An association weight matrix identified biological pathways associated with bull fertility traits in a multi-breed population.

Using seven indicator traits, we investigated the genetic basis of bull fertility and predicted gene interactions from SNP associations. We used percent normal sperm as the key phenotype for the association weight matrix-partial correlation information theory (AWM-PCIT) approach. Beyond a simple list of candidate genes, AWM-PCIT predicts significant gene interactions and associations for the selected traits. These interactions formed a network of 537 genes: 38 genes were transcription cofactors, and 41 genes were transcription factors. The network displayed two distinct clusters, one with 294 genes and another with 243 genes. The network is enriched in fertility-associated pathways: steroid biosynthesis, p53 signalling, and the pentose phosphate pathway. Enrichment analysis also highlighted gene ontology terms associated with 'regulation of neurotransmitter secretion' and 'chromatin formation'. Our network recapitulates some genes previously implicated in another network built with lower-density genotypes. Sequence-level data also highlights additional candidate genes relevant to bull fertility, such as FOXO4, FOXP3, GATA1, CYP27B1, and EBP. A trio of regulatory genes-KDM5C, LRRK2, and PME-was deemed core to the network because of their overarching connections. This trio probably influences bull fertility through their interaction with genes, both known and unknown as to their role in male fertility. Future studies may target the trio and their target genes to enrich our understanding of male fertility further.

Pleomorphic adenoma gene1 in reproduction and implication for embryonic survival in cattle: a review.

The pleomorphic adenoma gene1 (PLAG1) encodes a DNA-binding, C2H2 zinc-finger protein which acts as a transcription factor that regulates the expression of diverse genes across different organs and tissues; hence, the name pleomorphic. Rearrangements of the PLAG1 gene, and/or overexpression, are associated with benign tumors and cancers in a variety of tissues. This is best described for pleomorphic adenoma of the salivary glands in humans. The most notable expression of PLAG1 occurs during embryonic and fetal development, with lesser expression after birth. Evidence has accumulated of a role for PLAG1 protein in normal early embryonic development and placentation in mammals. PLAG1 protein influences the expression of the ike growth factor 2 (IGF2) gene and production of IGF2 protein. IGF2 is an important mitogen in ovarian follicles/oocytes, embryos, and fetuses. The PLAG1-IGF2 axis, therefore, provides one pathway whereby PLAG1 protein can influence embryonic survival and pregnancy. PLAG1 also influences over 1,000 other genes in embryos including those associated with ribosomal assembly and proteins. Brahman (Bos indicus) heifers homozygous for the PLAG1 variant, rs109815800 (G > T), show greater fertility than contemporary heifers with either one, or no copy, of the variant. Greater fertility in heifers homozygous for rs109815800 could be the result of early puberty and/or greater embryonic survival. The present review first looks at the broader roles of the PLAG1 gene and PLAG1 protein and then focuses on the emerging role of PLAG1/PLAG1 in embryonic development and pregnancy. A deeper understanding of factors which influence embryonic development is required for the next transformational increase in embryonic survival and successful pregnancy for both in vivo and in vitro derived embryos in cattle.

The pleomorphic adenoma gene1 (PLAG1) produces PLAG1 protein which, by binding to specific regions on DNA, influences the activity of other genes that regulate many body functions. One gene is insulin-like growth factor 2 (IGF2) which controls cell metabolism and growth. The PLAG1 gene is particularly active during embryonic and fetal growth, and through IGF2 determines stature later in life. IGF2 protein is also very important in early embryonic development. This review explores the hypothesis that PLAG1 is an important determinant of embryonic survival and the establishment of pregnancy in mammals.

Genomic regions and biological pathways associated with sex-limited reproductive traits in bovine species.

