How to estimate kinship

Missing genotype imputation in non-model species using self-organizing maps

Current methodologies of genome-wide single-nucleotide polymorphism (SNP) genotyping produce large amounts of missing data that may affect statistical inference and bias the outcome of experiments. Genotype imputation is routinely used in well-studied species to buffer the impact in downstream analysis, and several algorithms are available to fill in missing genotypes. The lack of reference haplotype panels precludes the use of these methods in genomic studies on non-model organisms. As an alternative, machine learning algorithms are employed to explore the genotype data and to estimate the missing genotypes. Here, we propose an imputation method based on self-organizing maps (SOM), a widely used neural networks formed by spatially distributed neurons that cluster similar inputs into close neurons. The method explores genotype datasets to select SNP loci to build binary vectors from the genotypes, and initializes and trains neural networks for each query missing SNP genotype. The SOM-derived clustering is then used to impute the best genotype. To automate the imputation process, we have implemented gtImputation, an open-source application programmed in Python3 and with a user-friendly GUI to facilitate the whole process. The method performance was validated by comparing its accuracy, precision and sensitivity on several benchmark genotype datasets with other available imputation algorithms. Our approach produced highly accurate and precise genotype imputations even for SNPs with alleles at low frequency and outperformed other algorithms, especially for datasets from mixed populations with unrelated individuals.

Distinguishing recrudescence from reinfection in lymphatic filariasis

BACKGROUND

The Global Program to Eliminate Lymphatic Filariasis (GPELF) is the largest public health program based on mass drug administration (MDA). Despite decades of MDA, ongoing transmission in some countries remains a challenge. To optimise interventions, it is critical to differentiate between recrudescence and new infections. Since adult filariae are inaccessible in humans, deriving a method that relies on the offspring microfilariae (mf) is necessary.

METHODS

We developed a genome amplification and kinship analysis-based approach using Brugia malayi samples from gerbils, and applied it to analyse Wuchereria bancrofti mf from humans in Côte d'Ivoire. We examined the pre-treatment genetic diversity in 269 mf collected from 18 participants, and further analysed 1-year post-treatment samples of 74 mf from 4 participants. Hemizygosity of the male X-chromosome allowed for direct inference of haplotypes, facilitating robust maternal parentage inference. To enrich parasite DNA from samples contaminated with host DNA, a whole-exome capture panel was created for W. bancrofti.

FINDINGS

By reconstructing and temporally tracking sibling relationships across pre- and post-treatment samples, we differentiated between new and established maternal families, suggesting reinfection in one participant and recrudescence in three participants. The estimated number of reproductively active adult females ranged between 3 and 11 in the studied participants. Population structure analysis revealed genetically distinct parasites in Côte d'Ivoire compared to samples from other countries. Exome capture identified protein-coding variants with ∼95% genotype concordance rate.

INTERPRETATION

We have generated resources to facilitate the development of molecular genetic tools that can estimate adult worm burdens and monitor parasite populations, thus providing essential information for the successful implementation of GPELF.

FUNDING

This work was financially supported by the Bill and Melinda Gates Foundation (https://www.gatesfoundation.org) under grant OPP1201530 (Co-PIs PUF & Gary J. Weil). B. malayi parasite material was generated with support of the Foundation for Barnes Jewish Hospital (PUF). In addition, the development of computational methods was supported by the National Institutes of Health under grants AI144161 (MM) and AI146353 (MM). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Detecting inbreeding depression in structured populations

Measuring inbreeding and its consequences on fitness is central for many areas in biology including human genetics and the conservation of endangered species. However, there is no consensus on the best method, neither for quantification of inbreeding itself nor for the model to estimate its effect on specific traits. We simulated traits based on simulated genomes from a large pedigree and empirical whole-genome sequences of human data from populations with various sizes and structures (from the 1,000 Genomes project). We compare the ability of various inbreeding coefficients ([Formula: see text]) to quantify the strength of inbreeding depression: allele-sharing, two versions of the correlation of uniting gametes which differ in the weight they attribute to each locus and two identical-by-descent segments-based estimators. We also compare two models: the standard linear model and a linear mixed model (LMM) including a genetic relatedness matrix (GRM) as random effect to account for the nonindependence of observations. We find LMMs give better results in scenarios with population or family structure. Within the LMM, we compare three different GRMs and show that in homogeneous populations, there is little difference among the different [Formula: see text] and GRM for inbreeding depression quantification. However, as soon as a strong population or family structure is present, the strength of inbreeding depression can be most efficiently estimated only if i) the phenotypes are regressed on [Formula: see text] based on a weighted version of the correlation of uniting gametes, giving more weight to common alleles and ii) with the GRM obtained from an allele-sharing relatedness estimator.

Parental kinship coefficient but not paternal coloration predicts early offspring growth in lake char

The 'good genes' hypotheses of sexual selection predict that females prefer males with strong ornaments because they are in good health and vigor and can afford the costs of the ornaments. A key assumption of this concept is that male health and vigor are useful predictors of genetic quality and hence offspring performance. We tested this prediction in wild-caught lake char (Salvelinus umbla) whose breeding coloration is known to reveal aspects of male health. We first reanalyzed results from sperm competition trials in which embryos of known parenthood had been raised singly in either a stress- or non-stress environment. Paternal coloration did not correlate with any measures of offspring performance. However, offspring growth was reduced with higher kinship coefficients between the parents. To test the robustness of these first observations, we collected a new sample of wild males and females, used their gametes in a full-factorial in vitro breeding experiment, and singly raised about 3000 embryos in either a stress- or non-stress environment (stress induced by microbes). Again, paternal coloration did not predict offspring performance, while offspring growth was reduced with higher kinship between the parents. We conclude that, in lake char, the genetic benefits of mate choice would be strongest if females could recognize and avoid genetically related males, while male breeding colors may be more relevant in intra-sexual selection.

Capturing and managing genetic diversity in ex situ collections of threatened tropical trees: A case study in Karomia gigas

Premise

Although ex situ collections of threatened plants are most useful when they contain maximal genetic variation, the conservation and maintenance of genetic diversity in collections are often poorly known. We present a case study using population genomic analyses of an ex situ collection of Karomia gigas, a critically endangered tropical tree from Tanzania. Only ~43 individuals are known in two wild populations, and ex situ collections containing 34 individuals were established in two sites from wild-collected seed. The study aimed to understand how much diversity is represented in the collection, analyze the parentage of ex situ individuals, and identify efficient strategies to capture and maintain genetic diversity.

Methods

We genotyped all known individuals using a 2b-RADseq approach, compared genetic diversity in wild populations and ex situ collections, and conducted parentage analysis of the collections.

Results

Wild populations were found to have greater levels of genetic diversity than ex situ populations as measured by number of private alleles, number of polymorphic sites, observed and expected heterozygosity, nucleotide diversity, and allelic richness. In addition, only 32.6% of wild individuals are represented ex situ and many individuals were found to be the product of selfing by a single wild individual.

Discussion

Population genomic analyses provided important insights into the conservation of genetic diversity in K. gigas, identifying gaps and inefficiencies, but also highlighting strategies to conserve genetic diversity ex situ. Genomic analyses provide essential information to ensure that collections effectively conserve genetic diversity in threatened tropical trees.

Polly: An R package for genotyping microsatellites and detecting highly polymorphic DNA markers from short-read data

Highly polymorphic markers, such as microsatellites, are invaluable for the study of natural populations. However, contemporary methods for genotyping highly polymorphic variants have serious drawbacks that impede their efficiency. We created Polly, an R package with C++ source code that uses Illumina short-read data to genotype microsatellites, detect highly polymorphic variants and identify clusters of highly polymorphic SNPs, indels and microsatellites. We tested Polly on short-read data from Xiphophorus birchmanni (Teleostei: Poeciliidae) and Arabidopsis thaliana, finding it to be efficient and accurate both for microsatellite genotyping and polymorphic marker detection. This program can be applied to any diploid population for which there exists short-read data and at least one scaffolded reference genome.

