Estimation of the inbreeding coefficient through use of genomic data

Assessment of inbreeding coefficients and inbreeding depression on complex traits from genomic and pedigree data in Nelore cattle

BACKGROUND

Nelore cattle play a key role in tropical production systems due to their resilience to harsh conditions, such as heat stress and seasonally poor nutrition. Monitoring their genetic diversity is essential to manage the negative impacts of inbreeding. Traditionally, inbreeding and inbreeding depression are assessed by pedigree-based coefficients (F), but recently, genetic markers have been preferred for their precision in capturing the inbreeding level and identifying animals at risk of reduced productive and reproductive performance. Hence, we compared the inbreeding and inbreeding depression for productive and reproductive performance traits in Nelore cattle using different inbreeding coefficient estimation methods from pedigree information (FPed), the genomic relationship matrix (FGRM), runs of homozygosity (FROH) of different lengths (> 1 Mb (genome), between 1 and 2 Mb - FROH 1-2; 2-4 Mb FROH 2-4 or > 8 Mb FROH >8) and excess homozygosity (FSNP).

RESULTS

The correlation between FPed and FROH was lower when the latter was based on shorter segments (r = 0.15 with FROH 1-2, r = 0.20 with FROH 2-4 and r = 0.28 with FROH 4-8). Meanwhile, the FPed had a moderate correlation with FSNP (r = 0.47) and high correlation with FROH >8 (r = 0.58) and FROH-genome (r = 0.60). The FROH-genome was highly correlated with inbreeding based on FROH>8 (r = 0.93) and FSNP (r = 0.88). The FGRM exhibited a high correlation with FROH-genome (r = 0.55) and FROH >8 (r = 0.51) and a lower correlation with other inbreeding estimators varying from 0.30 for FROH 2-4 to 0.37 for FROH 1-2. Increased levels of inbreeding had a negative impact on the productive and reproductive performance of Nelore cattle. The unfavorable inbreeding effect on productive and reproductive traits ranged from 0.12 to 0.51 for FPed, 0.19-0.59 for FGRM, 0.21-0.58 for FROH-genome, and 0.19-0.54 for FSNP per 1% of inbreeding scaled on the percentage of the mean. When scaling the linear regression coefficients on the standard deviation, the unfavorable inbreeding effect varied from 0.43 to 1.56% for FPed, 0.49-1.97% for FGRM, 0.34-2.2% for FROH-genome, and 0.50-1.62% for FSNP per 1% of inbreeding. The impact of the homozygous segments on reproductive and performance traits varied based on the chromosomes. This shows that specific homozygous chromosome segments can be signs of positive selection due to their beneficial effects on the traits.

CONCLUSIONS

The low correlation observed between FPed and genomic-based inbreeding estimates suggests that the presence of animals with one unknown parent (sire or dam) in the pedigree does not account for ancient inbreeding. The ROH hotspots surround genes related to reproduction, growth, meat quality, and adaptation to environmental stress. Inbreeding depression has adverse effects on productive and reproductive traits in Nelore cattle, particularly on age at puberty in young bulls and heifer calving at 30 months, as well as on scrotal circumference and body weight when scaled on the standard deviation of the trait.

Genomic and Conventional Inbreeding Coefficient Estimation Using Different Estimator Models in Korean Duroc, Landrace, and Yorkshire Breeds Using 70K Porcine SNP BeadChip

The purpose of this study was to estimate the homozygosity distribution and compute genomic and conventional inbreeding coefficients in three genetically diverse pig breed populations. The genomic and pedigree data of Duroc (1586), Landrace (2256), and Yorkshire (3646) were analyzed. We estimated and compared various genomic and pedigree inbreeding coefficients using different models and approaches. A total of 709,384 ROH segments in Duroc, 816,898 in Landrace, and 1,401,781 in Yorkshire, with average lengths of 53.59 Mb, 56.21 Mb, and 53.46 Mb, respectively, were identified. Relatively, the Yorkshire breed had the shortest ROH segments, whereas the Landrace breed had the longest mean ROH segments. Sus scrofa chromosome 1 (SSC1) had the highest chromosomal coverage by ROH across all breeds. Across breeds, an absolute correlation (1.0) was seen between FROH total and FROH1-2Mb, showing that short ROH were the primary contributors to overall FROH values. The overall association between genomic and conventional inbreeding was weak, with values ranging from 0.058 to 0.140. In contrast, total genomic inbreeding (FROH) and ROH classes showed a strong association, ranging from 0.663 to 1.00, across the genotypes. The results of genomic and conventional inbreeding estimates improve our understanding of the genetic diversity among genotypes.

Genomic inbreeding coefficients using imputation genotypes: Assessing the effect of ancestral genotyping in Holstein-Friesian dairy cows

The objective of this study was to assess the effect of using or not using the genotypes of the parents of a cow for imputing SNPs on the estimation of genomic inbreeding coefficients of cows. Imputation (i.e., genotyped plus imputed) genotypes from 68,127 Italian Holstein dairy cows registered in the Italian National Association of Holstein, Brown, and Jersey Breeders were analyzed. Cows were genotyped with the high-density (HD) Illumina Infinium BovineHD BeadChip and GeneSeek Genomic Profiler HD-150K, and the medium-density (MD) GeneSeek Genomic Profiler 3, GeneSeek Genomic Profiler 4, GeneSeek MD, and the Labogena MD. To assess differences among estimators, genomic inbreeding coefficients were estimated with 4 PLINK v1.9 estimators (F, Fhat1,Fhat2, andFhat3), 2 genomic relationship matrix- (grm) based estimators (Fgrm and Fgrm2, with the latter including also pedigree information), and one estimator of runs of homozygosity (ROH; FROH). Assuming that the correct genomic inbreeding coefficients should be those estimated from genotyped SNPs, a comparison of the genomic inbreeding coefficients estimated either with the genotyped SNPs or the SNPs after imputation was made. Information on the presence or absence of genotypic information from sire, dam, and maternal grandsire during the imputation was investigated. Genomic inbreeding coefficients estimated with genotyped SNPs or SNPs after imputation were consistent for F, Fhat3, Fgrm2, and FROH, when at least one of the parents was genotyped. Biased (mainly higher) genomic inbreeding coefficients of imputation SNPs were observed in cows that were genotyped with MD SNP panels whose SNPs were poorly represented in the selected imputation SNP dataset and also did not have their parents genotyped, when compared with what would be expected based on actual genotype data. For cows genotyped with MD the estimators Fhat1, Fhat2, and Fgrm provided higher genomic inbreeding coefficients of imputation SNPs even with both parents and the maternal grandsire genotyped. Overall, FROH was the most robust estimator, followed by F and Fhat3. Our findings suggest that SNPs selection, parental genotyping and estimator should be considered for designing imputation strategies in dairy cattle for estimating genomic inbreeding with imputation SNPs. For computing genomic inbreeding coefficients, it is recommendable to have at least one parent genotyped and use an ROH-based estimator.

Little evidence of inbreeding depression for birth mass, survival and growth in Antarctic fur seal pups

Inbreeding depression, the loss of offspring fitness due to consanguineous mating, is generally detrimental for individual performance and population viability. We investigated inbreeding effects in a declining population of Antarctic fur seals (Arctocephalus gazella) at Bird Island, South Georgia. Here, localised warming has reduced the availability of the seal's staple diet, Antarctic krill, leading to a temporal increase in the strength of selection against inbred offspring, which are increasingly failing to recruit into the adult breeding population. However, it remains unclear whether selection operates before or after nutritional independence at weaning. We therefore used microsatellite data from 885 pups and their mothers, and SNP array data from 98 mother-offspring pairs, to quantify the effects of individual and maternal inbreeding on three important neonatal fitness traits: birth mass, survival and growth. We did not find any clear or consistent effects of offspring or maternal inbreeding on any of these traits. This suggests that selection filters inbred individuals out of the population as juveniles during the time window between weaning and recruitment. Our study brings into focus a poorly understood life-history stage and emphasises the importance of understanding the ecology and threats facing juvenile pinnipeds.

Measuring the Efficiency of Purging by non-random Mating in Human Populations

Human populations harbor a high concentration of deleterious genetic variants. Here, we tested the hypothesis that non-random mating practices affect the distribution of these variants, through exposure in the homozygous state, leading to their purging from the population gene pool. To do so, we produced whole-genome sequencing data for two pairs of Asian populations exhibiting different alliance rules and rates of inbreeding, but with similar effective population sizes. The results show that populations with higher rates of inbred matings do not purge deleterious variants more efficiently. Purging therefore has a low efficiency in human populations, and different mating practices lead to a similar mutational load.

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.

