An Evolutionary Genomic Approach to Identify Genes Involved in Human Birth Timing

Stanford University, United States of America
PLoS Genetics (Impact Factor: 7.53). 04/2011; 7(4):e1001365. DOI: 10.1371/journal.pgen.1001365
Source: PubMed
ABSTRACT
Coordination of fetal maturation with birth timing is essential for mammalian reproduction. In humans, preterm birth is a disorder of profound global health significance. The signals initiating parturition in humans have remained elusive, due to divergence in physiological mechanisms between humans and model organisms typically studied. Because of relatively large human head size and narrow birth canal cross-sectional area compared to other primates, we hypothesized that genes involved in parturition would display accelerated evolution along the human and/or higher primate phylogenetic lineages to decrease the length of gestation and promote delivery of a smaller fetus that transits the birth canal more readily. Further, we tested whether current variation in such accelerated genes contributes to preterm birth risk. Evidence from allometric scaling of gestational age suggests human gestation has been shortened relative to other primates. Consistent with our hypothesis, many genes involved in reproduction show human acceleration in their coding or adjacent noncoding regions. We screened >8,400 SNPs in 150 human accelerated genes in 165 Finnish preterm and 163 control mothers for association with preterm birth. In this cohort, the most significant association was in FSHR, and 8 of the 10 most significant SNPs were in this gene. Further evidence for association of a linkage disequilibrium block of SNPs in FSHR, rs11686474, rs11680730, rs12473870, and rs1247381 was found in African Americans. By considering human acceleration, we identified a novel gene that may be associated with preterm birth, FSHR. We anticipate other human accelerated genes will similarly be associated with preterm birth risk and elucidate essential pathways for human parturition.

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An Evolutionary Genomic Approach to Identify Genes
Involved in Human Birth Timing
Jevon Plunkett
1,2.
, Scott Doniger
3.
, Guilherme Orabona
1,4
, Thomas Morgan
1,4
, Ritva Haataja
5
, Mikko
Hallman
5
, Hilkka Puttonen
6
, Ramkumar Menon
7,8
, Edward Kuczynski
9
, Errol Norwitz
9
, Victoria
Snegovskikh
9
, Aarno Palotie
10,11,12
, Leena Peltonen
10,11,12{
, Vineta Fellman
13,14
, Emily A. DeFranco
15
,
Bimal P. Chaudhari
16
, Tracy L. McGregor
1
, Jude J. McElroy
1,4
, Matthew T. Oetjens
4
, Kari Teramo
6
, Ingrid
Borecki
17
, Justin Fay
18"
, Louis Muglia
1,19,20"
*
1 Department of Pediatrics, Vanderbilt University School of Medicine and Monroe Carell Jr. Children’s Hospital at Vanderbilt, Nashville, Tennessee, United States of
America, 2 Human and Statistic Genetics Program, Washington University School of Medicine, St. Louis, Missouri, United States of America, 3 Computational Biology
Program, Washington University School of Medicine, St. Louis, Missouri, United States of America, 4 Center for Human Genetics Research, Vanderbilt University School of
Medicine, Nashville, Tennessee, United States of America, 5 Institute of Clinical Medicine, Department of Pediatrics, University of Oulu, Oulu, Finland, 6 Departments of
Obstetrics and Gynecology, University of Helsinki, Helsinki, Finland, 7 The Perinatal Research Center, Nashville, Tennessee, United States of America, 8 Department of
Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America, 9 Department of Obstetrics, Gynecology, and Reproductive
Sciences, Yale University School of Medicine, New Haven, Connecticut, United States of America, 10 Finnish Institute of Molecular Medicine, University of Helsinki, Helsinki,
Finland, 11 The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America, 12 Wellcome Trust Sanger Institute, Cambridge, United
Kingdom, 13 Department of Pediatrics, Lund University, Lund, Sweden, 14 Department of Pediatrics, University of Helsinki, Helsinki, Finland, 15 Department of Obstetrics
and Gynecology, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America, 16 Department of Pediatrics, Washington University School of
Medicine, St. Louis, Missouri, United States of America, 17 Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri , United States of
America, 18 Department of Genetics and Center for Genome Sciences, Washington University School of Medicine, St. Louis, Missouri, United States of America,
19 Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America, 20 Vanderbilt Kennedy
Center for Human Development, Vanderbilt University, Nashville, Tennessee, United States of America
Abstract
Coordination of fetal maturation with birth timing is essential for mammalian reproduction. In humans, preterm birth is a
disorder of profound global health significance. The signals initiating parturition in humans have remained elusive, due to
divergence in physiological mechanisms between humans and model organisms typically studied. Because of relatively
large human head size and narrow birth canal cross-sectional area compared to other primates, we hypothesized that genes
involved in parturition would display accelerated evolution along the human and/or higher primate phylogenetic lineages
to decrease the length of gestation and promote delivery of a smaller fetus that transits the birth canal more readily.
Further, we tested whether current variation in such accelerated genes contributes to preterm birth risk. Evidence from
allometric scaling of gestational age suggests human gestation has been shortened relative to other primates. Consistent
with our hypothesis, many genes involved in reproduction show human acceleration in their coding or adjacent noncoding
regions. We screened .8,400 SNPs in 150 human accelerated genes in 165 Finnish preterm and 163 control mothers for
association with preterm birth. In this cohort, the most significant association was in FSHR, and 8 of the 10 most significant
SNPs were in this gene. Further evidence for association of a linkage disequilibrium block of SNPs in FSHR, rs11686474,
rs11680730, rs12473870, and rs1247381 was found in African Americans. By considering human acceleration, we identified a
novel gene that may be associated with preterm birth, FSHR. We anticipate other human accelerated genes will similarly be
associated with preterm birth risk and elucidate essential pathways for human parturition.
