Powerful approaches to inferring recent or current population structure based on nearest neighbor haplotype “coancestry” have so far been inaccessible to users without high quality genome-wide haplotype data. With a boom in nonmodel organism genomics, there is a pressing need to bring these methods to communities without access to such data. Here, we present , a new program designed to infer the coancestry matrix from restriction-site-associated DNA sequencing (RADseq) data. We combine this program together with a previously published MCMC clustering algorithm into —a complete, easy to use, and fast population inference package for RADseq data (https://github.com/millanek/fineRADstructure; last accessed February 24, 2018). Finally, with two example data sets, we illustrate its use, benefits, and robustness to missing RAD alleles in double digest RAD sequencing.

Growing evidence shows that epigenetic mechanisms contribute to complex traits, with implications across many fields of biology. In plant ecology, recent studies have attempted to merge ecological experiments with epigenetic analyses to elucidate the contribution of epigenetics to plant phenotypes, stress responses, adaptation to habitat, and range distributions. While there has been some progress in revealing the role of epigenetics in ecological processes, studies with non-model species have so far been limited to describing broad patterns based on anonymous markers of DNA methylation. In contrast, studies with model species have benefited from powerful genomic resources, which contribute to a more mechanistic understanding but have limited ecological realism. Understanding the significance of epigenetics for plant ecology requires increased transfer of knowledge and methods from model species research to genomes of evolutionarily divergent species, and examination of responses to complex natural environments at a more mechanistic level. This requires transforming genomics tools specifically for studying non-model species, which is challenging given the large and often polyploid genomes of plants. Collaboration among molecular geneticists, ecologists and bioinformaticians promises to enhance our understanding of the mutual links between genome function and ecological processes.

Genetic variation that is generated by mutation, recombination, and gene flow can reduce the mean fitness of a population, both now and in the future. This 'genetic load' has been estimated in a wide range of animal taxa using various approaches.Advances in genome sequencing and computational techniques now enable us to estimate the genetic load in populations and individuals without direct fitness estimates. Here, we review the classic and contemporary literature of genetic load.We describe contemporary approaches to quantify the genetic load in whole genome sequence data based on evolutionary conservation and annotations. We show that splitting the load into its two componentsthe realized load (or expressed load) and

Survival and divergence in a small group: the extraordinary genomic history of the endangered Apennine brown bear stragglers 2 AbstractAbout 100 km east of Rome, in the Central Apennine mountains, a critically endangered population of approximately fifty brown bears live in complete isolation. Mating outside this population is prevented by several hundred kilometers of bear-free territories. We exploited this natural experiment to better understand the gene and genomic consequences of surviving at extremely small population size. First, we found that brown bear populations in Europe lost connectivity since Neolithic times, when farming communities expanded and forest burning was used for land clearance. In Central Italy, this resulted in a 40-fold population decline. The overall genomic impact of this decline included the complete loss of variation in the mitochondrial genome and along long stretches of the nuclear genome. Several private and deleterious amino acid changes were fixed by random drift; predicted effects include energy deficit, muscle weakness, anomalies in cranial and skeletal development, and reduced aggressiveness. Despite this extreme loss of diversity, Apennine bear genomes show non-random peaks of high variation, possibly maintained by balancing selection, at genomic regions significantly enriched for genes associated with immune and olfactory systems. Challenging the paradigm of increased extinction risk in small populations, we suggest that random fixation of deleterious alleles a) can be an important driver of divergence in isolation, b) can be tolerated when balancing selection prevents random loss of variation at important genes and c) is followed by or results directly in favorable behavioral changes. SignificanceA small and relict population of brown bears lives in complete isolation in the Italian Apennine mountains, providing a unique opportunity to study the impact of drift and selection on the genomes of a large endangered mammal and to reconstruct the phenotypic consequences and the conservation implications of such evolutionary processes. The Apennine bear is highly inbred and harbors very low genomic variation. Several deleterious mutations have been accumulated by drift. We found evidence that this is a consequence of habitat fragmentation in the Neolithic, when human expansion and land clearance shrank its habitat, and that retention of variation at immune system and olfactory receptor genes, as well as changes in diet and behavior, prevented the extinction of the Apennine bear.