VCF2PCACluster: a simple, fast and memory-efficient tool for principal component analysis of tens of millions of SNPs

Principal component analysis (PCA) is an important and widely used unsupervised learning method that determines population structure based on genetic variation. Genome sequencing of thousands of individuals usually generate tens of millions of SNPs, making it challenging for PCA analysis and interpretation. Here we present VCF2PCACluster, a simple, fast and memory-efficient tool for Kinship estimation, PCA and clustering analysis, and visualization based on VCF formatted SNPs. We implemented five Kinship estimation methods and three clustering methods for its users to choose from. Moreover, unlike other PCA tools, VCF2PCACluster possesses a clustering function based on PCA result, which enabling users to automatically and clearly know about population structure. We demonstrated the same accuracy but a higher performance of this tool in performing PCA analysis on tens of millions of SNPs compared to another popular PLINK2 software, especially in peak memory usage that is independent of the number of SNPs in VCF2PCACluster.

py_ped_sim - A flexible forward genetic simulator for complex family pedigree analysis

Background

Large-scale family pedigrees are commonly used across medical, evolutionary, and forensic genetics. These pedigrees are tools for identifying genetic disorders, tracking evolutionary patterns, and establishing familial relationships via forensic genetic identification. However, there is a lack of software to accurately simulate different pedigree structures along with genomes corresponding to those individuals in a family pedigree. This limits simulation-based evaluations of methods that use pedigrees.

Results

We have developed a python command-line-based tool called py_ped_sim that facilitates the simulation of pedigree structures and the genomes of individuals in a pedigree. py_ped_sim represents pedigrees as directed acyclic graphs, enabling conversion between standard pedigree formats and integration with the forward population genetic simulator, SLiM. Notably, py_ped_sim allows the simulation of varying numbers of offspring for a set of parents, with the capacity to shift the distribution of sibship sizes over generations. We additionally add simulations for events of misattributed paternity, which offers a way to simulate half-sibling relationships. We validated the accuracy of our software by simulating genomes onto diverse family pedigree structures, showing that the estimated kinship coefficients closely approximated expected values.

Conclusions

py_ped_sim is a user-friendly and open-source solution for simulating pedigree structures and conducting pedigree genome simulations. It empowers medical, forensic, and evolutionary genetics researchers to gain deeper insights into the dynamics of genetic inheritance and relatedness within families.

Construction of relatedness matrices in autopolyploid populations using low-depth high-throughput sequencing data

KEY MESSAGE

An improved estimator of genomic relatedness using low-depth high-throughput sequencing data for autopolyploids is developed. Its outputs strongly correlate with SNP array-based estimates and are available in the package GUSrelate. High-throughput sequencing (HTS) methods have reduced sequencing costs and resources compared to array-based tools, facilitating the investigation of many non-model polyploid species. One important quantity that can be computed from HTS data is the genetic relatedness between all individuals in a population. However, HTS data are often messy, with multiple sources of errors (i.e. sequencing errors or missing parental alleles) which, if not accounted for, can lead to bias in genomic relatedness estimates. We derive a new estimator for constructing a genomic relationship matrix (GRM) from HTS data for autopolyploid species that accounts for errors associated with low sequencing depths, implemented in the R package GUSrelate. Simulations revealed that GUSrelate performed similarly to existing GRM methods at high depth but reduced bias in self-relatedness estimates when the sequencing depth was low. Using a panel consisting of 351 tetraploid potato genotypes, we found that GUSrelate produced GRMs from genotyping-by-sequencing (GBS) data that were highly correlated with a GRM computed from SNP array data, and less biased than existing methods when benchmarking against the array-based GRM estimates. GUSrelate provides researchers with a tool to reliably construct GRMs from low-depth HTS data.

Sex-specific effects of inbreeding in juvenile brown trout

Inbreeding depression, that is, the reduction of health and vigour in individuals with high inbreeding coefficients, is expected to increase with environmental, social, or physiological stress. It has therefore been predicted that sexual selection and the associated stress usually lead to higher inbreeding depression in males than in females. However, sex-specific differences in life history may reverse that pattern during certain developmental stages. In some salmonids, for example, female juveniles start developing their gonads earlier than males who instead grow faster. We tested whether the sexes are differently affected by inbreeding during that time. To study the effects of inbreeding coefficients that may be typical for natural populations of brown trout (Salmo trutta), and also to control for potentially confounding maternal or paternal effects, we sampled males and females from the wild, used their gametes in a block-wise full-factorial breeding design to produce 60 full-sib families, released the offspring as yolk-sac larvae into the wild, sampled them 6 months later, identified their genetic sex, and used microsatellites to assign them to their parents. We used whole-genome resequencing to calculate the kinship coefficients for each breeding pair and hence the expected average inbreeding coefficient per family. Juvenile growth could be predicted from these expected inbreeding coefficients and the genetic sex: Females reached lower body sizes with increasing inbreeding coefficient, while no such link could be found in males. This sex-specific inbreeding depression led to the overall pattern that females were on average smaller than males by the end of their first summer.

Estimation of inbreeding and kinship coefficients via latent identity-by-descent states

MOTIVATION

Estimating the individual inbreeding coefficient and pairwise kinship is an important problem in human genetics (e.g. in disease mapping) and in animal and plant genetics (e.g. inbreeding design). Existing methods, such as sample correlation-based genetic relationship matrix, KING, and UKin, are either biased, or not able to estimate inbreeding coefficients, or produce a large proportion of negative estimates that are difficult to interpret. This limitation of existing methods is partly due to failure to explicitly model inbreeding. Since all humans are inbred to various degrees by virtue of shared ancestries, it is prudent to account for inbreeding when inferring kinship between individuals.

RESULTS

We present "Kindred," an approach that estimates inbreeding and kinship by modeling latent identity-by-descent states that accounts for all possible allele sharing-including inbreeding-between two individuals. Kindred used non-negative least squares method to fit the model, which not only increases computation efficiency compared to the maximum likelihood method, but also guarantees non-negativity of the kinship estimates. Through simulation, we demonstrate the high accuracy and non-negativity of kinship estimates by Kindred. By selecting a subset of SNPs that are similar in allele frequencies across different continental populations, Kindred can accurately estimate kinship between admixed samples. In addition, we demonstrate that the realized kinship matrix estimated by Kindred is effective in reducing genomic control values via linear mixed model in genome-wide association studies. Finally, we demonstrate that Kindred produces sensible heritability estimates on an Australian height dataset.

AVAILABILITY AND IMPLEMENTATION

Kindred is implemented in C with multi-threading. It takes vcf file or stream as input and works seamlessly with bcftools. Kindred is freely available at https://github.com/haplotype/kindred.

Fine-scale genetic structure in the orchid Gymnadenia conopsea is not associated with local density of flowering plants

PREMISE

Density-dependent pollinator visitation can lead to density-dependent mating patterns and within-population genetic structure. In Gymnadenia conopsea, individuals in low-density patches receive more self pollen than individuals in high-density patches, suggesting higher relatedness at low density. Ongoing fragmentation is also expected to cause more local matings, potentially leading to biparental inbreeding depression.

METHODS

To evaluate whether relatedness decreases with local density, we analyzed 1315 SNP loci in 113 individuals within two large populations. We quantified within-population genetic structure in one of the populations, recorded potential habitat barriers, and visualized gene flow using estimated effective migration surfaces (EEMS). We further estimated the magnitude of biparental inbreeding depression that would result from matings restricted to within 5 m.

RESULTS

There was no significant relationship between local density and relatedness in any population. We detected significant fine-scale genetic structure consistent with isolation by distance, with positive kinship coefficients at distances below 10 m. Kinship coefficients were low, and predicted biparental inbreeding depression resulting from matings within the closest 5 m was a modest 1-3%. The EEMS suggested that rocks and bushes may act as barriers to gene flow within a population.

