Expected values for the accuracy of predicted breeding values accounting for genetic differences between reference and target populations.

BACKGROUND: Genetic merit, or breeding values as referred to in livestock and crop breeding programs, is one of the keys to the successful selection of animals in commercial farming systems. The developments in statistical methods during the twentieth century and single nucleotide polymorphism (SNP) chip technologies in the twenty-first century have revolutionized agricultural production, by allowing highly accurate predictions of breeding values for selection candidates at a very early age. Nonetheless, for many breeding populations, realized accuracies of predicted breeding values (PBV) remain below the theoretical maximum, even when the reference population is sufficiently large, and SNPs included in the model are in sufficient linkage disequilibrium (LD) with the quantitative trait locus (QTL). This is particularly noticeable over generations, as we observe the so-called erosion of the effects of SNPs due to recombinations, accompanied by the erosion of the accuracy of prediction. While accurately quantifying the erosion at the individual SNP level is a difficult and unresolved task, quantifying the erosion of the accuracy of prediction is a more tractable problem. In this paper, we describe a method that uses the relationship between reference and target populations to calculate expected values for the accuracies of predicted breeding values for non-phenotyped individuals accounting for erosion. The accuracy of the expected values was evaluated through simulations, and a further evaluation was performed on real data. RESULTS: Using simulations, we empirically confirmed that our expected values for the accuracy of PBV accounting for erosion were able to correctly determine the prediction accuracy of breeding values for non-phenotyped individuals. When comparing the expected to the realized accuracies of PBV with real data, only one out of the four traits evaluated presented accuracies that were significantly higher than the expected, approaching h 2 . CONCLUSIONS: We defined an index of genetic correlation between reference and target populations, which summarizes the expected overall erosion due to differences in allele frequencies and LD patterns between populations. We used this correlation along with a trait's heritability to derive expected values for the accuracy ( R ) of PBV accounting for the erosion, and demonstrated that our derived E R | erosion is a reliable metric.

Runs of homozygosity and cross-generational inbreeding of Iranian fat-tailed sheep.

The Lori-Bakhtiari fat-tailed sheep is one of the most important heavyweight native breeds of Iran. The breed is robust and well-adapted to semi-arid regions and an important resource for smallholder farms. An established nucleus-based breeding scheme is used to improve their production traits but there is an indication of inbreeding depression and loss of genetic diversity due to selection. Here, we estimated the inbreeding levels and the distribution of runs of homozygosity (ROH) islands in 122 multi-generational female Lori-Bakhtiari from different half-sib families selected from a breeding station that were genotyped on the 50k array. A total of 2404 ROH islands were identified. On average, there were 19.70 ± 1.4 ROH per individual ranging between 6 and 41. The mean length of the ROH was 4.1 ± 0.14 Mb. There were 1999 short ROH of length 1-6 Mb and another 300 in the 6-12 Mb range. Additionally long ROH indicative of inbreeding were found in the ranges of 12-24 Mb (95) and 24-48 Mb (10). The average inbreeding coefficient (FROH) was 0.031 ± 0.003 with estimates varying from 0.006 to 0.083. Across generations, FROH increased from 0.019 ± 0.012 to 0.036 ± 0.007. Signatures of selection were identified on chromosomes 2, 6, and 10, encompassing 55 genes and 23 QTL associated with production traits. Inbreeding coefficients are currently within acceptable levels but across generations, inbreeding is increasing due to selection. The breeding program needs to actively monitor future inbreeding rates and ensure that the breed maintains or improves on its current levels of environmental adaptation.

deepGBLUP: joint deep learning networks and GBLUP framework for accurate genomic prediction of complex traits in Korean native cattle.

BACKGROUND: Genomic prediction has become widespread as a valuable tool to estimate genetic merit in animal and plant breeding. Here we develop a novel genomic prediction algorithm, called deepGBLUP, which integrates deep learning networks and a genomic best linear unbiased prediction (GBLUP) framework. The deep learning networks assign marker effects using locally-connected layers and subsequently use them to estimate an initial genomic value through fully-connected layers. The GBLUP framework estimates three genomic values (additive, dominance, and epistasis) by leveraging respective genetic relationship matrices. Finally, deepGBLUP predicts a final genomic value by summing all the estimated genomic values. RESULTS: We compared the proposed deepGBLUP with the conventional GBLUP and Bayesian methods. Extensive experiments demonstrate that the proposed deepGBLUP yields state-of-the-art performance on Korean native cattle data across diverse traits, marker densities, and training sizes. In addition, they show that the proposed deepGBLUP can outperform the previous methods on simulated data across various heritabilities and quantitative trait loci (QTL) effects. CONCLUSIONS: We introduced a novel genomic prediction algorithm, deepGBLUP, which successfully integrates deep learning networks and GBLUP framework. Through comprehensive evaluations on the Korean native cattle data and simulated data, deepGBLUP consistently achieved superior performance across various traits, marker densities, training sizes, heritabilities, and QTL effects. Therefore, deepGBLUP is an efficient method to estimate an accurate genomic value. The source code and manual for deepGBLUP are available at https://github.com/gywns6287/deepGBLUP .