Many animal species exhibit sex-limited traits, where certain phenotypes are exclusively expressed in one sex. Yet, the genomic regions that contribute to these sex-limited traits in males and females remain a subject of debate. Reproductive traits are ideal phenotypes to study sexual differences since they are mostly expressed in a sex-limited way. Therefore, this study aims to use local correlation analyses to identify genomic regions and biological pathways significantly associated with male and female sex-limited traits in two distinct cattle breeds (Brahman [BB] and Tropical Composite [TC]). We used the Correlation Scan method to perform local correlation analysis on 42 trait pairs consisting of six female and seven male reproductive traits recorded on ~1,000 animals for each sex in each breed. To pinpoint a specific region associated with these sex-limited reproductive traits, we investigated the genomic region(s) consistently identified as significant across the 42 trait pairs in each breed. The genes found in the identified regions were subjected to Quantitative Trait Loci (QTL) colocalization, QTL enrichment analyses, and functional analyses to gain biological insight into sexual differences. We found that the genomic regions associated with the sex-limited reproductive phenotypes are widely distributed across all the chromosomes. However, no single region across the genome was associated with all the 42 reproductive trait pairs in the two breeds. Nevertheless, we found a region on the X-chromosome to be most significant for 80% to 90% (BB: 33 and TC: 38) of the total 42 trait pairs. A considerable number of the genes in this region were regulatory genes. By considering only genomic regions that were significant for at least 50% of the 42 trait pairs, we observed more regions spread across the autosomes and the X-chromosome. All genomic regions identified were highly enriched for trait-specific QTL linked to sex-limited traits (percentage of normal sperm, metabolic weight, average daily gain, carcass weight, age at puberty, etc.). The gene list created from these identified regions was enriched for biological pathways that contribute to the observed differences between sexes. Our results demonstrate that genomic regions associated with male and female sex-limited reproductive traits are distributed across the genome. Yet, chromosome X seems to exert a relatively larger effect on the phenotypic variation observed between the sexes.

Many livestock species show sexual differences between males and females. However, we still do not fully understand the specific area of the genome responsible for these differences. This study used a novel method to investigate this research question in two distinct tropically adapted cattle. The study found that the drivers of sexual differences are widely distributed across the animal's genome, but the sex chromosome seems to play a large role. The genes within these regions are mostly protein-coding and regulatory genes. These genes were involved in biological processes that promote differences between males and females.

Ancestral alleles defined for 70 million cattle variants using a population-based likelihood ratio test.

BACKGROUND: The study of ancestral alleles provides insights into the evolutionary history, selection, and genetic structures of a population. In cattle, ancestral alleles are widely used in genetic analyses, including the detection of signatures of selection, determination of breed ancestry, and identification of admixture. Having a comprehensive list of ancestral alleles is expected to improve the accuracy of these genetic analyses. However, the list of ancestral alleles in cattle, especially at the whole genome sequence level, is far from complete. In fact, the current largest list of ancestral alleles (~ 42 million) represents less than 28% of the total number of detected variants in cattle. To address this issue and develop a genomic resource for evolutionary studies, we determined ancestral alleles in cattle by comparing prior derived whole-genome sequence variants to an out-species group using a population-based likelihood ratio test. RESULTS: Our study determined and makes available the largest list of ancestral alleles in cattle to date (70.1 million) and includes 2.3 million on the X chromosome. There was high concordance (97.6%) of the determined ancestral alleles with those from previous studies when only high-probability ancestral alleles were considered (29.8 million positions) and another 23.5 million high-confidence ancestral alleles were novel, expanding the available reference list to improve the accuracies of genetic analyses involving ancestral alleles. The high concordance of the results with previous studies implies that our approach using genomic sequence variants and a likelihood ratio test to determine ancestral alleles is appropriate. CONCLUSIONS: Considering the high concordance of ancestral alleles across studies, the ancestral alleles determined in this study including those not previously listed, particularly those with high-probability estimates, may be used for further genetic analyses with reasonable accuracy. Our approach that used predetermined variants in species and the likelihood ratio test to determine ancestral alleles is applicable to other species for which sequence level genotypes are available.

Estimating the heritability of nitrogen and carbon isotopes in the tail hair of beef cattle.

BACKGROUND: The natural abundance of nitrogen (δ15N) and carbon (δ13C) isotopes in animal tissues are used to estimate an animal's efficiency in nitrogen utilization, and their feed conversion efficiency, especially in tropical grazing systems with prolonged protein restriction. It is postulated that selection for improving these two characteristics (δ15N and δ13C) would assist the optimisation of the adaptation in ever-changing environments, particularly in response to climate change. The aim of this study was to determine the heritability of δ15N and δ13C in the tail hair of tropically adapted beef cattle to validate their inclusion in genetic breeding programs. METHODS: In total, 492 steers from two breeds, Brahman (n = 268) and Droughtmaster (n = 224) were used in this study. These steers were managed in two mixed breed contemporary groups across two years (year of weaning): steers weaned in 2019 (n = 250) and 2020 (n = 242). Samples of tail switch hair representing hair segments grown during the dry season were collected and analysed for δ15N and δ13C with isotope-ratio mass spectrometry. Heritability and variance components were estimated in a univariate multibreed (and single breed) animal model in WOMBAT and ASReml using three generations of full pedigree. RESULTS: The estimated heritability of both traits was significantly different from 0, i.e. 0.43 ± 0.14 and 0.41 ± 0.15 for δ15N and δ13C, respectively. These traits had favourable moderate to high genetic and phenotypic correlations (- 0.78 ± 0.16 and - 0.40 ± 0.04, respectively). The study also provides informative single-breed results in spite of the limited sample size, with estimated heritability values of 0.37 ± 0.19 and 0.19 ± 0.17 for δ15N and δ13C in Brahman, and 0.36 ± 0.21 and 0.46 ± 0.22 for δ15N and δ13C in Droughtmaster, respectively. CONCLUSIONS: The findings of this study show, for the first time, that the natural abundances of both nitrogen and carbon isotopes in the tail hair in cattle may be moderately heritable. With further research and validation, tail hair isotopes can become a practical tool for the large-scale selection of more efficient cattle.

