Weighted single step GWAS reveals genomic regions associated with economic traits in Murrah buffaloes.

The objective of the present study was to identify genomic regions influencing economic traits in Murrah buffaloes using weighted single step Genome Wide Association Analysis (WssGWAS). Data on 2000 animals, out of which 120 were genotyped using a double digest Restriction site Associated DNA (ddRAD) sequencing approach. The phenotypic data were collected from NDRI, India, on growth traits, viz., body weight at 6M (month), 12M, 18M and 24M, production traits like 305D (day) milk yield, lactation length (LL) and dry period (DP) and reproduction traits like age at first calving (AFC), calving interval (CI) and first service period (FSP). The biallelic genotypic data consisted of 49353 markers post-quality check. The heritability estimates were moderate to high, low to moderate, low for growth, production, reproduction traits, respectively. Important genomic regions explaining more than 0.5% of the total additive genetic variance explained by 30 adjacent SNPs were selected for further analysis of candidate genes. In this study, 105 genomic regions were associated with growth, 35 genomic regions with production and 42 window regions with reproduction traits. Different candidate genes were identified in these genomic regions, of which important are OSBPL8, NAP1L1 for growth, CNTNAP2 for production and ILDR2, TADA1 and POGK for reproduction traits.

Assessment of runs of homozygosity, heterozygosity-rich regions and genomic inbreeding estimates in a subpopulation of Guzerá (Bos indicus) dual-purpose cattle.

For decades, inbreeding in cattle has been evaluated using pedigree information. Nowadays, inbreeding coefficients can be obtained using genomic information such as runs of homozygosity (ROH). The aims of this study were to quantify ROH and heterozygosity-rich regions (HRR) in a subpopulation of Guzerá dual-purpose cattle, to examine ROH and HRR islands, and to compare inbreeding coefficients obtained by ROH with alternative genomic inbreeding coefficients. A subpopulation of 1733 Guzerá animals genotyped for 50k SNPs was used to obtain the ROH and HRR segments. Inbreeding coefficients by ROH (FROH ), by genomic relationship matrix based on VanRaden's method 1 using reference allele frequency in the population (FGRM ), by genomic relationship matrix based on VanRaden's method 1 using allele frequency fixed in 0.5 (FGRM_0.5 ), and by the proportion of homozygous loci (FHOM ) were calculated. A total of 15,660 ROH were identified, and the chromosome with the highest number of ROH was BTA6. A total of 4843 HRRs were identified, and the chromosome with the highest number of HRRs was BTA23. No ROH and HRR islands were identified according to established criteria, but the regions closest to the definition of an island were examined from 64 to 67 Mb of BTA6, from 36 to 37 Mb of BTA2 and from 0.50 to 1.25 Mb of BTA23. The genes identified in ROH islands have previously been associated with dairy and beef traits, while genes identified on HRR islands have previously been associated with reproductive traits and disease resistance. FROH was equal to 0.095 ± 0.084, and its Spearman correlation with FGRM was low (0.44) and moderate-high with FHOM (0.79) and with FGRM_0.5 (0.80). The inbreeding coefficients determined by ROH were higher than other cattle breeds' and higher than pedigree-based inbreeding in the Guzerá breed obtained in previous studies. It is recommended that future studies investigate the effects of inbreeding determined by ROH on the traits under selection in the subpopulation studied.

A genomic assessment of the marine-speciation paradox within the toothed whale superfamily Delphinoidea.