Testicular hypoplasia in Nellore Cattle: Genetic analysis and functional analysis of genome-wide association study results.

Characterized by the incomplete development of the germinal epithelium of the seminiferous tubules, Testicular hypoplasia (TH) leads to decreased sperm concentration, increased morphological changes in sperm and azoospermia. Economic losses resulting from the disposal of affected bulls reduce the efficiency of meat production systems. A genome-wide association study and functional analysis were performed to identify genomic windows and the underlying positional candidate genes associated with TH in Nellore cattle. Phenotypic and pedigree data from 207,195 animals and genotypes (461,057 single nucleotide polymorphism, SNP) from 17,326 sires were used in this study. TH was evaluated as a binary trait measured at 18 months of age. A possible correlated response on TH resulting from the selection for scrotal circumference was evaluated by using a two-trait analysis. Thus, estimated breeding values were calculated by fitting a linear-threshold animal model in a Bayesian approach. The SNP effects were estimated using the weighted single-step genomic BLUP method. Twelve non-overlapping windows of 20 adjacent SNP that explained more than 1% of the additive genetic variance were selected for candidate gene annotation. Functional and gene prioritization analysis of the candidate genes identified genes (KHDRBS3, GPX5, STAR, ERLIN2), which might play an important role in the expression of TH due to their known roles in the spermatogenesis process, synthesis of steroids and lipid metabolism.

Identification of genes affecting milk fat and fatty acid composition in Vrindavani crossbred cattle using 50 K SNP-Chip.

The aim of this study was to identify candidate genes associated with milk fat per cent and fatty acid (FA) composition in Vrindavani cattle using the Illumina 50 K single-nucleotide polymorphism (SNP) array. After quality control, a total of 41,427 informative and high-quality SNPs were used for a genome-wide association study (GWAS) for milk fat percentage and 16 different types of fatty acids. Lactation stage, parity, test day milk yield, and proportion of exotic inheritance were included as fixed effects in the GWAS model. A total of 67 genome-wide significant (P < 1.20 × 10-06) SNPs and 176 suggestive significant (P < 2.41 × 10-05) SNPs were identified. Out of these, 15 SNPs were associated with more than one trait. The strongest associations were found on BTA14 for milk fat percentage and on BTA2 and BTA16 for polyunsaturated fatty acids. Several significant SNPs were identified close to or within the genes ELOVL6, FABP4, PMP2, PLIN1, MFGE8, GHRL2, and LDLRAD3 which are known to be associated with fat percentage and FA composition in dairy cattle breeds. This study is a step forward to better characterize the molecular mechanisms of phenotypic variation in milk fatty acids in a taurine-indicine composite cattle breed reared in tropical environments.

Gene expression of Hanwoo satellite cell differentiation in longissimus dorsi and semimembranosus.

BACKGROUND: Korean Hanwoo cattle are known for their high meat quality, especially their high intramuscular fat compared to most other cattle breeds. Different muscles have very different meat quality traits and a study of the myogenic process in satellite cells can help us better understand the genes and pathways that regulate this process and how muscles differentiate. RESULTS: Cell cultures of Longissimus dorsi muscle differentiated from myoblast into multinucleated myotubes faster than semimembranosus. Time-series RNA-seq identified a total of 13 differentially expressed genes between the two muscles during their development. These genes seem to be involved in determining muscle lineage development and appear to modulate the expression of myogenic regulatory factors (mainly MYOD and MYF5) during differentiation of satellite cells into multinucleate myotubes. Gene ontology enriched terms were consistent with the morphological changes observed in the histology. Most of the over-represented terms and genes expressed during myoblast differentiation were similar regardless of muscle type which indicates a highly conserved myogenic process albeit the rates of differentiation being different. There were more differences in the enriched GO terms during the end of proliferation compared to myoblast differentiation. CONCLUSIONS: The use of satellite cells from newborn Hanwoo calves appears to be a good model to study embryonic myogenesis in muscle. Our findings provide evidence that the differential expression of HOXB2, HOXB4, HOXB9, HOXC8, FOXD1, IGFN1, ZIC2, ZIC4, HOXA11, HOXC11, PITX1, SIM2 and TBX4 genes could be involved in the differentiation of Longissimus dorsi and Semimembranosus muscles. These genes seem to modulate the muscle fate of the satellite cells during myogenesis through a differential expression profile that also controls the expression of some myogenic regulatory factors (MYOD and MYF5). The number of differentially expressed genes across time was unsurprisingly large. In relation to the baseline day 0, there were 631, 155, 175, 519 and 586 DE genes in LD, while in SM we found 204, 0, 615, 761 and 1154 DE genes at days 1, 2, 4, 7 and 14 respectively.

