IGF-I and GH Genes polymorphism and their association with milk yields, composition and reproductive performance in Holstein-Friesian dairy cattle.

BACKGROUND: The insulin-like growth factor (IGF-I) and growth hormone (GH) genes have been identified as major regulators of milk yield and composition, and reproductive performance in cattle. Genetic variations/polymorphism in these genes have been found to influence milk production, yield and quality. This investigation aimed to explore the association between IGF-I and GH polymorphisms and milk yield and composition, and reproductive performance in a herd consisting of 1000 Holstein-Friesian (HF) dairy cattle from El-Alamia farm. The experimental animals were 76 ± 7.25 months in age, with an average live weight of 750 ± 50.49 kg, and raised under the same conditions of feeding and weather. The studied animals were divided into three categories; high producers (n = 280), medium producers (n = 318) and low producers (n = 402). RESULTS: The digestion of 249 bp for IGF-I-SnaBI using the Restriction-fragment-length-polymorphism (RFLP) technique yielded two alleles; T (0.59) and C (0.41) and three genotypes; TT (0.52), TC (0.39) and CC (0.09) and this agrees with the results of DNA/gene sequencing technique. The sequencing analysis of the IGF-I gene revealed polymorphism in position 472 (C > T). Nucleotide sequencing of the amplified fragment of the IGF-I gene of different genotypes was done and submitted to the NCBI GenBank with Accession no. MH156812.1 and MH156811.1. While the digestion of 432 bp for GH-AluI using the RFLP technique yielded two alleles; A (0.81) and G (0.19) and two genotypes; AA (0.77) and AG (0.23) and this agrees with the results of DNA/gene sequencing technique. The sequencing analysis of the GH gene revealed polymorphism in the position 1758 C > G and in turn led to changes in amino acid sequence as Alanine for (A) compared to Glycine for (G). Nucleotide sequencing of the amplified fragment of the GH gene was done and submitted to the NCBI GenBank with Accession no. MH156810.1. The results of this study demonstrate the effects of variants of the GH-IGF-I somatotrophic axis on milk production and composition traits in commercial HF cattle. The greatest values of milk yield and reproductive performance were observed on IGF-I-SnaBI-TC and GH-AluI-AG genotypes. While the greatest % fat and % protein values were observed on IGF-I-SnaBI-CC and GH-AluI-AA genotyped individuals. CONCLUSION: The genetic variation of the studied genes can be utilized in selecting animals with superior milk yield, composition and reproductive performance in Holstein-Friesian Dairy Cattle under subtropical conditions.

Optimizing single-tube nested PCR for enhanced genotyping of single cells and in vitro produced bovine embryos.

Single-tube nested PCR (STnPCR) is a technique that improves nested PCR, reducing potential contamination and false-positive results, enhancing the amplification sensitivity. Despite being commonly used for the detection of microorganisms, STnPCR can be a valuable tool for bovine genotyping, encompassing essential targets as ROSA26 and TSPY, pivotal in the fields of animal reproduction, genetic improvement, and transgenic research. The objective of this study was to improve and innovate STnPCR for gene detection in cattle. We aimed to detect the ROSA26 and TSPY genes using low-concentration DNA samples, including single cells, small cell groups (one to five cells), in vitro-produced embryos, and bovine tissue samples. Moreover, we refined STnPCR for gene detection in up to single cells by conducting sensitivity testing with different concentration ratios of internal and external primers. Successful amplification of the ROSA26 and TSPY genes was achieved across all tested primer concentrations, even in single cells, with more consistent results observed at lower primer concentrations. Additionally, simultaneous gene amplification was achieved through STnPCR multiplexing, representing the first study of multiplex STnPCR in cattle. These outcomes not only confirm its effectiveness in detecting genetic markers for animal genetic improvement and transgenic elements but also pave the way for its widespread adoption in reproductive studies in bovines.

RNA-DNA differences in variant calls from cattle tissues result in erroneous eQTLs.

