Adaptive protein evolution and regulatory divergence in Drosophila.
ABSTRACT Two recent studies demonstrated a positive correlation between divergence in gene expression and protein sequence in Drosophila. This correlation could be driven by positive selection or variation in functional constraint. To distinguish between these alternatives, we compared patterns of molecular evolution for 1,862 genes with two previously reported estimates of expression divergence in Drosophila. We found a slight negative trend (nonsignificant) between positive selection on protein sequence and divergence in expression levels between Drosophila melanogaster and Drosophila simulans. Conversely, shifts in expression patterns during Drosophila development showed a positive association with adaptive protein evolution, though as before the relationship was weak and not significant. Overall, we found no strong evidence for an increase in the incidence of positive selection on protein-coding regions in genes with divergent expression in Drosophila, suggesting that the previously reported positive association between protein and regulatory divergence primarily reflects variation in functional constraint.
Article: Extensive evolutionary changes in regulatory element activity during human origins are associated with altered gene expression and positive selection.[show abstract] [hide abstract]
ABSTRACT: Understanding the molecular basis for phenotypic differences between humans and other primates remains an outstanding challenge. Mutations in non-coding regulatory DNA that alter gene expression have been hypothesized as a key driver of these phenotypic differences. This has been supported by differential gene expression analyses in general, but not by the identification of specific regulatory elements responsible for changes in transcription and phenotype. To identify the genetic source of regulatory differences, we mapped DNaseI hypersensitive (DHS) sites, which mark all types of active gene regulatory elements, genome-wide in the same cell type isolated from human, chimpanzee, and macaque. Most DHS sites were conserved among all three species, as expected based on their central role in regulating transcription. However, we found evidence that several hundred DHS sites were gained or lost on the lineages leading to modern human and chimpanzee. Species-specific DHS site gains are enriched near differentially expressed genes, are positively correlated with increased transcription, show evidence of branch-specific positive selection, and overlap with active chromatin marks. Species-specific sequence differences in transcription factor motifs found within these DHS sites are linked with species-specific changes in chromatin accessibility. Together, these indicate that the regulatory elements identified here are genetic contributors to transcriptional and phenotypic differences among primate species.PLoS Genetics 06/2012; 8(6):e1002789. · 8.69 Impact Factor
Article: Exacerbation of signs and symptoms of allergic conjunctivitis by a controlled adverse environment challenge in subjects with a history of dry eye and ocular allergy.[show abstract] [hide abstract]
ABSTRACT: The goal of this study was to assess the effect of a controlled adverse environment (CAE) challenge on subjects with both allergic conjunctivitis and dry eye. Thirty-three subjects were screened and 17 completed this institutional review board-approved study. Subjects underwent baseline ocular assessments and conjunctival allergen challenge (CAC) on days 0 and 3. Those who met the ocular redness and itching criteria were randomized to receive either the controlled adverse environment (CAE) challenge (group A, n = 9) or no challenge (group B, n = 8) at day 6. Thirty minutes after CAE/no-CAE, subjects were challenged with allergen and their signs and symptoms graded. Exploratory confocal microscopy was carried out in a subset of subjects at hourly intervals for 5 hours post-CAC on days 3 and 6. Seven minutes post-CAC, subjects exposed to the CAE had significantly greater itching (difference between groups, 0.55 ± 0.25, P = 0.028), conjunctival redness (0.59 ± 0.19, P = 0.002), episcleral redness (0.56 ± 0.19, P = 0.003) and mean overall redness (mean of conjunctival, episcleral, and ciliary redness, 0.59 ± 0.14, P < 0.001). The mean score at 7, 15, and 20 minutes post-CAC for conjunctival redness (0.43 ± 0.17, P = 0.012), episcleral redness (0.49 ± 0.15, P = 0.001), mean overall redness in all regions (0.43 ± 0.15, P = 0.005), and mean chemosis (0.20 ± 0.08, P = 0.017) were also all significantly greater in CAE-treated subjects. Confocal microscopic images of conjunctival vessels after CAC showed more inflammation in CAE-treated subjects. In subjects with both dry eye and allergic conjunctivitis, exposure to adverse environmental conditions causes an ocular surface perturbation that can intensify allergic reactions.Clinical ophthalmology (Auckland, N.Z.) 01/2013; 7:157-65.