Combining information from genome-wide association and multi-tissue gene expression studies to elucidate factors underlying genetic variation for residual feed intake in Australian Angus cattle.

BACKGROUND: Genome-wide association studies (GWAS) are extensively used to identify single nucleotide polymorphisms (SNP) underlying the genetic variation of complex traits. However, much uncertainly often still exists about the causal variants and genes at quantitative trait loci (QTL). The aim of this study was to identify QTL associated with residual feed intake (RFI) and genes in these regions whose expression is also associated with this trait. Angus cattle (2190 steers) with RFI records were genotyped and imputed to high density arrays (770 K) and used for a GWAS approach to identify QTL associated with RFI. RNA sequences from 126 Angus divergently selected for RFI were analyzed to identify the genes whose expression was significantly associated this trait with special attention to those genes residing in the QTL regions. RESULTS: The heritability for RFI estimated for this Angus population was 0.3. In a GWAS, we identified 78 SNPs associated with RFI on six QTL (on BTA1, BTA6, BTA14, BTA17, BTA20 and BTA26). The most significant SNP was found on chromosome BTA20 (rs42662073) and explained 4% of the genetic variance. The minor allele frequencies of significant SNPs ranged from 0.05 to 0.49. All regions, except on BTA17, showed a significant dominance effect. In 1 Mb windows surrounding the six significant QTL, we found 149 genes from which OAS2, STC2, SHOX, XKR4, and SGMS1 were the closest to the most significant QTL on BTA17, BTA20, BTA1, BTA14, and BTA26, respectively. In a 2 Mb windows around the six significant QTL, we identified 15 genes whose expression was significantly associated with RFI: BTA20) NEURL1B and CPEB4; BTA17) RITA1, CCDC42B, OAS2, RPL6, and ERP29; BTA26) A1CF, SGMS1, PAPSS2, and PTEN; BTA1) MFSD1 and RARRES1; BTA14) ATP6V1H and MRPL15. CONCLUSIONS: Our results showed six QTL regions associated with RFI in a beef Angus population where five of these QTL contained genes that have expression associated with this trait. Therefore, here we show that integrating information from gene expression and GWAS studies can help to better understand the genetic mechanisms that determine variation in complex traits.

Detection of genomic regions underlying resistance to gastrointestinal parasites in Australian sheep.

BACKGROUND: This study aimed at identifying genomic regions that underlie genetic variation of worm egg count, as an indicator trait for parasite resistance in a large population of Australian sheep, which was genotyped with the high-density 600 K Ovine single nucleotide polymorphism array. This study included 7539 sheep from different locations across Australia that underwent a field challenge with mixed gastrointestinal parasite species. Faecal samples were collected and worm egg counts for three strongyle species, i.e. Teladorsagia circumcincta, Haemonchus contortus and Trichostrongylus colubriformis were determined. Data were analysed using genome-wide association studies (GWAS) and regional heritability mapping (RHM). RESULTS: Both RHM and GWAS detected a region on Ovis aries (OAR) chromosome 2 that was highly significantly associated with parasite resistance at a genome-wise false discovery rate of 5%. RHM revealed additional significant regions on OAR6, 18, and 24. Pathway analysis revealed 13 genes within these significant regions (SH3RF1, HERC2, MAP3K, CYFIP1, PTPN1, BIN1, HERC3, HERC5, HERC6, IBSP, SPP1, ISG20, and DET1), which have various roles in innate and acquired immune response mechanisms, as well as cytokine signalling. Other genes involved in haemostasis regulation and mucosal defence were also detected, which are important for protection of sheep against invading parasites. CONCLUSIONS: This study identified significant genomic regions on OAR2, 6, 18, and 24 that are associated with parasite resistance in sheep. RHM was more powerful in detecting regions that affect parasite resistance than GWAS. Our results support the hypothesis that parasite resistance is a complex trait and is determined by a large number of genes with small effects, rather than by a few major genes with large effects.