Consanguinité et son impact sur la santé et la dynamique du génome : Un exemple de la Tunisie

The genetic disease spectrum in Tunisia arises from the founder effect, genetic drift, selection, and consanguinity. The latter represents a deviation from panmixia, characterized by a non-random matrimonial choice that may be subject to several rules, such as socio-cultural, economic, or other factors. This shifts the genetic structure away from the Hardy-Weinberg equilibrium, increasing homozygous genotypes and decreasing heterozygotes, thus raising the frequency of autosomal recessive diseases. Similar to other Arab populations, Tunisia displays high consanguinity rates that vary geographically. Approximately 60% of reported diseases in Tunisia are autosomal recessive, with consanguinity possibly occurring in 80% of families for a specific disease. In inbred populations, consanguinity amplifies autosomal recessive disease risk, yet it does not influence autosomal dominant disease likelihood but rather impacts its phenotype. Consanguinity is also suggested to be a major factor in the homozygosity of deleterious variants leading to comorbid expression. At the genome level, inbred individuals inherit homozygous mutations and adjacent genomic regions known as runs of homozygosity (ROHs). Short ROHs indicate distant inbreeding, while long ROHs refer to recent inbreeding. ROHs are distributed rather irregularly across the genome, with certain short regions featuring an excess of ROH, known as ROH islands. In this review, we discuss consanguinity's impact on population health and genome dynamics, using Tunisia as a model.

Inbreeding depression is associated with recent homozygous-by-descent segments in Belgian Blue beef cattle

BACKGROUND

Cattle populations harbor generally high inbreeding levels that can lead to inbreeding depression (ID). Here, we study ID with different estimators of the inbreeding coefficient F, evaluate their sensitivity to used allele frequencies (founder versus sample allele frequencies), and compare effects from recent and ancient inbreeding.

METHODS

We used data from 14,205 Belgian Blue beef cattle genotyped cows that were phenotyped for 11 linear classification traits. We computed estimators of F based on the pedigree information (FPED), on the correlation between uniting gametes (FUNI), on the genomic relationship matrix (FGRM), on excess homozygosity (FHET), or on homozygous-by-descent (HBD) segments (FHBD).

RESULTS

FUNI and FGRM were sensitive to used allele frequencies, whereas FHET and FHBD were more robust. We detected significant ID for four traits related to height and length; FHBD and FUNI presenting the strongest associations. Then, we took advantage of the classification of HBD segments in different age-related classes (the length of an HBD segment being inversely related to the number of generations to the common ancestors) to determine that recent HBD classes (common ancestors present approximately up to 15 generations in the past) presented stronger ID than more ancient HBD classes. We performed additional analyses to check whether these observations could result from a lower level of variation in ancient HBD classes, or from a reduced precision to identify these shorter segments.

CONCLUSIONS

Overall, our results suggest that mutational load decreases with haplotype age, and that mating plans should consider mainly the levels of recent inbreeding.

IBD sharing patterns as intra-breed admixture indicators in small ruminants

In this study, we investigated how IBD patterns shared between individuals of the same breed could be informative of its admixture level, with the underlying assumption that the most admixed breeds, i.e. the least genetically isolated, should have a much more fragmented genome. We considered 111 goat breeds (i.e. 2501 individuals) and 156 sheep breeds (i.e. 3304 individuals) from Europe, Africa and Asia, for which beadchip SNP genotypes had been performed. We inferred the breed's level of admixture from: (i) the proportion of the genome shared by breed's members (i.e. "genetic integrity level" assessed from ADMIXTURE software analyses), and (ii) the "AV index" (calculated from Reynolds' genetic distances), used as a proxy for the "genetic distinctiveness". In both goat and sheep datasets, the statistical analyses (comparison of means, Spearman correlations, LM and GAM models) revealed that the most genetically isolated breeds, also showed IBD profiles made up of more shared IBD segments, which were also longer. These results pave the way for further research that could lead to the development of admixture indicators, based on the characterization of intra-breed shared IBD segments, particularly effective as they would be independent of the knowledge of the whole genetic landscape in which the breeds evolve. Finally, by highlighting the fragmentation experienced by the genomes subjected to crossbreeding carried out over the last few generations, the study reminds us of the need to preserve local breeds and the integrity of their adaptive architectures that have been shaped over the centuries.

Genomic inbreeding measures applied to a population of mice divergently selected for birth weight environmental variance

This study aimed to compare different inbreeding measures estimated from pedigree and molecular data from two divergent mouse lines selected for environmental birth weight during 26 generations. Furthermore, the performance of different approaches and both molecular and pedigree data sources for estimating Ne were tested in this population. A total of 1,699 individuals were genotyped using a high-density genotyping array. Genomic relationship matrices were used to calculate molecular inbreeding: Nejati-Javaremi (F NEJ), Li and Horvitz (F L&H), Van Raden method 1 (F VR1) and method 2 (F VR2), and Yang (F YAN). Inbreeding based on runs of homozygosity (F ROH) and pedigree inbreeding (F PED) were also computed. F ROH, F NEJ, and F L&H were also adjusted for their average values in the first generation of selection and named F ROH0, F NEJ0, and F L&H0. ∆F was calculated from pedigrees as the individual inbreeding rate between the individual and his parents (∆F PEDt) and individual increases in inbreeding (∆F PEDi). Moreover, individual ∆F was calculated from the different molecular inbreeding coefficients (∆F NEJ0, ∆F L&H, ∆F L&H0, ∆F VR1, ∆F VR2, ∆F YAN, and ∆F ROH0). The Ne was obtained from different ∆F, such as Ne PEDt, Ne PEDi, Ne NEJ0, Ne L&H, Ne L&H0, Ne VR1, Ne VR2, Ne YAN, and Ne ROH0. Comparing with F PED , F ROH , F NEJ and F VR2 overestimated inbreeding while F NEJ0 , F L&H , F L&H0 , F VR1 and F YAN underestimated inbreeding. Correlations between inbreeding coefficients and ∆F were calculated. F ROH had the highest correlation with F PED (0.89); F YAN had correlations >0.95 with all the other molecular inbreeding coefficients. Ne PEDi was more reliable than Ne PEDt and presented similar behaviour to Ne L&H0 and Ne NEJ0. Stable trends in Ne were not observed until the 10th generation. In the 10th generation Ne PEDi was 42.20, Ne L&H0 was 45.04 and Ne NEJ0 was 45.05 and in the last generation these Ne were 35.65, 35.94 and 35.93, respectively F ROH presented the highest correlation with F PED, which addresses the identity by descent probability (IBD). The evolution of Ne L&H0 and Ne NEJ0 was the most similar to that of Ne PEDi. Data from several generations was necessary to reach a stable trend for Ne, both with pedigree and molecular data. This population was useful to test different approaches to computing inbreeding coefficients and Ne using molecular and pedigree data.

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 .

Exploring how space, time, and sampling impact our ability to measure genetic structure across Plasmodium falciparum populations

A primary use of malaria parasite genomics is identifying highly related infections to quantify epidemiological, spatial, or temporal factors associated with patterns of transmission. For example, spatial clustering of highly related parasites can indicate foci of transmission and temporal differences in relatedness can serve as evidence for changes in transmission over time. However, for infections in settings of moderate to high endemicity, understanding patterns of relatedness is compromised by complex infections, overall high forces of infection, and a highly diverse parasite population. It is not clear how much these factors limit the utility of using genomic data to better understand transmission in these settings. In particular, further investigation is required to determine which patterns of relatedness we expect to see with high quality, densely sampled genomic data in a high transmission setting and how these observations change under different study designs, missingness, and biases in sample collection. Here we investigate two identity-by-state measures of relatedness and apply them to amplicon deep sequencing data collected as part of a longitudinal cohort in Western Kenya that has previously been analysed to identify individual-factors associated with sharing parasites with infected mosquitoes. With these data we use permutation tests, to evaluate several hypotheses about spatiotemporal patterns of relatedness compared to a null distribution. We observe evidence of temporal structure, but not of fine-scale spatial structure in the cohort data. To explore factors associated with the lack of spatial structure in these data, we construct a series of simplified simulation scenarios using an agent based model calibrated to entomological, epidemiological and genomic data from this cohort study to investigate whether the lack of spatial structure observed in the cohort could be due to inherent power limitations of this analytical method. We further investigate how our hypothesis testing behaves under different sampling schemes, levels of completely random and systematic missingness, and different transmission intensities.

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.

