed by drift or positive selection .
Interestingly, human-specific changes in brain development are linked with
changes in miRNA expression [55]. Phylogenic analyses of miRNA generation indicate
the potential role novel miRNAs may play in species-specific traits, which has most
extensively been studied in primate lineages [56, 57].
For example, Somel et al.
analyzed human-specific evolutionary expression changes in cerebellum and prefrontal
cortex of human, chimpanzee, and rhesus macaque brains and found miRNAs that have
human-specific expression are enriched for neuronal function, suggesting an importance
of miRNA evolutionary divergence on speciation [55]. Unfortunately, because
evolutionary conservation has been used as one of the primary criteria in MRE
prediction, the phenotypic consequences of non-conserved MREs are significantly
9
understudied [34, 37]. Although there is strong negative selection against changes in
miRNA target sites, there is evidence for SNPs in many human miRNA targets, some of
which may have causal roles in human disease, though further studies are required to
fully test this [37, 58].
Gene Regulatory Networks
Transcription Factor Regulation
Transcription factors (TFs) are proteins that regulate cellular functions by binding
to specific consensus sequences on DNA and augmenting gene expression. Typically,
TFs will recognize short consensus sequences approximately 5-15 base pairs long,
although many mismatches are allowed, leading to different binding affinities to targets.
TFs may function by repressing or enhancing promoter activity. TF binding can be
regulated by DNA accessibility, which is regulated by nucleosome remodeling. Thus,
open chromatin regions generally have a higher probability of TF binding than closed.
Similar to MREs, TF binding sites are highly abundant throughout the genome, allowing
for one TF to function as a central hub in a functional regulatory network.
TF:MiRNA Circuitry
TFs and miRNAs are among the largest families of trans-acting gene regulatory
molecules. Among the two families, there are many similarities in action, such as
combinatorial and cooperative activity for gene regulation, necessity for accessible
binding sites, and their ability to function in network motifs to regulate gene expression
[33]. TFs and miRNAs have been shown to both co-regulate the expression of genes as
well as the expression of each other through feedback loops [59-62]. Recent reviews
have outlined the importance of feedback loops classified as either single-negative or
10
double-negative, and their roles in regulating networks [59, 63]. These feedback loops
can function as buffers or repressive switches to TF expression, dependent on the TF’s
repressive or enhancing nature on miRNA expression. Referring back to the inconsistent
MRE validation rate, our understanding of the current co-regulatory interactions of
miRNAs and TFs are diminished by the incomplete knowledge of MRE targeting at a
spatial and temporal level.
TF:MiRNA Circuitry Evolutionary Impact
A typical miRNA-regulated interaction with its target MRE generally produces
only subtle changes in protein levels. In fact, many miRNAs may be ablated without
obvious phenotypic consequences. Regardless, a miRNA leading to small changes in
protein levels can confer large changes in cellular function, especially when targeting
master regulators such as TFs [62]. Interestingly, studies indicate an excess of humanspecific expression divergence for TFs, especially in the brain [64], suggesting that
changes in TF expression might underlie human-specific transcriptome divergence. To
date the implications of miRNAs targeting TFs, from an evolutionary prospective, are
largely understudied.
Summary
In the work described here, I address the role of miRNA regulation in both in the
developing central nervous system and as a rich resource for the divergence of gene
regulation in human brain vs. those of lower mammals. In Chapter II, I extend the Dicer
depletion literature by disrupting in vivo miRNA production in mouse neural progenitor
cells and ascertaining the effects of that disruption on proliferation, apoptosis,
differentiation, and migration in the developing cerebral cortex. In Chapter III, I
11
determine if human-specific single nucleotide change(s) in MREs of TF 3’ UTR provides
differential feedback regulation in human vs. chimpanzee and mouse. Finally, in Chapter
IV, I propose future studies based on my work in Chapters II and III.
Published Work
With the exception of Figures 2 and 12, Chapter II is adapted from McLoughlin et
al. published in Neuroscience [65], where HSM was first and an equally-contributing
primary author. Chapter III represents work submitted for publication in Human
Molecular Genetics and is pending review. Work contributed by authors other than HSM
is indicated in the methods or figure legends.
12
Figure 1: MiRNA Biogenesis
Primary miRNA (pri-miRNA) transcripts are intergenically or intragenically
transcribed by RNA polymerase II and III [10]. The pri-miRNA hairpin structure
is excised via a Drosha/DGCR8 complex [11, 12] resulting in ~70 basepairs long
precursor miRNAs (pre-miRNAs). The pre-miRNA is transported to the
cytoplasm, via Exportin-5 and processed by a RNaseIII family ribonuclease called
Dicer complexed with TRBP, which cleaves the loop region of the hairpin,
creating a 21-22 base pair miR duplex [13, 14]. The most favorable duplex strand
is loaded into the effector complex RISC (RNA-induced silencing complex) [15].
The single-stranded mature miRNA within RISC (miRISC) forms imperfect
complementary contacts on target mRNAs, typically in the 3’ untranslated region
(3’UTR). Once bound to target mRNAs, miRISC may regulate mRNA
expression by translational inhibition or deadenylation.
13
Table 1: List of MiRNA Target Prediction Tools. (Adapted from [66]).
Paira
Tool
Siteb
Consvc
Accessd Multie Exprf
Target Scan
PicTar
miRanda
MicroCosm Targets
RNAhybrid
PITA
STarMiR
Rajewsky & Socci
Robins
mirWIP
MicroInspector
MicroTar
MirTarget2
miTarget
TargetMiner
EIMMo
NbmiRTar
TargetBoost
RNA22
TargetRank
EMBL
MovingTarget
DIANA-microT
HOCTAR
Stanhope
GenMiR++
HuMiTar
MirTif
Yan et al.
Xie et al.
a
[30, 36, 67]
[37, 68-70]
[71, 72]
[73-75]
[76, 77]
[78]
[79]
[80]
[81]
[82]
[83]
[84]
[85]
[86]
[87]
[88]
[89]
[90]
[32]
[91]
[92-94]
[95]
[96]
[97]
[98]
[99]
[100]
[101]
[102]
[103]
miRNA:mRNA pairing.
considered.
b
c
Site location.
Conservation.
considered.
: stringent seeds,
: moderately stringent seeds, Blank: seed sites not
: target positions considered, Blank: target positions not considered.
: with/without conservation filter,
d
: with conservation filter, Blank: conservation not
Site accessibility.
: site accessibility with minimum free energy considered,
considered, Blank: site accessibility not considered.
e
Multiple sites.
: multiple sites considered,
co-operability not considered.
f
Refs
Expression profile.
: A:U rich flanking
: the number of putative sites considered, Blank: multiple
: expression profiles used, Blank: expression profiles not used.
14
Table 2: List of Functional Impairment After Conditional Dicer Elimination.
(Adapted from [104]).
Transgenic Affected Cell
Phenotypes
Lines
Types
Pcp2-CrePurkinje cell degeneration and death (13
Purkinje cells
Dicer1
weeks) leading to ataxia
Post-mitotic
DAT-CreDAT+/TH+ cell loss, reduced open-field
Dopaminergic
Dicer1
locomotion
neurons
Post-mitotic
Front and hind limb clasping, gait
DR-1-CreDopamine
abnormalities, reduced brain size, and smaller
Dicer1
receptor-1
striatal medium spiny neurons, no neuron loss
neurons
Post-mitotic
Sclerosis of spinal cord ventral horns,
VAChTspinal motor
abnormal end plate architecture, muscle
Cre-Dicer1
neurons
denervation and myofiber atrophy
Cortical radial thickness reduction by E13.5,
neural stem and
Emx1-Creincreased apoptosis by E12.5, decreased
progenitor cells
Dicer1
proliferation by E14.5, impaired neuronal
in cortex
differentiation and layer formation
Reduced proliferating cells and altered cell
neural stem and
Nestin-Crecycle kinetics by E15.5, increased apoptosis
progenitor cells
Dicer1
by E15.5, aberrant cortical layering,
in brain
precocious astrocyte differentiation by E15.5
Microcephaly, reduced dendritic arborization
neurons of
CaMKIIαand increased spiny length, increases
cortex and
Cre-Dicer1
apoptosis by P0, no neuronal migration
hippocampus
defects
Tamoxifen-inducible CreERT2 at 8-10 weeks
with enhanced memory strength at 12 weeks
CamKadult forebrain
post-treatment, neuronal cell death 14 weeks
CreERT2neurons
post-treatment, at 12 weeks post-treatment
Dicer1
cells showed elongated filopodia-like shaped
dendritic spines
Neural crest migration normal but impaired
Wnt1-Creneural crest
post-migratory survival upon neural crest
Dicer1
differentiation
Expanded basal progenitor population and
Foxg1-Cre- telencephalic
mis-localized post-mitotic neurons; increased
Dicer1
progenitors
apoptosis by E11.5
Heterozygous shows decreased miRNA
cortical biogenesis by P25, reduced basal
Dgcr8 (-/-)
All tissues
dendrite length and branching, decreased
excitatory synaptic transmission and cognitive
task deficits
Dicer1 (-/-) All tissues
Lack primitive streak markers, death by E7.5
Refs.
[105]
[106]
[107]
[108]
[47,
48,
109]
[48,
65]
[110,
111]
[112]
[113]
[45,
46,
114]
[115117]
[42]
15
CHAPTER II:
DICER IS REQUIRED FOR PROLIFERATION, VIABILITY,
MIGRATION AND DIFFERENTIATION IN
CORTICONEUROGENESIS
Abstract
In mice, microRNAs (miRNAs) are required for embryonic viability, and
previous reports implicate miRNA participation in brain cortical neurogenesis. Here, we
provide a more comprehensive analysis of miRNA involvement in cortical brain
development. To accomplish this we used mice in which Dicer, the RNase III enzyme
necessary for canonical miRNA biogenesis, is depleted from Nestin expressing
progenitors and progeny cells. We systematically assessed how Dicer depletion impacts
proliferation, cell death, migration and differentiation in the developing brain. Using
markers for proliferation and in vivo labeling with thymidine analogs, we found reduced
numbers of proliferating cells, and altered cell cycle kinetics from embryonic day 15.5
(E15.5). Progenitor cells were distributed aberrantly throughout the cortex rather than
restricted to the ventricular and subventricular zones. Activated Caspase3 was elevated,
reflecting increased cortical cell death as early as E15.5. Cajal-Retzius positive cells
were more numerous at E15.5 and were dysmorphic relative to control cortices.
Consistent with this, Reelin levels were enhanced. Doublecortin and Rnd2 were also
increased and showed altered distribution, supporting a strong regulatory role for
miRNAs in both early and late neuronal migration. In addition, GFAP staining at E15.5
was more intense and disorganized throughout the cortex with Dicer depletion. These
results significantly extend earlier works, and emphasize the impact of miRNAs on
16
neural progenitor cell proliferation, apoptosis, migration, and differentiation in the
developing mammalian brain.
Introduction
Cortical neurogenesis is a highly regulated process broadly consisting of
proliferation, selective cell death, migration, and differentiation. Disruptions to these
controlled processes cause neurodevelopmental disorders. For instance, a decrease in
proliferation or an increase in cell death at early stages of corticoneurogenesis can cause a
microcephalic disorder [2, 118], whereas disrupted differentiation or migration during
cortical development can induce disorganized cortical laminae, a phenotype of
lissencephalic patients [119, 120]. Genetic dissection of loci important in the control of
cortical neurogenesis has improved our understanding of neurodevelopment. These loci
include not only protein coding genes [1, 2], but also noncoding RNAs [3-5].
MiRNAs are one class of noncoding RNAs, and they provide a mechanism for
post-transcriptional gene silencing upon base pairing with target mRNAs to induce
translational repression, often through de-adenylation of mRNAs [29, 121, 122]. MiRNA
control of gene expression has been implicated in developmental regulation and mature
cell maintenance [3, 5-9]. In the nervous system, gross evaluation of total miRNA
expression has been profiled, revealing strong miRNA enrichment in developing and
mature neuronal tissue [39-41]. And in CNS disorders, their expression can be impaired,
which may contribute to underlying disease phenotypes [105-107, 111, 123-127].
Many
reports have dissected relationships between miRNAs and disease phenotypes, and
deficiencies in miRNAs that regulate embryonic neurogenesis might contribute to CNS
defects and other neuropathies. We sought herein to define the impact of miRNA loss in
17
the development of the CNS, by assessing multiple aspects of cortical neurogenesis upon
blockade of canonical miRNA generation. An important goal of this survey was to
define primary disturbances, for future delineation of specific miRNAs and their potential
disease-related roles.
Dicer is a RNase III family ribonuclease that is important in miRNA maturation,
and is required for embryonic development; Dicer depleted embryos lack primitive streak
markers and arrest at E7.5 [42]. To analyze the gross impact of miRNAs in the
developing CNS, conditional Dicer depleted neural tissue has been studied in several
settings using mouse lines expressing various Cre drivers crossed to mice harboring lox-P
flanked Dicer loci. The FoxG1 promoter, active in telencephalic progenitor cells from
around E8, was used to drive Cre expression, and resulted in disorganized cortical
laminae, pronounced microcephaly and lethality in utero [45, 124]. Two different
groups used the Emx-1 promoter to drive expression of Cre in the cortex starting at E9.5
and concluded that miRNAs were required for neuronal maturation, but differed in their
interpretation of how Dicer depletion affects progenitor pools [47, 48].
