An Ancestral miR-1304 Allele Present in Neanderthals
Regulates Genes Involved in Enamel Formation and Could
Explain Dental Differences with Modern Humans
Maria Lopez-Valenzuela,1 Oscar Ramı́rez,1 Antonio Rosas,2 Samuel Garcı́a-Vargas,2
Marco de la Rasilla,3 Carles Lalueza-Fox,1 and Yolanda Espinosa-Parrilla*,1
1
Abstract
Genetic changes in regulatory elements are likely to result in phenotypic effects that might explain population-specific as
well as species-specific traits. MicroRNAs (miRNAs) are posttranscriptional repressors involved in the control of almost
every biological process. These small noncoding RNAs are present in various phylogenetic groups, and a large number of
them remain highly conserved at the sequence level. MicroRNA-mediated regulation depends on perfect matching
between the seven nucleotides of its seed region and the target sequence usually located at the 3# untranslated region of
the regulated gene. Hence, even single changes in seed regions are predicted to be deleterious as they may affect miRNA
target specificity. In accordance to this, purifying selection has strongly acted on these regions. Comparison between the
genomes of present-day humans from various populations, Neanderthal, and other nonhuman primates showed an
miRNA, miR-1304, that carries a polymorphism on its seed region. The ancestral allele is found in Neanderthal, nonhuman
primates, at low frequency (;5%) in modern Asian populations and rarely in Africans. Using miRNA target site prediction
algorithms, we found that the derived allele increases the number of putative target genes for the derived miRNA more
than ten-fold, indicating an important functional evolution for miR-1304. Analysis of the predicted targets for derived miR1304 indicates an association with behavior and nervous system development and function. Two of the predicted target
genes for the ancestral miR-1304 allele are important genes for teeth formation, enamelin, and amelotin. MicroRNA
overexpression experiments using a luciferase-based assay showed that the ancestral version of miR-1304 reduces the
enamelin- and amelotin-associated reporter gene expression by 50%, whereas the derived miR-1304 does not have any
effect. Deletion of the corresponding target sites for miR-1304 in these dental genes avoided their repression, which further
supports their regulation by the ancestral miR-1304. Morphological studies described several differences in the dentition of
Neanderthals and present-day humans like slower dentition timing and thicker enamel for present-day humans. The
observed miR-1304-mediated regulation of enamelin and amelotin could at least partially underlie these differences
between the two Homo species as well as other still-unraveled phenotypic differences among modern human populations.
Key words: Neanderthal, gene regulation, miR-SNP, microRNA, miR-1304, tooth development.
Introduction
Investigating the genetic differences associated with phenotypic diversity among hominins is a crucial step toward
the understanding of human adaptation and evolution.
Genetic and genomic alterations in regulatory regions
are a significant source of phenotypic diversity underlying
important interindividual and interspecies differences
(Carroll 2008; Hindorff et al. 2009). This record has been
recently confirmed in primates by the discovery that the
human loss of specific regulatory DNA, in particular the
loss of noncoding RNA with enhancer function, associates
with the appearance of specific human traits such as the
expansion of specific brain regions (McLean et al. 2011).
Increasing evidence supports that allelic changes involving
either microRNAs (miRNAs) or their regulatory machinery
are major contributors to phenotypic diversity in human
populations and may thus be important sources of phenotypic variation and have a role in the pathophysiology of
several disorders (Borel and Antonarakis 2008).
miRNAs are small noncoding RNAs of 19–25 nucleotides
in length in their mature form, processed from a longer
hairpin structure, that act as posttranscriptional regulators
of gene expression by either mRNA degradation or translational repression (Krol et al. 2010). It is estimated that
miRNAs regulate more than 30% of all protein-coding
genes, building complex regulatory networks that control
almost every cellular process (Filipowicz et al. 2008).
MicroRNAs act by means of partial complementarity to
© The Author 2012. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please
e-mail: [email protected]
Mol. Biol. Evol. 29(7):1797–1806. 2012 doi:10.1093/molbev/mss023 Advance Access publication January 27, 2012
1797
Research article
Institut de Biologia Evolutiva, Universitat Pompeu Fabra—Consejo Superior de Investigaciones Cientı́ficas, Barcelona, Catalonia,
Spain
2
Paleoanthropology Group, Department of Paleobiology, Museo Nacional de Ciencias Naturales, Consejo Superior de
Investigaciones Cientı́ficas, Madrid, Spain
3
Área de Prehistoria, Departamento de Historia, Universidad de Oviedo, Oviedo, Spain
*Corresponding author: E-mail: [email protected].
Associate editor: Anne Stone
MBE
Lopez-Valenzuela et al. · doi:10.1093/molbev/mss023
miRNA binding sites usually located in the 3# untranslated
regions (UTRs) of their target genes (Bartel 2004). Perfect
complementarity between the target sequence of the regulated messenger RNA and the so-called ‘‘seed’’ region—
nucleotides 2 through 7 or 8 from the 5# end of the mature
miRNA—is thought to determine successful binding and, together with the stability of the RNA hybrids, are the basis of
many miRNA target site prediction algorithms (Brennecke
et al. 2005; Lewis et al. 2005). Strong purifying selection acts
on the mature miRNA and particularly on nucleotides corresponding to the seed region, where no mutation is tolerated as it would most likely produce a change in the target
spectrum that could give rise to the emergence of a novel
miRNA (Chen and Rajewsky 2006; Liu et al. 2008; Quach
et al. 2009). Conservation of miRNAs through evolution is
well documented and has been used for the discovery of homologous miRNAs across different phylogenetic groups. It is
assumed that conserved miRNA may have high functional
relevance and hence many previous research efforts focused
on finding and characterizing those miRNAs (Grad et al.
2003; Berezikov et al. 2005; Chen and Rajewsky 2006). Nonetheless, the identification of species-specific miRNAs may
help to understand evolutionary novelties among different
phylogenetic groups. Several studies reach the conclusion
that miRNAs are strongly conserved among primates, but
still there is a set of miRNAs that are found only in
present-day humans and thus are good candidates to contribute to human-specific phenotypes (Bentwich et al. 2005;
Berezikov et al. 2005; Liu et al. 2008; Brameier 2010; Lin et al.
2010). The first published draft of the Neanderthal genome
revealed that present-day humans differ from Neanderthals
by a nucleotide substitution in the seed region of microRNA
miR-1304 (Green et al. 2010) that therefore it is likely to
change the spectrum of target genes for miR-1304.
Neanderthals are the closest known evolutionary relatives
of modern humans. They inhabited parts of Europe and
Western Asia during a succession of climatic cycles, exhibiting both behavioral and morphological adaptations probably
related to cold climates, until their extinction around 30,000
years ago (Mellars 2004; Finlayson et al. 2006). The morphological features that distinguish Neanderthals from other humans, including specific craniofacial and dental traits, first
appear in the European fossil record around 4,00,000 years
ago (Stringer and Hublin 1999; Hublin 2009). Estimated from
genomic data, these Homo populations diverged between
440,000 and 270,000 years ago (Endicott et al. 2010; Green
et al. 2010). The analysis of the Neanderthal genome has revealed that about 80 protein-coding genes show fixed amino
acid changes between Neanderthals and modern humans
(Green et al. 2010). Phenotypes evolve by functional differences in proteins but also do largely through mutations in
regulatory regions (Carroll 2008); thus, it seems clear that
genetic differences related to the distinctive Neanderthal
phenotype should not be restricted to a set of proteincoding genes and that the analysis shall be broadened to
incorporate gene regulation as well.