[show abstract] [hide abstract]
ABSTRACT: Dry eye is a common ocular surface inflammatory disease that significantly affects quality of life. Dysfunction of the lacrimal function unit (LFU) alters tear composition and breaks ocular surface homeostasis, facilitating chronic inflammation and tissue damage. Accordingly, the most effective treatments to date are geared towards reducing inflammation and restoring normal tear film. The pathogenic role of CD4+ T cells is well known, and the field is rapidly realizing the complexity of other innate and adaptive immune factors involved in the development and progression of disease. The data support the hypothesis that dry eye is a localized autoimmune disease originating from an imbalance in the protective immunoregulatory and proinflammatory pathways of the ocular surface.International Reviews Of Immunology 01/2013; 32(1):19-41. · 3.43 Impact Factor
Adaptive Protein Evolution and Regulatory Divergence in Drosophila
Jeffrey M. Good,* Celine A. Hayden,? and Travis J. Wheeler?
*Department of Ecology and Evolutionary Biology, University of Arizona; ?Department of Plant Sciences,
University of Arizona; and ?Department of Computer Science, University of Arizona
Two recent studies demonstrated a positive correlation between divergence in gene expression and protein sequence in
Drosophila. This correlation could be driven by positive selection or variation in functional constraint. To distinguish
between these alternatives, we compared patterns of molecular evolution for 1,862 genes with two previously reported
estimates of expression divergence in Drosophila. We found a slight negative trend (nonsignificant) between positive
selection on protein sequence and divergence in expression levels between Drosophila melanogaster and Drosophila
simulans. Conversely, shifts in expression patterns during Drosophila development showed a positive association with
adaptive protein evolution, though as before the relationship was weak and not significant. Overall, we found no strong
evidencefor an increase inthe incidence ofpositive selection on protein-coding regions in genes with divergent expression
in Drosophila, suggesting that the previously reported positive association between protein and regulatory divergence
primarily reflects variation in functional constraint.
Although changes in gene regulation and in protein
structure have been conventionally treated as independent
modes of evolution (King and Wilson 1975), two lines of
evidence suggest that protein sequence evolution might be
coupled with divergence in gene expression in Drosophila.
First, some of the classic examples of adaptive allozyme
polymorphisms within species are associated with differen-
ces in gene expression (Laurie-Ahlberg 1985; Berry and
Kreitman 1993; Odgers, Healy, and Oakeshott 1995).
Second, there is a positive correlation between the rate
of protein evolution (i.e., amino acid substitution, dN)
and divergence in expression levels for male-biased genes
surveyed in Drosophila melanogaster and Drosophila
simulans (Nuzhdin et al. 2004; Lemos et al. 2005).
A positive correlation between rates of protein se-
quence evolution and expression divergence could be dri-
ven by positive selection on genes causing both protein
structure and regulation to evolve rapidly (Nuzhdin et al.
2004). An alternative explanation for a coupling between
regulatory and structural divergence is variation in purify-
ing selection: genes with less functionally constrained pro-
tein sequence may also be less constrained in expression
associated with positive selection on protein sequences in
Drosophila. Using genomic data from five closely related
species of Drosophila (D. melanogaster, D. simulans, Dro-
sophila yakuba, Drosophila erecta, and Drosophila ana-
nassae), we used a maximum likelihood framework to
calculate rates of protein evolution for 1,862 genes and
tested for evidence of positive selection (Yang et al.
