Category Archives: Journal of Animal Breeding and Genetics

Genetic investigations on backfat thickness and body condition score in German Holstein cattle

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Abstract

Up to now, little has been known about backfat thickness (BFT) in dairy cattle. The objective of this study was to investigate the lactation curve and genetic parameters for BFT as well as its relationship with body condition score (BCS) and milk yield (MKG). For this purpose, a dataset was analysed including phenotypic observations of 1929 German Holstein cows for BFT, BCS and MKG recorded on a single research dairy farm between September 2005 and December 2022. Additionally, pedigree and genomic information was available. Lactation curves were predicted and genetic parameters were estimated for all traits in first to third lactation using univariate random regression models. For BCS, lactation curves had nadirs at 94 DIM, 101 DIM and 107 DIM in first, second and third lactation. By contrast, trajectories of BFT showed lowest values later in lactation at 129 DIM, 117 DIM and 120 DIM in lactation numbers 1 to 3, respectively. Although lactation curves of BCS and BFT had similar shapes, the traits showed distinct sequence of curves for lactation number 2 and 3. Cows in third lactation had highest BCS, whereas highest BFT values were found for second parity animals. Average heritabilities were 0.315 ± 0.052, 0.297 ± 0.048 and 0.332 ± 0.061 for BCS in lactation number 1 to 3, respectively. Compared to that, BFT had considerably higher heritability in all lactation numbers with estimates ranging between 0.357 ± 0.028 and 0.424 ± 0.034. Pearson correlation coefficients between estimated breeding values for the 3 traits were negative between MKG with both BCS (r = −0.245 to −0.322) and BFT (r = −0.163 to −0.301). Correlation between traits BCS and BFT was positive and consistently high (r = 0.719 to 0.738). Overall, the results of this study suggest that BFT and BCS show genetic differences in dairy cattle, which might be due to differences in depletion and accumulation of body reserves measured by BFT and BCS. Therefore, routine recording of BFT on practical dairy farms could provide valuable information beyond BCS measurements and might be useful, for example, to better assess the nutritional status of cows.

A review of the role of transcription factors in regulating adipogenesis and lipogenesis in beef cattle

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In the past few decades, genomic selection and other refined strategies have been used to increase the growth rate and lean meat production of beef cattle. Nevertheless, the fast growth rates of cattle breeds are often accompanied by a reduction in intramuscular fat (IMF) deposition, impairing meat quality. Transcription factors play vital roles in regulating adipogenesis and lipogenesis in beef cattle. Meanwhile, understanding the role of transcription factors in regulating adipogenesis and lipogenesis in beef cattle has gained significant attention to increase IMF deposition and meat quality. Therefore, the aim of this paper was to provide a comprehensive summary and valuable insight into the complex role of transcription factors in adipogenesis and lipogenesis in beef cattle. This review summarizes the contemporary studies in transcription factors in adipogenesis and lipogenesis, genome-wide analysis of transcription factors, epigenetic regulation of transcription factors, nutritional regulation of transcription factors, metabolic signalling pathways, functional genomics methods, transcriptomic profiling of adipose tissues, transcription factors and meat quality and comparative genomics with other livestock species. In conclusion, transcription factors play a crucial role in promoting adipocyte development and fatty acid biosynthesis in beef cattle. They control adipose tissue formation and metabolism, thereby improving meat quality and maintaining metabolic balance. Understanding the processes by which these transcription factors regulate adipose tissue deposition and lipid metabolism will simplify the development of marbling or IMF composition in beef cattle.

Genomic predictions and GWAS for heat tolerance in pigs based on reaction norm models with performance records and data from public weather stations considering alternative temperature thresholds