CONCLUSIONS

The results suggest that increased self-pollen deposition in sparse patches does not necessarily cause higher selfing rates or that inbreeding depression results in low establishment success of inbred individuals. The modest relatedness suggests that biparental inbreeding depression is unlikely to be an immediate problem following fragmentation of large populations. The results further indicate that habitat structure may contribute to governing fine-scale genetic structure in G. conopsea.

Taking identity-by-descent analysis into the wild: Estimating realized relatedness in free-ranging macaques

Biological relatedness is a key consideration in studies of behavior, population structure, and trait evolution. Except for parent-offspring dyads, pedigrees capture relatedness imperfectly. The number and length of DNA segments that are identical-by-descent (IBD) yield the most precise estimates of relatedness. Here, we leverage novel methods for estimating locus-specific IBD from low coverage whole genome resequencing data to demonstrate the feasibility and value of resolving fine-scaled gradients of relatedness in free-living animals. Using primarily 4-6× coverage data from a rhesus macaque (Macaca mulatta) population with available long-term pedigree data, we show that we can call the number and length of IBD segments across the genome with high accuracy even at 0.5× coverage. The resulting estimates demonstrate substantial variation in genetic relatedness within kin classes, leading to overlapping distributions between kin classes. They identify cryptic genetic relatives that are not represented in the pedigree and reveal elevated recombination rates in females relative to males, which allows us to discriminate maternal and paternal kin using genotype data alone. Our findings represent a breakthrough in the ability to understand the predictors and consequences of genetic relatedness in natural populations, contributing to our understanding of a fundamental component of population structure in the wild.

Review: Computational analysis of human skeletal remains in ancient DNA and forensic genetics

Degraded DNA is used to answer questions in the fields of ancient DNA (aDNA) and forensic genetics. While aDNA studies typically center around human evolution and past history, and forensic genetics is often more concerned with identifying a specific individual, scientists in both fields face similar challenges. The overlap in source material has prompted periodic discussions and studies on the advantages of collaboration between fields toward mutually beneficial methodological advancements. However, most have been centered around wet laboratory methods (sampling, DNA extraction, library preparation, etc.). In this review, we focus on the computational side of the analytical workflow. We discuss limitations and considerations to consider when working with degraded DNA. We hope this review provides a framework to researchers new to computational workflows for how to think about analyzing highly degraded DNA and prompts an increase of collaboration between the forensic genetics and aDNA fields.

Should sons breed independently or help? Local relatedness matters

In cooperatively breeding birds, why do some individuals breed independently but others have to help at home? This question has been rarely addressed despite its fundamental importance for understanding the evolution of social cooperation. We address it using 15 years of data from Tibetan ground tits Pseudopodoces humilis where helpers consist of younger males. Since whether younger males successfully breed depends critically on their chances to occupy territories nearby home, our analytic strategy is to identify the determinants of individual differences in gaining territory ownership among these ready-to-breed males. Across widowed, last-year helper and yearling males, an age advantage was evident in inheriting resident territories, occupying adjacent vacancies and budding off part of adjacent territories, which left some last-year helpers and most yearling males to take the latter two routes. These males were more likely to acquire a territory if they were genetically related to the previous or current territory owners; otherwise they remained on natal territories as helpers. The relatedness effect can arise from the prior residence advantage established in the preceding winter when younger males followed their parents to perform kin-directed off-territory forays. Our research highlights the key role of local kinship in determining younger males' territory acquisition and thus their fate in terms of independent reproduction versus help. This finding provides insight into the formation of kin-based, facultative cooperative societies prevailing among vertebrates.

An allele-sharing, moment-based estimator of global, population-specific and population-pair FST under a general model of population structure

Being able to properly quantify genetic differentiation is key to understanding the evolutionary potential of a species. One central parameter in this context is FST, the mean coancestry within populations relative to the mean coancestry between populations. Researchers have been estimating FST globally or between pairs of populations for a long time. More recently, it has been proposed to estimate population-specific FST values, and population-pair mean relative coancestry. Here, we review the several definitions and estimation methods of FST, and stress that they provide values relative to a reference population. We show the good statistical properties of an allele-sharing, method of moments based estimator of FST (global, population-specific and population-pair) under a very general model of population structure. We point to the limitation of existing likelihood and Bayesian estimators when the populations are not independent. Last, we show that recent attempts to estimate absolute, rather than relative, mean coancestry fail to do so.

Approaching autozygosity in a small pedigree of Gochu Asturcelta pigs

BACKGROUND

In spite of the availability of single nucleotide polymorphism (SNP) array data, differentiation between observed homozygosity and that caused by mating between relatives (autozygosity) introduces major difficulties. Homozygosity estimators show large variation due to different causes, namely, Mendelian sampling, population structure, and differences among chromosomes. Therefore, the ascertainment of how inbreeding is reflected in the genome is still an issue. The aim of this research was to study the usefulness of genomic information for the assessment of genetic diversity in the highly endangered Gochu Asturcelta pig breed. Pedigree depth varied from 0 (founders) to 4 equivalent discrete generations (t). Four homozygosity parameters (runs of homozygosity, FROH; heterozygosity-rich regions, FHRR; Li and Horvitz's, FLH; and Yang and colleague's FYAN) were computed for each individual, adjusted for the variability in the base population (BP; six individuals) and further jackknifed over autosomes. Individual increases in homozygosity (depending on t) and increases in pairwise homozygosity (i.e., increase in the parents' mean) were computed for each individual in the pedigree, and effective population size (Ne) was computed for five subpopulations (cohorts). Genealogical parameters (individual inbreeding, individual increase in inbreeding, and Ne) were used for comparisons.

RESULTS

The mean F was 0.120 ± 0.074 and the mean BP-adjusted homozygosity ranged from 0.099 ± 0.081 (FLH) to 0.152 ± 0.075 (FYAN). After jackknifing, the mean values were slightly lower. The increase in pairwise homozygosity tended to be twofold higher than the corresponding individual increase in homozygosity values. When compared with genealogical estimates, estimates of Ne obtained using FYAN tended to have low root-mean-squared errors. However, Ne estimates based on increases in pairwise homozygosity using both FROH and FHRR estimates of genomic inbreeding had lower root-mean-squared errors.

CONCLUSIONS

Parameters characterizing homozygosity may not accurately depict losses of variability in small populations in which breeding policy prohibits matings between close relatives. After BP adjustment, the performance of FROH and FHRR was highly consistent. Assuming that an increase in homozygosity depends only on pedigree depth can lead to underestimating it in populations with shallow pedigrees. An increase in pairwise homozygosity computed from either FROH or FHRR is a promising approach for characterizing autozygosity.

Sperm of more colourful males are better adapted to ovarian fluids in lake char (Salmonidae)

Fish often spawn eggs with ovarian fluids that have been hypothesized to support the sperm of some males over others (cryptic female choice). Alternatively, sperm reactions to ovarian fluids could reveal male strategies. We used wild-caught lake char (Salvelinus umbla) to experimentally test whether sperm react differently to the presence of ovarian fluid, and whether any differential sperm reaction could be predicted by male breeding coloration, male inbreeding coefficients (based of 4150 SNPs) or the kinship coefficients between males and females. Male coloration was positively linked to body size and current health (based on lymphocytosis and thrombocytosis) but was a poor predictor of inbreeding or kinship coefficients. We found that sperm of more colourful males were faster in diluted ovarian fluids than in water only, while sperm of paler males were faster in water than in ovarian fluids. We then let equal numbers of sperm compete for fertilizations in the presence or absence of ovarian fluids and genetically assigned 1464 embryos (from 70 experimental trials) to their fathers. The presence of ovarian fluids significantly increased the success of the more colourful competitors. Sperm of less inbred competitors were more successful when tested in water only than in diluted ovarian fluids. The kinship coefficients had no significant effects on sperm traits or fertilization success in the presence of ovarian fluids, although parallel stress tests on embryos had revealed that females would profit more from mating with least related males rather than most coloured ones. We conclude that sperm of more colourful males are best adapted to ovarian fluids, and that the observed reaction norms suggest male strategies rather than cryptic female choice.