of divergence in gene expression: (1) divergence in the
level of expression between D. melanogaster and D. sim-
ulans (Ranz et al. 2003) and (2) divergence in the pattern of
expression during metamorphosis in D. melanogaster,
D. simulans,and D. yakuba (Rifkin, Kim, and White 2003).
We found that genes with divergent expression levels
between D. melanogaster and D. simulans have rates of
protein evolution (dN/dS) that are similar to genes with
no expression divergence (table 1; all comparisons Wilcox-
on P . 0.10). However, in all comparisons, genes with di-
vergent expression levels do have higher median dN/dS
levels than genes with similar levels of expression, con-
sistent with previous reports of a weak positive correlation
between expression divergence and protein evolution
(Nuzhdin et al. 2004; Lemos et al. 2005). Interestingly,
we found that female-biased and male-biased genes evolve
at similar rates, in contrast to a previous report that male-
biased genes show a fourfold increase in dN/dS(Zhang,
Hambuch, and Parsch 2004).
We tested for a positive association between diver-
gence in gene expression level and positive selection on
protein sequence and found a slightly higher incidence
of positive selection (4.6% under selection) in genes with
similar expression levels between D. melanogaster and
D. simulans than in genes with divergent expression (3.2%
under selection; fig. 1). A negative association was also
observed when considering only male-biased genes (6.8%
vs. 5.6%) and only female-biased genes (4.0% vs. 3.6%).
None of these differences was significant using a Fisher’s
Exact test; however, in each case, the trend was in the
opposite direction of what would be expected if adaptive
protein evolution drives the positive relationship between
the rate of protein evolution and expression divergence.
morphosis in four D. melanogaster lines, one D. simulans,
and one D. yakuba (Rifkin, Kim, and White 2003). Their
experiment identified genes with divergent expression pat-
terns by comparing the ratio of gene expression at two de-
velopmental time points among lineages. Although a more
complex metric for measuring expression divergence, their
approach avoids hybridization artifacts due to interspecific
divergence (Gilad et al. 2005) because expression patterns
are based on within-lineage comparisons. As with expres-
sion level, genes with divergent expression patterns among
species during metamorphosis have similar rates of evolu-
tion as genes with no expression divergence among species
(table 1; Wilcoxon P . 0.10). In contrast to what we de-
tected when comparing divergence in expression level, we
found a slight positive association between expression
Key words: gene expression, positive selection, protein evolution.
Mol. Biol. Evol. 23(6):1101–1103. 2006
Advance Access publication March 14, 2006
? The Author 2006. Published by Oxford University Press on behalf of
the Society for Molecular Biology and Evolution. All rights reserved.
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divergence patternsduringmetamorphosis and incidence of
positiveselection onprotein-codingregions(6.0% vs.4.6%
under positive selection). But again, this difference was not
significant (Fisher’s Exact test, two-tailed P 5 0.224).
The lack of a strong relationship between structural
and regulatory evolution in our study may reflect noise in-
troduced by combining neutral and adaptive expression di-
vergence. For example, it is possible that positive selection
for expression divergence could be most frequent in genes
with less functionally constrained protein sequence. Such
a scenario could generate a positive correlation between
expression and protein sequence divergence but is difficult
to evaluate given the current data. The analysis by Rifkin,
Kim, and White (2003 and updates) of expression patterns
duringmetamorphosis represents one of the first attempts to
classify evolutionary modes of regulatory divergence using
genome-level data (see also Khaitovich, Pa ¨a ¨bo, and Weiss
2005) but is not a formal test of positive selection on ex-
pression. We combined genes identified to be neutrally
evolving with those identified as undergoing lineage-
specific selection to form our set of genes with divergent
expression during metamorphosis (fig. 1). However, we
found no difference in the rate of protein sequence evolu-
tion (Wilcoxon P . 0.10) or the frequency of positive se-
lection on protein-coding regions between genes whose
expression patterns were classified by Rifkin, Kim, and
White (2003) as evolving due to lineage-specific selection
and genes for which neutrality could not be rejected (5.9%
vs. 6.3%, fig. S1, see Supplementary Material online).
Overall, these data suggest that positive selection on
protein sequence is not strongly coupled with divergence
in gene expression in Drosophila (fig. 1). Thus, the corre-
lation between dNand expression divergence previously
documented by Nuzhdin et al. (2004) and Lemos et al.
