Abstract Existing models of parental investment have mainly focused on interactions at the level of the family, and have paid much less attention to the impact of population-level processes. Here we extend classical models of parental care to assess the impact of population structure and limited dispersal. We find that sex-differences in dispersal substantially affect the amount of care provided by each parent, with the more philopatric sex providing the majority of the care to young. This effect is most pronounced in highly viscous populations: in such cases, when classical models would predict stable biparental care, inclusion of a modest sex difference in dispersal leads to uniparental care by the philopatric sex. In addition, mating skew also affects sex-differences in parental investment, with the more numerous sex providing most of the care. However, the effect of mating skew only holds when parents care for their own offspring. When individuals breed communally, we recover the previous finding that the more philopatric sex provides most of the care, even when it is the rare sex. Finally, we show that sex-differences in dispersal can mask the existence of sex-specific costs of care, because the philopatric sex may provide most of the care even in the face of far higher mortality costs relative to the dispersing sex. We conclude that sex-biased dispersal is likely to be an important, yet currently overlooked driver of sex-differences in parental care.

Hybridization is known to occur in a wide range of avian species, yet the rate and persistence of hybridization on populations is often hard to assess. Genotyping using variable genetic marker sets has become a common tool to identify hybrid individuals, however assignment outputs can differ depending on the marker set used. Here, we study hybrid assignment in two sibling Hippolais warblers, where hybrid assignment has shown to differ between SSR and AFLP markers. Simulation of heterospecific individuals as well as backcrosses (typed using SSR markers) reveals a rapid loss of assignment probability in higher backcross generations. However, the characterization of F1 hybrids was clearly distinguished from both parental taxa. The differences in marker sets are not contradictory but complementary. The rate of hybridization is lower than previously expected with AFLP markers but introgression might be long-lasting. This could be either due to differences in power of the marker systems used or due to non-neutral variation covered by AFLP but not SSR markers. We call for more attention to be paid regarding the potential limits of classical marker systems to investigate hybridization and its persistence in natural systems.

Admixture-introduced linkage disequilibrium (LD) has recently been introduced into the inference of the histories of complex admixtures. However, the influence of ancestral source populations on the LD pattern in admixed populations is not properly taken into consideration by currently available methods, which affects the estimation of several gene flow parameters from empirical data. We first illustrated the dynamic changes of LD in admixed populations and mathematically formulated the LD under a generalized admixture model with finite population size. We next developed a new method, MALDmef, by fitting LD with multiple exponential functions for inferring and dating multiple-wave admixtures. MALDmef takes into account the effects of source populations which substantially affect modeling LD in admixed population, which renders it capable of efficiently detecting and dating multiple-wave admixture events. The performance of MALDmef was evaluated by simulation and it was shown to be more accurate than MALDER, a state-of-the-art method that was recently developed for similar purposes, under various admixture models. We further applied MALDmef to analyzing genome-wide data from the Human Genome Diversity Project (HGDP) and the HapMap Project. Interestingly, we were able to identify more than one admixture events in several populations, which have yet to be reported. For example, two major admixture events were identified in the Xinjiang Uyghur, occurring around 27???30 generations ago and 182???195 generations ago, respectively. In an African population (MKK), three recent major admixtures occurring 13???16, 50???67, and 107???139 generations ago were detected. Our method is a considerable improvement over other current methods and further facilitates the inference of the histories of complex population admixtures.

The stingless bee Tetragonisca angustula Latreille 1811 is one of the most widespread bee species in the Neotropics, distributed from Mexico to Argentina. However, this wide distribution contrasts with the low distance that females travel to build new nests whereas nothing is known about male dispersion. Previous studies of T. angustula were ambiguous concerning its genetic structure and were based only on nuclear markers and on small and/or limited sample size. Here we evaluate the genetic structure of several populations of T. angustula by using mitochondrial DNA and microsatellites. These markers can help us to detect differences in the migratory behavior between males and females. Our results showed that the populations were highly differentiated suggesting that both females and males are low dispersers. Therefore, its continental distribution might consist of several different taxa.