BACKGROUND: Association testing between molecular phenotypes and genomic variants can help to understand how genotype affects phenotype. RNA sequencing provides access to molecular phenotypes such as gene expression and alternative splicing while DNA sequencing or microarray genotyping are the prevailing options to obtain genomic variants. RESULTS: We genotype variants for 74 male Braunvieh cattle from both DNA (~ 13-fold coverage) and deep total RNA sequencing from testis, vas deferens, and epididymis tissue (~ 250 million reads per tissue). We show that RNA sequencing can be used to identify approximately 40% of variants (7-10 million) called from DNA sequencing, with over 80% precision. Within highly expressed coding regions, over 92% of expected variants were called with nearly 98% precision. Allele-specific expression and putative post-transcriptional modifications negatively impact variant genotyping accuracy from RNA sequencing and contribute to RNA-DNA differences. Variants called from RNA sequencing detect roughly 75% of eGenes identified using variants called from DNA sequencing, demonstrating a nearly 2-fold enrichment of eQTL variants. We observe a moderate-to-strong correlation in nominal association p-values (Spearman ρ2 ~ 0.6), although only 9% of eGenes have the same top associated variant. CONCLUSIONS: We find hundreds of thousands of RNA-DNA differences in variants called from RNA and DNA sequencing on the same individuals. We identify several highly significant eQTL when using RNA sequencing variant genotypes which are not found with DNA sequencing variant genotypes, suggesting that using RNA sequencing variant genotypes for association testing results in an increased number of false positives. Our findings demonstrate that caution must be exercised beyond filtering for variant quality or imputation accuracy when analysing or imputing variants called from RNA sequencing.

Effect of seven days heat stress on feed and water intake, milk characteristics, blood parameters, physiological indicators, and gene expression in Holstein dairy cows.

This study examined the effects of 7 days of heat stress on eight early lactating Holstein cows in climate-controlled chambers. The early lactating Holstein cows (42 ± 2 days in milk, 29.27 ± 0.38 kg/day milk yield, 1.21 ± 0.05 parity) were subjected to two 14-day periods, each consisting of 7 days of adaptation and 7 days of heat stress. Conditions were set to 22 °C and 50% humidity during adaptation, followed by heat stress periods with low-temperature, low-humidity (LTLH, 71 THI) and high-temperature, high-humidity (HTHH, 86 THI) treatments. Data from the last 7 days were analyzed using a mixed procedure in SAS. In the study, the HTHH group displayed marked physiological and biochemical changes on 14 days of heat stress exposure compared to the LTLH group. Firstly, the HTHH group's dry matter intake decreased by approximately 12% while their water intake increased by about 23%. Secondly, both milk yield and milk protein production in the HTHH group decreased by 10% and 20%, respectively. Thirdly, there was a reduction in white blood cells, hemoglobin, mean corpuscular hemoglobin, and platelets in the HTHH group, with concurrent increases in glucose, non-esterified fatty acids, and albumin concentrations. Additionally, the HTHH group exhibited elevated plasma concentrations of cortisol and haptoglobin. Moreover, the gene expression of heat shock protein 70 and heat shock protein 90 was significantly upregulated in the HTHH group's peripheral blood mononuclear cells. Lastly, key physiological indicators such as rectal temperature, heart rate, and skin temperature showed substantial elevations in the HTHH group. Considering the enormous negative effects observed in the analyzed blood metabolites, milk yield and compositions, and heat shock protein gene expression, early lactating Holstein cows were found to be more vulnerable to HTHH than LTLH over a 7 days exposure to heat stress.

Genotyping of Holstein Cows by SELL, MX1 and CXCR1 Gene Loci Associated With Mastitis Resistance.

Mastitis is a significant factor that decreases milk production in cows of different breeds in Kazakhstan. The objective of this study was to determine the genetic makeup of Holstein cows by analysing specific gene loci (SELL, MX1, CXCR1+291C>T and CXCR1+1093C>T) that are linked to resistance against mastitis. The goal was to identify cows with favourable genotypes that are less prone to udder diseases. At the SELL gene locus c.567T>C, all three genetic variants were identified in the control population with the respective frequencies: TT (0.20), CT (0.44), and CC (0.36). Genetic variation was also detected at the MX1 gene c.567T>C, CXCR1 c.+291C>T and CXCR1+1093C>T loci. Deviation from the expected Hardy-Weinberg equilibrium was observed for two gene loci, MX1 g.143182088 and CXCR1+1093C>T, with increased chi-square values of 10.6261 and 9.7137, respectively. The analysis of subclinical mastitis incidence indicates that cows carrying the heterozygous CT genotype at the L-selectin gene locus exhibit greater resistance to the disease. Animals carrying the CCCCCT genotype at the MX1 c.567T>C, CXCR1 c.+291C>T and CXCR1+1093C>T gene loci were discovered to have a significant likelihood of developing subclinical mastitis. This suggests that these genes could serve as potential indicators of susceptibility to the condition. The practical significance of this study lies in determining the frequency of genotypes linked to mammary gland morbidity in Holstein breeding farms in Kazakhstan.