Here, we performed extensive additional studies in mice with Dicer depletion
using the Nestin-Cre driver. Using BrdU/IdU double labeling, we found reduced
numbers of proliferating cells and altered cell cycle kinetics. We also identified early cell
death in all zones of the developing cerebral cortex. We found dysregulation of
important markers of differentiation and migration. Finally, we show an increased
expression level of a mature astrocyte marker at E15.5, well before normal induction of
large scale gliogenesis. Our data considerably supplement earlier surveys and clarify the
18
extent of impairments induced by depletion of Dicer in the developing mammalian
forebrain.
Results
Female mice with loxP sites flanking the essential RNase III domain of Dicer
(fd/fd mice) were bred to male mice harboring Cre recombinase driven by the Nestin
promoter (nCre mice) (Figure 2A). Embryos without Nestin-Cre expression (fd/fd;+/+)
were used as controls for fd/fd:nCre/+ mice in all studies. The Nestin promoter is active
in embryonic neural progenitor cells (NPCs) as early as E9.5 in mouse cerebral cortex
[128, 129]. Like Kawase-Koga and colleagues, we noted reduced numbers of fd/fd:nCre
embryos; only 13.5% of all E15.5 embryos and 9% of all E16.5 embryos were Dicer
depleted (Figure 2B). No Dicer depleted mice were recovered at birth.
We focused our study between E15.5 and E16.5 to capture the effects of Dicer
depletion at the height of neuronal proliferation and the onset of gliogenesis [130]. At
this time there was RNase III excision of Dicer, as assessed by PCR of genomic DNA
(Data not shown). This is congruent with others work showing Dicer expression by
western blot [48]. Additionally, a recent study calculated the average half-life of
miRNAs to be ~119hrs [131]. Thus to allow for Cre expression, Dicer excision, and
miRNA depletion, we choose E15.5 as the earliest time point of interest. Notably, while
a small number of Dicer depleted embryos exhibited massive cell loss and extremely
small cortices at E15.5, similar to that reported by De Pietri Tonelli et al, 2008, we found
these embryos to be outliers in our colony. Therefore, in this study we analyzed sections
from more representative embryos.
19
Gross Cortical Abnormalities of Dicer Depleted Mice
To evaluate the effects of Dicer ablation on the developing CNS, we prepared
E16.5 whole embryo sections in the sagittal plane and stained for Nissl to examine brain
size. Specific analysis of the cerebral cortex showed microcephalic characteristics,
including gross enlargement of the lateral ventricles and marked cortical thinning in the
Dicer depleted embryos compared to control embryos (data not shown). These findings
are analogous to previously published results where embryos were analyzed at a later
time point, E18.5 [48], wherein they ascribed the cortical reduction to abnormal
developmental of the late-born neurons. However, effects on late-born neurons cannot
explain the decrease in cortical thickness and ventricular enlargement we observed in
E15.5 embryos. We thus investigated other consequences of Dicer depletion.
Simply stated, developmental malformations of the cerebral cortex can be
categorized into defects in NPC proliferation, cell death, migration and/or differentiation
[2]. To assess which of these defects in early corticoneurogenesis are disrupted in the
Dicer depleted cortex, we first surveyed Nestin, a marker present in all NPCs, to
determine if proliferating cell populations differed. We quantified transcript levels via
RT-qPCR using cortical RNA harvested from E15.5 embryos and found Nestin mRNA
increased by ~8-fold in Dicer depleted cortical tissue relative to control brains (Figure
3A). In normal mice embryos, Nestin expressing cells are abundant within the
ventricular zone (VZ) and sparse throughout the subventricular zone (SVZ). However, in
Dicer depleted cortical tissue, Nestin expression was observed aberrantly distributed
throughout the cortical parenchyma at E15.5 (Figure 3B). The novel finding of an
altered pattern of Nestin expressing cells prompted us to examine mature neurons using
20
MAP2. In Dicer-depleted E15.5 cortical sections, we detected no significant decrease in
MAP2 transcript levels (Figure 3A), but the cortical layering was disorganized relative to
control tissues (Figure 3B). These results are consistent with the poor organization
reported throughout the normally non-proliferative region of the developing cortex in the
Emx1-Cre Dicer knockout mice [47]. Kawase-Koga and colleagues examined MAP2
and NeuN at E18.5 and P0 in the Nestin-Cre Dicer depleted mice, and detected a
reduction in mature neuron population [48]. Our data of MAP2 at E15.5 suggests that
dysregulation precedes mature neuron decline.
Dicer Inactivation Reduces Cell Division
Since reduced cortical thickness is commonly caused by decreased NPC
proliferation and/or increased cell death, we assessed the proliferative regions of the
developing cerebral cortex. Proliferating NPC density was ascertained by
immunostaining for the M-phase marker, PH3 at E15.5 and E16.5. Dicer depleted
cortices showed a significant decrease in PH3 positive cells in the VZ and SVZ by
greater than 20% at both E15.5 and E16.5 (Figure 4A and B). Our results appear to
contrast the data from Kawase-Koga and colleagues, who reported no difference in PH3
positive cells in E15.5 Dicer depleted cerebral cortex, although no quantification was
reported in that work [48]. To substantiate Dicer depletion effects on proliferation, and
gain information on cell cycle kinetics, we used the thymidine analogues BrdU and IdU
to quantify cells in S or G2/M phase, respectively [132]. IdU was intraperitoneally
injected into pregnant dams four hours before sacrifice, and BrdU 30 minutes before
sacrifice [133]. Sections were immunostained for BrdU and IdU; BrdU positive cells are
in S phase, and IdU-only positivity represent cells that were in S phase at the time of IdU
21
injection but subsequently progressed into G2/M. In agreement with our PH3
immunostaining, we found ~40% fewer immunopositive cells (cells that had incorporated
either BrdU and/or IdU) in Dicer depleted cortices relative to controls at E15.5 (Figure
5A and B), indicating significant loss of proliferating cells. Amongst the
immunopositive cells, Dicer depletion shifted the proportions to increase the S:G2/M
phase ratios, indicating that Dicer depleted cells take longer to progress through S-phase
(Figure 5C). According to calculations defined by Burns and Kuan, the interval time at
which the ratio of IdU-only cells to total labeled cells is 0.5 is considered the length of Sphase. Thus, our results indicate that control cortical cell S-phase length approximates 4
hrs for control cortex, while in Dicer depleted cortical progenitors, S-phase is greater
than 4 hrs [134] (Figure 5C). Together these data indicate that in Dicer depleted
proliferating zones, the progenitor pool is reduced and there is delayed cell cycle kinetics.
Dicer Depletion Induces Increased Apoptosis in
Late Corticogenesis
Increased cell death could also contribute significantly to the decrease in cortical
thickness found in E15.5 Dicer depleted mice. Earlier work reported no differences in
TUNEL staining between the cerebral cortex of Nestin-Cre Dicer depleted mice and
control tissue, at least up to E18.5 [48]. However, we observe a ~9- and ~4-fold increase
in cells positive for the apoptotic marker activated Caspase 3 at E15.5 and E16.5,
respectively (Figure 6A and B). Apoptotic cells were dispersed throughout the cortical
parenchyma. In support of our finding, De Pietri Tonelli and colleagues also showed
increased apoptotic cells throughout the cortex when examining cortices from Emx1-Cre
Dicer depleted mice from E12.5 to E14.5 [47].
22
Dicer Deficient Mice Have Dysregulated Neuronal
Migration and Differentiation
In E15.5 Dicer depleted embryonic cortices, we found ectopic Nestin expressing
cells in the upper layers (Figure 3B). Also, mature neurons within the cortical structure
at E15.5 were disorganized (Figure 3B). We therefore evaluated radial migration. The
first wave of radial migration, beginning around E11.5, is largely composed of CajalRetzius (C-R) neurons relocating from the VZ to the marginal zone, the uppermost area
of the developing cortex. The effects of Dicer depletion on C-R neuronal migration and
differentiation at E15.5 was assessed using the calcium binding protein, Calretinin as a
specific marker of C-R neurons. We found statistically significant increases in
Calretinin positive cells in Dicer depleted cortex relative to controls (Figure 7A and B).
Moreover, a substantial proportion of the C-R neurons exhibited a significant defect in
migration, being dispersed within the cortical plate rather than confined to the marginal
zone at E15.5 (Figure 7B). Interestingly, the C-R positive cells with migration defects
were dysmorphic relative to cells that migrated properly to the marginal zone (Figure
7A).
C-R neurons secrete Reelin, which is important for neuronal migration [135].
Contrary to a recently published study, which found no change in Reelin levels within
Nestin-Cre Dicer depleted cortices using histological assays at E15.5 and E18.5 [136],
we show a 3-fold increase in Reelin mRNA levels in Dicer depleted cortex relative to
control at E15.5 (Figure 8A). Reelin immunohistochemistry (IHC) corroborated this
result; expression throughout the cortex was enhanced (Figure 8B).
23
We next assessed migrating immature neurons. We found that DCX mRNA was
~7-fold higher in Dicer depleted tissue relative to controls at E15.5 (Figure 9A), and
DCX staining was regionally restricted to a significant degree (Figure 9B and D). DCX
signal intensity analysis also revealed a ~3-fold increase in E16.5 cortices relative to
controls (Figure 9C). Rnd2, a maturation marker, was evaluated by in situ hybridization
(ISH) (Figure 10B) and quantitation of mRNA levels (Figure 10A). We found in both
analyses the levels of Rnd2 mRNA to be increased in Dicer depleted brains relative to
control. Additionally, Rnd2 mRNA was aberrantly localized throughout the cortical
parenchyma in Dicer depleted embryos relative to control embryos [137]. The
overproduction of both DCX and Rnd2 in the Dicer depleted cerebral cortex may
contribute to the premature maturation of neurons in inappropriate locations, which in
turn causes the overall cortical lamina disorganization.
To test if Dicer depletion induces precocious or enhanced astrocyte
differentiation, we assessed GFAP levels in cortical sections. We found ~4-fold elevated
GFAP mRNA levels in Dicer depleted cortex relative to control (Figure 11A). IHC for
GFAP confirmed increased expression, with GFAP-positive cells distributed throughout
Dicer depleted cortical parenchyma (Figure 11B).
Discussion
We validate several key aspects of prior published reports in which Dicer was
depleted in the telencephalon of developing mice NPCs. More importantly, we extend
these results significantly by examining the effect of Dicer depletion on proliferating
progenitor cells, cell cycle kinetics, and cell death. In addition, we provide evidence for a
strong regulatory role of miRNAs in both early and late neuronal migration and
24
differentiation that may provide candidates for future exploration of miRNA regulation in
neuronal development. Finally, we implicate a role for miRNA regulation of astrocyte
differentiation during cortical development (Figure 12).
Dicer Depletion Impacts Proliferating Cells and
Induces Cell Death
We found significant decreases in proliferating cells in vivo and delayed cell cycle
kinetics. Previous work using PH3 staining did not detect significant differences in
dividing cells until E18.5 in this model [48]. However, our quantitative data demonstrates
reduced PH3 positive cells in the VZ and SVZ at both E15.5 and E16.5. Our findings are
the first to report cell cycle kinetic defects within the cerebral cortex of Dicer depleted
mice. Specifically, we showed an increase in S-phase length in Dicer depleted
proliferating cells compared to the 4 hrs S-phase length in control proliferating cells.
These results are congruent with reports indicating the importance of specific miRNAs in
proliferating cell regulation [138, 139]. The most well described miRNA associated with
neural cell proliferation is miR-9 [140, 141], which we found reduced in Dicer depleted
NPCs (data not shown).
Specific miRNAs have been identified as cell cycle regulators in many model
systems including those studied in cancer [142-148], and several have been specifically
implicated in regulating cell cycle kinetics within normal cortical neurogenesis [149151]. Our thymidine analog data provides solid evidence that miRNAs are required for
appropriate cell cycle kinetics within the developing cerebral cortex. Our BrdU/IdU data
analysis and PH3 data also suggest that the increase in Nestin positive cells is not due to
increased cell cycle kinetics or increased progenitor pool populations. Instead, cells
25
retaining Nestin expression are likely unable to progress past the progenitor state, similar
to the effects of miR-9 loss described by Delaloy and colleagues [140].
We also found increased apoptotic cell death beginning as early as E15.5
throughout the cortex, which may explain why the abundant immature cells do not result
in an increased mature population over time. Analysis of the Emx1-Cre Dicer depleted
model also revealed increased cell death, beginning largely in the VZ, by E12.5 [47],
however TUNEL analysis of the Nestin-Cre Dicer depleted cortex by others did not
reveal differences until at least E18.5 [48]. One possible explanation for the discrepancy
between our work and the earlier Nestin-Cre report may result from the better retention of
activated Caspase 3 within fixed tissue than the antigens for the TUNEL assay, thus
providing a more sensitive test for cell death [152-154].