Citation: Plunkett J, Doniger S, Orabona G, Morgan T, Haataja R, et al. (2011) An Evolutionary Genomic Approach to Identify Genes Involved in Human Birth
Timing. PLoS Genet 7(4): e1001365. doi:10.1371/journal.pgen.1001365
Editor: Gregory S. Barsh, Stanford University, United States of America
Received July 14, 2010; Accepted March 7, 2011; Published April 14, 2011
Copyright: ß 2011 Plunkett et al. This is an open-access article distributed under the term s of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by grants from the Children’s Discovery Institute at Washington University School of Medicine and St. Louis Children’s
Hospital awarded to JF and LM and from the March of Dimes awarded to LM and EN. This research was also supported by T32 GM081739 from the National
Institute of General Medical Science and the Mr. and Mrs. Spencer T. Olin Fellowship for Women in Graduate Study at Washington University in St. Louis awarded
to JP, a grant from the Sigrid Juselius Foundation awarded to MH, a grant from the Signe and Anne Gyllenberg foundation to VF, and grants from the Academy of
Finland to RH and MH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: Louis.Muglia@Vanderbilt.Edu
. These authors contributed equally to this work.
" These authors were joint senior authors on this work.
{ Deceased.
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Introduction
Despite the important public health consequences of preterm
birth [1,2], determinants of human parturition remain largely
uncharacterized. While some important physiological antecedents
of labor have been identified in model organisms, such as
progesterone withdrawal in rodents, such signals do not seem to
precede human labor. Because humans are born developmentally
less mature than other mammals [3,4], birth timing mechanisms
may differ between humans and model organisms that have been
typically studied [5].
Evidence suggests that parturition has changed along the
human lineage in response to other uniquely human adaptations.
The dramatic increase in brain size, along with the human pelvis
becoming narrower to facilitate bipedalism, places unique
constraints on birth in humans compared even with evolutionarily
close relatives such as Neanderthals and chimpanzees [6,7]. Given
the historically high mortality rate associated with pregnancy,
these human traits may generate selective pressure to initiate
parturition at a relatively earlier time in gestation compared to
non-human primates to avoid cephalopelvic disproportion and
arrested labor by delivery of a relatively smaller, less mature fetus.
High rates of human versus non-human primate divergence in
human pregnancy-related genes, such as genes in the reproduction
Gene Ontology (GO) category [8,9] as well as GO categories
related to fetal development, including transcription factors [10],
nuclear hormone receptors [10], transcriptional regulation [11]
and development [9], support the notion that human gestation
length has been altered to accommodate features unique to human
pregnancy.
Genetic influences on birth timing in humans appear to be
substantial, based on family and twin studies [12,13,14]. However,
association studies using candidates selected from suspected
pathways have not detected robust susceptibility variants for
preterm birth. Genome-wide association studies (GWAS) are
promising but will require large numbers of well-characterized
subjects in order to overcome the challenge of multiple statistical
comparisons. Here, we test the hypothesis that the set of genes
accelerated on the human lineage will include genes that play
important roles in regulating parturition and harbor variants that
influence preterm birth risk. We identified and analyzed genes
showing marked divergence between humans and other mammals,
defined by relative nucleotide substitution rates in coding and
highly conserved noncoding regions, for association with preterm
birth. We find that genes with evidence of rate acceleration in
humans may provide an informative group of candidates, and
demonstrate that the human accelerated gene, follicle-stimulating
hormone receptor (FSHR), may alter risk for preterm birth.
Results/Discussion
Life history traits
Because of large human head size and narrow birth canal cross-
section compared to other primates [6], we hypothesized that
genes involved in parturition have evolved rapidly along the
human phylogenetic lineage to decrease the length of gestation
and alleviate the complications arising from these constraints. We
performed a comparative analysis of life history traits in mammals
to further evaluate whether the relative gestational period in
humans has decreased compared to other primates and mammals.
Data acquired by Sacher and Staffeldt [15] and reanalyzed by us
show that both adult and neonatal higher primates (simians) have
higher brain to body weight ratios compared to other mammals
(Figure 1A, 1B and Table S1 for list of species). The difference in
brain/body size ratios in higher primates relative to other
mammals makes it possible to ask whether gestation in higher
primates is linked to brain size or body size. Higher primates and
other mammals have equivalent gestational periods with respect to
brain weight (Figure 1C). In contrast, the gestational period in
higher primates is longer relative to the length of gestation in
mammals with equivalent neonatal body weights (Figure 1D). This
suggests that the length of gestation is expected to change with
brain size but not body size.
Humans have evolved the highest adult brain to body weight
ratio of any mammal [16]. In contrast to the evolution of brain/
body ratios in higher primates, where both adult and neonatal
ratios are increased relative to other mammals, the increase in the
brain/body ratio in humans relative to other primates is present in
adults but not neonates (Figure 1B). The simplest explanation is
that human adult brain/body ratios have changed independently
of neonatal ratios. However, the ratio of brain/body weight is
highest at birth and declines until adulthood. Thus, an alternative
explanation is that both adult and neonatal brain/body ratios have
increased in humans, as in other higher primates, but that a
concurrent decrease in the length of gestation lowered the
neonatal brain/body ratio. This second possibility is supported
by the relative immaturity of human neonates compared to other
primates [3,4] and that the length of human gestation, relative to
either neonatal brain or body weight, is shorter than most other
higher primates (Figure 1C, 1D).