Recent evolution of flowering time across multiple European plant species correlates with changes in aridity

Ongoing global warming and increasing drought frequencies impact plant populations and potentially drive rapid evolutionary adaptations. Historical comparisons, where plants grown from seeds collected in the past are compared to plants grown from freshly collected seeds from populations of the same sites, are a powerful method to investigate recent evolutionary changes across many taxa. We used 21-38 years old seeds of 13 European plant species, stored in seed banks and originating from Mediterranean and temperate regions, together with recently collected seeds from the same sites for a greenhouse experiment to investigate shifts in flowering phenology as a potential result of adaptive evolution to changes in drought intensities over the last decades. We further used single nucleotide polymorphism (SNP) markers to quantify relatedness and levels of genetic variation. We found that, across species, current populations grew faster and advanced their flowering. These shifts were correlated with changes in aridity at the population origins, suggesting that increased drought induced evolution of earlier flowering, whereas decreased drought lead to weak or inverse shifts in flowering phenology. In five out of the 13 species, however, the SNP markers detected strong differences in genetic variation and relatedness between the past and current populations collected, indicating that other evolutionary processes may have contributed to changes in phenotypes. Our results suggest that changes in aridity may have influenced the evolutionary trajectories of many plant species in different regions of Europe, and that flowering phenology may be one of the key traits that is rapidly evolving.

Comparing pedigree and genomic inbreeding coefficients, and inbreeding depression of reproductive traits in Japanese Black cattle

BACKGROUND

Pedigree-based inbreeding coefficients have been generally included in statistical models for genetic evaluation of Japanese Black cattle. The use of genomic data is expected to provide precise assessment of inbreeding level and depression. Recently, many measures have been used for genome-based inbreeding coefficients; however, with no consensus on which is the most appropriate. Therefore, we compared the pedigree- ([Formula: see text]) and multiple genome-based inbreeding coefficients, which were calculated from the genomic relationship matrix with observed allele frequencies ([Formula: see text]), correlation between uniting gametes ([Formula: see text]), the observed vs expected number of homozygous genotypes ([Formula: see text]), runs of homozygosity (ROH) segments ([Formula: see text]) and heterozygosity by descent segments ([Formula: see text]). We quantified inbreeding depression from estimating regression coefficients of inbreeding coefficients on three reproductive traits: age at first calving (AFC), calving difficulty (CD) and gestation length (GL) in Japanese Black cattle.

RESULTS

The highest correlations with [Formula: see text] were for [Formula: see text] (0.86) and [Formula: see text] (0.85) whereas [Formula: see text] and [Formula: see text] provided weak correlations with [Formula: see text], with range 0.33-0.55. Except for [Formula: see text] and [Formula: see text], there were strong correlations among genome-based inbreeding coefficients ([Formula: see text] 0.94). The estimates of regression coefficients of inbreeding depression for [Formula: see text] was 2.1 for AFC, 0.63 for CD and -1.21 for GL, respectively, but [Formula: see text] had no significant effects on all traits. Genome-based inbreeding coefficients provided larger effects on all reproductive traits than [Formula: see text]. In particular, for CD, all estimated regression coefficients for genome-based inbreeding coefficients were significant, and for GL, that for [Formula: see text] had a significant.. Although there were no significant effects when using overall genome-level inbreeding coefficients for AFC and GL, [Formula: see text] provided significant effects at chromosomal level in four chromosomes for AFC, three chromosomes for CD, and two chromosomes for GL. In addition, similar results were obtained for [Formula: see text].

CONCLUSIONS

Genome-based inbreeding coefficients can capture more phenotypic variation than [Formula: see text]. In particular, [Formula: see text] and [Formula: see text] can be considered good estimators for quantifying inbreeding level and identifying inbreeding depression at the chromosome level. These findings might improve the quantification of inbreeding and breeding programs using genome-based inbreeding coefficients.

An empirical evaluation of the estimation of inbreeding depression from molecular markers under suboptimal conditions

Inbreeding depression (ID), the reduction in fitness due to inbreeding, is typically measured by the regression of the phenotypic values of individuals for a particular trait on their corresponding inbreeding coefficients (F). While genealogical records can provide these coefficients, they may be unavailable or incomplete, making molecular markers a useful alternative. The power to detect ID and its accuracy depend on the variation of F values of individuals, the sample sizes available, and the accuracy in the estimation of individual fitness traits and F values. In this study, we used Drosophila melanogaster to evaluate the effectiveness of molecular markers in estimating ID under suboptimal conditions. We generated two sets of 100 pairs of unrelated individuals from a large panmictic population and mated them for two generations to produce non-inbred and unrelated individuals (F = 0) and inbred individuals (full-sib progeny; F = 0.25). Using these expected genealogical F values, we calculated inbreeding depression for two fitness-related traits, pupae productivity and competitive fitness. We then sequenced the males from 17 non-inbred pairs and 17 inbred pairs to obtain their genomic inbreeding coefficients and estimate ID for the two traits. The scenario assumed was rather restrictive in terms of estimation of ID because: (1) the individuals belonged to the same generation of a large panmictic population, leading to low variation in individual F coefficients; (2) the sample sizes were small; and (3) the traits measured depended on both males and females while only males were sequenced. Despite the challenging conditions of our study, we found that molecular markers provided estimates of ID that were comparable to those obtained from simple pedigree estimations with larger sample sizes. The results therefore suggest that genomic measures of inbreeding are useful to provide estimates of inbreeding depression even under very challenging scenarios.

Population genomics and conservation management of the threatened black-footed tree-rat (Mesembriomys gouldii) in northern Australia

Genomic diversity is a fundamental component of Earth's total biodiversity, and requires explicit consideration in efforts to conserve biodiversity. To conserve genomic diversity, it is necessary to measure its spatial distribution, and quantify the contribution that any intraspecific evolutionary lineages make to overall genomic diversity. Here, we describe the range-wide population genomic structure of a threatened Australian rodent, the black-footed tree-rat (Mesembriomys gouldii), aiming to provide insight into the timing and extent of population declines across a large region with a dearth of long-term monitoring data. By estimating recent trajectories in effective population sizes at four localities, we confirm widespread population decline across the species' range, but find that the population in the peri-urban area of the Darwin region has been more stable. Based on current sampling, the Melville Island population made the greatest contribution to overall allelic richness of the species, and the prioritisation analysis suggested that conservation of the Darwin and Cobourg Peninsula populations would be the most cost-effective scenario to retain more than 90% of all alleles. Our results broadly confirm current sub-specific taxonomy, and provide crucial data on the spatial distribution of genomic diversity to help prioritise limited conservation resources. Along with additional sampling and genomic analysis from the far eastern and western edges of the black-footed tree-rat distribution, we suggest a range of conservation and research priorities that could help improve black-footed tree-rat population trajectories at large and fine spatial scales, including the retention and expansion of structurally complex habitat patches.

Non-random mating within an Island rookery of Hawaiian hawksbill turtles: demographic discontinuity at a small coastline scale

Hawksbill sea turtles (Eretmochelys imbricata) from the Hawaiian archipelago form a small and genetically isolated population, consisting of only a few tens of individuals breeding annually. Most females nest on the island of Hawai'i, but little is known about the demographics of this rookery. This study used genetic relatedness, inferred from 135 microhaplotype markers, to determine breeding sex-ratios, estimate female nesting frequency and assess relationships between individuals nesting on different beaches. Samples were collected during the 2017 nesting season and final data included 13 nesting females and 1002 unhatched embryos, salvaged from 41 nests, of which 13 had no observed mother. Results show that most females used a single nesting beach laying 1-5 nests each. From female and offspring alleles, the paternal genotypes of 12 breeding males were reconstructed and many showed high relatedness to their mates. Pairwise relatedness of offspring revealed one instance of polygyny but otherwise suggested a 1 : 1 breeding-sex ratio. Relatedness analysis and spatial-autocorrelation of genotypes indicate that turtles from different nesting areas do not regularly interbreed, suggesting that strong natal homing tendencies in both sexes result in non-random mating across the study area. Complexes of nearby nesting beaches also showed unique patterns of inbreeding across loci, further indicating that Hawaiian hawksbill turtles have demographically discontinuous nesting populations separated by only tens of km.