Decoding epigenetic markers: implications of traits and genes through DNA methylation in resilience and susceptibility to mastitis in dairy cows.

Cattle farming faces challenges linked to intensive exploitation and climate change, requiring the reinforcement of animal resilience in response to these dynamic environments. Currently, genetic selection is used to enhance resilience by identifying animals resistant to specific diseases; however, certain diseases, such as mastitis, pose difficulties in genetic prediction. This study introduced the utilization of enzymatic methyl sequencing (EM-seq) of the blood genomic DNA from twelve dairy cows to identify DNA methylation biomarkers, with the aim of predicting resilience and susceptibility to mastitis. The analysis uncovered significant differences between cows resilient and susceptible to mastitis, with 196,275 differentially methylated cytosines (DMCs) and 1,227 Differentially Methylated Regions (DMRs). Key genes associated with the immune response and morphological traits, including ENOPH1, MYL10 and KIR2DL5A, were identified by our analysis. Quantitative trait loci (QTL) were also highlighted and the body weight trait was the most targeted by DMCs and DMRs. Based on our results, the risk of developing mastitis can potentially be estimated with as few as fifty methylation biomarkers, paving the way for early animal selection. This research sets the stage for improved animal health management and economic yields within the framework of agricultural sustainability through early selection based on the epigenetic status of animals.

Association analysis of HSP90AA1 polymorphism with thermotolerance in tropically adapted Indian crossbred cattle.

Raising cattle is a lucrative business that operates globally but is confronted by many obstacles, such as thermal stress, which results in substantial monetary losses. A vital role of heat shock proteins (HSPs) is to protect cells from cellular damage. HSP90 is a highly prevalent, extremely adaptable gene linked to physiological resilience in thermal stress. This study aimed to find genetic polymorphisms of the HSP90AA1 gene in Karan Fries cattle and explore their relationship to thermal tolerance and production traits. One SNP (g.3292 A > C) was found in the Intron 8 and three SNPs loci (g.4776 A > G, g.5218T > C and g.5224 A > C) were found in the exon 11 of 100 multiparous Karan Fries cattle. The association study demonstrated that the SNP1-g.3292 A > C was significantly (P < 0.01) linked to the variables respiratory rate (RR), heat tolerance coefficient (HTC) and total milk yield (TMY (kg)) attributes. There was no significant correlation identified between any of the other SNP sites (SNP2-g.4776 A > G; SNP3-g.5218T > C; SNP4-g.5224 A > C) with the heat tolerance and production attributes in Karan Fries cattle. Haploview 4.2 and SHEsis software programs were used to analyse pair linkage disequilibrium and construct haplotypes for HSP90AA1. Association studies indicated that the Hap3 (CATA) was beneficial for heat tolerance breeding in Karan Fries cattle. In conclusion, genetic polymorphisms and haplotypes in the HSP90AA1 were associated with thermal endurance attributes. This relationship can be utilized as a beneficial SNP or Hap marker for genetic heat resistance selection in cow breeding platforms.

Genome-wide association study for conformation traits in Ayrshire cattle.

The genetic improvement of cattle is able to provide the highest economic efficiency. Animals with best external features often have the highest indicators of productivity and nonspecific resistance. In order to identify single nucleotide polymorphism (SNP) markers and genes, potentially responsible for conformation traits of Ayrshire cattle, we conducted a genome-wide association study (GWAS). Blood samples were collected from 495 first-calf Ayrshire heifers. For all animals, a linear assessment was carried out, which consisted of 17 conformation traits and 13 exterior flaws. Our study revealed a total of 43 SNPs on chromosomes BTA1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 14, 16, 18, 19, 22, 25, 27, and 29 associated with conformation traits, four of which have met the significance threshold. Among these four significant SNPs, genes associated with exterior flaws such as tilted udder floor and weak loin and SNPs associated with weak back were identified. The markers and genes identified in the corresponding genomic regions are promising candidates for further investigation of the biological processes involved in cow exterior formation and function. The results obtained, including the MYO1B gene associated with weak loin, PEPD and ZFC3H1 genes related to tilted udder floor, and EDNRB gene associated with weak back can be effectively used as molecular markers in genomic selection programs.