To examine the evolution of gestation length relative to
neonatal brain and body weight in primates we inferred the
evolution of these characters across a phylogenetic tree. For both
gestation-neonatal body ratio (Figure 2A) and gestation-neonatal
brain ratio (Figure 2B) there is a consistent trend of a relatively
shorter length of gestation on branches leading to humans. Of
note, humans have the lowest gestation-neonatal body ratio
(Figure 2A) or gestation-neonatal brain ratio (Figure 2B) of all the
20 primates evaluated. The gestation-neonatal brain ratio for
humans is 69% that of gorilla and 45% that of chimpanzee. The
gestation-neonatal body ratio of human is 49% that of gorilla and
50% that of chimpanzee.
Author Summary
The control of birth timing in humans is the greatest
unresolved question in reproductive biology, and preterm
birth is the most important medical issue in maternal and
child health. To begin to address this critical problem, we
test the hypothesis that genes accelerated in their rate of
evolution in humans, as compared with other primates
and mammals, are involved in birth timing. We first show
that human gestational length has been altered relative to
other non-human primates and mammals. Using allome-
tric scaling, we demonstrate that human gestation is
shorter than predicted based upon gestational length in
other mammalian species. Next, we show that genes with
rate acceleration in humans—in coding or regulatory
regions—are plausible candidates to be involved in birth
timing. Finally, we find that polymorphisms in the human
accelerated gene (FSHR), not before implicated in the
timing for birth, may alter risk for human preterm birth.
Our understanding of pathways for birth timing in humans
is limited, yet its elucidation remains one of the most
important issues in biology and medicine. The evolution-
ary genetic approach that we apply should be applicable
to many human disorders and assist other investigators
studying preterm birth.
Human Evolution and Preterm Birth
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Accelerated gene evolution in the human lineage
In light of this evidence for human adaptation for birth timing,
we examined whether genes involved in parturition would display
accelerated protein evolution along the human lineage measured
by an increased rate of amino acid altering to synonymous
nucleotide substitutions (dN/dS; Figure S1). We found that, of 120
suggested candidate genes for preterm birth that were included in
the ENSEMBL database, 7 showed statistically significant
increased rate acceleration (i.e. increased dN/dS; p,0.05) along
the human lineage in comparison to the other lineages. Table 1
shows these 7 genes plus 2 other genes significantly accelerated
along the human-chimpanzee ancestor lineage (complete analysis
of dN/dS provided in Dataset S1). Of these, common variants of
PGR [17] and MMP8 [18] have previously been found to
contribute to preterm birth risk. Using criterion agnostic to
possible involvement with preterm birth, and measuring genome-
wide changes, we identified 175 genes either accelerated along the
human (40 genes) or on the human and human-chimpanzee
Figure 1. Allometric analysis of brain size, body size, and gestational length by linear regression. Brain to body weight ratios for adults
(A) and neonates (B) are shown for humans (red), other higher primates (blue), and other mammals (black). The black line shows least squares fits to
the 91 mammalian species. Neonatal brain (C) and body size (D) to gestational time ratios are displayed for the same species. The blue line shows
least squares fits to 15 higher primate species. Allometric data was acquired by Sacher and Staffeldt (1974) [15].
doi:10.1371/journal.pgen.1001365.g001
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ancestor lineages combined (135 genes) at a 5% false discovery
rate (FDR) [19] from this analysis of protein-coding sequences.
Motivated by this evide nce of protein coding region evolution
for genes involved in parturition and th at acceleration h as also
been found to act on noncoding regions, we developed a method
to identify human accelerated noncoding sequences [11,20]. We
identified a total of 401 elements sign ifica nt along the human
lineage and 2,1 03 element s significan t along the human and
human-chimpa nzee ancest or line ages at a 5% FDR. To choose
candidate genes, we calculated gene-wise p-values for each gene
locus by assigning each conserved element to its nearest RefSeq
gene [21] and a Fisher’s combined p-value across the locus. This
resulted in iden tification of a t otal of 279 ca ndidate genes
(complete analysis of human accelerated non-coding regions
provided in Dataset S2). 1 50 of the g enes iden tified as huma n
accelerated in the protein-coding sequence and highly con-
served noncoding elements scre ens, selected based on express ion
and functional information suggestin g pote ntial r oles in
parturition, were analyzed for association with preterm birth
(Table S2).
Association analysis of human accelerated genes
Because recent data suggests that heritability of risk of preterm
birth acts largely through the maternal genome [14,16,22] and the
Finnish have low environmental risk and high genetic homoge-
neity compared to other populations, we genotyped Finnish (165
case, 163 control) mothers for 8,490 SNPs in the gene regions of
our prioritized list of 150 human accelerated genes. The most
significant finding was rs6741370 (p = 8.1610
25
) in the follicle-
stimulating hormone (FSH) receptor gene (FSHR). 91 SNPs were
significant at the p,0.01 level by allelic tests (Table S3). However,
no SNPs were significant after correcting for 5,377 independent
tests, considering relationships among markers, by the Bonferroni
method (p,9.3610
26
). Of note, 8 of the 10 most statistically
significant SNPs were located in FSHR. We identified FSHR as
human accelerated in the noncoding analysis, with 40 changes in
4,218 bp of 17 conserved elements (human lineage p = 5.4610
25
,
Dataset S2). Moreover, FSHR was revealed as rapidly evolving in a
study of noncoding conserved elements by Prabhakar and
colleagues [20], which otherwise had limited overlap with our
gene list (see Methods). FSHR also harbors SNPs with extreme iHS
Figure 2. Phylogenetic analysis of brain size, body size, and gestational length in primates. Gestational time to neonatal brain (A) and
neonatal body size (B) natural logarithm-transformed ratios are shown for each species and color coded along each lineage as inferred by parsimony.
Allometric data was acquired by Sacher and Staffeldt (1974) [15] and phylogeny by Purvis [41].
doi:10.1371/journal.pgen.1001365.g002
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values in the Yoruban population, reflecting extended haplotype
homozygosity and suggesting a recent selective sweep [23]. Bird
and colleagues [24] identified a region less than 1 megabase
downstream of the FSHR gene boundaries as rapidly evolving in
their study, further supporting human acceleration of the locus.