Mitochondrial-related consequences of heat stress exposure during bovine oocyte maturation persist in early embryo development.

Hyperthermia during estrus has direct consequences on the maturing oocyte that carries over to the resultant embryo to compromise its ability to continue in development. Because early embryonic development is reliant upon maternal transcripts and other ooplasmic components, we examined impact of heat stress on bovine oocyte transcripts using microarray. Oocytes were matured at 38.5ºC for 24 h or 41.0ºC for the first 12 h of in vitro maturation; 38.5ºC thereafter. Transcriptome profile was performed on total (adenylated + deadenylated) RNA and polyadenylated mRNA populations. Heat stress exposure altered the abundance of several transcripts important for mitochondrial function. The extent to which transcript differences are coincident with functional changes was evaluated by examining reactive oxygen species, ATP content, and glutathione levels. Mitochondrial reactive oxygen species levels were increased by 6 h exposure to 41.0ºC while cytoplasmic levels were reduced compared to controls (P < 0.0001). Exposure to 41.0ºC for 12 h increased total and reduced glutathione levels in oocytes at 12 h but reduced them by 24 h (time × temperature P < 0.001). ATP content was higher in heat-stressed oocytes at 24 h (P < 0.0001). Heat-induced increases in ATP content of matured oocytes persisted in early cleavage-stage embryos (8- to 16-cell embryos; P < 0.05) but were no longer apparent in blastocysts (P > 0.05). Collectively, results indicate that direct exposure of maturing oocytes to heat stress may alter oocyte mitochondrial processes/function, which is inherited by the early embryo after fertilization.

Genetic tests for estimating dairy breed proportion and parentage assignment in East African crossbred cattle.

BACKGROUND: Smallholder dairy farming in much of the developing world is based on the use of crossbred cows that combine local adaptation traits of indigenous breeds with high milk yield potential of exotic dairy breeds. Pedigree recording is rare in such systems which means that it is impossible to make informed breeding decisions. High-density single nucleotide polymorphism (SNP) assays allow accurate estimation of breed composition and parentage assignment but are too expensive for routine application. Our aim was to determine the level of accuracy achieved with low-density SNP assays. METHODS: We constructed subsets of 100 to 1500 SNPs from the 735k-SNP Illumina panel by selecting: (a) on high minor allele frequencies (MAF) in a crossbred population; (b) on large differences in allele frequency between ancestral breeds; (c) at random; or (d) with a differential evolution algorithm. These panels were tested on a dataset of 1933 crossbred dairy cattle from Kenya/Uganda and on crossbred populations from Ethiopia (N = 545) and Tanzania (N = 462). Dairy breed proportions were estimated by using the ADMIXTURE program, a regression approach, and SNP-best linear unbiased prediction, and tested against estimates obtained by ADMIXTURE based on the 735k-SNP panel. Performance for parentage assignment was based on opposing homozygotes which were used to calculate the separation value (sv) between true and false assignments. RESULTS: Panels of SNPs based on the largest differences in allele frequency between European dairy breeds and a combined Nelore/N'Dama population gave the best predictions of dairy breed proportion (r2 = 0.962 to 0.994 for 100 to 1500 SNPs) with an average absolute bias of 0.026. Panels of SNPs based on the highest MAF in the crossbred population (Kenya/Uganda) gave the most accurate parentage assignments (sv = -1 to 15 for 100 to 1500 SNPs). CONCLUSIONS: Due to the different required properties of SNPs, panels that did well for breed composition did poorly for parentage assignment and vice versa. A combined panel of 400 SNPs was not able to assign parentages correctly, thus we recommend the use of 200 SNPs either for breed proportion prediction or parentage assignment, independently.

Local and global patterns of admixture and population structure in Iranian native cattle.

