Effects of inbreeding on production traits and genetic evaluations in Guzerá beef cattle raised under tropical conditions.

The objectives of this study were to evaluate the influence of inbreeding on growth traits and body measurements, as well as on the estimation of genetic parameters and genetic trends in Guzerá cattle. Phenotypic records of 4,212 animals selected for postweaning weight from Guzerá Breeding Program of Advanced Beef Cattle Research Center were utilized. The pedigree file contained records from 7,213 animals born from 1928 to 2019. The traits analyzed were: birth weight (BW), weights adjusted to 210, 378 and 550 days of age (W210, W378 and W550, respectively), chest girth at 378 and 550 days of age (CG378 and CG550), scrotal circumference (SC), and hip height at 378 and 550 days of age (HH378 and H550). Linear regression was used to evaluate the effects of inbreeding on traits. Genetic parameters were obtained using models including or not the effect of inbreeding as a covariate. Inbreeding had negative effects (P ≤ 0.01) on BW (-0.09 kg), W378 (-2.86 kg), W550 (-2.95 kg), HH378 (-0.10 cm), and H550 (-0.29 cm). The lowest and highest heritability estimates were obtained for W210 (0.21 ± 0.07) and HH550 (0.57 ± 0.06), respectively. The genetic correlations were strong and positive between all traits, ranging from 0.44 ± 0.08 (SC x HH) to 0.99 ± 0.01 (W378 x W550). Spearman correlations between EBVs obtained with or without inbreeding effect ranged from 0.968 to 0.995 (P < 0.01). The results indicate loss of productive performance in inbred animals. However, the inclusion of inbreeding coefficient in genetic evaluation models did not alter the magnitude of genetic parameters or genetic trends for the traits studied.

Yak genome database: a multi-omics analysis platform.

BACKGROUND: The yak (Bos grunniens) is a large ruminant species that lives in high-altitude regions and exhibits excellent adaptation to the plateau environments. To further understand the genetic characteristics and adaptive mechanisms of yak, we have developed a multi-omics database of yak including genome, transcriptome, proteome, and DNA methylation data. DESCRIPTION: The Yak Genome Database ( http://yakgenomics.com/ ) integrates the research results of genome, transcriptome, proteome, and DNA methylation, and provides an integrated platform for researchers to share and exchange omics data. The database contains 26,518 genes, 62 transcriptomes, 144,309 proteome spectra, and 22,478 methylation sites of yak. The genome module provides access to yak genome sequences, gene annotations and variant information. The transcriptome module offers transcriptome data from various tissues of yak and cattle strains at different developmental stages. The proteome module presents protein profiles from diverse yak organs. Additionally, the DNA methylation module shows the DNA methylation information at each base of the whole genome. Functions of data downloading and browsing, functional gene exploration, and experimental practice were available for the database. CONCLUSION: This comprehensive database provides a valuable resource for further investigations on development, molecular mechanisms underlying high-altitude adaptation, and molecular breeding of yak.

Enhanced bovine genome annotation through integration of transcriptomics and epi-transcriptomics datasets facilitates genomic biology.

BACKGROUND: The accurate identification of the functional elements in the bovine genome is a fundamental requirement for high-quality analysis of data informing both genome biology and genomic selection. Functional annotation of the bovine genome was performed to identify a more complete catalog of transcript isoforms across bovine tissues. RESULTS: A total of 160,820 unique transcripts (50% protein coding) representing 34,882 unique genes (60% protein coding) were identified across tissues. Among them, 118,563 transcripts (73% of the total) were structurally validated by independent datasets (PacBio isoform sequencing data, Oxford Nanopore Technologies sequencing data, de novo assembled transcripts from RNA sequencing data) and comparison with Ensembl and NCBI gene sets. In addition, all transcripts were supported by extensive data from different technologies such as whole transcriptome termini site sequencing, RNA Annotation and Mapping of Promoters for the Analysis of Gene Expression, chromatin immunoprecipitation sequencing, and assay for transposase-accessible chromatin using sequencing. A large proportion of identified transcripts (69%) were unannotated, of which 86% were produced by annotated genes and 14% by unannotated genes. A median of two 5' untranslated regions were expressed per gene. Around 50% of protein-coding genes in each tissue were bifunctional and transcribed both coding and noncoding isoforms. Furthermore, we identified 3,744 genes that functioned as noncoding genes in fetal tissues but as protein-coding genes in adult tissues. Our new bovine genome annotation extended more than 11,000 annotated gene borders compared to Ensembl or NCBI annotations. The resulting bovine transcriptome was integrated with publicly available quantitative trait loci data to study tissue-tissue interconnection involved in different traits and construct the first bovine trait similarity network. CONCLUSIONS: These validated results show significant improvement over current bovine genome annotations.