Finally, because of being paralogous with other G-protein coupled
receptors, such as the luteinizing hormone receptor, FSHR was
excluded from our genome-wide coding region analysis. There-
fore, we separately analyzed FSHR coding region acceleration
along the human lineage. We found that the human-specific dN/
dS was 1.41 which was significantly accelerated (p = 0.0045) in
comparison to a constrained model for other primates and
mammals using a 5 way multi-Z alignment in HYPHY where dN/
dS was 0.174 over the entire tree (human, chimpanzee, rhesus,
dog, mouse). The human-specific dN/dS for FSHR greater than 1
provides evidence for recent positive selection in addition to rate
acceleration in humans. This information, together with the
known importance of variation in human FSHR in subfertility
[25,26], a risk factor for preterm delivery independent of the use of
assisted reproductive technologies [27,28], and evidence suggest-
ing its expression in uterus and cervix [29,30,31], motivated its
specific study.
11 SNPs in FSHR showing potential association in the screening
analysis (p,0.1) were genotyped in European American (147
preterm, 157 control), African American (79 cases, 171 controls)
and Hispanic (Mexican) American (73 preterm, 292 control)
mothers (Table 2 and Table S4). Several SNPs exhibited
suggestive association (p,0.01) with preterm birth risk. Three
SNPs in the African American mothers, rs11686474, rs11680730
and rs12473815, were significant after correcting for multiple
testing (OR 1.63–1.82 (95% CI 1.11–1.21), 10 independent tests;
p#0.005). The allele frequency for this high linkage disequilibrium
block differs considerably between HapMap CEU and YRI
populations. To determine whether this association reflects a
functional effect of local variation and not an artifact of population
stratification with greater African ancestry in the case population
relative to controls, we analyzed a limited set of ancestry
informative markers using STRUCTURE. We found a small
number of individuals (10, 3 cases and 7 controls) in our African
American cohort that grouped more closely with the HapMap
CEU cluster than the HapMap YRI cluster, though the relative
distribution of these between cases and controls did not statistically
differ from the relative sizes of the group. We performed a logistic
analysis including the quantitative measure of CEU clustering as a
covariate. The CEU cluster value was not significant in the model
(p = 0.77), and adjusting for this in the regression model had little
effect on statistical significance (e.g., unadjusted allelic p-value for
rs12473815 = 0.0032, adjusted p = 0.0047). While we do not find
Table 1. Sample of candidate genes showing coding region rate acceleration in humans.
Human Human-chimpanzee ancestor
Gene Expected Ratio
a
Observed Ratio p-value
b
Expected Ratio
a
Observed Ratio p-value
b
OXT Oxytocin-neurophysin 1 precursor 0.25 1.47 0.017 0.16 0.37 0.546
PTGER4
c
Prostaglandin E2 receptor, EP4 0.49 1.10 0.018 0.33 0.33 0.539
ESR1 Estrogen receptor 0.22 0.55 0.020 0.15 0.13 0.216
NR2C1 Orphan nuclear receptor TR2 0.36 0.93 0.024 0.24 0.22 0.818
NTF3
d
Neurotrophin-3 precursor 0.29 0.60 0.042 0.26 0.15 0.439
OXTR Oxytocin receptor 0.13 0.43 0.048 0.16 0.20 0.168
PGR
d
Progesterone receptor 0.24 0.68 0.048 0.27 0.31 0.127
PAPPA
d
Pregnancy-associated plasma protein-A 0.30 0.29 0.099 0.22 0.34 1.79610
28
MMP8 Matrix metalloproteinase-8 0.51 0.67 0.230 0.54 0.83 3.94610
24
a The ratio reported is the ratio of the nonsynonymous to synonymous substitutions (dN/dS) for coding sequence.
b The p-value reported is from the likelihood ratio test comparing the rate on the human or the human plus the human-chimpanzee ancestral lineage to the expected
rate from the background model.
c Gene identified as rapidly evolving b y Arbiza and colleagues [49].
d Gene also was identified as rapidl y evolving by Clark and colleagues [9].
doi:10.1371/journal.pgen.1001365.t001
Table 2. Demographic profile of study populations.
European American African American Finnish Hispanic
Variable Case Control Case Control Case Control Case Control
Age (years) 27 (6.45) 28 (5.79) 25 (5.15) 24 (5.61) 30 (4.93) 31 (4.50) 25 (6.28) 23 (5.90)
BMI* 25.74 (6.80) 24.41 (5.94) 24.96 (8.87) 28.27 (7.06) 22.10 (4.20) 22.00 (3.38) 22.67 (6.55) 24.03 (6.11)
Gravidity 2 (1.42) 2 (1.50) 2 (1.55) 2 (1.72) 2 (1.38) 2 (1.08) 2 (1.37) 2 (1.55)
Gestational Age (days)** 241 (22.27) 274 (7.23) 244 (24.61) 273 (7.05) 242 (13.64) 282 (6.35) 251 (13.79) 277 (8.75)
Birthweight (grams)** 2196 (745.12) 3446 (553.89) 2305 (719.23) 3200 (423.32) 2400 (506.16) 3610 (423.24) 2627.50 (567.67) 3415 (467.30)
All values median (standard deviation).
*Differs significantly by nonparametric independent-samples median test in only the African American dataset.
**Differs significantly by nonparametric independent-samples median test in all datasets.
doi:10.1371/journal.pgen.1001365.t002
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evidence that population substructure confounds the association
study in our African American cohort, we acknowledge that
further study exploiting a larger number of subjects along with
more dense ancestry markers will be needed for definitive
conclusions to be drawn regarding association in this population.
