Bailey N. Engle

Reproductive longevity is directly related to a cow’s lifetime productivity and cumulative economic value, making it one of the most important influences on herd profitability. Therefore, it would be advantageous to identify component traits correlated to longevity that can be measured and used as selection criteria in young replacement prospects. A herd of Bos indicus–Bos taurus crossbred cows (n = 293) were used to (i) characterize the relationship between first-parity calving season period with subsequent longevity and cow productivity and (ii) assess the influence of the cow’s birth period on her potential for stayability and productivity. Calving period was assigned by designating each of the calving seasons into four 21-d periods, and each cow was assigned a score of 1–4 for the time period of her first parturition and her own birth. The relationship between calving period and stayability to ages 3, 4, 5, 6, and 7 yr of age, first and lifetime average calving intervals, first-calf weight, lifetime average calf weights, and cumulative calf weight weaned were evaluated. There was a clear advantage for heifers calving within the first 21 d of the calving season as their calves were heavier at weaning (P < 0.05) and demonstrated greater preweaning weight gain (P < 0.05). This was further reflected in long-term productivity, as cows that calved in the first 21-d period of their first-parity calving season produced greater average calf crop weaned (P < 0.05) and greater cumulative calf crop weaned (P < 0.05) than cows that calved later in their first season. These early-calving heifers were more likely to meet stayability benchmarks at 3, 4, 5, 6, and 7 yr than heifers calving at later periods in the season (P < 0.05). Earlier born cows had a higher probability of heifer pregnancy (P < 0.05) and were heavier at first-calf weaning (P < 0.05), possibly because they were older at first calving (P < 0.05). Due to the advantages to both maternal productivity and calf performance, calving within the first 21 d of an annual calving season is expected to increase the herd longevity of these females, and may be considered as an earlier-in-life evaluation criterion when selecting for longevity or lifetime productivity in B. indicus-B. taurus crossbred beef cows.

Low-coverage sequencing refers to sequencing DNA of individuals to a low depth of coverage (e.g., 0.5X) and imputing that sequence to a genomic sequence based on reference haplotypes from individuals sequenced to a high depth of coverage (e.g., ≥10X). It has been proposed as an alternative to genotyping by Single-nucleotide polymorphisms (SNP) arrays. At least one commercial product based on it is available for agricultural species. Concerns limiting adoption in its current form are: 1) the cost of storing the huge volume of data it generates and 2) whether that additional data will result in improved accuracy of genetic evaluation. This work envisions future implementation of low-coverage sequencing to reduce storage costs and enhance genetic evaluations by leveraging the additional information in the full sequence of the pangenome to account for more genetic variation. We propose addressing the storage issue by representing genomic sequence of an individual in a pair of haplotype arrays with each element pointing to an enumerated haplotype of the sequence within one of approximately 50,000 defined genome segments. Assuming 60 million genomic variants, the infrastructure required to translate the identifier of any enumerated haplotype into its genomic sequence would require less than 10 gigabytes of binary storage. Each haplotype array element would require 2 bytes, so the marginal binary storage required to represent the genomic sequence of an individual would be about 200 kilobytes (KB), similar to the genotypes from a SNP array with 200,000 markers. This assumes no pedigree and no ambiguity of the imputation, though the latter is unrealistic. Strategies to minimize, and when necessary, to manage and efficiently represent ambiguity are proposed. The genomic sequence of an individual could be stored in about 1 KB (binary) if both parents have unambiguous sequences stored as described above. The proposed system for representing the pangenome includes algorithms for read mapping and imputation intended to leverage all known genetic variation in the target population. It is also designed to use sequencing reads generated for imputing the genomic sequence of new individuals to identify unrecognized mutations, crossovers, and structural variants, thus continuously improving the genome representation, especially if widespread use of low-coverage sequencing in livestock industries is realized. This could make improved genetic merit and management of livestock feasible without computational burden.