PSReliP: an integrated pipeline for analysis and visualization of population structure and relatedness based on genome-wide genetic variant data

BACKGROUND

Population structure and cryptic relatedness between individuals (samples) are two major factors affecting false positives in genome-wide association studies (GWAS). In addition, population stratification and genetic relatedness in genomic selection in animal and plant breeding can affect prediction accuracy. The methods commonly used for solving these problems are principal component analysis (to adjust for population stratification) and marker-based kinship estimates (to correct for the confounding effects of genetic relatedness). Currently, many tools and software are available that analyze genetic variation among individuals to determine population structure and genetic relationships. However, none of these tools or pipelines perform such analyses in a single workflow and visualize all the various results in a single interactive web application.

RESULTS

We developed PSReliP, a standalone, freely available pipeline for the analysis and visualization of population structure and relatedness between individuals in a user-specified genetic variant dataset. The analysis stage of PSReliP is responsible for executing all steps of data filtering and analysis and contains an ordered sequence of commands from PLINK, a whole-genome association analysis toolset, along with in-house shell scripts and Perl programs that support data pipelining. The visualization stage is provided by Shiny apps, an R-based interactive web application. In this study, we describe the characteristics and features of PSReliP and demonstrate how it can be applied to real genome-wide genetic variant data.

CONCLUSIONS

The PSReliP pipeline allows users to quickly analyze genetic variants such as single nucleotide polymorphisms and small insertions or deletions at the genome level to estimate population structure and cryptic relatedness using PLINK software and to visualize the analysis results in interactive tables, plots, and charts using Shiny technology. The analysis and assessment of population stratification and genetic relatedness can aid in choosing an appropriate approach for the statistical analysis of GWAS data and predictions in genomic selection. The various outputs from PLINK can be used for further downstream analysis. The code and manual for PSReliP are available at https://github.com/solelena/PSReliP .

Effect of reduced genomic representation on using runs of homozygosity for inbreeding characterization

Genomic measures of inbreeding based on identical-by-descent (IBD) segments are increasingly used to measure inbreeding and mostly estimated on SNP arrays and whole-genome sequencing (WGS) data. However, some softwares recurrently used for their estimation assume that genomic positions which have not been genotyped are nonvariant. This might be true for WGS data, but not for reduced genomic representations and can lead to spurious IBD segments estimation. In this project, we simulated the outputs of WGS, two SNP arrays of different sizes and RAD-sequencing for three populations with different sizes and histories. We compare the results of IBD segments estimation with two softwares: runs of homozygosity (ROHs) estimated with PLINK and homozygous-by-descent (HBD) segments estimated with RZooRoH. We demonstrate that to obtain meaningful estimates of inbreeding, RZooRoH requires a SNPs density 11 times smaller compared to PLINK: ranks of inbreeding coefficients were conserved among individuals above 22 SNPs/Mb for PLINK and 2 SNPs/Mb for RZooRoH. We also show that in populations with simple demographic histories, distribution of ROHs and HBD segments are correctly estimated with both SNP arrays and WGS. PLINK correctly estimated distribution of ROHs with SNP densities above 22 SNPs/Mb, while RZooRoH correctly estimated distribution of HBD segments with SNPs densities above 11 SNPs/Mb. However, in a population with a more complex demographic history, RZooRoH resulted in better distribution of IBD segments estimation compared to PLINK even with WGS data. Consequently, we advise researchers to use either methods relying on excess homozygosity averaged across SNPs or model-based HBD segments calling methods for inbreeding estimations.

A simulation-based evaluation of methods for estimating census population size of terrestrial game species from genetically-identified parent-offspring pairs

Estimates of wildlife population size are critical for conservation and management, but accurate estimates are difficult to obtain for many species. Several methods have recently been developed that estimate abundance using kinship relationships observed in genetic samples, particularly parent-offspring pairs. While these methods are similar to traditional Capture-Mark-Recapture, they do not need physical recapture, as individuals are considered recaptured if a sample contains one or more close relatives. This makes methods based on genetically-identified parent-offspring pairs particularly interesting for species for which releasing marked animals back into the population is not desirable or not possible (e.g., harvested fish or game species). However, while these methods have successfully been applied in commercially important fish species, in the absence of life-history data, they are making several assumptions unlikely to be met for harvested terrestrial species. They assume that a sample contains only one generation of parents and one generation of juveniles of the year, while more than two generations can coexist in the hunting bags of long-lived species, or that the sampling probability is the same for each individual, an assumption that is violated when fecundity and/or survival depend on sex or other individual traits. In order to assess the usefulness of kin-based methods to estimate population sizes of terrestrial game species, we simulated population pedigrees of two different species with contrasting demographic strategies (wild boar and red deer), applied four different methods and compared the accuracy and precision of their estimates. We also performed a sensitivity analysis, simulating population pedigrees with varying fecundity characteristics and various levels of harvesting to identify optimal conditions of applicability of each method. We showed that all these methods reached the required levels of accuracy and precision to be effective in wildlife management under simulated circumstances (i.e., for species within a given range of fecundity and for a given range of sampling intensity), while being robust to fecundity variation. Despite the potential usefulness of the methods for terrestrial game species, care is needed as several biases linked to hunting practices still need to be investigated (e.g., when hunting bags are biased toward a particular group of individuals).

A comparison of marker-based estimators of inbreeding and inbreeding depression

BACKGROUND

The availability of genome-wide marker data allows estimation of inbreeding coefficients (F, the probability of identity-by-descent, IBD) and, in turn, estimation of the rate of inbreeding depression (ΔID). We investigated, by computer simulations, the accuracy of the most popular estimators of inbreeding based on molecular markers when computing F and ΔID in populations under random mating, equalization of parental contributions, and artificially selected populations. We assessed estimators described by Li and Horvitz (F_LH1 and F_LH2), VanRaden (F_VR1 and F_VR2), Yang and colleagues (F_YA1 and F_YA2), marker homozygosity (F_HOM), runs of homozygosity (F_ROH) and estimates based on pedigree (F_PED) in comparison with estimates obtained from IBD measures (F_IBD).

RESULTS

If the allele frequencies of a base population taken as a reference for the computation of inbreeding are known, all estimators based on marker allele frequencies are highly correlated with F_IBD and provide accurate estimates of the mean ΔID. If base population allele frequencies are unknown and current frequencies are used in the estimations, the largest correlation with F_IBD is generally obtained by F_LH1 and the best estimator of ΔID is F_YA2. The estimators F_VR2 and F_LH2 have the poorest performance in most scenarios. The assumption that base population allele frequencies are equal to 0.5 results in very biased estimates of the average inbreeding coefficient but they are highly correlated with F_IBD and give relatively good estimates of ΔID. Estimates obtained directly from marker homozygosity (F_HOM) substantially overestimated ΔID. Estimates based on runs of homozygosity (F_ROH) provide accurate estimates of inbreeding and ΔID. Finally, estimates based on pedigree (F_PED) show a lower correlation with F_IBD than molecular estimators but provide rather accurate estimates of ΔID. An analysis of data from a pig population supports the main findings of the simulations.

CONCLUSIONS

When base population allele frequencies are known, all marker-allele frequency-based estimators of inbreeding coefficients generally show a high correlation with F_IBD and provide good estimates of ΔID. When base population allele frequencies are unknown, F_LH1 is the marker frequency-based estimator that is most correlated with F_IBD, and F_YA2 provides the most accurate estimates of ΔID. Estimates from F_ROH are also very precise in most scenarios. The estimators F_VR2 and F_LH2 have the poorest performances.

