Illumina BovineSNP50 BeadChip Research Articles

Genome-Wide Association Study for Milk Somatic Cell Score in Holstein Friesian Cows in Slovenia.

Mastitis is a serious challenge for the dairy industry, leading to economic losses and affecting milk quality. The aim of this study is to identify genetic factors associated with mastitis resistance by conducting a genome-wide association study (GWAS) for the somatic cell score (SCS). Phenotypic records of 350 Holstein Friesian cows were obtained from the Slovenian Cattle Recording Scheme Database and consisted of around 1500 lactation data from 2012 to 2023 collected on a single farm in Slovenia. Corresponding genotypic data were also retrieved from the same database and genotyped using the Illumina BovineSNP50 BeadChip (Illumina, Inc., San Diego, CA, USA). For the association study, three SCS parameters were considered, including lactation mean somatic cell score (LM_SCS), maximum SCS value (SCSMAX), and top three mean value of SCS (TOP3). After performing a GWAS using FarmCPU and BLINK models, five significant SNPs associated with the TOP3 trait were found on BTA 14, 15, 22, and 29. The identified SNP markers were closely linked to six known candidate genes (DNASE1L3, SLC36A4, ARMC1, PDE7A, MMP13, CD44). These results indicate potential genetic markers associated with SCS in the Slovenian Holstein Friesian population.

Genomic patterns of selection in morphometric traits across diverse Indian cattle breeds.

This study seeks a comprehensive exploration of genome-wide selective processes impacting morphometric traits across diverse cattle breeds, utilizing an array of statistical methods. Morphometric traits, encompassing both qualitative and quantitative variables, play a pivotal role in characterizing and selecting livestock breeds based on their external appearance, size, and physical attributes. While qualitative traits, such as color, horn structure, and coat type, contribute to adaptive features and breed identification, quantitative traits like body weight and conformation measurements bear a closer correlation with production characteristics. This study employs advanced genotyping technologies, including the Illumina BovineSNP50 Bead Chip and next-generation sequencing methods like Reduced Representation sequencing, to identify genomic signatures associated with these traits. We applied four intra-population methods to find evidence of selection, such as Tajima's D, CLR, iHS, and ROH. We found a total of 40 genes under the selection signature, that were associated with morphometric traits in five cattle breeds (Kankrej, Tharparkar, Nelore, Sahiwal, and Gir). Crucial genes such as ADIPDQ, DPP6, INSIG1, SLC35D2 in Kankrej, LPL, ATP6V1B2, CDC14B in Tharparkar, HPSE2, PLAG1 in Nelore, PCSK1, PRKD1 in Sahiwal, and GNAQ, HPCAL1 in Gir were identified in our study. This approach provides valuable insights into the genetic basis of variations in body weight and conformation traits, facilitating informed selection processes and offering a deeper understanding of the evolutionary and domestication processes in diverse cattle breeds.

The use of SNP markers for cattle breed identification.

A potential application of single nucleotide polymorphisms (SNPs) in animal husbandry and production is identification of the animal breed. In this study, using chosen marker selection methods and genotypic data obtained with the use of Illumina Bovine SNP50 BeadChip for individuals belonging to ten cattle breeds, the reduced panels containing the most informative SNP markers were developed. The suitability of selected SNP panels for the effective and reliable assignment of the studied individuals to the breed of origin was checked by three allocation algorithms implemented in GeneClass 2. The studied breeds set included both Polish-native breeds under the genetic resources conservation programs and highly productive breeds with a global range. For all of the tested marker selection methods ("delta" and two FST-based variants), two separate methodological approaches of marker assortment were used and three marker panels were created with 96, 192, and 288 SNPs respectively, to determine the minimum number of markers required for effective differentiation of the studied breeds. Moreover, the usefulness of the most effective panels of markers to assess the population structure and genetic diversity of the analyzed breeds was examined. The conducted analyses showed the possibility of using SNP subsets from medium-density genotypic microarrays to distinguish breeds of cattle kept in Poland and to analyze their genetic structure.

