Genome Wide Association Study of Beef Traits in Local Alpine Breed Reveals the Diversity of the Pathways Involved and the Role of Time Stratification

Genome-wide association studies for milk production traits in two autochthonous Aosta cattle breeds

Genome-wide association studies (GWASs) are used to identify quantitative trait loci for phenotypic traits of interest. The use of multilocus mixed models allows to correct for population stratification and account for long-range linkage disequilibrium. In this study, GWASs were conducted to identify the genetic bases of milk production (milk yield, protein and fat composition, and yield) in two autochthonous dual-purpose cattle breeds from the Aosta Valley. Using either the breeding values or the deregressed proofs, common significative single nucleotide polymorphisms have been identified for milk yield, protein percentage, and fat percentage. Two major quantitative trait loci regions have been identified on the chromosomes 5 and 14 for the fat percentage, harbouring the MGST1, CYHR1, VPS28, and CPSF1 genes. For the protein percentage, a candidate region has been identified on BTA 6; in this region, the CSN1S1, CSN2, HSTN, CSN3, and RUFY3 genes are annotated. Most of the identified genes have already been associated with milk composition in other studies on cosmopolitan and local cattle. These results show that the genes involved in milk composition quantitative traits in the Aosta cattle are common also in other cattle breeds and they can be further investigated with the use of whole genome sequencing data.

Genome-wide association analysis and transgenic characterization for amylose content regulating gene in tuber of Dioscorea zingiberensis

BACKGROUND

Amylose, a prebiotic found in yams is known to be beneficial for the gut microflora and is particularly advantageous for diabetic patients' diet. However, the genetic machinery underlying amylose production remains elusive. A comprehensive characterization of the genetic basis of amylose content in yam tubers is a prerequisite for accelerating the genetic engineering of yams with respect to amylose content variation.

RESULTS

To uncover the genetic variants underlying variation in amylose content, we evaluated amylose content in freshly harvested tubers from 150 accessions of Dioscorea zingibensis. With 30,000 high-quality single nucleotide polymorphisms (SNP), we performed a genome-wide association analysis (GWAS). The population structure analysis classified the D. zingiberensis accessions into three groups. A total of 115 significant loci were detected on four chromosomes. Of these, 112 significant SNPs (log10(p) = 5, q-value < 0.004) were clustered in a narrow window on the chromosome 6 (chr6). The peak SNP at the position 75,609,202 on chr6 could explain 63.15% of amylose variation in the population and fell into the first exon of the ADP-glucose pyrophosphorylase (AGPase) small subunit gene, causing a non-synonymous modification of the resulting protein sequence. Allele segregation analysis showed that accessions with the rare G allele had a higher amylose content than those harboring the common A allele. However, AGPase, a key enzyme precursor of amylose biosynthesis, was not expressed differentially between accessions with A and G alleles. Overexpression of the two variants of AGPase in Arabidopsis thaliana resulted in a significantly higher amylose content in lines transformed with the AGPase-G allele.

CONCLUSIONS

Overall, this study showed that a major genetic variant in AGPase probably enhances the enzyme activity leading to high amylose content in D. zingiberensis tuber. The results provide valuable insights for the development of amylose-enriched genotypes.

A review of the role of epigenetic studies for intramuscular fat deposition in beef cattle

Intramuscular fat (IMF) deposition profoundly influences meat quality and economic value in beef cattle production. Meanwhile, contemporary developments in epigenetics have opened new outlooks for understanding the molecular basics of IMF regulation, and it has become a key area of research for world scholars. Therefore, the aim of this paper was to provide insight and synthesis into the intricate relationship between epigenetic mechanisms and IMF deposition in beef cattle. The methodology involves a thorough analysis of existing literature, including pertinent books, academic journals, and online resources, to provide a comprehensive overview of the role of epigenetic studies in IMF deposition in beef cattle. This review summarizes the contemporary studies in epigenetic mechanisms in IMF regulation, high-resolution epigenomic mapping, single-cell epigenomics, multi-omics integration, epigenome editing approaches, longitudinal studies in cattle growth, environmental epigenetics, machine learning in epigenetics, ethical and regulatory considerations, and translation to industry practices from perspectives of IMF deposition in beef cattle. Moreover, this paper highlights DNA methylation, histone modifications, acetylation, phosphorylation, ubiquitylation, non-coding RNAs, DNA hydroxymethylation, epigenetic readers, writers, and erasers, chromatin immunoprecipitation followed by sequencing, whole genome bisulfite sequencing, epigenome-wide association studies, and their profound impact on the expression of crucial genes governing adipogenesis and lipid metabolism. Nutrition and stress also have significant influences on epigenetic modifications and IMF deposition. The key findings underscore the pivotal role of epigenetic studies in understanding and enhancing IMF deposition in beef cattle, with implications for precision livestock farming and ethical livestock management. In conclusion, this review highlights the crucial significance of epigenetic pathways and environmental factors in affecting IMF deposition in beef cattle, providing insightful information for improving the economics and meat quality of cattle production.

