Error rates in - comparisons depend on genetic architecture and estimation procedures.

Genetic and phenotypic variation among populations is one of the fundamental subjects of evolutionary genetics. One question that arises often in data on natural populations is whether differentiation among populations on a particular trait might be caused in part by natural selection. For the past several decades, researchers have used approaches to compare the amount of trait differentiation among populations on one or more traits (measured by the statistic ) with differentiation on genome-wide genetic variants (measured by ).

Estimation of demography and mutation rates from one million haploid genomes.

As genetic sequencing costs have plummeted, datasets with sizes previously un-thinkable have begun to appear. Such datasets present new opportunities to learn about evolutionary history, particularly via rare alleles that record the very recent past. However, beyond the computational challenges inherent in the analysis of many large-scale datasets, large population-genetic datasets present theoretical problems.

On forensic likelihood ratios from low-coverage sequencing.

Advances in sequencing technology are allowing forensic scientists to access genetic information from increasingly challenging samples. A recently published computational approach, IBDGem, analyzes sequencing reads, including from low-coverage samples, in order to arrive at likelihood ratios for human identification. Here, we show that likelihood ratios produced by IBDGem are best interpreted as testing a null hypothesis different from the traditional one used in a forensic genetics context.

Evaluating ARG-estimation methods in the context of estimating population-mean polygenic score histories.

Scalable methods for estimating marginal coalescent trees across the genome present new opportunities for studying evolution and have generated considerable excitement, with new methods extending scalability to thousands of samples. Benchmarking of the available methods has revealed general tradeoffs between accuracy and scalability, but performance in downstream applications has not always been easily predictable from general performance measures, suggesting that specific features of the ARG may be important for specific downstream applications of estimated ARGs. To exemplify this point, we benchmark ARG estimation methods with respect to a specific set of methods for estimating the historical time course of a population-mean polygenic score (PGS) using the marginal coalescent trees encoded by the ancestral recombination graph (ARG).

Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations.

In both statistical genetics and phylogenetics, a major goal is to identify correlations between genetic loci or other aspects of the phenotype or environment and a focal trait. In these two fields, there are sophisticated but disparate statistical traditions aimed at these tasks. The disconnect between their respective approaches is becoming untenable as questions in medicine, conservation biology, and evolutionary biology increasingly rely on integrating data from within and among species, and once-clear conceptual divisions are becoming increasingly blurred.

Heritability within groups is uninformative about differences among groups: Cases from behavioral, evolutionary, and statistical genetics.

Without the ability to control or randomize environments (or genotypes), it is difficult to determine the degree to which observed phenotypic differences between two groups of individuals are due to genetic vs. environmental differences. However, some have suggested that these concerns may be limited to pathological cases, and methods have appeared that seem to give-directly or indirectly-some support to claims that aggregate heritable variation within groups can be related to heritable variation among groups.

Tree-based QTL mapping with expected local genetic relatedness matrices.

Understanding the genetic basis of complex phenotypes is a central pursuit of genetics. Genome-wide association studies (GWASs) are a powerful way to find genetic loci associated with phenotypes. GWASs are widely and successfully used, but they face challenges related to the fact that variants are tested for association with a phenotype independently, whereas in reality variants at different sites are correlated because of their shared evolutionary history.

Heritability within groups is uninformative about differences among groups: cases from behavioral, evolutionary, and statistical genetics.

Without the ability to control or randomize environments (or genotypes), it is difficult to determine the degree to which observed phenotypic differences between two groups of individuals are due to genetic vs. environmental differences. However, some have suggested that these concerns may be limited to pathological cases, and methods have appeared that seem to give-directly or indirectly-some support to claims that aggregate heritable variation within groups can be related to heritable variation among groups.

A likelihood-based framework for demographic inference from genealogical trees.

The demographic history of a population drives the pattern of genetic variation and is encoded in the gene-genealogical trees of the sampled alleles. However, existing methods to infer demographic history from genetic data tend to use relatively low-dimensional summaries of the genealogy, such as allele frequency spectra. As a step toward capturing more of the information encoded in the genome-wide sequence of genealogical trees, here we propose a novel framework called the genealogical likelihood (gLike), which derives the full likelihood of a genealogical tree under any hypothesized demographic history.

Microsatellites used in forensics are in regions enriched for trait-associated variants.

The 20 short tandem repeat (STR) loci of the combined DNA index system (CODIS) are the basis of the vast majority of forensic genetics in the United States. One argument for permissive rules about the collection of CODIS genotypes is that the CODIS loci are thought to contain little information about ancestry or traits. However, in the past 20 years, a growing field has identified hundreds of thousands of genotype-trait associations.

Amplification is the primary mode of gene-by-sex interaction in complex human traits.