The Genome in a Bottle Consortium hosted by the National Institute of Standards and Technology, (NIST), is creating reference materials and data for human genome sequencing, as well as methods for genome comparison and benchmarking. Here, we describe a large, diverse set of sequencing data for seven human genomes; five are current or candidate NIST Reference Materials. The pilot genome, NA12878, has been released as NIST RM 8398. We also describe data from two Personal Genome Project trios, one of Ashkenazim Jewish ancestry and one of Asian ancestry. The data described come from 11 technologies: BioNano Genomics, Complete Genomics paired-end and LFR, Ion Proton exome, Oxford Nanopore, Pacific Biosciences, SOLiD, 10X Genomics GemCodeTM WGS, and Illumina paired-end, mate-pair, and synthetic long reads. Cell lines, DNA, and data from these individuals are publicly available and highly characterized. Therefore, we expect these data to be useful for revealing novel information about the human genome and improving sequencing technologies, SNP, indel, and structural variant calling, and de novo assembly.

Background A complete genome sequence and the advent of genome editing open up non-traditional model organisms to mechanistic genetic studies. The mosquito Aedes aegypti is an important vector of infectious diseases such as dengue, chikungunya, and yellow fever, and has a large and complex genome, which has slowed annotation efforts. We used comprehensive transcriptomic analysis of adult gene expression to improve the genome annotation and to provide a detailed tissue-specific catalogue of neural gene expression at different adult behavioral states. Results We carried out deep RNA sequencing across all major peripheral male and female sensory tissues, the brain, and (female) ovary. Furthermore, we examined gene expression across three important phases of the female reproductive cycle, a remarkable example of behavioral switching in which a female mosquito alternates between obtaining blood-meals from humans and laying eggs. Using genome-guided alignments and de novo transcriptome assembly, our re-annotation includes 572 new putative protein-coding genes and updates to 13.5% and 50.3% of existing transcripts within coding sequences and untranslated regions, respectively. Using this updated annotation, we detail gene expression in each tissue, identifying large numbers of transcripts regulated by blood-feeding and sexually dimorphic transcripts that may provide clues to the biology of male- and female-specific behaviors, such as mating and blood-feeding, which are areas of intensive study for those interested in vector control. Conclusions This neurotranscriptome forms a strong foundation for the study of genes in the mosquito nervous system and investigation of sensory-driven behaviors and their regulation. Furthermore, understanding the molecular genetic basis of mosquito chemosensory behavior has important implications for vector control.

Whole genome sequencing using high-throughput sequencing (HTS) technologies offers powerful opportunities to study genetic variation. Mapping the mutations responsible for different phenotypes is generally an involved and time-consuming process so researchers have developed user-friendly tools for mapping-by-sequencing, yet they are not applica- ble to organisms with non-sequenced genomes. We introduce SDM (SNP Distribution Method), a reference independent method for rapid discovery of mutagen-induced muta- tions in typical forward genetic screens. SDM aims to order a disordered collection of HTS reads or contigs such that the fragment carrying the causative mutation can be identified. SDM uses typical distributions of homozygous SNPs that are linked to a phenotype-altering SNP in a non-recombinant region as a model to order the fragments. To implement and test SDM, we created model genomes with an idealised SNP density based on Arabidop- sis thaliana chromosome 1 and analysed fragments with size distribution similar to reads or contigs assembled from HTS sequencing experiments. SDM groups the contigs by their normalised SNP density and arranges them to maximise the fit to the expected SNP distribution. We tested the procedure in existing datasets by examining SNP distributions in recent out-cross and back-cross experiments in Arabidopsis thaliana backgrounds. In all the examples we analysed, homozygous SNPs were normally distributed around the causal mutation. We used the real SNP densities obtained from these experiments to prove the efficiency and accuracy of SDM. The algorithm was able to successfully identify small sized (10-100 kb) genomic regions containing the causative mutation.

The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein’s rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces.

Barley was introduced to North America ~400 years ago but adaptation to modern production environments is more recent. Comparisons of allele frequencies among different growth habits and inflorescence types in North America indicate significant genetic differentiation has accumulated in a relatively short evolutionary time span. Allele frequency differentiation is greatest among barley with two-row versus six-row inflorescences, and then by spring versus winter growth habit. Large changes in allele frequency among breeding programs suggest a major contribution of genetic drift and linked selection on genetic variation. Despite this, comparisons of 3,613 modern North American cultivated breeding lines that differ for row type and growth habit permit the discovery of 183 SNP outliers putatively linked to targets of selection. For example, SNPs within the Cbf4, Ppd-H1, and Vrn-H1 loci which have previously been associated with agronomically-adaptive phenotypes, are identified as outliers. Analysis of extended haplotype-sharing identifies genomic regions shared within and among breeding programs, suggestive of a number of genomic regions subject to recent selection. Finally, we are able to identify recent bouts of gene flow between breeding programs that could point to the sharing of agronomically-adaptive variation. These results are supported by pedigrees and breeders understanding of germplasm sharing.