Privacy-aware estimation of relatedness in admixed populations

BACKGROUND

Estimation of genetic relatedness, or kinship, is used occasionally for recreational purposes and in forensic applications. While numerous methods were developed to estimate kinship, they suffer from high computational requirements and often make an untenable assumption of homogeneous population ancestry of the samples. Moreover, genetic privacy is generally overlooked in the usage of kinship estimation methods. There can be ethical concerns about finding unknown familial relationships in third-party databases. Similar ethical concerns may arise while estimating and reporting sensitive population-level statistics such as inbreeding coefficients for the concerns around marginalization and stigmatization.

RESULTS

Here, we present SIGFRIED, which makes use of existing reference panels with a projection-based approach that simplifies kinship estimation in the admixed populations. We use simulated and real datasets to demonstrate the accuracy and efficiency of kinship estimation. We present a secure federated kinship estimation framework and implement a secure kinship estimator using homomorphic encryption-based primitives for computing relatedness between samples in two different sites while genotype data are kept confidential. Source code and documentation for our methods can be found at https://doi.org/10.5281/zenodo.7053352.

CONCLUSIONS

Analysis of relatedness is fundamentally important for identifying relatives, in association studies, and for estimation of population-level estimates of inbreeding. As the awareness of individual and group genomic privacy is growing, privacy-preserving methods for the estimation of relatedness are needed. Presented methods alleviate the ethical and privacy concerns in the analysis of relatedness in admixed, historically isolated and underrepresented populations.

SHORT ABSTRACT

Genetic relatedness is a central quantity used for finding relatives in databases, correcting biases in genome wide association studies and for estimating population-level statistics. Methods for estimating genetic relatedness have high computational requirements, and occasionally do not consider individuals from admixed ancestries. Furthermore, the ethical concerns around using genetic data and calculating relatedness are not considered. We present a projection-based approach that can efficiently and accurately estimate kinship. We implement our method using encryption-based techniques that provide provable security guarantees to protect genetic data while kinship statistics are computed among multiple sites.

Population genomics of a predatory mammal reveals patterns of decline and impacts of exposure to toxic toads

Mammal declines across northern Australia are one of the major biodiversity loss events occurring globally. There has been no regional assessment of the implications of these species declines for genomic diversity. To address this, we conducted a species-wide assessment of genomic diversity in the northern quoll (Dasyurus hallucatus), an Endangered marsupial carnivore. We used next generation sequencing methods to genotype 10,191 single nucleotide polymorphisms (SNPs) in 352 individuals from across a 3220-km length of the continent, investigating patterns of population genomic structure and diversity, and identifying loci showing signals of putative selection. We found strong heterogeneity in the distribution of genomic diversity across the continent, characterized by (i) biogeographical barriers driving hierarchical population structure through long-term isolation, and (ii) severe reductions in diversity resulting from population declines, exacerbated by the spread of introduced toxic cane toads (Rhinella marina). These results warn of a large ongoing loss of genomic diversity and associated adaptive capacity as mammals decline across northern Australia. Encouragingly, populations of the northern quoll established on toad-free islands by translocations appear to have maintained most of the initial genomic diversity after 16 years. By mapping patterns of genomic diversity within and among populations, and investigating these patterns in the context of population declines, we can provide conservation managers with data critical to informed decision-making. This includes the identification of populations that are candidates for genetic management, the importance of remnant island and insurance/translocated populations for the conservation of genetic diversity, and the characterization of putative evolutionarily significant units.

Genomic basis of insularity and ecological divergence in barn owls (Tyto alba) of the Canary Islands

Islands, and the particular organisms that populate them, have long fascinated biologists. Due to their isolation, islands offer unique opportunities to study the effect of neutral and adaptive mechanisms in determining genomic and phenotypical divergence. In the Canary Islands, an archipelago rich in endemics, the barn owl (Tyto alba), present in all the islands, is thought to have diverged into a subspecies (T. a. gracilirostris) on the eastern ones, Fuerteventura and Lanzarote. Taking advantage of 40 whole-genomes and modern population genomics tools, we provide the first look at the origin and genetic makeup of barn owls of this archipelago. We show that the Canaries hold diverse, long-standing and monophyletic populations with a neat distinction of gene pools from the different islands. Using a new method, less sensitive to structure than classical F_ST, to detect regions involved in local adaptation to insular environments, we identified a haplotype-like region likely under selection in all Canaries individuals and genes in this region suggest morphological adaptations to insularity. In the eastern islands, where the subspecies is present, genomic traces of selection pinpoint signs of adapted body proportions and blood pressure, consistent with the smaller size of this population living in a hot arid climate. In turn, genomic regions under selection in the western barn owls from Tenerife showed an enrichment in genes linked to hypoxia, a potential response to inhabiting a small island with a marked altitudinal gradient. Our results illustrate the interplay of neutral and adaptive forces in shaping divergence and early onset speciation.

Moment estimators of relatedness from low-depth whole-genome sequencing data

Background

Estimating relatedness is an important step for many genetic study designs. A variety of methods for estimating coefficients of pairwise relatedness from genotype data have been proposed. Both the kinship coefficient \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varphi$$\end{document}φ and the fraternity coefficient \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document}ψ for all pairs of individuals are of interest. However, when dealing with low-depth sequencing or imputation data, individual level genotypes cannot be confidently called. To ignore such uncertainty is known to result in biased estimates. Accordingly, methods have recently been developed to estimate kinship from uncertain genotypes.

Results

We present new method-of-moment estimators of both the coefficients \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varphi$$\end{document}φ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\psi$$\end{document}ψ calculated directly from genotype likelihoods. We have simulated low-depth genetic data for a sample of individuals with extensive relatedness by using the complex pedigree of the known genetic isolates of Cilento in South Italy. Through this simulation, we explore the behaviour of our estimators, demonstrate their properties, and show advantages over alternative methods. A demonstration of our method is given for a sample of 150 French individuals with down-sampled sequencing data.

Conclusions

We find that our method can provide accurate relatedness estimates whilst holding advantages over existing methods in terms of robustness, independence from external software, and required computation time. The method presented in this paper is referred to as LowKi (Low-depth Kinship) and has been made available in an R package (https://github.com/genostats/LowKi).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04795-8.

Robust fingerprinting of genomic databases

MOTIVATION

Database fingerprinting has been widely used to discourage unauthorized redistribution of data by providing means to identify the source of data leakages. However, there is no fingerprinting scheme aiming at achieving liability guarantees when sharing genomic databases. Thus, we are motivated to fill in this gap by devising a vanilla fingerprinting scheme specifically for genomic databases. Moreover, since malicious genomic database recipients may compromise the embedded fingerprint (distort the steganographic marks, i.e. the embedded fingerprint bit-string) by launching effective correlation attacks, which leverage the intrinsic correlations among genomic data (e.g. Mendel's law and linkage disequilibrium), we also augment the vanilla scheme by developing mitigation techniques to achieve robust fingerprinting of genomic databases against correlation attacks.

RESULTS

Via experiments using a real-world genomic database, we first show that correlation attacks against fingerprinting schemes for genomic databases are very powerful. In particular, the correlation attacks can distort more than half of the fingerprint bits by causing a small utility loss (e.g. database accuracy and consistency of SNP-phenotype associations measured via P-values). Next, we experimentally show that the correlation attacks can be effectively mitigated by our proposed mitigation techniques. We validate that the attacker can hardly compromise a large portion of the fingerprint bits even if it pays a higher cost in terms of degradation of the database utility. For example, with around 24% loss in accuracy and 20% loss in the consistency of SNP-phenotype associations, the attacker can only distort about 30% fingerprint bits, which is insufficient for it to avoid being accused. We also show that the proposed mitigation techniques also preserve the utility of the shared genomic databases, e.g. the mitigation techniques only lead to around 3% loss in accuracy.

AVAILABILITY AND IMPLEMENTATION

https://github.com/xiutianxi/robust-genomic-fp-github.