Here, we analyze the primate-specific miR-1304 by
studying genetic variation of the human miR-1304 ‘‘locus’’
1798
and the spectrum of target genes predicted for the derived
and ancestral versions of this miRNA. By means of functional studies, we show repression of a cluster of dental
genes by the ancestral version of miR-1304 illustrating
how a single nucleotide change in a regulatory element
may underlie particular phenotypic differences.
Materials and Methods
Sequencing of Chimpanzee miR-1304 and
Neanderthal AMTN 3# UTR
miR-1304 was polymerase chain reaction (PCR)-amplified
from genomic DNA of three chimpanzee individuals using
primers listed in supplementary table 1 (Supplementary
Material online). Eight clones per individual were sequenced
using standard procedures.
The target site for miR-1304 on the 3# UTR of the Neanderthal AMTN was PCR-amplified in a Neanderthal specimen (SD-1253) from El Sidrón site (Asturias, Spain), and 55
clones were sequenced (supplementary fig. 1, Supplementary Material online) following a previously described
methodology (Lalueza-Fox et al. 2007) using specific primers (supplementary table 1, Supplementary Material online). This bone sample has been used to retrieve ;14,000
protein-coding positions (Krause et al. 2007; Lalueza-Fox
et al. 2008, 2009; Burbano et al. 2010), as well as 0.1% of
the nuclear genome (Green et al. 2010), and the complete
mitochondrial genome (Briggs et al. 2009). The degree of
contamination has been estimated to be 0.27–0.29% for
the mitochondrial DNA and 2% upper bound for autosomal DNA capture (Krause et al. 2007; Lalueza-Fox et al.
2008); these low figures render this specimen one of the
most suitable Neanderthal samples for targeted paleogenetic analysis.
Firefly Luciferase Constructs and Mutagenesis
The 3# UTRs of ENAM, AMTN, and GAD1 were PCR-amplified
from genomic DNA with Platinum Taq DNA polymerase
(Invitrogen, Carlsbad, CA), using primers containing an XbaI
restriction site at the 5# end (supplementary table 1, Supplementary Material online). PCR fragments were later purified,
XbaI-digested, and cloned into pGL4.13 vector (Promega,
Madison, WI) downstream of the firefly luciferase reporter
gene. Mutant reporter plasmids were generated as previously
described (Muiños-Gimeno et al. 2009) with the QuikChange
site-directed mutagenesis kit (Stratagene, La Jolla, CA), using
either the AMTN or the ENAM pGL4.13 construct as
a template and primers carrying the desired deletions
(supplementary table 1, Supplementary Material online).
Cell Culture and Transfection
HeLa cells were maintained in Dulbecco’s modified Eagle’s
medium supplemented with 10% fetal bovine serum, 100
units/ml penicillin, and 100 lg/ml Streptomycin (GIBCO;
Invitrogen). Cotransfection optimization has been previously described (Guidi et al. 2010). Briefly, HeLa cells were
seeded at 1.3 104 cells per well in 96-well plates and cotransfected 24 h later with the Firefly reporter constructs
An Ancestral miR-1304 Allele Regulates Dental Genes · doi:10.1093/molbev/mss023
MBE
FIG. 1. Genomic sequence conservation of miR-1304 among primates. First row of the figure shows the RNA sequence of mature reference
human miR-1304. The seed region and the nucleotide change in it are highlighted in gray on the genomic DNA alignment. hsa, Homo sapiens;
nea, Homo neanderthalensis; ptr, Pan troglodytes; ggo, Gorilla gorilla; ppy, Papio pygmaeus; mmu, Macaca mulatta.
described above or the empty pGL4.13 vector (24 ng), the
Renilla reporter plasmid pGL4.75 (3 ng), and 10 nM miRNA
mimic for derived miR-1304, ancestral miR-1304, and negative controls #2 and #4 (miRIDIAN; Dharmacon, Lafayette,
CO) using Lipofectamine 2000 (Invitrogen).
Luciferase Activity Assay
The activity of Firefly and Renilla luciferases was determined 24 h after transfection using the Dual-Glo Luciferase
Assay System (Promega). Relative reporter activity was obtained by normalization to the Renilla luciferase activity. In
order to correct for vector-dependent unspecific effects,
each relative reporter activity was normalized to the empty
vector cotransfected with the corresponding miRNA
(Guidi et al. 2010). Results were then compared with
the mean of the two negative controls. Each experiment
was done in triplicate, and at least three independent experiments were performed for each miRNA. Statistical significance was determined using Student’s t-test (P , 0.05).
Bonferroni correction for multiple comparisons was applied taking into account the analysis of two independent
reporter genes and two miRNA mimics. Using these criteria, the corrected level of significance was set up equal to
0.0125 (four comparisons).
Computational Methods
Targets were predicted using the web-based prediction
methods TargetScan (www.targetscan.org, release 5.1, Friedman et al. 2009) and TargetRank (www.hollywood.mit.edu/
targetrank, Nielsen et al. 2007) on the human genome assembly (NCBI36/hg18, March 2006). Genomic coordinates
are according to the following assemblies: Homo sapiens
GRCh37/hg19, Pan troglodytes CHIMP2, Gorilla gorilla gorGor3, Pongo pygmaeus PPYG2, Macaca mulatta MMUL_1.
Sequences, unless sequenced by ourselves, were obtained
from the University of California Santa Cruz (UCSC) Genome Browser (http://www.genome.ucsc.edu) and Ensembl
Genome Browser release 61 (www.ensembl.org). Pathway
analysis was performed with the Ingenuity Pathway Analysis
software (IPA) version 6.3 (www.ingenuity.com). Human genetic variation on miR-1304 was assessed using genotypes
for 1,094 individuals in the June 2011 data release of the
1000 Genomes Project (www.1000genomes.org). Exploration
for natural selection signatures in the human genome was
performed by the analysis of data from HapMap, using the
UCSC browser, and from the 53 populations of the Human
Genome Diversity Panel (HGDP), using the HGDP selection
browser (http://hgdp.uchicago.edu/) (Pickrell et al. 2009).
Results
Conservation of miR-1304 among Primates
As noted by Green et al. (2010), the Neanderthal draft
genome sequence differs from the reference genome of
present-day humans in one base in the seed region of
the primate-specific miRNA miR-1304 (fig. 1). The corresponding genomic sequence for Neanderthals is GCCTCGA
and GCCTCAA for the reference human sequence. We took
advantage of the recently completed genome sequencing of
four primates—M. mulatta, P. troglodytes, G. gorilla, and P.
pygmaeus—to compare primate sequences orthologous
with human miR-1304 (fig. 1). The sequence alignment confirmed that the reference human genome bear the derived
state at this nucleotide position, whereas Neanderthal and
other nonhuman primates share the ancestral state. The
rest of the hairpin sequence was identical between the Neanderthals and the reference human genome and showed
few changes in the other four primates. In the case of chimpanzee, the published shotgun assembly (March 2006
Pan_troglodytes-2.1 6x) showed a deletion of 26 nucleotides
together with an insertion that set apart the two resting
parts of the miRNA. To verify the possibility that chimpanzee had lost this miRNA, we sequenced three chimpanzees’
DNAs and, after analysis of eight clones per individual, identified a consensus sequence identical to the gorilla miR-1304
sequence that differs in only one nucleotide position from
the ancestral miR-1304 (fig. 1) indicating that chimpanzees
likely also have a functional copy of miR-1304.