Heterosis, or hybrid vigor, is traditionally defined as the advantage of crossbred progeny relative to the average performance of their purebred parents. This advantage is due to increased heterozygosity in these crosses, which increases phenotypic expression in traits influenced by non-additive gene action. These heterosis effects may vary depending on the breed of animals in the original cross; however, breed-specific estimates are difficult to obtain because of a lack of contemporary comparisons among crossbred and purebred cattle. The Germplasm Evaluation Program at the U.S. Meat Animal Research Center was designed to evaluate 18 of the most highly utilized beef breeds in the United States and enable contemporary comparisons among purebreds and their crosses. Therefore, the primary objective of this study was to quantify the differences in breed-specific heterosis for growth and carcass traits in these 18 U.S. beef breeds. Specific traits analyzed were direct and maternal birth weight, direct and maternal 205d adjusted weaning weight, 365 d postweaning gain, marbling score, ribeye area, backfat thickness, and carcass weight. Specific heterosis effects were estimated using 2 different models: 1) a biological-group heterosis model where heterosis was estimated for crosses between British, Continental, and Brahman as breed groups, and 2) an average breed heterosis model where heterosis was estimated as the regression on average predicted breed heterozygosity arising from mating each of the 18 breeds to a randomly chosen animal in the population. Each model also included a random breed-specific cross-effect for each pair of breeds. Biological-group heterosis, or the expected deviations from a purebred mean between all crosses of British, Brahman, and Continental groups, was found for all traits (P < 0.0001), except marbling. The greatest increases in calf performance were estimated for crosses containing Brahman, especially for growth traits and maternal ability. Average breed-specific heterosis was also significant (P < 0.05) under the second model for all traits except marbling and maternal birth weight. Again, the greatest increase in calf performance across a majority of traits was found to be the result of crosses with Brahman. These estimates may be used by breeders to make more informed crossbreeding decisions and to tailor their choice of breeds to their specific production environment and breeding objectives.

Most genetic variants associated with fertility in mammals fall in non-coding regions of the genome and it is unclear how these variants affect fertility. Here we use genome-wide association summary statistics for Heifer puberty (pubertal or not at 600 days) from 27,707 Bos indicus, Bos taurus and crossbred cattle; multi-trait GWAS signals from 2119 indicine cattle for four fertility traits, including days to calving, age at first calving, pregnancy status, and foetus age in weeks (assessed by rectal palpation of the foetus); and expression quantitative trait locus for whole blood from 489 indicine cattle, to identify 87 putatively functional genes affecting cattle fertility. Our analysis reveals a significant overlap between the set of cattle and previously reported human fertility-related genes, impling the existence of a shared pool of genes that regulate fertility in mammals. These findings are crucial for developing approaches to improve fertility in cattle and potentially other mammals.

Polled cattle, or those that are naturally hornless, are highly advantageous from both an economic and animal welfare perspective. While there are a number of different mutations that result in a polled phenotype, a duplication on bovine chromosome 1, referred to as the Celtic mutation, is the most common within beef cattle. Tropically adapted beef cattle typically have some degree of indicine influence, which are all naturally horned breeds. Polled genes must therefore be introgressed into tropically adapted cattle from naturally polled breeds, such as Angus, carrier of the Celtic mutation. However, Angus are not as well suited for hot, humid climates and introgression cannot happen at the expense of productivity or adaptation. Therefore, strategies must be developed to balance the introgression of poll alleles into a population with continued genetic improvement for economically important traits. This study utilized a privately owned, commercial population of admixed cattle to address this challenge. These cattle (n = ~3,000; single year cohort) were previously genotyped and SNP effects were estimated for heifer pregnancy as part of the internal genetic evaluation of the private enterprise. Management and selection of male and female replacements were modelled using actual production parameters in a digital twin framework. Four different breeding systems, multi-sire natural service, artificial insemination, and invitro fertilization collecting either five or 10 oocytes, were modelled and compared with account for differences in selection intensity. Selection index weighting of poll vs heifer pregnancy was modelled in eight different combinations. Genetic crosses were then simulated using the real genotypes in the genomicSimulation package in R for 5, 10, and 30 years of crosses to evaluate long and short-term consequences. We found that this approach of combining digital twin modelling with simulated crosses can be used to identify the selection strategy that should be applied to optimally balance selection for poll and economically important traits, such as fertility. This modelling approach provides a framework that may be customized to fit specific production parameters or genetic populations representing individual operations. More generally, this particular study used cattle and management practices representative of the northern Australian beef industry, and may be used as a reference for producers in that production system of strategies for increasing the rate of polled animals in their herds. Furthermore, this approach may be applied to the selection for or against other single gene traits, such as many genetic disorders. The USDA is an equal opportunity provider and employer.