Improving zebrafish laboratory welfare and scientific research through understanding their natural history

Globally, millions of zebrafish (Danio rerio) are used for scientific laboratory experiments for which researchers have a duty of care, with legal obligations to consider their welfare. Considering the growing use of the zebrafish as a vertebrate model for addressing a diverse range of scientific questions, optimising their laboratory conditions is of major importance for both welfare and improving scientific research. However, most guidelines for the care and breeding of zebrafish for research are concerned primarily with maximising production and minimising costs and pay little attention to the effects on welfare of the environments in which the fish are maintained, or how those conditions affect their scientific research. Here we review the physical and social conditions in which laboratory zebrafish are kept, identifying and drawing attention to factors likely to affect their welfare and experimental science. We also identify a fundamental lack knowledge of how zebrafish interact with many biotic and abiotic features in their natural environment to support ways to optimise zebrafish health and well-being in the laboratory, and in turn the quality of scientific data produced. We advocate that the conditions under which zebrafish are maintained need to become a more integral part of research and that we understand more fully how they influence experimental outcome and in turn interpretations of the data generated.

Comparing genome-based estimates of relatedness for use in pedigree-based conservation management

Researchers have long debated which estimator of relatedness best captures the degree of relationship between two individuals. In the genomics era, this debate continues, with relatedness estimates being sensitive to the methods used to generate markers, marker quality, and levels of diversity in sampled individuals. Here, we compare six commonly used genome-based relatedness estimators (kinship genetic distance (KGD), Wang Maximum Likelihood (TrioML), Queller and Goodnight (R_xy ), Kinship INference for Genome-wide association studies (KING-robust), and Pairwise Relatedness (R_AB ), allele-sharing co-ancestry (AS)) across five species bred in captivity-including three birds and two mammals-with varying degrees of reliable pedigree data, using reduced-representation and whole genome resequencing data. Genome-based relatedness estimates varied widely across estimators, sequencing methods, and species, yet the most consistent results for known first order relationships were found using R_xy , R_AB , and AS. However, AS was found to be less consistently correlated with known pedigree relatedness than either R_xy or R_AB . Our combined results indicate there is not a single genome-based estimator that is ideal across different species and data types. To determine the most appropriate genome-based relatedness estimator for each new dataset, we recommend assessing the relative: (1) correlation of candidate estimators with known relationships in the pedigree and (2) precision of candidate estimators with known first-order relationships. These recommendations are broadly applicable to conservation breeding programs, particularly where genome-based estimates of relatedness can complement and complete poorly pedigreed populations. Given a growing interest in the application of wild pedigrees, our results are also applicable to in-situ wildlife management.

SNP markers identification by genome wide association study for chemical quality traits of coffee (Coffea spp.) Germplasm

BACKGROUND

Coffee quality is an important selection criterion for coffee breeding. Metabolite profiling and Genome-Wide Association Studies (GWAS) effectively dissect the genetic background of complex traits such as metabolites content (caffeine, trigonelline, and 5-caffeoylquinic acid (5-CQA)) in coffee that affect quality. Therefore, it is important to determine the metabolic profiles of Coffea spp. genotypes. This study aimed to identify Single Nucleotide Polymorphisms (SNPs) within Coffea spp. genotypes through GWAS and associate these significant SNPs to the metabolic profiles of the different genotypes.

METHODS AND RESULTS

A total of 1,739 SNP markers were obtained from 80 genotypes using the DArTseq™ method. Caffeine, trigonelline, and 5-CQA content were determined in coffee leaves using Ultra-Performance Liquid Chromatography/tandem mass spectrometry (UPLC-MS/MS) analyses. The GWAS was carried out using the Genome Association and Prediction Integrated Tool (GAPIT) software and a compressed mixed linear model. Finally, a total of three significant SNP markers out of ten were identified. One SNP, located in the coffee chromosome (Chr) 8, was significantly associated with caffeine. The two remaining SNPs, located in Chr 4 and 5, were significantly associated with trigonelline and six SNPs markers were associated with 5-CQA in Chr 1, 5 and 10, but these six markers were not significant.

CONCLUSIONS

These significant SNP sequences were associated with protein ubiquitination, assimilation, and wall receptor kinases. Therefore, these SNPs might be useful hits in subsequent quality coffee breeding programs.

Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data

Analyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.

Rank-invariant estimation of inbreeding coefficients

The two alleles an individual carries at a locus are identical by descent (ibd) if they have descended from a single ancestral allele in a reference population, and the probability of such identity is the inbreeding coefficient of the individual. Inbreeding coefficients can be predicted from pedigrees with founders constituting the reference population, but estimation from genetic data is not possible without data from the reference population. Most inbreeding estimators that make explicit use of sample allele frequencies as estimates of allele probabilities in the reference population are confounded by average kinships with other individuals. This means that the ranking of those estimates depends on the scope of the study sample and we show the variation in rankings for common estimators applied to different subdivisions of 1000 Genomes data. Allele-sharing estimators of within-population inbreeding relative to average kinship in a study sample, however, do have invariant rankings across all studies including those individuals. They are unbiased with a large number of SNPs. We discuss how allele sharing estimates are the relevant quantities for a range of empirical applications.

Streamlining the decision-making process for international DNA kinship matching using Worldwide allele frequencies and tailored cutoff log10LR thresholds

The identification of human remains belonging to missing persons is one of the main challenges for forensic genetics. Although other means of identification can be applied to missing person investigations, DNA is often extremely valuable to further support or refute potential associations. When reference DNA samples cannot be collected from personal items belonging to a missing person, a direct DNA identification cannot be carried out. However, identifications can be made indirectly using DNA from the missing person's relatives. The ranking of likelihood ratio (LR) values, which measure the fit of a missing person for any given pedigree, is often the first step in selecting candidates in a DNA database. Although implementing DNA kinship matching in a national environment is feasible, many challenges need to be resolved before applying this method to an international configuration. In this study, we present an innovative and intuitive method to perform international DNA kinship matching and facilitate the comparison of DNA profiles when the ancestry is unknown or unsure and/or when different marker sets are used. This straightforward method, which is based on calculations performed with the DNA matching software BONAPARTE, Worldwide allele frequencies and tailored cutoff log₁₀LR thresholds, allows for the classification of potential candidates according to the strength of the DNA evidence and the predicted proportion of adventitious matches. This is a powerful method for streamlining the decision-making process in missing person investigations and DVI processes, especially when there are low numbers of overlapping typed STRs. Intuitive interpretation tables and a decision tree will help strengthen international data comparison for the identification of reported missing individuals discovered outside their national borders.

Bioindicator snake shows genomic signatures of natural and anthropogenic barriers to gene flow

Urbanisation alters landscapes, introduces wildlife to novel stressors, and fragments habitats into remnant 'islands'. Within these islands, isolated wildlife populations can experience genetic drift and subsequently suffer from inbreeding depression and reduced adaptive potential. The Western tiger snake (Notechis scutatus occidentalis) is a predator of wetlands in the Swan Coastal Plain, a unique bioregion that has suffered substantial degradation through the development of the city of Perth, Western Australia. Within the urban matrix, tiger snakes now only persist in a handful of wetlands where they are known to bioaccumulate a suite of contaminants, and have recently been suggested as a relevant bioindicator of ecosystem health. Here, we used genome-wide single nucleotide polymorphism (SNP) data to explore the contemporary population genomics of seven tiger snake populations across the urban matrix. Specifically, we used population genomic structure and diversity, effective population sizes (Ne), and heterozygosity-fitness correlations to assess fitness of each population with respect to urbanisation. We found that population genomic structure was strongest across the northern and southern sides of a major river system, with the northern cluster of populations exhibiting lower heterozygosities than the southern cluster, likely due to a lack of historical gene flow. We also observed an increasing signal of inbreeding and genetic drift with increasing geographic isolation due to urbanisation. Effective population sizes (Ne) at most sites were small (< 100), with Ne appearing to reflect the area of available habitat rather than the degree of adjacent urbanisation. This suggests that ecosystem management and restoration may be the best method to buffer the further loss of genetic diversity in urban wetlands. If tiger snake populations continue to decline in urban areas, our results provide a baseline measure of genomic diversity, as well as highlighting which 'islands' of habitat are most in need of management and protection.