Unravelling the genetic variability of host resilience to endo- and ectoparasites in Nellore commercial herds.

BACKGROUND: Host resilience (HR) to parasites can affect the performance of animals. Therefore, the aim of this study was to present a detailed investigation of the genetic mechanisms of HR to ticks (TICK), gastrointestinal nematodes (GIN), and Eimeria spp. (EIM) in Nellore cattle that were raised under natural infestation and a prophylactic parasite control strategy. In our study, HR was defined as the slope coefficient of body weight (BW) when TICK, GIN, and EIM burdens were used as environmental gradients in random regression models. In total, 1712 animals were evaluated at five measurement events (ME) at an average age of 331, 385, 443, 498, and 555 days, which generated 7307 body weight (BW) records. Of the 1712 animals, 1075 genotyped animals were used in genome-wide association studies to identify genomic regions associated with HR. RESULTS: Posterior means of the heritability estimates for BW ranged from 0.09 to 0.54 across parasites and ME. The single nucleotide polymorphism (SNP)-derived heritability for BW at each ME ranged from a low (0.09 at ME.331) to a moderate value (0.23 at ME.555). Those estimates show that genetic progress can be achieved for BW through selection. Both genetic and genomic associations between BW and HR to TICK, GIN, and EIM confirmed that parasite infestation impacted the performance of animals. Selection for BW under an environment with a controlled parasite burden is an alternative to improve both, BW and HR. There was no impact of age of measurement on the estimates of genetic variance for HR. Five quantitative trait loci (QTL) were associated with HR to EIM but none with HR to TICK and to GIN. These QTL contain genes that were previously shown to be associated with the production of antibody modulators and chemokines that are released in the intestinal epithelium. CONCLUSIONS: Selection for BW under natural infestation and controlled parasite burden, via prophylactic parasite control, contributes to the identification of animals that are resilient to nematodes and Eimeria ssp. Although we verified that sufficient genetic variation existed for HR, we did not find any genes associated with mechanisms that could justify the expression of HR to TICK and GIN.

Multi-breed genomic predictions and functional variants for fertility of tropical bulls.

Worldwide, most beef breeding herds are naturally mated. As such, the ability to identify and select fertile bulls is critically important for both productivity and genetic improvement. Here, we collected ten fertility-related phenotypes for 6,063 bulls from six tropically adapted breeds. Phenotypes were comprised of four bull conformation traits and six traits directly related to the quality of the bull's semen. We also generated high-density DNA genotypes for all the animals. In total, 680,758 single nucleotide polymorphism (SNP) genotypes were analyzed. The genomic correlation of the same trait observed in different breeds was positive for scrotal circumference and sheath score on most breed comparisons, but close to zero for the percentage of normal sperm, suggesting a divergent genetic background for this trait. We confirmed the importance of a breed being present in the reference population to the generation of accurate genomic estimated breeding values (GEBV) in an across-breed validation scenario. Average GEBV accuracies varied from 0.19 to 0.44 when the breed was not included in the reference population. The range improved to 0.28 to 0.59 when the breed was in the reference population. Variants associated with the gene HDAC4, six genes from the spermatogenesis-associated (SPATA) family of proteins, and 29 transcription factors were identified as candidate genes. Collectively these results enable very early in-life selection for bull fertility traits, supporting genetic improvement strategies currently taking place within tropical beef production systems. This study also improves our understanding of the molecular basis of male fertility in mammals.

Correlation scan: identifying genomic regions that affect genetic correlations applied to fertility traits.