Many of the world’s agriculturally important plant and animal populations consist of hybrids of subspecies. Cattle in tropical and sub-tropical regions for example, originate from two subspecies, Bos taurus indicus (Bos indicus) and Bos taurus taurus (Bos taurus). Methods to derive the underlying genetic architecture for these two subspecies are essential to develop accurate genomic predictions in these hybrid populations. We propose a novel method to achieve this. First, we use haplotypes to assign SNP alleles to ancestral subspecies of origin in a multi-breed and multi-subspecies population. Then we use a BayesR framework to allow SNP alleles originating from the different subspecies differing effects. Applying this method in a composite population of B. indicus and B. taurus hybrids, our results show that there are underlying genomic differences between the two subspecies, and these effects are not identified in multi-breed genomic evaluations that do not account for subspecies of origin effects. The method slightly improved the accuracy of genomic prediction. More significantly, by allocating SNP alleles to ancestral subspecies of origin, we were able to identify four SNP with high posterior probabilities of inclusion that have not been previously associated with cattle fertility and were close to genes associated with fertility in other species. These results show that haplotypes can be used to trace subspecies of origin through the genome of this hybrid population and, in conjunction with our novel Bayesian analysis, subspecies SNP allele allocation can be used to increase the accuracy of QTL association mapping in genetically diverse populations.

Many of the world’s agriculturally important plant and animal populations consist of hybrids of subspecies. Cattle in tropical and sub-tropical regions for example, originate from two genetically distinct subspecies, Bos indicus and Bos taurus. Methods to derive the underlying genetic architecture for these two subspecies are essential to develop accurate genomic predictions in these hybrid populations. We propose a novel method to achieve this. First, we use haplotypes to assign single nucleotide polymorphism (SNP) alleles to ancestral subspecies-of-origin in a multi-breed and multi-subspecies population. Then we use a BayesR framework to allow SNP alleles originating from the different subspecies to have different effects (unequal variances). Applying this method in a composite population of B. indicus and B. taurus hybrids, our results show that there are underlying genomic differences between the two subspecies, and these effects are not identified in multi-breed genomic evaluations that do not account for subspecies-of-origin effects. The method slightly improved the accuracy of genomic prediction. More significantly, by allocating SNP alleles to ancestral subspecies-of-origin, we were able to identify four SNP with high posterior probabilities of inclusion that have not been previously associated with cattle fertility and were very close to genes associated with fertility in other species. These results show that haplotypes can be used to trace subspecies-of-origin through the genome of this hybrid population and, in conjunction with our novel Bayesian analysis, subspecies SNP allele allocation can be used to increase the accuracy of quantitative trait loci (QTL) association mapping in genetically diverse populations.

Background Genomic prediction describes the use of SNP genotypes to predict complex phenotypes and has been widely applied in humans and agriculture species. Genotyping-by-sequencing, a method which uses low-coverage sequence data paired with genotype imputation, is becoming increasingly popular for SNP genotyping. The development of Oxford Nanopore Technologies’ (ONT) MinION sequencer has now made genotyping-by-sequencing portable and rapid. Here we evaluate the speed and accuracy of genomic predictions using low-coverage ONT sequence data in a population of cattle using four imputation approaches. We also investigate the effect of SNP reference panel size on their performance. Results SNP array genotypes and ONT sequence data for 64 beef heifers were used to calculate genomic estimated breeding values (GEBVs) from 641k SNP for four traits. Accuracy of the GEBVs was much higher when flanking SNP from sequence data was used to help impute the 641k panel used for genomic predictions. Using the imputation package QUILT, correlations between ONT and low-density SNP array genomic breeding values were greater than 0.91 and up to 0.97 for sequencing coverages as low as 0.1x using a panel of 48 million SNP that flanked the 641k in the prediction equation. Imputation time was significantly reduced by decreasing the number of flanking sequence SNP used in imputation for all methods. Genomic breeding values calculated using QUILT also had higher correlations to high density SNP arrays than genomic breeding values from imputed-low density arrays for coverages as low as 0.5x. Conclusions Here we demonstrated accurate genomic prediction is possible with ONT sequence data from sequencing coverages as low as 0.1x, and imputation time can be as short as 10 minutes per sample.