(2005) is more likely due to differences in purifying selec-
tion than inadaptive evolution on both protein structure and
All predicted protein and nucleotide sequences for
D. melanogaster were downloaded from the Ensembl da-
tabase (http://www.ensembl.org/index.html). Orthologous
sequences from D. simulans, D. yakuba, D. erecta, and
D. ananassae were identified from the Eisen Group Anno-
tations Release 1.0 (February 18, 2005; Venky Iyer, Daniel
Pollard, and Michael Eisen) based on a combination of
direct pairwise comparisons with D. melanogaster and
computational gene prediction. Orthologous amino acid
sequences were aligned with ClustalW v1.8 using default
parameters (Thompson, Higgins, and Gibson 1994). We
used the amino acid alignment for each gene as a guide
v1.3 (Wernersson and Pedersen 2003).
All analyses on the rate of protein evolution among
taxa and tests of positive selection were conducted using
the codeml program in the PAML package v3.14 (Yang
FIG. 1.—The incidence of positive selection on protein-coding regions of genes (M7 vs. M8; P , 0.01) relative to divergence in expression level or
pattern. All comparisons are nonsignificant using a Fisher’s Exact test.
Median Rate of Protein Evolution and Divergence in
aPairwise comparisons between Drosophila melanogaster and Drosophila
bExpression data from Ranz et al. (2003).
cExpression data from Rifkin, Kim, and White (2003 and updates).
1102Good et al.
substitutions per nonsynonymous site (dN) and the number
of synonymous substitutions per synonymous site (dS)
were calculated using maximum likelihood (Goldman
and Yang 1994). To test for evidence of positive selection
in each gene, we fit sequence data from D. melanogaster,
models allowing evolutionary rates (dN/dS) to vary across
codon sites (models M7 and M8; Yang et al. 2000). M7
assumes that dN/dSvalues vary across codon sites but are
functionally constrained between 0 and 1, while M8 allows
for an additional category of sites under positive selection
(dN/dS. 1). Genes were assumed to be under positive se-
lection if the data fit M8 better with a likelihood ratio test
(P , 0.01). We required the dN/dSratio for positively se-
the proportion of positively selected sites to exceed 1%.
Less conservative criteria produced similar results.
We defined expression divergence according to previ-
ously published results. Divergent transcripts between D.
melanogaster and D. simulans were defined as genes with
nonoverlapping 95% confidence intervals in expression
level between species estimated using a Bayesian approach
(Ranz et al. 2003). Rifkin, Kim, and White (2003) surveyed
gene expression in D. melanogaster (four lines), D. simu-
lans, and D. yakuba at two developmental time points. In
their experiment, expression divergence was classified into
three evolutionary categories based on patterns of variation
among the six lineages (see Rifkin, Kim, and White 2003
for details). Briefly, genes were assumed to be evolving due
to stabilizing selection if they showed little or no variation
among the six lineages (i.e., genes not divergent in expres-
sion in our study). Genes showing significant variation
among lineages (i.e., genes divergent in expression) were
classified as evolving due to lineage-specific selection if
they showed insignificant variation within D. melanogaster
or neutral if the patterns were consistent with a mutation-
drift model. We used an updated version of these data
available from the authors at http://genome.med.yale.edu/
Comparative/. Estimates of protein evolution and summa-
rized expression data for all 1,862 genes are given in table
S1 (see Supplementary Material online).
Supplementary fig. S1 and table S1 are available
at Molecular Biology and Evolution online (http://
We thank V. Iyer, D. Pollard, and M. Eisen for making
their genome annotations publicly available. We are grate-
ful to H. Ochman and the Integrative Graduate Education
and Research Traineeship (IGERT) fellows for insightful
discussion during the development of this project. The
manuscript was improved by comments from M. Dean,
H. Ochman, M. Nachman, and two anonymous reviewers.
This research was conducted as part of the University of
Arizona National Science Foundation IGERT grant
Genomics Initiative (DGE-0114420).
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Accepted March 1, 2006
Structural and Regulatory Evolution in Flies1103