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.

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.

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

Growing evidence makes a strong case that epigenetic mechanisms contribute to complex traits, with implications across many fields of biology from dissecting developmental processes to understanding aspects of human health and disease. In ecology, recent studies have merged ecological experimental design with epigenetic analyses to elucidate the contribution of epigenetics to plant phenotypes, stress response, adaptation to habitat, or species range distributions. While there has been some progress in revealing the role of epigenetics in ecological processes, many 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 allow for a more mechanistic understanding but have limited ecological realism. To understand the true significance of epigenetics for plant ecology and evolution, we must combine both approaches transferring knowledge and methods from model-species research to genomes of evolutionarily divergent species, and examining 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 between molecular epigeneticists, ecologists and bioinformaticians promises to enhance our understanding of the mutual links between genome function and ecological processes.All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

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.

Summary The mosaic distribution of interbreeding taxa with contrasting ecology and morphology offers an opportunity to study microevolutionary dynamics during ecological divergence. We investigate here the evolutionary history of an alpine and a montane ecotype of Heliosperma pusillum (Caryophyllaceae) in the south‐eastern Alps.From six pairs of geographically close populations of the two ecotypes (120 individuals) we obtained a high‐coverage restriction site associated DNA sequencing (RADseq) dataset that was used for demographic inference to test the hypothesis of parallel evolution of the two ecotypes.The data are consistent with repeated ecological divergence in H. pusillum, uncovering up to five polytopic origins of one ecotype from the other. A complex evolutionary history is evidenced, with local isolation‐with‐migration in two population pairs and intra‐ecotype migration in two others. In all cases, the time of divergence or secondary contact was inferred as postglacial. A metagenomic analysis on exogenous contaminant RAD sequences suggests divergent microbial communities between the ecotypes.The lack of shared genomic regions of high divergence across population pairs illustrates the action of drift and/or local selection in shaping genetic divergence across repeated cases of ecological divergence.

Epigenetic modifications are expected to occur at a much faster rate than genetic mutations, potentially causing isolated populations to stochastically drift apart, or if they are subjected to different selective regimes, to directionally diverge. A high level of genome‐wide epigenetic divergence between individuals occupying distinct habitats is therefore predicted. Here, we introduce bisulfite‐converted restriction site associated DNA sequencing (bsRADseq), an approach to quantify the level of DNA methylation differentiation across multiple individuals. This reduced representation method is flexible in the extent of DNA sequence interrogated. We showcase its applicability in three natural systems, each comprising individuals adapted to divergent environments: a diploid plant (Heliosperma, Caryophyllaceae), a tetraploid plant (Dactylorhiza, Orchidaceae) and an animal (Gasterosteusaculeatus, Gasterosteidae). We present a robust bioinformatic pipeline, combining tools for RAD locus assembly, SNP calling, bisulfite‐converted read mapping and DNA methylation calling to analyse bsRADseq data with or without a reference genome. Importantly, our approach accurately distinguishes between SNPs and methylation polymorphism (SMPs). Although DNA methylation frequency between different positions of a genome varies widely, we find a surprisingly high consistency in the methylation profile between individuals thriving in divergent ecological conditions, particularly in Heliosperma. This constitutive stability points to significant molecular or developmental constraints acting on DNA methylation variation. Altogether, by combining the flexibility of RADseq with the accuracy of bisulfite sequencing in quantifying DNA methylation, the bsRADseq methodology and our bioinformatic pipeline open up the opportunity for genome‐wide epigenetic investigations of evolutionary and ecological relevance in non‐model species, independent of their genomic features.

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