Genomic inbreeding coefficients using imputed genotypes: assessing differences among SNP panels in Holstein-Friesian dairy cows

The objective of this study was to evaluate the effect of imputation of single nucleotide polymorphisms (SNP) on the estimation of genomic inbreeding coefficients. Imputed genotypes of 68,127 Italian Holstein dairy cows were analyzed. Cows were initially genotyped with two high density (HD) SNP panels, namely the Illumina Infinium BovineHD BeadChip (678 cows; 777,962 SNP) and the Genomic Profiler HD-150K (641 cows; 139,914 SNP), and four medium density (MD): GeneSeek Genomic Profiler 3 (10,679 cows; 26,151 SNP), GeneSeek Genomic Profiler 4 (33,394 cows; 30,113 SNP), GeneSeek MD (12,030 cows; 47,850 SNP) and the Labogena MD (10,705 cows; 41,911 SNP). After imputation, all cows had genomic information on 84,445 SNP. Seven genomic inbreeding estimators were tested: (i) four PLINK v1.9 estimators (F, F_hat1,2,3), (ii) two genomic relationship matrix (grm) estimators [VanRaden's 1^st method, but with observed allele frequencies (F_grm) and VanRaden's 3^rd method that is allelic free and pedigree dependent (F_grm2)], and (iii) a runs of homozygosity (roh) - based estimator (F_roh). Genomic inbreeding coefficients of each SNP panel were compared with genomic inbreeding coefficients derived from the 84,445 imputation SNP. Coefficients of the HD SNP panels were consistent between genotyped-imputed SNP (Pearson correlations ~99%), while variability across SNP panels and estimators was observed in the MD SNP panels, with Labogena MD providing, on average, more consistent estimates. The robustness of Labogena MD, can be partly explained by the fact that 97.85% of the SNP of this panel is included in the 84,445 SNP selected by ANAFIBJ for routine genomic imputations, while this percentage for the other MD SNP panels varied between 55 and 60%. Runs of homozygosity was the most robust estimator. Genomic inbreeding estimates using imputation SNP are influenced by the SNP number of the SNP panel that are included in the imputed SNP, and performance of genomic inbreeding estimators depends on the imputation.

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.

Genomic prediction of carcass traits using different haplotype block partitioning methods in beef cattle

Genomic prediction (GP) based on haplotype alleles can capture quantitative trait loci (QTL) effects and increase predictive ability because the haplotypes are expected to be in linkage disequilibrium (LD) with QTL. In this study, we constructed haploblocks using LD-based and the fixed number of single nucleotide polymorphisms (fixed-SNP) methods with Illumina BovineHD chip in beef cattle. To evaluate the performance of different haplotype block partitioning methods, we constructed haploblocks based on LD thresholds (from r 2 > 0.2 to r 2 > 0.8) and the number of fixed-SNPs (5, 10, 20). The performance of predictive methods for three carcass traits including liveweight (LW), dressing percentage (DP), and longissimus dorsi muscle weight (LDMW) was evaluated using three approaches (GBLUP and BayesB model based on the SNP, GHBLUP, and BayesBH models based on the haploblock, and GHBLUP+GBLUP and BayesBH+BayesB models based on the combined haploblock and the nonblocked SNPs, which were located between blocks). In this study, we found the accuracies of LD-based and fixed-SNP haplotype Bayesian methods outperformed the Bayesian models (up to 8.54 ± 7.44% and 5.74 ± 2.95%, respectively). GHBLUP showed a high improvement (up to 11.29 ± 9.87%) compared with GBLUP. The Bayesian models have higher accuracies than BLUP models in most scenarios. The average computing time of the BayesBH+BayesB model can reduce by 29.3% compared with the BayesB model. The prediction accuracies using the LD-based haplotype method showed higher improvements than the fixed-SNP haplotype method. In addition, to avoid the influence of rare haplotypes generated from haplotype construction, we compared the performance of GP by filtering four types of minor haplotype allele frequency (MHAF) (0.01, 0.025, 0.05, and 0.1) under different conditions (LD levels were set at r 2 > 0.3, and the fixed number of SNPs was 5). We found the optimal MHAF threshold for LW was 0.01, and the optimal MHAF threshold for DP and LDMW was 0.025.

Comparative analysis of genomic inbreeding parameters and runs of homozygosity islands in several fancy and meat rabbit breeds

Runs of homozygosity (ROH) are defined as long stretches of DNA homozygous at each polymorphic position. The proportion of genome covered by ROH and their length are indicators of the level and origin of inbreeding. In this study, we analysed SNP chip datasets (obtained using the Axiom OrcunSNP Array) of a total of 702 rabbits from 12 fancy breeds and four meat breeds to identify ROH with different approaches and calculate several genomic inbreeding parameters. The highest average number of ROH per animal was detected in Belgian Hare (~150) and the lowest in Italian Silver (~106). The average length of ROH ranged from 4.001 ± 0.556 Mb in Italian White to 6.268 ± 1.355 Mb in Ermine. The same two breeds had the lowest (427.9 ± 86.4 Mb, Italian White) and the highest (921.3 ± 179.8 Mb, Ermine) average values of the sum of all ROH segments. More fancy breeds had a higher level of genomic inbreeding (as defined by ROH) than meat breeds. Several ROH islands contain genes involved in body size, body length, pigmentation processes, carcass traits, growth, and reproduction traits (e.g.: AOX1, GPX5, IFRD1, ITGB8, NELL1, NR3C1, OCA2, TRIB1, TRIB2). Genomic inbreeding parameters can be useful to overcome the lack of information in the management of rabbit genetic resources. ROH provided information to understand, to some extent, the genetic history of rabbit breeds and to identify signatures of selection in the rabbit genome.

Simultaneous testing of rule- and model-based approaches for runs of homozygosity detection opens up a window into genomic footprints of selection in pigs

BACKGROUND

Past selection events left footprints in the genome of domestic animals, which can be traced back by stretches of homozygous genotypes, designated as runs of homozygosity (ROHs). The analysis of common ROH regions within groups or populations displaying potential signatures of selection requires high-quality SNP data as well as carefully adjusted ROH-defining parameters. In this study, we used a simultaneous testing of rule- and model-based approaches to perform strategic ROH calling in genomic data from different pig populations to detect genomic regions under selection for specific phenotypes.

RESULTS

Our ROH analysis using a rule-based approach offered by PLINK, as well as a model-based approach run by RZooRoH demonstrated a high efficiency of both methods. It underlined the importance of providing a high-quality SNP set as input as well as adjusting parameters based on dataset and population for ROH calling. Particularly, ROHs ≤ 20 kb were called in a high frequency by both tools, but to some extent covered different gene sets in subsequent analysis of ROH regions common for investigated pig groups. Phenotype associated ROH analysis resulted in regions under potential selection characterizing heritage pig breeds, known to harbour a long-established breeding history. In particular, the selection focus on fitness-related traits was underlined by various ROHs harbouring disease resistance or tolerance-associated genes. Moreover, we identified potential selection signatures associated with ear morphology, which confirmed known candidate genes as well as uncovered a missense mutation in the ABCA6 gene potentially supporting ear cartilage formation.

CONCLUSIONS

The results of this study highlight the strengths and unique features of rule- and model-based approaches as well as demonstrate their potential for ROH analysis in animal populations. We provide a workflow for ROH detection, evaluating the major steps from filtering for high-quality SNP sets to intersecting ROH regions. Formula-based estimations defining ROHs for rule-based method show its limits, particularly for efficient detection of smaller ROHs. Moreover, we emphasize the role of ROH detection for the identification of potential footprints of selection in pigs, displaying their breed-specific characteristics or favourable phenotypes.

Estimate of inbreeding depression on growth and reproductive traits in a Large White pig population

With the broad application of genomic information, SNP-based measures of estimating inbreeding have been widely used in animal breeding, especially based on runs of homozygosity. Inbreeding depression is better estimated by SNP-based inbreeding coefficients than pedigree-based inbreeding in general. However, there are few comprehensive comparisons of multiple methods in pigs so far, to some extent limiting their application. In this study, to explore an appropriate strategy for estimating inbreeding depression on both growth traits and reproductive traits in a Large White pig population, we compared multiple methods for the inbreeding coefficient estimation based on both pedigree and genomic information. This pig population for analyzing the influence of inbreeding was from a pig breeding farm in the Inner Mongolia of China. There were 26,204 pigs with records of age at 100 kg (AGE) and back-fat thickness at 100 kg (BF), and 6,656 sows with reproductive records of the total number of piglets at birth (TNB), and the number of alive piglets at birth (NBA), and litter weight at birth. Inbreeding depression affected growth and reproductive traits. The results indicated that pedigree-based and SNP-based inbreeding coefficients had significant effects on AGE, TNB, and NBA, except for BF. However, only SNP-based inbreeding coefficients revealed a strong association with inbreeding depression on litter weight at birth. Runs of homozygosity-based methods showed a slight advantage over other methods in the correlation analysis of inbreeding coefficients and estimation of inbreeding depression. Furthermore, our results demonstrated that the model-based approach (RZooRoH) could avoid miscalculations of inbreeding and inbreeding depression caused by inappropriate parameters, which had a good performance on both AGE and reproductive traits. These findings might improve the extensive application of runs of homozygosity analysis in pig breeding and breed conservation.