Sex differences in complex traits are suspected to be in part due to widespread gene-by-sex interactions (GxSex), but empirical evidence has been elusive. Here, we infer the mixture of ways in which polygenic effects on physiological traits covary between males and females. We find that GxSex is pervasive but acts primarily through systematic sex differences in the magnitude of many genetic effects ("amplification") rather than in the identity of causal variants.

Tree-based QTL mapping with expected local genetic relatedness matrices.

Understanding the genetic basis of complex phenotypes is a central pursuit of genetics. Genome-wide Association Studies (GWAS) are a powerful way to find genetic loci associated with phenotypes. GWAS are widely and successfully used, but they face challenges related to the fact that variants are tested for association with a phenotype independently, whereas in reality variants at different sites are correlated because of their shared evolutionary history.

Microsatellites used in forensics are located in regions unusually rich in trait-associated variants.

The 20 short tandem repeat (STR) markers of the combined DNA index system (CODIS) are the basis of the vast majority of forensic genetics in the United States. One argument for permissive rules about the collection of CODIS genotypes is that the CODIS markers are thought to contain information relevant to identification only (such as a human fingerprint would), with little information about ancestry or traits. However, in the past 20 years, a quickly growing field has identified hundreds of thousands of genotype-trait associations.

Gattaca as a lens on contemporary genetics: marking 25 years into the film's "not-too-distant" future.

The 1997 film Gattaca has emerged as a canonical pop culture reference used to discuss modern controversies in genetics and bioethics. It appeared in theaters a few years prior to the announcement of the "completion" of the human genome (2000), as the science of human genetics was developing a renewed sense of its social implications. The story is set in a near-future world in which parents can, with technological assistance, influence the genetic composition of their offspring on the basis of predicted life outcomes.

Open practices in our science and our courtrooms.

Advocates of transparency in science often point to the benefits of open practices for the scientific process. Here, we focus on a possibly underappreciated effect of standards for transparency: their influence on non-scientific decisions. As a case study, we consider the current state of probabilistic genotyping software in forensics.

Skin deep: The decoupling of genetic admixture levels from phenotypes that differed between source populations.

Objectives: In genetic admixture processes, source groups for an admixed population possess distinct patterns of genotype and phenotype at the onset of admixture. Particularly in the context of recent and ongoing admixture, such differences are sometimes taken to serve as markers of ancestry for individuals-that is, phenotypes initially associated with the ancestral background in one source population are assumed to continue to reflect ancestry in that population. Such phenotypes might possess ongoing significance in social categorizations of individuals, owing in part to perceived continuing correlations with ancestry.

Attacks on genetic privacy via uploads to genealogical databases.

Direct-to-consumer (DTC) genetics services are increasingly popular, with tens of millions of customers. Several DTC genealogy services allow users to upload genetic data to search for relatives, identified as people with genomes that share identical by state (IBS) regions. Here, we describe methods by which an adversary can learn database genotypes by uploading multiple datasets.

Interpreting polygenic scores, polygenic adaptation, and human phenotypic differences.

Recent analyses of polygenic scores have opened new discussions concerning the genetic basis and evolutionary significance of differences among populations in distributions of phenotypes. Here, we highlight limitations in research on polygenic scores, polygenic adaptation and population differences. We show how genetic contributions to traits, as estimated by polygenic scores, combine with environmental contributions so that differences among populations in trait distributions need not reflect corresponding differences in genetic propensity.

Reconstructing the History of Polygenic Scores Using Coalescent Trees.

Genome-wide association studies (GWAS) have revealed that many traits are highly polygenic, in that their within-population variance is governed, in part, by small-effect variants at many genetic loci. Standard population-genetic methods for inferring evolutionary history are ill-suited for polygenic traits: when there are many variants of small effect, signatures of natural selection are spread across the genome and are subtle at any one locus. In the last several years, various methods have emerged for detecting the action of natural selection on polygenic scores, sums of genotypes weighted by GWAS effect sizes.

Statistical Detection of Relatives Typed with Disjoint Forensic and Biomedical Loci.

In familial searching in forensic genetics, a query DNA profile is tested against a database to determine whether it represents a relative of a database entrant. We examine the potential for using linkage disequilibrium to identify pairs of profiles as belonging to relatives when the query and database rely on nonoverlapping genetic markers. Considering data on individuals genotyped with both microsatellites used in forensic applications and genome-wide SNPs, we find that ∼30%-32% of parent-offspring pairs and ∼35%-36% of sib pairs can be identified from the SNPs of one member of the pair and the microsatellites of the other.

Consanguinity Rates Predict Long Runs of Homozygosity in Jewish Populations.

Objectives: Recent studies have highlighted the potential of analyses of genomic sharing to produce insight into the demographic processes affecting human populations. We study runs of homozygosity (ROH) in 18 Jewish populations, examining these groups in relation to 123 non-Jewish populations sampled worldwide.

Methods: By sorting ROH into 3 length classes (short, intermediate, and long), we evaluate the impact of demographic processes on genomic patterns in Jewish populations.