Yearly Archives: 2014

LD Score Regression Distinguishes Confounding from Polygenicity in Genome-Wide Association Studies

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LD Score Regression Distinguishes Confounding from Polygenicity in Genome-Wide Association Studies
Brendan Bulik-Sullivan, Po-Ru Loh, Hilary Finucane, Stephan Ripke, Jian Yang, Schizophrenia Working Group Psychiatric Genomics Consortium, Nick Patterson, Mark J Daly, Alkes L Price, Benjamin M Neale

Both polygenicity (i.e. many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield inflated distributions of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from bias and true signal from polygenicity. We have developed an approach that quantifies the contributions of each by examining the relationship between test statistics and linkage disequilibrium (LD). We term this approach LD Score regression. LD Score regression provides an upper bound on the contribution of confounding bias to the observed inflation in test statistics and can be used to estimate a more powerful correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of test statistic inflation in many GWAS of large sample size.

An experimentally determined evolutionary model dramatically improves phylogenetic fit

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An experimentally determined evolutionary model dramatically improves phylogenetic fit
Jesse D Bloom

All modern approaches to molecular phylogenetics require a quantitative model for how genes evolve. Unfortunately, existing evolutionary models do not realistically represent the site-heterogeneous selection that governs actual sequence change. Attempts to remedy this problem have involved augmenting these models with a burgeoning number of free parameters. Here I demonstrate an alternative: experimental determination of a parameter-free evolutionary model via mutagenesis, functional selection, and deep sequencing. Using this strategy, I create an evolutionary model for influenza nucleoprotein that describes the gene phylogeny far better than existing models with dozens or even hundreds of free parameters. High-throughput experimental strategies such as the one employed here provide fundamentally new information that has the potential to transform the sensitivity of phylogenetic analyses.

No evidence that natural selection has been less effective at removing deleterious mutations in Europeans than in West Africans

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No evidence that natural selection has been less effective at removing deleterious mutations in Europeans than in West Africans
Ron Do, Daniel Balick, Heng Li, Ivan Adzhubei`, Shamil Sunyaev, David Reich

Non-African populations have experienced major bottlenecks in the time since their split from West Africans, which has led to the hypothesis that natural selection to remove weakly deleterious mutations may have been less effective in non-Africans. To directly test this hypothesis, we measure the per-genome accumulation of deleterious mutations across diverse humans. We fail to detect any significant differences, but find that archaic Denisovans accumulated non-synonymous mutations at a higher rate than modern humans, consistent with the longer separation time of modern and archaic humans. We also revisit the empirical patterns that have been interpreted as evidence for less effective removal of deleterious mutations in non-Africans than in West Africans, and show they are not driven by differences in selection after population separation, but by neutral evolution.

Estimating the evolution of human life history traits in age-structured populations

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Estimating the evolution of human life history traits in age-structured populations

Ryan Baldini

I propose a method that estimates the selection response of all vital rates in an age-structured population. I assume that vital rates are determined by the additive genetic contributions of many loci. The method uses all relatedness information in the sample to inform its estimates of genetic parameters, via an MCMC Bayesian framework. One can use the results to estimate the selection response of any life history trait that is a function of the vital rates, including the age at first reproduction, total lifetime fertility, survival to adulthood, and others. This method closely ties the empirical analysis of life history evolution to dynamically complete models of natural selection, and therefore enjoys some theoretical advantages over other methods. I demonstrate the method on a simulated model of evolution with two age classes. Finally I discuss how the method can be extended to more complicated cases.