Heterozygous PNPT1 variants cause spinocerebellar ataxia type 25

OBJECTIVE

Dominant spinocerebellar ataxias (SCA) are characterized by genetic heterogeneity. Some mapped and named loci remain without a causal gene identified. Here we applied next generation sequencing (NGS) to uncover the genetic etiology of the SCA25 locus.

METHODS

Whole-exome and whole-genome sequencing were performed in families linked to SCA25, including the French family in which the SCA25 locus was originally mapped. Whole exome sequence data was interrogated in a cohort of 796 ataxia patients of unknown aetiology.

RESULTS

The SCA25 phenotype spans a slowly evolving sensory and cerebellar ataxia, in most cases attributed to ganglionopathy. A pathogenic variant causing exon skipping was identified in the gene encoding Polyribonucleotide Nucleotidyltransferase PNPase 1 (PNPT1) located in the SCA25 linkage interval. A second splice variant in PNPT1 was detected in a large Australian family with a dominant ataxia also mapping to SCA25. An additional nonsense variant was detected in an unrelated individual with ataxia. Both nonsense and splice heterozygous variants result in premature stop codons, all located in the S1-domain of PNPase. In addition, an elevated type I interferon response was observed in blood from all affected heterozygous carriers tested. PNPase notably prevents the abnormal accumulation of double-stranded mtRNAs in the mitochondria and leakage into the cytoplasm, associated with triggering a type I interferon response.

INTERPRETATION

This study identifies PNPT1 as a new SCA gene, responsible for SCA25, and highlights biological links between alterations of mtRNA trafficking, interferonopathies and ataxia. This article is protected by copyright. All rights reserved.

Correspondence Between Genomic- and Genealogical/Coalescent-Based Inference of Homozygosity by Descent in Large French-Canadian Genealogies

Research on the genetics of complex traits overwhelmingly focuses on the additive effects of genes. Yet, animal studies have shown that non-additive effects, in particular homozygosity effects, can shape complex traits. Recent investigations in human studies found some significant homozygosity effects. However, most human populations display restricted ranges of homozygosity by descent (HBD), making the identification of homozygosity effects challenging. Founder populations give rise to higher HBD levels. When deep genealogical data are available in a founder population, it is possible to gain information on the time to the most recent common ancestor (MRCA) from whom a chromosomal segment has been transmitted to both parents of an individual and in turn to that individual. This information on the time to MRCA can be combined with the time to MRCA inferred from coalescent models of gene genealogies. HBD can also be estimated from genomic data. The extent to which the genomic HBD measures correspond to the genealogical/coalescent measures has not been documented in founder populations with extensive genealogical data. In this study, we used simulations to relate genomic and genealogical/coalescent HBD measures. We based our simulations on genealogical data from two ongoing studies from the French-Canadian founder population displaying different levels of inbreeding. We simulated single-nucleotide polymorphisms (SNPs) in a 1-Mb genomic segment from a coalescent model in conjunction with the observed genealogical data. We compared genealogical/coalescent HBD to two genomic methods of HBD estimation based on hidden Markov models (HMMs). We found that genomic estimates of HBD correlated well with genealogical/coalescent HBD measures in both study genealogies. We described generation time to coalescence in terms of genomic HBD estimates and found a large variability in generation time captured by genomic HBD when considering each SNP. However, SNPs in longer segments were more likely to capture recent time to coalescence, as expected. Our study suggests that estimating the coalescent gene genealogy from the genomic data to use in conjunction with observed genealogical data could provide valuable information on HBD.

A family study implicates GBE1 in the etiology of autism spectrum disorder

Autism spectrum disorders (ASD) are neurodevelopmental disorders with an estimated heritability of >60%. Family-based genetic studies of ASD have generally focused on multiple small kindreds, searching for de novo variants of major effect. We hypothesized that molecular genetic analysis of large multiplex families would enable the identification of variants of milder effects. We studied a large multigenerational family of European ancestry with multiple family members affected with ASD or the broader autism phenotype (BAP). We identified a rare heterozygous variant in the gene encoding 1,4-ɑ-glucan branching enzyme 1 (GBE1) that was present in seven of seven individuals with ASD, nine of ten individuals with the BAP, and none of four tested unaffected individuals. We genotyped a community-acquired cohort of 389 individuals with ASD and identified three additional probands. Cascade analysis demonstrated that the variant was present in 11 of 13 individuals with familial ASD/BAP and neither of the two tested unaffected individuals in these three families, also of European ancestry. The variant was not enriched in the combined UK10K ASD cohorts of European ancestry but heterozygous GBE1 deletion was overrepresented in large ASD cohorts, collectively suggesting an association between GBE1 and ASD.

Unraveling Admixture, Inbreeding, and Recent Selection Signatures in West African Indigenous Cattle Populations in Benin

The Dwarf Lagune and the Savannah Somba cattle in Benin are typical representatives of the endangered West African indigenous Shorthorn taurine. The Lagune was previously exported to African and European countries and bred as Dahomey cattle, whereas the Somba contributed to the formation of two indigenous hybrids known as Borgou and Pabli cattle. These breeds are affected by demographic, economic, and environmental pressures in local production systems. Considering current and historical genomic data, we applied a formal test of admixture, estimated admixture proportions, and computed genomic inbreeding coefficients to characterize the five breeds. Subsequently, we unraveled the most recent selection signatures using the cross-population extended haplotype homozygosity approach, based on the current and historical genotypes. Results from principal component analyses and high proportion of Lagune ancestry confirm the Lagune origin of the European Dahomey cattle. Moreover, the Dahomey cattle displayed neither indicine nor European taurine (EUT) background, but they shared on average 40% of autozygosity from common ancestors, dated approximately eight generations ago. The Lagune cattle presented inbreeding coefficients larger than 0.13; however, the Somba and the hybrids (Borgou and Pabli) were less inbred (≤0.08). We detected evidence of admixture in the Somba and Lagune cattle, but they exhibited a similar African taurine (AFT) ancestral proportion (≥96%) to historical populations, respectively. A moderate and stable AFT ancestral proportion (62%) was also inferred for less admixed hybrid cattle including the Pabli. In contrast, the current Borgou samples displayed a lower AFT ancestral proportion (47%) than historical samples (63%). Irrespective of the admixture proportions, the hybrid populations displayed more selection signatures related to economic traits (reproduction, growth, and milk) than the taurine. In contrast, the taurine, especially the Somba, presented several regions known to be associated with adaptive traits (immunity and feed efficiency). The identified subregion of bovine leukocyte antigen (BoLA) class IIb (including DSB and BOLA-DYA) in Somba cattle is interestingly uncommon in other African breeds, suggesting further investigations to understand its association with specific adaptation to endemic diseases in Benin. Overall, our study provides deeper insights into recent evolutionary processes in the Beninese indigenous cattle and their aptitude for conservation and genetic improvement.

Comparative analysis of inbreeding parameters and runs of homozygosity islands in 2 Italian autochthonous cattle breeds mainly raised in the Parmigiano-Reggiano cheese production region

Reggiana and Modenese are autochthonous cattle breeds, reared in the North of Italy, that can be mainly distinguished for their standard coat color (Reggiana is red, whereas Modenese is white with some pale gray shades). Almost all milk produced by these breeds is transformed into 2 mono-breed branded Parmigiano-Reggiano cheeses, from which farmers receive the economic incomes needed for the sustainable conservation of these animal genetic resources. After the setting up of their herd books in 1960s, these breeds experienced a strong reduction in the population size that was subsequently reverted starting in the 1990s (Reggiana) or more recently (Modenese) reaching at present a total of about 2,800 and 500 registered cows, respectively. Due to the small population size of these breeds, inbreeding is a very important cause of concern for their conservation programs. Inbreeding is traditionally estimated using pedigree data, which are summarized in an inbreeding coefficient calculated at the individual level (F_PED). However, incompleteness of pedigree information and registration errors can affect the effectiveness of conservation strategies. High-throughput SNP genotyping platforms allow investigation of inbreeding using genome information that can overcome the limits of pedigree data. Several approaches have been proposed to estimate genomic inbreeding, with the use of runs of homozygosity (ROH) considered to be the more appropriate. In this study, several pedigree and genomic inbreeding parameters, calculated using the whole herd book populations or considering genotyping information (GeneSeek GGP Bovine 150K) from 1,684 Reggiana cattle and 323 Modenese cattle, were compared. Average inbreeding values per year were used to calculate effective population size. Reggiana breed had generally lower genomic inbreeding values than Modenese breed. The low correlation between pedigree-based and genomic-based parameters (ranging from 0.187 to 0.195 and 0.319 to 0.323 in the Reggiana and Modenese breeds, respectively) reflected the common problems of local populations in which pedigree records are not complete. The high proportion of short ROH over the total number of ROH indicates no major recent inbreeding events in both breeds. ROH islands spread over the genome of the 2 breeds (15 in Reggiana and 14 in Modenese) identified several signatures of selection. Some of these included genes affecting milk production traits, stature, body conformation traits (with a main ROH island in both breeds on BTA6 containing the ABCG2, NCAPG, and LCORL genes) and coat color (on BTA13 in Modenese containing the ASIP gene). In conclusion, this work provides an extensive comparative analysis of pedigree and genomic inbreeding parameters and relevant genomic information that will be useful in the conservation strategies of these 2 iconic local cattle breeds.