Although the genetic correlations between complex traits have been estimated for more than a century, only recently we have started to map and understand the precise localization of the genomic region(s) that underpin these correlations. Reproductive traits are often genetically correlated. Yet, we don't fully understand the complexities, synergism, or trade-offs between male and female fertility. In this study, we used reproductive traits in two cattle populations (Brahman; BB, Tropical Composite; TC) to develop a novel framework termed correlation scan (CS). This framework was used to identify local regions associated with the genetic correlations between male and female fertility traits. Animals were genotyped with bovine high-density single nucleotide polymorphisms (SNPs) chip assay. The data used consisted of ~1000 individual records measured through frequent ovarian scanning for age at first corpus luteum (AGECL) and a laboratory assay for serum levels of insulin growth hormone (IGF1 measured in bulls, IGF1b, or cows, IGF1c). The methodology developed herein used correlations of 500-SNP effects in a 100-SNPs sliding window in each chromosome to identify local genomic regions that either drive or antagonize the genetic correlations between traits. We used Fisher's Z-statistics through a permutation method to confirm which regions of the genome harboured significant correlations. About 30% of the total genomic regions were identified as driving and antagonizing genetic correlations between male and female fertility traits in the two populations. These regions confirmed the polygenic nature of the traits being studied and pointed to genes of interest. For BB, the most important chromosome in terms of local regions is often located on bovine chromosome (BTA) 14. However, the important regions are spread across few different BTA's in TC. Quantitative trait loci (QTLs) and functional enrichment analysis revealed many significant windows co-localized with known QTLs related to milk production and fertility traits, especially puberty. In general, the enriched reproductive QTLs driving the genetic correlations between male and female fertility are the same for both cattle populations, while the antagonizing regions were population specific. Moreover, most of the antagonizing regions were mapped to chromosome X. These results suggest regions of chromosome X for further investigation into the trade-offs between male and female fertility. We compared the CS with two other recently proposed methods that map local genomic correlations. Some genomic regions were significant across methods. Yet, many significant regions identified with the CS were overlooked by other methods.

Utility of multi-omics data to inform genomic prediction of heifer fertility traits.

Biologically informed single nucleotide polymorphisms (SNPs) impact genomic prediction accuracy of the target traits. Our previous genomics, proteomics, and transcriptomics work identified candidate genes related to puberty and fertility in Brahman heifers. We aimed to test this biological information for capturing heritability and predicting heifer fertility traits in another breed i.e., Tropical Composite. The SNP from the identified genes including 10 kilobases (kb) region on either side were selected as biologically informed SNP set. The SNP from the rest of the Bos taurus genes including 10-kb region on either side were selected as biologically uninformed SNP set. Bovine high-density (HD) complete SNP set (628,323 SNP) was used as a control. Two populations-Tropical Composites (N = 1331) and Brahman (N = 2310)-had records for three traits: pregnancy after first mating season (PREG1, binary), first conception score (FCS, score 1 to 3), and rebreeding score (REB, score 1 to 3.5). Using the best linear unbiased prediction method, effectiveness of each SNP set to predict the traits was tested in two scenarios: a 5-fold cross-validation within Tropical Composites using biological information from Brahman studies, and application of prediction equations from one breed to the other. The accuracy of prediction was calculated as the correlation between genomic estimated breeding values and adjusted phenotypes. Results show that biologically informed SNP set estimated heritabilities not significantly better than the control HD complete SNP set in Tropical Composites; however, it captured all the observed genetic variance in PREG1 and FCS when modeled together with the biologically uninformed SNP set. In 5-fold cross-validation within Tropical Composites, the biologically informed SNP set performed marginally better (statistically insignificant) in terms of prediction accuracies (PREG1: 0.20, FCS: 0.13, and REB: 0.12) as compared to HD complete SNP set (PREG1: 0.17, FCS: 0.10, and REB: 0.11), and biologically uninformed SNP set (PREG1: 0.16, FCS: 0.10, and REB: 0.11). Across-breed use of prediction equations still remained a challenge: accuracies by all SNP sets dropped to around zero for all traits. The performance of biologically informed SNP was not significantly better than other sets in Tropical Composites. However, results indicate that biological information obtained from Brahman was successful to predict the fertility traits in Tropical Composite population.