We did not find a statistically significant association in our
European American or Hispanic cohorts for this LD block in
FSHR, though risk trends for the minor allele (OR 1.08–1.38) were
in the same direction as the Finnish and African American
populations. This finding may reflect the limited sample size
analyzed, or a specific role for variants in this LD block in the
genetically isolated, homogeneous Finnish population and ances-
trally distinct African American population.
In FSHR, these 4 SNPs in high LD lie within intron 2 of FSHR
(Figure 3) and show little LD with variants outside of this intron,
based on available information from the International HapMap
Project database [32]. Variants in this intron may tag yet
uncharacterized variants in coding regions or nearby regu latory
sequences. Alternatively, an intronic variant in FSHR may affect
risk directly by altering fu nctional sequence s contained within
the intron, such as microRNA binding sites, splice regulatory
sites or transcription regulation sites. For instance, a variant in a
splice enhancer site may change splicing patterns in favor of
transcripts that promote preterm birth risk, as several alterna-
tively spli ced FSHR isoforms have been observed with altered
funct ion [33]. Further suggesting functional importance of this
LD block, rs12473870 is signi ficantly associa ted (p,0.0001) with
altered expression of CCNJ, FURIN, DDR1, TBCD10A, and
NAGA in quantitative trait databases for YRI populations
(http://scan.bsd.uchicago.edu/newinterface/about.html). Risk-
promoting variation in this gene may contribute to birth timing,
rather than size at birth, ba sed on additional tests examining
gestational age or birth-weight Z-score as a quantitative tr ait,
rather than preterm birth affection status (Table S5). Hence,
FSHR may repr esent a novel gene involved in birth timing and
preterm birth risk.
FSHR encodes the follicle-stimulating hormone (FSH) receptor.
FSH is secreted from the pituitary and, in females, acts primarily
on receptors in the ovaries to stimulate follicle development and
synthesis of estrogens. Investigators also have observed FSHR
protein and mRNA expression in nongonadal tissues, including
uterus and cervix [29,30,31]. In these tissues, FSHR may mediate
uterine relaxation, as suggested by FSH’s ability to modify
electrical signaling in the myometrium, independent of estrogen
and progesterone [29]. Padmanabhan and colleagues [34] noted a
progressive rise in bioactive serum FSH levels during pregnancy.
Figure 3. Overview of the SNPs tested in the
FSHR
gene region. The gene structure for FSHR is represented by an arrow in which black
rectangles designate 39 and 59 untranslated regions and dark grey rectangles designate coding exons. Diamonds represent SNPs on the Affymetrix
SNP 6.0 array examined in the Finnish cohort. Triangles represent SNPs tested in the replication cohorts. A star indicates rs12473815, and the LD block
that includes rs11686474 and rs11680730, which is significant after multiple testing correction in African Americans (p#0.005). Circles represent
conserved elements examined in the region.
doi:10.1371/journal.pgen.1001365.g003
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Because high levels of FSH are known to downregulate FSHR
expression [35], increasing levels of FSH may lead to gradual
desensitization to the hormone and resultant increase in
contractility as term approaches. Additionally, evidence from the
FSHR haploinsufficient mouse [36] suggests that FSHR levels
affect the relative abundance of progesterone receptor isoforms A
(PR-A) and B (PR-B). Increased PR-A: PR-B ratios, occurring in
human pregnancy normally near term and observed in FSHR
haploinsufficient mice in non-pregnant states, are correlated with
increased myometrium contractility. Hence, dysregulation of
FSHR may contribute to early uterine contractility and promote
preterm birth.
Aspects of our approach pose limitations on interpretation of
this work. First, we assigned conserved elements to the nearest
RefSeq gene to calculate gene-wise p-values; however, conserved
elements may not be associated with the nearest gene per se,
potentially affecting the accuracy of the estimate gene-wise
p-values. Additionally, because we use adjacent genes to estimate
expected synonymous and nonsynonymous rates for a given locus,
human accelerated genes that are located physically nearby other
genes undergoing human acceleration, such as gene families with
multiple members in the same region, may miss detection. The
variability in number of probes represented on the Affymetrix
Genome-Wide Human SNP Array 6.0 within the gene regions of
the 150 human accelerated genes tested poses another limitation.
Although the coverage is adequate for most human accelerated
genes, there are some genes with too few probes tested to support
or refute their potential association with preterm birth; as a result,
this study may have failed to detect association between preterm
birth and human accelerated genes underrepresented on this
genotyping array. Lastly, while precedence exists for intronic
variants affecting protein structure and function [37,38], addi-
tional study is needed to prove whether any of the SNPs associated
with preterm birth in this work have a functional effect.
We find that human gestational length has been altered relative to
other non-human primates and mammals. Using allometric scaling,
we demonstrate that human gestation is shorter than predicted
based upon gestational length in other mammalian species. By using
comparative genomics to identify genes with an accelerated rate of
change in humans, we identified a gene that shows evidence of
association with preterm birth that otherwise would not have been
revealed by current models of parturition physiology [39].
Moreover, our approach exploits a filter for relevant genes based
upon rate of evolution in humans to more efficiently utilize currently
available datasets for preterm birth, which are probably under-
powered to detect variants of effect sizes reported in GWAS of other
complex traits. Our approach represents an alternative method for a
priori gene discovery in which fewer comparisons are made than in
GWAS, thus potentially retaining more power to detect effect sizes
typical for common variants. We provide evidence that FSHR,
identified by these means, may alter risk for preterm birth. We
anticipate that other human accelerated genes will similarly be
associated with preterm birth risk and elucidate the essential
pathways for human parturition.
