Estimation of inbreeding and identification of regions under heavy selection based on runs of homozygosity in a Large White pig population

Genome-wide detection of runs of homozygosity and heterozygosity in Tunchang pigs

Tunchang pigs, mainly distributed throughout Hainan Province of China, are well-known for their superior meat quality, crude feed tolerance, and adaptability to high temperatures and humidity. Runs of homozygosity (ROH) can provide valuable information about the inbreeding coefficient in individuals and selection signals that may reveal candidate genes associated with key functional traits. Runs of heterozygosity (ROHet) are commonly associated with balance selection, which can help us understand the adaptive evolutionary history of domestic animals. In this study, we investigated ROHs and ROHets in 88 Tunchang pigs. We also compared the estimates of inbreeding coefficients in individuals calculated based on four methods. In summary, we detected a total of 16 ROH islands in our study, and 100 genes were found within ROH regions. These genes were correlated with economically important traits such as reproduction (e.g., SERPIND1, HIRA), meat quality (e.g., PI4KA, TBX1), immunity (e.g., ESS2, RANBP1), adaption to heat stress (TXNRD2 and DGCR8), and crude food tolerance (TRPM6). Moreover, we discovered 18 ROHet islands harbouring genes associated with reproduction (e.g., ARHGEF12, BMPR2), immune system (e.g., BRD4, DNMT3B). These findings may help us design effective breeding and conservation strategies for this unique breed.

Identification of consensus homozygous regions and their associations with growth and feed efficiency traits in American mink

The recent chromosome-based genome assembly and the newly developed 70K single nucleotide polymorphism (SNP) array for American mink (Neogale vison) facilitate the identification of genetic variants underlying complex traits in this species. The objective of this study was to evaluate the association between consensus runs of homozygosity (ROH) with growth and feed efficiency traits in American mink. A subsample of two mink populations (n = 2,986) were genotyped using the Affymetrix Mink 70K SNP array. The identified ROH segments were included simultaneously, concatenated into consensus regions, and the ROH-based association studies were carried out with linear mixed models considering a genomic relationship matrix for 11 growth and feed efficiency traits implemented in ASReml-R version 4. In total, 298,313 ROH were identified across all individuals, with an average length and coverage of 4.16 Mb and 414.8 Mb, respectively. After merging ROH segments, 196 consensus ROH regions were detected and used for genome-wide ROH-based association analysis. Thirteen consensus ROH regions were significantly (P < 0.01) associated with growth and feed efficiency traits. Several candidate genes within the significant regions are known for their involvement in growth and body size development, including MEF2A, ADAMTS17, POU3F2, and TYRO3. In addition, we found ten consensus ROH regions, defined as ROH islands, with frequencies over 80% of the population. These islands harbored 12 annotated genes, some of which were related to immune system processes such as DTX3L, PARP9, PARP14, CD86, and HCLS1. This is the first study to explore the associations between homozygous regions with growth and feed efficiency traits in American mink. Our findings shed the light on the effects of homozygosity in the mink genome on growth and feed efficiency traits, that can be utilized in developing a sustainable breeding program for mink.

Runs of homozygosity and selection signature analyses reveal putative genomic regions for artificial selection in layer breeding

BACKGROUND

The breeding of layers emphasizes the continual selection of egg-related traits, such as egg production, egg quality and eggshell, which enhance their productivity and meet the demand of market. As the breeding process continued, the genomic homozygosity of layers gradually increased, resulting in the emergence of runs of homozygosity (ROH). Therefore, ROH analysis can be used in conjunction with other methods to detect selection signatures and identify candidate genes associated with various important traits in layer breeding.

RESULTS

In this study, we generated whole-genome sequencing data from 686 hens in a Rhode Island Red population that had undergone fifteen consecutive generations of intensive artificial selection. We performed a genome-wide ROH analysis and utilized multiple methods to detect signatures of selection. A total of 141,720 ROH segments were discovered in whole population, and most of them (97.35%) were less than 3 Mb in length. Twenty-three ROH islands were identified, and they overlapped with some regions bearing selection signatures, which were detected by the De-correlated composite of multiple signals methods (DCMS). Sixty genes were discovered and functional annotation analysis revealed the possible roles of them in growth, development, immunity and signaling in layers. Additionally, two-tailed analyses including DCMS and ROH for 44 phenotypes of layers were conducted to find out the genomic differences between subgroups of top and bottom 10% phenotype of individuals. Combining the results of GWAS, we observed that regions significantly associated with traits also exhibited selection signatures between the high and low subgroups. We identified a region significantly associated with egg weight near the 25 Mb region of GGA 1, which exhibited selection signatures and has higher genomic homozygosity in the low egg weight subpopulation. This suggests that the region may be play a role in the decline in egg weight.

CONCLUSIONS

In summary, through the combined analysis of ROH, selection signatures, and GWAS, we identified several genomic regions that associated with the production traits of layers, providing reference for the study of layer genome.

Analysis of 206 whole-genome resequencing reveals selection signatures associated with breed-specific traits in Hu sheep

As an invaluable Chinese sheep germplasm resource, Hu sheep are renowned for their high fertility and beautiful wavy lambskins. Their distinctive characteristics have evolved over time through a combination of artificial and natural selection. Identifying selection signatures in Hu sheep can provide a straightforward insight into the mechanism of selection and further uncover the candidate genes associated with breed-specific traits subject to selection. Here, we conducted whole-genome resequencing on 206 Hu sheep individuals, each with an approximate 6-fold depth of coverage. And then we employed three complementary approaches, including composite likelihood ratio, integrated haplotype homozygosity score and the detection of runs of homozygosity, to detect selection signatures. In total, 10 candidate genomic regions displaying selection signatures were simultaneously identified by multiple methods, spanning 88.54 Mb. After annotating, these genomic regions harbored collectively 92 unique genes. Interestingly, 32 candidate genes associated with reproduction were distributed in nine genomic regions detected. Out of them, two stood out as star candidates: BMPR1B and GNRH2, both of which have documented associations with fertility, and a HOXA gene cluster (HOXA1-5, HOXA9, HOXA10, HOXA11 and HOXA13) had also been linked to fertility. Additionally, we identified other genes that are related to hair follicle development (LAMTOR3, EEF1A2), ear size (HOXA1, KCNQ2), fat tail formation (HOXA10, HOXA11), growth and development (FAF1, CCNDBP1, GJB2, GJA3), fat deposition (ACOXL, JAZF1, HOXA3, HOXA4, HOXA5, EBF4), immune (UBR1, FASTKD5) and feed intake (DAPP1, RNF17, NPBWR2). Our results offer novel insights into the genetic mechanisms underlying the selection of breed-specific traits in Hu sheep and provide a reference for sheep genetic improvement programs.