Effect of MiRNA Depletion in Migration and
Differentiation in Developing Cortex
Upon evaluation of the first wave of migration, we found significant increases in
C-R neurons within the Dicer depleted cortex. A recent report using the FoxG1 promoter
to drive Cre beginning at ~E8 also found increased C-R neurons but no elevation of the
secretory molecule of C-R neurons, Reelin, upon Dicer depletion at E11.5 [114]. Using
the Nestin-Cre model with Dicer excision beginning ~E9, we also showed a significant
increase in C-R neurons, but with a significant increase in Reelin at E15.5. Likely, the
discrepancy between our study and the Nowakowski et al., report is due to activation of
Cre expression and the timing in which analysis was completed [114]. It is possible that
the overproduction of Reelin is a consequence of more C-R neurons that is not
discernible until after E11.5. Whether this in vivo increase in Reelin levels is due to
26
increased proliferation of C-R neurons and/or if Reelin levels are directly regulated by
miRNAs is an avenue for future exploration. Interestingly, we also report an abnormal
morphology of the migrationally delayed C-R neurons in the Dicer depleted cortex. Our
finding that some C-R neurons were well-formed may reflect the fact that some miRNAs
persisted for several days beyond the onset of Dicer expression (expected at ~E9) and CR differentiation around E11. This is consistent with the finding that some miRNAs
persist weeks after Dicer depletion in other models [48, 131]. One explanation of the
dysmorphic C-R neurons may be due specifically to the greater overall reduction of miR9 in the migrationally stunted C-R neurons. A previous report established that miR-9
modulated C-R cell differentiation by suppressing FoxG1 expression [155].
The importance of miRNAs in migration and differentiation is implicated
primarily in tumor invasion, and is less well described with regard to neuronal
differentiation/migration in the developing cortex. Of particular interest are the potential
for miRNAs in cortical organization that, when disrupted or ablated, may predispose a
brain to aberrant wiring as found in disorders such as epilepsy and schizophrenia [1, 156].
Specifically, we showed i) increased Reelin expression, possibly due to increased C-R
neuron numbers, ii) increased DCX mRNA with a reduction in the normally constrained
layers of DCX positive cells, and iii) increased numbers of Rnd2 positive cells and Rnd2
mRNA levels. These findings indicate that miRNA-mediated regulation is likely
required at multiple stages of neuronal differentiation and migration. Specifically, Rnd2
is vital for neurite branching and retraction, important in the transition from multipolar to
bipolar neuronal orientation, and is directly regulated by Neurogenin2 in the developing
cortex [137, 157]. Whether miRNA repression of Rnd2 is direct or indirect via an
27
upstream regulator such as Neurogenin2 is yet to be defined. In neuroblastoma cells,
miR-128 upregulation inhibits Reelin and DCX expression and reduces neuroblastoma
cell motility and invasiveness [158]. Interestingly, one recently published study showed
miR-134 directly targets DCX in vivo, repressing differentiation and maintaining the
proliferation state of neural progenitors [139].
Dicer Depletion Leads to a Precocious Induction
of Astrocyte Differentiation
At the end of neurogenesis, Nestin positive radial glia differentiate into GFAP
positive mature astrocytes [159]. The onset of this process normally occurs at ~E16 in
the developing cerebral cortex, but in our Dicer depleted cortices we find an advanced
increase in both GFAP mRNA levels and protein expression throughout the cortical
parenchyma relative to control brains at E15.5. Although previous Dicer depletion
models investigated the role of miRNA on gliogenesis in the developing spinal cord
[160] and interneurons in the telencephalon [48], we are the first to identify the gross
effect of Dicer depletion on astrocyte differentiation with the developing cerebral cortex.
Our finding suggests an important regulatory role for miRNAs in the binary switch from
neurogenesis to gliogenesis within the developing cerebral cortex. An interesting
candidate for this transitional regulation may be miR-125b, which is reported to play a
direct role in the development of glioma stem cells [161, 162].
In summary, we significantly extend the growing body of evidence indicating a
strong regulatory role of miRNAs in proliferation and cell cycle kinetics, as well as in
neuronal and astrocyte migration and differentiation in the developing mammalian brain.
It will be interesting to test in future studies the extent to which miRNAs modulate the
28
expression of RNA-binding proteins important in neural development [163], transcription
factors or repressors [9], or splicing factors [45]. Dissecting the complex effects of
reducing miRNAs that modulate master regulators vs. the direct impact on proteins with
more specialized activities will provide a wealth of information about their overall
importance in the developing brain.
Materials and Methods
Animal Care and Use
Floxed Dicer (fd) mice were kindly provided by Michael McManus at UCSF and
re-derived at the University of Iowa Animal Care Facility. Animals were bred to
homozygosity, and genotyped using published protocols [164]. Dicer excision was
validated by PCR amplification of DNA harvested from cortices using methods described
earlier [164]. Nestin-Cre (nCre) mice were purchased from Jackson Labs (Strain name
B6.Cg-Tg(Nes-Cre)1Kln/J; Stock number 003771) and genotyped using the following
primers: forward, AGCGATCGCTGCCAGGAT; reverse,
ACCAGCGTTTTCGTTCTGCC. Animals were housed and handled according to
protocols approved by the University of Iowa Institutional Animal Use and Care
Committee.
Embryo Collection
For timed matings, male (fd/+;nCre/+) and female (fd/fd; +/+) mice were cohoused overnight. On the day of harvest, pregnant dams were over anaesthetized with
inhaled isoflurane and euthanized. Embryos were harvested and anesthetized for five
minutes in weigh boats on wet ice. Appendages were removed for genotyping. For
histology sections, decapitated embryo heads were stored in 4% paraformaldehyde (PFA)
29
solution for two or 24 hrs for in situ hybridization (ISH) or immunohistochemistry (IHC)
analysis respectively. IHC tissue was incubated in 30% sucrose/ 0.05% sodium azide at 4
˚C for 48 hrs. Tissues were embedded in OCT matrix, sectioned using a micron cryostat
at 10 m thickness onto Superfrost plus slides (Sigma). Tissues were stored at -80 ˚C
until used.
Immunohistochemistry
Sections were post fixed in 4% PFA for 15 minutes and for antigen retrieval,
immersed in sodium citrate buffer pH 6.0 in microwave at 95 ˚C for 3 x 5 min. Sections
were blocked for one hr in 10% serum, 0.03% Triton-100 in 1 x PBS at room
temperature, then incubated in primary antibody in 2% serum, 0.03% Triton-100 in 1 x
PBS overnight at 4 ˚C. Primary antibodies used were Nestin (mouse anti-Rat401,
Developmental Studies Hybridoma Bank, 1:5), MAP2 (mouse anti-MAP2, Sigma,
1:200), PH3 (rabbit anti-phosphohistone 3 (ser10), Upstate division of Millipore, 1:200),
activated Caspase3 (rabbit anti-cleaved Caspase3 (Asp75), Cell Signaling Technologies,
1:100), DCX (goat anti-Doublecortin (N-19), Santa Cruz, 1:200), Reelin (mouse antiReelin, Millipore, 1:500), Calretinin (rabbit anti-Calretinin, Swant, 1:200), Cre (mouse
anti-Cre, Sigma, 1:200), BrdU/IdU (mouse anti-5’-Bromo-2’-deoxyuridine /5’-Iodo-2’deoxyuridine, Becton Dickinson, 1:50), and BrdU (rat anti-BrdU, Serotec, 1:200). For
fluorescent IHC, sections were incubated with fluorescent secondary antibodies at 1:1000
in 2% serum, 0.03% Triton-100 in PBS for one hour, then stained with 1:1000 Hoechst
33258 (Molecular Probes) in 1 x PBS for one minute for nuclear visualization. Coverslips
were mounded using Vectashield (Vector Labs). For DAB IHC, sections were incubated
in biotin-labeled secondary antibodies (Jackson Immunoresearch) at 1:200 in 2% serum,
30
0.03% Triton-100 in PBS for one hour at room temperature. Tissues were developed via
the Vectastain ABC Elite Kit (Vector Labs) according to the manufacturer’s instructions.
Coverslips were mounted on dehydrated sections using Fluoro Gel (Electron Microscopy
Science).
RNA In Situ Hybridization
Sections were fixed at room temperature in 4% PFA in 1 x TBS for 20 minutes.
Prior to hybridization, sections at room temperature were dehydrated sequentially in
70%, 90%, 100% ethanol for five min each, treated with 1.32% triethanolamine solution
for three min, and incubated in acetic anhydride solution for ten min. Sections were then
pretreated with pre-hybridization solution (100 L/slide; 50% formamide, 5 x SSC, 0.5%
Roche blocking reagent, 0.1% Tween-20, 0.1% CHAPS, 50 g/mL yeast tRNA, 5 mM
EDTA, 50 g/mL heparin in ddH20) for one hr in a humid chamber at 55 ˚C.
Hybridization solution is composed of pre-hybridization solution plus Rnd2 probe (5’CAGAAGATCGGGAGGAACATTC -3’) was designed to the reverse complement of
the targeted Rnd2 mRNA using 2’-O-Methyl RNA (2’OMe) bases with phosphodiester
linkages, ZEN non-nucleotide chemical modifier between the last and next to last base
on both the 5’- and 3’-ends, and DIG group added to both ends to allow for detection
[165]. Sections were incubated in 1.25 pmol Rnd2 probe or scrambled negative control
probe (Integrated DNA Technologies, Coralville, IA, USA) with pre-hybridization
solution (100 L/ slide) for 48 hrs at 55 ˚C under parafilm coverslips. Sections were
washed three times for 30 min each in preheated 2 x SSC/0.1% CHAPS and 0.2 x
SSC/0.01%CHAPS at 55 ˚C prior to blocking sections in 20% sheep serum in KTBT for
one hr at room temperature. Sections were then incubated in 1:500 sheep anti-DIG AP
31
Fab fragment in blocking buffer at 4 ˚C overnight. After washing 3 x 5 min each in 100
mM Tris-HCl, 50 mM MgCl2, 100 mM NaCl, 0.1% Tween-20 in ddH20 at room
temperature, sections were developed using Pierce NBT/BCIP one-touch solution
(34042) in the dark for approximately three hrs. Once developed, sections were washed
briefly in 1 x TBS prior to dehydration and mounting of coverslips using Fluoro Gel
(Electron Microscopy Science).
Microscopy and Statistics
Histology sections were imaged either with a Leica Leitz DM R fluorescent
microscope connected to a Olympus DP72 camera using the Olympus DP2-BSW
software or on the confocal 710 microscope using Zen software. For cell count
quantification, counts were obtained from the motor cortex and surrounding neocortex as
defined by the prenatal brain atlas (gestational day 16 sagittal image 8/9, Schambra
2008). Sections were analyzed from both control and Nestin-Cre Dicer depleted tissue
using mice from three independent breedings. To determine IdU positive cells, we
subtracted the total number of BrdU only positive cells (Serotec) from BrdU/IdU positive
cells (BD Biosciences). All cell count results were normalized to total cells. Statistical
significance was tested using the two-tailed Student’s t-test for unpaired differences with
GraphPad (San Diego, CA) Prism software. For signal intensity quantification, mediallateral plane matched sections were compared using ImageJ software (Rasband, W.S.,
ImageJ, U.S. National Institute of Health, Bethesta, Maryland, USA,
http://imagej.nih.gov/ij, 1997-2011). DCX signal intensity was calculated from a 100
pixels2 area within the cortical plate (CP) and normalized to a 100 pixel2 background area
within the ventricular zone (VZ).
32
RNA Isolation and RT-qPCR Analysis
Total RNA was isolated from the cortex of E15.5 Dicer depleted and control
embryos using Trizol reagent according to manufacturer’s protocol (Invitrogen, CA).
RNA quantity and quality was measured using a ND-1000 (Nanodrop, Wilmington, DE).
Reverse transcription was performed on 1 g of total RNA using the Superscript III
Reverse Transcriptase kit according to manufacturer’s instructions (Invitrogen, CA).
The cDNA was diluted 1:15 in ddH20. Taqman relative quantification PCR was
performed on the diluted cDNA of total cortical RNA following the manufacturer’s
protocol (Applied Biosystems, Foster City, CA), loaded into 384-well plates by an
epMotionTM robot and results normalized to total RNA. Analysis was performed using
average adjusted relative quantification on the following probes: Nestin (Applied
Biosystems, assay ID: Mm00450205_m1), DCX (Applied Biosystems, assay ID:
Mm00438401_m1*), Reelin (Applied Biosystems, assay ID: Mm00465200_m1*), and
Rnd2 (Applied Biosystems, assay ID: Mm00501561_m1*).
33
Figure 2: Transgenic Breeding Scheme
(A) Breeding scheme used for depletion of Dicer in mouse CNS. Fd/Fd; +/+
embryos were used as control samples, while embryos expressing Cre under the
Nestin promoter (fd/fd;ncre/+) were studied for Dicer depletion. (B) Less than
expected Mendelian ratios of Dicer depleted embryos were found at E15.5 and
E16.5.