Genome-wide association study for growth traits in Blanco Orejinegro and Romosinuano cattle

Growth traits are economically important characteristics for the genetic improvement of local cattle breeds. Genome-wide association studies (GWAS) provide valuable information to enhance the understanding on the genetics of complex traits. The aim of this study was to perform a GWAS to identify genomic regions and genes associated to birth weight, weaning weight adjusted for 240 days, 16 months, and 24 months weight in Romosinuano (ROMO) and Blanco Orejinegro (BON) cattle. A single-step genomic-BLUP was implemented using 596 BON and 569 ROMO individuals that were genotyped with an Illumina BovineSNP50 BeadChip. There were 25 regions of interest identified on different chromosomes, with few of them simultaneously associated with two or more growth traits and some were common to both breeds. The gene mapping allowed to find 173 annotations on these regions, from which 49 represent potential candidate genes with known growth-related functions in cattle and other species. Among the regions that were associated with several growth traits, that at 24 – 27 MB of BTA14, has important candidate genes such as LYPLA1, XKR4, TMEM68 and PLAG1. Another region of interest at 0.40–0.77 Mb of BTA23 was identified in both breeds, containing KHDRBS2 as a potential candidate gene influencing body weight. Future studies targeting these regions could provide more knowledge to uncover the genetic architecture underlying growth traits in BON and ROMO cattle. The genomic regions and genes identified in this study could be used to improve the prediction of genetic merit for growth traits in these creole cattle breeds.

Genetic evaluations for endangered dual-purpose German Black Pied cattle using 50K SNPs, a breed-specific 200K chip, and whole-genome sequencing

Genetic evaluations of local cattle breeds are hampered due to small reference groups or biased due to the utilization of SNP effects estimated in other large populations. Against this background, there is a lack of studies addressing the possible advantage of whole-genome sequences (WGS) or consideration of specific variants from WGS data in genomic predictions for local breeds with small population size. Consequently, the aim of this study was to compare genetic parameters and accuracies of genomic estimated breeding values (GEBV) for 305-d production traits, fat-to protein ratio (FPR), and somatic cell score (SCS) at the first test date after calving and confirmation traits of the endangered German Black Pied cattle (DSN) breed using 4 different marker panels: (1) the commercial 50K Illumina BovineSNP50 BeadChip, (2) a customized 200K chip designed for DSN (DSN200K) which considers the most important variants for DSN from WGS, (3) randomly generated 200K chips based on WGS data, and (4) a WGS panel. The same number of animals was considered for all marker panel analyses (i.e., 1,811 genotyped or sequenced cows for conformation traits, 2,383 cows for lactation production traits, and 2,420 cows for FPR and SCS). Mixed models for the estimation of genetic parameters directly included the respective genomic relationship matrix from the different marker panels plus the trait-specific fixed effects. For the calculation of GEBV accuracies, we applied repeated random subsampling validation. In the process of separate cross-validations per trait, we created a validation set including 20% of cows with masked phenotypes, and a training set comprising 80% of the cows. The cows were selected randomly in a procedure with 10 replicates considering replacements in the different scenarios. The accuracy was defined as the correlation between the direct GEBV and the phenotypes with subtracted corresponding fixed effects for the cows in the validation set. For FPR and SCS, as well as for lactation production traits, heritabilities were largest based on WGS data, but the increase compared with the 50K or DSN200K applications was quite small in the range from 0.01 to 0.03. Also, for most of the conformation traits, heritabilities were largest based on WGS and DSN200K data, but the increase was in the range of the corresponding standard error. Accordingly, GEBV accuracies for most of the studied traits were highest based on WGS data or when utilizing the DSN200K chip, but the accuracy differences across the marker panels were quite small and nonsignificant. In conclusion, WGS data and the DSN200K chip only contributed to minor improvements in genomic predictions, still justifying the use of the commercial 50K chip. Nevertheless, WGS and the 200KDSN chip harbor breed-specific variants, which are valuable for studying causal genetic mechanisms in the endangered DSN population.

Genomic dissection of repeatability considering additive and nonadditive genetic effects for semen production traits in beef and dairy bulls.