Integrating Bioinformatics and Machine Learning for Genomic Prediction in Chickens

Genomic prediction plays an increasingly important role in modern animal breeding, with predictive accuracy being a crucial aspect. The classical linear mixed model is gradually unable to accommodate the growing number of target traits and the increasingly intricate genetic regulatory patterns. Hence, novel approaches are necessary for future genomic prediction. In this study, we used an illumina 50K SNP chip to genotype 4190 egg-type female Rhode Island Red chickens. Machine learning (ML) and classical bioinformatics methods were integrated to fit genotypes with 10 economic traits in chickens. We evaluated the effectiveness of ML methods using Pearson correlation coefficients and the RMSE between predicted and actual phenotypic values and compared them with rrBLUP and BayesA. Our results indicated that ML algorithms exhibit significantly superior performance to rrBLUP and BayesA in predicting body weight and eggshell strength traits. Conversely, rrBLUP and BayesA demonstrated 2-58% higher predictive accuracy in predicting egg numbers. Additionally, the incorporation of suggestively significant SNPs obtained through the GWAS into the ML models resulted in an increase in the predictive accuracy of 0.1-27% across nearly all traits. These findings suggest the potential of combining classical bioinformatics methods with ML techniques to improve genomic prediction in the future.

Genomic Inbreeding and Runs of Homozygosity Analysis of Cashmere Goat

Cashmere goats are valuable genetic resources which are famous worldwide for their high-quality fiber. Runs of homozygosity (ROHs) have been identified as an efficient tool to assess inbreeding level and identify related genes under selection. However, there is limited research on ROHs in cashmere goats. Therefore, we investigated the ROH pattern, assessed genomic inbreeding levels and examined the candidate genes associated with the cashmere trait using whole-genome resequencing data from 123 goats. Herein, the Inner Mongolia cashmere goat presented the lowest inbreeding coefficient of 0.0263. In total, we identified 57,224 ROHs. Seventy-four ROH islands containing 50 genes were detected. Certain identified genes were related to meat, fiber and milk production (FGF1, PTPRM, RERE, GRID2, RARA); fertility (BIRC6, ECE2, CDH23, PAK1); disease or cold resistance and adaptability (PDCD1LG2, SVIL, PRDM16, RFX4, SH3BP2); and body size and growth (TMEM63C, SYN3, SDC1, STRBP, SMG6). 135 consensus ROHs were identified, and we found candidate genes (FGF5, DVL3, NRAS, KIT) were associated with fiber length or color. These findings enhance our comprehension of inbreeding levels in cashmere goats and the genetic foundations of traits influenced by selective breeding. This research contributes significantly to the future breeding, reservation and use of cashmere goats and other goat breeds.

Genomic structure analysis and construction of DNA fingerprint for four sheep populations

The Yongdeng Qishan sheep (QS) is a sheep population found locally in China. To gain in-depth knowledge of its population characteristics, three control groups were chosen, comprising the Lanzhou fat-tailed sheep (LFT), TAN sheep (TAN), and Minxian black fur sheep (MBF), inhabiting the nearby environments. This study genotyped a total of 120 individuals from four sheep populations: QS, LFT, TAN, and MBF. Using Specific-Locus Amplified Fragment Sequencing, we conducted genetic diversity, population structure, and selective sweep analysis, and constructed the fingerprint of each population. In total, there were 782 535 single nucleotide polymorphism (SNP) variations identified, with most being situated within regions that are intergenic or intronic. The genetic diversity analysis revealed that the QS population exhibited lower genetic diversity compared to the other three populations. Consistent results were obtained from the principal component, phylogenetic tree, and population structure analysis, indicating significant genetic differences between QS and the other three populations. However, a certain degree of differentiation was observed within the QS population. The linkage disequilibrium (LD) patterns among the four populations showed clear distinctions, with the QS group demonstrating the most rapid LD decline. Kinship analysis supported the findings of population structure, dividing the 90 QS individuals into two subgroups consisting of 23 and 67 individuals. Selective sweep analysis identified a range of genes associated with reproduction, immunity, and adaptation to high-altitude hypoxia. These genes hold potential as candidate genes for marker-assisted selection breeding. Additionally, a total of 86 523 runs of homozygosity (ROHs) were detected, showing non-uniform distribution across chromosomes, with chromosome 1 having the highest coverage percentage and chromosome 26 the lowest. In the high-frequency ROH islands, 79 candidate genes were associated with biological processes such as reproduction and fat digestion and absorption. Furthermore, a DNA fingerprint was constructed for the four populations using 349 highly polymorphic SNPs. In summary, our research delves into the genetic diversity and population structure of QS population. The construction of DNA fingerprint profiles for each population can provide valuable references for the identification of sheep breeds both domestically and internationally.

Runs of Homozygosity Detection and Selection Signature Analysis for Local Goat Breeds in Yunnan, China

Runs of Homozygosity (ROH) are continuous homozygous DNA segments in diploid genomes, which have been used to estimate the genetic diversity, inbreeding levels, and genes associated with specific traits in livestock. In this study, we analyzed the resequencing data from 10 local goat breeds in Yunnan province of China and five additional goat populations obtained from a public database. The ROH analysis revealed 21,029 ROH segments across the 15 populations, with an average length of 1.27 Mb, a pattern of ROH, and the assessment of the inbreeding coefficient indicating genetic diversity and varying levels of inbreeding. iHS (integrated haplotype score) was used to analyze high-frequency Single-Nucleotide Polymorphisms (SNPs) in ROH regions, specific genes related to economic traits such as coat color and weight variation. These candidate genes include OCA2 (OCA2 melanosomal transmembrane protein) and MLPH (melanophilin) associated with coat color, EPHA6 (EPH receptor A6) involved in litter size, CDKAL1 (CDK5 regulatory subunit associated protein 1 like 1) and POMC (proopiomelanocortin) linked to weight variation and some putative genes associated with high-altitude adaptability and immune. This study uncovers genetic diversity and inbreeding levels within local goat breeds in Yunnan province, China. The identification of specific genes associated with economic traits and adaptability provides actionable insights for utilization and conservation efforts.

