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Simple Summary: Evaluating population genetic background and genomic selection signatures can provide important insights into the uniqueness and the genetic relationship among breeds. In this study, we analyzed the genetic diversity, population structure, and phylogenetic relationships between Huaxi cattle and its ancestors. The results showed that Huaxi cattle has formed its own unique genetic structure features, which could be clearly distinguished from its ancestors and similar populations. Moreover, some genes associated with important economic traits, including growth and development, reproduction, milk quality, and immune response, were identified by scanning potentially selected genomic regions, which may play an essential role in the excellent environmental adaptability and growth performance of Huaxi cattle. Our study will contribute to the genetic evaluation and rational breeding strategy, and give an extensive reference for understanding the genetic basis of economically important traits in Huaxi cattle. Huaxi cattle, a specialized beef cattle breed in China, has the characteristics of fast growth, high slaughter rate, and net meat rate, good reproductive performance, strong stress resistance, and wide adaptability. In this study, we evaluated the genetic diversity, population structure, and genetic relationships of Huaxi cattle and its ancestor populations at the genome-wide level, as well as detecting the selection signatures of Huaxi cattle. Principal component analysis (PCA) and phylogenetic analysis revealed that Huaxi cattle were obviously separated from other cattle populations. The admixture analysis showed that Huaxi cattle has distinct genetic structures among all populations at K = 4. It can be concluded that Huaxi cattle has formed its own unique genetic features. Using integrated haplotype score (iHS) and composite likelihood ratio (CLR) methods, we identified 143 and 199 potentially selected genes in Huaxi cattle, respectively, among which nine selected genes (KCNK1, PDLIM5, CPXM2, CAPN14, MIR2285D, MYOF, PKDCC, FOXN3, and EHD3) related to ion binding, muscle growth and differentiation, and immunity were detected by both methods. Our study sheds light on the unique genetic feature and phylogenetic relationship of Huaxi cattle, provides a basis for the genetic mechanism analysis of important economic traits, and guides further intensive breeding improvement of Huaxi cattle. [ABSTRACT FROM AUTHOR]

With the advance of high-throughput genotyping technologies, it is possible to estimate the pattern of linkage disequilibrium (LD) and haplotype block structure at genome wide level in farm animals. Understanding LD characteristics and haplotype blocks can provide useful information to guide genome wide association study (GWAS) and genomic selection (GS). In this study, we investigated the LD pattern and haplotype block structure in two beef cattle populations (Chinese Simmental and Wagyu) using the BovineHD BeadChip. We found the average LD measured by r 2 in Chinese Wagyu was higher than that in Simmental. We observed LD decayed more slowly on the X chromosome than autosomes for both populations. The persistence of LD phase varied from 0.96 at a distance of <2.5 kb to 0.51 at a distance from 400 kb to 500 kb. The estimated ancestral effective population sizes ( N e ) in Chin e se Simmental and Wagyu 5 years ago were approximately 74 and 23, respectively. Moreover, we detected 50,475 (991.1 Mb, 69.3%) haplotype blocks shared by two populations, 18,440 (238.9 Mb, 16.7%) unique blocks in Chinese Simmental and 15,417 (199.8 Mb, 14%) in Wagyu. Our study revealed that the r 2 dropped below 0.2 at distances of 34 kb and 40 kb in Chinese Simmental and Wagyu, which indicated that the implementation of GS for both populations require at least 77,941 and 66,250 markers, respectively. The pattern of LD mirrored the slightly different selection histories for Chinese Simmental and Wagyu, and our result suggested the shared haplotype blocks may offer valuable insights for the implementation of genome wide association and genomic selection studies based on multi-population. [ABSTRACT FROM AUTHOR]

The Pingliang red cattle, an outstanding indigenous resource in China, possesses an exceptional breeding value attributed to its tender meat and superior marbling quality. Currently, research efforts have predominantly concentrated on exploring its maternal origin and conducting conventional phenotypic studies. However, there remains a lack of comprehensive understanding regarding its genetic basis. To address this gap, we conducted a thorough whole-genome analysis to investigate the population structure, phylogenetic relationships, and gene flows of this breed using genomic SNP chip data from 17 bovine breeds. The results demonstrate that Pingliang red cattle have evolved distinct genetic characteristics unique to this breed, clearly distinguishing it from other breeds. Based on the analysis of the population structure and phylogenetic tree, it can be classified as a hybrid lineage between Bos taurus and Bos indicus . Furthermore, Pingliang red cattle display a more prominent B. taurus pedigree in comparison with Jinnan, Qinchuan, Zaosheng, Nanyang, and Luxi cattle. Moreover, this study also revealed closer genetic proximity within the Chinese indigenous cattle breed, particularly Qinchuan cattle, which shares the longest identical by descent (IBD) fragment with Pingliang red cattle. Gene introgression analysis shows that Pingliang red cattle have undergone gene exchange with South Devon and Red Angus cattle from Europe. Admixture analysis revealed that the proportions of East Asian taurine and Chinese indicine in the ancestry of Pingliang red cattle are approximately 52.44% and 21.00%, respectively, while Eurasian taurine, European taurine, and Indian indicine account for approximately 17.55%, 7.27%, and 1.74%. Our findings unveil distinct genetic characteristics in Pingliang red cattle and attribute their origin to B. taurus and B. indicus ancestry, as well as contributions from Qinchuan cattle, South Devon, and Red Angus.