The low heritability and moderate repeatability of semen production traits in beef and dairy bulls suggest that nonadditive genetic effects, such as dominance and epistatic effects, play an important role in semen production and should therefore be considered in genetic improvement programs. In this study, the repeatability of semen production traits in Japanese Black bulls (JB) as beef bulls and Holstein bulls (HOL) as dairy bulls was evaluated by considering additive and nonadditive genetic effects using the Illumina BovineSNP50 BeadChip. We also evaluated the advantage of using more complete models that include nonadditive genetic effects by comparing the rank of genotyped animals and the phenotype prediction ability of each model. In total, 65,463 records for 615 genotyped JB and 48,653 records for 845 genotyped HOL were used to estimate additive and nonadditive (dominance and epistatic) variance components for semen volume (VOL), sperm concentration (CON), sperm motility (MOT), MOT after freeze-thawing (aMOT), and sperm number (NUM). In the model including both additive and nonadditive genetic effects, the broad-sense heritability (0.17 to 0.43) was more than twice as high as the narrow-sense heritability (0.04 to 0.11) for all traits and breeds, and the differences between the broad-sense heritability and repeatability were very small for VOL, NUM, and CON in both breeds. A large proportion of permanent environmental variance was explained by epistatic variance. The epistatic variance as a proportion of total phenotypic variance was 0.07 to 0.33 for all traits and breeds. In addition, heterozygosity showed significant positive relationships with NUM, MOT, and aMOT in JB and NUM in HOL, when the heterozygosity rate was included as a covariate. In a comparison of models, the inclusion of nonadditive genetic effects resulted in a re-ranking of the top genotyped bulls for the additive effects. Adjusting for nonadditive genetic effects could be expected to produce a more accurate breeding value, even if the models have similar fitting. However, including nonadditive genetic effects did not improve the ability of any model to predict phenotypic values for any trait or breed compared with the predictive ability of a model that includes only additive effects. Consequently, although nonadditive genetic effects, especially epistatic effects, play an important role in semen production traits, they do not improve prediction accuracy in beef and dairy bulls.

Genome-Wide Genomic and Functional Association Study for Workability and Calving Traits in Holstein Cattle.

Simple SummaryTraits related to the calving abilities and workability of cows are essential both for the dairy economy and for the welfare of cows. We analysed the direct and maternal components of calving ease, direct and maternal components of stillbirth, milking speed, and temperament by looking for SNPs, gene ontologies, and metabolic pathways significantly associated with the additive genetic variability of those traits. At the genetic level, 150 significant SNPs were identified whereas at the functional level we found 45 significant gene ontology terms and 5 metabolic pathways.The goal of our study was to identify the SNPs, metabolic pathways (KEGG), and gene ontology (GO) terms significantly associated with calving and workability traits in dairy cattle. We analysed direct (DCE) and maternal (MCE) calving ease, direct (DSB) and maternal (MSB) stillbirth, milking speed (MSP), and temperament (TEM) based on a Holstein-Friesian dairy cattle population consisting of 35,203 individuals. The number of animals, depending on the trait, ranged from 22,301 bulls for TEM to 30,603 for DCE. We estimated the SNP effects (based on 46,216 polymorphisms from Illumina BovineSNP50 BeadChip Version 2) using a multi-SNP mixed model. The SNP positions were mapped to genes and the GO terms/KEGG pathways of the corresponding genes were assigned. The estimation of the GO term/KEGG pathway effects was based on a mixed model using the SNP effects as dependent variables. The number of significant SNPs comprised 59 for DCE, 25 for DSB and MSP, 17 for MCE and MSB, and 7 for TEM. Significant KEGG pathways were found for MSB (2), TEM (2), and MSP (1) and 11 GO terms were significant for MSP, 10 for DCE, 8 for DSB and TEM, 5 for MCE, and 3 for MSB. From the perspective of a better understanding of the genomic background of the phenotypes, traits with low heritabilities suggest that the focus should be moved from single genes to the metabolic pathways or gene ontologies significant for the phenotype.