Genome-Wide Detection for Runs of Homozygosity in Baoshan Pigs Using Whole Genome Resequencing

Baoshan pigs (BS) are a local breed in Yunnan Province that may face inbreeding owing to its limited population size. To accurately evaluate the inbreeding level of the BS pig population, we used whole-genome resequencing to identify runs of homozygosity (ROH) regions in BS pigs, calculated the inbreeding coefficient based on pedigree and ROH, and screened candidate genes with important economic traits from ROH islands. A total of 22,633,391 SNPS were obtained from the whole genome of BS pigs, and 201 ROHs were detected from 532,450 SNPS after quality control. The number of medium-length ROH (1-5 Mb) was the highest (98.43%), the number of long ROH (>5 Mb) was the lowest (1.57%), and the inbreeding of BS pigs mainly occurred in distant generations. The inbreeding coefficient FROH, calculated based on ROH, was 0.018 ± 0.016, and the FPED, calculated based on the pedigree, was 0.027 ± 0.028, which were positively correlated. Forty ROH islands were identified, containing 507 genes and 891 QTLs. Several genes were associated with growth and development (IGFALS, PTN, DLX5, DKK1, WNT2), meat quality traits (MC3R, ACSM3, ECI1, CD36, ROCK1, CACNA2D1), and reproductive traits (NPW, TSHR, BMP7). This study provides a reference for the protection and utilization of BS pigs.

Detection of Runs of Homozygosity and Identification of Candidate Genes in the Whole Genome of Tunchang Pigs

Tunchang pigs are an indigenous pig population in China known for their high tolerance to roughage, delicious meat, and fecundity. However, the number of Tunchang pigs has been declining due to the influence of commercial breeds and African swine fever, which could potentially lead to inbreeding. To assess the inbreeding level and the genetic basis of important traits in Tunchang pigs, our research investigated the patterns in "runs of homozygosity" (ROHs) using whole genome resequencing data from 32 Tunchang pigs. The study aimed to determine the length, number, coverage, and distribution model of ROHs in Tunchang pigs, as well as genomic regions with high ROH frequencies. The results of the study revealed that a total of 20,499,374 single-nucleotide polymorphisms (SNPs) and 1953 ROH fragments were recognized in 32 individuals. The ROH fragments in Tunchang pigs were predominantly short, ranging from 0.5 to 1 megabases (Mb) in length. Furthermore, the coverage of ROHs varied across chromosomes, with chromosome 3 having the highest coverage and chromosome 11 having the lowest coverage. The genetic diversity of Tunchang pigs was found to be relatively high based on the values of HE (expected heterozygosity), HO (observed heterozygosity), pi (nucleotide diversity), Ne (effective population size), and MAF (minor allele frequency). The average inbreeding coefficients of Tunchang pigs, as determined by three different methods (FHOM, FGRM, and FROH), were 0.019, 0.0138, and 0.0304, respectively. These values indicate that the level of inbreeding in Tunchang pigs is currently low. Additionally, the study identified a total of 13 ROH islands on all chromosomes, which in total contained 38,913 SNPs and 120 genes. These ROH islands included genes associated with economically important traits, including meat quality (GYS1, PHLPP1, SLC27A5, and CRTC1), growth and development (ANKS1A, TAF11, SPDEF, LHB, and PACSIN1), and environmental adaptation (SLC26A7). The findings of this research offer valuable perspectives on the present status of Tunchang pig resources and offer a reference for breeding conservation plans and the efficient utilization of Tunchang pigs in the future. By understanding the inbreeding level and genetic basis of important traits in Tunchang pigs, conservation efforts can be targeted towards maintaining genetic diversity and promoting the sustainable development of this indigenous pig population.

Impacts of Population Size and Domestication Process on Genetic Diversity and Genetic Load in Genus Ovis

In theoretical biology, a prevailing hypothesis posits a profound interconnection between effective population size (Ne), genetic diversity, inbreeding, and genetic load. The domestication and improvement processes are believed to be pivotal in diminishing genetic diversity while elevating levels of inbreeding and increasing genetic load. In this study, we performed a whole genome analysis to quantity genetic diversity, inbreeding, and genetic load across seven wild Ovis species and five domesticated sheep breeds. Our research demonstrates that the genetic load and diversity of species in the genus Ovis have no discernible impact on recent Ne, and three species within the subgenus Pachyceros tend to carry a higher genetic load and lower genetic diversity patterns. The results coincide with these species' dramatic decline in population sizes within the subgenus Pachyceros ~80-250 thousand years ago. European mouflon presented with the lowest Ne, lower genetic diversity, and higher individual inbreeding coefficient but a lower genetic load (missense and LoF). This suggests that the small Ne of European mouflon could reduce harmful mutations compared to other species within the genus Ovis. We showed lower genetic diversity in domesticated sheep than in Asiatic mouflon, but counterintuitive patterns of genetic load, i.e., lower weak genetic load (missense mutation) and no significant difference in strong genetic load (LoF mutation) between domestic sheep and Asiatic mouflon. These findings reveal that the "cost of domestication" during domestication and improvement processes reduced genetic diversity and purified weak genetic load more efficiently than wild species.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement

BACKGROUND

Genomic selection involves choosing as parents those elite individuals with the higher genomic estimated breeding values (GEBV) to accelerate the speed of genetic improvement in domestic animals. But after multi-generation selection, the rate of inbreeding and the occurrence of homozygous harmful alleles might increase, which would reduce performance and genetic diversity. To mitigate the above problems, we can utilize genomic mating (GM) based upon optimal mate allocation to construct the best genotypic combinations in the next generation. In this study, we used stochastic simulation to investigate the impact of various factors on the efficiencies of GM to optimize pairing combinations after genomic selection of candidates in a pig population. These factors included: the algorithm used to derive inbreeding coefficients; the trait heritability (0.1, 0.3 or 0.5); the kind of GM scheme (focused average GEBV or inbreeding); the approach for computing the genomic relationship matrix (by SNP or runs of homozygosity (ROH)). The outcomes were compared to three traditional mating schemes (random, positive assortative or negative assortative matings). In addition, the performance of the GM approach was tested on real datasets obtained from a Large White pig breeding population.

