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High rate of extrapair paternity in a human population demonstrates diversity in human reproductive strategies.
Among nonhuman species, social monogamy is rarely accompanied by complete fidelity. Evolutionary theory predicts that the rate of extrapair paternity (EPP) should vary according to socioecological conditions. In humans, however, geneticists contend that EPP is negligible and relatively invariable. This conclusion is based on a limited set of studies, almost all of which describe European-descent groups. Using a novel, double-blind method designed in collaboration with a community of Himba pastoralists, we find that the rate of EPP in this population is 48%, with 70% of couples having at least one EPP child. Both men and women were very accurate at detecting cases of EPP. These data suggest that the range of variation in EPP across human populations is substantially greater than previously thought. We further show that a high rate of EPP can be accompanied by high paternity confidence, which highlights the importance of disaggregating EPP from the notion of "cuckoldry.
Inferring archaic introgression from hominin genetic data
Questions surrounding the timing, extent, and evolutionary consequences of archaic admixture into human populations have a long history in evolutionary anthropology. More recently, advances in human genetics, particularly in the field of ancient DNA, have shed new light on the question of whether or not Homo sapiens interbred with other hominin groups. By the late 1990s, published genetic work had largely concluded that archaic groups made no lasting genetic contribution to modern humans; less than a decade later, this conclusion was reversed following the successful DNA sequencing of an ancient Neanderthal. This reversal of consensus is noteworthy, but the reasoning behind it is not widely understood across all academic communities. There remains a communication gap between population geneticists and paleoanthropologists. In this review, we endeavor to bridge this gap by outlining how technological advancements, new statistical methods, and notable controversies ultimately led to the current consensu
The geography of recent genetic ancestry across Europe
The recent genealogical history of human populations is a complex mosaic
formed by individual migration, large-scale population movements, and other
demographic events. Population genomics datasets can provide a window into this
recent history, as rare traces of recent shared genetic ancestry are detectable
due to long segments of shared genomic material. We make use of genomic data
for 2,257 Europeans (the POPRES dataset) to conduct one of the first surveys of
recent genealogical ancestry over the past three thousand years at a
continental scale. We detected 1.9 million shared genomic segments, and used
the lengths of these to infer the distribution of shared ancestors across time
and geography. We find that a pair of modern Europeans living in neighboring
populations share around 10-50 genetic common ancestors from the last 1500
years, and upwards of 500 genetic ancestors from the previous 1000 years. These
numbers drop off exponentially with geographic distance, but since genetic
ancestry is rare, individuals from opposite ends of Europe are still expected
to share millions of common genealogical ancestors over the last 1000 years.
There is substantial regional variation in the number of shared genetic
ancestors: especially high numbers of common ancestors between many eastern
populations likely date to the Slavic and/or Hunnic expansions, while much
lower levels of common ancestry in the Italian and Iberian peninsulas may
indicate weaker demographic effects of Germanic expansions into these areas
and/or more stably structured populations. Recent shared ancestry in modern
Europeans is ubiquitous, and clearly shows the impact of both small-scale
migration and large historical events. Population genomic datasets have
considerable power to uncover recent demographic history, and will allow a much
fuller picture of the close genealogical kinship of individuals across the
world.Comment: Full size figures available from
http://www.eve.ucdavis.edu/~plralph/research.html; or html version at
http://ralphlab.usc.edu/ibd/ibd-paper/ibd-writeup.xhtm
Gene expression drives the evolution of dominance.
Dominance is a fundamental concept in molecular genetics and has implications for understanding patterns of genetic variation, evolution, and complex traits. However, despite its importance, the degree of dominance in natural populations is poorly quantified. Here, we leverage multiple mating systems in natural populations of Arabidopsis to co-estimate the distribution of fitness effects and dominance coefficients of new amino acid changing mutations. We find that more deleterious mutations are more likely to be recessive than less deleterious mutations. Further, this pattern holds across gene categories, but varies with the connectivity and expression patterns of genes. Our work argues that dominance arises as a consequence of the functional importance of genes and their optimal expression levels
Inference of population splits and mixtures from genome-wide allele frequency data
Many aspects of the historical relationships between populations in a species
are reflected in genetic data. Inferring these relationships from genetic data,
however, remains a challenging task. In this paper, we present a statistical
model for inferring the patterns of population splits and mixtures in multiple
populations. In this model, the sampled populations in a species are related to
their common ancestor through a graph of ancestral populations. Using
genome-wide allele frequency data and a Gaussian approximation to genetic
drift, we infer the structure of this graph. We applied this method to a set of
55 human populations and a set of 82 dog breeds and wild canids. In both
species, we show that a simple bifurcating tree does not fully describe the
data; in contrast, we infer many migration events. While some of the migration
events that we find have been detected previously, many have not. For example,
in the human data we infer that Cambodians trace approximately 16% of their
ancestry to a population ancestral to other extant East Asian populations. In
the dog data, we infer that both the boxer and basenji trace a considerable
fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to
domestication, and that East Asian toy breeds (the Shih Tzu and the Pekingese)
result from admixture between modern toy breeds and "ancient" Asian breeds.