The impact of post-divergence gene flow in speciation has been documented across a range of taxa in recent years, and may have been especially widespread in highly mobile, wide-ranging marine species, such as cetaceans. Here, we studied individual genomes from nine species across the three families of the toothed whale superfamily Delphinoidea (Delphinidae, Phocoenidae and Monodontidae). To investigate the role of post-divergence gene flow in the speciation process, we used a multifaceted approach, including (i) phylogenomics, (ii) the distribution of shared derived alleles and (iii) demographic inference. We found the divergence of lineages within Delphinoidea did not follow a process of pure bifurcation, but was much more complex. Sliding-window phylogenomics reveal a high prevalence of discordant topologies within the superfamily, with further analyses indicating these discordances arose due to both incomplete lineage sorting and gene flow. D-statistics and f-branch analyses supported gene flow between members of Delphinoidea, with the vast majority of gene flow occurring as ancient interfamilial events. Demographic analyses provided evidence that introgressive gene flow has likely ceased between all species pairs tested, despite reports of contemporary interspecific hybrids. Our study provides the first steps towards resolving the large complexity of speciation within Delphinoidea; we reveal the prevalence of ancient interfamilial gene flow events prior to the diversification of each family, and suggest that contemporary hybridisation events may be disadvantageous, as hybrid individuals do not appear to contribute to the parental species' gene pools.

Genome-Wide Assessment of Runs of Homozygosity by Whole-Genome Sequencing in Diverse Horse Breeds Worldwide.

In the genomes of diploid organisms, runs of homozygosity (ROH), consecutive segments of homozygosity, are extended. ROH can be applied to evaluate the inbreeding situation of individuals without pedigree data and to detect selective signatures via ROH islands. We sequenced and analyzed data derived from the whole-genome sequencing of 97 horses, investigated the distribution of genome-wide ROH patterns, and calculated ROH-based inbreeding coefficients for 16 representative horse varieties from around the world. Our findings indicated that both ancient and recent inbreeding occurrences had varying degrees of impact on various horse breeds. However, recent inbreeding events were uncommon, particularly among indigenous horse breeds. Consequently, the ROH-based genomic inbreeding coefficient could aid in monitoring the level of inbreeding. Using the Thoroughbred population as a case study, we discovered 24 ROH islands containing 72 candidate genes associated with artificial selection traits. We found that the candidate genes in Thoroughbreds were involved in neurotransmission (CHRNA6, PRKN, and GRM1), muscle development (ADAMTS15 and QKI), positive regulation of heart rate and heart contraction (HEY2 and TRDN), regulation of insulin secretion (CACNA1S, KCNMB2, and KCNMB3), and spermatogenesis (JAM3, PACRG, and SPATA6L). Our findings provide insight into horse breed characteristics and future breeding strategies.

Genome-wide comparative identification and analysis of membrane-FADS-like superfamily genes in freshwater economic fishes.

Membrane fatty acid desaturase (FADS)-like superfamily proteins (FADSs) are essential for the synthesis of unsaturated fatty acids (UFAs). Recently, studies on FADS in fishes have mostly focused on marine species, and a comprehensive analysis of the FADS superfamily, including the FADS, stearoyl-CoA desaturase (SCD), and sphingolipid delta 4-desaturase (DEGS) families, in freshwater economic fishes is urgently required. To this end, we conducted a thorough analysis of the number, gene/protein structure, chromosomal location, gene linkage map, phylogeny, and expression of the FADS superfamily. We identified 156 FADSs genes in the genome of 27 representative species. Notably, FADS1 and SCD5 were lost in most freshwater fish and other teleosts. All FADSs proteins contain 4 transmembrane helices and 2-3 amphipathic α-helices. FADSs in the same family are often linked on the same chromosome; moreover, FADS and SCD or DEGS are frequently collocated on the same chromosome. In addition, FADS, SCD, and DEGS family proteins share similar evolutionary patterns. Interestingly, FADS6, as a member of the FADS family, exhibits a similar gene structure and chromosome location to that of SCD family members, which may be the transitional form of FADS and SCD. This study shed light on the type, structure, and phylogenetic relationship of FADSs in freshwater fishes, offering a new perspective into the functional mechanism analysis of FADSs.

Genetic insights into the social organization of Neanderthals.