RESULTS

Genomic mating outperforms other approaches in limiting the inbreeding accumulation for the same expected genetic gain. The use of ROH-based genealogical relatedness in GM achieved faster genetic gains than using relatedness based on individual SNPs. The G_ROH-based GM schemes with the maximum genetic gain resulted in 0.9%-2.6% higher rates of genetic gain ΔG, and 13%-83.3% lower ΔF than positive assortative mating regardless of heritability. The rates of inbreeding were always the fastest with positive assortative mating. Results from a purebred Large White pig population, confirmed that GM with ROH-based GRM was more efficient than traditional mating schemes.

CONCLUSION

Compared with traditional mating schemes, genomic mating can not only achieve sustainable genetic progress but also effectively control the rates of inbreeding accumulation in the population. Our findings demonstrated that breeders should consider using genomic mating for genetic improvement of pigs.

Runs of homozygosity and signatures of selection for number of oocytes and embryos in the Gir Indicine cattle

Runs of homozygosity (ROH) and signatures of selection are the results of selection processes in livestock species that have been shown to affect several traits in cattle. The aim of the current work was to verify the profile of ROH and inbreeding depression in the number of total (TO) and viable oocytes (VO) and the number of embryos (EMBR) in Gir Indicine cattle. In addition, we aim to identify signatures of selection, genes, and enriched regions between Gir subpopulations sorted by breeding value for these traits. The genotype file contained 2093 animals and 420,718 SNP markers. Breeding values used to sort Gir animals were previously obtained. ROH and signature of selection analyses were performed using PLINK software, followed by ROH-based (F_ROH) and pedigree-based inbreeding (F_ped) and a search for genes and their functions. An average of 50 ± 8.59 ROHs were found per animal. ROHs were separated into classes according to size, ranging from 1 to 2 Mb (ROH_1-2Mb: 58.17%), representing ancient inbreeding, ROH_2-4Mb (22.74%), ROH_4-8Mb (11.34%), ROH_8-16Mb (5.51%), and ROH_>16Mb (2.24%). Combining our results, we conclude that the increase in general F_ROH and F_ped significantly decreases TO and VO; however, in different chromosomes traits can increase or decrease with F_ROH. In the analysis for signatures of selection, we identified 15 genes from 47 significant genomic regions, indicating differences in populations with high and low breeding value for the three traits.

The coefficients of inbreeding revealed by ROH study among inbred individuals belonging to each type of the first cousin marriage: A preliminary report from North India

BACKGROUND

Genome-wide runs of homozygosity (ROH) are appropriate to estimate genomic inbreeding, determine population history, unravel the genetic architecture of complex traits and disorders.

OBJECTIVE

The study sought to investigate and compare the actual proportion of homozygosity or autozygosity in the genomes of progeny of four subtypes of first cousin mating in humans, using both pedigree and genomic measures for autosomes and sex chromosomes.

METHODS

For this purpose, Illumina Global Screening Array-24 v1.0 BeadChip followed by cyto-ROH analysis through Illumina Genome Studio was used to characterise the homozygosity in five participants from North Indian state (Uttar Pradesh). PLINK v.1.9 software was used to estimate the genomic inbreeding coefficients viz. ROH-based inbreeding estimate (F_ROH) and homozygous loci-based inbreeding estimate (F_HOM).

RESULTS

A total of 133 ROH segments were detected with maximum number and genomic coverage in Matrilateral Parallel (MP) type and minimum in outbred individual. ROH pattern revealed that MP type has a higher degree of homozygosity than other subtypes. The comparison of F_ROH, F_HOM, and pedigree-based inbreeding estimate (F_PED) showed some difference in theoretical and realised proportion of homozygosity for sex-chromosomal loci but not for autosome for each type of consanguinity.

CONCLUSIONS

This is the very first study to compare and estimate the pattern of homozygosity among the kindreds of first cousin unions. However, a greater number of individuals from each type of marriage is required for statistical inference of no difference between theoretical and realized homozygosity among different degrees of inbreeding prevalent in humans worldwide.

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.

Integrating genome-wide association studies and population genomics analysis reveals the genetic architecture of growth and backfat traits in pigs

Growth and fat deposition are complex traits, which can affect economical income in the pig industry. Due to the intensive artificial selection, a significant genetic improvement has been observed for growth and fat deposition in pigs. Here, we first investigated genomic-wide association studies (GWAS) and population genomics (e.g., selection signature) to explore the genetic basis of such complex traits in two Large White pig lines (n = 3,727) with the GeneSeek GGP Porcine HD array (n = 50,915 SNPs). Ten genetic variants were identified to be associated with growth and fatness traits in two Large White pig lines from different genetic backgrounds by performing both within-population GWAS and cross-population GWAS analyses. These ten significant loci represented eight candidate genes, i.e., NRG4, BATF3, IRS2, ANO1, ANO9, RNF152, KCNQ5, and EYA2. One of them, ANO1 gene was simultaneously identified for both two lines in BF100 trait. Compared to single-population GWAS, cross-population GWAS was less effective for identifying SNPs with population-specific effect, but more powerful for detecting SNPs with population-shared effects. We further detected genomic regions specifically selected in each of two populations, but did not observe a significant enrichment for the heritability of growth and backfat traits in such regions. In summary, the candidate genes will provide an insight into the understanding of the genetic architecture of growth-related traits and backfat thickness, and may have a potential use in the genomic breeding programs in pigs.

