Rates and spectra of de novo structural mutations in Chlamydomonas reinhardtii.

Genetic variation originates from several types of spontaneous mutation, including single-nucleotide substitutions, short insertions and deletions (indels), and larger structural changes. Structural mutations (SMs) drive genome evolution and are thought to play major roles in evolutionary adaptation, speciation, and genetic disease, including cancers. Sequencing of mutation accumulation (MA) lines has provided estimates of rates and spectra of single-nucleotide and indel mutations in many species, yet the rate of new SMs is largely unknown. Here, we use long-read sequencing to determine the full mutation spectrum in MA lines derived from two strains (CC-1952 and CC-2931) of the green alga Chlamydomonas reinhardtii The SM rate is highly variable between strains and between MA lines, and SMs represent a substantial proportion of all mutations in both strains (CC-1952 6%; CC-2931 12%). The SM spectra differ considerably between the two strains, with almost all inversions and translocations occurring in CC-2931 MA lines. This variation is associated with heterogeneity in the number and type of active transposable elements (TEs), which comprise major proportions of SMs in both strains (CC-1952 22%; CC-2931 38%). In CC-2931, a Crypton and a previously undescribed type of DNA element have caused 71% of chromosomal rearrangements, whereas in CC-1952, a Dualen LINE is associated with 87% of duplications. Other SMs, notably large duplications in CC-2931, are likely products of various double-strand break repair pathways. Our results show that diverse types of SMs occur at substantial rates, and support prominent roles for SMs and TEs in evolution.

purgeR: inbreeding and purging in pedigreed populations.

SUMMARY: Inbreeding depression and genetic purging are important processes shaping the survivability and evolution of small populations. However, detecting purging is challenging in practice, in part because there are limited tools dedicated to it. I present a new R package to assist population analyses on detection and quantification of the inbreeding depression and genetic purging of biological fitness in pedigreed populations. It includes a collection of methods to estimate different measurements of inbreeding (Wright's, partial and ancestral inbreeding coefficients) as well as purging parameters (purged inbreeding, and opportunity of purging coefficients). Additional functions are also included to estimate population parameters, allowing to contextualize inbreeding and purging these results in terms of the population demographic history. purgeR is a valuable tool to gain insight into processes related to inbreeding and purging, and to better understand fitness and inbreeding load evolution in small populations. AVAILABILITY AND IMPLEMENTATION: purgeR is an R package available at CRAN, and can be installed via install.packages("purgeR"). Source code is maintained at a GitLab repository (https://gitlab.com/elcortegano/purgeR). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genetic purging in captive endangered ungulates with extremely low effective population sizes.

Inbreeding threatens the survival of small populations by producing inbreeding depression, but also exposes recessive deleterious effects in homozygosis allowing for genetic purging. Using inbreeding-purging theory, we analyze early survival in four pedigreed captive breeding programs of endangered ungulates where population growth was prioritized so that most adult females were allowed to contribute offspring according to their fitness. We find evidence that purging can substantially reduce inbreeding depression in Gazella cuvieri (with effective population size Ne = 14) and Nanger dama (Ne = 11). No purging is detected in Ammotragus lervia (Ne = 4), in agreement with the notion that drift overcomes purging under fast inbreeding, nor in G. dorcas (Ne = 39) where, due to the larger population size, purging is slower and detection is expected to require more generations. Thus, although smaller populations are always expected to show smaller fitness (as well as less adaptive potential) than larger ones due to higher homozygosis and deleterious fixation, our results show that a substantial fraction of their inbreeding load and inbreeding depression can be purged when breeding contributions are governed by natural selection. Since management strategies intended to maximize the ratio from the effective to the actual population size tend to reduce purging, the search for a compromise between these strategies and purging could be beneficial in the long term. This could be achieved either by allowing some level of random mating and some role of natural selection in determining breeding contributions, or by undertaking reintroductions into the wild at the earliest opportunity.

Long-term exhaustion of the inbreeding load in Drosophila melanogaster.

Inbreeding depression, the decline in fitness of inbred individuals, is a ubiquitous phenomenon of great relevance in evolutionary biology and in the fields of animal and plant breeding and conservation. Inbreeding depression is due to the expression of recessive deleterious alleles that are concealed in heterozygous state in noninbred individuals, the so-called inbreeding load. Genetic purging reduces inbreeding depression by removing these alleles when expressed in homozygosis due to inbreeding. It is generally thought that fast inbreeding (such as that generated by full-sib mating lines) removes only highly deleterious recessive alleles, while slow inbreeding can also remove mildly deleterious ones. However, a question remains regarding which proportion of the inbreeding load can be removed by purging under slow inbreeding in moderately large populations. We report results of two long-term slow inbreeding Drosophila experiments (125-234 generations), each using a large population and a number of derived lines with effective sizes about 1000 and 50, respectively. The inbreeding load was virtually exhausted after more than one hundred generations in large populations and between a few tens and over one hundred generations in the lines. This result is not expected from genetic drift alone, and is in agreement with the theoretical purging predictions. Computer simulations suggest that these results are consistent with a model of relatively few deleterious mutations of large homozygous effects and partially recessive gene action.