34
Figure 3: Nestin and MAP2 Dysregulation in Nestin-Cre Dicer Depleted Cerebral
Cortices.
(A) RT-qPCR quantification of Nestin and MAP2 RNA expression from total
RNA isolated from E15.5 cerebral cortex of both control (fd/fd;+/+) and
conditional Dicer depleted (fd/fd:nCre/+) mice, with results normalized to total
RNA. Ctrl, control (fd/fd;+/+); Dd, conditional Dicer depleted (fd/fd:nCre/+).
Error bars represent mean ± SEM. ns= not significant, ***p<0.0001 using a
two-tailed unpaired t-test. (B) Representative photomicrographs showing IHC
for Nestin and MAP2 in the cerebral cortex at E15.5. Scale bars, 100 m.
VZ/SVZ, ventricular zone/subventricular zone; CP, cortical plate
35
Figure 4: Decreased in Progenitor Cell Proliferation in Dicer Depleted Cortical
Tissue.
(A) Representative photomicrograph showing IHC for PH3 in cerebral cortices
at both E15.5 and E16.5. Scale bars, 100 m. (B) Quantification of IHC
staining of E15.5 and E16.5 PH3 positive cells within the medial-lateral plane in
matched sections shows decreased proliferating cells within Dicer depleted
cortical tissue. Ctrl, control (fd/fd;+/+); Dd, conditional Dicer depleted
(fd/fd:nCre/+). Y-axis denotes number of PH3 positive cells per 1000 total
cells as defined by Hoechst staining in a 20x field. Error bars represent mean ±
SEM. ***p<0.0001 using a two-tailed unpaired t-test.
36
Figure 5: Reduction in Proliferation and Cell Cycle Kinetics in Dicer Depleted
Brains.
(A) Representative photomicrograph showing immunofluorescence staining for
BrdU and IdU in the medialcryosections from control (fd/fd:+/+) and conditional Dicer depleted
(fd/fd:nCre/+) mice. Scale bars, 20 m. VZ, ventricular zone; SVZ,
subventricular zone. (B) Quantification of total immunofluorescence staining of
E15.5 BrdU and BrdU/IdU positive cells showing reduction in overall
proliferating cell number. Y-axis denotes number of labeled cells per 100 total
cells as defined by Hoechst staining in a 40x field. (C) Quantification of
immunofluorescence staining of E15.5 BrdU or IdU positive cells, showing a
retardation of the cell cycle kinetics in Dicer depleted brains as defined by the
increase in S Phase cells and decrease in G2/M Phase cells. Y-axis denotes
percentage of BrdU labeled or IdU-only labeled cells within the total labeled
cell count. Ctrl, control (fd/fd;+/+); Dd, conditional Dicer depleted
(fd/fd:nCre/+); S Phase = percentage of labeled cells positive for BrdU; G2/M
Phase = percentage of labeled cells positive only for IdU. Error bars represent
mean ± SEM. *p<0.5, ***p <0.0001 using a two-tailed unpaired t-test.
37
Figure 6: Increased Apoptotic Cell Death in Dicer Depleted Cortical Tissues.
(A) Representative photomicrographs of immunofluorescence staining for
activated Caspase3 (Casp3) in cerebral cortices at both E15.5 and E16.5. Scale
bars, 100 m. VZ/SVZ, ventricular zone/subventricular zone; CP, cortical plate.
(B) Quantification of immunofluorescence staining of E15.5 and E16.5 Casp3
positive cells completed in the medial-lateral plane in matched sections, show
significantly increased apoptotic cell death within Dicer depleted cortices. Yaxis denotes number of Casp3 positive cells per 1000 total cells as defined by
Hoechst staining in a 20x field. Ctrl, control (fd/fd;+/+); Dd, conditional Dicer
depleted (fd/fd;nCre/+). Error bars represent mean ± SEM. *p<0.01, ***p
<0.0001 using a two-tailed unpaired t-test.
38
Figure 7: Impaired Migration of C-R Neurons in the Dicer Depleted Cerebral
Cortex.
(A) Immunofluorescence staining for activated Calretinin (CR; red) and
Hoechst33258 (blue) at E15.5 with higher magnification inset. Scale bars, 20
m. VZ/SVZ, ventricular zone/subventricular zone; CP, cortical plate; MZ,
marginal zone. (B) Quantification of immunofluorescence staining of E15.5 CR
positive cells completed in the medial-lateral plane in matched sections show
significant changes in CR positive cells numbers, with the contributing increase
of CR+ neurons showing impaired migration to the marginal zone in Dicer
depleted cortical tissue. Y-axis denotes number of CR positive cells per 500
total cells as defined by Hoechst staining in a 40x field. Ctrl, control
(fd/fd;+/+); Dd, conditional Dicer depleted (fd/fd;nCre/+). Error bars represent
mean ± SEM. *p<0.05, ***p <0.0001 using a two-tailed unpaired t-test.
39
Figure 8: Overexpression of Reelin in Dicer Depleted Cerebral Cortices.
(A) RT-qPCR quantification of Reelin RNA expression from total RNA
isolated from E15.5 cerebral cortex of control (fd/fd;+/+) and conditional Dicer
depleted (fd/fd;nCre/+) mice. Error bars represent mean ± SEM. **p<0.001
using a two-tailed unpaired t-test. (B) Representative photomicrograph of IHC
for control (fd/fd;+/+) and Dicer depleted (fd/fd;nCre/+) mice cortices show a
gradient of Reelin overexpression throughout Dicer depleted brains with the
strongest signal intensity in the lateral portion of the cortical plate. Scale bars,
100 m. VZ/SVZ, ventricular zone/subventricular zone; CP, cortical plate.
40
Figure 9: Reduced Immature Migrating Neurons in Dicer Depleted Cortices.
(A) RT-qPCR quantification of DCX RNA expression from total RNA isolated
from E15.5 cerebral cortex of control (fd/fd;+/+) or conditional Dicer depleted
(fd/fd;nCre/+) mice with results normalized to total RNA. Error bars represent
mean ± SEM. Values are statistically significant (*p<0.01) using a two-tailed
unpaired t-test. (B) Representative photomicrograph of IHC for DCX in control
(fd/fd;+/+) and conditional Dicer depleted (fd/fd;nCre/+) embryos showing
reduced spread of DCX positive cells throughout the Dicer depleted cortex.
Scale bars, 100 m. (C) Quantification of average IHC DAB signal intensity
per 100 pixels2 within the cortical plate relative to the VZ, showed increased
DCX signal intensity within E16.5 Dicer depleted cortices. Error bars represent
mean ± SEM. ***p<0.0001 using a two-tailed unpaired t-test. (D)
Quantification of the DCX spread across the cortex is presented as a ratio of
IHC staining of DCX compared to total cortex thickness, with decreased DCX
spread within E15.5 Dicer depleted cortices. Error bars represent mean ± SEM.
*p<0.01 using a two-tailed unpaired t-test. VZ/SVZ, ventricular
zone/subventricular zone; CP, cortical plate.
41
Figure 10: Overexpression of Rnd2, a Multipolar to Bipolar Transition Regulator
in Dicer Depleted Cortical Tissue.
(A) RT-qPCR quantification of Rnd2 RNA expression from total RNA isolated
from E15.5 cerebral cortex of both control (fd/fd;+/+) and conditional Dicer
depleted (fd/fd;nCre/+) mice with results normalized to total RNA. Error bars
represent mean ± SEM. *p<0.01 using a two-tailed unpaired t-test. (B) In situ
hybridization staining for Rnd2. Shown are representative photomicrographs
from 10 m sagittal cryosections through the dorsal telencephalon of control
(fd/fd;+/+) and conditional Dicer depleted (fd/fd;nCre/+) mice, with
overexpression of Rnd2 mRNA is evident throughout the Dicer depleted
cortical tissue. Scale bars, 100 m. VZ/SVZ, ventricular zone/subventricular
zone; CP, cortical plate.
42
Figure 11: The Astrocytic Marker GFAP is Overexpressed in Dicer Depleted
Cortices.
(A) RT-qPCR quantification of GFAP RNA expression from total RNA isolated
from E15.5 cerebral cortex of both control (fd/fd;+/+) and conditional Dicer
depleted (fd/fd;nCre/+) with results normalized to total RNA. Error bars
represent mean ± SEM. *p<0.05 using a two-tailed unpaired t-test. (B)
Representative photomicrographs of IHC staining in control (fd/fd;+/+) and
conditional Dicer depleted (fd/fd;nCre/+) mice cortices show disorganized and
broad expression of GFAP in the Dicer depleted mice cortex. Scale bars, 100
m. VZ/SVZ, ventricular zone/subventricular zone; CP, cortical plate.
43
Figure 12: Dicer Depletion Summary of Results
In summary, Dicer loss leads to mislocalized progenitor cells and disorganized
cortical lamina, reduction in cell cycle kinetics in the developing cortex.
Without Dicer there is early cell death in the developing cerebral cortex and
dysregulated differentiation and migration markers. Dicer depletion causes a
precocious induction of astrocyte differentiation.
44
CHAPTER III:
HUMAN-SPECIFIC MIRNA REGULATION OF FOXO1:
IMPLICATIONS FOR MIRNA RECOGNITION
ELEMENT EVOLUTION
Abstract
MicroRNAs (miRNAs) have been established as important negative posttranscriptional regulators for gene expression. Within the past decade miRNAs targeting
transcription factors (TFs) has emerged as an important mechanism for gene expression
regulation. Here, we tested the hypothesis that in TF 3’UTRs, the human-specific single
nucleotide change(s) that create novel miRNA recognition elements (MREs) contribute to
species-specific differences in TF expression. From several potential human-specific TF
MREs, one candidate, a member of the FOXO subclass in the Forkhead family known as
Forkhead Box O1 (FOXO1; FKHR; NM_002015) was tested further. Human FOXO1
contains two sites predicted to confer miR-183 mediated post-transcriptional regulation:
one specific to humans and one conserved. Utilizing dual luciferase expression
reporters, we show that only the human FOXO1 3’UTR contains a functional miR-183
site, not found in chimpanzee or mouse 3’UTRs. Site directed mutagenesis supports
functionality of the human-specific miR-183 site, but not the conserved miR-183 site.
Via overexpression and target site protection assays, we show that human FOXO1 is
regulated by miR-183, but mouse FOXO1 is not. Finally, FOXO1 regulated cellular
phenotypes, including cell invasion and proliferation are impacted by miR-183 targeting
only in human cells. These results provide strong evidence for human-specific gain of
45
TF MREs, a process that may underlie evolutionary differences between phylogenic
groups.
Introduction
MicroRNAs (miRNAs) are predicted to regulate between 30-66% of all proteincoding genes, ranking them among the largest classes of gene regulators [36, 67]. These
~21-23 nucleotide non-coding RNAs function by post-transcriptionally silencing gene
expression through imperfect base pairing of target messenger RNAs (mRNAs) to induce
translational repression, deadenylation or degradation. Many miRNA gene families are
highly conserved with implications in the regulation of many biological processes,
including cell development, differentiation, metabolism, the cell cycle, and ageing [3, 65,
166]. The canonical miRNA recognition element (MRE) on a target mRNA consists of a
perfect or near perfect reverse complement of miRNA nucleotide positions 2 through 8
from the 5’ end (known as the seed region), together with partial complementarity
throughout the rest of the miRNA and target transcript sequences. Prediction algorithms
query mRNAs for reverse complement miRNA seed sequences to identify predicted
MREs [167].
Insights into the evolution of miRNAs have emerged from bioinformatic analyses
in whole animal studies, and suggest that selective pressure can impart their loss or
conservation [56, 168, 169]. Data support that de novo creation of miRNAs (transevolution) throughout speciation occurs, as evidenced through computational biology and
reporter assay validation [170, 171]. Less is known, however, regarding species-specific
evolution and the functional consequences of a single MRE through cis-evolution.
Moreover, no investigation to date has directly assessed the human cis-evolutionary
46
implications of the relationship between a miRNA and a target mRNA that encodes a
transcription factor (TF), which can have broad implications via indirect regulation of TF
target genes [61, 172-175].
TFs can enhance or repress transcription of genes containing the corresponding
TF consensus binding sequence. TF regulated genes function as central hubs in wellestablished gene regulatory networks, for example those that control the cell cycle state
or cell migration [176-180]. Within the past decade miRNA-TF interactions have
emerged as important mechanisms for gene expression regulation, acting either as buffers
for gene expression or as quick repressive switches in a central hub [9, 125, 141, 181,
182]. Interestingly, tissue- and species-specific miRNAs have a higher propensity to
target TFs than expected [183]. Together with work indicating that in humans, TF
expression diverges more in brain than in other tissues [64], we hypothesized that humanspecific single nucleotide change(s) in a MRE of a TF 3’UTRs would contribute to
species-specific differences in TF expression and subsequent downstream TF-regulated
functional processes.
Here, we identified using bioinformatic methods, candidate TF:MRE pairs that
may be unique to TF regulation in human cells vs. other mammals, including primates.
