Genomic adaptation to extreme climate conditions in beef cattle as a consequence of cross-breeding program.

BACKGROUND: Understanding the evolutionary forces related to climate changes that have been shaped genetic variation within species has long been a fundamental pursuit in biology. In this study, we generated whole-genome sequence (WGS) data from 65 cross-bred and 45 Mongolian cattle. Together with 62 whole-genome sequences from world-wide cattle populations, we estimated the genetic diversity and population genetic structure of cattle populations. In addition, we performed comparative population genomics analyses to explore the genetic basis underlying variation in the adaptation to cold climate and immune response in cross-bred cattle located in the cold region of China. To elucidate genomic signatures that underlie adaptation to cold climate, we performed three statistical measurements, fixation index (FST), log2 nucleotide diversity (θπ ratio) and cross population composite likelihood ratio (XP-CLR), and further investigated the results to identify genomic regions under selection for cold adaptation and immune response-related traits. RESULTS: By generating WGS data, we investigated the population genetic structure and phylogenetic relationship of studied cattle populations. The results revealed clustering of cattle groups in agreement with their geographic distribution. We detected noticeable genetic diversity between indigenous cattle ecotypes and commercial populations. Analysis of population structure demonstrated evidence of shared genetic ancestry between studied cross-bred population and both Red-Angus and Mongolian breeds. Among all studied cattle populations, the highest and lowest levels of linkage disequilibrium (LD) per Kb were detected in Holstein and Rashoki populations (ranged from ~ 0.54 to 0.73, respectively). Our search for potential genomic regions under selection in cross-bred cattle revealed several candidate genes related with immune response and cold shock protein on multiple chromosomes. We identified some adaptive introgression genes with greater than expected contributions from Mongolian ancestry into Molgolian x Red Angus composites such as TRPM8, NMUR1, PRKAA2, SMTNL2 and OXR1 that are involved in energy metabolism and metabolic homeostasis. In addition, we detected some candidate genes probably associated with immune response-related traits. CONCLUSION: The study identified candidate genes involved in responses to cold adaptation and immune response in cross-bred cattle, including new genes or gene pathways putatively involved in these adaptations. The identification of these genes may clarify the molecular basis underlying adaptation to extreme environmental climate and as such they might be used in cattle breeding programs to select more efficient breeds for cold climate regions.

Leveraging Functional Genomics for Understanding Beef Quality Complexities and Breeding Beef Cattle for Improved Meat Quality.

Consumer perception of beef is heavily influenced by overall meat quality, a critical factor in the cattle industry. Genomics has the potential to improve important beef quality traits and identify genetic markers and causal variants associated with these traits through genomic selection (GS) and genome-wide association studies (GWAS) approaches. Transcriptomics, proteomics, and metabolomics provide insights into underlying genetic mechanisms by identifying differentially expressed genes, proteins, and metabolic pathways linked to quality traits, complementing GWAS data. Leveraging these functional genomics techniques can optimize beef cattle breeding for enhanced quality traits to meet high-quality beef demand. This paper provides a comprehensive overview of the current state of applications of omics technologies in uncovering functional variants underlying beef quality complexities. By highlighting the latest findings from GWAS, GS, transcriptomics, proteomics, and metabolomics studies, this work seeks to serve as a valuable resource for fostering a deeper understanding of the complex relationships between genetics, gene expression, protein dynamics, and metabolic pathways in shaping beef quality.

Genomic heritability and correlation between carcass traits in Japanese Black cattle evaluated under different ceilings of relatedness among individuals.