Estimation of genetic variability and identification of regions under selection based on runs of homozygosity in Beijing-You Chickens

The genetic composition of populations is the result of a long-term process of selection and adaptation to specific environments and ecosystems. Runs of homozygosity (ROHs) are homozygous segments of the genome where the 2 haplotypes inherited from the parents are identical. The detection of ROH can be used to describe the genetic variability and quantify the level of inbreeding in an individual. Here, we investigated the occurrence and distribution of ROHs in 40 Beijing-You Chickens from the random breeding population (BJY_C) and 40 Beijing-You Chickens from the intramuscular fat (IMF) selection population (BJY_S). Principal component analysis (PCA) and maximum likelihood (ML) analyses showed that BJY_C was completely separated from the BJY_S. The nucleotide diversity of BJY_C was higher than that of BJY_S, and the decay rate of LD of BJY_C was faster. The ROHs were identified for a total of 7,101 in BJY_C and 9,273 in BJY_S, respectively. The ROH-based inbreeding estimate (F_ROH) of BJY_C was 0.079, which was significantly lower than that of BJY_S (F_ROH = 0.114). The results were the same as the estimates of the inbreeding coefficients calculated based on homozygosity (F_HOM), the correlation between uniting gametes (F_UNI), and the genomic relationship matrix (F_GRM). Additionally, the distribution and number of ROH islands in chromosomes of BJY_C and BJY_S were significantly different. The ROH islands of BJY_S that included genes associated with lipid metabolism and fat deposition, such as CIDEA and S1PR1, were absent in BJY_C. However, GPR161 was detected in both populations, which is a candidate gene for the formation of the unique five-finger trait in Beijing-You chickens. Our findings contributed to the understanding of the genetic diversity of random or artificially selected populations, and allowed the accurate monitoring of population inbreeding using genomic information, as well as the detection of genomic regions that affect traits under selection.

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.

Genome-Wide Association Studies, Runs of Homozygosity Analysis, and Copy Number Variation Detection to Identify Reproduction-Related Genes in Bama Xiang Pigs

Litter size and teat number are economically important traits in the porcine industry. However, the genetic mechanisms influencing these traits remain unknown. In this study, we analyzed the genetic basis of litter size and teat number in Bama Xiang pigs and evaluated the genomic inbreeding coefficients of this breed. We conducted a genome-wide association study to identify runs of homozygosity (ROH), and copy number variation (CNV) using the novel Illumina PorcineSNP50 BeadChip array in Bama Xiang pigs and annotated the related genes in significant single nucleotide polymorphisms and common copy number variation region (CCNVR). We calculated the ROH-based genomic inbreeding coefficients (FROH) and the Spearman coefficient between FROH and reproduction traits. We completed a mixed linear model association analysis to identify the effect of high-frequency copy number variation (HCNVR; over 5%) on Bama Xiang pig reproductive traits using TASSEL software. Across eight chromosomes, we identified 29 significant single nucleotide polymorphisms, and 12 genes were considered important candidates for litter-size traits based on their vital roles in sperm structure, spermatogenesis, sperm function, ovarian or follicular function, and male/female infertility. We identified 9,322 ROHs; the litter-size traits had a significant negative correlation to FROH. A total of 3,317 CNVs, 24 CCNVR, and 50 HCNVR were identified using cnvPartition and PennCNV. Eleven genes related to reproduction were identified in CCNVRs, including seven genes related to the testis and sperm function in CCNVR1 (chr1 from 311585283 to 315307620). Two candidate genes (NEURL1 and SH3PXD2A) related to reproduction traits were identified in HCNVR34. The result suggests that these genes may improve the litter size of Bama Xiang by marker-assisted selection. However, attention should be paid to deter inbreeding in Bama Xiang pigs to conserve their genetic diversity.

Genome-wide detection of genetic structure and runs of homozygosity analysis in Anhui indigenous and Western commercial pig breeds using PorcineSNP80k data

Background

Runs of homozygosity (ROH) are continuous homozygous regions typically located in the DNA sequence of diploid organisms. Identifications of ROH that lead to reduced performance can provide valuable insight into the genetic architecture of complex traits. Here, we systematically investigated the population genetic structure of five Anhui indigenous pig breeds (AHIPs), and compared them to those of five Western commercial pig breeds (WECPs). Furthermore, we examined the occurrence and distribution of ROHs in the five AHIPs and estimated the inbreeding coefficients based on the ROHs (F_ROH) and homozygosity (F_HOM). Finally, we identified genomic regions with high frequencies of ROHs and annotated candidate genes contained therein.

Results

The WECPs and AHIPs were clearly differentiated into two separate clades consistent with their geographical origins, as revealed by the population structure and principal component analysis. We identified 13,530 ROHs across all individuals, of which 4,555 and 8,975 ROHs were unique to AHIPs and WECPs, respectively. Most ROHs identified in our study were short (< 10 Mb) or medium (10–20 Mb) in length. WECPs had significantly higher numbers of short ROHs, and AHIPs generally had longer ROHs. F_ROH values were significantly lower in AHIPs than in WECPs, indicating that breed improvement and conservation programmes were successful in AHIPs. On average, F_ROH and F_HOM values were highly correlated (0.952–0.991) in AHIPs and WECPs. A total of 27 regions had a high frequency of ROHs and contained 17 key candidate genes associated with economically important traits in pigs. Among these, nine candidate genes (CCNT2, EGR2, MYL3, CDH13, PROX1, FLVCR1, SETD2, FGF18, and FGF20) found in WECPs were related to muscular and skeletal development, whereas eight candidate genes (CSN1S1, SULT1E1, TJP1, ZNF366, LIPC, MCEE, STAP1, and DUSP) found in AHIPs were associated with health, reproduction, and fatness traits.

Conclusion

Our findings provide a useful reference for the selection and assortative mating of pig breeds, laying the groundwork for future research on the population genetic structures of AHIPs, ultimately helping protect these local varieties.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08583-9.