We used wet lab approaches to fully characterize the functional implications of one of
these, FOXO1, and show that FOXO1 is regulated by miR-183 in human cells through
the gain of a single nucleotide substitution, and that this regulation is important for
FOXO1-dependent functions including proliferation and migration. [176-179].
47
Results
Selection of Candidate Human-Specific MRE
To detect human specific MREs, we first predicted human MREs in the 3’ UTRs
of 100 human transcription factors. Next, we identified single nucleotide changes of
human MREs in the 3’ UTRs of orthologous transcription factors in chimpanzee (Pan
troglodytes), rhesus macaque (Macaca mulatta) and mouse (Mus musculus). This
bioinformatic analysis resulted in 198 human-specific MREs in 100 transcription factors
from 136 conserved miRs (Figure 13). We supported our output by comparing our
predictions to the PITA algorithm, which computes a ΔΔG score by subtracting the MRE
openness score (ΔGopen) from the binding energy of miRNA-target duplex (ΔGduplex) (data
not shown). MiRNA sequence target prediction is greater when ΔΔG=ΔGduplex - ΔGopen
scores are < -10 units. Additionally, we completed a gene ontology (GO) analysis over
orthologous genes with human specific MREs and found that biological processes related
to neuron and brain function are highly enriched (data not shown).
We chose four candidate human-specific TF MREs from the bioinformatic
analysis for further validation. As a first round of validation for human-specific TF
MREs, we cloned the human TF 3’UTRs into psiCHECK-2TM dual luciferase plasmid,
downstream of R. luciferase, to test for miRNA regulation using pre-miRNAs at
increasing doses. We found that the human-specific predicted miR-145* site on RBPJ
(Recombining binding protein suppressor of hairless) and the miR-183 site on FOXO1
(Forkhead Box O1) showed significant decreases in luciferase expression relative to
control pre-miRs (Figure 14A and Figure 17B). No evidence of luciferase expression
48
regulation was found when co-transfecting pre-miR-7 or pre-miR-7* with psiCHECKTM2-NFYA (nuclear transcription factor Y subunit alpha) or psiCHECKTM-2 MEF2A
(myocyte enhancer factor-2a) plasmids, respectively (Figure 14B and C). Given the
high false positive rates of miRNA target prediction algorithms [66], we were encouraged
that 50% of our in silico predictions are putative MREs.
Human FOXO1 Contains Predicted
MiR-183 Regulatory Sites
Of the candidate TFs predicted to be regulated by human-specific MREs, FOXO1
was particularly interesting because its 3’ UTR harbors both conserved and humanspecific miR-183 sites (Figure 15). To determine the impact of two miR-183 MREs on
the human FOXO1 mRNA relative to those from other species, we also amplified
genomic DNA from chimpanzee and mouse FOXO1 3’UTRs and cloned them into
psiCHECKTM-2 dual luciferase plasmids downstream of Renilla luciferase. A positive
control for miRNA regulation included a perfect target control cloned into the 3’UTR of
Renilla Luciferase. When the perfect target control plasmid was transfected into cells
with pre-miR-183, there was significant silencing (Figure 16). To test for miRNA
regulation of the independent MREs, each 3’UTR reporter was co-transfected with
increasing doses of synthetic pre-miR-183. We also tested the effects of both a
scrambled control pre-miR-NEG and an additional irrelevant pre-miR-146b control,
which is not predicted to target the FOXO1 3’UTR in any species. Co-transfection of
pre-miR-183 and FOXO1 3’UTR reporter plasmids resulted in a dose dependent
reduction of luciferase constructs harboring the human FOXO1-3’UTR (Figure 17A and
49
B), but no change in chimpanzee (Figure 17A and C) or mouse (Figure 17A and D)
FOXO1-3’UTR reporter constructs relative to negative controls. These data indicate that
the conserved miR-183 MRE is not a functional site. Interestingly, the conserved human
miR-183 site has a ΔΔG score of -1.86 and the human-specific miR-183 site a ΔΔG score
of -10.35. From this we infer that the human-specific miR-183 site is more available for
miRNA regulation than the conserved site [78].
To confirm that the single nucleotide difference in human FOXO1 3’UTR is the
sole contributor to the functional human-specific miR-183 site, we completed site
directed mutagenesis to generate single nucleotide seed sequence changes, which either
ablated the potential miR-183 MRE in the human specific MRE or created a predicted
miR-183 MRE in the chimpanzee and mouse 3’UTRs. We repeated the relative
luciferase assay with these constructs and observed a dose dependent reduction in the
RLU expression in the chimpanzee (Figure 18A and D) and mouse (Figure 18A and E)
FOXO1-3’UTR mutant constructs, which now match the human-specific miR-183 MRE.
Conversely, when the human-specific miR-183 site was mutated to match the analogous
chimpanzee 3’UTR, miR-183 repression was lost (Figure 18A and C). These results
show that the single nucleotide change in human FOXO1 3-UTR is necessary and
sufficient to induce miR-183 targeting in the context of the psiCHECKTM-2 dual
luciferase system. Interestingly, ablation of the conserved human miR-183 site via site
directed mutagenesis had no impact on luciferase expression relative to the normal
FOXO1 human 3’UTR (Figure 18A and B), indicating that the conserved miR-183 site
in the human FOXO1 3’UTR is not functional. This result is supported by output from
the PITA algorithm, which computes a ΔΔG score by subtracting the MRE openness
50
score (ΔGopen) from the binding energy of miRNA-target duplex (ΔGduplex). MiRNA
sequence target prediction is greater when ΔΔG=ΔGduplex - ΔGopen scores are < -10 units.
The conserved human miR-183 site has a ΔΔG score of -1.86 and the human-specific
miR-183 site a ΔΔG score of -10.35. The main distinguishing difference between the two
sites are that the conserved site has a lower ΔGopen score of -12.13, while the humanspecific miR-183 site has a ΔGopen score of -6.24; from this we infer that the humanspecific miR-183 site is more available for miRNA regulation than the conserved site
[78].
MiR-183 Targets Endogenous FOXO1 at
the Human-Specific MRE
Further evidence for human-specific regulation of FOXO1 expression by miR183 was tested with the endogenous FOXO1 transcript as a target in human and mouse
cell lines. While FOXO1 transcripts are ubiquitously expressed throughout the central
nervous system, miR-183 is preferentially expressed in the cerebellum and striatum.
Thus we chose the human ONS-76 medulloblastoma cell line, which arises from granular
cells, and the mouse C17-2 cerebellar stem cell line, also derived from granule cells
[184]. Both lines have robust FOXO1 and miR-183 expression [185]. We first added
exogenous pre-miR-183 and quantified FOXO1 mRNA levels by RT-qPCR. Pre-miRNEG and pre-miR-146b were used as negative controls. Results showed a dose
dependent decrease in FOXO1 transcripts in human ONS-76 cells transfected with premiR-183 (Figure 19A), but no significant changes in FOXO1 levels in similarly treated
mouse C17-2 cells (Figure 19B). Western blot for FOXO1 protein levels following miR183 transfection was consistent with this; there was decreased FOXO1 protein levels in
51
miR-183 transfected ONS-76 cells (Figure 20A), and no changes in C17-2 cells (Figure
20B). These results confirm that in human ONS-76 cells, but not mouse cells, miR-183
can post-transcriptionally repress FOXO1 transcripts, causing significantly reduced
human FOXO1 protein levels.
We next tested if endogenous miR-183 regulates endogenous FOXO1 transcripts.
For this, we designed oligonucleotides to act as target site protectors (TSPs) to the miR183 MREs. This provides a mechanism to test directly the functional activity of a given
MRE on the transcript in question, without sponging away the miRNA from other
potential targets. TSPs blocking the human-specific MRE (TSP2-183) or sequences
which would recognize the corresponding mouse 3’UTR region of FOXO1 (does not
contain a miR-183 MRE) were transfected into ONS-76 or C17-2 cells, respectively, and
FOXO1 levels quantified by RT-qPCR and western blot. A scrambled negative control
TSP (TSP-NEG) and TSP against the conserved miR-183 site (TSP1-183) were also
tested. While there were no changes in transcript levels with any of the TSPs (Figure 21
A and B), we found that TSP2-183 significantly increased human FOXO1 protein levels
relative to control treated cells or TSP1-183 treated cells (Figure 22A). This change in
FOXO1 protein levels was not found in mouse C17-2 cells transfected with either TSP1183 or TSP2-183 (Figure 22B). These results confirm translational repression of
FOXO1 protein at the human-specific miR-183 MRE in human cells.
Functional Implications of Human FOXO1 Regulation
by MiR-183: Cellular Invasion
FOXO1 plays a known role in transcriptionally regulating cell movement [186].
In human medulloblastoma cell lines, altering miR-183 levels impacts metastasis and
52
invasion [185]. We next confirmed FOXO1’s ability to affect cell invasion by
transfecting siRNAs against FOXO1 in human ONS-76 and mouse C17-2 cells (Figure
23 and Figure 24) and assessed invasion using a MatrigelTM invasion assay. In both
ONS-76 and C17-2 cells there was increased invasion relative to control treatment
(Figure 25). To test if miR-183 regulation of FOXO1 is responsible for this effect, we
performed MatrigelTM invasion assays in cell lines after transfecting with pre-miRs.
Overexpression of pre-miR-183 increased the number of invading cells after 24 hours in
human ONS-76 cells (Figure 26A and B) relative to control pre-miRs, but did not affect
cell invasion in mouse C17-2 cells (Figure 26A and C). To determine if increased
migration after miR-183 transfection occurs through the human specific MRE, we
transfected ONS-76 or C17.6 cells with TSP2-183 or TSP-NEG. We found decreased
invasion relative to TSP-NEG transfected cells in human ONS-76 cell lines (Figure 27A
and B), with no significant change in invasion in similarly treated mouse C17-2 cells
(Figure 27A and C).
Functional Implications of Human FOXO1 Regulation
by MiR-183: Cellular Proliferation
FOXO1 is also implicated in transcriptional regulation of cell cycle progression
[187-189]. We first validated this finding in our cell models using siRNAs against
FOXO1. Using flow cytometry to determine BrdU/propidium iodide (PI) DNA content,
we found decreased FOXO1 expression led to corresponding increases in cells entering
S-phase relative to control treated cells (Figure 28). We next tested if FOXO1-mediated
changes were recapitulated after overexpression of pre-miR-183 in human ONS-76 but
not mouse C17-2 cells. Interestingly, quantification of BrdU/PI DNA content showed a
53
decrease in the total number of cells entering S-phase after pre-miR-183 transfection in
both human ONS-76 cells (Figure 29A and B) and mouse C17-2 cells (Figure 29A and
C). This suggests that pre-miR-183 regulates cell proliferation in each of the tested cell
lines. To test the relevance of the human specific miR-183 MRE in proliferation, we
transfected TSP2-183 and the analogous mouse FOXO1 3’ UTR-specific TSP into ONS76 cells and C17-2 cells, respectively. Quantification showed an increase in total number
of cells entering S-phase when the human-specific miR-183 MRE is protected relative to
a TSP-NEG in ONS-76 cells (Figure 30A and B). No effect on cell cycle was found in
mouse C17-2 cells transfected with sequences analogous to TSP2-183 (Figure 30A and
C). These results indicate that the human-specific miR-183 site along with other miR183 gene targets contribute to a cellular proliferation phenotype.
Discussion
One of the central sources of phenotypic evolution is changes in regulation of
gene expression via mechanisms that act directly on the genome, such as TFs, or through
post-transcriptional mechanisms, such as occurs with miRNAs [33]. A potential source
for positive selection by miRNA regulation is 3’ UTR changes. Interestingly, work by
Miura et al. indicate that 3’UTRs in the mammalian brain are elongated by~ 5-6 Mb
relative to all other mammalian tissues analyzed [190]. Furthermore, in silico studies by
Gardner et al. implicate mutations causing functional loss of MREs during human
evolution, however no function gain of MREs analysis has been completed to date [191].
Phenotypic differences within species may also be caused by changes in miRNAmediated regulation of target transcripts. For example, the TYRP1 is regulated by miR155 and changes in the MRE may underlie differences in skin pigmentation [192].
54
Combining the two central sources of phenotypic evolution, miRNAs have been found to
preferentially target genes with high regulatory complexity (e.g. TFs), and both TF and
miRNA regulation have strong dependent effects on protein evolutionary rates [61, 193,
194]. Together with our data showing gain of MRE target sites in TFs regulated by
miRNAs, it is worth revisiting MREs in the context of large scale phenotypic evolution
through novel targeting of TF 3’UTRs.