Mendelian randomization analysis of 34,497 German Holstein cows to infer causal associations between milk production and health traits.

BACKGROUND: Claw diseases and mastitis represent the most important health issues in dairy cattle with a frequently mentioned connection to milk production. Although many studies have aimed at investigating this connection in more detail by estimating genetic correlations, they do not provide information about causality. An alternative is to carry out Mendelian randomization (MR) studies using genetic variants to investigate the effect of an exposure on an outcome trait mediated by genetic variants. No study has yet investigated the causal association of milk yield (MY) with health traits in dairy cattle. Hence, we performed a MR analysis of MY and seven health traits using imputed whole-genome sequence data from 34,497 German Holstein cows. We applied a method that uses summary statistics and removes horizontal pleiotropic variants (having an effect on both traits), which improves the power and unbiasedness of MR studies. In addition, genetic correlations between MY and each health trait were estimated to compare them with the estimates of causal effects that we expected. RESULTS: All genetic correlations between MY and each health trait were negative, ranging from - 0.303 (mastitis) to - 0.019 (digital dermatitis), which indicates a reduced health status as MY increases. The only non-significant correlation was between MY and digital dermatitis. In addition, each causal association was negative, ranging from - 0.131 (mastitis) to - 0.034 (laminitis), but the number of significant associations was reduced to five nominal and two experiment-wide significant results. The latter were between MY and mastitis and between MY and digital phlegmon. Horizontal pleiotropic variants were identified for mastitis, digital dermatitis and digital phlegmon. They were located within or nearby variants that were previously reported to have a horizontal pleiotropic effect, e.g., on milk production and somatic cell count. CONCLUSIONS: Our results confirm the known negative genetic connection between health traits and MY in dairy cattle. In addition, they provide new information about causality, which for example points to the negative energy balance mediating the connection between these traits. This knowledge helps to better understand whether the negative genetic correlation is based on pleiotropy, linkage between causal variants for both trait complexes, or indeed on a causal association.

Single nucleotide polymorphisms of growth hormone gene in cattle and their association with growth traits: a systematic review.

Growth traits in livestock animals are quantitative parameters, which are often controlled by many genes including growth hormone (GH) gene. However, the evidence of effect of GH gene on growth traits of cattle is poorly understood. Hence, the objective of the study was to systematically investigate the literature on single nucleotide polymorphisms (SNPs) of GH gene and their association with growth traits in cattle from four databases Google Scholar, PubMed, ScienceDirect, and Web of Science. The results indicated that fifteen (n = 15) articles with 27% of them from Indonesia qualified to be used in this study after screening. The results revealed five SNPs (1047T > C, 1180 C > T, 86,273,136 A/G, 3338 A > G and 4251 C > T) occurred across multiple investigated breeds with no common identified SNPs. Six articles observed a significant difference (p < 0.05) between growth traits and genotypes of identified SNPs. The findings showed that 7 articles (47%) investigated body weight (BW) with 6 (40%) of them found non-significant and 1 (7%) found a significant association with genotypes of the identified SNPs (3338 A > G). While 7 articles (47%) investigated weaning weight (WW) with 5 (33%) of them revealed a non-significant and 2 (13%) found a significant association with genotypes of identified SNPs (3338 A > G and 4251 C > T). This study shows that there is a lack of evidence on effect of growth hormone gene on growth traits in cattle. However, more studies are recommended for further validation of the identified SNPs and effect of growth hormone gene on growth traits in cattle.