Genome-Wide Estimates of Runs of Homozygosity, Heterozygosity, and Genetic Load in Two Chinese Indigenous Goat Breeds

Runs of homozygosity (ROH) and heterozygosity (ROHet) are windows into population demographic history and adaptive evolution. Numerous studies have shown that deleterious mutations are enriched in the ROH of humans, pigs, cattle, and chickens. However, the relationship of deleterious variants to ROH and the pattern of ROHet in goats have been largely understudied. Here, 240 Guangfeng and Ganxi goats from Jiangxi Province, China, were genotyped using the Illumina GoatSNP50 BeadChip and genome-wide ROH, ROHet, and genetic load analyses were performed in the context of 32 global goat breeds. The classes with the highest percentage of ROH and ROHet were 0.5–2 Mb and 0.5–1 Mb, respectively. The results of inbreeding coefficients (based on SNP and ROH) and ROHet measurements showed that Guangfeng goats had higher genetic variability than most Chinese goats, while Ganxi goats had a high degree of inbreeding, even exceeding that of commercial goat breeds. Next, the predicted damaging homozygotes were more enriched in long ROHs, especially in Guangfeng goats. Therefore, we suggest that information on damaging alleles should also be incorporated into the design of breeding and conservation programs. A list of genes related to fecundity, growth, and environmental adaptation were identified in the ROH hotspots of two Jiangxi goats. A sense-related ROH hotspot (chromosome 12: 50.55–50.81 Mb) was shared across global goat breeds and may have undergone selection prior to goat domestication. Furthermore, an identical ROHet hotspot (chromosome 1: 132.21–132.54 Mb) containing two genes associated with embryonic development (STAG1 and PCCB) was detected in domestic goat breeds worldwide. Tajima’s D and BetaScan2 statistics indicated that this region may be caused by long-term balancing selection. These findings not only provide guidance for the design of conservation strategies for Jiangxi goat breeds but also enrich our understanding of the adaptive evolution of goats.

Genetic diversity and population structure of six autochthonous pig breeds from Croatia, Serbia, and Slovenia

BACKGROUND

The importance of local breeds as genetic reservoirs of valuable genetic variation is well established. Pig breeding in Central and South-Eastern Europe has a long tradition that led to the formation of several local pig breeds. In the present study, genetic diversity parameters were analysed in six autochthonous pig breeds from Slovenia, Croatia and Serbia (Banija spotted, Black Slavonian, Turopolje pig, Swallow-bellied Mangalitsa, Moravka and Krskopolje pig). Animals from each of these breeds were genotyped using microsatellites and single nucleotide polymorphisms (SNPs). The results obtained with these two marker systems and those based on pedigree data were compared. In addition, we estimated inbreeding levels based on the distribution of runs of homozygosity (ROH) and identified genomic regions under selection pressure using ROH islands and the integrated haplotype score (iHS).

RESULTS

The lowest heterozygosity values calculated from microsatellite and SNP data were observed in the Turopolje pig. The observed heterozygosity was higher than the expected heterozygosity in the Black Slavonian, Moravka and Turopolje pig. Both types of markers allowed us to distinguish clusters of individuals belonging to each breed. The analysis of admixture between breeds revealed potential gene flow between the Mangalitsa and Moravka, and between the Mangalitsa and Black Slavonian, but no introgression events were detected in the Banija spotted and Turopolje pig. The distribution of ROH across the genome was not uniform. Analysis of the ROH islands identified genomic regions with an extremely high frequency of shared ROH within the Swallow-bellied Mangalitsa, which harboured genes associated with cholesterol biosynthesis, fatty acid metabolism and daily weight gain. The iHS approach to detect signatures of selection revealed candidate regions containing genes with potential roles in reproduction traits and disease resistance.

CONCLUSIONS

Based on the estimation of population parameters obtained from three data sets, we showed the existence of relationships among the six pig breeds analysed here. Analysis of the distribution of ROH allowed us to estimate the level of inbreeding and the extent of homozygous regions in these breeds. The iHS analysis revealed genomic regions potentially associated with phenotypic traits and allowed the detection of genomic regions under selection pressure.

Analysis of the Genetic Diversity and Family Structure of the Licha Black Pig Population on Jiaodong Peninsula, Shandong Province, China

Simple Summary

This study investigated the current conservation status, including the genetic diversity, the family structure, and inbreeding, of the Licha black pig population on Jiaodong Peninsula (Shandong Province, China). The results provide insights into the management and conservation of a local pig breed. Breeders are encouraged to utilize genomic data to improve mating schemes based on the family information obtained in this study, such as keeping an equivalent number of boars and sows in each family and selecting individuals with a kinship coefficient of less than 0.1 for mating.

Abstract

The Licha black pig, a popular indigenous Chinese pig breed, is known for its multi-vertebral trait and higher lean meat rate. Understanding the current conservation status, family structure, and degree of inbreeding of the Licha black pig population will be useful to maintain a sufficient level of genetic diversity in these animal resources. In the present study, the genetic diversity, population structure, and inbreeding coefficient of this conserved population were analyzed using SNP genotyping data from 209 Licha black pigs. Based on the genomic information, this population was divided into eight different families with boars. The effective population size (N_e), polymorphic marker ratio (P_N), expected heterozygosity (H_e), and observed heterozygosity (H_o) of this population were 8.7, 0.827, 0.3576, and 0.3512, respectively. In addition, a total of 5976 runs of homozygosity (ROHs) were identified, and most of the ROHs (54.9%) were greater than 5 Mb. The genomic inbreeding coefficient of each individual was estimated based on ROHs (F_ROH) with an average inbreeding coefficient of 0.11 for the population. Five statistics (N_e, P_N, H_o, H_e, and F_ROH) showed a decrease in the level of genetic diversity and a high degree of inbreeding in this population. Thus, special preservation programs need to be implemented in the future, such as introducing new individuals or improving the mating plan. Altogether, our study provides the first genomic overview of the genetic diversity and population structure of Licha black pigs, which will be useful for the management and long-term preservation of this breed.