We first tested four candidate human-specific TF MRE sites and show regulation
by the predicted miRNA within two of the TF 3’UTRs, FOXO1 and RBPJ. Given the
high false positive rates of miRNA target prediction algorithms [66], we were encouraged
that 50% of our tested in silico predictions are putative MREs. We went on to show that
FOXO1 is regulated by miR-183 in human cells at a novel MRE site which arose from a
single nucleotide substitution. Interestingly, the more conserved of the predicted sites
was not functional. This data helps clarify several conflicting reports regarding the role of
miR-183 on the regulation of FOXO1. Stittrich et al. reported earlier that increased
miR-183 levels after IL-2 induction induced FOXO1, but concluded that the effect of
miR-183 was indirect because only the contribution of the conserved miR-183 binding
site on FOXO1was tested [179]. In studies in endometrial cancer cells, elevated miR-183
correlated with reduced FOXO1 levels compared to control cells, and anti-miR
experiments relieved this repression; however, direct testing of miR-183 MREs was not
done [195]. We find that the gain of the MRE is not present in chimpanzee or mice
FOXO1 3’UTRs, indicating that this site arose after the split of humans and chimpanzees.
Our study shows that the human-specific MRE in FOXO1 impacts TF’s
expression and alters downstream phenotypes associated with FOXO1 levels, thus
55
altering in a species-specific way these TF-regulated phenotypes. More specifically, we
found that miR-183 elevation, or inhibition of its activity at the FOXO1 3’UTR MRE
altered FOXO1 levels and impacted cell invasion and proliferation in human cells. These
results have relevance for human cancers, where FOXO1 is decreased and miR-183
levels are elevated [185, 196-198]. Interestingly, the FOXO1 transcript also contains
predicted conserved and non-conserved MREs for the two other miRNAs in the miR183~96~182 cluster, although neither miR-96 nor miR-182 were predicted in our analysis
to be human-specific MREs. The predicted target sites of miR-182/96 in the FOXO1
3’UTR do not overlap with the target sites of miR-183, and thus do not contribute to
competitive inhibition of miR-183 regulation. Additionally, PITA predictions of the nonconserved miR-182 and miR-96 sites indicate a low likelihood of targeting potential,
similar to what was found for the nonfunctional, conserved miR-183 site. It would be
interesting in subsequent work to evaluate the relationship of these miRNAs on FOXO1
regulation, especially in the context of cancer cell biology where this cluster is shown to
be upregulated [199].
We used PITA to identify MREs of low ΔΔG score (ΔΔG <-10 units), as
described in the results section, with the idea that these may represent novel, humanspecific TF MREs. In addition to the miR-183:FOXO1 interaction, miR-205 may target
the human ras responsive element binding protein 1 (RREB1) 3’UTR. Interestingly,
RREB1 is a human oncogene and miR-205 is a putative tumor suppressor [200-202].
Moreover, the TF Specific protein 1 (Sp1) has two conserved miR-7 MREs and one
human-specific miR-7 MRE that provide for additive regulation in human brain tissue,
where both Sp1 and miR-7 are highly expressed [203]. Individually, Sp1 and miR-7
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dysregulation has been found in many cancers and neurodegenerative disorders, but their
relationship has not been defined.
While our study defined in silico predictions based on canonical seed sequence
complementarity, non-canonical miRNA:mRNA target interactions have also been shown
to be functional [29, 204]. Also, recent work suggests that miRNAs can target coding,
intronic, and 5’UTR regions, although these predicted binding sites have low validation
rates. Further experimental analyses of the TF:MRE sites presented here should consider
MRE accessibility with relation to both mRNA secondary structure and protein-regulated
site competition, as well as miRNA and mRNA co-expression in the tissue or cell of
interest [33, 183]. Several methods to identify bona fide targets include HITS-CLIP,
PAR-CLIP, and CLASH [205-207], which additionally take into consideration tissuespecificity of miRNA interactions, an aspect that was not addressed in our study due to
the publicly available databases to determine tissue-specific expression, including
ArrayExpress [208], BioGPS [209], BODYMAP [210], GEO [211], and TiGER [212].
Darnell and colleagues generated the first mouse brain transcriptome-wide Ago2 binding
map, with many Ago2 footprints in 3’UTRs, coding regions and introns corresponding to
known, highly-enriched, brain mRNAs. A similar investigation in human brain samples
will increase our understanding of how miRNA regulation on brain transcripts
participates in evolutionary speciation.
Materials and Methods
Bioinformatic Analysis
We retrieved human mature miR sequences (miRBase release16) [213] and their
orthologous sequences in chimpanzee (panTro2), rhesus macaque (rheMac2) and mouse
57
(mm9) from the UCSC 46-way alignment of the human genome and 45 other vertebrate
genomes (http://hgdownload.soe.ucsc.edu/goldenPath/hg19/multiz46way/) [214]. The
347 mature miR families with conserved seed regions (2nd to 8th position of the mature
miR) in all four species were retained for MRE prediction. We used TargetScan [30] to
predict the MREs of conserved miRs in the Ensembl 3’ UTRs (Ensembl release 63) of
125 human transcription factors which were compiled from TRANSFAC database [215]
and filtered for: (1) one-to-one orthologous genes in chimpanzee, rhesus macaque and
mouse based on Ensembl annotation [216] and (2) the availability of corresponding
ChIP-Seq data in ENCODE project. Next, predicted human MREs were compared to
their orthologous sequences in chimpanzee, rhesus macaque and mouse. If none of the
orthologous sequences of a human MRE forms a canonical base-pairing with the miR
according to TargetScan, it is defined as a human-specific MRE. To focus only on fixed
human-specific MREs, Human dbSNP 138 database was searched for SNPs at the
mutation sites of human-specific MREs. The allele frequency data were retrieved from
1000 Genomes human genetic variation project (http://www.1000genomes.org/data).
This analysis identified 198 human-specific MREs from 136 miRs on 100 transcription
factors. Analysis completed by Ji Wan.
PITA Target Site Predictions
Binding energies were calculated for each miRNA/target site pair identified as
being a human-specific TF MREs using the standalone implementation of the PITA
target prediction algorithm (http://genie.weizmann.ac.il/pubs/mir07/mir07_exe.html).
Target sites overlapping the human-specific TF MREs were identified. Binding energies
58
(ΔΔG) are reported as the average score for all miRNAs in the respective miRNA
families. Analysis completed by Ryan Spengler.
Cell Cultures
Human HEK 293 and ONS-76 cells were cultured in Dulbecco’s modified
Eagle’s medium (DMEM) (Gibco-BRL, Grand Island, NY) supplemented with 10% fetal
bovine serum and 1% Penicillin/Streptomycin. Mouse C17-2 cerebellar stem cells were
cultured in DMEM supplemented with 10% fetal bovine serum, 5% equine serum, 1%
Penicillin/Streptomycin, and 1% L-Glutamine. All cells were incubated at 37 ˚C in a 5%
CO2 atmosphere.
PsiCHECKTM-2 Dual Luciferase 3’UTR Plasmids
The 3’ UTRs of candidate TFs from human, chimp, and mouse were amplified from
genomic DNA of human HEK 293, chimp fibroblast cell lines, and mouse tail fibroblasts
using Expand High Fidelity DNA polymerase (Roche Applied Science) and 3’ UTR
specific primers (designed using Primer3 software and purchased from Integrated DNA
Technologies) (Supplemental Methods). Cloned PCR products were ligated into Topo
TA plasmid and maintained as stock. Validation of correct PCR product insertion into
Topo TA plasmid was confirmed through restriction enzyme digestion and Sanger
sequencing. Proper PCR amplicons were digested out of Topo TA plasmid and ligated
into a psiCHECKTM-2 dual luciferase plasmid downstream of Renilla luciferase.
Perfect Target Luciferase Controls
Artificial 3’UTR perfect target (PT) controls were created to control for pre-miR
silencing efficiency. PTs were created by complexing 8 M of sense and antisense
oligonucleotides containing a site with perfect complementarity to the mature miRNA
59
with random flanking sequence and restriction sites (Supplemental Methods). PCR
cycles were performed three times at 94 ˚C for 3 min, oligo Tm ˚C for 2 min, and 72 ˚C
for 15 min. Purified sequences were cloned downstream of Renilla luciferase.
PsiCHECKTM-2 Dual Luciferase Assay
HEK293 cells were transfected on 24-well plates using Lipofectamine 2000 (Invitrogen)
per manufacturer’s instructions to facilitate co-transfection of 4 ng of psiCHECKTM-2
3’UTR plasmids and 0-30 nM of artificial precursor miRNAs (pre-miRs): pre-miR of
interest, irrelevant control pre-miR or a neg-control pre-miR. Artificial pre-miRs were
purchased from Life Technologies: pre-miR-NEG #2 (AM17111), pre-miR-183-5p
(PM12830), and pre-miR-146b (PM10105). Transfection media was completely
removed 24 hours post-transfection and cells were washed in ice cold PBS. Relative
luciferase units (RLU) were measured according to the manufactures instructions
(Promega) using a moon light luminometer (Pharmingen). Dual luciferase assays are
reported by normalizing Renilla luciferase values to firefly luciferase values and
normalized relative to controls. All experiments are performed in triplicate for each dose
with a total of three experiments (n=3) for statistical analysis. Data represents an average
of the triplicates for each condition.
Site Directed Mutagenesis
Using the psi-CHECK-2 dual luciferase plasmids with candidate TF 3’UTRs, single
nucleotide mutations were made in the predicted human-specific MREs using the
Phusion Site-Directed Mutagenesis Kit according to manufacturer’s instructions
(Finnzymes) (Supplemental Methods). All constructs were sequenced across both
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junctions to confirm the correct 3’UTR target was inserted with the proper orientation
and sequence.
Overexpression In Vitro Studies
In vitro expression assays were completed in both human ONS-76 medulloblastoma cell
line and mouse C17-2 cerebellar stem cell line. For all expression assay experiments, we
used RNAimax as per manufacturer’s instructions for more efficient transfection of small
RNAs. Overexpression assays consisted of cells transfected with 0-30nM of artificial
pre-miR as described in psiCHECKTM-2 Dual Luciferase Assays.
Target Site Protectors Transfections
Target site protectors (TSPs) to the transcript of interest were designed as a variant on the
ZEN-AMO chemistry design from Integrated DNA Technologies, Coralville, IA. Each
TSP sequence contains 2-O-methyl RNA nucleotides and a ZEN non-nucleotide modifier
between the first two and last two nucleotides of each sequence. TSP assays consisted of
cells transfected with 30nM of TSP. Experiments were performed using TSP against the
conserved miR-183 (TSP1-183), the human-specific miR-183 site (TSP2-183), or a
negative control TSP (TSP-NEG) at a final concentration of 30 nM.
RNA Isolation and RT-qPCR Analysis
Total RNA was isolated from cells 24 hours post-transfection using Trizol reagent
according to manufacturer’s protocol (Invitrogen, CA) . Reverse transcription was
performed on 1 g of total RNA using the High Capacity cDNA Reverse Transcriptase
kit according to manufacturer’s instructions (Invitrogen, CA). The cDNA was diluted
1:15 in ddH20. Taqman relative quantification PCR was performed on the diluted cDNA
of total RNA following the manufacturer’s protocol (Applied Biosystems, Foster City,
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CA) and results normalized to total RNA. Analysis was performed using average
adjusted relative quantification on the following probes from Applied Biosystems:
FOXO1 (Hs01054576_m1, Mm00490672_m1), Human GAPDH (4326317E), Mouse βActin (4352341E), miR-183-5p (002269), RNU48 (1006), Sno202 (1232).
Western Blot Assay
Protein was harvested using RIPA buffer (Pierce) and 1x protease inhibitor using
standard techniques and quantified using DC Protein Assay (Bio-Rad). Protein extracts
were separated on a 4%-12% Bis-Tris Gel with MES (Invitrogen) and transferred to
Immobilon 0.45m PVDF transfer membranes (Millipore). Primary antibodies to
FOXO1 (1:200; sc-11350; Santa Cruz Biotechnology, Inc.) and β-Actin (1:2,500; A5441;
Sigma ) were used. Blots were developed using ECL Plus Western Blotting Detection
System (GE Healthcare) and quantified by VercaDoc 5000 MP (BioRad Laboratories,
Inc.).
Invasion Assay
Human ONS-76 and mouse C17-2 cell lines were cultured and transfected according to
techniques described. Prior to transfection, cells were serum starved in 0.5% serum
culture media. Following 24 hours transfection, upper chambers of MitragelTM Invasion
Chambers (354480; BD Biosciences) with 8 m pores were seeded with 1.0 x 105
transfected cells in 0.5% serum culture media and placed in 24-well dishes containing
10% serum culture media. Cells were allowed to migrate to underside of membrane for
24 hours, then gently washed in cold PBS and fixed in 4% paraformaldehyde for 10
minutes. Non-invading cells were removed by gently wiping upper chamber with cottontipped swab. Invaded cells were incubated in Hoechst (1:5000; 33342; Sigma), washed
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and imaged by a Leica Leitz DMR fluorescent microscope at 20x magnification. Cell
counts were determined using ImageJ software (Rasband, W.S., ImageJ, U.S. National
Institute of Health, Bethesda, Maryland, USA, http://imagej.nih.gov/ij, 1997-2011). All
cell counts were normalized to negative control + FBS condition. All experiments were
performed in triplicate.
PI Flow Cytometric Analysis for DNA Content
Human ONS-76 and mouse C17-2 cell lines were cultured and transfected
according to technique describe above. 5-bromo-2’-deoxyuridine/propidium iodide
(BrdU/PI) cell cycle analysis (similar to Fineberg et al. [217]). Thirty minutes prior to
cell harvest, BrdU (20 M, Sigma) was added to cell media for S-phase cell integration.