Genomic analyses of Neanderthals have previously provided insights into their population history and relationship to modern humans1-8, but the social organization of Neanderthal communities remains poorly understood. Here we present genetic data for 13 Neanderthals from two Middle Palaeolithic sites in the Altai Mountains of southern Siberia: 11 from Chagyrskaya Cave9,10 and 2 from Okladnikov Cave11-making this one of the largest genetic studies of a Neanderthal population to date. We used hybridization capture to obtain genome-wide nuclear data, as well as mitochondrial and Y-chromosome sequences. Some Chagyrskaya individuals were closely related, including a father-daughter pair and a pair of second-degree relatives, indicating that at least some of the individuals lived at the same time. Up to one-third of these individuals' genomes had long segments of homozygosity, suggesting that the Chagyrskaya Neanderthals were part of a small community. In addition, the Y-chromosome diversity is an order of magnitude lower than the mitochondrial diversity, a pattern that we found is best explained by female migration between communities. Thus, the genetic data presented here provide a detailed documentation of the social organization of an isolated Neanderthal community at the easternmost extent of their known range.

Whole-genome sequence analysis reveals selection signatures for important economic traits in Xiang pigs.

Xiang pig (XP) is one of the best-known indigenous pig breeds in China, which is characterized by its small body size, strong disease resistance, high adaptability, favorite meat quality, small litter sizes, and early sexual maturity. However, the genomic evidence that links these unique traits of XP is still poorly understood. To identify the genomic signatures of selection in XP, we performed whole-genome resequencing on 25 unrelated individual XPs. We obtained 876.70 Gb of raw data from the genomic libraries. The LD analysis showed that the lowest level of linkage disequilibrium was observed in Xiang pig. Comparative genomic analysis between XPs and other breeds including Tibetan, Meishan, Duroc and Landrace revealed 3062, 1228, 907 and 1519 selected regions, respectively. The genes identified in selected regions of XPs were associated with growth and development processes (IGF1R, PROP1, TBX19, STAC3, RLF, SELENOM, MSTN), immunity and disease resistance (ZCCHC2, SERPINB2, ADGRE5, CYP7B1, STAT6, IL2, CD80, RHBDD3, PIK3IP1), environmental adaptation (NR2E1, SERPINB8, SERPINB10, SLC26A7, MYO1A, SDR9C7, UVSSA, EXPH5, VEGFC, PDE1A), reproduction (CCNB2, TRPM6, EYA3, CYP7B1, LIMK2, RSPO1, ADAM32, SPAG16), meat quality traits (DECR1, EWSR1), and early sexual maturity (TAC3). Through the absolute allele frequency difference (ΔAF) analysis, we explored two population-specific missense mutations occurred in NR6A1 and LTBP2 genes, which well explained that the vertebrae numbers of Xiang pigs were less than that of the European pig breeds. Our results indicated that Xiang pigs were less affected by artificial selection than the European and Meishan pig breeds. The selected candidate genes were mainly involved in growth and development, disease resistance, reproduction, meat quality, and early sexual maturity. This study provided a list of functional candidate genes, as well as a number of genetic variants, which would provide insight into the molecular basis for the unique traits of Xiang pig.

EBP-Colombia and the bioeconomy: Genomics in the service of biodiversity conservation and sustainable development.

The 2016 Peace Agreement has increased access to Colombia's unique ecosystems, which remain understudied and increasingly under threat. The Colombian government has recently announced its National Bioeconomic Strategy (NBS), founded on the sustainable characterization, management, and conservation of the nation's biodiversity as a means to achieve sustainability and peace. Molecular tools will accelerate such endeavors, but capacity remains limited in Colombia. The Earth Biogenome Project's (EBP) objective is to characterize the genomes of all eukaryotic life on Earth through networks of partner institutions focused on sequencing either specific taxa or eukaryotic communities at regional or national scales. Colombia's immense biodiversity and emerging network of stakeholders have inspired the creation of the national partnership "EBP-Colombia." Here, we discuss how this Colombian-driven collaboration between government, academia, and the private sector is integrating research with sustainable, environmentally focused strategies to develop Colombia's postconflict bioeconomy and conserve biological and cultural diversity. EBP-Colombia will accelerate the uptake of technology and promote partnership and exchange of knowledge among Colombian stakeholders and the EBP's global network of experts; assist with conservation strategies to preserve Colombia's vast biological wealth; and promote innovative approaches among public and private institutions in sectors such as agriculture, tourism, recycling, and medicine. EBP-Colombia can thus support Colombia's NBS with the objective of sustainable and inclusive development to address the many social, environmental, and economic challenges, including conflict, inequality, poverty, and low agricultural productivity, and so, offer an alternative model for economic development that similarly placed countries can adopt.