Population structure and identification of genomic regions associated with productive traits in five Italian beef cattle breeds.

Italy has a long history in beef production, with local breeds such as Marchigiana, Chianina, Romagnola, Maremmana, and Podolica which produce high-quality meat. Selection has improved meat production, precocity, growth ability and muscle development, but the genetic determinism of such traits is mostly unknown. Using 33K SNPs-data from young bulls (N = 4064) belonging to these five Italian breeds, we demonstrated that the Maremmana and Podolica rustic breeds are closely related, while the specialised Marchigiana, Chianina, and Romagnola breeds are more differentiated. A genome-wide association study for growth and muscle development traits (average daily gain during the performance test, weight at 1 year old, muscularity) was conducted in the five Italian breeds. Results indicated a region on chromosome 2, containing the myostatin gene (MSTN), which displayed significant genome-wide associations with muscularity in Marchigiana cattle, a breed in which the muscle hypertrophy phenotype is segregating. Moreover, a significant SNP on chromosome 14 was associated, in the Chianina breed, to muscularity. The identification of diverse genomic regions associated with conformation traits might increase our knowledge about the genomic basis of such traits in Italian beef cattle and, eventually, such information could be used to implement marker-assisted selection of young bulls tested in the performance test.

Identification of runs of homozygosity (ROHs) in Curraleiro Pé-Duro and Pantaneiro cattle breeds.

This study aimed to identify and characterize runs of homozygosis (ROHs), genes involved in production characteristics and adaptation to tropical systems and to estimate the inbreeding coefficient of Curraleiro Pé-Duro (CPD) and Pantaneiro (PANT), two brazilian locally adapted cattle breeds. The results demonstrated that 79.25% and 54.29% of ROH segments were bigger than 8 Mb in CPD and PANT, respectively, indicating recent inbred matings in the studied population. Six homozygosis islands were identified simultaneously in both breeds, where 175 QTLs and 1072 genes previously described as associated with production traits are located. The inbreeding coefficient (FROH) estimated based on ROHs (FROH) showed that inbreeding is low (2 to 4%), which is different from expected for small populations such as locally adapted ones.

Phenotypic and genetic characterization of unexplored, potential cattle population of Madhya Pradesh.

Bawri or Garri, a non-descript cattle population managed under an extensive system in Madhya Pradesh state of India, was identified and characterized both genetically and phenotypically to check whether or not it can be recognised as a breed. The cattle have white and gray colour and are medium sized with 122.5 ± 7.5 cm and 109.45 ± 0.39 cm height at withers in male and female, respectively. Double-digest restriction site associated DNA (ddRAD) sequencing was employed to identify ascertainment bias free SNPs representing the entire genome cost effectively; resulting in calling 1,156,650 high quality SNPs. Observed homozygosity was 0.76, indicating Bawri as a quite unique population. However, the inbreeding coefficient was 0.025, indicating lack of selection. SNPs found here can be used in GWAS and genetic evaluation programs. Considering the uniqueness of Bawri cattle, it can be registered as a breed for its better genetic management.

Population Structure and Selection Signal Analysis of Nanyang Cattle Based on Whole-Genome Sequencing Data.