Prior biological information can be helpful in the genomic prediction of the traits. Previous multi-omics studies by our group identified genes relevant to puberty and fertility in Brahman cattle, a beef breed in northern Australia. We used this biological information in the genomic prediction of three heifer fertility traits, measured in another beef cattle breed: Tropical Composites. The three traits were: pregnancy status after the first mating season (PREG1), first conception score (FCS), and rebreeding score (REB). To test if prior biological information could capture genetic variation in the traits and improve genomic predictions, we compared the results obtained using three subsets of genetic information (i.e., subsets of DNA variants). The first subset contained only variants deemed biologically relevant (as per previous multi-omics studies). The second subset contained only variants considered biologically irrelevant. The third subset had all the variants contained in the commercial DNA assay known as the bovine high-density chip, intended as a practical control. The results indicate that multi-omics data was informative across breed scenario and can be useful in informing genomic predictions of traits of interest.

Bias, dispersion, and accuracy of genomic predictions for feedlot and carcase traits in Australian Angus steers.

BACKGROUND: Improving feedlot performance, carcase weight and quality is a primary goal of the beef industry worldwide. Here, we used data from 3408 Australian Angus steers from seven years of birth (YOB) cohorts (2011-2017) with a minimal level of sire linkage and that were genotyped for 45,152 SNPs. Phenotypic records included two feedlot and five carcase traits, namely average daily gain (ADG), average daily dry matter intake (DMI), carcase weight (CWT), carcase eye muscle area (EMA), carcase Meat Standard Australia marbling score (MBL), carcase ossification score (OSS) and carcase subcutaneous rib fat depth (RIB). Using a 7-way cross-validation based on YOB cohorts, we tested the quality of genomic predictions using the linear regression (LR) method compared to the traditional method (Pearson's correlation between the genomic estimated breeding value (GEBV) and its associated adjusted phenotype divided by the square root of heritability); explored the factors, such as heritability, validation cohort, and phenotype that affect estimates of accuracy, bias, and dispersion calculated with the LR method; and suggested a novel interpretation for translating differences in accuracy into phenotypic differences, based on GEBV quartiles (Q1Q4). RESULTS: Heritability (h2) estimates were generally moderate to high (from 0.29 for ADG to 0.53 for CWT). We found a strong correlation (0.73, P-value < 0.001) between accuracies using the traditional method and those using the LR method, although the LR method was less affected by random variation within and across years and showed a better ability to discriminate between extreme GEBV quartiles. We confirmed that bias of GEBV was not significantly affected by h2, validation cohort or trait. Similarly, validation cohort was not a significant source of variation for any of the GEBV quality metrics. Finally, we observed that the phenotypic differences were larger for higher accuracies. CONCLUSIONS: Our estimates of h2 and GEBV quality metrics suggest a potential for accurate genomic selection of Australian Angus for feedlot performance and carcase traits. In addition, the Q1Q4 measure presented here easily translates into possible gains of genomic selection in terms of phenotypic differences and thus provides a more tangible output for commercial beef cattle producers.

Chromatin accessibility and regulatory vocabulary across indicine cattle tissues.

BACKGROUND: Spatiotemporal changes in the chromatin accessibility landscape are essential to cell differentiation, development, health, and disease. The quest of identifying regulatory elements in open chromatin regions across different tissues and developmental stages is led by large international collaborative efforts mostly focusing on model organisms, such as ENCODE. Recently, the Functional Annotation of Animal Genomes (FAANG) has been established to unravel the regulatory elements in non-model organisms, including cattle. Now, we can transition from prediction to validation by experimentally identifying the regulatory elements in tropical indicine cattle. The identification of regulatory elements, their annotation and comparison with the taurine counterpart, holds high promise to link regulatory regions to adaptability traits and improve animal productivity and welfare. RESULTS: We generate open chromatin profiles for liver, muscle, and hypothalamus of indicine cattle through ATAC-seq. Using robust methods for motif discovery, motif enrichment and transcription factor binding sites, we identify potential master regulators of the epigenomic profile in these three tissues, namely HNF4, MEF2, and SOX factors, respectively. Integration with transcriptomic data allows us to confirm some of their target genes. Finally, by comparing our results with Bos taurus data we identify potential indicine-specific open chromatin regions and overlaps with indicine selective sweeps. CONCLUSIONS: Our findings provide insights into the identification and analysis of regulatory elements in non-model organisms, the evolution of regulatory elements within two cattle subspecies as well as having an immediate impact on the animal genetics community in particular for a relevant productive species such as tropical cattle.

Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle.

Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV.

Meta-Analysis of Heifer Traits Identified Reproductive Pathways in Bos indicus Cattle.