ROHMM-A flexible hidden Markov model framework to detect runs of homozygosity from genotyping data

Runs of long homozygous (ROH) stretches are considered to be the result of consanguinity and usually contain recessive deleterious disease-causing mutations. Several algorithms have been developed to detect ROHs. Here, we developed a simple alternative strategy by examining X chromosome non-pseudoautosomal region to detect the ROHs from next-generation sequencing data utilizing the genotype probabilities and the hidden Markov model algorithm as a tool, namely ROHMM. It is implemented purely in java and contains both a command line and a graphical user interface. We tested ROHMM on simulated data as well as real population data from the 1000G Project and a clinical sample. Our results have shown that ROHMM can perform robustly producing highly accurate homozygosity estimations under all conditions thereby meeting and even exceeding the performance of its natural competitors.

Estimating inbreeding depression for growth and reproductive traits using pedigree and genomic methods in Argentinean Brangus cattle

Inbreeding depression reduces the mean phenotypic value of important traits in livestock populations. The goal of this work was to estimate the level of inbreeding and inbreeding depression for growth and reproductive traits in Argentinean Brangus cattle, in order to obtain a diagnosis and monitor breed management. Data comprised 359,257 (from which 1,990 were genotyped for 40,678 single nucleotide polymorphisms [SNPs]) animals with phenotypic records for at least one of three growth traits: birth weight (BW), weaning weight (WW), and finishing weight (FW). For scrotal circumference (SC), 52,399 phenotypic records (of which 256 had genotype) were available. There were 530,938 animals in pedigree. Three methods to estimate inbreeding coefficients were used. Pedigree-based inbreeding coefficients were estimated accounting for missing parents. Inbreeding coefficients combining genotyped and nongenotyped animal information were also computed from matrix H of the single-step approach. Genomic inbreeding coefficients were estimated using homozygous segments obtained from a Hidden Markov model (HMM) approach. Inbreeding depression was estimated from the regression of the phenotype on inbreeding coefficients in a multiple-trait mixed model framework, either for the whole dataset or for the dataset of genotyped animals. All traits were unfavorably affected by inbreeding depression. A 10% increase in pedigree-based or combined inbreeding would result in a reduction of 0.34 to 0.39 kg in BW, 2.77 to 3.28 kg in WW, and 0.23 cm in SC. For FW, a 10% increase in pedigree-based, genomic, or combined inbreeding would result in a decrease of 8.05 to 11.57 kg. Genomic inbreeding based on the HMM was able to capture inbreeding depression, even in such a compressed genotyped dataset.

End-Truncated LAMB1 Causes a Hippocampal Memory Defect and a Leukoencephalopathy

OBJECTIVE

The majority of patients with a familial cerebral small vessel disease (CSVD) referred for molecular screening do not show pathogenic variants in known genes. In this study, we aimed to identify novel CSVD causal genes.

METHODS

We performed a gene-based collapsing test of rare protein-truncating variants identified in exome data of 258 unrelated CSVD patients of an ethnically matched control cohort and of 2 publicly available large-scale databases, gnomAD and TOPMed. Western blotting was used to investigate the functional consequences of variants. Clinical and magnetic resonance imaging features of mutated patients were characterized.

RESULTS

We showed that LAMB1 truncating variants escaping nonsense-mediated messenger RNA decay are strongly overrepresented in CSVD patients, reaching genome-wide significance (p < 5 × 10^-8 ). Using 2 antibodies recognizing the N- and C-terminal parts of LAMB1, we showed that truncated forms of LAMB1 are expressed in the endogenous fibroblasts of patients and trapped in the cytosol. These variants are associated with a novel phenotype characterized by the association of a hippocampal type episodic memory defect and a diffuse vascular leukoencephalopathy.

INTERPRETATION

These findings are important for diagnosis and clinical care, to avoid unnecessary and sometimes invasive investigations, and also from a mechanistic point of view to understand the role of extracellular matrix proteins in neuronal homeostasis. ANN NEUROL 2021;90:962-975.

Parental relatedness through time revealed by runs of homozygosity in ancient DNA

Parental relatedness of present-day humans varies substantially across the globe, but little is known about the past. Here we analyze ancient DNA, leveraging that parental relatedness leaves genomic traces in the form of runs of homozygosity. We present an approach to identify such runs in low-coverage ancient DNA data aided by haplotype information from a modern phased reference panel. Simulation and experiments show that this method robustly detects runs of homozygosity longer than 4 centimorgan for ancient individuals with at least 0.3 × coverage. Analyzing genomic data from 1,785 ancient humans who lived in the last 45,000 years, we detect low rates of first cousin or closer unions across most ancient populations. Moreover, we find a marked decay in background parental relatedness co-occurring with or shortly after the advent of sedentary agriculture. We observe this signal, likely linked to increasing local population sizes, across several geographic transects worldwide.

Genomic data of different resolutions reveal consistent inbreeding estimates but contrasting homozygosity landscapes for the threatened Aotearoa New Zealand hihi

Inbreeding can lead to a loss of heterozygosity in a population and when combined with genetic drift may reduce the adaptive potential of a species. However, there is uncertainty about whether resequencing data can provide accurate and consistent inbreeding estimates. Here, we performed an in-depth inbreeding analysis for hihi (Notiomystis cincta), an endemic and nationally vulnerable passerine bird of Aotearoa New Zealand. We first focused on subsampling variants from a reference genome male, and found that low-density data sets tend to miss runs of homozygosity (ROH) in some places and overestimate ROH length in others, resulting in contrasting homozygosity landscapes. Low-coverage resequencing and 50 K SNP array densities can yield comparable inbreeding results to high-coverage resequencing approaches, but the results for all data sets are highly dependent on the software settings employed. Second, we extended our analysis to 10 hihi where low-coverage whole genome resequencing, RAD-seq and SNP array genotypes are available. We inferred ROH and individual inbreeding to evaluate the relative effects of sequencing depth versus SNP density on estimating inbreeding coefficients and found that high rates of missingness downwardly bias both the number and length of ROH. In summary, when using genomic data to evaluate inbreeding, studies must consider that ROH estimates are heavily dependent on analysis parameters, data set density and individual sequencing depth.

How Depressing Is Inbreeding? A Meta-Analysis of 30 Years of Research on the Effects of Inbreeding in Livestock

Inbreeding depression has been widely documented for livestock and other animal and plant populations. Inbreeding is generally expected to have a stronger unfavorable effect on fitness traits than on other traits. Traditionally, the degree of inbreeding depression in livestock has been estimated as the slope of the linear regression of phenotypic values on pedigree-based inbreeding coefficients. With the increasing availability of SNP-data, pedigree inbreeding can now be replaced by SNP-based measures. We performed a meta-analysis of 154 studies, published from 1990 to 2020 on seven livestock species, and compared the degree of inbreeding depression (1) across different trait groups, and (2) across different pedigree-based and SNP-based measures of inbreeding. Across all studies and traits, a 1% increase in pedigree inbreeding was associated with a median decrease in phenotypic value of 0.13% of a trait’s mean, or 0.59% of a trait’s standard deviation. Inbreeding had an unfavorable effect on all sorts of traits and there was no evidence for a stronger effect on primary fitness traits (e.g., reproduction/survival traits) than on other traits (e.g., production traits or morphological traits). p-values of inbreeding depression estimates were smaller for SNP-based inbreeding measures than for pedigree inbreeding, suggesting more power for SNP-based measures. There were no consistent differences in p-values for percentage of homozygous SNPs, inbreeding based on runs of homozygosity (ROH) or inbreeding based on a genomic relationship matrix. The number of studies that directly compares these different measures, however, is limited and comparisons are furthermore complicated by differences in scale and arbitrary definitions of particularly ROH-based inbreeding. To facilitate comparisons across studies in future, we provide the dataset with inbreeding depression estimates of 154 studies and stress the importance of always reporting detailed information (on traits, inbreeding coefficients, and models used) along with inbreeding depression estimates.