Analysis of the Genetic Variation of miR-1304 in
Human Populations
We checked for genetic variation at the miR-1304 locus
among human populations using the single nucleotide
polymorphism (SNP) database. We found one SNP,
rs79759099, at this particular position in the seed region
indicating that this change is not fixed in human populations. Using the new release of the 1000 Genomes Project
(June 2011 data release) with 1,094 individuals representing
14 populations worldwide, we found that although all the
individuals in the European (GBR, FIN, IBS, CEU, and TSI),
Colombian (CLM), Mexican (MXL), and Kenyan (LWK)
populations only presented the derived allele, the ancestral
allele of miR-1304 was present as the minor allele in the
Asian Japanese (JPT, MAF 5 0.067) and Chinese (CHB,
MAF 5 0.072; CHS, MAF 5 0.05) populations and, at very
low frequency, in the Yoruban (YRI, MAF 5 0.028); Puerto
Rican (PUR, MAF 5 0.009), and African-American (ASW,
1799
MBE
Lopez-Valenzuela et al. · doi:10.1093/molbev/mss023
Table 1. Target Gene Prediction for the Ancestral Version of miR-1304 by TargetRank.
Conserved Seed Matches
M8
Gene
PTGFRN
DEK
AMTN
CD24
PIK3AP1
C1orf85
CAMKK2
KATNAL1
MGC13017
FOXH1
DLST
ENAM
RIC8A
C1orf21
TNNI1
RBPMS2
IGFBP3
TCF4a
FIZ1
CABP7
CLCF1
GRAP
KLF15
LRRN2
PI4K2A
SLAMF8
TNIP2
ATP1B3
L3MBTL3
SOX17
TMED4
DAPL1
EDF1a
FAM90A1
TADA3L
Target Gene
Prostaglandin F2 receptor negative regulator
DEK oncogene
Amelotin
CD24 antigen precursor
Phosphoinositide-3-kinase adaptor protein 1
Kidney predominant protein NCU-G1
Calcium/calmodulin-dependent protein kinase
Katanin p60 subunit A-like 1
Hypothetical protein LOC91368
Forkhead box H1
Dihydrolipoamide S-succinyltransferase
Enamelin
Resistance to inhibitors of cholinesterase 8
Chromosome 1 open reading frame 21
Troponin I
RNA-binding protein with multiple splicing 2
Insulin-like growth factor binding protein 3
Transcription factor 4
FLT3-interacting zinc finger 1
Calcium-binding protein 7
Cardiotrophin-like cytokine factor 1
GRB2-related adaptor protein
Kruppel-like factor 15
Leucine-rich repeat neuronal 2
Phosphatidylinositol 4-kinase type 2 alpha
SLAM family member 8
A20-binding inhibitor of NF-kappaB activation 2
Na1/K1 ATPase beta 3 subunit
Lethal (3) malignant brain tumor-like protein 3
SRY-box 17
Transmembrane emp24 protein transport domain
Death-associated protein-like 1
Endothelial differentiation-related factor 1
Hypothetical protein LOC55138
Transcriptional adaptor 3-like
Nonconserved Seed
Matches
A1
M8
A1
Conserved
Score Total 8mer 7mer 7mer 6mer 8mer 7mer 7mer 6mer in Primates
0.337
0.309
0.302
0.281
0.281
0.263
0.261
0.259
0.259
0.257
0.253
0.253
0.253
0.251
0.240
0.237
0.237
0.237
0.236
0.210
0.210
0.210
0.210
0.210
0.210
0.210
0.210
0.209
0.209
0.209
0.209
0.203
0.203
0.203
0.203
1
1
1
1
1
2
2
1
1
1
1
1
1
2
3
2
1
1
2
1
1
1
1
1
1
1
1
1
1
2
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
0
0
0
0
1
1
1
1
1
1
1
1
0
0
0
0
1
0
1
1
0
0
0
0
0
1
1
0
0
0
0
0
0
1
0
0
1
1
1
0
0
0
0
0
0
0
0
1
1
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1
0
0
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
H,
H,
H,
H,
H,
H,
H,
H,
H,
H,
nr
H,
H,
H,
H,
nr
H,
H,
H,
H,
H,
H,
H,
H,
H,
H,
H,
H,
H,
nr
H,
H,
H,
H,
H,
N,
N,
N,
N
N,
N,
N,
N,
N,
N,
C
C
C
C
C
C
C
C
C
N,
N,
N,
N,
C
C
C
C
N,
N,
N,
N,
N,
N,
N,
N,
N,
N,
N,
N,
N,
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N, C
N, C
N, C
N
NOTE.—Underlined are the two genes involved in teeth formation. A1 indicates presence of an adenosine opposite to miRNA base 1; M8 indicates a Watson–Crick match to
miRNA base 8. Conserved in Primates indicates conservation of the binding target site among different primate species: H, human; N, Neanderthal; C, chimpanzee; nr, no
Neanderthal reads available.
a
Target gene prediction common to TargetScan and TargetRank.
MAF 5 0.008) populations (supplementary table 2, Supplementary Material online). Furthermore, since this different
allelic distribution could be the result of selective sweeps
within recent human populations, we looked for signatures
of selection for the derived miR-1304 by the study and
comparison of linkage disequilibrium (integrated haplotype score), population differentiation (Fst), and the frequency of rare variants (Tajima’s D) along the genomic
region using public data from HapMap and HGDP. However, neither a significant excess of rare variants nor significant population differentiation indexes compatibles with
a selective sweep were found in the region.
Analysis of Target Gene Predictions for miR-1304
To assess the variation in the target gene spectrum for the
ancestral and derived miR-1304, we used different prediction
algorithms based on seed sequence matching, namely TargetScan and TargetRank. For the ancestral miR-1304, TargetRank predicted 35 target genes and TargetScan predicted
1800
only four genes (LCORL, RIMBP2, EDF1, and TCF4, the last
two being common to both prediction programs, table 1).
A limitation of these predictions is that they were performed
on the modern human genome, thus we checked if predicted
target genes had identical binding sites for the ancestral miR1304 in the chimpanzee and Neanderthal genomes. Among
the 37 different predicted target genes for this variant, there
were 29 genes with an identical binding site in chimpanzee,
which we considered a valid proxy for conservation in Neanderthals as well. As for the other eight genes, the Neanderthal
genome assembly indicated that in four cases (CD24, TMED4,
TAD3L, and RIMBP2), the target site is identical between the
two hominins, whereas for the other four genes (DLST,
RBPMS2, LCORL, and SOX17) complete Neanderthal reads
were not available (table 1). Interestingly, for the derived version of miR-1304, we found a large increase in the putative
targets in comparison with the ancestral version. TargetRank
predictions generated a list of 515 target genes, whereas TargetScan generated 140, with an intersection of 79
MBE
An Ancestral miR-1304 Allele Regulates Dental Genes · doi:10.1093/molbev/mss023
Table 2. Top Associations of the Predicted Target Genes for the Derived Version of miR-1304 with Biological Processes.