The investigation of carcass traits to produce meat with high efficiency has been in focus on Japanese Black cattle since 1972. To implement a successful breeding program in carcass production, a comprehensive understanding of genetic characteristics and relationships between the traits is of paramount importance. In this study, genomic heritability and genomic correlation between carcass traits, including carcass weight (CW), rib eye area (REA), rib thickness (RT), subcutaneous fat thickness (SFT), yield rate (YI), and beef marbling score (BMS) were estimated using the genomic data of 9,850 Japanese Black cattle (4,142 heifers and 5,708 steers). In addition, we investigated the effect of genetic relatedness degree on the estimation of genetic parameters of carcass traits in sub-populations created based on different GRM-cutoff values. Genome-based restricted maximum likelihood (GREML) analysis was applied to estimate genetic parameters. Using all animal data, the heritability values for carcass traits were estimated as moderate to relatively high magnitude, ranging from 0.338 to 0.509 with standard errors, ranging from 0.014 to 0.015. The genetic correlations were obtained low and negative between SFT and REA [-0.198 (0.034)] and between SFT and BMS [-0.096 (0.033)] traits, and high and negative between SFT and YI [-0.634 (0.022)]. REA trait was genetically highly correlated with YI and BMS [0.811 (0.012) and 0.625 (0.022), respectively]. In sub-populations created based on the genetic-relatedness ceiling, the heritability estimates ranged from 0.212 (0.131) to 0.647 (0.066). At the genetic-relatedness ceiling of 0.15, the correlation values between most traits with low genomic correlation were overestimated while the correlations between the traits with relatively moderate to high correlations, ranging from 0.380 to 0.811, were underestimated. The values were steady at the ceilings of 0.30-0.95 (sample size of 5,443-9,850) for most of the highly correlated traits. The results demonstrated that there is considerable genetic variation and also favorable genomic correlations between carcass traits. Therefore, the genetic improvement for the traits can be simultaneously attained through genomic selection. In addition, we observed that depending on the degree of relationship between individuals and sample size, the genomic heritability and correlation estimates for carcass traits may be different.

Major effect of retinal short-chain dehydrogenase reductase (RDHE2) on bovine fat colour.

Beef with yellow fat is considered undesirable by consumers in most European and Asian markets. ß-Carotene is the major carotenoid deposited in the adipose tissue and milk fat of cattle (Bos taurus), which can result in the yellowness. The effects of retinal short-chain dehydrogenase reductase (RDHE2) and ß, ß-carotene 9',10-dioxygenase (BCO2) were considered jointly as major candidate genes for causing the yellow fat colour, based on their genomic locations in the fat colour quantitative trait loci (QTL) and their roles in the metabolism of ß-carotene. In a secondary pathway, BCO2 cleaves ß-carotene into retinoic acid, the most potent form of vitamin A. RDHE2 converts trans-retinol to trans-retinal, a less active form of vitamin A. We evaluated the effects of two amino acid variants of the RDHE2 gene (V6A and V33A) along with a mutation in the BCO2 gene that results in a stop codon (W80X) in seven cattle populations. The RDHE2 V6A genotype affected several fat colour traits but the size of the effect varied in the populations studied. The genotype effect of the RDHE2 V33A variant was observed only in New Zealand samples of unknown breed. In general, the individual effects of RDHE2 V6A and V33A SNPs genotypes were greater in the random New Zealand samples than in samples from pedigreed Jersey-Limousin backcross progeny, accounting for 8-17 % of the variance in one population. Epistasis between the BCO2 W80X and RDHE2 variants was observed, and in some populations this explained more of the variation than the effects of the individual RDHE2 variants.

Gene network analysis to determine the effect of hypoxia-associated genes on brain damages and tumorigenesis using an avian model.

BACKGROUND: Hypoxia refers to the condition of low oxygen pressure in the atmosphere and characterization of response to hypoxia as a biological complex puzzle, is challenging. Previously, we carried out a comparative genomic study by whole genome resequencing of highland and lowland Iranian native chickens to identify genomic variants associated with hypoxia conditions. Based on our previous findings, we used chicken as a model and the identified hypoxia-associated genes were converted to human's orthologs genes to construct the informative gene network. The main goal of this study was to visualize the features of diseases due to hypoxia-associated genes by gene network analysis. RESULTS: It was found that hypoxia-associated genes contained several gene networks of disorders such as Parkinson, Alzheimer, cardiomyopathy, drug toxicity, and cancers. We found that biological pathways are involved in mitochondrion dysfunctions including peroxynitrous acid production denoted in brain injuries. Lewy body and neuromelanin were reported as key symptoms in Parkinson disease. Furthermore, calmodulin, and amyloid precursor protein were detected as leader proteins in Alzheimer's diseases. Dexamethasone was reported as the candidate toxic drug under the hypoxia condition that implicates diabetes, osteoporosis, and neurotoxicity. Our results suggested DNA damages caused by the high doses of UV radiation in high-altitude conditions, were associated with breast cancer, ovarian cancer, and colorectal cancer. CONCLUSIONS: Our results showed that hypoxia-associated genes were enriched in several gene networks of disorders including Parkinson, Alzheimer, cardiomyopathy, drug toxicity, and different types of cancers. Furthermore, we suggested, UV radiation and low oxygen conditions in high-altitude regions may be responsible for the variety of human diseases.