Evaluation of genomic prediction considering non-additive genetic effects on fatty acid traits of Japanese Black cattle.

Genomic prediction was conducted using 2494 Japanese Black cattle from Hiroshima Prefecture and both single-nucleotide polymorphism information and phenotype data on monounsaturated fatty acid (MUFA) and oleic acid (C18:1) analyzed with gas chromatography. We compared the prediction accuracy for four models (A, additive genetic effects; AD, as for A with dominance genetic effects; ADR, as for AD with the runs of homozygosity (ROH) effects calculated by ROH-based relationship matrix; and ADF, as for AD with the ROH-based inbreeding coefficient of the linear regression). Bayesian methods were used to estimate variance components. The narrow-sense heritability estimates for MUFA and C18:1 were 0.52-0.53 and 0.57, respectively; the corresponding proportions of dominance genetic variance were 0.04-0.07 and 0.04-0.05, and the proportion of ROH variance was 0.02. The deviance information criterion values showed slight differences among the models, and the models provided similar prediction accuracy.

Genomic Reference Resource for African Cattle: Genome Sequences and High-Density Array Variants.

The diversity in genome resources is fundamental to designing genomic strategies for local breed improvement and utilisation. These resources also support gene discovery and enhance our understanding of the mechanisms of resilience with applications beyond local breeds. Here, we report the genome sequences of 555 cattle (208 of which comprise new data) and high-density (HD) array genotyping of 1,082 samples (537 new samples) from indigenous African cattle populations. The new sequences have an average genome coverage of ~30X, three times higher than the average (~10X) of the over 300 sequences already in the public domain. Following variant quality checks, we identified approximately 32.3 million sequence variants and 661,943 HD autosomal variants mapped to the Bos taurus reference genome (ARS-UCD1.2). The new datasets were generated as part of the Centre for Tropical Livestock Genetics and Health (CTLGH) Genomic Reference Resource for African Cattle (GRRFAC) initiative, which aspires to facilitate the generation of this livestock resource and hopes for its utilisation for complete indigenous breed characterisation and sustainable global livestock improvement.

Evaluating genomic inbreeding of two Chinese yak (Bos grunniens) populations.

BACKGROUND: Yaks are a vital livestock in the Qinghai-Tibetan Plateau area for providing food products, maintaining sustainable ecosystems, and promoting cultural heritage. Because of uncontrolled mating, it is impossible to estimate inbreeding level of yak populations using the pedigree-based approaches. With the aims to accurately evaluate inbreeding level of two Chinese yak populations (Maiwa and Jiulong), we obtained genome-wide single nucleotide polymorphisms (SNPs) by DNA sequencing and calculated five SNP-by-SNP estimators ([Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]), as well as two segment-based estimators of runs of homozygosity (ROH, [Formula: see text]) and homozygous-by-descent (HBD, [Formula: see text]). Functional implications were analyzed for the positional candidate genes located within the related genomic regions. RESULTS: A total of 151,675 and 190,955 high-quality SNPs were obtained from 71 Maiwa and 30 Jiulong yaks, respectively. Jiulong had greater genetic diversity than Maiwa in terms of allele frequency and nucleotide diversity. The two populations could be genetically distinguished by principal component analysis, with the mean differentiation index (Fst) of 0.0054. The greater genomic inbreeding levels of Maiwa yaks were consistently supported by all five SNP-by-SNP estimators. Based on simple proportion of homozygous SNPs ([Formula: see text]), a lower inbreeding level was indicated by three successfully sequenced old leather samples that may represent historical Maiwa yaks about five generations ago. There were 3304 ROH detected among all samples, with mean and median length of 1.97 Mb and 1.0 Mb, respectively. A total of 94 HBD segments were found among all samples, whereas 92 of them belonged to the shortest class with the mean length of 10.9 Kb. Based on the estimates of [Formula: see text] and [Formula: see text], however, there was no difference in inbreeding level between Maiwa and Jiulong yaks. Within the genomic regions with the significant Fst or enriched by ROH, we found several candidate genes and pathways that have been reported to be related to diverse production traits in farm animals. CONCLUSIONS: We successfully evaluated the genomic inbreeding level of two Chinese yak populations. Although different estimators resulted in inconsistent conclusions on their genomic inbreeding levels, our results may be helpful to implement the genetic conservation and utilization programs for the two yak populations.