Genetic legacy and adaptive signatures: investigating the history, diversity, and selection signatures in Rendena cattle resilient to eighteenth century rinderpest epidemics

BACKGROUND

Rendena is a dual-purpose cattle breed, which is primarily found in the Italian Alps and the eastern areas of the Po valley, and recognized for its longevity, fertility, disease resistance and adaptability to steep Alpine pastures. It is categorized as 'vulnerable to extinction' with only 6057 registered animals in 2022, yet no comprehensive analyses of its molecular diversity have been performed to date. The aim of this study was to analyse the origin, genetic diversity, and genomic signatures of selection in Rendena cattle using data from samples collected in 2000 and 2018, and shed light on the breed's evolution and conservation needs.

RESULTS

Genetic analysis revealed that the Rendena breed shares genetic components with various Alpine and Po valley breeds, with a marked genetic proximity to the Original Braunvieh breed, reflecting historical restocking efforts across the region. The breed shows signatures of selection related to both milk and meat production, environmental adaptation and immune response, the latter being possibly the result of multiple rinderpest epidemics that swept across the Alps in the eighteenth century. An analysis of the Rendena cattle population spanning 18 years showed an increase in the mean level of inbreeding over time, which is confirmed by the mean number of runs of homozygosity per individual, which was larger in the 2018 sample.

CONCLUSIONS

The Rendena breed, while sharing a common origin with Brown Swiss, has developed distinct traits that enable it to thrive in the Alpine environment and make it highly valued by local farmers. Preserving these adaptive features is essential, not only for maintaining genetic diversity and enhancing the ability of this traditional animal husbandry to adapt to changing environments, but also for guaranteeing the resilience and sustainability of both this livestock system and the livelihoods within the Rendena valley.

Unraveling inbreeding patterns and selection signals in Alpine Grey cattle

Inbreeding plays a crucial role in livestock breeding, influencing genetic diversity and phenotypic traits. Genomic data have helped address limitations posed by incomplete pedigrees, providing deeper insights into breed genetic diversity. This study assesses inbreeding levels via pedigree and genomic approaches and analyzes old and recent inbreeding using runs of homozygosity (ROH), and selection signals in Alpine Grey cattle. Pedigree data from 165 575 individuals, analyzed with INBUPGF90 software, computed inbreeding coefficients. Genomic-based coefficients derived from PLINK v1.9. or DetectRUNS R package analyses of 1 180 individuals' genotypes. Common single nucleotide polymorphisms within ROH pinpointed genomic regions, aggregating into "ROH islands" indicative of selection pressure. Overlaps with USCS Genome Browser unveiled gene presence. Moderate correlations (0.20-0.54) existed between pedigree and genomic coefficients, with most genomic estimators having higher (>0.8) correlation values. Inbreeding averaged 0.04 in < 8 Mb ROH segments, and 0.03 in > 16 Mb segments; > 90% of ROHs were < 8 Mb, indicating ancient inbreeding prevalence. Recent inbreeding proved less detrimental than in cosmopolitan breeds. Two major ROH islands on chromosomes 6 and 7 harbored genes linked to immune response, disease resistance (PYURF, HERC3), and fertility (EIF4EBP3, SRA1). This study underscores the need for detailed inbreeding analyses to understand genetic characteristics and historical changes in local breeds like Alpine Grey cattle. Genomic insights, especially from ROH, facilitated overcoming pedigree limitations, illuminating breed genetic diversity. Our findings reveal ancient inbreeding's enduring genetic impact and ROH islands potential for selective sweeps, elucidating traits in Alpine Grey cattle.

Uncovering genetic parameters and environmental influences on fertility, milk production, and quality in autochthonous Reggiana cattle