Mapping eQTL networks with mixed graphical Markov models

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Mapping eQTL networks with mixed graphical Markov models

Inma Tur, Alberto Roverato, Robert Castelo
(Submitted on 19 Feb 2014 (v1), last revised 29 Oct 2014 (this version, v5))

Expression quantitative trait loci (eQTL) mapping constitutes a challenging problem due to, among other reasons, the high-dimensional multivariate nature of gene-expression traits. Next to the expression heterogeneity produced by confounding factors and other sources of unwanted variation, indirect effects spread throughout genes as a result of genetic, molecular and environmental perturbations. From a multivariate perspective one would like to adjust for the effect of all of these factors to end up with a network of direct associations connecting the path from genotype to phenotype. In this paper we approach this challenge with mixed graphical Markov models, higher-order conditional independences and q-order correlation graphs. These models show that additive genetic effects propagate through the network as function of gene-gene correlations. Our estimation of the eQTL network underlying a well-studied yeast data set leads to a sparse structure with more direct genetic and regulatory associations that enable a straightforward comparison of the genetic control of gene expression across chromosomes. Interestingly, it also reveals that eQTLs explain most of the expression variability of network hub genes.

Migration and interaction in a contact zone: mtDNA variation among Bantu-speakers in southern Africa

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Migration and interaction in a contact zone: mtDNA variation among Bantu-speakers in southern Africa

Chiara Barbieri, Mário Vicente, Sandra Oliveira, Koen Bostoen, Jorge Rocha, Mark Stoneking, Brigitte Pakendorf

Bantu speech communities expanded over large parts of sub-Saharan Africa within the last 4000-5000 years, reaching different parts of southern Africa 1200-2000 years ago. The Bantu languages subdivide in several major branches, with languages belonging to the Eastern and Western Bantu branches spreading over large parts of Central, Eastern, and Southern Africa. There is still debate whether this linguistic divide is correlated with a genetic distinction between Eastern and Western Bantu speakers. During their expansion, Bantu speakers would have come into contact with diverse local populations, such as the Khoisan hunter-gatherers and pastoralists of southern Africa, with whom they may have intermarried. In this study, we analyze complete mtDNA genome sequences from over 900 Bantu-speaking individuals from Angola, Zambia, Namibia, and Botswana to investigate the demographic processes at play during the last stages of the Bantu expansion. Our results show that most of these Bantu-speaking populations are genetically very homogenous, with no genetic division between speakers of Eastern and Western Bantu languages. Most of the mtDNA diversity in our dataset is due to different degrees of admixture with autochthonous populations. Only the pastoralist Himba and Herero stand out due to high frequencies of particular L3f and L3d lineages; the latter are also found in the neighboring Damara, who speak a Khoisan language and were foragers and small-stock herders. In contrast, the close cultural and linguistic relatives of the Herero and Himba, the Kuvale, are genetically similar to other Bantu-speakers. Nevertheless, as demonstrated by resampling tests, the genetic divergence of Herero, Himba, and Kuvale is compatible with a common shared ancestry with high levels of drift and differential female admixture with local pre-Bantu populations.

Hierarchical Bayesian model of population structure reveals convergent adaptation to high altitude in human populations

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Hierarchical Bayesian model of population structure reveals convergent adaptation to high altitude in human populations

Matthieu Foll, Oscar E. Gaggiotti, Josephine T. Daub, Laurent Excoffier
(Submitted on 18 Feb 2014)

Detecting genes involved in local adaptation is challenging and of fundamental importance in evolutionary, quantitative, and medical genetics. To this aim, a standard strategy is to perform genome scans in populations of different origins and environments, looking for genomic regions of high differentiation. Because shared population history or population sub-structure may lead to an excess of false positives, analyses are often done on multiple pairs of populations, which leads to i) a global loss of power as compared to a global analysis, and ii) the need for multiple tests corrections. In order to alleviate these problems, we introduce a new hierarchical Bayesian method to detect markers under selection that can deal with complex demographic histories, where sampled populations share part of their history. Simulations show that our approach is both more powerful and less prone to false positive loci than approaches based on separate analyses of pairs of populations or those ignoring existing complex structures. In addition, our method can identify selection occurring at different levels (i.e. population or region-specific adaptation), as well as convergent selection in different regions. We apply our approach to the analysis of a large SNP dataset from low- and high-altitude human populations from America and Asia. The simultaneous analysis of these two geographic areas allows us to identify several new candidate genome regions for altitudinal selection, and we show that convergent evolution among continents has been quite common. In addition to identifying several genes and biological processes involved in high altitude adaptation, we identify two specific biological pathways that could have evolved in both continents to counter toxic effects induced by hypoxia.