Detection and evaluation of parameters influencing the identification of heterozygous-enriched regions in Holstein cattle based on SNP chip or whole-genome sequence data.

BACKGROUND: A heterozygous-enriched region (HER) is a genomic region with high variability generated by factors such as balancing selection, introgression, and admixture processes. In this study, we evaluated the genomic background of HERs and the impact of different parameters (i.e., minimum number of SNPs in a HER, maximum distance between two consecutive SNPs, minimum length of a HER, maximum number of homozygous allowed in a HER) and scenarios [i.e., different SNP panel densities and whole-genome sequence (WGS)] on the detection of HERs. We also compared HERs characterized in Holstein cattle with those identified in Angus, Jersey, and Norwegian Red cattle using WGS data. RESULTS: The parameters used for the identification of HERs significantly impact their detection. The maximum distance between two consecutive SNPs did not impact HERs detection as the same average of HERs (269.31 ± 787.00) was observed across scenarios. However, the minimum number of markers, maximum homozygous markers allowed inside a HER, and the minimum length size impacted HERs detection. For the minimum length size, the 10 Kb scenario showed the highest average number of HERs (1,364.69 ± 1,483.64). The number of HERs decreased as the minimum number of markers increased (621.31 ± 1,271.83 to 6.08 ± 21.94), and an opposite pattern was observed for the maximum homozygous markers allowed inside a HER (54.47 ± 195.51 to 494.89 ± 1,169.35). Forty-five HER islands located in 23 chromosomes with high Tajima's D values and differential among the observed and estimated heterozygosity were detected in all evaluated scenarios, indicating their ability to potentially detect regions under balancing selection. In total, 3,440 markers and 28 genes previously related to fertility (e.g., TP63, ZSCAN23, NEK5, ARHGAP44), immunity (e.g., TP63, IGC, ARHGAP44), residual feed intake (e.g., MAYO9A), stress sensitivity (e.g., SERPINA6), and milk fat percentage (e.g., NOL4) were identified. When comparing HER islands among breeds, there were substantial overlaps between Holstein with Angus (95.3%), Jersey (94.3%), and Norwegian Red cattle (97.1%), indicating conserved HER across taurine breeds. CONCLUSIONS: The detection of HERs varied according to the parameters used, but some HERs were consistently identified across all scenarios. Heterozygous genotypes observed across generations and breeds appear to be conserved in HERs. The results presented could serve as a guide for defining HERs detection parameters and further investigating their biological roles in future studies.

Genetic Markers Related to Meat Quality Properties in Fattened HF and HF x Charolaise Steers.

This study involved 45 Holstein and 60 Holstein-Charolaise steers, tailored with specific diets according to breed and rearing systems. DNA genotyping was conducted for DGAT1, LEP, SCD1, SREBF1, and TG genes to investigate their impact on carcass conformation traits, beef quality traits, and sensory quality traits. The results showed associations between the genetic variants and the analyzed traits. Specifically, DGAT1 was found to affect drip loss, meat brightness, and color saturation. The TG gene was associated with marbling and meat color. LEP influenced trim fat and pH levels, while SCD1 was linked to metabolic energy live weight gains, and pH levels. SREBF1 was related to fatness.

Genome-Wide Identification and Evolutionary and Mutational Analysis of the Bos taurus Pax Gene Family.

Bos taurus is known for its tolerance of coarse grains, adaptability, high temperature, humidity, and disease resistance. Primarily, cattle are raised for their meat and milk, and pinpointing genes associated with traits relevant to meat production can enhance their overall productivity. The aim of this study was to identify the genome, analyze the evolution, and explore the function of the Pax gene family in B. taurus to provide a new molecular target for breeding in meat-quality-trait cattle. In this study, 44 Pax genes were identified from the genome database of five species using bioinformatics technology, indicating that the genetic relationships of bovids were similar. The Pax3 and Pax7 protein sequences of the five animals were highly consistent. In general, the Pax gene of the buffalo corresponds to the domestic cattle. In summary, there are differences in affinity between the Pax family genes of buffalo and domestic cattle in the Pax1/9, Pax2/5/8, Pax3/7, and Pax4/6 subfamilies. We believe that Pax1/9 has an effect on the growth traits of buffalo and domestic cattle. The Pax3/7 gene is conserved in the evolution of buffalo and domestic animals and may be a key gene regulating the growth of B. taurus. The Pax2/5/8 subfamily affects coat color, reproductive performance, and milk production performance in cattle. The Pax4/6 subfamily had an effect on the milk fat percentage of B. taurus. The results provide a theoretical basis for understanding the evolutionary, structural, and functional characteristics of the Pax family members of B. taurus and for molecular genetics and the breeding of meat-production B. taurus species.