Reggiana is a local cattle breed from northern Italy known for its rusticity and profitability, due to the production of branded Parmigiano Reggiano cheese. To ensure the persistence of such profitability in the long term, an adequate breeding program is required. To this aim, in the present study we estimate the genetic parameters of the main productive and reproductive traits, and we evaluate the effect of genotype by environment interaction (GxE) on these traits using 2 environmental covariates: (1) productivity and (2) temperature-humidity index (THI). Milk, fat, protein, and casein yield were considered as daily production traits, whereas protein, fat, casein percentage, casein index, and somatic cell score were considered as milk quality traits. Finally, reproductive traits such as the number of inseminations, days open, calving interval, and calving-to-first-insemination interval were evaluated. Reggiana cattle produce an average of 19 kg of milk per day with 3.7% fat and 3.4% protein content and have excellent fertility parameters. Compared with other breeds, they have slightly lower heritability for production and quality for production traits (e.g., 0.12 [0.09; 0.15] for milk yield), but similar heritability for fertility traits. Milk, protein, and fat daily yields are highly correlated but negatively correlated with the percentage of protein, fat, and casein, whereas fertility traits have an unfavorable genetic correlation with daily production traits. When considering productivity, a consistent amount of variability due to GxE was observed for all daily production traits, somatic cell count, and casein index. A modest amount of GxE was observed for fertility parameters, while the percentage of solid content showed almost no GxE effect. A similar situation occurred when considering the THI, but no GxE interaction was observed for reproduction traits. In conclusion, this study provides useful information for the implementation of accurate selection plans in this local breed, accounting for environmental plasticity measured through the consistent GxE interaction observed.

Genome-wide association study for body weight and feed consumption traits in Japanese quail using Bayesian approaches

The aim of this study was to perform a genome-wide association study (GWAS) based on Bayes A and Bayes B statistical methods to identify genomic loci and candidate genes associated with body weight gain, feed intake, and feed conversion ratio in Japanese quail. For this purpose, genomic data obtained from Illumina iSelect 4K quail SNP chip were utilized. After implementing various quality control steps, genotype data from a total of 875 birds for 2,015 SNP markers were used for subsequent analyses. The Bayesian analyses were performed using hibayes package in R (version 4.3.1) and Gibbs sampling algorithm. The results of the analyses showed that Bayes A accounted for 11.43, 11.65, and 11.39% of the phenotypic variance for body weight gain, feed intake, and feed conversion ratio, respectively, while the variance explained by Bayes B was 7.02, 8.61, and 6.48%, respectively. Therefore, in the current study, results obtained from Bayes A were used for further analyses. In order to perform the gene enrichment analysis and to identify the functional pathways and classes of genes that are over-represented in a large set of genes associated with each trait, all markers that accounted for more than 0.1% of the phenotypic variance for each trait were used. The results of this analysis revealed a total of 23, 38, and 14 SNP markers associated with body weight gain, feed intake, and feed conversion ratio in Japanese quail, respectively. The results of the gene enrichment analysis led to the identification of biological pathways (and candidate genes) related to lipid phosphorylation (TTC7A gene) and cell junction (FGFR4 and FLRT2 genes) associated with body weight gain, calcium signaling pathway (ADCY2 and CAMK1D genes) associated with feed intake, and glycerolipid metabolic process (LIPC gene), lipid metabolic process (ADGRF5 and ESR1 genes), and glutathione transferase (GSTK1 gene) associated with feed conversion ratio. Overall, the findings of this study can provide valuable insights into the genetic architecture of growth and feed consumption traits in Japanese quail.

Genetic correlations of direct and indirect genetic components of social dominance with fitness and morphology traits in cattle

BACKGROUND

Within the same species, individuals show marked variation in their social dominance. Studies on a handful of populations have indicated heritable genetic variation for this trait, which is determined by both the genetic background of the individual (direct genetic effect) and of its opponent (indirect genetic effect). However, the evolutionary consequences of selection for this trait are largely speculative, as it is not a usual target of selection in livestock populations. Moreover, studying social dominance presents the challenge of working with a phenotype with a mean value that cannot change in the population, as for every winner of an agonistic interaction there will necessarily be a loser. Thus, to investigate what could be the evolutionary response to selection for social dominance, it is necessary to focus on traits that might be correlated with it. This study investigated the genetic correlations of social dominance, both direct and indirect, with several morphology and fitness traits. We used a dataset of agonistic contests involving cattle (Bos taurus): during these contests, pairs of cows compete in ritualized interactions to assess social dominance. The outcomes of 37,996 dominance interactions performed by 8789 cows over 20 years were combined with individual data for fertility, mammary health, milk yield and morphology and analysed using bivariate animal models including indirect genetic effects.

RESULTS

We found that winning agonistic interactions has a positive genetic correlation with more developed frontal muscle mass, lower fertility, and poorer udder health. We also discovered that the trends of changes in the estimated breeding values of social dominance, udder health and more developed muscle mass were consistent with selection for social dominance in the population.

CONCLUSIONS

We present evidence that social dominance is genetically correlated with fitness traits, as well as empirical evidence of the possible evolutionary trade-offs between these traits. We show that it is feasible to estimate genetic correlations involving dyadic social traits.