Highly pleiotropic variants of human traits are enriched in genomic regions with strong background selection.

Recent studies have shown the ubiquity of pleiotropy for variants affecting human complex traits. These studies also show that rare variants tend to be less pleiotropic than common ones, suggesting that purifying natural selection acts against highly pleiotropic variants of large effect. Here, we investigate the mean frequency, effect size and recombination rate associated with pleiotropic variants, and focus particularly on whether highly pleiotropic variants are enriched in regions with putative strong background selection. We evaluate variants for 41 human traits using data from the NHGRI-EBI GWAS Catalog, as well as data from other three studies. Our results show that variants involving a higher degree of pleiotropy tend to be more common, have larger mean effect sizes, and contribute more to heritability than variants with a lower degree of pleiotropy. This is consistent with the fact that variants of large effect and frequency are more likely detected by GWAS. Using data from four different studies, we also show that more pleiotropic variants are enriched in genome regions with stronger background selection than less pleiotropic variants, suggesting that highly pleiotropic variants are subjected to strong purifying selection. From the above results, we hypothesized that a number of highly pleiotropic variants of low effect/frequency may pass undetected by GWAS.

De Novo Mutation Rate Variation and Its Determinants in Chlamydomonas.

De novo mutations are central for evolution, since they provide the raw material for natural selection by regenerating genetic variation. However, studying de novo mutations is challenging and is generally restricted to model species, so we have a limited understanding of the evolution of the mutation rate and spectrum between closely related species. Here, we present a mutation accumulation (MA) experiment to study de novo mutation in the unicellular green alga Chlamydomonas incerta and perform comparative analyses with its closest known relative, Chlamydomonas reinhardtii. Using whole-genome sequencing data, we estimate that the median single nucleotide mutation (SNM) rate in C. incerta is µ = 7.6 × 10-10, and is highly variable between MA lines, ranging from µ = 0.35 × 10-10 to µ = 131.7 × 10-10. The SNM rate is strongly positively correlated with the mutation rate for insertions and deletions between lines (r > 0.97). We infer that the genomic factors associated with variation in the mutation rate are similar to those in C. reinhardtii, allowing for cross-prediction between species. Among these genomic factors, sequence context and complexity are more important than GC content. With the exception of a remarkably high C→T bias, the SNM spectrum differs markedly between the two Chlamydomonas species. Our results suggest that similar genomic and biological characteristics may result in a similar mutation rate in the two species, whereas the SNM spectrum has more freedom to diverge.

Conservation Priorities Analysis of Chinese Indigenous Pig Breeds in the Taihu Lake Region.

Most indigenous pig resources are known to originate from China. Thus, establishing conservation priorities for these local breeds is very essential, especially in the case of limited conservation funds. Therefore, in this study, we analyzed 445 individuals belonging to six indigenous breeds from the Taihu Lake Region, using a total of 131,300 SNPs. In order to determine the long-term guidelines for the management of these breeds, we analyzed the level of diversity in the metapopulation following a partition of diversity within and between breed subpopulations, using both measures of genic and allelic diversity. From the study, we found that the middle Meishan (MMS) pig population contributes the most (22%) to the total gene diversity while the Jiaxing black (JX) pig population contributes the most (27%) to the gene diversity between subpopulations. Most importantly, when we consider one breed is removed from the meta-population, the first two breeds prioritized should be JX pig breed and Fengjing pig breed followed by small Meishan (SMS), Mizhu (MI), and Erhualian (EH) if we pay more attention to the gene diversity between subpopulations. However, if the priority focus is on the total gene diversity, then the first breed to be prioritized would be the Shawutou (SW) pig breed followed by JX, MI, EH, and Fengjing (FJ). Furthermore, we noted that if conservation priority is to be based on the allelic diversity between subpopulations, then the MI breed should be the most prioritized breed followed by SW, Erhuanlian, and MMS. Summarily, our data show that different breeds have different contributions to the gene and allelic diversity within subpopulations as well as between subpopulations. Our study provides a basis for setting conservation priorities for indigenous pig breeds with a focus on different priority criteria.