Materials and Methods
Allometric analysis
Data acquired by Sacher and Staffeldt [15] was used to examine
the relationships among brain size, body size and gestation length
among mammalian species. Specifically, we compared logarithm-
transformed values for these traits between human, primate and
non-primate mammals, using linear regression implemented in R
[40]. Additionally, we used allometric data from this paper and the
primate phylogeny delineated by Purvis [41] to trace the evolution
of gestation-neonatal body size ratio, and gestation-neonatal brain
size ratio, using Mesquite [42]. Given a phylogenic tree, the
Mesquite method uses parsimony to reconstruct the ancestral
states by assuming a squared change for a continuous character
from state x to state y is (x–y)
2
.
Coding sequence multiple sequence alignments
We obtained a set of 10,639 human gene predictions from the
ENSEMBL database with one-to-one orthologs in the chimpan-
zee, macaque, mouse, rat, dog, and cow genomes (Release 46)
[43]. We limited our analysis to only those proteins where the
human, chimpanzee, macaque, and at least 75% of the
mammalian genomes were present (Text S1). The list of 120
possible candidate genes for preterm birth assessed for dN/dS
included those in the Institute of Medicine report [39], SPEED
(pregnancy), GeneCards (parturition), and progesterone/prosta-
glandin metabolic pathways.
Noncoding sequence multiple sequence alignments
We obtained a set of highly conserved elements from UCSC
Genome Browser [44] and tested 443,061 noncoding sequences
with a conservation score . = 400. From the 17-way MultiZ
alignments that are publicly available (downloaded March, 2007)
[45], we extracted the human, chimpanzee, macaque, mouse, rat,
dog and cow sequences (Text S1).
Likelihood ratio tests
We used the phylogeny ((Human, Chimpanzee), Macaque),
((Mouse, Rat), (Dog, Cow))). The evolutionary models were
implemented in the HYPHY package [46] and we used the Q-
value software [19] to establish statistical thresholds to achieve 5%
false discovery rates (p-value distributions and pi_0 values in
Figure S2).
Previous studies of both coding [9,46] and noncoding [11,21]
sequences identify regions evolving under positive selection by a
rate of evolution faster than a neutral rate. However, we felt that
this criterion is too restrictive since some genes may have an
increased rate of evolution along the human lineage relative to
other mammals, but not increased above the neutral rate. To
include genes with a significantly increased rate in humans
compared to other mammals for testing in a population association
study, we identify genes as human accelerated by testing whether
omega along the human (or human+human-chimpanzee ancestor)
lineage is significantly higher than omega along the non-human
lineages (or non-human+non-human-chimpanzee ancestor). Here,
omega is dN/dS-adj or dNC/dNC-adj, where dNC is the
noncoding rate and dS-adj and dNC-adj are the adjacent
synonymous rates from the 10 upstream and 10 downstream
genes and the adjacent noncoding rates from 25 kb of conserved
noncoding sequences, respectively. Thus, we test whether the data
is more likely under a model with 1 omega value or 2 omega
values (Figure S1). The coding sequence model used the
MG946HKY85 [47] model of codon evolution. The noncoding
sequences model used an HKY85 model. For both tests, the
alternative model has one additional degree of freedom and the
significance of the change in likelihood was determined using chi-
squared statistics. Both models use adjacent coding or conserved
noncoding sequences to estimate the expectation for a given
sequence that accounts for variable mutation rates across the
genome and lineage-specific differences in effective population
size, by allowing for branch-specific differences in selective
constraint. Our list of human accelerated coding region gene list
showed low overlap with previous studies that required for dN/
Human Evolution and Preterm Birth
PLoS Genetics | www.plosgenetics.org 7 April 2011 | Volume 7 | Issue 4 | e1001365
Page 7
dS.1 in their analyses (6% with Clark et al. [9], 0% Nielson et al.
[48]) and more overlap with Arbiza et al. [49] (26%) which
considered rate acceleration on the human lineage by methods
more similar to ours than those used by [9,48] (Figure S3). For
human accelerated conserved noncoding elements in humans,
22% of the elements we identified were in common with
Prabhakar et al. [20]. Considering unique genes associated with
human accelerated conserved noncoding elements in humans,
11% of our genes also were identified by Prabhakar et al. [20], and
4% identified by Pollard et al. [11]. Similar to our study, 4% of
unique genes in the Prabhakar study overlapped with those
identified by Pollard et al. (Figure S4).
We calculated gene-wise p-values for each gene locus by
assigning each conserved element to its nearest RefSeq gene [21]
and a Fisher’s combined p-value across the locus. Chi-squared
analysis was used to determine the statistical significance of
observed and expected genes with p,0.05 in suggested preterm
birth candidate and overall human gene lists.
Candidate human accelerated gene list
To minimize the number of te sts we wo uld perform and
thereby retain more power to detect small effects, we selected a
subset of genes likely to be involved in parturition, based on
expression and functional informa tion, to use as candidate
genes. Duplicated genes from a list developed by Bailey and
colleagues [50] identified as pregnan cy, fetal , placent al or
hormone-related genes were also included as candidates. A total
of 150 of genes were used as candidate g enes in subs equent
analysis (Table S2).
Human subjects
Mothers of preterm or term infants were en rolled for gene tic
analysis by methods approved by Institutional Review Boards/
Ethics Committees at each participating institution. Informed
consent was obtained for all participants. Mothers with preterm
birth were included if the birth was spontaneous (non-iatrogenic),
singleton, had no obvious precipitatin g stimulus (trauma,
infection, drug use), and was less the 37 weeks (Yale Uni versity;
New York University) or 36 weeks (University of Helsinki;
University of Oulu; Centennial Hospital, Nashville, TN) of
compl eted gestation. DNA from blood or saliva was prepared by
standard methods. Race/ethnicity was assigned by self-report.