Fertility traits measured early in life define the reproductive potential of heifers. Knowledge of genetics and biology can help devise genomic selection methods to improve heifer fertility. In this study, we used ~2400 Brahman cattle to perform GWAS and multi-trait meta-analysis to determine genomic regions associated with heifer fertility. Heifer traits measured were pregnancy at first mating opportunity (PREG1, a binary trait), first conception score (FCS, score 1 to 3) and rebreeding score (REB, score 1 to 3.5). The heritability estimates were 0.17 (0.03) for PREG1, 0.11 (0.05) for FCS and 0.28 (0.05) for REB. The three traits were highly genetically correlated (0.75-0.83) as expected. Meta-analysis was performed using SNP effects estimated for each of the three traits, adjusted for standard error. We identified 1359 significant SNPs (p-value < 9.9 × 10-6 at FDR < 0.0001) in the multi-trait meta-analysis. Genomic regions of 0.5 Mb around each significant SNP from the meta-analysis were annotated to create a list of 2560 positional candidate genes. The most significant SNP was in the vicinity of a genomic region on chromosome 8, encompassing the genes SLC44A1, FSD1L, FKTN, TAL2 and TMEM38B. The genomic region in humans that contains homologs of these genes is associated with age at puberty in girls. Top significant SNPs pointed to additional fertility-related genes, again within a 0.5 Mb region, including ESR2, ITPR1, GNG2, RGS9BP, ANKRD27, TDRD12, GRM1, MTHFD1, PTGDR and NTNG1. Functional pathway enrichment analysis resulted in many positional candidate genes relating to known fertility pathways, including GnRH signaling, estrogen signaling, progesterone mediated oocyte maturation, cAMP signaling, calcium signaling, glutamatergic signaling, focal adhesion, PI3K-AKT signaling and ovarian steroidogenesis pathway. The comparison of results from this study with previous transcriptomics and proteomics studies on puberty of the same cattle breed (Brahman) but in a different population identified 392 genes in common from which some genes-BRAF, GABRA2, GABR1B, GAD1, FSHR, CNGA3, PDE10A, SNAP25, ESR2, GRIA2, ORAI1, EGFR, CHRNA5, VDAC2, ACVR2B, ORAI3, CYP11A1, GRIN2A, ATP2B3, CAMK2A, PLA2G, CAMK2D and MAPK3-are also part of the above-mentioned pathways. The biological functions of the positional candidate genes and their annotation to known pathways allowed integrating the results into a bigger picture of molecular mechanisms related to puberty in the hypothalamus-pituitary-ovarian axis. A reasonable number of genes, common between previous puberty studies and this study on early reproductive traits, corroborates the proposed molecular mechanisms. This study identified the polymorphism associated with early reproductive traits, and candidate genes that provided a visualization of the proposed mechanisms, coordinating the hypothalamic, pituitary, and ovarian functions for reproductive performance in Brahman cattle.

Network Analyses Predict Small RNAs That Might Modulate Gene Expression in the Testis and Epididymis of Bos indicus Bulls.

Spermatogenesis relies on complex molecular mechanisms, essential for the genesis and differentiation of the male gamete. Germ cell differentiation starts at the testicular parenchyma and finishes in the epididymis, which has three main regions: head, body, and tail. RNA-sequencing data of the testicular parenchyma (TP), head epididymis (HE), and tail epididymis (TE) from four bulls (three biopsies per bull: 12 samples) were subjected to differential expression analyses, functional enrichment analyses, and co-expression analyses. The aim was to investigate the co-expression and infer possible regulatory roles for transcripts involved in the spermatogenesis of Bos indicus bulls. Across the three pairwise comparisons, 3,826 differentially expressed (DE) transcripts were identified, of which 384 are small RNAs. Functional enrichment analysis pointed to gene ontology (GO) terms related to ion channel activity, detoxification of copper, neuroactive receptors, and spermatogenesis. Using the regulatory impact factor (RIF) algorithm, we detected 70 DE small RNAs likely to regulate the DE transcripts considering all pairwise comparisons among tissues. The pattern of small RNA co-expression suggested that these elements are involved in spermatogenesis regulation. The 3,826 DE transcripts (mRNAs and small RNAs) were further subjected to co-expression analyses using the partial correlation and information theory (PCIT) algorithm for network prediction. Significant correlations underpinned the co-expression network, which had 2,216 transcripts connected by 158,807 predicted interactions. The larger network cluster was enriched for male gamete generation and had 15 miRNAs with significant RIF. The miRNA bta-mir-2886 showed the highest number of connections (601) and was predicted to down-regulate ELOVL3, FEZF2, and HOXA13 (negative co-expression correlations and confirmed with TargetScan). In short, we suggest that bta-mir-2886 and other small RNAs might modulate gene expression in the testis and epididymis, in Bos indicus cattle.