Opportunities for genomic selection of cheese-making traits in Montbéliarde cows

As part of the From'MIR project, traits related to the composition and cheese-making properties (CMP) of milk were predicted from 6.6 million mid-infrared spectra taken from 410,622 Montbéliarde cows (19,862 with genotypes). Genome-wide association studies of imputed whole-genome sequences highlighted candidate SNPs that were then added to the EuroG10K BeadChip, which is routinely used in genomic selection. In the present study, we (1) assessed the reliability of single-step genomic BLUP breeding values (ssEBVs) for cheese yields, coagulation traits, and casein and calcium content generated from test-day records of the first 3 lactations, (2) estimated realized genetic trends for these traits over the last decade, and (3) simulated different cheese-making breeding objectives and estimated the responses for CMP as well as for other traits currently selected in the Montbéliarde breed. To estimate the reliability of ssEBVs, the available data were split into 2 independent training and validation sets that respectively contained cows with the oldest and the most recent lactation data. The training set included 155,961 cows (12,850 with genotypes) and was used to predict ssEBVs of 2,125 genotyped cows in the validation set. We first tested 4 models that included either lactation (LACT) or test-day (TD) records from the first (1) or the first 3 (3) lactations, giving equal weight to all 50K SNP effects. Mean reliabilities were 61%, 62%, 63%, and 64% for the LACT1, LACT3, TD1, and TD3 models, respectively. Using the most accurate model (TD3), we then compared the reliabilities of 3 scenarios with: SNPs from the Illumina BovineSNP50 BeadChip only, equally weighted (50K); 50K SNPs plus additional candidate SNPs, equally weighted (50K+); and 50K and candidate SNPs with additional weight given to 7 to 14 candidate SNPs, depending on the trait (CAND). The 50K+ and CAND scenarios led to similar mean reliabilities (67%) and both outperformed the 50K scenario (64%), whereas the CAND scenario generated the less biased ssEBVs. To assess genetic trends, SNP effects were estimated with a single-step GBLUP based on the TD3 model and the 50K scenario applied to the whole population (2.6 million performance records from 190,261 cows and 423,348 animals in the pedigree, of which 21,874 were genotyped) and then applied to 50K genotypes of 21,171 males and 311,761 females. We detected a positive genetic trend for all CMP during the last decade, probably due to selection for an increase in milk protein and fat content in Montbéliarde cows. Finally, we compared the selection responses to 3 different breeding objectives: the current Montbéliarde total merit index (TMI) and 2 alternative scenarios that gave a weight of 70% to TMI and the remaining 30% to either milk casein content (TMI-COMP) or a combination of 3 CMP (TMI-Cheese). The TMI-Cheese scenario yielded the best responses for all the CMP analyzed, whereas values in the TMI-COMP scenario were intermediate, with a slight effect on other traits currently included in TMI. Based on these results, a program of genomic evaluation for CMP predicted from mid-infrared spectra was designed and implemented for the Montbéliarde breed.

Comparing BeadChip and WGS Genotyping: Non-Technical Failed Calling Is Attributable to Additional Variation within the Probe Target Sequence.

Microarray-based genomic selection is a central tool to increase the genetic gain of economically significant traits in dairy cattle. Yet, the effectivity of this tool is slightly limited, as estimates based on genotype data only partially explain the observed heritability. In the analysis of the genomes of 17 Israeli Holstein bulls, we compared genotyping accuracy between whole-genome sequencing (WGS) and microarray-based techniques. Using the standard GATK pipeline, the short-variant discovery within sequence reads mapped to the reference genome (ARS-UCD1.2) was compared to the genotypes from Illumina BovineSNP50 BeadChip and to an alternative method, which computationally mimics the hybridization procedure by mapping reads to 50 bp spanning the BeadChip source sequences. The number of mismatches between the BeadChip and WGS genotypes was low (0.2%). However, 17,197 (40% of the informative SNPs) had extra variation within 50 bp of the targeted SNP site, which might interfere with hybridization-based genotyping. Consequently, with respect to genotyping errors, BeadChip varied significantly and systematically from WGS genotyping, introducing null allele-like effects and Mendelian errors (<0.5%), whereas the GATK algorithm of local de novo assembly of haplotypes successfully resolved the genotypes in the extra-variable regions. These findings suggest that the microarray design should avoid polymorphic genomic regions that are prone to extra variation and that WGS data may be used to resolve erroneous genotyping, which may partially explain missing heritability.

Genome-wide detection of non-additive quantitative trait loci for semen production traits in beef and dairy bulls