For the African American cohort, no differences in allele
frequency were found in the distribution of 24 ancestry
informative markers selected across the genome comparing cases
and controls (all p.0.05 performing Chi square analysis between
cases and controls; data not shown). All specimens were linked
with demographi c and med ical data abstracted from maternal/
neonatal records.
Genotyping
Initial genotyping of the Finnish cohort was performed using the
Affymetrix Genome-Wide Human SNP Array 6.0. Genotypes
were called from cell intensity data by the birdseed v2 algorithm,
implemented in Affymetrix Genotyping Console 3.0. We selected
SNPs represented on the array within the gene regions of
candidate genes for analysis. SNPs examined in replication cohorts
were genotyped using the Sequenom iPLEX massARRAY
technology (Sequenom, San Diego, CA).
Data analysis
Data cleaning and analysis was performed with Whole-genome
Association Study Pipeline (WASP) [51] and PLINK [52]. We
excluded individuals in the Affymetrix Genome-Wide Human
SNP Array 6.0 analysis based on genotyping quality (,95% call
rate) and possible cryptic relatedness, and SNPs based on the
following criteria: not in Hardy-Weinberg Equilibrium in controls
(p,0.001 chi-squared test), ,95% genotype call rate, minor allele
frequency (MAF) ,0.05, duplicate probes. Our primary analysis
considered preterm birth affection status (i.e. delivery ,36 weeks)
as a binary trait, comparing allele and genotype frequencies
between case and control groups by chi-squared test. We also
examined gestational age and birth-weight Z-score as quantitative
traits, standardized to normal distributions (m =0, s = 1) using a
Wald test to compare the mean phenotype between different allele
or genotype classes. We corrected for multiple testing using the
simpleM method [53], which estimates the number of indepen-
dent tests, given the LD relationships among SNPs, used to adjust
the significance level. Genetic ancestry in the African American
population was inferred using STRUCTURE 2.3.1 [54] and the
available ancestry informative markers that had been genotyped.
Assuming K = 4 with the admixture function on and allowing
10,000 iterations and 10,000 burn-in cycles, genetic ancestry was
determined for study samples using unrelated individuals from
Hapmap Phase 3 (112 CEU, 113 YRI, and 48 ASW) as learning
populations for STRUCTURE.
Supporting Information
Dataset S1 Complete Coding Screen Analysis.
Found at: doi:10.1371/journal.pgen.1001365.s001 (15.64 MB XLS)
Dataset S2 Complete Non-Coding Screen Analysis.
Found at: doi:10.1371/journal.pgen.1001365.s002 (9.86 MB XLS)
Figure S1 Evolution Model. A likelihood ratio test to identify
lineage specific constraints. For each gene of interest, we use the
ten upstream and downstream genes to estimate a regional
synonymous rate (dSr) and the expected lineage-specific constraint
scaling factors (a). These scaling factors take into account that the
constraint on each lineage will vary due to the effective population
size and other species-specific parameters. Using these regional
parameters, a gene-specific dN/dS ratio (w) is estimated. In this
case, the lineage of interest leads to extant species C. In the null
model, the nonsynonymous substitution rate is estimated as
aCwndSr. This is compared to the alternative model, where
nonsynonymous branch length is set to a free parameter (R).
Found at: doi:10.1371/journal.pgen.1001365.s003 (0.91 MB TIF)
Figure S2 Distributions of p-values for coding and noncoding
screens used to determine false discovery rate thresholds for
significance. Panel A depicts the distribution of p-values for test for
significant rate acceleration on human lineage compared to other
mammalian lineages for coding sequences. Panel B depicts the
distribution of p-values for test for significant rate acceleration on
human-chimpanzee lineage compared to other mammalian
lineages for coding sequences. Panel C depicts the distribution of
gene-wise p-values for test for significant rate acceleration on
human lineage compared to other mammalian lineages for
noncoding sequences.
Found at: doi:10.1371/journal.pgen.1001365.s004 (0.24 MB PDF)
Figure S3 Venn diagram illustrating the overlap between the
results of our coding analysis and similar studies. Genes identified
by Arbiza et al. [49], Clark et al. [9], Nielson et al. [48] are
compared to genes we identified as accelerated on the human
lineage (10% FDR, Panel A) or on the human+human-
chimpanzee ancestor lineage (5% FDR, Panel B). Panel C depicts
the overlap between genes we identified as accelerated on the
Human Evolution and Preterm Birth
PLoS Genetics | www.plosgenetics.org 8 April 2011 | Volume 7 | Issue 4 | e1001365
Page 8
human lineage (10% FDR) or on the human+human-chimpanzee
ancestor lineage (5% FDR).
Found at: doi:10.1371/journal.pgen.1001365.s005 (0.66 MB PDF)
Figure S4 Venn diagram illustrating the overlap between the
results of our noncoding analysis and similar studies. Unique genes
identified by Pollard et al. [11] and Prabhakar et al. [20] are
compared to genes we identified as accelerated on the human
lineage (10% FDR).
Found at: doi:10.1371/journal.pgen.1001365.s006 (0.27 MB PDF)
Table S1 List of species used in allometric analysis.
Found at: doi:10.1371/journal.pgen.1001365.s007 (0.02 MB
XLS)
Table S2 Candidate human accelerated genes examined for
association with preterm birth.
Found at: doi:10.1371/journal.pgen.1001365.s008 (0.13 MB PDF)
Table S3 SNPs in the human accelerated gene regions tested
with p-values,0.01 in the Finnish cohort.
Found at: doi:10.1371/journal.pgen.1001365.s009 (0.13 MB PDF)
Table S4 SNPs in the FSHR gene region tested across Finnish
and 3 independent US populations.