Top Networks
Score
Cell morphology, cellular function and maintenance, cellular movement
Neurological disease, behavior, genetic disorder
Lipid metabolism, molecular transport, small molecule biochemistry
Cell cycle, cellular development, cellular growth and proliferation
Auditory disease, genetic disorder, neurological disease
51
51
30
5
5
Diseases and Disorders
P value
Genetic disorder
Neurological disease
Cancer
Infection mechanism
Cardiovascular disease
5.93
5.93
1.27
2.12
4.49
3
3
3
3
3
Molecular and Cellular Functions
P value
Cellular assembly and organization
Cell compromise
Cellular growth and proliferation
Cellular development
Gene expression
3.21
3.89
1.13
2.00
2.12
Physiological System Development and Function
P value
Nervous system development and function
Tissue morphology
Tumor morphology
Connective tissue development and function
Behavior
5.45
5.45
1.13
3.48
4.49
3
3
3
3
3
3
3
3
3
3
Molecules
10205
10205
10203
10203
10203
to
to
to
to
to
4.04
4.04
3.10
1.81
4.40
3
3
3
3
3
10202
10202
10202
10202
10202
10204
10204
10203
10203
10203
to
to
to
to
to
4.40
3.10
4.83
4.68
4.83
3
3
3
3
3
10202
10202
10202
10202
10202
3
3
3
3
3
202
24
14
5
6
4
Molecules
16
6
11
9
19
Molecules
204
10
10204
10203
10203
10203
to
to
to
to
to
4.40
4.83
3.97
4.83
4.49
10
10202
10202
10202
10203
13
8
5
8
1
NOTE.—The five most significant associations with molecular networks and with different categories of biological functions are shown (IPA software).
(supplementary table 3, Supplementary Material online).
Next, we analyzed the association of these 79 potential target
genes for the derived miR-1304 with biological processes using the IPA software. The program was interrogated for enrichment in biological functions and molecular networks, and
the statistical significance of the associations was calculated
with the right-tailed Fisher’s exact test. As shown in table 2
and supplementary fig. 2 (Supplementary Material online),
some of the most relevant associations for the derived
miR-1304 target genes were found with genetic disorders
(24 genes) and neurological diseases (14 genes) as well as nervous system development and function (13 genes). As far as
top networks, the highest significance was found in one related to neurological disease and behavior and another one
regarding cellular function and maintenance (supplementary
fig. 2, Supplementary Material online). Despite the small number of predicted target genes, we observed that 2 of the 35
genes predicted to be regulated by the ancestral version of
miR-1304 by TargetRank—ENAM and AMTN that code for
the proteins enamelin and amelotin, respectively—are involved in teeth formation. The finding of two genes both involved in a process of such high specificity as odontogenesis
within a relatively small set of putative targets was interesting,
particularly given that the best-described differences between
Neanderthals and modern humans are related to cranial and
dental traits. Thus, among the predicted target genes, we focused on the study of the ENAM and AMTN genes.
Analysis of the 3# UTR of the ENAM and AMTN
Genes in Neanderthal
Because the human genome was used as a reference for
predicting the role of the ancestral variant of miR-1304
in the regulation of ENAM and AMTN, it is necessary that
Neanderthals match humans in the target site sequences
for these genes. In the case of the ENAM Neanderthal gene,
the sequence corresponding to the target site for this
miRNA is identical to the modern human sequence, and
the 3# UTR exhibits only two changes in its vicinity
(fig. 2A). The first is a C to G substitution corresponding
to a common SNP also present in modern humans
(rs7664896) located 7 bp from the seed region binding site.
The second is a G to A nucleotide change, which is among
the most common forms of postmortem DNA damage and
may be considered an artifact induced by cytosine deamination occurring in the complementary strand (Hofreiter
et al. 2001; Briggs et al. 2007). Neither of these changes
is predicted to interfere with the correct binding of the
miRNA. In the case of the AMTN gene, the sole available
read from Vindija Neanderthal ends up at the beginning of
the target sequence for miR-1304 and displays two G to A
nucleotide changes that, as stated before, could be an artifact due to postmortem DNA damage (fig. 2A). To ascertain if the extinct Homo had a complete binding site for the
ancestral miR-1304 at AMTN 3# UTR, we sequenced part of
this region in a Neanderthal specimen (SD-1253) from El
Sidrón site (Asturias, Spain) dated to about 49,000 years
ago and extracted under controlled conditions (Rosas
et al. 2006; Lalueza-Fox et al. 2011). The analysis of 55 clones
showed that the recognition site for miR-1304 in the AMTN
gene is identical in both hominin groups (supplementary
fig. 1, Supplementary Material online). The 3# UTRs of
ENAM and AMTN are also highly conserved among other
primates studied (chimpanzee, gorilla, orangutan, and rhesus monkey), and all but the rhesus monkey carries the
1801
Lopez-Valenzuela et al. · doi:10.1093/molbev/mss023
MBE
A
B
FIG. 2. Genomic sequence conservation of ENAM and AMTN 3# UTRs among primates. (A) 3# UTR of the ENAM and AMTN genes, the target
sequence that binds the seed region of miR-1304 is highlighted in gray. hsa, Homo sapiens; nea, Homo neanderthalensis; ptr, Pan troglodytes;
ggo, Gorilla gorilla; ppy, Papio pygmaeus; mmu, Macaca mulatta. (B) Sequence alignments for the ancestral miR-1304 (Anc. miR-1304) showing
the predicted binding with the 3# UTRs of the Neanderthal ENAM and AMTN mRNAs.
exact matching sequence for the ancestral miR-1304 seed
region (fig. 2). Accordingly, the seed region of this version of
miR-1304 presents perfect complementarity with its predicted target site region at the 3# UTR of ENAM and AMTN
(fig. 2B) and might be regulating both dental genes in
Neanderthal as well as in other nonhuman primates and
humans carrying the ancestral allele of miR-1304.
Functional Screening of miR-1304 Target Sites in
ENAM and AMTN
To investigate the interaction between ENAM and AMTN
mRNAs and the different versions of miR-1304, functional
validation of the predicted ancestral miR-1304 target site
was performed using a dual-luciferase assay in HeLa cells.