Genomic resources for rhesus macaques (Macaca mulatta).

Rhesus macaques (Macaca mulatta) are among the most extensively studied of nonhuman primates. This species has been the subject of many investigations concerning basic primate biology and behavior, including studies of social organization, developmental psychology, physiology, endocrinology, and neurodevelopment. Rhesus macaques are also critically important as a nonhuman primate model of human health and disease, including use in studies of infectious diseases, metabolic diseases, aging, and drug or alcohol abuse. Current research addressing fundamental biological and/or applied biomedical questions benefits from various genetic and genomic analyses. As a result, the genome of rhesus macaques has been the subject of more study than most nonhuman primates. This paper briefly discusses a number of information resources that can provide interested researchers with access to genetic and genomic data describing the content of the rhesus macaque genome, available information regarding genetic variation within the species, results from studies of gene expression, and other aspects of genomic analysis. Specific online databases are discussed, including the US National Center for Biotechnology Information, the University of California Santa Cruz genome browser, Ensembl genome browser, the Macaque Genotype and Phenotype database (mGAP), Rhesusbase, and others.

Identification, molecular evolution, and expression analysis of the transcription factor Smad gene family in lamprey.

Transcription factor small mothers against decapentaplegic (Smad) family SMAD proteins are the essential intracellular signal mediators and transcription factors for transforming growth factor ß (TGF-ß) signal transduction pathway, which usually exert pleiotropic actions on cell physiology, including immune response, cell migration and differentiation. In this study, the Smad family was identified in the most primitive vertebrates through the investigation of the transcriptome data of lampreys. The topology of phylogenetic tree showed that the four Smads (Smad1, Smad3, Smad4 and Smad6) in lampreys were subdivided into four different groups. Meanwhile, homology analysis indicated that most Smads were conserved with typical Mad Homology (MH) 1 and MH2 domains. In addition, Lethenteron reissneri Smads (Lr-Smads) adopted general Smads folding structure and had high tertiary structural similarity with human Smads (H-Smads). Genomic synteny analysis revealed that the large-scale duplication blocks were not found in lamprey genome and neighbor genes of lamprey Smads presented dramatic differences compared with jawed vertebrates. Importantly, quantitative real-time PCR analysis demonstrated that Smads were widely expressed in lamprey, and the expression level of Lr-Smads mRNA was up-regulated with different pathogenic stimulations. Moreover, depending on the weighted gene co-expression network analysis (WGCNA), four Lr-Smads were identified as two meaningful modules (green and gray). The functional analysis of these two modules showed that they might have a correlation with ployI:C. And these genes presented strong positive correlation during the immune response from the results of Pearson's correlation analysis. In conclusion, our results would not only enrich the information of Smad family in jawless vertebrates, but also lay the foundation for immunity in further study.

Genome survey and high-resolution genetic map provide valuable genetic resources for Fenneropenaeus chinensis.

Fenneropenaeus chinensis is one of the most important aquaculture species in China. Research on its genomic and genetic structure not only helps us comprehend the genetic basis of complex economic traits, but also offers theoretical guidance in selective breeding. In the present study, a genome survey sequencing was performed to generate a rough reference genome utilized for groping preliminary genome characteristics and facilitate linkage and quantitative trait locus (QTL) mapping. Linkage mapping was conducted using a reduced-representation sequencing method 2b-RAD. In total, 36,762 SNPs were genotyped from 273 progenies in a mapping family, and a high-resolution linkage map was constructed. The consensus map contained 12,884 markers and spanned 5257.81 cM with an average marker interval of 0.41 cM, which was the first high-resolution genetic map in F. chinensis to our knowledge. QTL mapping and association analysis were carried out in 29 characters including body size, sex and disease resistance. 87 significant QTLs were detected in several traits and they were also evaluated by association analysis. Results of this study provide us valuable suggestions in genetic improvement and breeding of new varieties and also lay a basic foundation for further application of cloning of economic genes in selective breeding program and marker-assisted selection.