Comparison of Genetic Merit for Weight and Meat Traits between the Polled and Horned Cattle in Multiple Beef Breeds.

Breeding for polled animals is deemed the most practical solution to eradicate horns naturally and circumvent management costs and risks on health and welfare. However, there has been a historical reluctance by some farmers to select polled animals due to perceived lower productivity of their calves. This study has compared estimated breeding values (EBVs) between horned and polled animals (N = 2,466,785) for 12 production and carcass traits to assess historical (before 2000) and recent (2000-2018) genetic implications of poll breeding. Older generations of the polled animals in most breeds had significantly lower (Bonferroni-corrected p = 0.05) genetic merits for live (birth to maturity) and carcass weights, milk, meat quality, and fat content traits. Substantial gains of genetic potential were achieved during 2000 to 2018 in each breed, such that polled animals have significantly improved for the majority of traits studied. Generally, polled cohorts showed advantageous EBVs for live and carcass weights irrespective of the lower birth weights in some breeds. While Polled Brahman showed inferior production parameters, the poll genetics' effect size (d) and correlation (r) were very small on recent birth weight (d = -0.30, r = -0.08), 200 days (-0.19, -0.05), 400 days (-0.06, -0.02), 600 days (-0.05, -0.01), mature cow live weight (-0.08, -0.02), and carcass weight (-0.19, -0.05). In conclusion, although there is some evidence that historical selection for polled breeding animals may have reduced productivity, there is strong evidence that more recent selection for polled genotypes in the breeds studied has not resulted in any adverse effects on genetic merit.

Introgression, admixture, and selection facilitate genetic adaptation to high-altitude environments in cattle.

Domestication and subsequent selection of cattle to form breeds and biological types that can adapt to different environments partitioned ancestral genetic diversity into distinct modern lineages. Genome-wide selection particularly for adaptation to extreme environments left detectable signatures genome-wide. We used high-density genotype data for 42 cattle breeds and identified the influence of Bos grunniens and Bos javanicus on the formation of Chinese indicine breeds that led to their divergence from India-origin zebu. We also found evidence for introgression, admixture, and migration in most of the Chinese breeds. Selection signature analyses between high-altitude (≥1800 m) and low-altitude adapted breeds (<1500 m) revealed candidate genes (ACSS2, ALDOC, EPAS1, EGLN1, NUCB2) and pathways that are putatively involved in hypoxia adaptation. Immunohistochemical, real-time PCR and CRISPR/cas9 ACSS2-knockout analyses suggest that the up-regulation of ACSS2 expression in the liver promotes the metabolic adaptation of cells to hypoxia via the hypoxia-inducible factor pathway. High altitude adaptation involved the introgression of alleles from high-altitude adapted yaks into Chinese Bos taurus taurus prior to their formation into recognized breeds and followed by selection. In addition to selection, adaptation to high altitude environments has been facilitated by admixture and introgression with locally adapted cattle populations.

ImmuneDEX: a strategy for the genetic improvement of immune competence in Australian Angus cattle.

In animal breeding and genetics, the ability to cope with disease, here defined as immune competence (IC), with minimal detriment to growth and fertility is a desired objective which addresses both animal production and welfare considerations. However, defining and objectively measuring IC phenotypes using testing methods which are practical to apply on-farm has been challenging. Based on previously described protocols, we measured both cell-mediated immune response (Cell-IR) and antibody-mediated immune response (Ab-IR) and combined these measures to determine an animal's IC. Using a population of 2,853 Australian Angus steers and heifers, we compared 2 alternative methods to combine both metrics into a single phenotype to be used as a tool for the genetic improvement of IC. The first method, named ZMEAN, is obtained by taking the average of the individual metrics after subjecting each to a Z-score standardization. The second, ImmuneDEX (IDEX), is a weighted average that considers the correlation between Cell-IR and Ab-IR, as well as the difference in ranking of individuals by each metric, and uses these as weights in the averaging. Both simulation and real data were used to understand the behavior of ZMEAN and IDEX. To further ascertain the relationship between IDEX and other traits of economic importance, we evaluated a range of traits related to growth, feedlot performance, and carcass characteristics. We report estimates of heritability of 0.31 ± 0.06 for Cell-IR, 0.42 ± 0.06 for Ab-IR, 0.42 ± 0.06 for ZMEAN and 0.370 ± 0.06 for IDEX, as well as a unity genetic correlation (rg) between ZMEAN and IDEX. While a moderately positive rg was estimated between Cell-IR and Ab-IR (rg = 0.33 ± 0.12), strongly positive estimates were obtained between IDEX and Cell-IR (rg = 0.80 ± 0.05) and between IDEX and Ab-IR (rg = 0.85 ± 0.04). We obtained a moderately negative rg between IC traits and growth including an rg = -0.38 ± 0.14 between IDEX and weaning weight, and negligible with carcass fat measurements, including an rg = -0.03 ± 0.12 between IDEX and marbling. Given that breeding with a sole focus on production might inadvertently increase susceptibility to disease and associated antibiotic use, our analyses suggest that ImmuneDEX will provide a basis to breed animals that are both highly productive and with an enhanced ability to resist disease.