Liver Transcriptomic Profiles of Ruminant Species Fed Spent Hemp Biomass Containing Cannabinoids.

The inclusion of spent hemp biomass (SHB), an extracted byproduct from industrial cannabidiol (CBD) production, in the diets of dairy cows and lambs appears to be safe with minor effects on the metabolism, including a decrease in circulating cholesterol and increase bilirubinemia, both associated with liver metabolism. Those effects could be consequence of the presence of cannabinoids, particularly Δ9-tetrahydrocannabinol (THC) and CBD in the SHB. This study aimed to study the transcriptional profile of the liver of dairy cows and lambs fed SHB. Dairy cows received SHB or alfalfa pellet for four weeks of intervention (IP) and four weeks of withdrawal periods (WP). Finishing lambs were fed a control diet (CON), 10% (LH2), or 20% (HH2) SHB for 2 months or 1 month followed by 1-month SHB withdrawal (LH1 and HH1, respectively). RNA sequencing was performed, and the mRNA was annotated using the latest reference genomes. The RNAseq data were filtered, normalized for library size and composition, and statistically analyzed by DESeq2. The bioinformatic analysis was performed by using DAVID, Gene Set Enrichment Analysis (GSEA), and the Dynamic Impact Approach. Using a 0.2 FDR cut-off, we identified only ≤24 differentially expressed genes (DEG) in the liver by feeding SHB in dairy cows and a larger number of DEGs in lambs (from 71 in HH1 vs. CON to 552 in LH1 vs. CON). The KEGG analysis demonstrated that feeding SHB in dairy cows and lambs had relatively minor to moderate metabolic alterations in dairy cows and lambs mainly associated with amino acids and lipid metabolism whereas cholesterol synthesis was overall activated in lambs. GSEA identified activation of the PPAR signaling pathway only in dairy cows. We found an opposite effect on activation of metabolism of drug and xenobiotics by cytochrome P450 enzymes in dairy cows and lambs receiving less SHB but an inhibition in HH2 lambs. Immune system-related pathways were inhibited by feeding SHB in lambs, but the impact was minor. Cumulatively, inclusion of SHB containing cannabinoids in dairy and lambs demonstrate very little effects on the alteration of transcriptomic profile of the liver.

Heritability estimates and genome-wide association study of methane emission traits in Nellore cattle.

The objectives of the present study were to estimate the heritability for daily methane emission (CH4) and residual daily methane emission (CH4res) in Nellore cattle, as well as to perform genome-wide association studies (GWAS) to identify genomic regions and candidate genes influencing the genetic variation of CH4 and CH4res. Methane emission phenotypes of 743 Nellore animals belonging to 3 breeding programs were evaluated. CH4 was measured using the sulfur hexafluoride (SF6) tracer technique (which involves an SF6 permeation tube introduced into the rumen, and an appropriate apparatus on each animal), and CH4res was obtained as the difference between observed CH4 and CH4 adjusted for dry matter intake. A total of 6,252 genotyped individuals were used for genomic analyses. Data were analyzed with a univariate animal model by the single-step GBLUP method using the average information restricted maximum likelihood (AIREML) algorithm. The effects of single nucleotide polymorphisms (SNPs) were obtained using a single-step GWAS approach. Candidate genes were identified based on genomic windows associated with quantitative trait loci (QTLs) related to the 2 traits. Annotation of QTLs and identification of candidate genes were based on the initial and final coordinates of each genomic window considering the bovine genome ARS-UCD1.2 assembly. Heritability estimates were of moderate to high magnitude, being 0.42 ±â€…0.09 for CH4 and 0.21 ±â€…0.09 for CH4res, indicating that these traits will respond rapidly to genetic selection. GWAS revealed 11 and 15 SNPs that were significantly associated (P < 10-6) with genetic variation of CH4 and CH4res, respectively. QTLs associated with feed efficiency, residual feed intake, body weight, and height overlapped with significant markers for the traits evaluated. Ten candidate genes were present in the regions of significant SNPs; 3 were associated with CH4 and 7 with CH4res. The identified genes are related to different functions such as modulation of the rumen microbiota, fatty acid production, and lipid metabolism. CH4 and CH4res presented sufficient genetic variation and may respond rapidly to selection. Therefore, these traits can be included in animal breeding programs aimed at reducing enteric methane emissions across generations.