Semen production traits are important aspects of bull fertility, because semen quantity leads to direct profits for artificial insemination centres, and semen quality is associated with the probability of achieving a pregnancy. Most genome-wide association studies (GWASs) for semen production traits have assumed that each quantitative trait locus (QTL) has an additive effect. However, GWASs that account for non-additive effects are also important in fitness traits, such as bull fertility. Here, we performed a GWAS using models that accounted for additive and non-additive effects to evaluate the importance of non-additive effects on five semen production traits in beef and dairy bulls. A total of 65 463 records for 615 Japanese Black bulls (JB) and 50 734 records for 873 Holstein bulls (HOL), which were previously genotyped using the Illumina BovineSNP50 BeadChip, were used to estimate genetic parameters and perform GWAS. The heritability estimates were low (ranged from 0.11 to 0.23), and the repeatability estimates were low to moderate (ranged from 0.28 to 0.45) in both breeds. The estimated repeatability was approximately twice as high as the estimated heritability for all traits. In this study, only one significant region with an additive effect was detected in each breed, but multiple significant regions with non-additive effects were detected for each breed. In particular, the region at approximately 64 Mbp on Bos taurus autosome 17 had the highest significant non-additive effect on four semen production traits in HOL. The rs41843851 single nucleotide polymorphism (SNP) in the region had a much lower P-value for the non-additive effect (P-value = 1.1 × 10−31) than for the additive effect (P-value = 1.1 × 10−8) in sperm motility. The AA and AB genotypes on the SNP had a higher phenotype than the BB genotype in HOL, and there was no bull with the BB genotype in JB. Our results showed that non-additive QTLs affect semen production traits, and a novel QTL accounting for non-additive effects could be detected by GWAS. This study provides new insights into non-additive QTLs that affect fitness traits, such as semen production traits in beef and dairy bulls.

GENOMIC LOCALIZATION OF QTL ASSOCIATED SNP WITH PHENOTYPIC EFFECTS COMMON TO KAZAKH WHITE-HEADED AND AULIEKOL BREEDS

The article presents the results of a genome-wide search for QTL associated SNP with phenotypic effects in Kazakh white-headed and Auliekol cattle. There were determined 6 genomic regions common for the two breeds (with a total length of 192.8 mB bp), 7 breed-specific regions for the Kazakh white-headed (total length of 19.52 mB bp), and 12 breed-specific for the Auliekol breed (total length of 15, 10 mB bp). Of the 479 breed-wide QTL associated SNP (161 for birth weight, 224 for weaning weight, 10 for body weight at 12 months, and 84 for average daily weight gain), only 44 are in the regions of the genome most similar in the two breeds and 1 in the area breed-specific for the Kazakh white-headed breed. A significant part of the QTL associated SNP that we established was also described by other authors who conducted a genome-wide search in other breeds. At the same time, the studies were mainly carried out on the Illumina BovineSNP50 BeadChip chip with a lower coating density, which partly explains the lack of data on other polymorphisms that we detected. Candidate genes, which contain QTL associated SNP common to both breeds, mainly encode intracellular proteins that are translated into all types of tissues and are involved in general body metabolic and physiological processes. Regarding intragenic localization, it can be noted that for the most part, breed-wide QTL associated SNP are located within introns or in the regulatory regions of candidate genes.

Design and performance of a bovine 200\u2009k SNP chip developed for endangered German Black Pied cattle (DSN)

BackgroundGerman Black Pied cattle (DSN) are an endangered dual-purpose breed which was largely replaced by Holstein cattle due to their lower milk yield. DSN cattle are kept as a genetic reserve with a current herd size of around 2500 animals. The ability to track sequence variants specific to DSN could help to support the conservation of DSN’s genetic diversity and to provide avenues for genetic improvement.ResultsWhole-genome sequencing data of 304 DSN cattle were used to design a customized DSN200k SNP chip harboring 182,154 variants (173,569 SNPs and 8585 indels) based on ten selection categories. We included variants of interest to DSN such as DSN unique variants and variants from previous association studies in DSN, but also variants of general interest such as variants with predicted consequences of high, moderate, or low impact on the transcripts and SNPs from the Illumina BovineSNP50 BeadChip. Further, the selection of variants based on haplotype blocks ensured that the whole-genome was uniformly covered with an average variant distance of 14.4 kb on autosomes. Using 300 DSN and 162 animals from other cattle breeds including Holstein, endangered local cattle populations, and also a Bos indicus breed, performance of the SNP chip was evaluated. Altogether, 171,978 (94.31%) of the variants were successfully called in at least one of the analyzed breeds. In DSN, the number of successfully called variants was 166,563 (91.44%) while 156,684 (86.02%) were segregating at a minor allele frequency > 1%. The concordance rate between technical replicates was 99.83 ± 0.19%.ConclusionThe DSN200k SNP chip was proved useful for DSN and other Bos taurus as well as one Bos indicus breed. It is suitable for genetic diversity management and marker-assisted selection of DSN animals. Moreover, variants that were segregating in other breeds can be used for the design of breed-specific customized SNP chips. This will be of great value in the application of conservation programs for endangered local populations in the future.

Local Ancestry to Identify Selection in Response to Trypanosome Infection in Baoulé x Zebu Crossbred Cattle in Burkina Faso.