Associations between immune competence phenotype and feedlot health and productivity in Angus cattle.

Genetic strategies aimed at improving general immune competence (IC) have the potential to reduce the incidence and severity of disease in beef production systems, with resulting benefits of improved animal health and welfare and reduced reliance on antibiotics to prevent and treat disease. Implementation of such strategies first requires that methodologies be developed to phenotype animals for IC and demonstration that these phenotypes are associated with health outcomes. We have developed a methodology to identify IC phenotypes in beef steers during the yard weaning period, which is both practical to apply on-farm and does not restrict the future sale of tested animals. In the current study, a total of 838 Angus steers, previously IC phenotyped at weaning, were categorized as low (n = 98), average (n = 653), or high (n = 88) for the IC phenotype. Detailed health and productivity data were collected on all steers during feedlot finishing, and associations between IC phenotype, health outcomes, and productivity were investigated. A favorable association between IC phenotype and number of mortalities during feedlot finishing was observed with higher mortalities recorded in low IC steers (6.1%) as compared with average (1.2%, P < 0.001) or high (0%, P = 0.018) IC steers. Disease incidence was numerically highest in low IC steers (15.3 cases/100 animals) and similar in average IC steers (10.1 cases/100 animals) and high IC steers (10.2 cases/100 animals); however, differences between groups were not significant. No significant influence of IC phenotype on average daily gain was observed, suggesting that selection for improved IC is unlikely to incur a significant penalty to production. The potential economic benefits of selecting for IC in the feedlot production environment were calculated. Health-associated costs were calculated as the sum of lost production costs, lost capital investment costs, and disease treatment costs. Based on these calculations, health-associated costs were estimated at AUS$103/head in low IC steers, AUS$25/head in average IC steers, and AUS$4/head in high IC steers, respectively. These findings suggest that selection for IC has the potential to reduce mortalities during feedlot finishing and, as a consequence, improve the health and welfare of cattle in the feedlot production environment and reduce health-associated costs incurred by feedlot operators.

A low-density SNP genotyping panel for the accurate prediction of cattle breeds.

Genomic tools to better define breed composition in agriculturally important species have sparked scientific and commercial industry interest. Knowledge of breed composition can inform multiple scientifically important decisions of industry application including DNA marker-assisted selection, identification of signatures of selection, and inference of product provenance to improve supply chain integrity. Genomic tools are expensive but can be economized by deploying a relatively small number of highly informative single-nucleotide polymorphisms (SNP) scattered evenly across the genome. Using resources from the 1000 Bull Genomes Project we established calibration (more stringent quality criteria; N = 1,243 cattle) and validation (less stringent; N = 864) data sets representing 17 breeds derived from both taurine and indicine bovine subspecies. Fifteen successively smaller panels (from 500,000 to 50 SNP) were built from those SNP in the calibration data that increasingly satisfied 2 criteria, high differential allele frequencies across the breeds as measured by average Euclidean distance (AED) and high uniformity (even spacing) across the physical genome. Those SNP awarded the highest AED were in or near genes previously identified as important signatures of selection in cattle such as LCORL, NCAPG, KITLG, and PLAG1. For each panel, the genomic breed composition (GBC) of each animal in the validation dataset was estimated using a linear regression model. A systematic exploration of the predictive accuracy of the various sized panels was then undertaken on the validation population using 3 benchmarking approaches: (1) % error (expressed relative to the estimated GBC made from over 1 million SNP), (2) % breed misassignment (expressed relative to each individual's breed recorded), and (3) Shannon's entropy of estimated GBC across the 17 target breeds. Our analyses suggest that a panel of just 250 SNP represents an adequate balance between accuracy and cost-only modest gains in accuracy are made as one increases panel density beyond this point.