A luciferase reporter pGL4.13 construct carrying the 3#
UTR of either the ENAM or the AMTN genes was cotransfected with the corresponding miRNA mimic: ancestral
miR-1304, derived miR-1304, or two different control
miRNAs. As shown in figure 3A, a statistically significant
reduction of the luciferase activity was observed for ENAM
and AMTN when cotransfected with the ancestral
miR-1304 as compared with the modern miR-1304 (P ,
0.0125, Bonferroni corrected Student’s t-test). In the case
of the ENAM construct, the associated luciferase activity
descended to 51% and for the AMTN construct to 39%
when cotransfected with the ancestral miR-1304, which
is compatible with a strong repression of the ENAM and
AMTN genes by this regulator. Finally, in order to demonstrate the specificity of the binding of the ancestral
miR-1304 to the ENAM and AMTN 3# UTRs, we used
site-directed mutagenesis to delete the corresponding target sequences that bind the seed region of the ancestral
1802
miR-1304 in the ENAM and AMTN pGL4.13 constructs
and cotransfected the plasmids with the respective
miRNAs. A statistically significant recovery of the luciferase
activity was observed when the ancestral miR-1304 was cotransfected with the deleted ENAM and AMTN plasmids in
comparison with the wild-type constructs, reaching levels
of recovery of about 100% (fig. 3B). The observed rescue of
the quantitative phenotype further supports the predicted
repression of these two dental genes by this version of
miR-1304.
Analysis of the Genetic Variation of ENAM and
AMTN in Human Populations
To further characterize the gene-miRNA interaction, we
analyzed genetic variation on the ENAM and AMTN
miR-1304 target site sequences in present-day populations
using the 1000 Genomes Project data. Although we did not
find genetic variation in the target site of AMTN, the
ENAM target site harbors the SNP rs117342040 (G/A with
A being the minor allele). Interestingly, the affected nucleotide in the target site of ENAM is located exactly matching
the described change in the miR-1304 seed region in such
a way that the minor allele of rs117342040 would interfere
with the proper binding of the ancestral allele of miR-1304.
Moreover, the allele frequencies for this SNP are differentially distributed among human populations being absent
in European populations, very rare in Africans (one carrier
of African origin from Kenya), and present in about 2.5% of
Asian individuals (supplementary table 2, Supplementary
Material online). As this variant is found in populations
where the ancestral version of miR-1304 is also detected,
we studied if they were correlated using a hypergeometric
An Ancestral miR-1304 Allele Regulates Dental Genes · doi:10.1093/molbev/mss023
A
B
FIG. 3. The ancestral version of miR-1304 targets ENAM and AMTN
3# UTRs. Results of the luciferase reporter assay used to test the
interaction between ancestral (Anc.) and derived (Der.) miR-1304
with the ENAM and AMTN genes. (A) HeLa cells were cotransfected
with the miRNA mimic of interest, the Renilla reporter plasmid
pGL4.75, and either the empty pGL4.13 plasmid or pGL14.3 carrying
the 3# UTR of GAD1, ENAM, or AMTN followed by the firefly
luciferase reporter gene. The previously proven regulation of GAD1
by miR-7 was used as a positive control. The ratios of Firefly to
Renilla luciferase luminescence are presented after normalization to
the empty pGL4.13 and to the mean of two different mimic
controls. (B) The binding site for the ancestral miR-1304 was
removed from the 3# UTRs in the constructs by mutagenesis, and
the luciferase assay was repeated. Each experiment was done in
triplicate, and at least three independent experiments were
performed. Data reported here are the means ± standard deviation
of independent experiments. Significant associations after Bonferroni correction (P , 0.0125, corrected Student’s t-test) are indicated
with an asterisk. Anc. miR-1304, ancestral miR-1304 mimic.
test and observed that, for the total of 1,094 individuals
analyzed, our finding of 3 individuals having both minor
alleles was significant (P 5 0.0162) meaning that there
are more carriers of both minor ENAM and miR-1304 alleles
than expected by chance.
Discussion
The main basis of miRNA action is its sequence complementarity with the target regions of the genes that they
regulate. Functional SNPs that create or disrupt these
miRNA target sites have been shown to have diverse
MBE
phenotypic implications contributing sometimes to human disease susceptibility (Borel and Antonarakis 2008).
Since one miRNA can have multiple targets, SNPs located
on the miRNA regions important for target recognition
would be expected to exhibit a broader biological effect
than SNPs on the target sequences. So far, very few functional variants in miRNA genes have been described, and
only a small number of studies have been devoted to describe their functional consequences (Jazdzewski et al. 2008;
Sun et al. 2009; Vinci et al. 2011).
Analysis of the Neanderthal genome sequence led to the
detection of a miRNA, miR-1304, that differs from the reference human miR-1304 sequence at one nucleotide position in the seed region (Green et al. 2010). Interestingly,
analysis of 1000 Genomes Project data revealed that this
nucleotide change is not fixed in present-day human populations, and it turned out to be an SNP (rs79759099) present in Asian populations (allele frequency of about 0.06). In
European and East-African populations, the ancestral allele
was not found, and populations with West-African origin
carry the ancestral allele but at very low frequencies. Since
this distribution schema could be the result of selective
sweeps within recent human populations compatible with
a beneficial role for the new derived miR-1304 allele, we
looked for signatures of selection along the region using
HapMap and HGDP data, but no evidences for a selective
sweep, such as an excess rare allele variants or a block of
extensive linkage disequilibrium, could be found. Other explanation for the presence of the ancestral allele in Asian
populations could be that it was reintroduced through admixture with Neanderthals; however, because Neanderthal
admixture is restricted to non-African populations (Green
et al. 2010) and given the presence of the ancestral miR1304 in some Africans and its low frequency in Asia, the
distribution of the ancestral miR-1304 could not solely
be explained in terms of introgression. Furthermore,
miR-1304 is not included into the 13 regions that have been
identified as candidate gene flow regions between Neanderthals and modern humans that were described through
the analysis on extended Neanderthal haplotype blocks in
modern human genomes (Green et al. 2010). In this scenario, a combination of admixture in Asia such as the described by Skoglund (Skoglund and Jakobsson 2011) with
rs79759099 being a retained ancient polymorphism in Africa could be the most plausible explanation.
miR-1304 is a relatively novel primate-specific miRNA
that was recently discovered at very low levels in human
embryonic stem cells and after differentiation of these cells
into embryonic bodies (Morin et al. 2008). Since then deep
RNA sequencing studies have found miR-1304, also lowly
expressed, in diverse tissues such as peripheral blood, brain
cortex, and melanoma (Martı́ et al. 2010; Stark et al. 2010;
Vaz et al. 2010), but its targets and function remain largely
unknown. The in silico approach based on target site predictions performed in this work allowed us to gain insights
into the putative functional differences between the two
versions of miR-1304. One of the main restrictions to find
target genes for the ancestral miR-1304 was the dearth of
1803
Lopez-Valenzuela et al. · doi:10.1093/molbev/mss023
good quality Neanderthal sequence data. The use of the
modern humans genome for target gene predictions
may have lead us to disregard Neanderthal target genes
that diverged from human genes in their 3# UTRs; nevertheless, we did not find false positive as all target genes for
the ancestral miR-1304 that could be tested (33 of 37, 89%)
have an identical and conserved binding site in the
Neanderthal and human genomes.
Remarkably, we observed a significant difference in the
number of predicted target genes between both miRNAs:
the derived version of miR-1304 has more than 14 times
more predicted targets than the ancestral one, which is
indicative of a critical functional evolution for miR-1304.