BACKGROUND: Two separate domestication events gave rise to humped zebu cattle in India and humpless taurine cattle in the Fertile Crescent of the Near and Middle East. Iran covers the Eastern side of the Fertile Crescent and exhibits a variety of native cattle breeds, however, only little is known about the admixture patterns of Iranian cattle and their contribution to the formation of modern cattle breeds. RESULTS: Genome-wide data (700 k chip) of eight Iranian cattle breeds (Sarabi N = 19, Kurdi N = 7, Taleshi N = 7, Mazandarani N = 10, Najdi N = 7, Pars N = 7, Kermani N = 9, and Sistani N = 9) were collected from across Iran. For a local assessment, taurine (Holstein and Jersey) and indicine (Brahman) outgroup samples were used. For the global perspective, 134 world-wide cattle breeds were included. Between breed variation amongst Iranian cattle explained 60 % (p < 0.001) of the total molecular variation and 82.88 % (p < 0.001) when outgroups were included. Several migration edges were observed within the Iranian cattle breeds. The highest indicine proportion was found in Sistani. All Iranian breeds with higher indicine ancestry were more admixed with a complex migration pattern. Nineteen founder populations most accurately explained the admixture of 44 selected representative cattle breeds (standard error 0.4617). Low levels of African ancestry were identified in Iranian cattle breeds (on average 7.5 %); however, the signal did not persist through all analyses. Admixture and migration analyses revealed minimal introgression from Iranian cattle into other taurine cattle (Holstein, Hanwoo, Anatolian breeds). CONCLUSION: The eight Iranian cattle breeds feature a discrete genetic composition which should be considered in conservation programs aimed at preserving unique species and genetic diversity. Despite a complex admixture pattern among Iranian cattle breeds, there was no strong introgression from other world-wide cattle breeds into Iranian cattle and vice versa. Considering Iran's central location of cattle domestication, Iranian cattle might represent a local domestication event that remained contained and did not contribute to the formation of modern breeds, or genetics of the ancestral population that gave rise to modern cattle is too diluted to be linked directly to any current cattle breeds.

Characterization and Profiling of Liver microRNAs by RNA-sequencing in Cattle Divergently Selected for Residual Feed Intake.

MicroRNAs (miRNAs) are short non-coding RNAs that post-transcriptionally regulate expression of mRNAs in many biological pathways. Liver plays an important role in the feed efficiency of animals and high and low efficient cattle demonstrated different gene expression profiles by microarray. Here we report comprehensive miRNAs profiles by next-gen deep sequencing in Angus cattle divergently selected for residual feed intake (RFI) and identify miRNAs related to feed efficiency in beef cattle. Two microRNA libraries were constructed from pooled RNA extracted from livers of low and high RFI cattle, and sequenced by Illumina genome analyser. In total, 23,628,103 high quality short sequence reads were obtained and more than half of these reads were matched to the bovine genome (UMD 3.1). We identified 305 known bovine miRNAs. Bta-miR-143, bta-miR-30, bta-miR-122, bta-miR-378, and bta-let-7 were the top five most abundant miRNAs families expressed in liver, representing more than 63% of expressed miRNAs. We also identified 52 homologous miRNAs and 10 novel putative bovine-specific miRNAs, based on precursor sequence and the secondary structure and utilizing the miRBase (v. 21). We compared the miRNAs profile between high and low RFI animals and ranked the most differentially expressed bovine known miRNAs. Bovine miR-143 was the most abundant miRNA in the bovine liver and comprised 20% of total expressed mapped miRNAs. The most highly expressed miRNA in liver of mice and humans, miR-122, was the third most abundant in our cattle liver samples. We also identified 10 putative novel bovine-specific miRNA candidates. Differentially expressed miRNAs between high and low RFI cattle were identified with 18 miRNAs being up-regulated and 7 other miRNAs down-regulated in low RFI cattle. Our study has identified comprehensive miRNAs expressed in bovine liver. Some of the expressed miRNAs are novel in cattle. The differentially expressed miRNAs between high and low RFI give some insights into liver miRNAs regulating physiological pathways underlying variation in this measure of feed efficiency in bovines.

Towards breed formation by island model divergence in Korean cattle.

BACKGROUND: The main cattle breed in Korea is the brown Hanwoo, which has been under artificial selection within a national breeding program for several decades. Varieties of the Hanwoo known as Jeju Black and Chikso were not included in the breeding program and remained isolated from the effects of recent artificial selection advancements. We analysed the Jeju Black and Chikso populations in regards to their genetic variability, state of inbreeding, as well as level of differentiation from the mainland Hanwoo population. RESULTS: Jeju Black and Chikso were found to have small estimated effective population sizes (N e ) of only 11 and 7, respectively. Despite a small N e , higher than expected heterozygosity levels were observed (0.303 and 0.306), however, lower allelic richness was found for the two island populations (1.76 and 1.77) compared to the mainland population (1.81). The increase in heterozygosity could be due to environmental disease challenges that promoted maintenance of higher genetic variability; however, no direct proof exists. Increased heterozygosity due to a first generation crossing of genetically different populations is not recorded. The differentiation between the Korean populations had F ST values between 0.014 and 0.036 which is not as high as the differentiation within European beef or dairy cattle breeds (0.047-0.111). This suggests that the three populations have not separated into independent breeds. CONCLUSION: Results agree with an island model of speciation where the brown Hanwoo represents the ancestral breed, whilst the Jeju Black and Chikso diverge from this common ancestor, following different evolutionary trajectories. Nevertheless, differences are minor and whether Jeju Black and Chikso cattle will develop into discrete breeds or reintegrate with the main population has to be seen in the future and will largely depend on human management decisions. This offers a rare opportunity to accompany the development of new breeds but also poses challenges on how to preserve these incipient breeds and ensure their long term viability.