Tracing evolutionary links between species

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Tracing evolutionary links between species

Mike Steel
(Submitted on 16 Feb 2014)

The idea that all life on earth traces back to a common beginning dates back at least to Charles Darwin’s {\em Origin of Species}. Ever since, biologists have tried to piece together parts of this `tree of life’ based on what we can observe today: fossils, and the evolutionary signal that is present in the genomes and phenotypes of different organisms. Mathematics has played a key role in helping transform genetic data into phylogenetic (evolutionary) trees and networks. Here, I will explain some of the central concepts and basic results in phylogenetics, which benefit from several branches of mathematics, including combinatorics, probability and algebra.

Evolutionary rates for multivariate traits: the role of selection and genetic variation

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Evolutionary rates for multivariate traits: the role of selection and genetic variation

William Pitchers, Jason B. Wolf, Tom Tregenza, John Hunt, Ian Dworkin

A fundamental question in evolutionary biology is the relative importance of selection and genetic architecture in determining evolutionary rates. Adaptive evolution can be described by the multivariate breeders’ equation (Δz = Gβ ), which predicts evolutionary change for a suite of phenotypic traits (Δz ) as a product of directional selection acting on them (β) and the genetic variance-covariance matrix for those traits (G). Despite being empirically challenging to estimate, there are enough published estimates of G and β to allow for synthesis of general patterns across species. We use published estimates to test the hypotheses that there are systematic differences in the rate of evolution among trait types, and that these differences are in part due to genetic architecture. We find evidence that sexually selected traits exhibit faster rates of evolution compared to life-history or morphological traits. This difference does not appear to be related to stronger selection on sexually selected traits. Using numerous proposed approaches to quantifying the shape, size and structure of G we examine how these parameters relate to one another, and how they vary among taxonomic and trait groupings. Despite considerable variation, they do not explain the observed differences in evolutionary rates.

A Novel Approach for Multi-Domain and Multi-Gene Family Identification Provides Insights into Evolutionary Dynamics of Disease Resistance Genes in Core Eudicot Plants

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A Novel Approach for Multi-Domain and Multi-Gene Family Identification Provides Insights into Evolutionary Dynamics of Disease Resistance Genes in Core Eudicot Plants

Johannes A. Hofberger, Beifei Zhou, Haibao Tang, Jonathan DG Jones, M. Eric Schranz

Recent advances in DNA sequencing techniques resulted in more than forty sequenced plant genomes representing a diverse set of taxa of agricultural, energy, medicinal and ecological importance. However, gene family curation is often only inferred from DNA sequence homology and lacks insights into evolutionary processes contributing to gene family dynamics. In a comparative genomics framework, we integrated multiple lines of evidence provided by gene synteny, sequence homology and protein-based Hidden Markov Modelling to extract homologous super-clusters composed of multi-domain resistance (R)-proteins of the NB-LRR type (for NUCLEOTIDE BINDING/LEUCINE-RICH REPEATS), that are involved in plant innate immunity. To assess the diversity of R-proteins within and between species, we screened twelve eudicot plant genomes including six major crops and found a total of 2,363 NB-LRR genes. Our curated R-proteins set shows a 50% average for tandem duplicates and a 22% fraction of gene copies retained from ancient polyploidy events (ohnologs). We provide evidence for strong positive selection acting on all identified genes and show significant differences in molecular evolution rates (Ka/Ks-ratio) among tandem- (mean=1.59), ohnolog (mean=1.36) and singleton (mean=1.22) R-gene duplicates. To foster the process of gene-edited plant breeding, we report species-specific presence/absence of all 140 NB-LRR genes present in the model plant Arabidopsis and describe four distinct clusters of NB-LRR ?gatekeeper? loci sharing syntelogs across all analyzed genomes. In summary, we designed and implemented an easy-to-follow computational framework for super-gene family identification, and provide the most curated set of NB-LRR genes whose genetic versatility among twelve lineages can underpin crop improvement.