Inbred lab mice are not isogenic: genetic variation within inbred strains used to infer the mutation rate per nucleotide site.

For over a century, inbred mice have been used in many areas of genetics research to gain insight into the genetic variation underlying traits of interest. The generalizability of any genetic research study in inbred mice is dependent upon all individual mice being genetically identical, which in turn is dependent on the breeding designs of companies that supply inbred mice to researchers. Here, we compare whole-genome sequences from individuals of four commonly used inbred strains that were procured from either the colony nucleus or from a production colony (which can be as many as ten generations removed from the nucleus) of a large commercial breeder, in order to investigate the extent and nature of genetic variation within and between individuals. We found that individuals within strains are not isogenic, and there are differences in the levels of genetic variation that are explained by differences in the genetic distance from the colony nucleus. In addition, we employ a novel approach to mutation rate estimation based on the observed genetic variation and the expected site frequency spectrum at equilibrium, given a fully inbred breeding design. We find that it provides a reasonable per nucleotide mutation rate estimate when mice come from the colony nucleus (~7.9 × 10-9 in C3H/HeN), but substantially inflated estimates when mice come from production colonies.

Optimal Management of Genetic Diversity in Subdivided Populations.

One of the main objectives of conservation programs is the maintenance of genetic diversity because this provides the adaptive potential of populations to face new environmental challenges. Genetic diversity is generally assessed by means of neutral molecular markers, and it is usually quantified by the expected heterozygosity under Hardy-Weinberg equilibrium and the number of alleles per locus or allelic diversity. These two measures of genetic diversity are complementary because whereas the former is directly related to genetic variance for quantitative traits and, therefore, to the short-term response to selection and adaptation, the latter is more sensitive to population bottlenecks and relates more strongly to the long-term capacity of adaptation of populations. In the context of structured populations undergoing conservation programs, it is important to decide the optimum management strategy to preserve as much genetic diversity as possible while avoiding inbreeding. Here we examine, through computer simulations, the consequences of choosing a conservation strategy based on maximizing either heterozygosity or allelic diversity of single-nucleotide polymorphism haplotypes in a subdivided population. Our results suggest that maximization of allelic diversity can be more efficient in maintaining the genetic diversity of subdivided populations than maximization of expected heterozygosity because the former maintains a larger number of alleles while making a better control of inbreeding. Thus, maximization of allelic diversity should be a recommended strategy in conservation programs for structured populations.

GWEHS: A Genome-Wide Effect Sizes and Heritability Screener.

During the last decade, there has been a huge development of Genome-Wide Association Studies (GWAS), and thousands of loci associated to complex traits have been detected. These efforts have led to the creation of public databases of GWAS results, making a huge source of information available on the genetic background of many diverse traits. Here we present GWEHS (Genome-Wide Effect size and Heritability Screener), an open-source online application to screen loci associated to human complex traits and diseases from the NHGRI-EBI GWAS Catalog. This application provides a way to explore the distribution of effect sizes of loci affecting these traits, as well as their contribution to heritability. Furthermore, it allows for making predictions on the change in the expected mean effect size, as well as in the heritability as new loci are found. The application enables inferences on whether the additive contribution of loci expected to be discovered in the future will be able to explain the estimates of familial heritability for the different traits. We illustrate the use of this tool, compare some of the results obtained with those from a previous meta-analysis, and discuss its uses and limitations.

Inferring the Nature of Missing Heritability in Human Traits Using Data from the GWAS Catalog.

Thousands of genes responsible for many diseases and other common traits in humans have been detected by Genome Wide Association Studies (GWAS) in the last decade. However, candidate causal variants found so far usually explain only a small fraction of the heritability estimated by family data. The most common explanation for this observation is that the missing heritability corresponds to variants, either rare or common, with very small effect, which pass undetected due to a lack of statistical power. We carried out a meta-analysis using data from the NHGRI-EBI GWAS Catalog in order to explore the observed distribution of locus effects for a set of 42 complex traits and to quantify their contribution to narrow-sense heritability. With the data at hand, we were able to predict the expected distribution of locus effects for 16 traits and diseases, their expected contribution to heritability, and the missing number of loci yet to be discovered to fully explain the familial heritability estimates. Our results indicate that, for 6 out of the 16 traits, the additive contribution of a great number of loci is unable to explain the familial (broad-sense) heritability, suggesting that the gap between GWAS and familial estimates of heritability may not ever be closed for these traits. In contrast, for the other 10 traits, the additive contribution of hundreds or thousands of loci yet to be found could potentially explain the familial heritability estimates, if this were the case. Computer simulations are used to illustrate the possible contribution from nonadditive genetic effects to the gap between GWAS and familial estimates of heritability.

metapop2: Re-implementation of software for the analysis and management of subdivided populations using gene and allelic diversity.