Genomic signatures of inbreeding in a critically endangered parrot, the kākāpō

Events of inbreeding are inevitable in critically endangered species. Reduced population sizes and unique life-history traits can increase the severity of inbreeding, leading to declines in fitness and increased risk of extinction. Here, we investigate levels of inbreeding in a critically endangered flightless parrot, the kākāpō (Strigops habroptilus), wherein a highly inbred island population and one individual from the mainland of New Zealand founded the entire extant population. Genotyping-by-sequencing (GBS), and a genotype calling approach using a chromosome-level genome assembly, identified a filtered set of 12,241 single-nucleotide polymorphisms (SNPs) among 161 kākāpō, which together encompass the total genetic potential of the extant population. Multiple molecular-based estimates of inbreeding were compared, including genome-wide estimates of heterozygosity (FH), the diagonal elements of a genomic-relatedness matrix (FGRM), and runs of homozygosity (RoH, FRoH). In addition, we compared levels of inbreeding in chicks from a recent breeding season to examine if inbreeding is associated with offspring survival. The density of SNPs generated with GBS was sufficient to identify chromosomes that were largely homozygous with RoH distributed in similar patterns to other inbred species. Measures of inbreeding were largely correlated and differed significantly between descendants of the two founding populations. However, neither inbreeding nor ancestry was found to be associated with reduced survivorship in chicks, owing to unexpected mortality in chicks exhibiting low levels of inbreeding. Our study highlights important considerations for estimating inbreeding in critically endangered species, such as the impacts of small population sizes and admixture between diverse lineages.

There Is No 'Rule of Thumb': Genomic Filter Settings for a Small Plant Population to Obtain Unbiased Gene Flow Estimates

The application of high-density polymorphic single-nucleotide polymorphisms (SNP) markers derived from high-throughput sequencing methods has heralded plenty of biological questions about the linkages of processes operating at micro- and macroevolutionary scales. However, the effects of SNP filtering practices on population genetic inference have received much less attention. By performing sensitivity analyses, we empirically investigated how decisions about the percentage of missing data (MD) and the minor allele frequency (MAF) set in bioinformatic processing of genomic data affect direct (i.e., parentage analysis) and indirect (i.e., fine-scale spatial genetic structure - SGS) gene flow estimates. We focus specifically on these manifestations in small plant populations, and particularly, in the rare tropical plant species Dinizia jueirana-facao, where assumptions implicit to analytical procedures for accurate estimates of gene flow may not hold. Avoiding biases in dispersal estimates are essential given this species is facing extinction risks due to habitat loss, and so we also investigate the effects of forest fragmentation on the accuracy of dispersal estimates under different filtering criteria by testing for recent decrease in the scale of gene flow. Our sensitivity analyses demonstrate that gene flow estimates are robust to different setting of MAF (0.05-0.35) and MD (0-20%). Comparing the direct and indirect estimates of dispersal, we find that contemporary estimates of gene dispersal distance (σ _{r t} = 41.8 m) was ∼ fourfold smaller than the historical estimates, supporting the hypothesis of a temporal shift in the scale of gene flow in D. jueirana-facao, which is consistent with predictions based on recent, dramatic forest fragmentation process. While we identified settings for filtering genomic data to avoid biases in gene flow estimates, we stress that there is no 'rule of thumb' for bioinformatic filtering and that relying on default program settings is not advisable. Instead, we suggest that the approach implemented here be applied independently in each separate empirical study to confirm appropriate settings to obtain unbiased population genetics estimates.

Are immigrants outbred and unrelated? Testing standard assumptions in a wild metapopulation

Immigration into small recipient populations is expected to alleviate inbreeding and increase genetic variation, and hence facilitate population persistence through genetic and/or evolutionary rescue. Such expectations depend on three standard assumptions: that immigrants are outbred, unrelated to existing natives at arrival, and unrelated to each other. These assumptions are rarely explicitly verified, including in key field systems in evolutionary ecology. Yet, they could be violated due to non-random or repeated immigration from adjacent small populations. We combined molecular genetic marker data for 150-160 microsatellite loci with comprehensive pedigree data to test the three assumptions for a song sparrow (Melospiza melodia) population that is a model system for quantifying effects of inbreeding and immigration in the wild. Immigrants were less homozygous than existing natives on average, with mean homozygosity that closely resembled outbred natives. Immigrants can therefore be considered outbred on the focal population scale. Comparisons of homozygosity of real or hypothetical offspring of immigrant-native, native-native and immigrant-immigrant pairings implied that immigrants were typically unrelated to existing natives and to each other. Indeed, immigrants' offspring would be even less homozygous than outbred individuals on the focal population scale. The three standard assumptions of population genetic and evolutionary theory were consequently largely validated. Yet, our analyses revealed some deviations that should be accounted for in future analyses of heterosis and inbreeding depression, implying that the three assumptions should be verified in other systems to probe patterns of non-random or repeated dispersal and facilitate precise and unbiased estimation of key evolutionary parameters.

Applying Population Viability Analysis to Inform Genetic Rescue That Preserves Locally Unique Genetic Variation in a Critically Endangered Mammal

Genetic rescue can reduce the extinction risk of inbred populations, but it has the poorly understood risk of ‘genetic swamping’—the replacement of the distinctive variation of the target population. We applied population viability analysis (PVA) to identify translocation rates into the inbred lowland population of Leadbeater’s possum from an outbred highland population that would alleviate inbreeding depression and rapidly reach a target population size (N) while maximising the retention of locally unique neutral genetic variation. Using genomic kinship coefficients to model inbreeding in Vortex, we simulated genetic rescue scenarios that included gene pool mixing with genetically diverse highland possums and increased the N from 35 to 110 within ten years. The PVA predicted that the last remaining population of lowland Leadbeater’s possum will be extinct within 23 years without genetic rescue, and that the carrying capacity at its current range is insufficient to enable recovery, even with genetic rescue. Supplementation rates that rapidly increased population size resulted in higher retention (as opposed to complete loss) of local alleles through alleviation of genetic drift but reduced the frequency of locally unique alleles. Ongoing gene flow and a higher N will facilitate natural selection. Accordingly, we recommend founding a new population of lowland possums in a high-quality habitat, where population growth and natural gene exchange with highland populations are possible. We also recommend ensuring gene flow into the population through natural dispersal and/or frequent translocations of highland individuals. Genetic rescue should be implemented within an adaptive management framework, with post-translocation monitoring data incorporated into the models to make updated predictions.

Inheritance of DNA methylation differences in the mangrove Rhizophora mangle

The capacity to respond to environmental challenges ultimately relies on phenotypic variation which manifests from complex interactions of genetic and nongenetic mechanisms through development. While we know something about genetic variation and structure of many species of conservation importance, we know very little about the nongenetic contributions to variation. Rhizophora mangle is a foundation species that occurs in coastal estuarine habitats throughout the neotropics where it provides critical ecosystem functions and is potentially threatened by anthropogenic environmental changes. Several studies have documented landscape-level patterns of genetic variation in this species, but we know virtually nothing about the inheritance of nongenetic variation. To assess one type of nongenetic variation, we examined the patterns of DNA sequence and DNA methylation in maternal plants and offspring from natural populations of R. mangle from the Gulf Coast of Florida. We used a reduced representation bisulfite sequencing approach (epi-genotyping by sequencing; epiGBS) to address the following questions: (a) What are the levels of genetic and epigenetic diversity in natural populations of R. mangle? (b) How are genetic and epigenetic variation structured within and among populations? (c) How faithfully is epigenetic variation inherited? We found low genetic diversity but high epigenetic diversity from natural populations of maternal plants in the field. In addition, a large portion (up to ~25%) of epigenetic differences among offspring grown in common garden was explained by maternal family. Therefore, epigenetic variation could be an important source of response to challenging environments in the genetically depauperate populations of this foundation species.