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Abstract

Genetic improvement of livestock productivity has resulted in greater production of metabolic heat and potentially greater susceptibility to heat stress. Various studies have demonstrated that there is genetic variability for heat tolerance and genetic selection for more heat tolerant individuals is possible. The rate of genetic progress tends to be greater when genomic information is incorporated into the analyses as more accurate breeding values can be obtained for young individuals. Therefore, this study aimed (1) to evaluate the predictive ability of genomic breeding values for heat tolerance based on routinely recorded traits, and (2) to investigate the genetic background of heat tolerance based on single-step genome-wide association studies for economically important traits related to body composition, growth and reproduction in Large White pigs. Pedigree information was available for 265,943 animals and genotypes for 8686 animals. The studied traits included ultrasound backfat thickness (BFT), ultrasound muscle depth (MDP), piglet weaning weight (WW), off-test weight (OTW), interval between farrowing (IBF), total number of piglets born (TNB), number of piglets born alive (NBA), number of piglets born dead (NBD), number of piglets weaned (WN) and weaning-to-estrus interval (IWE). The number of phenotypic records ranged from 6059 (WN) to 172,984 (TNB). Single-step genomic reaction norm predictions were used to calculate the genomic estimated breeding values for each individual. Predictions of breeding values for the validation population individuals were compared between datasets containing phenotypic records measured in the whole range of temperatures (WR) and datasets containing only phenotypic records measured when the weather station temperature was above 10°C (10C) or 15°C (15C), to evaluate the usefulness of these datasets that may better reflect the within-barn temperature. The use of homogeneous or heterogeneous residual variance was found to be trait-dependent, where homogeneous variance presented the best fit for MDP, BFT, OTW, TNB, NBA, WN and IBF, while the other traits (WW and IWE) had better fit with heterogeneous variance. The average prediction accuracy, dispersion and bias values considering all traits for WR were 0.36 ± 0.05, −0.07 ± 0.13 and 0.76 ± 0.10, respectively; for 10C were 0.39 ± 0.02, −0.05 ± 0.07 and 0.81 ± 0.05, respectively; and for 15C were 0.32 ± 0.05, −0.05 ± 0.11 and 0.84 ± 0.10, respectively. Based on the studied traits, using phenotypic records collected when the outside temperature (from public weather stations) was above 10°C provided better predictions for most of the traits. Forty-three and 62 candidate genomic regions were associated with the intercept (overall performance level) and slope term (specific biological mechanisms related to environmental sensitivity), respectively. Our results contribute to improve genomic predictions using existing datasets and better understand the genetic background of heat tolerance in pigs. Furthermore, the genomic regions and candidate genes identified will contribute to future genomic studies and breeding applications.

Pedigree diversity and implications for genetic selection of Katahdin sheep

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The Katahdin hair breed gained popularity in the United States as low input and prolific, with a propensity to exhibit parasite resistance. With the introduction of genomically enhanced estimated breeding values (GEBV) to the Katahdin genetic evaluation, defining the diversity present in the breed is pertinent. Utilizing pedigree records (n = 92,030) from 1984 to 2019 from the National Sheep Improvement Program, our objectives were to (i) estimate the completeness and quality of the pedigree, (ii) calculate diversity statistics for the whole pedigree and relevant reference subpopulations and (iii) assess the impact of current diversity on genomic selection. Reference 1 was Katahdins born from 2017 to 2019 (n = 23,494), while reference 2 was a subset with at least three generations of Katahdin ancestry (n = 9327). The completeness of the whole pedigree, and the pedigrees of reference 1 and reference 2, were above 50% through the fourth, fifth and seventh generation of ancestors, respectively. Effective population size (N e) averaged 111 animals with a range from 42.2 to 451.0. The average generation interval was 2.9 years for the whole pedigree and reference 1, and 2.8 years for reference 2. The mean individual inbreeding and average relatedness coefficients were 1.62% and 0.91%, 1.74% and 0.90% and 2.94% and 1.46% for the whole pedigree, reference 1, and reference 2, respectively. There were over 300 effective founders in the whole pedigree and reference 1, with 169 in reference 2. Effective number of ancestors were over 150 for the whole pedigree and reference 1, while there were 67 for reference 2. Prediction accuracies increased as the reference population grew from 1k to 7.5k and plateaued at 15k animals. Given the large number of founders and ancestors contributing to the base genetic variation in the breed, the N e is sufficient to maintain diversity while achieving progress with selection. Stable low rates of inbreeding and relatedness suggest that incorporating genetic conservation in breeding decisions is currently not of high priority. Current N e suggests that with limited genotyping, high levels of accuracy for genomic prediction can be achieved. However, intense selection on GEBV may cause loss of genetic diversity long term.

Longevity in South African Afrikaner cows as assessed through survival analysis

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The Afrikaner breed of cattle is indigenous to South Africa and, due to their hardiness, was once the most popular breed amongst South African farmers, although in recent years their numbers have decreased. The goal of this study was to assess factors affecting length of productive life, defined as the interval between production of the first and last calf, in Afrikaner cattle using survival analysis. The data spanned 40 years with an observed measure of length of life for 29,379 cows from 374 herds. Relative to similar analyses, few (n = 2964; 8.4%) cows had records that were right censored. The median length of productive life of an Afrikaner cow was just less than 6 years. Cows that were younger at their first parturition had longer productive lives than those that were older at their first calving. Cows that were born in the period from December to February had shorter productive lives than those born between March and November. The estimated animal genetic variance of 0.266 resulted in a heritability estimate for length of productive life in Afrikaner cattle of 0.225. Thus, there appeared to be sufficient additive genetic variance in Afrikaner cattle to enable genetic improvement in their length of productive life.