With a rich breeding history, Nanyang cattle (NY cattle) have undergone extensive natural and artificial selection, resulting in distinctive traits such as high fertility, excellent meat quality, and disease resistance. This makes them an ideal model for studying the mechanisms of environmental adaptability. To assess the population structure and genetic diversity of NY cattle, we performed whole-genome resequencing on 30 individuals. These data were then compared with published whole-genome resequencing data from 432 cattle globally. The results indicate that the genetic structure of NY cattle is significantly different from European commercial breeds and is more similar to North-Central Chinese breeds. Furthermore, among all breeds, NY cattle exhibit the highest genetic diversity and the lowest population inbreeding levels. A genome-wide selection signal analysis of NY cattle and European commercial breeds using Fst, θπ-ratio, and θπ methods revealed significant selection signals in genes associated with reproductive performance and immunity. Our functional annotation analysis suggests that these genes may be responsible for reproduction (MAP2K2, PGR, and GSE1), immune response (NCOA2, HSF1, and PAX5), and olfaction (TAS1R3). We provide a comprehensive overview of sequence variations in the NY cattle genome, revealing insights into the population structure and genetic diversity of NY cattle. Additionally, we identify candidate genes associated with important economic traits, offering valuable references for future conservation and breeding efforts of NY cattle.

Extraction of Innate Immune Genes in Dairy Cattle and the Regulation of Their Expression in Early Embryos.

As more and more of the available genomic data have been published, several databases have been developed for deciphering early mammalian embryogenesis; however, less research has been conducted on the regulation of the expression of natural immunity genes during early embryonic development in dairy cows. To this end, we explored the regulatory mechanism of innate immunity genes at the whole-genome level. Based on comparative genomics, 1473 innate immunity genes in cattle were obtained by collecting the latest reports on human innate immunity genes and updated bovine genome data for comparison, and a preliminary database of bovine innate immunity genes was constructed. In order to determine the regulatory mechanism of innate immune genes in dairy cattle early embryos, we conducted weighted co-expression network analysis of the innate immune genes at different developmental stages of dairy cattle early embryos. The results showed that specific module-related genes were significantly enriched in the MAPK signaling pathway. Protein-protein interaction (PPI) analysis showed gene interactions in each specific module, and 10 of the highest connectivity genes were chosen as potential hub genes. Finally, combined with the results for differential expressed genes (DEGs), ATF3, IL6, CD8A, CD69, CD86, HCK, ERBB3, LCK, ITGB2, LYN, and ERBB2 were identified as the key genes of innate immunity in dairy cattle early embryos. In conclusion, the bovine innate immunity gene set was determined and the co-expression network of innate immunity genes in the early embryonic stage of dairy cattle was constructed by comparing and analyzing the whole genome of bovines and humans. The findings in this study provide the basis for exploring the involvement and regulation of innate immune genes in the early embryonic development of dairy cattle.

A novel imprinted locus on bovine chromosome 18 homologous with human chromosome 16q24.1.

Genomic imprinting is an epigenetic regulation mechanism in mammals resulting in the parentally dependent monoallelic expression of genes. Imprinting disorders in humans are associated with several congenital syndromes and cancers and remain the focus of many medical studies. Cattle is a better model organism for investigating human embryo development than mice. Imprinted genes usually cluster on chromosomes and are regulated by different methylation regions (DMRs) located in imprinting control regions that control gene expression in cis. There is an imprinted locus on human chromosome 16q24.1 associated with congenital lethal developmental lung disease in newborns. However, genomic imprinting on bovine chromosome 18, which is homologous with human chromosome 16 has not been systematically studied. The aim of this study was to analyze the allelic expressions of eight genes (CDH13, ATP2C2, TLDC1, COTL1, CRISPLD2, ZDHHC7, KIAA0513, and GSE1) on bovine chromosome 18 and to search the DMRs associated gene allelic expression. Three transcript variants of the ZDHHC7 gene (X1, X2, and X5) showed maternal imprinting in bovine placentas. In addition, the monoallelic expression of X2 and X5 was tissue-specific. Five transcripts of the KIAA0513 gene showed tissue- and isoform-specific monoallelic expression. The CDH13, ATP2C2, and TLDC1 genes exhibited tissue-specific imprinting, however, COTL1, CRISLPLD2, and GSE1 escaped imprinting. Four DMRs, established after fertilization, were found in this region. Two DMRs were located between the ZDHHC7 and KIAA0513 genes, and two were in exon 1 of the CDH13 and ATP2C2 genes, respectively. The results from this study support future studies on the molecular mechanism to regulate the imprinting of candidate genes on bovine chromosome 18.