At harvest, cells were dissociated with 0.25 % trypsin, pelleted, washed in ice-cold PBS,
and resuspended in 0.4 mL of ice-cold PBS. While vortexing, 3.6 mL of ice-cold 95%
EtOH was added to cells incubated at room temperature (RT) for 45 minutes. Cells were
then washed in PBS-TB (PBS with 0.2% Tween and 0.1% BSA) and re-suspended in 0.3
mL of 2 N HCL and incubated for 30 minutes in the dark at RT. To neutralize, 0.9 mL of
0.1 M sodium tetraborate was added to acidic cell solution. Pelleted cells were washed
and incubated with PBS-TB diluted anti-BrdU (1:50, BD Biosciences #347580)
overnight at 4 ºC on the rocker. Cells were washed 2x in PBS-TB and incubated with
Alexa Fluor-488-conjugated goat anti-mouse IgG (Invitrogen) for 30 minutes at RT in the
dark. Pelleted and washed cells were then re-suspension in 500uL fresh propidium iodide
(PI)/RNaseA solution (PBS with PI at 20ug/mL, RNaseA at 200ug/mL, and 0.05%
tween-20) and incubated in the dark for 30 minutes at RT. Cell samples were stored up to
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1 day at 4ºC before collected on Becton Dickinson LSR II with UV at the University of
Iowa Flow Cytometry Facility (http://www.healthcare.uiowa.edu/corefacilities/flow
cytometry/). Fifteen thousand single-nuclei events were acquired and analyzed using
FlowJo software to determine cell cycle proportions in quadrants. Upper left and upper
right quadrants represent all S-phase BrdU positive cells. The lower left indicates G1
phase cells and lower right indicates G2/M phase cells. All experiments were performed
in triplicate.
Statistics
Statistical significance was determined using either Student’s unpaired t-test, oneway ANOVA followed by Dunnettt’s post hoc analysis, or two-way ANOVA followed
by Bonferroni post hoc analysis (GraphPad Prism software, San Diego CA).
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Figure 13: Schematic Representation for Human-Specific MRE Detection
(A) miR seed region is defined as 2-8nt region of mature miR. Single nucleotide
change is required to exist in all three species (chimpanzee, rhesus macaque and
mouse) before defining a human-specific MRE. See “Methods” for details.
Created by McLoughlin and Wan.
65
Figure 14: Human Gain of Target Candidate Validation of MRE in 3'UTR
Dual luciferase plasmids (psiCHECKTM-2) containing the human (Hsa) 3’UTR of
either RBPJ, NFYA, or MEF2A were co-transfected with increasing doses of
either pre-miR-NEG control (black), relevant pre-miR (blue), or irrelevant premiR control (white) into HEK293 cells. (A) Increasing expression of pre-miR145* in cells transfected with psiCHECKTM-2-RPBJ 3-UTR plasmid leads to a
dose dependent decrease of RLU expression relative to controls pre-miRs. (B , C)
No significant change in RLU expression was found when co-transfecting premiR-7 or pre-miR-7* with psiCHECKTM-2-NFYA or psiCHECKTM-2 MEF2A
plasmids, respectively. (C) Interestingly, expression of pre-miR-183 in cells
transfected with psiCHECKTM-2-MEF2A 3-UTR plasmid led to a dose dependent
decrease of RLU expression relative to controls pre-miRs. Prediction databases
validated this result as a conserved miR-183 target site in the MEF2A 3’UTR.
All luciferase experiments were performed in triplicate for each pre-miR dose [030nM]. Each experiment was repeated in triplicate for each dose. Bars represent
mean ± SEM, *p<0.05, **p<0.01, ***p<0.001.
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Figure 15: FOXO1 3’UTR Schematic of MiR-183 MRE
(A) Schematic of FOXO1 of both the conserved and human-specific miR-183
prediction MREs in human (hsa), chimpanzee (pan), and mouse (mmu) 3’UTRs.
67
Figure 16: Validation of Pre-miR-183 Processing and Targeting Capacity
(A) PsiCHECKTM-2 plasmids of antisense oligonucleotides containing a site
with perfect complementarity to the mature miR-183 (PT 183) or miR-183*
(PT 183*) and were co-transfected with 30nM of either pre-miR-NEG
control or pre-miR-183 in HEK293 cells. A pre-miR-183 dependent
repression was only found when co-transfected with psiCHECKTM-2-PT 183
plasmid, but not psiCHECKTM-2-PT 183* plasmids relative to pre-miRNEG control. All luciferase experiments were performed in triplicate for
each pre-miR. Bars represent mean ± SEM, ***p<0.001.
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Figure 17: Human FOXO1 3’UTR Targeted by MiR-183
(A) Schematic of human (hsa), chimpanzee (pan), and mouse (mmu) FOXO1
3’UTR psiCHECKTM-2 plasmids. PsiCHECKTM-2 plasmids containing the
3’UTR of FOXO1 cloned from (B) hsa, (C) pan, and (D) mmu were cotransfected with either pre-miR-NEG control, pre-miR-183, or irrelevant pre-miR146b control into HEK293 cells. All luciferase experiments were performed in
triplicate for each pre-miR dose [0-30nM]. Bars represent mean ± SEM, *p<0.05,
**p<0.01, ***p<0.001.
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Figure 18: Human-Specific MiR-183 MRE is Functional on Human FOXO1 3’UTR
(A) Schematic of FOXO1 3’UTR psiCHECKTM-2 plasmids human (hsa),
chimpanzee (pan), and mouse (mmu) single nucleotide mutations in the
psiCHECKTM-2 3’UTR constructs included: (B) a nucleotide change at the
conserved site of the hsa 3’UTR from GA; (C) a nucleotide change at the hsaspecific miR-183 predict site in the hsa 3’UTR from GA; (D, E) a mutation in
pan and mmu 3’UTR from AG or CG, respectively. PsiCHECKTM-2
constructs were co-transfected with either pre-miR-NEG control, pre-miR-183, or
irrelevant pre-miR-146b control into HEK293 cells. All luciferase experiments
were performed in triplicate for each pre-miR dose [0-30nM]. Bars represent
mean ± SEM, *p<0.05, **p<0.01, ***p<0.001.
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Figure 19: Pre-miR-183 Modulates FOXO1 Transcript Levels in Hsa ONS-76 Cells
but not Mmu C17-2 Cells
Hsa ONS-76 and mmu C17-2 cells were transfected with increasing doses of
either pre-miR-NEG control, pre-miR-183, or irrelevant pre-miR-146b control.
Transfection of pre-miR-183 in hsa ONS-76 cells, showed significant dose
dependent decreases in hsa FOXO1 (hFOXO1) (A) mRNA expression relative to
control treatments. (B) Transfection of pre-miRs in mmu C17-2 cells results in no
change to endogenous levels of mouse FOXO1 (mFOXO1) mRNA expression.
All mRNA experiments were performed in triplicate for each pre-miR dose [030nM]. Each experiment was repeated in triplicate for each dose. Bars represent
mean ± SEM, *p<0.05, **p<0.01.
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Figure 20: Pre-miR-183 Modulates FOXO1 Protein Expression Levels in Hsa ONS76 Cells but not Mmu C17-2 Cells
Hsa ONS-76 and mmu C17-2 cells were transfected with increasing doses of
either pre-miR-NEG control, pre-miR-183, or irrelevant pre-miR-146b control.
Transfection of pre-miR-183 in hsa ONS-76 cells, showed significant dose
dependent decreases in hsa FOXO1 (hFOXO1) (A) mRNA expression relative to
control treatments. (B) Transfection of pre-miRs in mmu C17-2 cells results in no
change to endogenous levels of mouse FOXO1 (mFOXO1) mRNA expression.
Protein assessed after 30 nM pre-miR transfection. Each experiment was repeated
in triplicate for each dose. Bars represent mean ± SEM, **p<0.01.
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Figure 21: TSP of FOXO1 3’UTR does not Change FOXO1 Transcript Levels
Hsa ONS-76 and mmu C17-2 cells were transfected with either TSP-NEG
control, TSP1-183, or TSP2-183. Transfection of TSPs in (A) hsa ONS-76 and
(B) mmu C17-2 cells, showed no significant changes in FOXO1 mRNA
expression after TSP transfection. All experiments were performed in triplicate
for each TSP [30nM]. Each experiment was repeated in triplicate for each TSP.
Bars represent mean ± SEM.
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Figure 22: TSP of FOXO1 3’UTR Regulates Expression Levels at Human-Specific
MRE in Hsa ONS-76 Cells
Hsa ONS-76 and mmu C17-2 cells were transfected with either TSP-NEG
control, conserved TSP1-183, or human-specific TSP2-183. Transfection of TSPs
in (A) hsa ONS-76 and (B) mmu C17-2 cells, showed significant changes in
FOXO1 protein expression in TSP2-183 transfected hsa ONS-76 cells, but not
mmu C17-2 cells. All experiments were performed in triplicate for each TSP
[30nM]. Each experiment was repeated in triplicate for each TSP. Bars represent
mean ± SEM, *p<0.05.
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Figure 23: SiRNA Against FOXO1 Decreases RNA Transcript Levels
Hsa ONS-76 and mmu C17-2 cells were transfected with siRNA against FOXO1.
Transfection of 10nM siRNAs in (A) ONS-76 and (B) C17-2 cells, showed
significant decreases in endogenous FOXO1 mRNA expression after 24hrs. All
experiments were performed in triplicate for each siRNA. Bars represent mean ±
SEM, *p<0.05, **p<0.01, ***p<0.001.
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Figure 24: SiRNA Against FOXO1 Decreases Protein Expression Levels
Hsa ONS-76 and mmu C17-2 cells were transfected with siRNA against FOXO1.
Transfection of 10 nM siRNA in (A) ONS-76 and (B) C17-2 cells, showed
significant decreases in endogenous FOXO1 protein expression after 24hrs. All
experiments were performed in triplicate for each siRNA. Bars represent mean ±
SEM, *p<0.05, **p<0.01, ***p<0.001.
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Figure 25: SiRNA Against FOXO1 Induces Cell Invasion in ONS-76 Cells and C172 Cells
Hsa ONS-76 and mmu C17-2 cells were transfected with 10nM of either siRNANEG control, FOXO1-siRNA1, or FOXO1-siRNA2 and plated into MatrigelTM
transwells. (A) Representative images from a transwell MatrigelTM invasion show
significant increase in cell invasion upon overexpression of FOXO1-siRNA1 in
ONS-76 cells and FOXO1-siRNA1 and FOXO1-siRNA2 in C17-2 cells. (B) Hsa
ONS-76 and (C) mmu C17-2 migrated cells were quantified from 20x fields and
normalized to the average number of siRNA-NEG cells with FBS chemoattractant in at least three independent experiments. Bars represent mean ± SEM,
*p<0.05, **p<0.01, ***p<0.001.
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Figure 26: Pre-miR-183 Induces Cell Invasion in Hsa ONS-76 Cells but not Mmu
C17-2 Cells
Hsa ONS-76 and mmu C17-2 cells were transfected with 30nM of either pre-miRNEG control, pre-miR-183, or irrelevant pre-miR-146b control and plated into
MatrigelTM transwells. (A) Representative images from a MatrigelTM transwell
invasion show significant increase in cell invasion upon overexpression of premiR-183 in ONS-76 cells, but not in C17-2 cells. (B) Hsa ONS-76 and (C) mmu
C17-2 migrated cells were quantified from 20x fields and normalized to the
average number of pre-miR-NEG cells with FBS chemo-attractant in at least three
independent experiments. Bars represent mean ± SEM, *p<0.05, **p<0.01,
***p<0.001.
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Figure 27: TSP of Human-Specific MiR-183 MRE Impedes Cell Invasion in Hsa
ONS-76 Cells but not Mmu C17-2 Cells
Hsa ONS-76 and mmu C17-2 cells were transfected with 30nM of either TSPNEG control, conserved TSP1-183, or human-specific TSP2-183 and plated into
MatrigelTM transwells. (A) Representative images from a transwell MatrigelTM
invasion show significant decrease in cell invasion upon target site protection
with TSP2-183 in ONS-76 cells, but not in C17-2 cells. (B) Hsa ONS-76 and (C)
mmu C17-2 migrated cells were quantified from 20x fields and normalized to the
average number of TSP-NEG cells with FBS chemo-attractant in at least three
independent experiments. Bars represent mean ± SEM, *p<0.05, ***p<0.001.
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Figure 28: SiRNA Against FOXO1 Impedes S-Phase Progression in ONS-76 Cells
and C17-2 Cells
Hsa ONS-76 and mmu C17-2 cells were transfected with 10nM of either siRNANEG control, FOXO1-siRNA1, or FOXO1-siRNA2. Prior to harvest, cells were
pulsed with BrdU for 30 minutes under proliferating conditions and processed to
determine BrdU incorporation (A488) and DNA content (PI-A). (A)
Representative BrdU/PI dot plots are shown, and quadrant statistics for 3 replicate
experiments are displayed on the dot-plots (mean ± SEM of three experiments) .