Interestingly, the analysis performed using the Ingenuity
software associated the predicted targets of derived
miR-1304 with biological processes and disorders related
to central nervous system development and function,
which suggests that the evolutionary change of miR1304 may affect aspects of human brain functioning and
cognition. Previous work showed that SNP variants in
the vicinity of miR-22, miR-148a, and miR-488 associate
with panic disorder and that these miRNAs effectively repress candidate genes for anxiety (Muiños-Gimeno et al.
2011). In this context, involvement of miR-1304 in brain
function regulation raises the interesting possibility of particular neurological phenotypes being associated with one
miR-1304 allele or the other. On the other hand, comparison of the Neanderthal genome and modern humans’ genomes identified a number of genomic regions that may
have been affected by positive selection in ancestral modern humans, including regions involved in cognitive abilities like NRG3, a gene involved in schizophrenia (Green
et al. 2010). Taken together these data suggest that human
cognition has been an important target of recent human
evolution that could have been shaped in part by miRNAs.
Among the few predicted target genes for the ancestral
miR-1304, CD24 and the transcription factor 4 (TCF4) are of
interest for their involvement in neurological disorders in
humans. CD24 has been associated with multiple sclerosis
(Zhou et al. 2003), and TCF4 (predicted by TargetRank and
TargetScan) has been recently associated with a range of
neuropsychiatric phenotypes including schizophrenia, impaired verbal learning, and Pitt–Hopkins syndrome (Amiel
et al. 2007; Stefansson et al. 2009; Lennertz et al. 2011). Two
other noteworthy target genes are ENAM and AMTN, both
involved in odontogenesis. We focused on these genes due
to the known dental differences between Neanderthals and
modern humans and demonstrated the conservation of
their 3# UTRs among primates as well as their differential
response after transfection with either the derived or the
ancestral miR-1304. These two genes are involved in teeth
formation and map near each other in an interesting cluster on chromosome 4 together with other genes also involved in dental formation as well as salivary proteins
such as ameloblastin (AMBN) or mucin 7 (MUC7).
Tooth enamel, the hardest substance in vertebrates, is
formed by epithelium-derived ameloblasts. As ameloblasts
differentiate, they deposit specific proteins necessary for
1804
MBE
enamel formation, including amelogenin, ameloblastin,
and enamelin, in the organic enamel matrix. Enamelin is
the largest protein in the enamel matrix of developing
teeth. It is involved in the mineralization and structural organization of enamel. Amelotin was discovered in mouse,
where it is specifically expressed in maturation-stage ameloblasts. It has been hypothesized that it functions as a protease helping the processing of the enamel matrix at this
stage (Iwasaki et al. 2005). We can only speculate about the
function of the ancestral miR-1304 in Neanderthals but,
given the involvement of ENAM and AMTN in odontogenesis, their observed repression by the ancestral miR-1304
could implicate this miRNA, acting together with other divergent genes, in a range of differences related to Neanderthal and modern humans dentition (Macchiarelli et al.
2006; Olejniczak et al. 2008). For example, the union surface
between dentine and enamel was more complex in Neanderthals than it is in Homo sapiens. Additionally, the volume of coronal dentine was larger in the extinct Homo and,
since enamel volume is similar in both species, this results
in significantly thinner cuspal enamel in Neanderthals
(Ramirez Rozzi and Bermudez De Castro 2004; Olejniczak
et al. 2008). Moreover, it is believed that enamel cusps
formed faster in Neanderthals as evidenced by a significantly lower periodicity of their enamel growth marks (Retzius marks or perikymata) (Aiello and Dean 1990), a fact
that has often lead to overestimation of Neanderthal’s age
at death (Olejniczak et al. 2008; Smith et al. 2009, 2010).
This would imply a different rate of ameloblastic activity,
a process that may be influenced by miR-1304. This hypothesis is in agreement with recent studies performed
in rodents that denote that miRNAs have a prominent role
in teeth development being required for normal ameloblast
differentiation and enamel matrix formation (Cao et al.
2010; Michon et al. 2010). Since the ancestral allele of
miR-1304 still segregates in some modern humans, this
miR-1304 variant could be involved in dental development
and be associated, for example, with the degree of enamel
thickness. Although little is known about variations of dental morphology among human populations, it has been reported that average enamel thickness is similar among
Asian, European, and African dentitions (Feeney et al.
2010). Nevertheless, given the fact that only about 0.5%
of Asian individuals would be homozygous for the ancestral
miR-1304, we do not expect this allele to be involved in
phenotypic traits that differ among populations but rather
in less common traits somehow related with disease. In this
regard, defects in enamel formation create the condition
known as amelogenesis imperfecta (AI), a disease in which
the enamel does not fully form or forms in insufficient
amounts and teeth affected may be discolored, sensitive,
or prone to disintegration. AI is commonly inherited as
an autosomic trait, and ENAM mutations appear to be responsible for a big part of the autosomally inherited cases.
However, genetic studies provide evidence for the existence
of at least one further autosomal AI locus (Kärrman et al.
1997; Dong et al. 2000). The ancestral miR-1304, as repressor of ENAM and AMTN, is a strong candidate to be
An Ancestral miR-1304 Allele Regulates Dental Genes · doi:10.1093/molbev/mss023
involved in the susceptibility to AI and other forms of
enamel hypoplasia. It would be of interest to test this hypothesis in familial cases of the disorder for which the underlying genetic defect has not been identified yet and
furthermore study if Asian populations show higher AI incidence than other populations (the exact incidence of AI is
uncertain and estimates vary from 1:700 people to 1:14,000
according to the populations studied; Seow 1993). The finding of correlation between the presence of the ancestral allele of miR-1304 and the minor allele of rs117342040 in
ENAM, a variant that would interfere with the binding of
the ancestral miR-1304 to the mRNA and would avoid its
repression rescuing a hypothetical phenotype, is very appealing. It strengthens the idea that the presence of the ancestral
miR-1304 in modern humans could have some adverse effect, and thus, removal of downregulation of ENAM could
have been beneficial to modern humans. Unfortunately,
we could not find evidences for a selective sweep happening
in the miR-1304 gene, which would have reinforced this hypothesis. Finally, we should not forget about other predicted
target genes for the ancestral miR-1304 that are also related
to disease such as the above stated CD24 and TCF4 genes
that are involved in neurological disorders in humans.
Future analysis on the differential gene repression by the
two alleles of miR-1304 and deeper studies on the functional significance of this regulation would be of great interest not only to gain insights into primate evolution but
also in the possible implication of this miRNA in phenotypic differences among present-day human populations
and its relationship with complex human disorders.
Supplementary Material
Supplementary figures 1 and 2 and supplementary tables
1–3 are available at Molecular Biology and Evolution online
(http://www.mbe.oxfordjournals.org/).