The genomes of crossbred (admixed) individuals are a mosaic of ancestral haplotypes formed by recombination in each generation. The proportion of these ancestral haplotypes in certain genomic regions can be responsible for either susceptibility or tolerance against pathogens, and for performances in production traits. Using a medium-density genomic marker panel from the Illumina Bovine SNP50 BeadChip, we estimated individual admixture proportions for Baoulé x Zebu crossbred cattle in Burkina Faso, which were tested for trypanosome infection by direct ELISA from blood samples. Furthermore, we calculated local ancestry deviation from average for each SNP across 29 autosomes to identify potential regions under selection in the trypanotolerant Baoulé cattle and their crossbreds. We identified significant deviation from the local average ancestry (above 5 and 10% genome-wide thresholds) on chromosomes 8 and 19 in the positive animals, while the negative ones showed higher deviation on chromosomes 6, 19, 21, and 22. Some candidate genes on chromosome 6 (PDGFRA) and chromosome 19 (CDC6) have been found associated to trypanotolerance in West African taurines. Screening for FST outliers in trypanosome positive/negative animals we detected seven variants putatively under selection. Finally, we identified a minimum set of highly ancestry informative markers for routine admixture testing. The results of this study contribute to a better understanding of the genetic basis of trypanotolerance in Baoulé cattle and their crossbreeds. Furthermore, we provide a small informative marker set to monitor admixture in this valuable indigenous breed. As such, our results are important for conserving the genetic uniqueness and trypanotolerance of Baoulé cattle, as well as for the improvement of Baoulé and Zebu crossbreds in specific community-based breeding programs.

Genomic prediction of milk-production traits and somatic cell score using single-step genomic best linear unbiased predictor with random regression test-day model in Thai dairy cattle

Cow genotypes are expected to improve the accuracy of genomic estimated breeding values (GEBV) for young bulls in relatively small populations such as Thai Holstein-Friesian crossbred dairy cattle in Thailand. The objective of this study was to investigate the effect of cow genotypes on the predictive ability and individual accuracies of GEBV for young dairy bulls in Thailand. Test-day data included milk yield (n = 170,666), milk component traits (fat yield, protein yield, total solids yield, fat percentage, protein percentage, and total solids percentage; n = 160,526), and somatic cell score (n = 82,378) from 23,201, 82,378, and 13,737 (for milk yield, milk component traits, and SCS, respectively) cows calving between 1993 and 2017, respectively. Pedigree information included 51,128; 48,834; and 32,743 animals for milk yield, milk component traits, and somatic cell score, respectively. Additionally, 876, 868, and 632 pedigreed animals (for milk yield, milk component traits, and SCS, respectively) were genotyped (152 bulls and 724 cows), respectively, using Illumina Bovine SNP50 BeadChip. We cut off the data in the last 6 yr, and the validation animals were defined as genotyped bulls with no daughters in the truncated set. We calculated GEBV using a single-step random regression test-day model (SS-RR-TDM), in comparison with estimated breed value (EBV) based on the pedigree-based model used as the official method in Thailand (RR-TDM). Individual accuracies of GEBV were obtained by inverting the coefficient matrix of the mixed model equations, whereas validation accuracies were measured by the Pearson correlation between deregressed EBV from the full data set and (G)EBV predicted with the reduced data set. When only bull genotypes were used, on average, SS-RR-TDM increased individual accuracies by 0.22 and validation accuracies by 0.07, compared with RR-TDM. With cow genotypes, the additional increase was 0.02 for individual accuracies and 0.06 for validation accuracies. The inflation of GEBV tended to be reduced using cow genotypes. Genomic evaluation by SS-RR-TDM is feasible to select young bulls for the longitudinal traits in Thai dairy cattle, and the accuracy of selection is expected to be increased with more genotypes. Genomic selection using the SS-RR-TDM should be implemented in the routine genetic evaluation of the Thai dairy cattle population. The genetic evaluation should consider including genotypes of both sires and cows.

Genome-wide association study of trypanosome prevalence and morphometric traits in purebred and crossbred Baoulé cattle of Burkina Faso.

