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Sex-biased demography, including sex-biased survival or migration, can alter allele frequency changes across the genome. In particular, we can expect different patterns of genetic variation on autosomes and sex chromosomes due to sex-specific differences in life histories, as well as differences in effective population size, transmission modes, and the strength and mode of selection. Here, we demonstrate the role that sex differences in life history played in shaping short-term evolutionary dynamics across the genome. We used a 25-year pedigree and genomic dataset from a long-studied population of Florida Scrub-Jays (Aphelocoma coerulescens) to directly characterize the relative roles of sex-biased demography and inheritance in shaping genome-wide allele frequency trajectories. We used gene dropping simulations to estimate individual genetic contributions to future generations and to model drift and immigration on the known pedigree. We quantified differential expected genetic contributions of males and females over time, showing the impact of sex-biased dispersal in a monogamous system. Due to female-biased dispersal, more autosomal variation is introduced by female immigrants. However, due to male-biased transmission, more Z variation is introduced by male immigrants. Finally, we partitioned the proportion of variance in allele frequency change through time due to male and female contributions. Overall, most allele frequency change is due to variance in survival and births. Males and females make similar contributions to autosomal allele frequency change, but males make higher contributions to allele frequency change on the Z chromosome. Our work shows the importance of understanding sex-specific demographic processes in characterizing genome-wide allele frequency change in wild populations. [ABSTRACT FROM AUTHOR]

In a genetically admixed population, admixed individuals possess genealogical and genetic ancestry from multiple source groups. Under a mechanistic model of admixture, we study the number of distinct ancestors from the source populations that the admixture represents. Combining a mechanistic admixture model with a recombination model that describes the probability that a genealogical ancestor is a genetic ancestor, for a member of a genetically admixed population, we count genetic ancestors from the source populations—those genealogical ancestors from the source populations who contribute to the genome of the modern admixed individual. We compare patterns in the numbers of genealogical and genetic ancestors across the generations. To illustrate the enumeration of genetic ancestors from source populations in an admixed group, we apply the model to the African-American population, extending recent results on the numbers of African and European genealogical ancestors that contribute to the pedigree of an African-American chosen at random, so that we also evaluate the numbers of African and European genetic ancestors who contribute to random African-American genomes. The model suggests that the autosomal genome of a random African-American born in the interval 1960–1965 contains genetic contributions from a mean of 162 African (standard deviation 47, interquartile range 127–192) and 32 European ancestors (standard deviation 14, interquartile range 21–43). The enumeration of genetic ancestors can potentially be performed in other diploid species in which admixture and recombination models can be specified. [ABSTRACT FROM AUTHOR]

Restriction site-associated DNA sequencing or genotyping-by-sequencing (GBS) approaches allow for rapid and cost-effective discovery and genotyping of thousands of single-nucleotide polymorphisms (SNPs) in multiple individuals. However, rigorous quality control practices are needed to avoid high levels of error and bias with these reduced representation methods. We developed a formal statistical framework for filtering spurious loci, using Mendelian inheritance patterns in nuclear families, that accommodates variable-quality genotype calls and missing data--both rampant issues with GBS data--and for identifying sex-linked SNPs. Simulations predict excellent performance of both the Mendelian filter and the sex-linkage assignment under a variety of conditions. We further evaluate our method by applying it to real GBS data and validating a subset of high-quality SNPs. These results demonstrate that our metric of Mendelian inheritance is a powerful quality filter for GBS loci that is complementary to standard coverage and Hardy-Weinberg filters. The described method, implemented in the software MendelChecker, will improve quality control during SNP discovery in nonmodel as well as model organisms., (Copyright © 2014 by the Genetics Society of America.)