Runs of Homozygosity Uncover Potential Functional-Altering Mutation Associated With Body Weight and Length in Two Duroc Pig Lines

Runs of homozygosity (ROH) are widely used to investigate genetic diversity, demographic history, and positive selection signatures of livestock. Commercial breeds provide excellent materials to reveal the landscape of ROH shaped during the intense selection process. Here, we used the GeneSeek Porcine 50K single-nucleotide polymorphism (SNP) Chip data of 3,770 American Duroc (AD) and 2,096 Canadian Duroc (CD) pigs to analyze the genome-wide ROH. First, we showed that AD had a moderate genetic differentiation with CD pigs, and AD had more abundant genetic diversity and significantly lower level of inbreeding than CD pigs. In addition, sows had larger levels of homozygosity than boars in AD pigs. These differences may be caused by differences in the selective intensity. Next, ROH hotspots revealed that many candidate genes are putatively under selection for growth, sperm, and muscle development in two lines. Population-specific ROHs inferred that AD pigs may have a special selection for female reproduction, while CD pigs may have a special selection for immunity. Moreover, in the overlapping ROH hotspots of two Duroc populations, we observed a missense mutation (rs81216249) located in the growth and fat deposition-related supergene (ARSB-DMGDH-BHMT) region. The derived allele of this variant originated from European pigs and was nearly fixed in Duroc pigs. Further selective sweep and association analyses indicated that this supergene was subjected to strong selection and probably contributed to the improvement of body weight and length in Duroc pigs. These findings will enhance our understanding of ROH patterns in different Duroc lines and provide promising trait-related genes and a functional-altering marker that can be used for genetic improvement of pigs.

Analysis of Autozygosity Using Whole-Genome Sequence Data of Full-Sib Families in Pikeperch (Sander lucioperca)

Pikeperch (Sander lucioperca) has emerged as a high value species to the aquaculture industry. However, its farming techniques are at an early stage and its production is often performed without a selective breeding program, potentially leading to high levels of inbreeding. In this study, we identified and characterized autozygosity based on genome-wide runs of homozygosity (ROH) on a sample of parental and offspring individuals, determined effective population size (N_e), and assessed relatedness among parental individuals. A mean of 2,235 ± 526 and 1,841 ± 363 ROH segments per individual, resulting in a mean inbreeding coefficient of 0.33 ± 0.06 and 0.25 ± 0.06 were estimated for the progeny and parents, respectively. N_e was about 12 until four generations ago and at most 106 for 63 generations in the past, with varying genetic relatedness amongst the parents. This study shows the importance of genomic information when family relationships are unknown and the need of selective breeding programs for reproductive management decisions in the aquaculture industry.

Genome-Wide Assessment of Runs of Homozygosity and Estimates of Genomic Inbreeding in a Chinese Composite Pig Breed

The primary purpose of the current study was to assess the genetic diversity, runs of homozygosity (ROH) and ROH islands in a Chinese composite pig and explore hotspot regions for traces of selection. First, we estimated the length, number, and frequency of ROH in 262 Xidu black pigs using the Porcine SNP50 BeadChip and compared the estimates of inbreeding coefficients, which were calculated based on ROHs (F_ROH) and homozygosity (F_HOM). Our result shows that a total of 7,248 ROH exceeding 1Mb were detected in 262 pigs. In addition, Sus scrofa chromosome (SSC) 8 and SSC10, respectively, has the highest and lowest chromosome coverage by ROH. These results suggest that inbreeding estimation based on total ROH may be a useful method, especially for crossbreed or composite populations. We also calculated an inbreeding coefficient of 0.077 from the total ROH. Eight ROH islands were found in this study. These ROH islands harbored genes associated with fat deposition, muscular development, reproduction, ear shape, and adaptation, such as TRAF7, IGFBP7, XPO1, SLC26A8, PPARD, and OR1F1. These findings may help to understand the effects of environmental and artificial selection on the genome structure of composite pigs. Our results provide a basis for subsequent genomic selection (GS), and provides a reference for the hybrid utilization of other pig breeds.

Estimates of genomic inbreeding and identification of candidate regions that differ between Chinese indigenous sheep breeds

BACKGROUND

A run of homozygosity (ROH) is a consecutive tract of homozygous genotypes in an individual that indicates it has inherited the same ancestral haplotype from both parents. Genomic inbreeding can be quantified based on ROH. Genomic regions enriched with ROH may be indicative of selection sweeps and are known as ROH islands. We carried out ROH analyses in five Chinese indigenous sheep breeds; Altay sheep (n = 50 individuals), Large-tailed Han sheep (n = 50), Hulun Buir sheep (n = 150), Short-tailed grassland sheep (n = 150), and Tibetan sheep (n = 50), using genotypes from an Ovine Infinium HD SNP BeadChip.

RESULTS

A total of 18,288 ROH were identified. The average number of ROH per individual across the five sheep breeds ranged from 39 (Hulun Buir sheep) to 78 (Large-tailed Han sheep) and the average length of ROH ranged from 0.929 Mb (Hulun Buir sheep) to 2.544 Mb (Large-tailed Han sheep). The effective population size (Ne) of Altay sheep, Large-tailed Han sheep, Hulun Buir sheep, Short-tailed grassland sheep and Tibetan sheep were estimated to be 81, 78, 253, 238 and 70 five generations ago. The highest ROH-based inbreeding estimate (FROH) was 0.0808 in Large-tailed Han sheep, whereas the lowest FROH was 0.0148 in Hulun Buir sheep. Furthermore, the highest proportion of long ROH fragments (> 5 Mb) was observed in the Large-tailed Han sheep breed which indicated recent inbreeding. In total, 49 ROH islands (the top 0.1% of the SNPs most commonly observed in ROH) were identified in the five sheep breeds. Three ROH islands were common to all the five sheep breeds, and were located on OAR2: 12.2-12.3 Mb, OAR12: 78.4-79.1 Mb and OAR13: 53.0-53.6 Mb. Three breed-specific ROH islands were observed in Altay sheep (OAR15: 3.4-3.8 Mb), Large-tailed Han sheep (ORA17: 53.5-53.8 Mb) and Tibetan sheep (ORA5:19.8-20.2 Mb). Collectively, the ROH islands harbored 78 unique genes, including 19 genes that have been documented as having associations with tail types, adaptation, growth, body size, reproduction or immune response.

CONCLUSION

Different ROH patterns were observed in five Chinese indigenous sheep breeds, which reflected their different population histories. Large-tailed Han sheep had the highest genomic inbreeding coefficients and the highest proportion of long ROH fragments indicating recent inbreeding. Candidate genes in ROH islands could be used to illustrate the genetic characteristics of these five sheep breeds. Our findings contribute to the understanding of genetic diversity and population demography, and help design and implement breeding and conservation strategies for Chinese sheep.