(B) Hsa ONS-76 and (C) mmu C17-2 cells displayed significant decrease in % of
S-phase cells upon overexpression of all FOXO1-siRNAs. Bars represent mean
± SEM, *p<0.05, **p<0.01, ***p<0.001.
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Figure 29: Pre-miR-183 Impedes S-Phase Progression in both Hsa ONS-76 and
Mmu C17-2 Cells
Hsa ONS-76 and mmu C17-2 cells were transfected with 30nM of either pre-miRNEG control, pre-miR-183, or irrelevant pre-miR-146b control. Prior to harvest,
cells were pulsed with BrdU for 30 minutes under proliferating conditions and
processed to determine BrdU incorporation (A488) and DNA content (PI-A). (A)
Representative BrdU/PI dot plots are shown, and quadrant statistics for 3 replicate
experiments are displayed on the dot-plots (mean ± SEM of three experiments).
Both (B) hsa ONS-76 and (C) mmu C17-2 cells displayed significant decrease in
% of S-phase cells upon overexpression of pre-miR-183. Bars represent mean ±
SEM, *p<0.05, **p<0.01, ***p<0.001.
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Figure 30: TSP of Human-Specific MiR-183 MRE Induces S-Phase Progression
Only in Hsa ONS-76 Cells but not in Mmu C17-2 Cells
Hsa ONS-76 and mmu C17-2 cells were transfected with 30nM of either TSPNEG control, conserved TSP1-183, or human-specific TSP2-183. Prior to
harvest, cells were pulsed with BrdU for 30 minutes under proliferating
conditions and processed to determine BrdU incorporation (A488) and DNA
content (PI-A). (A) Representative BrdU/PI dot plots are shown, and quadrant
statistics for 3 replicate experiments are displayed on the dot-plots (mean ± SEM
of three experiments) . (B) Hsa ONS-76 cells displayed significant increase in %
of S-phase cells upon overexpression of pre-miR-183, while (C) mmu C17-2
cells displayed no significant change. Bars represent mean ± SEM, *p<0.05,
**p<0.01, ***p<0.001.
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CHAPTER IV:
CONCLUSIONS AND FUTURE DIRECTIONS
Cell Specific Regulation and Transcriptome
Wide Mapping of MREs
In Chapter II, I ablated CNS expressed Dicer and significantly expanded the
evidence for a strong regulatory role of miRNAs in the developing mammalian brain.
Future directions of this work could entail a high-throughput method to improve our
understanding of miRNA regulation at the transcriptome-wide levels. For example, high
throughput sequencing of miRNAs engaged during development, using various cell lines
and tissues of interest. This would create a more refined map of miRNAs required for
development and/or differentiation than the Dicer depletion experiment, which provides
broad insight of the variability of miRNA regulation both at a spatial and temporal level.
A transcriptome wide mapping of MREs would also be useful for understanding how
disease states impact miRNA regulation. As for methods to accomplish this, I would
propose the use of a high-throughput miRNA technique, either HITS-CLIP, PAR-CLIP,
or CLASH, all of which are described in more detail below.
HITS-CLIP
High-throughput sequencing of RNA isolated by crosslinking
immunoprecipitation (HITS-CLIP) is one method for mapping MRE engaged in silencing
activity. HITS-CLIP involves immunoprecipitating cross-linked Ago bound miRNA and
mRNA target messages, both of which are captured, sequenced, and bioinformatically
analyzed to identify high confidence MREs and miRNAs. Our lab has successfully
created the first map of miRNA expression and targets in the adult human brain [58],
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whereas past HITS-CLIP assays have been done in developing mouse brain [206] and
human cells lines [206, 207, 218]. The human brain HITS-CLIP analysis done by the
Davidson lab defined more than 7000 Ago2 binding sites, of which over 75%
corresponded to predicted MREs of the top 20 most abundant brain miRNAs this analysis
also confirmed the prevalence of MREs outside of the 3’UTR, where ~60% of the Ago2
binding sites were located in 5’UTRs, introns and coding sequences [58]. One important
caveat to the HITS-CLIP technique is the inability to determine direct miRNA and
mRNA target pairing. To overcome this issue, sequences from tissue replicates can be
compared to assess bioinformatic MRE peak calling reproducibility [219].
PAR-CLIP
A second well-known high-throughput technique, known as PhotoactivatableRibonucleoside-Enhanced Crosslinking and Immunoprecipitation (PAR-CLIP), uses
photoactivatable nucleotide analogues to efficiently crosslink protein and RNA of interest
with ultraviolet A (UVA) light [207]. Importantly, the incorporated nucleotide analogues
cause a base transition at the crosslinked site, which is apparent when sequencing
samples are reverse transcribed. The computational mutation analysis of base transitions
is used to identify crosslinked sites to a single nucleotide. While this technique provides
greater specificity to MREs, the necessity of a nucleotide analog incorporation limit its
use to cultured cells [220].
CLASH
The third technique to assess RNA-RNA high-throughput interactions is by crosslinking, ligating, and sequencing of hybrids (CLASH) [205, 221]. How this method
differs from HITS-CLIP and PAR-CLIP is through a unique linker strategy that creates a
84
chimeric RNA of the miRNA and its MRE, which are then sequenced and mapped to
determine the direct relationships [205]. CLASH also utilizes UV crosslinking without
the need for a nucleoside analog and thus has the capacity to assess RNA-RNA
interactions both in vitro and in vivo [221]. The major limitation to this method is the
poor efficiency of miRNA and MRE linkering. For instance, Helwak et al. studied RNARNA interactions in mammalian cells, and found that only 2% of all sequencing
mappable reads were miRNA-MRE chimeras [205]. Thus, the value of this method is
highly dependent on the high-throughput sequencing read depth.
Interestingly, the
direct assessment of miRNA-MRE relationship by the CLASH method has found that
more than 60% of chimeric miRNA-MRE reads exhibit a noncanonical relationship, with
either bulged or mismatched binding [205]. This high proportion of noncanonical sites
differs from datasets derived from HITS-CLIP and PAR-CLIP studies [206, 207].
With these tools, the miRNA field can develop a valuable developmental timeline
resource of miRNA targets and functions, similar to the goals of the Encyclopedia of
DNA Elements (ENCODE) project, which is a consortium formed to define the
comprehensive list of functional elements from various cell lines and tissues [222]. A
miRNA resource of this extent would improve the validation rate of what are now
predicted MREs by first querying the spatial and temporal miRNA-MRE atlas. With
increasing bioinformatic analysis of functional networks, we can incorporate bona fide
MRE sites to supplement pathways and network interactions [223, 224]. These data
would also elucidate the contributions of intra-species SNPs on MREs in disease etiology
[58] and define species-specific variations that may contribute to evolutionary differences
in miR-MRE interactions, similar to our candidate validation in Chapter III of the human-
85
specific targeting of FOXO13’UTR by miR-183. Finally, as more and more miRNA
expression profiling is explored in disease pathology and individual miRNAs are teased
out as aberrantly expressed, the whole-transcriptome MRE mapping will become an
essential tool in understanding the extent miRNA regulatory network disruption.
Identification of MiRNAs that Cause Dicer Phenotypes
Our Dicer depletion project illustrates the broad implications of miRNA
regulation in the developing brain. One obvious future direction to this work is to ask
which specific miRNAs are integral to corticoneurogenesis; just one miRNA, a few, or
many working in conjunction to elegantly network brain function. Results from HITSCLIP in the human brain, indicate that greater than 55% of MRE hits are regulated by
only five total miRNAs [58]. Thus, one way to address the question of which miRNAs
are key players in corticoneurogenesis would be to utilize results gained from the
transcriptome-wide mapping of mouse neocortex MREs and their associated miRNA
expression across a developmental timeline to determine the most prominent functionally
expressed miRNAs. Experimentally, we could utilize the CRISPR system, reviewed by
Wiedenhelf et al., to delete target miRNA genes of interest and assess how only a handful
of miRNAs depleted in mice brains phenocopy our Dicer depletion model [225].
Importantly, we could also rescue the miRNAs of interest by delivering them back into
the Dicer-depleted developing mouse brain via AAV injections or standard transgenesis
and assess phenotypic rescue. A few technical caveats to these experiments that would
need to be overcome are how, where and when to delivery or express both CRISPR or the
miRNAs. For miRNAs, dosage is an important consideration as well. Too much may
cause new transcripts to be regulated and confound interpretation.
86
Evolutionary Prospective of TF MRE regulation
Future directions of transcriptome-wide mapping of MREs could also carry over
into a great understanding of our work assessed in Chapter III. We could associate
expressed transcription factors with their miRNA regulation profiles as well as determine
conserved and non-conserved MREs for an evolutionary prospective of miRNA
regulation through MRE mapping across species. A better understanding of the true in
vivo MREs will substantially corroborate our in silico analysis of human-specific TF
3’UTR MRE regulation.
Analysis of the Human-Specific FOXO1 MRE In Vivo
While the analysis of transcriptome-wide mapping is underway, analysis of our in
vitro validation of the human-specific miR-183 FOXO1 MRE with functional
implications on neuronal cell invasion and cell cycle progression should be further
explored. We believe an interesting future direction of this work would be to generate a
mouse line that contains a gain of the miR-183 site in the location analogous to the
human-specific miR-183 FOXO1 MRE. We would expect this single nucleotide change
to allow for miR-183 targeting based on our dual-luciferase results in Figure 18E and
anticipate that careful analysis of corticoneurogenesis relative to control mice would
provide distinct insights into the evolutionary implications of the human site on brain
development, especially in the context of cell cycle progress and cell migration/invasion.
Investigate Additional Gain of Human-Specific TF MREs
Functional Implications
In Chapter III, I cloned four human TF 3’UTRs into psi-check2TM plasmids and
reported a 50% validation rate of the predicted human-specific MREs. One obvious
87
future direction from this work is to assess how many other predicted human-specific TF
MREs predicted in our study are functional. Preliminary results from Chapter III defined
a potential human-specific miR-145* (also known as miR-145-3p) site on RBPJ TF
3’UTR (Figure 14A). Although little is known about the expression pattern of miR145*, literature supports RBPJ functioning as a translational repressor or activator [226]
and it is expressed in the developing neural tube and cerebellum [227]. RBPJ is found to
be an important regulator in neural stem cells of both the developing and adult
telencephalon [228], due to its role as a primary effector of Notch signaling [229], a
pathway important for neuronal differentiation [230]. Additionally, RBPJ is essential for
Gabaergic specification [227]. Our analysis identified 225 human-specific MREs for 148
miRs in 106 transcription factors. I highlight a few candidates with significant PITA
predictions scores in Table 3.
An unanswered question from Chapter III remains: What are the functional
impacts of a human-specific feedback loop? I briefly introduced in Chapter I the theory
of a TF:miRNA feedback loop, where a TF may regulate the expression of a miRNA that
may then feedback and regulate the expression of the same TF. Whether this relationship
results in a quick switch or a buffer depends on the nature of the TF regulation,
enhancing or inhibiting transcription, respectively. Specific feedback loops have been
validated in the literature many times over [9, 125, 141, 181], but only in silico evidence
has been completed to determine the propensity for evolutionary relevance [62, 191].
Our list of TFs with predicted human-specific MREs can be readily queried with publicly
available ChIP-seq data to identify full feedback loop circuits that may be further studied
with regards to their regulatory function.
88
Summary
In conclusion, my work addresses the role of miRNA regulation in both in the
developing central nervous system and their species-specific role in evolution. I
significantly extend the growing body of evidence indicating a strong regulatory role of
miRNAs in proliferation and cell cycle kinetics, as well as in neuronal and astrocyte
migration and differentiation in the developing mammalian brain. I also validate in proof
of concept studies that a human-specific single nucleotide change in an MRE of a TF
3’UTR provides differential regulation in human vs. chimpanzee and mouse, imparting
downstream functional divergence. Both studies elucidate a picture of miRNA function
in the brain, and open up many avenues for further exploration.
Table 3: Bioinformatic Predictions of Human-Specific MREs in TF 3'UTR
Human ΔΔG
Chimp
TF
miRNA
Human MRE
PITA predictions
analogous site
PAX8
miR-24
CTGAGCCA
-15.46
TTGAGCCA
RREB1
miR-205
TGAAGGA
-9.72
TGAAGAA
SP1
miR-7
GTCTTCC
-10.41
ATCTTCC
TFE3
miR-184
TCCGTCC
-12.16
TCCATCC
THRB
miR-181
GAATGTA
-11.09
GAATATA
VDR
miR-185
CTCTCCA
-13.26
CTCTGCG
VDR
miR-23
AATGTGAA
-9.22
AGTGTGAA
Rhesus
analogous site
TCAAGCCA
TGAGGGA
ATCTTCC
TCCATCC
GAATGCA
GTCTCCG
ATCGTGAA
Mouse
analogous site
CCATGCCA
TCAAGCC
ATCTTCC
CTTTTCC
GAATGTG
CTCTCTG
AGTGAGAC
89
90
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