Effect of temperature-humidity index on the evolution of trade-offs between fertility and production in dairy cattle.

BACKGROUND: In the current context of climate change, livestock production faces many challenges to improve the sustainability of systems. Dairy farming, in particular, must find ways to select animals that will be able to achieve sufficient overall production while maintaining their reproductive ability in environments with increasing temperatures. With future forecasted climate conditions in mind, this study used data from Holstein and Montbeliarde dairy cattle to: (1) estimate the genetic-by-temperature-humidity index (THI) interactions for female fertility, and (2) evaluate the production-fertility trade-off with increasing values of THI. RESULTS: Two-trait random regression models were fitted for conception rate (fertility) and test-day protein yield (production). For fertility, genetic correlations between different THI values were generally above 0.75, suggesting weak genotype-by-THI interactions for conception rate in both breeds. However, the genetic correlations between the conception rate breeding values at the current average THI (THI = 50, corresponding to a 24-h average temperature of 8 °C at 50% relative humidity) and their slopes (i.e., potential reranking) for heat stress scenarios (THI > 70), were different for each breed. For Montbeliarde, this correlation tended to be positive (i.e., overall the best reproducers are less affected by heat stress), whereas for Holstein it was approximately zero. Finally, our results indicated a weak antagonism between production and fertility, although for Montbeliarde this antagonism intensified with increasing THI. CONCLUSIONS: Within the range of weather conditions studied, increasing temperatures are not expected to exacerbate the fertility-production trade-off. However, our results indicated that the animals with the best breeding values for production today will be the most affected by temperature increases, both in terms of fertility and production. Nonetheless, these animals should remain among the most productive ones during heat waves. For Montbeliarde, the current selection program for fertility seems to be adequate for ensuring the adaptation of fertility traits to temperature increases, without adverse effects on production. Such a conclusion cannot be drawn for Holstein. In the future, the incorporation of a heat tolerance index into dairy cattle breeding programs would be valuable to promote the selection of animals adapted to future climate conditions.

Multi-tissue gene expression profiling of cows with a genetic predisposition for low and high milk urea levels.

Milk urea (MU) concentration is proposed as an indicator trait for breeding toward reduced nitrogen (N) emissions and leaching in dairy. We selected 20 German Holstein cows based on MU breeding values, with 10 cows each having low (LMUg) and high (HMUg) MU genetic predisposition. Using RNA-seq, we characterized these cows to unravel molecular pathways governing post-absorptive body N pools focusing on renal filtration and reabsorption of nitrogenous compounds, hepatic urea formation and mammary gland N excretion. While we observed minor adjustments in cellular energy metabolism in different tissues associated with different MU levels, no transcriptional differences in liver ammonia detoxification were detected, despite significant differences in MU between the groups. Differential expression of AQP3 and SLC38A2 in the kidney provides evidence for higher urea concentration in the collecting duct of LMU cows than HMU cows. The mammary gland exhibited the most significant differences, particularly in tricarboxylic acid (TCA) cycle genes, amino acid transport, tRNA binding, and casein synthesis. These findings suggest that selecting for lower MU could lead to altered urinary urea (UU) handling and changes in milk protein synthesis. However, given the genetic variability in N metabolism components, the long-term effectiveness of MU-based selection in reducing N emissions remains uncertain.

Copy number variations within fibroblast growth factor 13 gene influence growth traits and alternative splicing in cattle.