Background: Genomic regions with a high frequency of runs of homozygosity (ROH) are related to important traits in farm animals. We carried out a comprehensive analysis of ROH and evaluated their association with production traits using the BovineHD (770 K) SNP array in Chinese Simmental beef cattle., Results: We detected a total of 116,953 homozygous segments with 2.47Gb across the genome in the studied population. The average number of ROH per individual was 99.03 and the average length was 117.29 Mb. Notably, we detected 42 regions with a frequency of more than 0.2. We obtained 17 candidate genes related to body size, meat quality, and reproductive traits. Furthermore, using Fisher's exact test, we found 101 regions were associated with production traits by comparing high groups with low groups in terms of production traits. Of those, we identified several significant regions for production traits (P < 0.05) by association analysis, within which candidate genes including ECT2, GABRA4, and GABRB1 have been previously reported for those traits in beef cattle., Conclusions: Our study explored ROH patterns and their potential associations with production traits in beef cattle. These results may help to better understand the association between production traits and genome homozygosity and offer valuable insights into managing inbreeding by designing reasonable breeding programs in farm animals., (© 2021. The Author(s).)

Water holding capacity (WHC) is an important sensory attribute that greatly influences meat quality. However, the molecular mechanism that regulates the beef WHC remains to be elucidated. In this study, the longissimus dorsi (LD) muscles of 49 Chinese Simmental beef cattle were measured for meat quality traits and subjected to RNA sequencing. WHC had significant correlation with 35 kg water loss (r = - 0.99, p < 0.01) and IMF content (r = 0.31, p < 0.05), but not with SF (r = - 0.20, p = 0.18) and pH (r = 0.11, p = 0.44). Eight individuals with the highest WHC (H-WHC) and the lowest WHC (L-WHC) were selected for transcriptome analysis. A total of 865 genes were identified as differentially expressed genes (DEGs) between two groups, of which 633 genes were up-regulated and 232 genes were down-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment revealed that DEGs were significantly enriched in 15 GO terms and 96 pathways. Additionally, based on protein-protein interaction (PPI) network, animal QTL database (QTLdb), and relevant literature, the study not only confirmed seven genes (HSPA12A, HSPA13, PPARγ, MYL2, MYPN, TPI, and ATP2A1) influenced WHC in accordance with previous studies, but also identified ATP2B4, ACTN1, ITGAV, TGFBR1, THBS1, and TEK as the most promising novel candidate genes affecting the WHC. These findings could offer important insight for exploring the molecular mechanism underlying the WHC trait and facilitate the improvement of beef quality.

Genomic selection (GS) using the whole-genome molecular makers to predict genomic estimated breeding values (GEBVs) is revolutionizing the livestock and plant breeding. Seeking out novel strategies with higher prediction accuracy for GS has been the ultimate goal of breeders. With the rapid development of artificial intelligence, machine learning algorithms were applied to estimate the GEBVs increasingly. Although some machine learning methods have better performance in phenotype prediction, there is still considerable room for improvement. In this study, we applied an ensemble-learning algorithm, Adaboost.RT, which integrated support vector regression (SVR), kernel ridge regression (KRR) and random forest (RF), to predict genomic breeding values of three economic traits (carcass weight, live weight, and eye muscle area) in Chinese Simmental beef cattle. Predictive accuracy measured as the Pearson correlation between the corrected phenotypes and predicted GEBVs. Moreover, we compared the reliability of SVR, KRR, RF, Adaboost.RT and GBLUP methods. The result showed that machine learning methods outperformed GBLUP, and the average improvement of four machine learning methods over the GBLUP was 12.8%, 14.9%, 5.4% and 14.4%, respectively. Among the four machine learning methods, the reliability of Adaboost.RT was comparable to KRR with higher stability. We therefore believe that the Adaboost.RT algorithm is a reliable and efficient method for GS., (© 2020 Wiley-VCH GmbH.)