Genetic selection designed to reduce the amount of enteric methane emission from livestock is a mitigation strategy to ensure more sustainable production over generations since genetic gains are cumulative. Brazil is a large producer of beef, and the Nellore breed (Bos taurus indicus) plays a very important role in this production. There are a few studies evaluating genetic and genomic aspects of enteric methane emission in Nellore cattle. The objectives of the present study were to estimate the heritability of daily methane emission (CH4) and residual daily methane emission (CH4res) in Nellore cattle, as well as to identify genomic regions and candidate genes associated with genetic variation of these traits. The heritability estimates for CH4 and CH4res were of moderate to high magnitude (0.42 ±â€…0.09 and 0.21 ±â€…0.09, respectively). Genome-wide association analyses revealed new loci associated with methane emission in Nellore cattle on chromosomes 5, 11, 17, and 20, where 10 candidate genes were identified, 3 for CH4 and 7 for CH4res. The 2 traits possess sufficient genetic variability to be included as selection criteria in breeding programs.

Breed of origin analysis in genome-wide association studies: enhancing SNP-based insights into production traits in a commercial Brangus population.

BACKGROUND: Carcass weight (HCW) and marbling (MARB) are critical for meat quality and market value in beef cattle. In composite breeds like Brangus, which meld the genetics of Angus and Brahman, SNP-based analyses have illuminated some genetic influences on these traits, but they fall short in fully capturing the nuanced effects of breed of origin alleles (BOA) on these traits. Focus on the impacts of BOA on phenotypic features within Brangus populations can result in a more profound understanding of the specific influences of Angus and Brahman genetics. Moreover, the consideration of BOA becomes particularly significant when evaluating dominance effects contributing to heterosis in crossbred populations. BOA provides a more comprehensive measure of heterosis due to its ability to differentiate the distinct genetic contributions originating from each parent breed. This detailed understanding of genetic effects is essential for making informed breeding decisions to optimize the benefits of heterosis in composite breeds like Brangus. OBJECTIVE: This study aims to identify quantitative trait loci (QTL) influencing HCW and MARB by utilizing SNP and BOA information, incorporating additive, dominance, and overdominance effects within a multi-generational Brangus commercial herd. METHODS: We analyzed phenotypic data from 1,066 genotyped Brangus steers. BOA inference was performed using LAMP-LD software using Angus and Brahman reference sets. SNP-based and BOA-based GWAS were then conducted considering additive, dominance, and overdominance models. RESULTS: The study identified numerous QTLs for HCW and MARB. A notable QTL for HCW was associated to the SGCB gene, pivotal for muscle growth, and was identified solely in the BOA GWAS. Several BOA GWAS QTLs exhibited a dominance effect underscoring their importance in estimating heterosis. CONCLUSIONS: Our findings demonstrate that SNP-based methods may not detect all genetic variation affecting economically important traits in composite breeds. BOA inclusion in genomic evaluations is crucial for identifying genetic regions contributing to trait variation and for understanding the dominance value underpinning heterosis. By considering BOA, we gain a deeper understanding of genetic interactions and heterosis, which is integral to advancing breeding programs. The incorporation of BOA is recommended for comprehensive genomic evaluations to optimize trait improvements in crossbred cattle populations.

Congenital syndromic Chiari-like malformation (CSCM) in Holstein cattle: towards unravelling of possible genetic causes.