Genome-wide linkage disequilibrium and genetic diversity in five populations of Australian domestic sheep.

BACKGROUND: Knowledge of the genetic structure and overall diversity of livestock species is important to maximise the potential of genome-wide association studies and genomic prediction. Commonly used measures such as linkage disequilibrium (LD), effective population size (N e ), heterozygosity, fixation index (F ST) and runs of homozygosity (ROH) are widely used and help to improve our knowledge about genetic diversity in animal populations. The development of high-density single nucleotide polymorphism (SNP) arrays and the subsequent genotyping of large numbers of animals have greatly increased the accuracy of these population-based estimates. METHODS: In this study, we used the Illumina OvineSNP50 BeadChip array to estimate and compare LD (measured by r (2) and D'), N e , heterozygosity, F ST and ROH in five Australian sheep populations: three pure breeds, i.e., Merino (MER), Border Leicester (BL), Poll Dorset (PD) and two crossbred populations i.e. F1 crosses of Merino and Border Leicester (MxB) and MxB crossed to Poll Dorset (MxBxP). RESULTS: Compared to other livestock species, the sheep populations that were analysed in this study had low levels of LD and high levels of genetic diversity. The rate of LD decay was greater in Merino than in the other pure breeds. Over short distances (<10 kb), the levels of LD were higher in BL and PD than in MER. Similarly, BL and PD had comparatively smaller N e than MER. Observed heterozygosity in the pure breeds ranged from 0.3 in BL to 0.38 in MER. Genetic distances between breeds were modest compared to other livestock species (highest F ST = 0.063) but the genetic diversity within breeds was high. Based on ROH, two chromosomal regions showed evidence of strong recent selection. CONCLUSIONS: This study shows that there is a large range of genome diversity in Australian sheep breeds, especially in Merino sheep. The observed range of diversity will influence the design of genome-wide association studies and the results that can be obtained from them. This knowledge will also be useful to design reference populations for genomic prediction of breeding values in sheep.

Genome-wide association study of body weight in Australian Merino sheep reveals an orthologous region on OAR6 to human and bovine genomic regions affecting height and weight.

BACKGROUND: Body weight (BW) is an important trait for meat production in sheep. Although over the past few years, numerous quantitative trait loci (QTL) have been detected for production traits in cattle, few QTL studies have been reported for sheep, with even fewer on meat production traits. Our objective was to perform a genome-wide association study (GWAS) with the medium-density Illumina Ovine SNP50 BeadChip to identify genomic regions and corresponding haplotypes associated with BW in Australian Merino sheep. METHODS: A total of 1781 Australian Merino sheep were genotyped using the medium-density Illumina Ovine SNP50 BeadChip. Among the 53 862 single nucleotide polymorphisms (SNPs) on this array, 48 640 were used to perform a GWAS using a linear mixed model approach. Genotypes were phased with hsphase; to estimate SNP haplotype effects, linkage disequilibrium blocks were identified in the detected QTL region. RESULTS: Thirty-nine SNPs were associated with BW at a Bonferroni-corrected genome-wide significance threshold of 1 %. One region on sheep (Ovis aries) chromosome 6 (OAR6) between 36.15 and 38.56 Mb, included 13 significant SNPs that were associated with BW; the most significant SNP was OAR6_41936490.1 (P = 2.37 × 10(-16)) at 37.69 Mb with an allele substitution effect of 2.12 kg, which corresponds to 0.248 phenotypic standard deviations for BW. The region that surrounds this association signal on OAR6 contains three genes: leucine aminopeptidase 3 (LAP3), which is involved in the processing of the oxytocin precursor; NCAPG non-SMC condensin I complex, subunit G (NCAPG), which is associated with foetal growth and carcass size in cattle; and ligand dependent nuclear receptor corepressor-like (LCORL), which is associated with height in humans and cattle. CONCLUSIONS: The GWAS analysis detected 39 SNPs associated with BW in sheep and a major QTL region was identified on OAR6. In several other mammalian species, regions that are syntenic with this region have been found to be associated with body size traits, which may reflect that the underlying biological mechanisms share a common ancestry. These findings should facilitate the discovery of causative variants for BW and contribute to marker-assisted selection.

hsphase: an R package for pedigree reconstruction, detection of recombination events, phasing and imputation of half-sib family groups.