The northern Australia beef cattle industry operates in harsh environmental conditions which consistently suppress female fertility. To better understand the environmental effect on cattle raised extensively in northern Australia, new environmental descriptors were defined for 54 commercial herds located across the region. Three fertility traits, based on the presence of a corpus luteum at 600 d of age, indicating puberty, (CL Presence, n = 25,176), heifer pregnancy (n = 20,989) and first lactation pregnancy (n = 10,072) were recorded. Temperature, humidity, and rainfall were obtained from publicly available data based on herd location. Being pubertal at 600 d (i.e. CL Presence) increased the likelihood of success at heifer pregnancy and first lactation pregnancy (P < 0.05), underscoring the importance of early puberty in reproductive success. A temperature humidity index (THI) of 65–70 had a significant (P < 0.05) negative effect on first lactation pregnancy rate, heifer pregnancy and puberty at 600 d of age. Area under the curve of daily THI was significant (P < 0.05) and reduced the likelihood of pregnancy at first lactation and puberty at 600 days. Deviation from long-term average rainfall was not significant (P < 0.05) for any trait. Average daily weight gain had a significant and positive relationship (P < 0.05) for heifer and first lactation pregnancy. The results indicate that chronic or cumulative heat load is more determinantal to reproductive performance than acute heat stress. The reason for the lack of a clear relationship between acute heat stress and reproductive performance is unclear but may be partially explained by peak THI and peak nutrition coinciding at the same time. Sufficient evidence was found to justify the use of average daily weight gain and chronic heat load as descriptors to define an environmental gradient.

Variation in the genome region coding for PLAG1 has well-documented associations with skeletal growth and age at puberty in cattle. However, the influence of PLAG1 on other economically important traits such as cow stayability has not yet been explored. Here we investigate the effect of PLAG1 variation on early and later in life female fertility, as well as size and growth, in a well-phenotyped Australian Brahman herd. Yearly pregnancy and productivity records were collected from 2,839 genotyped Brahman cows and used to generate fertility, growth, and weight phenotypes. A variant on chromosome 14 in PLAG1 (NC_037341.1:g.23338890G>T, rs109815800) was previously determined to be a putative causative mutation associated with variation in cattle stature. The imputed PLAG1 genotype at this variant was isolated for each animal and the effect of PLAG1 genotype on each trait was estimated using linear modeling. Regardless of how heifer fertility was measured, there was a significant (P < 0.05) and desirable relationship between the additive effects of PLAG1 genotype and successful heifer fertility. Heifers with two copies of the alternate allele (TT) conceived earlier and had higher pregnancy and calving rates. However, the effects of PLAG1 genotype on fertility began to diminish as cows aged and did not significantly influence stayability at later ages. While there was no effect of genotype on growth, PLAG1 had a negative effect on mature cow weight (P < 0.01), where females with two copies of the alternate allele (TT) were significantly smaller than those with either one or none. Selection emphasis on improved Brahman heifer fertility will likely increase the frequency of the T allele of rs109815800, which may also increase herd profitability and long-term sustainability through improved reproductive efficiency and reduced mature cow size. PLAG1 is a gene with allelic variation that has well-documented associations with stature and age at puberty in cattle. Here we extend knowledge of the effect of the PLAG1 alleles to later in life female fertility, as well as size and growth, in Australian Brahmans. Records were collected from 2,839 genotyped Brahman cows and used to generate fertility, growth, and weight phenotypes. A variant on chromosome 14 in PLAG1 (rs109815800) was previously determined to be highly associated with variation in cattle stature. The allele combination (the genotype) at this position was isolated for each animal and the effect of PLAG1 genotype on each trait was estimated using linear modeling. Regardless of how heifer fertility was measured, there was a significant and desirable relationship between PLAG1 genotype and successful heifer fertility. However, the effects of allele combination on fertility began to diminish as cows aged and did not significantly influence stayability at later ages. While there was no effect of genotype on growth, PLAG1 had a negative effect on mature cow weight. Selection emphasis on improved Brahman heifer fertility will likely increase the frequency of the desirable PLAG1 allele, which may have additional benefits on herd profitability and long-term sustainability.