Software implementing the model described here, called TreeMix, is available at
http://treemix.googlecode.comComment: 28 pages, 6 figures in main text. Attached supplement is 22 pages, 15
figures. This is an updated version of the preprint available at
http://precedings.nature.com/documents/6956/version/
Correlation function of null polygonal Wilson loops with local operators
We consider the correlator of a light-like polygonal Wilson loop
with n cusps with a local operator (like the dilaton or the chiral primary
scalar) in planar N =4 super Yang-Mills theory. As a consequence of conformal
symmetry, the main part of such correlator is a function F of 3n-11 conformal
ratios. The first non-trivial case is n=4 when F depends on just one conformal
ratio \zeta. This makes the corresponding correlator one of the simplest
non-trivial observables that one would like to compute for generic values of
the `t Hooft coupling \lambda. We compute F(\zeta,\lambda) at leading order in
both the strong coupling regime (using semiclassical AdS5 x S5 string theory)
and the weak coupling regime (using perturbative gauge theory). Some results
are also obtained for polygonal Wilson loops with more than four edges.
Furthermore, we also discuss a connection to the relation between a correlator
of local operators at null-separated positions and cusped Wilson loop suggested
in arXiv:1007.3243.Comment: 36 pages, 2 figure
The genetic prehistory of southern Africa
Southern and eastern African populations that speak non-Bantu languages with
click consonants are known to harbour some of the most ancient genetic lineages
in humans, but their relationships are poorly understood. Here, we report data
from 23 populations analyzed at over half a million single nucleotide
polymorphisms, using a genome-wide array designed for studying human history.
The southern African Khoisan fall into two genetic groups, loosely
corresponding to the northwestern and southeastern Kalahari, which we show
separated within the last 30,000 years. We find that all individuals derive at
least a few percent of their genomes from admixture with non-Khoisan
populations that began approximately 1,200 years ago. In addition, the east
African Hadza and Sandawe derive a fraction of their ancestry from admixture
with a population related to the Khoisan, supporting the hypothesis of an
ancient link between southern and eastern AfricaComment: To appear in Nature Communication
Routes for breaching and protecting genetic privacy
We are entering the era of ubiquitous genetic information for research,
clinical care, and personal curiosity. Sharing these datasets is vital for
rapid progress in understanding the genetic basis of human diseases. However,
one growing concern is the ability to protect the genetic privacy of the data
originators. Here, we technically map threats to genetic privacy and discuss
potential mitigation strategies for privacy-preserving dissemination of genetic
data.Comment: Draft for comment
Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders
Personality is influenced by genetic and environmental factors1
and associated with mental health. However, the underlying
genetic determinants are largely unknown. We identified six
genetic loci, including five novel loci2,3, significantly associated
with personality traits in a meta-analysis of genome-wide
association studies (N = 123,132–260,861). Of these genomewide
significant loci, extraversion was associated with variants
in WSCD2 and near PCDH15, and neuroticism with variants
on chromosome 8p23.1 and in L3MBTL2. We performed a
principal component analysis to extract major dimensions
underlying genetic variations among five personality traits
and six psychiatric disorders (N = 5,422–18,759). The first
genetic dimension separated personality traits and psychiatric
disorders, except that neuroticism and openness to experience
were clustered with the disorders. High genetic correlations
were found between extraversion and attention-deficit–
hyperactivity disorder (ADHD) and between openness and
schizophrenia and bipolar disorder. The second genetic
dimension was closely aligned with extraversion–introversion
and grouped neuroticism with internalizing psychopathology
(e.g., depression or anxiety)
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