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Vietnamese smallholder dairy cows (VDC) are the result of crossbreeding between different zebu (ZEB) and taurine dairy breeds through many undefined generations. Thus, the predominant breed composition of VDC is currently unknown. This study aimed to evaluate the level of genetic diversity and breed composition of VDC. The SNP data of 344 animals from 32 farms located across four dairy regions of Vietnam were collected and merged with genomic reference data, which included three ZEB breeds: Red Sindhi, Sahiwal and Brahman, three taurine breeds: Holstein (HOL), Jersey (JER) and Brown Swiss (BSW), and a composite breed: Chinese Yellow cattle. Diversity and admixture analyses were applied to the merged data set. The VDC were not excessively inbred, as indicated by very low inbreeding coefficients (Wright's FIS ranged from −0.017 to 0.003). The genetic fractions in the test herds suggested that the VDC are primarily composed of HOL (85.0%); however, JER (6.0%), BSW 5.3%) and ZEB (4.5%) had also contributed. Furthermore, major genotype groupings in the test herds were pure HOL (48%), B3:15/16HOL_1/16ZEB (22%) and B2:7/8HOL_1/8ZEB (12%). The genetic makeup of the VDC is mainly components of various dairy breeds but also has a small percentage of ZEB; thus, the VDC could be a good genetic base for selecting high milk‐producing cows with some degree of adaptation to tropical conditions. [ABSTRACT FROM AUTHOR]

ABSTRACT Genomic selection (GS) and genome‐wide association studies (GWAS) have not been investigated in Vietnamese dairy cattle, even for basic milk production traits, largely due to the scarcity of individual phenotype recording in smallholder dairy farms (SDFs). This study aimed to estimate heritability (h2) and test the applicability of GS and GWAS for milk production, body conformation and novel heat tolerance traits using single test day phenotypic data. Thirty‐two SDFs located in either the north (a lowland vs. a highland) or the south (a lowland vs. a highland) of Vietnam were each visited for an afternoon and the next morning to collect phenotype data of all lactating cows (n = 345). Tail hair from each cow was sampled for subsequent genotyping with a 50K SNP chip at that same visit. Milk production traits (single‐test day) were milk yield (MILK, kg/cow/day), energy corrected milk yield adjusted for body weight (ECMbw, kg/100 kg BW/day), fat (mFA, %), protein (mPR, %) and dry matter (mDM, %). Conformation traits were body weight (BW, kg) and body condition score (BCS, 1 = thin to 5 = obese). Heat tolerance traits were panting score (PS, 0 = normal to 4.5 = extremely heat‐stressed) and infrared temperatures (IRTs, °C) at 11 areas on the external body surface of the cow (inner vulval lip, outer vulval surface, inner tail base surface, ocular area, muzzle, armpit area, paralumbar fossa area, fore udder, rear udder, forehoof and hind hoof), assessed by an Infrared Camera. Univariate linear mixed models and a 10‐fold cross‐validation approach were applied for GS. Univariate single SNP mixed linear models were applied for the GWAS. Estimated h2 (using the genotype information to build relationships among animals) were moderate (0.20–0.37) for ECMbw, mFA, mPR, mRE, BW, BCS and IRT at rear udder; low (0.08–0.19) for PS and other IRTs; and very low (≤ 0.07) for MILK, ECM and mDM. Accuracy of genomic estimated breeding values (GEBVs) was low (≤ 0.12) for MILK, ECM, mDM and IRT at hind hoof; and moderate to high (0.32–0.46) for all other traits. The most significant regions on chromosomes (BTA) associated with milk production traits were 0.47–1.18 Mb on BTA14. Moderate to high h2 and moderate accuracies of GEBVs for mFA, mPR, ECMbw, BCS, BW, PS and IRTs at rear udder and outer vulval surface suggested that GS using single test day phenotypic data could be applied for these traits. However, a greater sample size is required to decrease the bias of GEBVs by GS and increase the power of detecting significant quantitative trait loci (QTLs) by GWAS. [ABSTRACT FROM AUTHOR]

Many breeds of modern cattle are naturally horned, and for sound husbandry management reasons the calves frequently undergo procedures to physically remove the horns by disbudding or dehorning. These procedures are however a welfare concern. Selective breeding for polledness - absence of horns - has been effective in some cattle breeds but not in others ( Bos indicus genotypes) due in part to the complex genetics of horn phenotype. To address this problem different approaches to genetic testing which provide accurate early-in-life prediction of horn phenotype have been evaluated, initially using microsatellites (MSAT) and more recently single nucleotide polymorphism (SNP). A direct gene test is not effective given the genetic heterogeneity and large-sized sequence variants associated with polledness in different breeds. The current study investigated 39,943 animals of multiple breeds to assess the accuracy of available poll testing assays. While the standard SNP-based test was an improvement on the earlier MSAT haplotyping method, 1999 (9.69%) out of 20,636 animals tested with this SNP-based assay did not predict a genotype, most commonly associated with the Indicus-influenced breeds. The current study has developed an optimized poll gene test that resolved the vast majority of these 1999 unresolved animals, while the predicted genotypes of those previously resolved remained unchanged. Hence the optimized poll test successfully predicted a genotype in 99.96% of samples assessed. We demonstrated that a robust set of 5 SNPs can effectively determine P C and P F alleles and eliminate the ambiguous and undetermined results of poll gene testing previously identified as an issue in cattle., (Copyright © 2020 Randhawa et al.)

Understanding the evolution and molecular architecture of complex traits is important in domestic animals. Due to phenotypic selection, genomic regions develop unique patterns of genetic diversity called signatures of selection, which are challenging to detect, especially for complex polygenic traits. In this study, we applied the composite selection signals (CSS) method to investigate evidence of positive selection in a complex polygenic trait by examining stature in phenotypically diverse cattle comprising 47 European and 8 African Bos taurus breeds, utilizing a panel of 38,033 SNPs genotyped on 1106 animals. CSS were computed for phenotypic contrasts between multibreed cohorts of cattle by classifying the breeds according to their documented wither height to detect the candidate regions under selection. Using the CSS method, clusters of signatures of selection were detected at 26 regions (9 in European and 17 in African cohorts) on 13 bovine autosomes. Using comparative mapping information on human height, 30 candidate genes mapped at 12 selection regions (on 8 autosomes) could be linked to bovine stature diversity. Of these 12 candidate gene regions, three contained known genes (i.e., NCAPG-LCORL, FBP2-PTCH1, and PLAG1-CHCHD7) related to bovine stature, and nine were not previously described in cattle (five in European and four in African cohorts). Overall, this study demonstrates the utility of CSS coupled with strategies of combining multibreed datasets in the identification and discovery of genomic regions underlying complex traits. Characterization of multiple signatures of selection and their underlying candidate genes will elucidate the polygenic nature of stature across cattle breeds., (Copyright © 2015 Randhawa et al.)