BACKGROUND: Identification of recombination events and which chromosomal segments contributed to an individual is useful for a number of applications in genomic analyses including haplotyping, imputation, signatures of selection, and improved estimates of relationship and probability of identity by descent. Genotypic data on half-sib family groups are widely available in livestock genomics. This structure makes it possible to identify recombination events accurately even with only a few individuals and it lends itself well to a range of applications such as parentage assignment and pedigree verification. RESULTS: Here we present hsphase, an R package that exploits the genetic structure found in half-sib livestock data to identify and count recombination events, impute and phase un-genotyped sires and phase its offspring. The package also allows reconstruction of family groups (pedigree inference), identification of pedigree errors and parentage assignment. Additional functions in the package allow identification of genomic mapping errors, imputation of paternal high density genotypes from low density genotypes, evaluation of phasing results either from hsphase or from other phasing programs. Various diagnostic plotting functions permit rapid visual inspection of results and evaluation of datasets. CONCLUSION: The hsphase package provides a suite of functions for analysis and visualization of genomic structures in half-sib family groups implemented in the widely used R programming environment. Low level functions were implemented in C++ and parallelized to improve performance. hsphase was primarily designed for use with high density SNP array data but it is fast enough to run directly on sequence data once they become more widely available. The package is available (GPL 3) from the Comprehensive R Archive Network (CRAN) or from http://www-personal.une.edu.au/~cgondro2/hsphase.htm.

Detection of recombination events, haplotype reconstruction and imputation of sires using half-sib SNP genotypes.

BACKGROUND: Identifying recombination events and the chromosomal segments that constitute a gamete is useful for a number of applications in genomic analyses. In livestock, genotypic data are commonly available for half-sib families. We propose a straightforward but computationally efficient method to use single nucleotide polymorphism marker genotypes on half-sibs to reconstruct the recombination and segregation events that occurred during meiosis in a sire to form the haplotypes observed in its offspring. These meiosis events determine a block structure in paternal haplotypes of the progeny and this can be used to phase the genotypes of individuals in single half-sib families, to impute haplotypes of the sire if they are not genotyped or to impute the paternal strand of the offspring's sequence based on sequence data of the sire. METHODS: The hsphase algorithm exploits information from opposing homozygotes among half-sibs to identify recombination events, and the chromosomal regions from the paternal and maternal strands of the sire (blocks) that were inherited by its progeny. This information is then used to impute the sire's genotype, which, in turn, is used to phase the half-sib family. Accuracy (defined as R2) and performance of this approach were evaluated by using simulated and real datasets. Phasing results for the half-sibs were benchmarked to other commonly used phasing programs - AlphaPhase, BEAGLE and PedPhase 3. RESULTS: Using a simulated dataset with 20 markers per cM, and for a half-sib family size of 4 and 40, the accuracy of block detection, was 0.58 and 0.96, respectively. The accuracy of inferring sire genotypes was 0.75 and 1.00 and the accuracy of phasing was around 0.97, respectively. hsphase was more robust to genotyping errors than PedPhase 3, AlphaPhase and BEAGLE. Computationally, hsphase was much faster than AlphaPhase and BEAGLE. CONCLUSIONS: In half-sib families of size 8 and above, hsphase can accurately detect block structure of paternal haplotypes, impute genotypes of ungenotyped sires and reconstruct haplotypes in progeny. The method is much faster and more accurate than other widely used population-based phasing programs. A program implementing the method is freely available as an R package (hsphase).

SNPQC--an R pipeline for quality control of Illumina SNP genotyping array data.

In genome-wide association studies, quality control (QC) of genotypes is important to avoid spurious results. It is also important to maintain long-term data integrity, particularly in settings with ongoing genotyping (e.g. estimation of genomic breeding values). Here we discuss SNPQc, a fully automated pipeline to perform QC analyses of Illumina SNP array data. It applies a wide range of common quality metrics with user-defined filtering thresholds to generate a comprehensive QC report and a filtered dataset, including a genomic relationship matrix, ready for further downstream analyses which make it amenable for integration in high-throughput environments. SNPQC also builds a database to store genotypic, phenotypic and quality metrics to ensure data integrity and the option of integrating more samples from subsequent runs. The program is generic across species and array designs, providing a convenient interface between the genotyping laboratory and downstream genome-wide association study or genomic prediction.