Genome-Wide Association Study Provides Insights into Important Genes for Reproductive Traits in Nelore Cattle

Simple Summary

In this study, we investigated the association between single nucleotide polymorphisms (SNPs) and reproductive traits in order to identify candidate genes and biological pathways associated with these traits in Nelore beef cattle. The genome-wide association analysis revealed genomic regions that could explain part of the genetic variance of the studied traits. The results revealed genes with important functions for reproductive traits, such as fertility and precocity. Some genes were associated with more than one trait, being important for reproductive efficiency. The identification of candidate genes that were associated with the studied traits as well as genes enriched in the functional terms and pathways may be useful for exploring the genetic architecture underlying reproductive traits and may be used in Nelore breeding programs.

Abstract

The identification of genomic regions associated with reproductive traits as well as their biological processes allows a better understanding of the phenotypic variability of these traits. This information could be applied to animal breeding programs to accelerate genetic gain. The aim of this study was to evaluate the association between single nucleotide polymorphisms (SNP) with a scrotal circumference at 365 days of age (SC365) and at 450 days of age (SC450), gestation length (GL) as a calf trait, age at first calving (AFC), accumulated productivity (ACP), heifer early calving until 30 months (HC30), and stayability (STAY) traits, in order to identify candidate genes and biological pathways associated with reproductive traits in Nelore cattle. The data set consisted of pedigree, phenotypes, and genotypes of Nelore cattle from the “Associação Nacional de Criadores e Pesquisadores” (ANCP). The association analyses were performed using the Weighted Single-Step Genome-Wide Association method; the regions, consisting of 10 consecutive SNP, which explained more than 0.5% of additive genetic variance, were considered as a significant association. A total of 3, 6, 7, 5, 10, 25, and 12 windows were associated with SC355, SC450, GL, AFC, ACP, HC30, and STAY, respectively. The results revealed genes with important functions for reproductive traits, such as fertility and precocity. Some genes were associated with more than one trait, among them CAMK1D, TASP1, ACOXL, RAB11FIP5, and SFXN5. Moreover, the genes were enriched in functional terms, like negative regulation of fat cell differentiation, fatty acid alpha-oxidation, and sphingolipids signaling pathway. The identification of the genes associated with the traits, as well as genes enriched in the terms and pathway mentioned above, should contribute to future biological validation studies and may be used as candidate genes in Nelore breeding programs.

Runs of homozygosity provide a genome landscape picture of inbreeding and genetic history of European autochthonous and commercial pig breeds

ROHs are long stretches of DNA homozygous at each polymorphic position. The proportion of genome covered by ROHs and their length are indicators of the level and origin of inbreeding. Frequent common ROHs within the same population define ROH islands and indicate hotspots of selection. In this work, we investigated ROHs in a total of 1131 pigs from 20 European local pig breeds and in three cosmopolitan breeds, genotyped with the GGP Porcine HD Genomic Profiler. plink software was used to identify ROHs. Size classes and genomic inbreeding parameters were evaluated. ROH islands were defined by evaluating different thresholds of homozygous SNP frequency. A functional overview of breed-specific ROH islands was obtained via over-representation analyses of GO biological processes. Mora Romagnola and Turopolje breeds had the largest proportions of genome covered with ROH (~1003 and ~955 Mb respectively), whereas Nero Siciliano and Sarda breeds had the lowest proportions (~207 and 247 Mb respectively). The highest proportion of long ROH (>16 Mb) was in Apulo-Calabrese, Mora Romagnola and Casertana. The largest number of ROH islands was identified in the Italian Landrace (n = 32), Cinta Senese (n = 26) and Lithuanian White Old Type (n = 22) breeds. Several ROH islands were in regions encompassing genes known to affect morphological traits. Comparative ROH structure analysis among breeds indicated the similar genetic structure of local breeds across Europe. This study contributed to understanding of the genetic history of the investigated pig breeds and provided information to manage these pig genetic resources.

Probabilistic Estimation of Identity by Descent Segment Endpoints and Detection of Recent Selection

Most methods for fast detection of identity by descent (IBD) segments report identity by state segments without any quantification of the uncertainty in the endpoints and lengths of the IBD segments. We present a method for determining the posterior probability distribution of IBD segment endpoints. Our approach accounts for genotype errors, recent mutations, and gene conversions which disrupt DNA sequence identity within IBD segments, and it can be applied to large cohorts with whole-genome sequence or SNP array data. We find that our method's estimates of uncertainty are well calibrated for homogeneous samples. We quantify endpoint uncertainty for 77.7 billion IBD segments from 408,883 individuals of white British ancestry in the UK Biobank, and we use these IBD segments to find regions showing evidence of recent natural selection. We show that many spurious selection signals are eliminated by the use of unbiased estimates of IBD segment endpoints and a pedigree-based genetic map. Eleven of the twelve regions with the greatest evidence for recent selection in our scan have been identified as selected in previous analyses using different approaches. Our computationally efficient method for quantifying IBD segment endpoint uncertainty is implemented in the open source ibd-ends software package.

Single-Step Genomic Evaluations from Theory to Practice: Using SNP Chips and Sequence Data in BLUPF90

Single-step genomic evaluation became a standard procedure in livestock breeding, and the main reason is the ability to combine all pedigree, phenotypes, and genotypes available into one single evaluation, without the need of post-analysis processing. Therefore, the incorporation of data on genotyped and non-genotyped animals in this method is straightforward. Since 2009, two main implementations of single-step were proposed. One is called single-step genomic best linear unbiased prediction (ssGBLUP) and uses single nucleotide polymorphism (SNP) to construct the genomic relationship matrix; the other is the single-step Bayesian regression (ssBR), which is a marker effect model. Under the same assumptions, both models are equivalent. In this review, we focus solely on ssGBLUP. The implementation of ssGBLUP into the BLUPF90 software suite was done in 2009, and since then, several changes were made to make ssGBLUP flexible to any model, number of traits, number of phenotypes, and number of genotyped animals. Single-step GBLUP from the BLUPF90 software suite has been used for genomic evaluations worldwide. In this review, we will show theoretical developments and numerical examples of ssGBLUP using SNP data from regular chips to sequence data.

Genetic architecture of individual variation in recombination rate on the X chromosome in cattle

Meiotic recombination is an essential biological process that ensures proper chromosome segregation and creates genetic diversity. Individual variation in global recombination rates has been shown to be heritable in several species, and variants significantly associated with this trait have been identified. Recombination on the sex chromosome has often been ignored in these studies although this trait may be particularly interesting as it may correspond to a biological process distinct from that on autosomes. For instance, recombination in males is restricted to the pseudo-autosomal region (PAR). We herein used a large cattle pedigree with more than 100,000 genotyped animals to improve the genetic map of the X chromosome and to study the genetic architecture of individual variation in recombination rate on the sex chromosome (XRR). The length of the genetic map was 46.4 and 121.2 cM in males and females, respectively, but the recombination rate in the PAR was six times higher in males. The heritability of CO counts on the X chromosome was comparable to that of autosomes in males (0.011) but larger than that of autosomes in females (0.024). XRR was highly correlated (0.76) with global recombination rate (GRR) in females, suggesting that both traits might be governed by shared variants. In agreement, a set of eleven previously identified variants associated with GRR had correlated effects on female XRR (0.86). In males, XRR and GRR appeared to be distinct traits, although more accurate CO counts on the PAR would be valuable to confirm these results.

Autozygosity-driven genetic diagnosis in consanguineous families from Italy and the Greater Middle East

Autozygosity-driven exome analysis has been shown effective for identification of genes underlying recessive diseases especially in countries of the so-called Greater Middle East (GME), where high consanguinity unravels the phenotypic effects of recessive alleles and large family sizes facilitate homozygosity mapping. In Italy, as in most European countries, consanguinity is estimated low. Nonetheless, consanguineous Italian families are not uncommon in publications of genetic findings and are often key to new associations of genes with rare diseases. We collected 52 patients from 47 consanguineous families with suspected recessive diseases, 29 originated in GME countries and 18 of Italian descent. We performed autozygosity-driven exome analysis by detecting long runs of homozygosity (ROHs > 1.5 Mb) and by prioritizing candidate clinical variants within. We identified a pathogenic synonymous variant that had been previously missed in NARS2 and we increased an initial high diagnostic rate (47%) to 55% by matchmaking our candidate genes and including in the analysis shorter ROHs that may also happen to be autozygous. GME and Italian families contributed to diagnostic yield comparably. We found no significant difference either in the extension of the autozygous genome, or in the distribution of candidate clinical variants between GME and Italian families, while we showed that the average autozygous genome was larger and the mean number of candidate clinical variants was significantly higher (p = 0.003) in mutation-positive than in mutation-negative individuals, suggesting that these features influence the likelihood that the disease is autozygosity-related. We highlight the utility of autozygosity-driven genomic analysis also in countries and/or communities, where consanguinity is not widespread cultural tradition.