Gaussian process regression for survival time prediction with genome-wide gene expression.

Predicting the survival time of a cancer patient based on his/her genome-wide gene expression remains a challenging problem. For certain types of cancer, the effects of gene expression on survival are both weak and abundant, so identifying non-zero effects with reasonable accuracy is difficult. As an alternative to methods that use variable selection, we propose a Gaussian process accelerated failure time model to predict survival time using genome-wide or pathway-wide gene expression data. Using a Monte Carlo expectation-maximization algorithm, we jointly impute censored log-survival time and estimate model parameters. We demonstrate the performance of our method and its advantage over existing methods in both simulations and real data analysis. The real data that we analyze were collected from 513 patients with kidney renal clear cell carcinoma and include survival time, demographic/clinical variables, and expression of more than 20 000 genes. In addition to the right-censored survival time, our method can also accommodate left-censored or interval-censored outcomes; and it provides a natural way to combine multiple types of high-dimensional -omics data. An R package implementing our method is available in the Supplementary material available at Biostatistics online.

Comparative accuracies of genetic values predicted for economically important milk traits, genome-wide association, and linkage disequilibrium patterns of Canadian Holstein cows.

Genomic selection methodologies and genome-wide association studies use powerful statistical procedures that correlate large amounts of high-density SNP genotypes and phenotypic data. Actual 305-d milk (MY), fat (FY), and protein (PY) yield data on 695 cows and 76,355 genotyping-by-sequencing-generated SNP marker genotypes from Canadian Holstein dairy cows were used to characterize linkage disequilibrium (LD) structure of Canadian Holstein cows. Also, the comparison of pedigree-based BLUP, genomic BLUP (GBLUP), and Bayesian (BayesB) statistical methods in the genomic selection methodologies and the comparison of Bayesian ridge regression and BayesB statistical methods in the genome-wide association studies were carried out for MY, FY, and PY. Results from LD analysis revealed that as marker distance decreases, LD increases through chromosomes. However, unexpected high peaks in LD were observed between marker pairs with larger marker distances on all chromosomes. The GBLUP and BayesB models resulted in similar heritability estimates through 10-fold cross-validation for MY and PY; however, the GBLUP model resulted in higher heritability estimates than BayesB model for FY. The predictive ability of GBLUP model was significantly lower than that of BayesB for MY, FY, and PY. Association analyses indicated that 28 high-effect markers and markers on Bos taurus autosome 14 located within 6 genes (DOP1B, TONSL, CPSF1, ADCK5, PARP10, and GRINA) associated significantly with FY.

Assessment of Genetic Drift in Large Pharmacogenomic Studies.

Genomic instability affects the reproducibility of experiments that rely on cancer cell lines. However, measuring the genomic integrity of these cells throughout a study is a costly endeavor that is commonly forgone. Here, we validate the identity of cancer cell lines in three pharmacogenomic studies and screen for genetic drift within and between datasets. Using SNP data from these datasets encompassing 1,497 unique cell lines and 63 unique pharmacological compounds, we show that genetic drift is widely prevalent in almost all cell lines with a median of 4.5%-6.1% of the total genome size drifted between any two isogenic cell lines. This study highlights the need for molecular profiling of cell lines to minimize the effects of passaging or misidentification in biomedical studies. We developed the CCLid web application, available at www.cclid.ca, to allow users to screen the genomic profiles of their cell lines against these datasets. A record of this paper's transparent peer review process is included in the Supplemental Information.

An assessment of genomic connectedness measures in Nellore cattle.

