Answers to Assignment Problems - Chapter 16
16.10 Paraphyly occurs when a taxon does not include all of the descendants from the most
recent common ancestor. Reptiles are paraphyletic because they do not include birds, which are
descended from reptiles.
Polyphyly occurs when a group does not contain the most recent common ancestor as a
member of the group. For example, the group consisting of warm-blooded animals is
polyphyletic, because it contains both mammals and birds, but the most recent common ancestor
of mammals and birds was cold-blooded (and is not included in the warm-blooded grouping).
Warm-bloodedness evolved separately in the ancestors of mammals and the ancestors of birds.
The figure below (modified from Wikipedia) helps explain the difference between
paraplyly and polyphyly using a phylogeny from primates.
Phylogeny of the primates, showing monophyly (the simians, in yellow), paraphyly (the
prosimians, in blue, including the red patch), and polyphyly (the night-active primates, the
lorises and the tarsiers, in red). Arrow shows the most recent common ancestor which is included
in the blue (paraphyly) but not red (polyphyly. Modified from Wikipedia.
16.11 We might wrongly infer that a genetic discontinuity (partial barrier) exists between
sampling locations if only one local group of individuals is sampled from each of two
geographically-distant locations (in a continuous population); this is because individuals within
each spatially-distant group will be genetically similar (and cluster together) yet each group will
be genetically differentiated from each other (especially if the groups are far apart
geographically). Thus a researcher might conclude there is a barrier to gene flow, when in fact
there is only isolation by distance with continual or gradual genetic change but without a sudden
geographic break in gene flow.
To avoid this kind of erroneous ‘barrier’ inference, biologists should first be aware of this
potential problem. Second, we should avoid having large spatial gaps in our sampling
distribution (i.e., individuals should be sampled on a grid in a continuous pattern - evenly
distributed across the study area). Biologists could also test for isolation by distance and
quantify the spatial scale at which spatial autocorrelation occurs among individuals (genotypes)
to help understand if a continuous population structure exists without genetic discontinuities.
16.12 High gene flow among MUs makes it challenging to identify the MUs because FST can be
very low suggesting panmixia even if few or no migrants exist (and thus demographic
independence exists). For example, if drift is weak due to large effective size in each population,
the FST can remain low for many generations even if no migration occurs. This occurs in many
marine fish species, for example.
(b) FST alone is not particularly useful for identifying MUs because the same FST can
result between populations with low migration rates (and thus demographic independence) and
with moderate migration rates (no independence) (see Table 16.4).
16.13 The four sequences yield the following parsimony network:
2
27
4
7
8
13
23
3
1
(b) The first sequence matches a major histocompatibility complex (MHC) class II gene (DRB)
from ungulate species as below. Hemitragus jemlahicus, Bos taurus, Ovis canadensis, Ovis
dalli, and Capra hircus all have this sequence.
The table below contains the top rows of a table provided by GenBank. It reports 100%
sequence identity (Max ident).
Sequences producing significant alignments:
Max
Accession
Description
score
Transcripts
Ovis canadensis MHC class II antigen (DRB) mRNA,
JN081876.1
79.8
DRB*24 allele, partial cds
Ovis canadensis MHC class II antigen (DRB) mRNA,
JN081875.1
79.8
DRB*2 allele, partial cds
Ovis canadensis MHC class II antigen (DRB) mRNA,
JN081873.1
79.8
DRB*3 allele, partial cds
Hemitragus jemlahicus MHC class II antigen (HejeAF336341.1
79.8
DRB) mRNA, complete cds
Bos taurus mRNA for MHC class II antigen,
Y18308.1
79.8
DRB3*1102 allele
Bos taurus major histocompatibility complex, class II,
DRB3 (BOLA-DRB3), mRNA
NM_001012680.2
79.8
>gb|U77067.1|BTU77067 Bos taurus MHC class II DR
beta-chain (allele: DRB3*3101) mRNA, complete cds
Bos taurus major histocompatibility complex, class II,
BT025473.1
69.9
DR beta 4 (HLA-DRB4), mRNA, complete cds
Total Query
E
Max
score coverage value ident
79.8
100%
8e-13 100%
79.8
100%
8e-13 100%
79.8
100%
8e-13 100%
79.8
100%
8e-13 100%
79.8
100%
8e-13 100%
79.8
100%
8e-13 100%
69.9
97%
8e-10 97%
Below is an example alignment given by GenBank:
gb|JN081876.1|
allele,
partial cds
Length=793
Ovis canadensis MHC class II antigen (DRB) mRNA, DRB*24
Score = 79.8 bits (40), Expect = 8e-13
Identities = 40/40 (100%), Gaps = 0/40 (0%)
Strand=Plus/Plus
Query
1
Sbjct
112
GAGTATTATAAGGGCGAGTGTCATTTCTTCAACGGGACCG
||||||||||||||||||||||||||||||||||||||||
GAGTATTATAAGGGCGAGTGTCATTTCTTCAACGGGACCG
40
151
16.14 It is difficult to determine a minimum number of adaptive gene markers needed to
identify adaptively-differentiated populations. Adaptive genes should not be used alone because
genes under selection might not reflect genome-wide variation (including both neutral and
adaptive gene variation important in future environments), as mentioned in the Assignment
Problem 16.5. Prioritization of populations for conservation based on a few genes under
selection could lead to a genome-wide loss of variation, including a loss of variation at other
adaptive loci. Note that a small proportion of gene markers under selection (e.g., 5 out of 100)
can change inferences about population relationships (Figure 16.22; see review by Luikart et al.
2003). Thus researchers should test for selection and its effects on inferences about
relationships.
Markers in a few adaptive genes might help to delineate ESU if applied along with many neutral
genetic markers (e.g., Figure 16.21). Other non-genetic information should also be considered
(Figure 16.20). Ideally, the adaptive gene markers would have a well-understood function that is
closely related to phenotypic traits or environmental variables that are also measured from each
population unit being studied (Hansen et al. 2012). Adaptive gene markers under strong
selection should only be used to complement neutral loci.
(b) The optimal proportion of the exome to sequence to identify ESUs is extremely difficult to
determine. The whole exome (or genome) can now be sequenced for many species. However,
this is still generally too expensive and perhaps unnecessary (overkill) for detecting patterns of
genome-wide neutral and adaptive differentiation among populations useful for CU delineation.
It is possible that informative markers in exons from a subset of 5,000 to 10,000 genes (e.g.,
from a vertebrate genome) would suffice if many adaptive genes and genome-wide markers were
included. These 5,000 to 10,000 genes represent approximately 20% to 30% of genes in most
vertebrate species. This is a small enough number of genes to allow simultaneous multiplex
sequencing of many individuals to minimize costs. It also fills the smallest size of capture array
currently available from some commercial companies.
The optimal proportion of the exome to sequence depends on gametic disequlibrium
(GD) because species with very high GD (e.g., wild sheep or small trout populations) require far
fewer markers per chromosomal region to assess genome-wide variation at both neutral and
adaptive genes. Species with large population effective sizes and low GD (e.g., marine fish)
would likely require far more markers (e.g., 10x or 100x more markers) than a species with high
GD.
(c) To empirically investigate the number of genes that must be sequenced (or genotyped) to
reliably identify ESUs, we could choose a species for which ESUs are already well defined and
for which 10,000-100,000 DNA markers exist, e.g., stickleback fish in Guest Box 8. We could
then subsample markers to see how many independent subsamples (of say 1,000, 5,000, or
10,000 markers) give the full and accurate relationships among known ESUs.