Multi-omics data elucidate parasite-host-microbiota interactions and resistance to Haemonchus contortus in sheep.

BACKGROUND: The integration of molecular data from hosts, parasites, and microbiota can enhance our understanding of the complex biological interactions underlying the resistance of hosts to parasites. Haemonchus contortus, the predominant sheep gastrointestinal parasite species in the tropics, causes significant production and economic losses, which are further compounded by the diminishing efficiency of chemical control owing to anthelmintic resistance. Knowledge of how the host responds to infection and how the parasite, in combination with microbiota, modulates host immunity can guide selection decisions to breed animals with improved parasite resistance. This understanding will help refine management practices and advance the development of new therapeutics for long-term helminth control. METHODS: Eggs per gram (EPG) of feces were obtained from Morada Nova sheep subjected to two artificial infections with H. contortus and used as a proxy to select animals with high resistance or susceptibility for transcriptome sequencing (RNA-seq) of the abomasum and 50 K single-nucleotide genotyping. Additionally, RNA-seq data for H. contortus were generated, and amplicon sequence variants (ASV) were obtained using polymerase chain reaction amplification and sequencing of bacterial and archaeal 16S ribosomal RNA genes from sheep feces and rumen content. RESULTS: The heritability estimate for EPG was 0.12. GAST, GNLY, IL13, MGRN1, FGF14, and RORC genes and transcripts were differentially expressed between resistant and susceptible animals. A genome-wide association study identified regions on chromosomes 2 and 11 that harbor candidate genes for resistance, immune response, body weight, and adaptation. Trans-expression quantitative trait loci were found between significant variants and differentially expressed transcripts. Functional co-expression modules based on sheep genes and ASVs correlated with resistance to H. contortus, showing enrichment in pathways of response to bacteria, immune and inflammatory responses, and hub features of the Christensenellaceae, Bacteroides, and Methanobrevibacter genera; Prevotellaceae family; and Verrucomicrobiota phylum. In H. contortus, some mitochondrial, collagen-, and cuticle-related genes were expressed only in parasites isolated from susceptible sheep. CONCLUSIONS: The present study identified chromosome regions, genes, transcripts, and pathways involved in the elaborate interactions between the sheep host, its gastrointestinal microbiota, and the H. contortus parasite. These findings will assist in the development of animal selection strategies for parasite resistance and interdisciplinary approaches to control H. contortus infection in sheep.

Genomic divergence of zebu and taurine cattle identified through high-density SNP genotyping.

BACKGROUND: Natural selection has molded evolution across all taxa. At an arguable date of around 330,000 years ago there were already at least two different types of cattle that became ancestors of nearly all modern cattle, the Bos taurus taurus more adapted to temperate climates and the tropically adapted Bos taurus indicus. After domestication, human selection exponentially intensified these differences. To better understand the genetic differences between these subspecies and detect genomic regions potentially under divergent selection, animals from the International Bovine HapMap Experiment were genotyped for over 770,000 SNP across the genome and compared using smoothed F(ST). The taurine sample was represented by ten breeds and the contrasting zebu cohort by three breeds. RESULTS: Each cattle group evidenced similar numbers of polymorphic markers well distributed across the genome. Principal components analyses and unsupervised clustering confirmed the well-characterized main division of domestic cattle. The top 1% smoothed F(ST), potentially associated to positive selection, contained 48 genomic regions across 17 chromosomes. Nearly half of the top F(ST) signals (n = 22) were previously detected using a lower density SNP assay. Amongst the strongest signals were the BTA7:~50 Mb and BTA14:~25 Mb; both regions harboring candidate genes and different patterns of linkage disequilibrium that potentially represent intrinsic differences between cattle types. The bottom 1% of the smoothed F(ST) values, potentially associated to balancing selection, included 24 regions across 13 chromosomes. These regions often overlap with copy number variants, including the highly variable region at BTA23:~24 Mb that harbors a large number of MHC genes. Under these regions, 318 unique Ensembl genes are annotated with a significant overrepresentation of immune related pathways. CONCLUSIONS: Genomic regions that are potentially linked to purifying or balancing selection processes in domestic cattle were identified. These regions are of particular interest to understand the natural and human selective pressures to which these subspecies were exposed to and how the genetic background of these populations evolved in response to environmental challenges and human manipulation.