Effect of genomic selection on rate of inbreeding and coancestry and effective population size of Holstein and Jersey cattle populations

Genetic diversity in livestock populations is a significant contributor to the sustainability of animal production. Also, genetic diversity allows animal production to become more responsive to environmental changes and market demands. The loss of genetic diversity can result in a plateau in production and may also result in loss of fitness or viability in animal production. In this study, we investigated the rate of inbreeding (ΔF), rate of coancestry (Δf), and effective population size (N_e) as important quantitative indicators of genetic diversity and evaluated the effect of the recent implementation of genomic selection on the loss of genetic diversity in North American Holstein and Jersey dairy cattle. To estimate the rate of inbreeding and coancestry, inbreeding and coancestry coefficients were calculated using the traditional pedigree method and genomic methods estimated from segment- and marker-based approaches. Furthermore, we estimated N_e from the rate of inbreeding and coancestry and extent of linkage disequilibrium. A total of 205,755 and 89,238 pedigreed and genotyped animals born between 1990 and 2018 inclusively were available for Holsteins and Jerseys, respectively. The estimated average pedigree inbreeding coefficients were 7.74 and 7.20% for Holsteins and Jerseys, respectively. The corresponding values for the segment and marker-by-marker genomic inbreeding coefficients were 13.61, 15.64, and 31.40% for Holsteins and 21.16, 22.54, and 42.62% for Jerseys, respectively. The average coancestry coefficients were 8.33 and 15.84% for Holsteins and 9.23 and 23.46% for Jerseys with pedigree and genomic measures, respectively. Generation interval for the whole 29-yr time period averaged approximately 5 yr for all selection pathways combined. The ΔF per generation based on pedigree, segment, and marker-by-marker genomic measures for the entire 29-yr period was estimated to be 0.75, 1.10, 1.16, and 1.02% for Holstein animals and 0.67, 0.62, 0.63, and 0.59% for Jersey animals, respectively. The Δf was estimated to be 0.98 and 0.98% for Holsteins and 0.73 and 0.78% for Jerseys with pedigree and genomic measures, respectively. These ΔF and Δf translated to an N_e that ranged from 43 to 66 animals for Holsteins and 64 to 85 animals for Jerseys. In addition, the N_e based on linkage disequilibrium was 58 and 120 for Holsteins and Jerseys, respectively. The 10-yr period that involved the application of genomic selection resulted in an increased ΔF per generation with ranges from 1.19 to 2.06% for pedigree and genomic measures in Holsteins. Given the rate at which inbreeding is increasing after the implementation of genomic selection, there is a need to implement measures and means for controlling the rate of inbreeding per year, which will help to manage and maintain farm animal genetic resources.

A Fast and Simple Method for Detecting Identity-by-Descent Segments in Large-Scale Data

Segments of identity by descent (IBD) are used in many genetic analyses. We present a method for detecting identical-by-descent haplotype segments in phased genotype data. Our method, called hap-IBD, combines a compressed representation of haplotype data, the positional Burrows-Wheeler transform, and multi-threaded execution to produce very fast analysis times. An attractive feature of hap-IBD is its simplicity: the input parameters clearly and precisely define the IBD segments that are reported, so that program correctness can be confirmed by users. We evaluate hap-IBD and four state-of-the-art IBD segment detection methods (GERMLINE, iLASH, RaPID, and TRUFFLE) using UK Biobank chromosome 20 data and simulated sequence data. We show that hap-IBD detects IBD segments faster and more accurately than competing methods, and that hap-IBD is the only method that can rapidly and accurately detect short 2-4 centiMorgan (cM) IBD segments in the full UK Biobank data. Analysis of 485,346 UK Biobank samples through the use of hap-IBD with 12 computational threads detects 231.5 billion autosomal IBD segments with length ≥2 cM in 24.4 h.

A homozygous UBA5 pathogenic variant causes a fatal congenital neuropathy

BACKGROUND

UBA5 is the activating enzyme of UFM1 in the ufmylation post-translational modification system. Different neurological phenotypes have been associated with UBA5 pathogenic variants including epilepsy, intellectual disability, movement disorders and ataxia.

METHODS AND RESULTS

We describe a large multigenerational consanguineous family presenting with a severe congenital neuropathy causing early death in infancy. Whole exome sequencing and linkage analysis identified a novel homozygous UBA5 NM_024818.3 c.31C>T (p.Arg11Trp) mutation. Protein expression assays in mouse tissue showed similar levels of UBA5 in peripheral nerves to the central nervous system. CRISPR-Cas9 edited HEK (human embrionic kidney) cells homozygous for the UBA5 p.Arg11Trp mutation showed reduced levels of UBA5 protein compared with the wild-type. The mutant p.Arg11Trp UBA5 protein shows reduced ability to activate UFM1.

CONCLUSION

This report expands the phenotypical spectrum of UBA5 mutations to include fatal peripheral neuropathy.

The Iberian legacy into a young genetic xeroderma pigmentosum cluster in central Brazil

In central Brazil, in the municipality of Faina (state of Goiás), the small and isolated village of Araras comprises a genetic cluster of xeroderma pigmentosum (XP) patients. The high level of consanguinity and the geographical isolation gave rise to a high frequency of XP patients. Recently, two founder events were identified affecting that community, with two independent mutations at the POLH gene, c.764 + 1 G > A (intron 6) and c.907 C > T; p.Arg303* (exon 8). These deleterious mutations lead to the xeroderma pigmentosum variant syndrome (XP-V). Previous reports identified both mutations in other countries: the intron 6 mutation in six patients (four families) from Northern Spain (Basque Country and Cantabria) and the exon 8 mutation in two patients from different families in Europe, one of them from Kosovo. In order to investigate the ancestry of the XP patients and the age for these mutations at Araras, we generated genotyping information for 22 XP-V patients from Brazil (16), Spain (6) and Kosovo (1). The local genomic ancestry and the shared haplotype segments among the patients showed that the intron 6 mutation at Araras is associated with an Iberian genetic legacy. All patients from Goiás, homozygotes for intron 6 mutation, share with the Spanish patients identical-by-descent (IBD) genomic segments comprising the mutation. The entrance date for the Iberian haplotype at the village was calculated to be approximately 200 years old. This result is in agreement with the historical arrival of Iberian individuals at the Goiás state (BR). Patients from Goiás and the three families from Spain share 1.8 cM (family 14), 1.7 cM (family 15), and a more significant segment of 4.7 cM within family 13. On the other hand, the patients carrying the exon 8 mutation do not share any specific genetic segment, indicating an old genetic distance between them or even no common ancestry.

Jeanne Calment's Unique 122-Year Life Span: Facts and Factors; Longevity History in Her Genealogical Tree

Jeanne Calment's (JC) still unmatched validated human life span of 122 years and 164 days, over 3 years longer than any other, surprises many. While her case is broadly accepted as a golden standard of validation, her record age still raises skepticism among some. The probability of such a record to be achieved by someone born in the second half of the 19th century, in the world population documentarily eligible to age validation, and also in the G7 countries, can be calculated by applying some logistic and Gompertz mortality models to these populations, taken, respectively, from the age of 117 and of 100. This probability appears substantial, respectively, 7.1% and 4.7%, when using a four-parameter logistic model, which I validated on the observed survivals of centenarians until the age of 118. A 3-year interval with the second oldest is then expected. The known facts and documents constitute consistent evidence that JC died at 122: regular official records during her life, her verified memories from her 19th century life, her usage of specialized terms and of an abbreviation system specific to this period of time, photographs, her signature and handwriting, testimonies from numerous witnesses of her life, plus the expertise of gerontologists. Meanwhile, nothing contradicts her record: the daughter/mother identity swap hypothesis appears unrealistic and not supported by any evidence; especially no plausible motive can be found, on the contrary. The latest article, which defends this hypothesis, "Bayesian assessment of the longevity of JC," contains major errors, making its result subjective and invalid. The study of JC's genealogical tree on six generations, using longevity performance and total immediate ancestor longevity indicators, shows how, in two centuries, her ancestors have been living 10% longer on average at each generation, increasingly overperforming their French 25-year-old contemporaries, from around 7% in the early 18th century to 43% for her parents, and up to 56% for her older brother and 80% for herself, which suggests a progressive concentration of longevity factors. In addition to the hereditary factors, JC's personal overperformance suggests also some environmental factors, and indeed many are known. Further knowledge could be obtained by studying JC's existing blood and DNA samples: those could not only provide an additional proof of her authenticity, but more importantly could be of immense contribution for understanding deeper the factors and patterns of her longevity, and more generally the longevity and aging processes in humans in general as well.