BACKGROUND: Chiari malformation type II (CMII) was originally reported in humans as a rare disorder characterized by the downward herniation of the hindbrain and towering cerebellum. The congenital brain malformation is usually accompanied by spina bifida, a congenital spinal anomaly resulting from incomplete closure of the dorsal aspect of the spinal neural tube, and occasionally by other lesions. A similar disorder has been reported in several animal species, including cattle, particularly as a congenital syndrome. A cause of congenital syndromic Chiari-like malformation (CSCM) in cattle has not been reported to date. We collected a series of 14 CSCM-affected Holstein calves (13 purebred, one Red Danish Dairy F1 cross) and performed whole-genome sequencing (WGS). WGS was performed on 33 cattle, including eight cases with parents (trio-based; group 1), three cases with one parent (group 2), and three single cases (solo-based; group 3). RESULTS: Sequencing-based genome-wide association study of the 13 Holstein calves with CSCM and 166 controls revealed no significantly associated genome region. Assuming a single Holstein breed-specific recessive allele, no region of shared homozygosity was detected suggesting heterogeneity. Subsequent filtering for protein-changing variants that were only homozygous in the genomes of the individual cases allowed the identification of two missense variants affecting different genes, SHC4 in case 4 in group 1 and WDR45B in case 13 in group 3. Furthermore, these two variants were only observed in Holstein cattle when querying WGS data of > 5,100 animals. Alternatively, potential de novo mutational events were assessed in each case. Filtering for heterozygous private protein-changing variants identified one DYNC1H1 frameshift variant as a candidate causal dominant acting allele in case 12 in group 3. Finally, the presence of larger structural DNA variants and chromosomal abnormalities was investigated in all cases. Depth of coverage analysis revealed two different partial monosomies of chromosome 2 segments in cases 1 and 7 in group 1 and a trisomy of chromosome 12 in the WDR45B homozygous case 13 in group 3. CONCLUSIONS: This study presents for the first time a detailed genomic evaluation of CSCM in Holstein cattle and suggests an unexpected genetic and allelic heterogeneity considering the mode of inheritance, as well as the type of variant. For the first time, we propose candidate causal variants that may explain bovine CSCM in a certain proportion of affected calves. We present cattle as a large animal model for human CMII and propose new genes and genomic variants as possible causes for related diseases in both animals and humans.

Genetic and genomic analysis of Belgian Blue's susceptibility for psoroptic mange.

BACKGROUND: Psoroptic mange, caused by Psoroptes ovis mites, is affecting Belgian Blue cattle's welfare and production potential. The Belgian Blue cattle-known for its high degree of muscling, low feed conversion ratio and high beef quality-is highly susceptible for this disease. RESULTS: In this study, we phenotyped 1975 Belgian Blue cattle from more than 100 different groups on commercial beef farms for their psoroptic mange susceptibility. Substantial individual differences were observed within these management groups, with lesion extent differences up to ± 15%. Animal models showed that estimated heritabilities were low for lesion extent and severe lesion extent (0.07 and 0.09, respectively) and 0.12 for the number of mites. A genome wide association study for mange susceptibility revealed signals on BTA6, BTA11, BTA15 and BTA24. In these regions, candidate genes GBA3, RAG2, and TRAF6 were identified. CONCLUSIONS: Despite the challenges in phenotyping for psoroptic mange due to the timing of screening, the continuous evolution of lesions and different management conditions, we successfully conducted a study on the genetic susceptibility to psoroptic mange in Belgian Blue cattle. Our results clearly indicate that psoroptic mange is under polygenic control and the underlying candidate genes should be studied more thoroughly. This is the first study providing candidate genes for this complex disease. These results are already valuable for Belgian Blue breeding, however, further research is needed to unravel the architecture of this disease and to identify causal mutations.

Classification accuracy of machine learning algorithms for Chinese local cattle breeds using genomic markers.

Accurate breed classification is required for the conservation and utilization of farm animal genetic resources. Traditional classification methods mainly rely on phenotypic characterization. However, it is difficult to distinguish between the highly similar breeds due to the challenges in qualifying the phenotypic character. Machine learning algorithms show unique advantages in breed classification using genomic information. To evaluate the classification methods for Chinese cattle breeds, this study utilized genomic SNP data from 213 individuals across seven Chinese local breeds and compared the classification accuracies of three feature selection methods (FST value sorting and screening, mRMR, and Relief-F) and three machine learning algorithms (Random Forest, Support Vector Machine, and Naive Bayes). Results showed that: 1) using the FST method to screen more than 1500 SNPs, or using the mRMR algorithm to screen more than 1000 SNPs, the SVM classification algorithm can achieve more than 99.47% classification accuracy; 2) the most effective algorithm was SVM, followed by NB, while the best SNP selection method was FST and mRMR, followed by Relief-F; 3) species misclassification often occurs between breeds with high similarity. This study demonstrates that machine learning classification models combined with genomic data are effective methods for the classification of local cattle breeds, providing a technical basis for the rapid and accurate classification of cattle breeds in China.