Genome-Wide Association and Pathway Analysis of Carcass and Meat Quality Traits in Karachai Young Goats

Goats with diverse economic phenotypic traits play an important role in animal husbandry. However, the genetic mechanisms underlying complex phenotypic traits are unclear in goats. Genomic studies of variations provided a lens to identify functional genes. The work aimed to search for candidate genes related to body measurements and body weight of Karachai goats and develop an experimental PCR-RV test system for genotyping significant SNPs. Comparison of GWAS results for ages 4 and 8 months revealed 58 common SNPs for significant genotypes. 11 common SNPs were identified for body weight, 4 SNPs-for group of traits withers height, rump height, body length, 2 SNPs-for withers height and rump height, 1 SNP-for body length and chest depth. Structural annotation of genomic regions covering a window of ±0.20 Mb showed the presence of 288 genes; 52 of them had the described functions in accordance with gene ontology. The main molecular functions of proteins encoded by these genes are the regulation of transcription, cell proliferation, angiogenesis, body growth, fatty acid and lipid metabolism, nervous system development, and spermatogenesis. SNPs common to body weight and localized within a window of ±200 kb from the structural genes CRADD, HMGA2, MSRB3, FUT8, MAX, and RAB15 were selected to create a test system. The study of meat productivity after slaughter and chemical analysis of muscle tissue in Karachai goats at the age of 8 months of different genotypes according to the identified SNPs revealed that rs268269710 is the most promising for further research and use in breeding. The GG genotype is associated with a larger live weight of animals, a larger carcass yield, the content of the boneless part in it, and the ratio of protein and adipose tissue in meat preferred for dietary nutrition. These results will contribute to the genetic improvement of Karachai goats.

Genomic Regions and Candidate Genes Associated with Milk Production Traits in Holstein and Its Crossbred Cattle: A Review

Genome-wide association studies (GWAS) are a powerful tool for identifying genomic regions and causative genes associated with economically important traits in dairy cattle, particularly complex traits, such as milk production. This is possible due to advances in next-generation sequencing technology. This review summarized information on identified candidate genes and genomic regions associated with milk production traits in Holstein and its crossbreds from various regions of the world. Milk production traits are important in dairy cattle breeding programs because of their direct economic impact on the industry and their close relationship with nutritional requirements. GWAS has been used in a large number of studies to identify genomic regions and candidate genes associated with milk production traits in dairy cattle. Many genomic regions and candidate genes have already been identified in Holstein and its crossbreds. Genes and single nucleotide polymorphisms (SNPs) that significantly affect milk yield (MY) were found in all autosomal chromosomes except chromosomes 27 and 29. Half of the reported SNPs associated with fat yield and fat percentage were found on chromosome 14. However, a large number of significant SNPs for protein yield (PY) and protein percentage were found on chromosomes 1, 5, and 20. Approximately 155 SNPs with significant influence on multiple milk production traits have been identified. Several promising candidate genes, including diacylglycerol O-acyltransferase 1, plectin, Rho GTPase activating protein 39, protein phosphatase 1 regulatory subunit 16A, and sphingomyelin phosphodiesterase 5 were found to have pleiotropic effects on all five milk production traits. Thus, to improve milk production traits it is of practical relevance to focus on significant SNPs and pleiotropic genes frequently found to affect multiple milk production traits.

Improvement of Genomic Predictions in Small Breeds by Construction of Genomic Relationship Matrix Through Variable Selection

Genomic selection has been increasingly implemented in the animal breeding industry, and it is becoming a routine method in many livestock breeding contexts. However, its use is still limited in several small-population local breeds, which are, nonetheless, an important source of genetic variability of great economic value. A major roadblock for their genomic selection is accuracy when population size is limited: to improve breeding value accuracy, variable selection models that assume heterogenous variance have been proposed over the last few years. However, while these models might outperform traditional and genomic predictions in terms of accuracy, they also carry a proportional increase of breeding value bias and dispersion. These mutual increases are especially striking when genomic selection is performed with a low number of phenotypes and high shrinkage value—which is precisely the situation that happens with small local breeds. In our study, we tested several alternative methods to improve the accuracy of genomic selection in a small population. First, we investigated the impact of using only a subset of informative markers regarding prediction accuracy, bias, and dispersion. We used different algorithms to select them, such as recursive feature eliminations, penalized regression, and XGBoost. We compared our results with the predictions of pedigree-based BLUP, single-step genomic BLUP, and weighted single-step genomic BLUP in different simulated populations obtained by combining various parameters in terms of number of QTLs and effective population size. We also investigated these approaches on a real data set belonging to the small local Rendena breed. Our results show that the accuracy of GBLUP in small-sized populations increased when performed with SNPs selected via variable selection methods both in simulated and real data sets. In addition, the use of variable selection models—especially those using XGBoost—in our real data set did not impact bias and the dispersion of estimated breeding values. We have discussed possible explanations for our results and how our study can help estimate breeding values for future genomic selection in small breeds.