In this study, single-SNP GWAS analyses were conducted to find regions affecting tolerance against trypanosomosis and morphometrics traits in purebred and crossbred Baoulé cattle of Burkina Faso. The trypanosomosis status (positive and negative) and a wide set of morphological traits were recorded for purebred Baoulé and crossbred Zebu x Baoulé cattle, and genotyped with the Illumina Bovine SNP50 BeadChip. After quality control, 36,203 SNPs and 619 animals including 343 purebred Baoulé and 279 crossbreds were used for the GWAS analyses. Several important genes were found that can influence morphological parameters. Although there were no genes identified with a reported strong connection to size traits, many of them were previously identified in various growth-related studies. A re-occurring theme for the genes residing in the regions identified by the most significant SNPs was pleiotropic effect on growth of the body and the cardiovascular system. Regarding trypanosomosis tolerance, two potentially important regions were identified in purebred Baoulé on chromosomes 16 and 24, containing the CFH, CRBN, TRNT1 and, IL5RA genes, and one additional genomic region in Baoulé, x Zebu crossbreds on chromosome 5, containing MGAT4C and NTS. Almost all of these regions and genes were previously related to the trait of interest, while the CRBN gene was to our knowledge presented in the context of trypanosomiasis tolerance for the first time.

The evaluation of genomic diversity and selection signals in the autochthonous Slovak Spotted cattle

The aim of this study was to evaluate the effective population size based on linkage disequilibrium and the trend of inbreeding derived from runs of homozygosity (ROH) in the Slovak Spotted cattle. The ROH segments longer than 4 Mb were then analysed to identify selection signals. Eighty-five individuals were genotyped using the ICBF International Dairy and Beef chip (dams of sires) and Illumina BovineSNP50 BeadChip (sires). The ROH segments &amp;gt; 1 Mb occurred most often in the autosomal genome with an average number of 16.75 ± 7.23. The ROH segments &amp;gt; 16 Mb covering 0.41% of the genome pointed to the long-term effort of breeders to reduce inbreeding in the population of Slovak Spotted cattle. However, the average observed heterozygosity indicated a decrease in overall diversity in the current population. The decrease of heterozygosity per generation also confirmed the estimates of historical and recent effective population size (a decrease of 6.88 animals per generation). The predicted current effective population size was 58 animals. Twenty-one regions across 12 different autosomes were fixed due to the high selection pressure. Within these genomic regions were identified various genes associated with reproduction (SLC9C1, PTPN12), milk production (IGF1, ABCG2), beef production (IFRD1, PTPN4), developmental processes (FMNL2, GLI2), immune system (CD96, CSK) and coat colour (KIT). These selection signals detected in the genome of Slovak Spotted cattle confirm the constant effort of breeders to preserve the dual-purpose nature of this breed.

Admixture study of Ongole grade cattle based on genome-wide SNP data

We present population structure analysis of two differed Ongole grade cattle strains in Indonesia i.e., common Ongole grade (PO) and Kebumen Ongole grade (PO Kebumen). The aim of this study was to identify the genomic characteristic of both PO and PO Kebumen cattle strains. In this study, genotyping method of 15 PO and 25 PO Kebumen was carried out using an Illumina BovineSNP50 Bead Chip. In order to deeper analyses, we used additional 50K SNP data of 20 PO, 20 Nellore, 20 Brahman, 20 Simmental, and 20 Limousin that freely available in the data repositories. An estimation of the genetic population study was carried out using following approaches: pairwise fixation indices, heterozygosity and Nei’s standard genetic distance, and ancestral based admixture. These analyses revealed a B. taurus influence in PO but none in PO Kebumen. Furthermore, we also identified the close admixture of PO Kebumen to Nellore. Since Nellore was originated from Ongole cattle, we presume the PO Kebumen is the maintained Pure Ongole Breed in Indonesia.

Structural equation modeling for unraveling the multivariate genomic architecture of milk proteins in dairy cattle