Acknowledgments
We would like to thank M. Vallés, B. Kagerbauer, and F. Sánchez-Quinto for their technical support and advice and to
the anonymous referees whose comments and suggestions
greatly improved this manuscript. Support was provided by
the Spanish National Institute for Bioinformatics (www.inab.
org). This work was supported by the Ministerio de Ciencia e
Innovación, España (BFU2010-18477, BFU2009-06974, and
CGL2009-09013) and the European Union Seventh Framework Programme (PIOF-GA-2009-236836). This publication
has been cofinanced by FEDER—European Regional Development Fund ‘‘A way to build Europe.’’ Fieldwork at El Sidrón site has been funded by the Consejerı́a de Cultura,
Principado de Asturias. M.L.V. is funded by a Beca per
a la Formació de Personal Investigador (FI) fellowship from
the Agència de Gestió d’Ajuts Universitaris i de Recerca,
Generalitat de Catalunya.
References
Aiello LC, Dean MC. 1990. An introduction to human evolutionary
anatomy. London: Academic Press Limited. p. 106–132.
MBE
Amiel J, Rio M, de Pontual L, et al. (11 co-authors). 2007. Mutations
in TCF4, encoding a class I basic helix-loop-helix transcription
factor, are responsible for Pitt-Hopkins syndrome, a severe
epileptic encephalopathy associated with autonomic dysfunction. Am J Hum Genet. 80:988–993.
Bartel DP. 2004. MicroRNAs: genomics, biogenesis, mechanism, and
function. Cell 116:281–297.
Bentwich I, Avniel A, Karov Y, et al. (13 co-authors). 2005.
Identification of hundreds of conserved and nonconserved
human microRNAs. Nat Genet. 37:766–770.
Berezikov E, Guryev V, van de Belt J, Wienholds E, Plasterk R,
Cuppen E. 2005. Phylogenetic shadowing and computational
identification of human microRNA genes. Cell 120:21–24.
Borel C, Antonarakis SE. 2008. Functional genetic variation of
human miRNAs and phenotypic consequences. Mamm Genome.
19:503–509.
Brameier M. 2010. Genome-wide comparative analysis of microRNAs in three non-human primates. BMC Res Notes. 3:64.
Brennecke J, Stark A, Russell RB, Cohen SM. 2005. Principles of
microRNA-target recognition. PLoS Biol. 3:e85.
Briggs AW, Good JM, Green RE, et al. (18 co-authors). 2009.
Targeted retrieval and analysis of five Neandertal mtDNA
genomes. Science 325:318–321.
Briggs AW, Stenzel U, Johnson PL, et al. (11 co-authors). 2007.
Patterns of damage in genomic DNA sequences from
a Neandertal. Proc Natl Acad Sci U S A. 104:14616–14621.
Burbano HA, Hodges E, Green RE, et al. (20 co-authors). 2010.
Targeted investigation of the Neandertal genome by array-based
sequence capture. Science 328:723–725.
Cao H, Wang J, Li X, et al. (11 co-authors). 2010. MicroRNAs play
a critical role in tooth development. J Dent Res. 89:779–784.
Carroll SB. 2008. Evo-devo and an expanding evolutionary synthesis:
a genetic theory of morphological evolution. Cell 134(1):25–36.
Chen K, Rajewsky N. 2006. Deep conservation of microRNA-target
relationships and 3#UTR motifs in vertebrates, flies, and
nematodes. Cold Spring Harb Symp Quant Biol. 71:149–156.
Dong J, Gu TT, Simmons D, MacDougall M. 2000. Enamelin maps to
human chromosome 4q21 within the autosomal dominant
amelogenesis imperfecta locus. Eur J Oral Sci. 108:353–358.
Endicott P, Ho SY, Stringer C. 2010. Using genetic evidence to
evaluate four palaeoanthropological hypotheses for the timing of
Neanderthal and modern human origins. J Hum Evol. 59:87–95.
Feeney RN, Zermeno JP, Reid DJ, Nakashima S, Sano H, Bahar A,
Hublin JJ, Smith TM. 2010. Enamel thickness in Asian human
canines and premolars. Anthropol Sci. 118(3):191–198.
Filipowicz W, Bhattacharyya SN, Sonenberg N. 2008. Mechanisms of
post-transcriptional regulation by microRNAs: are the answers
in sight? Nat Rev Genet. 9:102–114.
Finlayson C, Pacheco FG, Rodrı́guez-Vidal J, et al. (26 co-authors).
2006. Late survival of Neanderthals at the southernmost
extreme of Europe. Nature 443:850–853.
Friedman RC, Farh KK, Burge CB, Bartel DP. 2009. Most mammalian
mRNAs are conserved targets of microRNAs. Genome Res. 19:92–105.
Grad Y, Aach J, Hayes GD, Reinhart BJ, Church GM, Ruvkun G, Kim J.
2003. Computational and experimental identification of C.
elegans microRNAs. Mol Cell. 11:1253–1263.
Green RE, Krause J, Briggs AW, et al. (56 co-authors). 2010. A draft
sequence of the Neandertal genome. Science 328:710–722.
Guidi M, Muiños-Gimeno M, Kagerbauer B, Martı́ E, Estivill X,
Espinosa-Parrilla Y. 2010. Overexpression of miR-128 specifically
inhibits the truncated isoform of NTRK 3 and upregulates BCL 2
in SH-SY 5 Y neuroblastoma cells. BMC Mol Biol. 11:95.
Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP,
Collins FS, Manolio TA. 2009. Potential etiologic and functional
implications of genome-wide association loci for human diseases
and traits. Proc Natl Acad Sci U S A. 106:9362–9367.
1805
Lopez-Valenzuela et al. · doi:10.1093/molbev/mss023
Hofreiter M, Jaenicke V, Serre D, Haeseler Av A, Pääbo S. 2001. DNA
sequences from multiple amplifications reveal artifacts induced
by cytosine deamination in ancient DNA. Nucleic Acids Res.
29:4793–4799.
Hublin JJ. 2009. The origin of Neandertals. Proc Natl Acad Sci U S A.
106:16022–16027.
Iwasaki K, Bajenova E, Somogyi-Ganss E, Miller M, Nguyen V,
Nourkeyhani H, Gao Y, Wendel M, Ganss B. 2005. Amelotin—a
novel secreted, ameloblast-specific protein. J Dent Res. 84:1127–1132.
Jazdzewski K, Murray EL, Franssila K, Jarzab B, Schoenberg DR, de la
Chapelle A. 2008. Common SNP in pre-miR-146a decreases
mature miR expression and predisposes to papillary thyroid
carcinoma. Proc Natl Acad Sci U S A. 105(20):7269–7274.
Kärrman C, Bäckman B, Dixon M, Holmgren G, Forsman K. 1997.
Mapping of the locus for autosomal dominant amelogenesis
imperfecta (AIH2) to a 4-Mb YAC contig on chromosome 4q11q21. Genomics 39:164–170.
Krause J, Lalueza-Fox C, Orlando L, et al. (13 co-authors). 2007. The
derived FOXP2 variant of modern humans was shared with
Neandertals. Curr Biol. 17:1908–1912.
Krol J, Loedige I, Filipowicz W. 2010. The widespread regulation of
microRNA biogenesis, function and decay. Nat Rev Genet.
11:597–610.
Lalueza-Fox C, Gigli E, de la Rasilla M, Fortea J, Rosas A. 2009. Bitter
taste perception in Neanderthals through the analysis of the
TAS2R38 gene. Biol. Lett. 5:809–811.