Genome-wide scan for runs of homozygosity identifies candidate genes in Wannan Black pigs

Objective

Runs of homozygosity (ROH) are contiguous lengths of homozygous genotypes that can reveal inbreeding levels, selection pressure, and mating schemes. In this study, ROHs were evaluated in Wannan Black pigs to assess the inbreeding levels and the genome regions with high ROH frequency.

Methods

In a previous study, we obtained 501.52 GB of raw data from resequencing (10×) of the genome and identified 21,316,754 single-nucleotide variants in 20 Wannan Black pig samples. We investigated the number, length, and frequency of ROH using resequencing data to characterize the homozygosity in Wannan Black pigs and identified genomic regions with high ROH frequencies.

Results

In this work, 1,813 ROHs (837 ROHs in 100 to 500 kb, 449 ROHs in 500 to 1,000 kb, 527 ROHs in >1,000 kb) were identified in all samples, and the average genomic inbreeding coefficient (F_ROH) in Wannan Black pigs was 0.5234. Sixty-one regions on chromosomes 2, 3, 7, 8, 13, 15, and 16 harbored ROH islands. In total, 105 genes were identified in 42 ROH islands, among which some genes were related to production traits.

Conclusion

This is the first study to identify ROH across the genome of Wannan Black pigs, the Chinese native breed of the Anhui province. Overall, Wannan Black pigs have high levels of inbreeding due to the influence of ancient and recent inbreeding due to the genome. These findings are a reliable resource for future studies and contribute to save and use the germplasm resources of Wannan Black pigs.

Whole-genome SNP markers reveal conservation status, signatures of selection, and introgression in Chinese Laiwu pigs

Laiwu pigs are a Chinese indigenous breed that is renowned for its exceptionally high intramuscular fat content (average greater than 6%), providing an excellent genetic resource for the genetic improvement of meat quality of modern commercial pigs. To uncover genetic diversity, population structure, signature of selection, and potential exotic introgression in this breed, we sampled 238 Laiwu pigs from a state-supported conservation population and genotyped these individuals using GeneSeek 80K SNP BeadChip. We then conducted in-depth population genetics analyses for the Laiwu pig in a context of 1,116 pigs from 42 Eurasian diverse breeds. First, we show that the current Laiwu population has more abundant genetic diversity than the population of 18 years ago likely due to gene flow from European commercial breeds. Both neighbor-joining (NJ) and principal component analyses indicate the introgression of European haplotypes into Laiwu pigs. The admixture analysis reveals that an average 26.66% of Laiwu genetic components are of European origin. Then, we assigned the tested individuals to different families according to their clustering patterns in the NJ tree and proposed a family-based conservation strategy to reduce the risk of inbreeding depression in Laiwu pigs. Next, we explored three statistics (ROH and iHS and EigenGWAS) to identify a list of candidate genes for fat deposition, reproduction, and growth in Laiwu pigs. Last, we detected a strong signature of introgression from European pigs into Laiwu pigs at the GPC6 locus that regulates the growth of developing long bones. Further association analyses indicate that the introgressed GPC6 haplotype likely contributed to the improvement of growth performance in Laiwu pigs. Altogether, this study not only benefits the better conservation of the Laiwu pig, but also advances our knowledge of the poorly understood effect of human-mediated introgression on phenotypic traits in Chinese indigenous pigs.

Characterization of Autozygosity in Pigs in Three-Way Crossbreeding

Crossbreeding in livestock can be used to increase genetic diversity. The resulting increase in variability is related to the heterozygosity of the crossbred animal. The evolution of diversity during crossbreeding can be assessed using genomic data. The objective of this study was to describe patterns of runs of homozygosity (ROH) in animals resulting from three-way crossbreeding, from parental pure lines, and in their crossbred offspring. The crossbreeding scheme consisted of a first crossbreeding Pietrain boars and Large White sows, after which the offspring of the Pietrain × Large White were crossed with Duroc boars. The offspring of the second crossbreeding are called G0, the offspring of G0 boars and G0 sows are called G1. All the animals were genotyped using the Illumina SNP60 porcine chip. After filtering, analyses were performed with 2,336 animals and 48,579 autosomal single nucleotide polymorphism (SNP). The mean ROH-based inbreeding coefficients were shown to be 0.27 ± 0.05, 0.23 ± 0.04, and 0.26 ± 0.04 for Duroc, Large White, and Pietrain, respectively. ROH were detected in the Pietrain × Large White crossbred but the homozygous segments were fewer and smaller than in their parents. Similar results were obtained in the G0 crossbred. However, in the G1 crossbreds the number and the size of ROH were higher than in G0 parents. Similar ROH hotspots were detected on SSC1, SSC4, SSC7, SSC9, SSC13, SSC14, and SSC15 in both G0 and G1 animals. Long ROH (>16 Mb) were observed in G1 animals, suggesting regions with low recombination rates. The conservation of these homozygous segments in the three crossbred populations means that some haplotypes were shared between parental breeds. Gene annotation in ROH hotspots in G0 animals identified genes related to production traits including carcass composition and reproduction. These findings advance our understanding of how to manage genetic diversity in crossbred populations.

Tracing selection signatures in the pig genome gives evidence for selective pressures on a unique curly hair phenotype in Mangalitza

Selection for desirable traits and breed-specific phenotypes has left distinctive footprints in the genome of pigs. As representative of a breed with strong selective traces aiming for robustness, health and performance, the Mangalitza pig, a native curly-haired pig breed from Hungary, was investigated in this study. Whole genome sequencing and SNP chip genotyping was performed to detect runs of homozygosity (ROH) in Mangalitza and Mangalitza-crossbreeds. We identified breed specific ROH regions harboring genes associated with the development of the curly hair type and further characteristics of this breed. Further analysis of two matings of Mangalitza with straight-coated pig breeds confirmed an autosomal dominant inheritance of curly hair. Subsequent scanning of the genome for variant effects on this trait revealed two variants potentially affecting hair follicle development and differentiation. Validation in a large sample set as well as in imputed SNP data confirmed these variants to be Mangalitza-specific. Herein, we demonstrated how strong artificial selection has shaped the genome in Mangalitza pigs and left traces in the form of selection signatures. This knowledge on genomic variation promoting unique phenotypes like curly hair provides an important resource for futures studies unraveling genetic effects for special characteristics in livestock.