The aims of this study were to investigate potential functional relationships among milk protein fractions in dairy cattle and to carry out a structural equation model (SEM) GWAS to provide a decomposition of total SNP effects into direct effects and effects mediated by traits that are upstream in a phenotypic network. To achieve these aims, we first fitted a mixed Bayesian multitrait genomic model to infer the genomic correlations among 6 milk nitrogen fractions [4 caseins (CN), namely κ-, β-, αS1-, and αS2-CN, and 2 whey proteins, namely β-lactoglobulin (β-LG) and α-lactalbumin (α-LA)], in a population of 989 Italian Brown Swiss cows. Animals were genotyped with the Illumina BovineSNP50 Bead Chip v.2 (Illumina Inc.). A Bayesian network approach using the max-min hill-climbing (MMHC) algorithm was implemented to model the dependencies or independence among traits. Strong and negative genomic correlations were found between β-CN and αS1-CN (-0.706) and between β-CN and κ-CN (-0.735). The application of the MMHC algorithm revealed that κ-CN and β-CN seemed to directly or indirectly influence all other milk protein fractions. By integrating multitrait model GWAS and SEM-GWAS, we identified a total of 127 significant SNP for κ-CN, 89 SNP for β-CN, 30 SNP for αS1-CN, and 14 SNP for αS2-CN (mostly shared among CN and located on Bos taurus autosome 6) and 15 SNP for β-LG (mostly located on Bos taurus autosome 11), whereas no SNP passed the significance threshold for α-LA. For the significant SNP, we assessed and quantified the contribution of direct and indirect paths to total marker effect. Pathway analyses confirmed that common regulatory mechanisms (e.g., energy metabolism and hormonal and neural signals) are involved in the control of milk protein synthesis and metabolism. The information acquired might be leveraged for setting up optimal management and selection strategies aimed at improving milk quality and technological characteristics in dairy cattle.

SNP panels for the estimation of dairy breed proportion and parentage assignment in African crossbred dairy cattle

BackgroundUnderstanding the relationship between genetic admixture and phenotypic performance is crucial for the optimization of crossbreeding programs. The use of small sets of informative ancestry markers can be a cost-effective option for the estimation of breed composition and for parentage assignment in situations where pedigree recording is difficult. The objectives of this study were to develop small single nucleotide polymorphism (SNP) panels that can accurately estimate the total dairy proportion and assign parentage in both West and East African crossbred dairy cows.MethodsMedium- and high-density SNP genotype data (Illumina BovineSNP50 and BovineHD Beadchip) for 4231 animals sampled from African crossbreds, African Bos taurus, European Bos taurus, Bos indicus, and African indigenous populations were used. For estimating breed composition, the absolute differences in allele frequency were calculated between pure ancestral breeds to identify SNPs with the highest discriminating power, and different combinations of SNPs weighted by ancestral origin were tested against estimates based on all available SNPs. For parentage assignment, informative SNPs were selected based on the highest minor allele frequency (MAF) in African crossbred populations assuming two Scenarios: (1) parents were selected among all the animals with known genotypes, and (2) parents were selected only among the animals known to be a parent of at least one progeny.ResultsFor the medium-density genotype data, SNPs selected for the largest differences in allele frequency between West African indigenous and European Bos taurus breeds performed best for most African crossbred populations and achieved a prediction accuracy (r2) for breed composition of 0.926 to 0.961 with 200 SNPs. For the high-density dataset, a panel with 70% of the SNPs selected on their largest difference in allele frequency between African and European Bos taurus performed best or very near best across all crossbred populations with r2 ranging from 0.978 to 0.984 with 200 SNPs. In all African crossbred populations, unambiguous parentage assignment was possible with ≥ 300 SNPs for the majority of the panels for Scenario 1 and ≥ 200 SNPs for Scenario 2.ConclusionsThe identified low-cost SNP assays could overcome incomplete or inaccurate pedigree records in African smallholder systems and allow effective breeding decisions to produce progeny of desired breed composition.

Short communication: Genome wide association study for gastrointestinal nematodes resistance in Bos taurus x Bos indicus crossbred cattle

Gastrointestinal nematodes (GIN) parasitism is a very important problem on livestock production, especially in cattle, where the infections are usually subclinical making difficult the diagnosis and aggravating the losses caused by these parasites. This study aimed to identify genomic regions associated with nematode fecal egg count (FEC) in a Gir x Holstein F2 experimental population and to identify candidate genes within the quantitative trait loci (QTL) regions. The FEC phenotypes were evaluated in F2 animals during dry and rainy seasons. Illumina BovineSNP50 BeadChip was used to genotype the animals for single-SNP genome wide association studies. Three significant SNPs on chromosome 15 were found to be associated with FEC. From the QTL regions containing the SNPs, one functional candidate gene was identified: the myogenic differentiation 1 (MYOD1) gene, which plays an important role in the myogenesis and muscle repair. Further studies are needed to refine the QTL region identified here and to pursue additional SNPs associated to FEC trait in the Gir x Holstein genome, as well as to deeply investigate and validate the effect of this functional candidate gene.