An important criterion to consider in genetic evaluations is the extent of genetic connectedness across management units (MU), especially if they differ in their genetic mean. Reliable comparisons of genetic values across MU depend on the degree of connectedness: the higher the connectedness, the more reliable the comparison. Traditionally, genetic connectedness was calculated through pedigree-based methods; however, in the era of genomic selection, this can be better estimated utilizing new approaches based on genomics. Most procedures consider only additive genetic effects, which may not accurately reflect the underlying gene action of the evaluated trait, and little is known about the impact of non-additive gene action on connectedness measures. The objective of this study was to investigate the extent of genomic connectedness measures, for the first time, in Brazilian field data by applying additive and non-additive relationship matrices using a fatty acid profile data set from seven farms located in the three regions of Brazil, which are part of the three breeding programs. Myristic acid (C14:0) was used due to its importance for human health and reported presence of non-additive gene action. The pedigree included 427,740 animals and 925 of them were genotyped using the Bovine high-density genotyping chip. Six relationship matrices were constructed, parametrically and non-parametrically capturing additive and non-additive genetic effects from both pedigree and genomic data. We assessed genome-based connectedness across MU using the prediction error variance of difference (PEVD) and the coefficient of determination (CD). PEVD values ranged from 0.540 to 1.707, and CD from 0.146 to 0.456. Genomic information consistently enhanced the measures of connectedness compared to the numerator relationship matrix by at least 63%. Combining additive and non-additive genomic kernel relationship matrices or a non-parametric relationship matrix increased the capture of connectedness. Overall, the Gaussian kernel yielded the largest measure of connectedness. Our findings showed that connectedness metrics can be extended to incorporate genomic information and non-additive genetic variation using field data. We propose that different genomic relationship matrices can be designed to capture additive and non-additive genetic effects, increase the measures of connectedness, and to more accurately estimate the true state of connectedness in herds.

Impact of sub-setting the data of the main Limousin beef cattle population on the estimates of across-country genetic correlations.

BACKGROUND: Cattle international genetic evaluations allow the comparison of estimated breeding values (EBV) across different environments, i.e. countries. For international evaluations, across-country genetic correlations (rg) need to be estimated. However, lack of convergence of the estimated parameters and high standard errors of the rg are often experienced for beef cattle populations due to limited across-country genetic connections. Furthermore, using all available genetic connections to estimate rg is prohibitive due to computational constraints, thus sub-setting the data is necessary. Our objective was to investigate and compare the impact of strategies of data sub-setting on estimated across-country rg and their computational requirements. METHODS: Phenotype and pedigree information for age-adjusted weaning weight was available for ten European countries and 3,128,338 Limousin beef cattle males and females. Using a Monte Carlo based expectation-maximization restricted maximum likelihood (MC EM REML) methodology, we estimated across-country rg by using a multi-trait animal model where countries are modelled as different correlated traits. Values of rg were estimated using the full data and four different sub-setting strategies that aimed at selecting the most connected herds from the largest population. RESULTS: Using all available data, direct and maternal rg (standard errors in parentheses) were on average equal to 0.79 (0.14) and 0.71 (0.19), respectively. Direct-maternal within-country and between-country rg were on average equal to - 0.12 (0.09) and 0.00 (0.14), respectively. Data sub-setting scenarios gave similar results: on average, estimated rg were smaller compared to using all data for direct (0.02) and maternal (0.05) genetic effects. The largest differences were obtained for the direct-maternal within-country and between-country rg, which were, on average 0.13 and 0.12 smaller compared to values obtained by using all data. Standard errors always increased when reducing the data, by 0.02 to 0.06, on average. The proposed sub-setting strategies reduced the required computing time up to 22% compared to using all data. CONCLUSIONS: Estimating all 120 across-country rg that are required for beef cattle international evaluations, using a multi-trait MC EM REML approach, is feasible but involves long computing time. We propose four strategies to reduce computational requirements while keeping a multi-trait estimation approach. In all scenarios with data sub-setting, the estimated rg were consistently smaller (mainly for direct-maternal rg) and had larger standard errors.

CONY: A Bayesian procedure for detecting copy number variations from sequencing read depths.