Previous researches revealed a copy number variation (CNV) region in the bovine fibroblast growth factor 13 (FGF13) gene. However, its effects remain unknown. This study detected the various copy number types in seven Chinese cattle breeds and analysed their population genetic characteristics and effects on growth traits and transcription levels. Copy number Loss was more frequent in Caoyuan Red cattle and Xianan cattle than in the other breeds. Association analysis between CNV and growth traits of Qinchuan indicated that the CNV was significantly related to chest depth, hip width and hucklebone width (P < 0.05). Additionally, the growth traits of individuals with copy number Loss were significantly inferior to those with copy number Gain or Median (P < 0.05). Besides, we found two splicing isoforms, AS1 and AS2, in FGF13 gene, which resulted from alternative 5' splicing sites of intron 1. These isoforms showed varied expression levels in various tissues. Moreover, CNV was significantly and negatively associated with the mRNA expression of AS1 (r = -0.525, P < 0.05). The CNVs in bovine FGF13 gene negatively regulated growth traits and gene transcription. These observations provide new insights into bovine FGF13 gene, delivering potentially useful information for future Chinese cattle breeding programs.

Exploring genomic inbreeding and selection signatures in a commercial Brangus herd through functional annotation.

Composite breeds, including Brangus, are widely utilized in subtropical and tropical regions to harness the advantages of both Bos t. taurus and Bos t. indicus breeds. The formation and subsequent selection of composite breeds may result in discernible signatures of selection and shifts in genomic population structure. The objectives of this study were to 1) assess genomic inbreeding, 2) identify signatures of selection, 3) assign functional roles to these signatures in a commercial Brangus herd, and 4) contrast signatures of selection between selected and non-selected cattle from the same year. A total of 4035 commercial Brangus cattle were genotyped using the GGP-F250K array. Runs of Homozygosity (ROH) were used to identify signatures of selection and calculate genomic inbreeding. Quantitative trait loci (QTL) enrichment analysis and literature search identified phenotypic traits linked to ROH islands. Genomic inbreeding averaged 5%, primarily stemming from ancestors five or more generations back. A total of nine ROH islands were identified, QTL enrichment analysis revealed traits related to growth, milk composition, carcass, reproductive, and meat quality traits. Notably, the ROH island on BTA14 encompasses the pleiomorphic adenoma (PLAG1) gene, which has been linked to growth, carcass, and reproductive traits. Moreover, ROH islands associated with milk yield and composition were more pronounced in selected replacement heifers of the population, underscoring the importance of milk traits in cow-calf production. In summary, our research sheds light on the changing genetic landscape of the Brangus breed due to selection pressures and reveals key genomic regions impacting production traits.

Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows.

BACKGROUND: Over the last decades, it was subject of many studies to investigate the genomic connection of milk production and health traits in dairy cattle. Thereby, incorporating functional information in genomic analyses has been shown to improve the understanding of biological and molecular mechanisms shaping complex traits and the accuracies of genomic prediction, especially in small populations and across-breed settings. Still, little is known about the contribution of different functional and evolutionary genome partitioning subsets to milk production and dairy health. Thus, we performed a uni- and a bivariate analysis of milk yield (MY) and eight health traits using a set of ~34,497 German Holstein cows with 50K chip genotypes and ~17 million imputed sequence variants divided into 27 subsets depending on their functional and evolutionary annotation. In the bivariate analysis, eight trait-combinations were observed that contrasted MY with each health trait. Two genomic relationship matrices (GRM) were included, one consisting of the 50K chip variants and one consisting of each set of subset variants, to obtain subset heritabilities and genetic correlations. In addition, 50K chip heritabilities and genetic correlations were estimated applying merely the 50K GRM. RESULTS: In general, 50K chip heritabilities were larger than the subset heritabilities. The largest heritabilities were found for MY, which was 0.4358 for the 50K and 0.2757 for the subset heritabilities. Whereas all 50K genetic correlations were negative, subset genetic correlations were both, positive and negative (ranging from -0.9324 between MY and mastitis to 0.6662 between MY and digital dermatitis). The subsets containing variants which were annotated as noncoding related, splice sites, untranslated regions, metabolic quantitative trait loci, and young variants ranked highest in terms of their contribution to the traits` genetic variance. We were able to show that linkage disequilibrium between subset variants and adjacent variants did not cause these subsets` high effect. CONCLUSION: Our results confirm the connection of milk production and health traits in dairy cattle via the animals` metabolic state. In addition, they highlight the potential of including functional information in genomic analyses, which helps to dissect the extent and direction of the observed traits` connection in more detail.