Genome-wide single nucleotide polymorphism (SNP) arrays can be used to explore homozygosity segments, where two haplotypes inherited from the parents are identical. In this study, we identified a total of 27,358 runs of homozygosity (ROH) with an average of 153 ROH events per animal in Chinese local cattle. The sizes of ROH events varied considerably ranging from 0.5 to 66 Mb, with an average length of 1.22 Mb. The highest average proportion of the genome covered by ROH (~11.54% of the cattle genome) was found in Nanda cattle (NDC) from South China, whereas the lowest average proportion (~3.1%) was observed in Yanhuang cattle (YHC). The average estimated F ROH ranged from 0.03 in YHC to 0.12 in NDC. For each of three ROH classes with different sizes (Small 0.5-1 Mb, Medium 1-5 Mb and Large >5 Mb), the numbers and total lengths of ROH per individual showed considerable differences across breeds. Moreover, we obtained 993 to 3603 ROH hotspots (which were defined where ROH frequency at a SNP within each breed exceeded the 1% threshold) among eight cattle breeds. Our results also revealed several candidate genes embedded with ROH hotspots which may be related to environmental conditions and local adaptation. In conclusion, we generated baselines for homozygosity patterns in diverse Chinese cattle breeds. Our results suggested that selection has, at least partially, played a role with other factors in shaping the genomic patterns of ROH in Chinese local cattle and might provide valuable insights for understanding the genetic basis of economic and adaptive traits.

Chinese Simmental beef cattle are the most economically important cattle breed in China. Estimated breeding values for growth, carcass, and meat quality traits are commonly used as selection criteria in animal breeding. The objective of this study was to evaluate the accuracy of alternative statistical methods for the estimation of genomic breeding values. Analyses of the accuracy of genomic best linear unbiased prediction (GBLUP), BayesB, and elastic net (EN) were performed with an Illumina BovineHD BeadChip on 1,217 animals by applying 5-fold cross-validation. Overall, the accuracies ranged from 0.17 to 0.296 for ten traits, and the heritability estimates ranged from 0.36 to 0.63. The EN (alpha = 0.001) model provided the most accurate prediction, which was also slightly higher (0.2-2%) than that of GBLUP for most traits, such as average daily weight gain (ADG) and carcass weight (CW). BayesB was less accurate for each trait than were EN (alpha = 0.001) and GBLUP. These findings indicate the importance of using an appropriate variable selection method for the genomic selection of traits and suggest the influence of the genetic architecture of the traits we analyzed., Competing Interests: The authors have declared that no competing interests exist.

Background: China exhibits a great diversity of ecosystems and abundant cattle resources, with nearly 30 million cattle from 53 indigenous breeds reared in specific geographic regions. To explore the genetic diversity and population structure of Chinese indigenous cattle, a population genetic analysis at both the individual and population levels was conducted and the admixture analysis was performed. We genotyped 572 samples from 20 Chinese indigenous cattle breeds using GeneSeek Genomic Profiler Bovine LD (GGP-LD, 30 K) and downloaded the published data of 77 samples from 4 worldwide commercial breeds genotyped with Illumina BovineSNP50 Beadchip (SNP50, 50 K)., Results: In principal component analysis (PCA) and neighbour-joining (NJ) tree analysis, samples of the same breeds were grouped together, leading to clear separation from other breeds. And Chinese indigenous cattle were clustered into two groups of southern and northern breeds, originated from Asian Bos indicus lineage and Eurasian Bos taurus lineage, respectively. In STRUCTURE K = 2, a clear transition occurred from the northern breeds to the southern breeds. Additionally, the northern breeds contained a smaller Eurasian taurine (62.5%) descent proportion than that reported previously (more than 90%). In STRUCTURE K = 3, a distinct descent was detected in the southern Chinese breeds, which could reflect a long-term selection history of Chinese indigenous cattle. The results from TreeMix and f3 statistic provided the evidence of an admixture history between southern breeds and northern breeds., Conclusions: Consistent with the observed geographical distributions, Chinese indigenous cattle were divided into two genetic clusters, northern indigenous cattle and southern indigenous cattle. Three improved breeds in the northern area also exhibited northern indigenous ancestry. We found that the breeds distributed in the northern China showed more southern lineage introgression than previously reported. Central-located populations appeared to the admixture between southern and northern lineages, and introgression events from European cattle were observed in Luxi Cattle, Qinchuan Cattle and Jinnan Cattle. The study revealed the population structures and levels of admixture pattern among Chinese indigenous cattle, shedding light on the origin and evolutionary history of these breeds.

Copy number variations (CNVs) are defined as deletions, insertions, and duplications between two individuals of a species. To investigate the diversity and population-genetic properties of CNVs and their diverse selection patterns, we performed a genome-wide CNV analysis using high density SNP array in Chinese native cattle. In this study, we detected a total of 13,225 CNV events and 3,356 CNV regions (CNVRs), overlapping with 1,522 annotated genes. Among them, approximately 71.43 Mb of novel CNVRs were detected in the Chinese cattle population for the first time, representing the unique genomic resources in cattle. A new V i statistic was proposed to estimate the region-specific divergence in CNVR for each group based on unbiased estimates of pairwise V ST . We obtained 12 and 62 candidate CNVRs at the top 1% and top 5% of genome-wide V i value thresholds for each of four groups (North, Northwest, Southwest and South). Moreover, we identified many lineage-differentiated CNV genes across four groups, which were associated with several important molecular functions and biological processes, including metabolic process, response to stimulus, immune system, and others. Our findings provide some insights into understanding lineage-differentiated CNVs under divergent selection in the Chinese native cattle.