Copy number variations (CNVs) are genomic structural mutations consisting of abnormal numbers of fragment copies. Next-generation sequencing of read-depth signals mirrors these variants. Some tools used to predict CNVs by depth have been published, but most of these tools can be applied to only a specific data type due to modeling limitations. We develop a tool for copy number variation detection by a Bayesian procedure, i.e., CONY, that adopts a Bayesian hierarchical model and an efficient reversible-jump Markov chain Monte Carlo inference algorithm for whole genome sequencing of read-depth data. CONY can be applied not only to individual samples for estimating the absolute number of copies but also to case-control pairs for detecting patient-specific variations. We evaluate the performance of CONY and compare CONY with competing approaches through simulations and by using experimental data from the 1000 Genomes Project. CONY outperforms the other methods in terms of accuracy in both single-sample and paired-samples analyses. In addition, CONY performs well regardless of whether the data coverage is high or low. CONY is useful for detecting both absolute and relative CNVs from read-depth data sequences. The package is available at https://github.com/weiyuchung/CONY.

Conservation Assessment of the State Goat Farms by Using SNP Genotyping Data.

Conservation of genetic resources is of great concern globally to maintain genetic diversity for sustainable food security. Comprehensive identification of the breed composition, estimation of inbreeding and effective population size are essential for the effective management of farm animal genetic resources and to prevent the animals from genetic erosion. The Zhongwei male (ZWM), Arbas Cashmere male (ACM) and Jining Grey male (JGM) goats are conserved in three different state goat farms in China but their family information, level of inbreeding and effective population size are unknown. We investigated the genomic relationship, inbreeding coefficient and effective population size in these three breeds from three state goat farms using the Illumina goat SNP50 BeadChip. Genomic relationships and phylogenetic analysis revealed that the breeds are clearly separated and formed separate clusters based on their genetic relationship. We obtained a high proportion of informative SNPs, ranging from 91.8% in the Arbas Cashmere male to 96.2% in the Jining Grey male goat breeds with an average mean of 96.8%. Inbreeding, as measured by FROH, ranged from 1.79% in ZWM to 8.62% in ACM goat populations. High FROH values, elevated genomic coverage of very long ROH (>30 Mb) and severe decline in effective population size were recorded in ACM goat farm. The existence of a high correlation between FHOM and FROH indicates that FROH can be used as an alternative to inbreeding estimates in the absence of pedigree records. The Ne estimates 13 generations ago were 166, 69 and 79 for ZWM, ACM and JGM goat farm, respectively indicating that these goat breeds were strongly affected by selection pressure or genetic drift. This study provides insight into the genomic relationship, levels of inbreeding and effective population size in the studied goat populations conserved in the state goat farms which will be valuable in prioritizing populations for conservation and for developing suitable management practices for further genetic improvement of these Chinese male goats.

Using Monte Carlo method to include polygenic effects in calculation of SNP-BLUP model reliability.

An SNP-BLUP model is computationally scalable even for large numbers of genotyped animals. When genetic variation cannot be completely captured by SNP markers, a more accurate model is obtained by fitting a residual polygenic effect (RPG) as well. However, inclusion of the RPG effect increases the size of the SNP-BLUP mixed model equations (MME) by the number of genotyped animals. Consequently, the calculation of model reliabilities requiring elements of the inverted MME coefficient matrix becomes more computationally challenging with increasing numbers of genotyped animals. We present a Monte Carlo (MC)-based sampling method to estimate the reliability of the SNP-BLUP model including the RPG effect, where the MME size depends on the number of markers and MC samples. We compared reliabilities calculated using different RPG proportions and different MC sample sizes in analyzing 2 data sets. Data set 1 (data set 2) contained 19,757 (222,619) genotyped animals, with 11,729 (50,240) SNP markers, and 231,186 (13.35 million) pedigree animals. Correlations between the correct and the MC-calculated reliabilities were above 98% even with 5,000 MC samples and an 80% RPG proportion in both data sets. However, more MC samples were needed to achieve a small maximum absolute difference and mean squared error, particularly when the RPG proportion exceeded 20%. The computing time for MC SNP-BLUP was shorter than for GBLUP. In conclusion, the MC-based approach can be an effective strategy for calculating SNP-BLUP model reliability with an RPG effect included.