Genetic parameters for yearling male reproduction traits in tropical composite cattle population.

Fertility is economically important but is hard to quantify and measure in breeding programs which has led extensive breeding programs to ignore fertility in their selection criteria. While female fertility traits have been extensively researched, male fertility traits have been largely ignored. It is estimated that 20% to 40% of bulls have sub-fertility, reducing the number of calves born and profits, highlighting the importance of investigating bull fertility. The most practical measure of male fertility is a bull breeding soundness evaluation (BBSE) which assesses structure as well as semen quality and quantity. Generally, traits recorded in a BBSE are neither genetically evaluated nor used for selection in breeding programs. All traits recorded during a BBSE were analyzed through a series of univariate and bivariate linear mixed models using a genomic relationship matrix to estimate genetic parameters. All genotype and phenotype data were obtained from a tropical composite commercial cattle population and imputed to 27,638 single-nucleotide polymorphisms (SNPs) with a total of 2,613 genotyped animals with BBSE records ranging from 616 to 826 animals depending on the trait. The heritabilities of the 27 traits recorded during a BBSE ranged from 0.02 to 0.49. Seven of the male fertility traits were recommended to be included in a breeding program based on their heritability and their phenotypic and genetic correlations. These traits are scrotal circumference, percent normal sperm, proximal droplets, distal midpiece reflex, knobbed acrosomes, vacuoles/teratoids, and sheath score. Using these seven traits in a breeding program would result in higher calving rates, increasing production and profitability.

One of the key profit drivers in any animal breeding program is fertility as it contributes directly to the progeny produced. Typically, fertility traits are hard to quantify and lowly heritable so they are often ignored in breeding programs. The inclusion of male fertility traits could allow for selection on heritable traits that are easy to measure and implement in a commercial breeding program. The utilization of male fertility traits could improve overall fertility and production. Bull breeding soundness evaluation traits were heritable, ranging from low to high, allowing for genetic improvement in those traits. Seven traits were recommended as selection criteria in a breeding program, which included two physical traits and five sperm traits. Implementing these seven traits in a breeding program would allow for a higher calving rate and associated increased profits.

Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle.

BACKGROUND: Growth rate is an important component of feed conversion efficiency in cattle and varies across the different stages of the finishing period. The metabolic effect of the rumen microbiome is essential for cattle growth, and investigating the genomic and microbial factors that underlie this temporal variation can help maximize feed conversion efficiency at each growth stage. RESULTS: By analysing longitudinal body weights during the finishing period and genomic and metagenomic data from 359 beef cattle, our study demonstrates that the influence of the host genome on the functional rumen microbiome contributes to the temporal variation in average daily gain (ADG) in different months (ADG1, ADG2, ADG3, ADG4). Five hundred and thirty-three additive log-ratio transformed microbial genes (alr-MG) had non-zero genomic correlations (rg) with at least one ADG-trait (ranging from |0.21| to |0.42|). Only a few alr-MG correlated with more than one ADG-trait, which suggests that a differential host-microbiome determinism underlies ADG at different stages. These alr-MG were involved in ribosomal biosynthesis, energy processes, sulphur and aminoacid metabolism and transport, or lipopolysaccharide signalling, among others. We selected two alternative subsets of 32 alr-MG that had a non-uniform or a uniform rg sign with all the ADG-traits, regardless of the rg magnitude, and used them to develop a microbiome-driven breeding strategy based on alr-MG only, or combined with ADG-traits, which was aimed at shaping the rumen microbiome towards increased ADG at all finishing stages. Combining alr-MG information with ADG records increased prediction accuracy of genomic estimated breeding values (GEBV) by 11 to 22% relative to the direct breeding strategy (using ADG-traits only), whereas using microbiome information, only, achieved lower accuracies (from 7 to 41%). Predicted selection responses varied consistently with accuracies. Restricting alr-MG based on their rg sign (uniform subset) did not yield a gain in the predicted response compared to the non-uniform subset, which is explained by the absence of alr-MG showing non-zero rg at least with more than one of the ADG-traits. CONCLUSIONS: Our work sheds light on the role of the microbial metabolism in the growth trajectory of beef cattle at the genomic level and provides insights into the potential benefits of using microbiome information in future genomic breeding programs to accurately estimate GEBV and increase ADG at each finishing stage in beef cattle.

