Association Between Polymorphisms in theSLC27A1Gene and Milk Production Traits in Chinese Holstein Cattle

Genomic insights into adaptation and inbreeding among Sub-Saharan African cattle from pastoral and agropastoral systems

Background

In Sub-Saharan Africa (SSA), cattle are crucial for socioeconomic stability yet face numerous environmental stressors such as diseases, parasites, and extreme heat within pastoral and agropastoral systems. Despite their significance, gaps remain in understanding how genetic diversity and inbreeding influence traits essential for disease resistance and environmental adaptability. This study examines the genomic adaptations that enable SSA cattle to thrive under these conditions and assesses the impact of inbreeding on such adaptive traits.

Methods

We analyzed genomic data from 113 cattle across four breeds-Kuri, N'dama, Zebu-Fulani, and Zebu-Bororo-employing Runs of Homozygosity (ROH) and Integrated Haplotype Score (iHS) analyses to identify historical and recent genetic selections. Strict quality controls using PLINK software ensured accurate genomic pattern identification related to adaptation and inbreeding.

Results

ROH analysis revealed islands with genes such as RSAD2, CMPK2, and NOTCH1, which are involved in immune response and cellular stress management, highlighting regions of historical selection that have likely provided adaptive advantages in overcoming environmental and pathogenic stresses. In contrast, iHS analysis identified genes under recent selection like HIPK1, involved in stress response regulation, and EPHA5, which plays a crucial role in neural development and synaptic functions, potentially equipping these breeds with novel adaptations to ongoing and emergent environmental challenges.

Conclusion

This research confirms that selective pressures inherent in pastoral and agropastoral systems profoundly influence the genetic structure of SSA cattle. By delineating the genetic bases of key adaptive traits, our study offers crucial insights for targeted breeding programs to enhance cattle resilience and productivity. These findings provide a valuable framework for future genetic improvements and conservation strategies, crucial for sustainable livestock management and economic stability in SSA.

Meta-analysis of mammary RNA seq datasets reveals the molecular understanding of bovine lactation biology

A better understanding of the biology of lactation, both in terms of gene expression and the identification of candidate genes for the production of milk and its components, is made possible by recent advances in RNA seq technology. The purpose of this study was to understand the synthesis of milk components and the molecular pathways involved, as well as to identify candidate genes for milk production traits within whole mammary transcriptomic datasets. We performed a meta-analysis of publically available RNA seq transcriptome datasets of mammary tissue/milk somatic cells. In total, 11 562 genes were commonly identified from all RNA seq based mammary gland transcriptomes. Functional annotation of commonly expressed genes revealed the molecular processes that contribute to the synthesis of fats, proteins, and lactose in mammary secretory cells and the molecular pathways responsible for milk synthesis. In addition, we identified several candidate genes responsible for milk production traits and constructed a gene regulatory network for RNA seq data. In conclusion, this study provides a basic understanding of the lactation biology of cows at the gene expression level.

Identification of meat from yak and cattle using SNP markers with integrated allele-specific polymerase chain reaction-capillary electrophoresis method

Correct species identification is necessary for meat product quality assurance. Genetic markers are useful tools to accurately determine the animal source of meat products. To better protect yak meat and its products, ten single nucleotide polymorphism (SNP) loci from bovine meat-related genes and one positive control primer set were selected to discriminate meat sourced from yak or cattle. A multiplex allele-specific polymerase chain reaction and capillary electrophoresis method was employed for SNP genotyping. The samples were identified as from yak or cattle based on the number of amplicons. Yak samples generally produced one to three amplicon peaks, and the cattle samples yielded five or more peaks in the electropherogram. This method could be useful to distinguish yak meat from cattle beef, and would protect consumers and yak meat producers.

A genome-wide association study suggests new candidate genes for milk production traits in Chinese Holstein cattle

A genome-wide association study (GWAS) was conducted on 15 milk production traits in Chinese Holstein. The experimental population consisted of 445 cattle, each genotyped by the GGP (GeneSeek genomic profiling)-BovineLD V3 SNP chip, which had 26 151 public SNPs in its manifest file. After data cleaning, 20 326 SNPs were retained for the GWAS. The phenotypes were estimated breeding values of traits, provided by a public dairy herd improvement program center that had been collected once a month for 3 years. Two statistical models, a fixed-effect linear regression model and a mixed-effect linear model, were used to estimate the association effects of SNPs on each of the phenotypes. Genome-wide significant and suggestive thresholds were set at 2.46E-06 and 4.95E-05 respectively. The two statistical models concurrently identified two genome-wide significant (P < 0.05) SNPs on milk production traits in this Chinese Holstein population. The positional candidate genes, which were the ones closest to these two identified SNPs, were EEF2K (eukaryotic elongation factor 2 kinase) and KLHL1 (kelch like family member 1). These two genes could serve as new candidate genes for milk yield and lactation persistence, yet their roles need to be verified in further function studies.

A genome scan for milk production traits in dairy goats reveals two new mutations in Dgat1 reducing milk fat content

The quantity of milk and milk fat and proteins are particularly important traits in dairy livestock. However, little is known about the regions of the genome that influence these traits in goats. We conducted a genome wide association study in French goats and identified 109 regions associated with dairy traits. For a major region on chromosome 14 closely associated with fat content, the Diacylglycerol O-Acyltransferase 1 (DGAT1) gene turned out to be a functional and positional candidate gene. The caprine reference sequence of this gene was completed and 29 polymorphisms were found in the gene sequence, including two novel exonic mutations: R251L and R396W, leading to substitutions in the protein sequence. The R251L mutation was found in the Saanen breed at a frequency of 3.5% and the R396W mutation both in the Saanen and Alpine breeds at a frequencies of 13% and 7% respectively. The R396W mutation explained 46% of the genetic variance of the trait, and the R251L mutation 6%. Both mutations were associated with a notable decrease in milk fat content. Their causality was then demonstrated by a functional test. These results provide new knowledge on the genetic basis of milk synthesis and will help improve the management of the French dairy goat breeding program.