Found at: doi:10.1371/journal.pgen.1001365.s010 (0.13 MB PDF)
Table S5 Comparison of association results for SNPs in the
FSHR gene region in Finnish mothers for the binary phenotype
preterm birth affection status and quantitative phenotypes
gestational age and birthweight Z-score.
Found at: doi:10.1371/journal.pgen.1001365.s011 (0.21 MB PDF)
Text S1 Supplementary Methods.
Found at: doi:10.1371/journal.pgen.1001365.s012 (0.15 MB PDF)
Acknowledgments
We thank the Microarray Core Facility at Washington University, Cara
Sutcliffe and Rachel Wiseman in the DNA Resources Core at Vanderbilt
University Medical Center for their assistance with genotyping, and Dr.
Dana Crawford for assistance with the STRUCTURE analysis.
Author Contributions
Conceived and designed the experiments: JP SD TM JF LM. Performed
the experiments: JP SD GO JJM MTO. Analyzed the data: JP SD TM
RM TLM JJM MTO IB JF LM. Contributed reagents/materials/analysis
tools: RH MH HP EK EN VS AP LP VF EAD BPC MTO KT LM.
Wrote the paper: JP TM MH RM EN IB JF LM.
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  • Source
    • "At the opposite end of the gestational age spectrum, the major genetic determinants of preterm birth (that could be used to diagnose or prevent prematurity) also have yet to be found [44], as a meta-analysis of the available studies has failed to support earlier associations of preterm birth with genetic loci [9,45,46]. These studies have included several single-nucleotide polymorphisms (SNPs) located within the follicle stimulating hormone receptor (FSHR) gene [47], a functional SNP in the promoter of the Serpin Peptidase Inhibitor, Clade H (Heat Shock Protein 47), Member 1 (SERPINH1) gene [48], and the type 1 insulin-like growth factor receptor (IGF1R) gene [49]. However, it has been shown that inclusion of very preterm infants (22–34 weeks) in the analysis by Lunde et al. resulted in a decrease in the estimated genetic effect on gestation, suggesting that the genetics of preterm, term, and post-term births may differ [9]. "
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    Full-text · Article · Oct 2014 · BMC Research Notes
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    • "In many mammals, including primates, the length of gestation appears to be limited by the energetic demand of the fetus in relation to maternal provision (Martin, 1996; Dunsworth et al., 2012). Although the precise mechanism for timing human birth remains elusive, and has been called 'the greatest unresolved question in reproductive biology' (Plunkett et al., 2011), the maternal or metabolic crossover hypothesis (Ellison, 2001) suggests that parturition occurs when the energy demands of the fetus threaten to exceed maternal capacity for supply. During pregnancy, a human mother's metabolic rate rises to twice her basal metabolic rate (BMR); by 9 months, fetal demand pushes maternal energy requirements close to 2.1 × BMR, and this coincides with the end of gestation (Dunsworth et al., 2012) (Fig. 1). "
    [Show abstract] [Hide abstract] ABSTRACT: Historically, paleoanthropology has focused on explaining human uniqueness. This review paper highlights several recent challenges to key features that have been considered to be exclusive to hominins, testing three long-standing theories in evolutionary anthropology. The knuckle-walking quadrupedalism model describes the evolution of modern gorillines, panins and hominins from a common, knuckle-walking ancestor. But the homology of knuckle-walking in African apes has been questioned. Although habitual bipedalism is unique to humans, it may have developed from occasional bipedalism in ancestors, without a quadrupedal stage. The obstetric dilemma seeks to explain the helplessness of human infants. The timing of human birth is seen as uniquely constrained by fetal head size and maternal pelvic width. An alternative hypothesis suggests that birth occurs when fetal demand for energy threatens to exceed maternal supply; this mechanism also appears to operate in other mammals. The expensive tissue hypothesis suggests that the expansion of energy-hungry brain tissue in hominins was offset by a reduction in gut tissue. But although large brains are correlated with both good quality diets and relatively short guts in primates, the causes of this correlation are not clear. An alternative suggestion is that the large human brain is paid for by savings in other functions, such as locomotion and reproduction, and that a concurrent expansion of low-cost adipose tissue in humans keeps metabolic rate low. In the past, paleoanthropology may have focused on defining a boundary between humans and animals, but recent research has seen a shift of focus to exploring humans as animals. Aspects of bipedalism, birth and brains have been considered to be exclusively human, but in the last few years even these have been eroded. It is the package of features that characterizes Homo sapiens that is unique.
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    • "Intriguingly, one of the rapidly evolving genes is the progesterone receptor, which might contribute to humans' lack of response to progesterone therapy compared to mice (Muglia and Katz, 2010). Rapid evolution has also been found in both the coding and a nearby noncoding region of FSHR (Plunkett et al., 2011 ). However, FSHR primarily functions in the establishment of pregnancy , rendering its association with preterm birth not only intriguing but also enigmatic. "
    [Show abstract] [Hide abstract] ABSTRACT: Adaptive evolution has provided us with a unique set of characteristics that define us as humans, including morphological, physiological and cellular changes. Yet, natural selection provides no assurances that adaptation is without human health consequences; advantageous mutations will increase in frequency so long as there is a net gain in fitness. As such, the current incidence of human disease can depend on previous adaptations. Here, I review genome-wide and gene-specific studies in which adaptive evolution has played a role in shaping human genetic disease. In addition to the disease consequences of adaptive phenotypes, such as bipedal locomotion and resistance to certain pathogens, I review evidence that adaptive mutations have influenced the frequency of linked disease alleles through genetic hitchhiking. Taken together, the links between human adaptation and disease highlight the importance of their combined influence on functional variation within the human genome and offer opportunities to discover and characterize such variation.
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