Genome-wide association study for carcass quality traits and growth in purebred and crossbred pigs1

Carcass quality traits such as back fat (BF), loin depth (LD), and ADG are of extreme economic importance for the swine industry. This study aimed to (i) estimate the genetic parameters for such traits and (ii) conduct a single-step genome-wide association study (ssGWAS) to identify genomic regions that affect carcass quality and growth traits in purebred (PB) and three-way crossbred (CB) pigs. A total of 28,497 PBs and 135,768 CBs pigs were phenotyped for BF, LD, and ADG. Of these, 4,857 and 3,532 were genotyped using the Illumina PorcineSNP60K Beadchip. After quality control, 36,328 SNPs were available and were used to perform an ssGWAS. A bootstrap analysis (n = 1,000) and a signal enrichment analysis were performed to declare SNP significance. Genome regions were based on the variance explained by significant 10-SNP sliding windows. Estimates of PB heritability (SE) were 0.42 (0.019) for BF, 0.39 (0.020) for LD, and 0.35 (0.021) for ADG. Estimates of CB heritability were 0.49 (0.042) for BF, 0.27 (0.029) for LD, and 0.12 (0.021) for ADG. Genetic correlations (SE) across the two populations were 0.81 (0.02), 0.79 (0.04), and 0.56 (0.05), for BF, LD, and ADG, respectively. The variance explained by significant regions for each trait in PBs ranged from 1.51% to 1.35% for BF, from 4.02% to 3.18% for LD, and from 2.26% to 1.45% for ADG. In CBs, the variance explained by significant regions ranged from 1.88% to 1.37% for BF, from 1.29% to 1.23% for LD, and from 1.54% to 1.32% for ADG. In this study, we have described regions of the genome that determine carcass quality and growth traits of PB and CB pigs. These results provide evidence that there are overlapping and nonoverlapping regions in the genome influencing carcass quality and growth traits in PBs and three-way CB pigs.

Efficient computation of the kinship coefficients

MOTIVATION

For families, kinship coefficients are quantifications of the amount of genetic sharing between a pair of individuals. These coefficients are critical for understanding the breeding habits and genetic diversity of diploid populations. Historically, computations of the inbreeding coefficient were used to prohibit inbred marriages and prohibit breeding of some pairs of pedigree animals. Such prohibitions foster genetic diversity and help prevent recessive Mendelian disease at a population level.

RESULTS

This paper gives the fastest known algorithms for computing the kinship coefficient of a set of individuals with a known pedigree, especially for large pedigrees. These algorithms outperform existing methods. In addition, the algorithms given here consider the possibility that the founders of the known pedigree may themselves be inbred and compute the appropriate inbreeding-adjusted kinship coefficients, which has not been addressed in literature. The exact kinship algorithm has running-time O(n2) for an n-individual pedigree. The recursive-cut exact kinship algorithm has running time O(s2m) where s is the number of individuals in the largest segment of the pedigree and m is the number of cuts. The approximate algorithm has running-time O(nd) for an n-individual pedigree on which to estimate the kinship coefficients of n individuals of interest from n founder kinship coefficients and d is the number of samples.

AVAILABILITY AND IMPLEMENTATION

The above polynomial-time exact algorithm and the linear-time approximation algorithms are implemented as PedKin in C++ and are available under the GNU GPL v2.0 open source license. The PedKin source code is available at: http://www.intrepidnetcomputing.com/research/code/.

Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.

Gene-based association analysis of survival traits via functional regression-based mixed effect cox models for related samples

The importance to integrate survival analysis into genetics and genomics is widely recognized, but only a small number of statisticians have produced relevant work toward this study direction. For unrelated population data, functional regression (FR) models have been developed to test for association between a quantitative/dichotomous/survival trait and genetic variants in a gene region. In major gene association analysis, these models have higher power than sequence kernel association tests. In this paper, we extend this approach to analyze censored traits for family data or related samples using FR based mixed effect Cox models (FamCoxME). The FamCoxME model effect of major gene as fixed mean via functional data analysis techniques, the local gene or polygene variations or both as random, and the correlation of pedigree members by kinship coefficients or genetic relationship matrix or both. The association between the censored trait and the major gene is tested by likelihood ratio tests (FamCoxME FR LRT). Simulation results indicate that the LRT control the type I error rates accurately/conservatively and have good power levels when both local gene or polygene variations are modeled. The proposed methods were applied to analyze a breast cancer data set from the Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA). The FamCoxME provides a new tool for gene-based analysis of family-based studies or related samples.

From matrimonial practices to genetic diversity in Southeast Asian populations: the signature of the matrilineal puzzle

In matrilineal populations, the descent group affiliation is transmitted by women whereas the socio-political power frequently remains in the hands of men. This situation, named the 'matrilineal puzzle', is expected to promote local endogamy as a coping mechanism allowing men to maintain their decision-making power over their natal descent group. In this paper, we revisit this 'matrilineal puzzle' from a population genetics' point of view. Indeed, such tendency for local endogamy in matrilineal populations is expected to increase their genetic inbreeding and generate isolation-by-distance patterns between villages. To test this hypothesis, we collected ethno-demographic data for 3261 couples and high-density genetic data for 675 individuals from 11 Southeast Asian populations with a wide range of social organizations: matrilineal and matrilocal populations (M), patrilineal and patrilocal populations (P) or cognatic populations with predominant matrilocal residence (C). We observed that M and C populations have higher levels of village endogamy than P populations, and that such higher village endogamy leads to higher genetic inbreeding. M populations also exhibit isolation-by-distance patterns between villages. We interpret such genetic patterns as the signature of the 'matrilineal puzzle'. Notably, our results suggest that any form of matrilocal marriage (whatever the descent rule is) increases village endogamy. These findings suggest that male dominance, when combined with matrilocality, constrains inter-village migrations, and constitutes an underexplored cultural process shaping genetic patterns in human populations. This article is part of the theme issue 'The evolution of female-biased kinship in humans and other mammals'.

Estimating Relatedness Between Malaria Parasites

Understanding the relatedness of individuals within or between populations is a common goal in biology. Increasingly, relatedness features in genetic epidemiology studies of pathogens. These studies are relatively new compared to those in humans and other organisms, but are important for designing interventions and understanding pathogen transmission. Only recently have researchers begun to routinely apply relatedness to apicomplexan eukaryotic malaria parasites, and to date have used a range of different approaches on an ad hoc basis. Therefore, it remains unclear how to compare different studies and which measures to use. Here, we systematically compare measures based on identity-by-state (IBS) and identity-by-descent (IBD) using a globally diverse data set of malaria parasites, Plasmodium falciparum and P. vivax, and provide marker requirements for estimates based on IBD. We formally show that the informativeness of polyallelic markers for relatedness inference is maximized when alleles are equifrequent. Estimates based on IBS are sensitive to allele frequencies, which vary across populations and by experimental design. For portability across studies, we thus recommend estimates based on IBD. To generate estimates with errors below an arbitrary threshold of 0.1, we recommend ∼100 polyallelic or 200 biallelic markers. Marker requirements are immediately applicable to haploid malaria parasites and other haploid eukaryotes. C.I.s facilitate comparison when different marker sets are used. This is the first attempt to provide rigorous analysis of the reliability of, and requirements for, relatedness inference in malaria genetic epidemiology. We hope it will provide a basis for statistically informed prospective study design and surveillance strategies.

Genome-Wide Scan for Runs of Homozygosity Identifies Candidate Genes in Three Pig Breeds

Runs of homozygosity (ROH) are contiguous homozygous genotype segments in the genome that are present in an individual since the identical haplotypes are inherited from each parent. The aim of this study was to investigate the frequency and distribution of ROH in the genomes of Landrace, Songliao black and Yorkshire pigs. We calculated two types of genome inbreeding coefficients and their correlation, including the inbreeding coefficient based on ROH (FROH) and the inbreeding coefficient based on the difference between the observed and expected number of homozygous genotypes (FHOM). Furthermore, we identified candidate genes in the genomic region most associated with ROH. We identified 21,312 ROH in total. The average number of ROH per individual was 32.99 ± 0.38 and the average length of ROH was 6.40 ± 0.070 Mb in the three breeds. The FROH results showed that Yorkshire pigs exhibited the highest level of inbreeding (0.092 ± 0.0015) and that Landrace pigs exhibited the lowest level of inbreeding (0.073 ± 0.0047). The average correlation between FROH and FHOM was high (0.94) within three breeds. The length of ROH provides insight into the inbreeding history of these three pig breeds. In this study, Songliao black pigs presented a higher frequency and average length of long ROH (>40 Mb) compared with those of Landrace and Yorkshire pigs, which indicated greater inbreeding in recent times. Genes related to reproductive traits (GATM, SPATA46, HSD17B7, VANGL2, DAXX, CPEB1), meat quality traits (NR1I3, APOA2, USF1) and energy conversion (NDUFS2) were identified within genomic regions with a high frequency of ROH. These genes could be used as target genes for further marker-assisted selection and genome selection.