Lalueza-Fox C, Gigli E, de la Rasilla M, Fortea J, Rosas A,
Bertranpetit J, Krause J. 2008. Genetic characterization of the
ABO blood group in Neandertals. BMC Evol Biol. 8:342.
Lalueza-Fox C, Römpler H, Caramelli D, et al. (17 co-authors). 2007.
A melanocortin 1 receptor allele suggests varying pigmentation
among Neanderthals. Science 318:1453–1455.
Lalueza-Fox C, Rosas A, Estalrrich A, et al. (16 co-authors). 2011.
Genetic evidence for patrilocal mating behavior among
Neandertal groups. Proc Natl Acad Sci U S A. 108:250–253.
Lennertz L, Rujescu D, Wagner M, et al. (14 co-authors). 2011. Novel
schizophrenia risk gene TCF4 influences verbal learning and
memory functioning in schizophrenia patients. Neuropsychobiology
63:131–136.
Lewis BP, Burge CB, Bartel DP. 2005. Conserved seed pairing, often
flanked by adenosines, indicates that thousands of human genes
are microRNA targets. Cell 120:15–20.
Lin S, Cheung WK, Chen S, Lu G, Wang Z, Xie D, Li K, Lin MC,
Kung HF. 2010. Computational identification and characterization of primate-specific microRNAs in human genome. Comput
Biol Chem. 34:232–241.
Liu N, Okamura K, Tyler DM, Phillips MD, Chung WJ, Lai EC. 2008.
The evolution and functional diversification of animal microRNA genes. Cell Res. 18:985–996.
Macchiarelli R, Bondioli L, Debénath A, Mazurier A, Tournepiche JF,
Birch W, Dean MC. 2006. How Neanderthal molar teeth grew.
Nature 444:748–751.
Martı́ E, Pantano L, Bañez-Coronel M, Llorens F, Miñones-Moyano E,
Porta S, Sumoy L, Ferrer I, Estivill X. 2010. A myriad of miRNA
variants in control and Huntington’s disease brain regions detected
by massively parallel sequencing. Nucleic Acids Res. 38:7219–7235.
McLean CY, Reno PL, Pollen AA, et al. (13 co-authors). 2011.
Human-specific loss of regulatory DNA and the evolution of
human-specific traits. Nature 471:216–219.
Mellars P. 2004. Neanderthals and the modern human colonization
of Europe. Nature 432:461–465.
Michon F, Tummers M, Kyyrönen M, Frilander MJ, Thesleff I. 2010.
Tooth morphogenesis and ameloblast differentiation are
regulated by micro-RNAs. Dev Biol. 340:355–368.
Morin R, O’Connor M, Griffith M, et al. (12 co-authors). 2008.
Application of massively parallel sequencing to microRNA
1806
MBE
profiling and discovery in human embryonic stem cells. Genome
Res. 18:610–621.
Muiños-Gimeno M, Espinosa-Parrilla Y, Guidi M, et al. (14 coauthors). 2011. Human microRNAs miR-22, miR-138-2, miR148a, and miR-488 are associated with panic disorder and
regulate several anxiety candidate genes and related pathways.
Biol Psychiatry. 69:526–533.
Muiños-Gimeno M, Guidi M, Kagerbauer B, Martı́n-Santos R,
Navinés R, Alonso P, Menchón JM, Gratacòs M, Estivill X,
Espinosa-Parrilla Y. 2009. Allele variants in functional MicroRNA
target sites of the neurotrophin-3 receptor gene (NTRK3) as
susceptibility factors for anxiety disorders. Hum Mutat.
30:1062–1071.
Nielsen CB, Shomron N, Sandberg R, Hornstein E, Kitzman J,
Burge CB. 2007. Determinants of targeting by endogenous and
exogenous microRNAs and siRNAs. RNA 13:1894–1910.
Olejniczak AJ, Smith TM, Feeney RN, et al. (14 co-authors). 2008.
Dental tissue proportions and enamel thickness in Neandertal
and modern human molars. J Hum Evol. 55:12–23.
Pickrell JK, Coop G, Novembre J, et al. (8 co-authors). 2009. Signals
of recent positive selection in a worldwide sample of human
populations. Genome Res. 19(5):826–837.
Quach H, Barreiro LB, Laval G, et al. (11 co-authors). 2009.
Signatures of purifying and local positive selection in human
miRNAs. Am J Hum Genet. 84:316–327.
Ramirez Rozzi FV, Bermudez De Castro JM. 2004. Surprisingly rapid
growth in Neanderthals. Nature 428:936–939.
Rosas A, Martı́nez-Maza C, Bastir M, et al. (18 co-authors). 2006.
Paleobiology and comparative morphology of a late Neandertal
sample from El Sidron, Asturias, Spain. Proc Natl Acad Sci U S A.
103:19266–19271.
Seow WK. 1993. Clinical diagnosis and management strategies of
amelogenesis imperfecta variants. Pediatr Dent. 15:384–393.
Skoglund P, Jakobsson M. 2011. Archaic human ancestry in East
Asia. Proc Natl Acad Sci U S A. 108:18301–18306.
Smith TM, Harvati K, Olejniczak AJ, Reid DJ, Hublin JJ,
Panagopoulou E. 2009. Brief communication: dental development and enamel thickness in the Lakonis Neanderthal molar.
Am J Phys Anthropol. 138:112–118.
Smith TM, Tafforeau P, Reid DJ, et al. (14 co-authors). 2010.
Dental evidence for ontogenetic differences between modern
humans and Neanderthals. Proc Natl Acad Sci U S A.
107:20923–20928.
Stark MS, Tyagi S, Nancarrow DJ, Boyle GM, Cook AL,
Whiteman DC, Parsons PG, Schmidt C, Sturm RA,
Hayward NK. 2010. Characterization of the melanoma miRNAome
by deep sequencing. PLoS One. 5:e9685.
Stefansson H, Ophoff RA, Steinberg S, et al. (87 co-authors). 2009.
Common variants conferring risk of schizophrenia. Nature
460:744–747.
Stringer CB, Hublin JJ. 1999. New age estimates for the Swanscombe
hominid, and their significance for human. J Hum Evol. 37:873–877.
Sun G, Yan J, Noltner K, Feng J, Li H, Sarkis DA, Sommer SS, Rossi JJ.
2009. SNPs in human miRNA genes affect biogenesis and
function. RNA 15:1640–1651.
Vaz C, Ahmad HM, Sharma P, Gupta R, Kumar L, Kulshreshtha R,
Bhattacharya A. 2010. Analysis of microRNA transcriptome by
deep sequencing of small RNA libraries of peripheral blood. BMC
Genomics 11:288.
Vinci S, Gelmini S, Pratesi N, Conti S, Malentacchi F, Simi L, Pazzagli M,
Orlando C. 2011. Genetic variants in miR-146a, miR-149, miR196a2, miR-499 and their influence on relative expression in lung
cancers. Clin Chem Lab Med. doi:10.1515/CCLM.
Zhou Q, Rammohan K, Lin S, et al. (14 co-authors). 2003. CD24 is
a genetic modifier for risk and progression of multiple sclerosis.
Proc Natl Acad Sci U S A. 100:15041–15046.