Short communication: Correlation of methane production, intensity, and yield with residual feed intake throughout lactation in Holstein cows.

The environmental impact of dairy production can be reduced in several ways, including increasing feed efficiency and reducing methane (CH4) emissions. There is no consensus on their relationship. This study aimed at estimating the correlations between residual feed intake (RFI) and CH4 emissions expressed in g/d methane production (MeP), g/kg of fat- and protein-corrected milk methane intensity (MeI), or g/kg of DM intake methane yield (MeY) throughout lactation. We collected CH4 data using GreenFeed devices from 107 Holstein cows, as well as production and intake phenotypes. RFI was predicted from DM intake, fat- and protein-corrected milk, BW, and body condition score. Five-trait random regression models were used to estimate the individual variance components of the CH4 and production traits, which were used to calculate the correlations between RFI and CH4 traits throughout lactation. We found positive correlations of RFI with MeP and MeI ranging from 0.05 to 0.47 throughout the lactation. Correlations between RFI and MeY are low and vary from positive to negative, ranging from -0.18 to 0.17. Both MeP and MeI are favorably correlated with RFI, as is MeY during the first half of lactation. These correlations are mostly favorable for genetic selection, but the confirmation of these results is needed with genetic correlations over a larger dataset.

GWABLUP: genome-wide association assisted best linear unbiased prediction of genetic values.

BACKGROUND: Since the very beginning of genomic selection, researchers investigated methods that improved upon SNP-BLUP (single nucleotide polymorphism best linear unbiased prediction). SNP-BLUP gives equal weight to all SNPs, whereas it is expected that many SNPs are not near causal variants and thus do not have substantial effects. A recent approach to remedy this is to use genome-wide association study (GWAS) findings and increase the weights of GWAS-top-SNPs in genomic predictions. Here, we employ a genome-wide approach to integrate GWAS results into genomic prediction, called GWABLUP. RESULTS: GWABLUP consists of the following steps: (1) performing a GWAS in the training data which results in likelihood ratios; (2) smoothing the likelihood ratios over the SNPs; (3) combining the smoothed likelihood ratio with the prior probability of SNPs having non-zero effects, which yields the posterior probability of the SNPs; (4) calculating a weighted genomic relationship matrix using the posterior probabilities as weights; and (5) performing genomic prediction using the weighted genomic relationship matrix. Using high-density genotypes and milk, fat, protein and somatic cell count phenotypes on dairy cows, GWABLUP was compared to GBLUP, GBLUP (topSNPs) with extra weights for GWAS top-SNPs, and BayesGC, i.e. a Bayesian variable selection model. The GWAS resulted in six, five, four, and three genome-wide significant peaks for milk, fat and protein yield and somatic cell count, respectively. GWABLUP genomic predictions were 10, 6, 7 and 1% more reliable than those of GBLUP for milk, fat and protein yield and somatic cell count, respectively. It was also more reliable than GBLUP (topSNPs) for all four traits, and more reliable than BayesGC for three of the traits. Although GWABLUP showed a tendency towards inflation bias for three of the traits, this was not statistically significant. In a multitrait analysis, GWABLUP yielded the highest accuracy for two of the traits. However, for SCC, which was relatively unrelated to the yield traits, including yield trait GWAS-results reduced the reliability compared to a single trait analysis. CONCLUSIONS: GWABLUP uses GWAS results to differentially weigh all the SNPs in a weighted GBLUP genomic prediction analysis. GWABLUP yielded up to 10% and 13% more reliable genomic predictions than GBLUP for single and multitrait analyses, respectively. Extension of GWABLUP to single-step analyses is straightforward.