Management programmes often have to make decisions based on the analysis of the genetic properties and diversity of populations. Expected heterozygosity (or gene diversity) and population structure parameters are often used to make recommendations for conservation, such as avoidance of inbreeding or migration across subpopulations. Allelic diversity, however, can also provide complementary and useful information for conservation programmes, as it is highly sensitive to population bottlenecks, and is more related to long-term selection response than heterozygosity. Here we present a completely revised and updated re-implementation of the software metapop for the analysis of diversity in subdivided populations, as well as a tool for the management and dynamic estimation of optimal contributions in conservation programmes. This new update includes computation of allelic diversity for population analysis and management, as well as a simulation mode to forecast the consequences of taking different management strategies over time. Furthermore, the new implementation in C++ includes code optimization and improved memory usage, allowing for fast analysis of large data sets including single nucleotide polymorphism markers, as well as enhanced cross-software and cross-platform compatibility.

Detection of genetic purging and predictive value of purging parameters estimated in pedigreed populations.

The consequences of inbreeding for fitness are important in evolutionary and conservation biology, but can critically depend on genetic purging. However, estimating purging has proven elusive. Using PURGd software, we assess the performance of the Inbreeding-Purging (IP) model and of ancestral inbreeding (Fa) models to detect purging in simulated pedigreed populations, and to estimate parameters that allow reliably predicting the evolution of fitness under inbreeding. The power to detect purging in a single small population of size N is low for both models during the first few generations of inbreeding (t ≈ N/2), but increases for longer periods of slower inbreeding and is, on average, larger for the IP model. The ancestral inbreeding approach overestimates the rate of inbreeding depression during long inbreeding periods, and produces joint estimates of the effects of inbreeding and purging that lead to unreliable predictions for the evolution of fitness. The IP estimates of the rate of inbreeding depression become downwardly biased when obtained from long inbreeding processes. However, the effect of this bias is canceled out by a coupled downward bias in the estimate of the purging coefficient so that, unless the population is very small, the joint estimate of these two IP parameters yields good predictions of the evolution of mean fitness in populations of different sizes during periods of different lengths. Therefore, our results support the use of the IP model to detect inbreeding depression and purging, and to estimate reliable parameters for predictive purposes.

Predictive Model and Software for Inbreeding-Purging Analysis of Pedigreed Populations.

The inbreeding depression of fitness traits can be a major threat to the survival of populations experiencing inbreeding. However, its accurate prediction requires taking into account the genetic purging induced by inbreeding, which can be achieved using a "purged inbreeding coefficient". We have developed a method to compute purged inbreeding at the individual level in pedigreed populations with overlapping generations. Furthermore, we derive the inbreeding depression slope for individual logarithmic fitness, which is larger than that for the logarithm of the population fitness average. In addition, we provide a new software, PURGd, based on these theoretical results that allows analyzing pedigree data to detect purging, and to estimate the purging coefficient, which is the parameter necessary to predict the joint consequences of inbreeding and purging. The software also calculates the purged inbreeding coefficient for each individual, as well as standard and ancestral inbreeding. Analysis of simulation data show that this software produces reasonably accurate estimates for the inbreeding depression rate and for the purging coefficient that are useful for predictive purposes.

Estimation of genetic purging under competitive conditions.

Inbreeding depression for fitness traits is a key issue in evolutionary biology and conservation genetics. The magnitude of inbreeding depression, though, may critically depend on the efficiency of genetic purging, the elimination or recessive deleterious mutations by natural selection after they are exposed by inbreeding. However, the detection and quantification of genetic purging for nonlethal mutations is a rather difficult task. Here, we present two comprehensive sets of experiments with Drosophila aimed at detecting genetic purging in competitive conditions and quantifying its magnitude. We obtain, for the first time in competitive conditions, an estimate for the predictive parameter, the purging coefficient (d), that quantifies the magnitude of genetic purging, either against overall inbreeding depression (d ≈ 0.3), or against the component ascribed to nonlethal alleles (dNL ≈ 0.2). We find that competitive fitness declines at a high rate when inbreeding increases in the absence of purging. However, in moderate size populations under competitive conditions, inbreeding depression need not be too dramatic in the medium to short term, as the efficiency of purging is also very high. Furthermore, we find that purging occurred under competitive conditions also reduced the inbreeding depression that is expressed in the absence of competition.