Characteristics of restricted selection indices and geometrical interpretation of restricted breeding values

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Restricted selection is used to control genetic changes in one or more characters. Three main selection indices are adopted for this purpose. First, Kempthorne's index is used to maximize aggregate breeding value (BV) with changes in some traits restricted to zero; second, Harville's index is used to maximize aggregate BV with proportional changes for some traits; and third, Yamada's index is mathematically used to achieve the relative desired changes for all traits. Kempthorne's index is equivalent to Harville's index. However, the relationship between Kempthorne's and Yamada's indices has not been clarified. In addition, the characteristics of restricted selection indices and the relationship between BV and restricted BV (RBV) are also unknown. The aim of this study was to clarify the characteristics of restricted selection indices and describe the relationship between BV and RBV by using linear algebra and geometric techniques, respectively. First, I proved that Yamada's index is part of Kempthorne's index. Second, I investigated the relationship between BVs that were estimated using an ordinary selection index (EBVs) and RBVs estimated using a restricted selection index (ERBVs) and proved that the ERBVs of the restricted traits are proportional to the relative desired changes. Third, I proved that RBV is represented by a linear function of BV and geometrically represented the relationship between BV and RBV. In this study, new findings on restricted selection indices and RBV were obtained. This useful clarification of the relationship between BV and RBV will make it possible to evaluate the response to selection using not only a restricted selection index, but also a restricted BLUP in computer simulation studies.

Microsatellite imputation using SNP data for parentage verification in four Italian sheep breeds

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Microsatellite markers (MS) have been widely used for parentage verification in most of the livestock species over the past decades mainly due to their high polymorphic information content. In the genomic era, the spread of genotype information as single-nucleotide polymorphism (SNP) has raised the question to effectively use SNPs also for parentage testing. Despite the clear advantages of SNP panels in terms of cost, accuracy, and automation, the transition from MS to SNP markers for parentage verification is still very slow and, so far, only routinely applied in cattle. A major difficulty during this transition period is the need of SNP data for parents and offspring, which in most cases is not yet feasible due to the genotyping cost. To overcome the unavailability of same genotyping platform during the transition period, in this study we aimed to assess the feasibility of a MS imputation pipeline from SNPs in four native sheep dairy breeds: Comisana (N = 331), Massese (N = 210), Delle Langhe (N = 59) and Sarda (N = 1003). Those sheep were genotyped for 11 MS and with the Ovine SNP50 Bead Chip. Prior to imputation, a quality control (QC) was performed, and SNPs located within a window of 2 Mb from each MS were selected. The core of the developed pipeline was made up of three steps: (a) storing of both MS and SNP data in a Variant Call Format file, (b) masking MS information in a random sample of individuals (10%), (c) imputing masked MS based on non-missing individuals (90%) using an imputation program. The feasability of the proposed methodology was assessed also among different training − testing split ratio, population size, number of flanking SNPs as well as within and among breeds. The accuracy of the MS imputation was assessed based on the genotype concordance as well as at parentage verification level in a subset of animals in which assigned parents' MS were available. A total of 8 MS passed the QC, and 505 SNPs were located within the ±2 Mb window from each MS, with an average of 63 SNPs per MS. The results were encouraging since when excluding the worst imputed MS (OARAE129), and regardless on the analyses performed (within and across breeds) for all breeds, we achieved an overall concordance rate over 94%. In addition, on average, the imputed offspring MS resulted in equivalent parentage outcome in 94% of the cases when compared to verification using original MS, highlighting both the feasibility and the eventual practical advantage of using this imputation pipeline.

Genomic analysis of feed efficiency traits in beef cattle using random regression models

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Feed efficiency plays a major role in the overall profitability and sustainability of the beef cattle industry, as it is directly related to the reduction of the animal demand for input and methane emissions. Traditionally, the average daily feed intake and weight gain are used to calculate feed efficiency traits. However, feed efficiency traits can be analysed longitudinally using random regression models (RRMs), which allow fitting random genetic and environmental effects over time by considering the covariance pattern between the daily records. Therefore, the objectives of this study were to: (1) propose genomic evaluations for dry matter intake (DMI), body weight gain (BWG), residual feed intake (RFI) and residual weight gain (RWG) data collected during an 84-day feedlot test period via RRMs; (2) compare the goodness-of-fit of RRM using Legendre polynomials (LP) and B-spline functions; (3) evaluate the genetic parameters behaviour for feed efficiency traits and their implication for new selection strategies. The datasets were provided by the EMBRAPA–GENEPLUS beef cattle breeding program and included 2920 records for DMI, 2696 records for BWG and 4675 genotyped animals. Genetic parameters and genomic breeding values (GEBVs) were estimated by RRMs under ssGBLUP for Nellore cattle using orthogonal LPs and B-spline. Models were compared based on the deviance information criterion (DIC). The ranking of the average GEBV of each test week and the overall GEBV average were compared by the percentage of individuals in common and the Spearman correlation coefficient (top 1%, 5%, 10% and 100%). The highest goodness-of-fit was obtained with linear B-Spline function considering heterogeneous residual variance. The heritability estimates across the test period for DMI, BWG, RFI and RWG ranged from 0.06 to 0.21, 0.11 to 0.30, 0.03 to 0.26 and 0.07 to 0.27, respectively. DMI and RFI presented within-trait genetic correlations ranging from low to high magnitude across different performance test-day. In contrast, BWG and RWG presented negative genetic correlations between the first 3 weeks and the other days of performance tests. DMI and RFI presented a high-ranking similarity between the GEBV average of week eight and the overall GEBV average, with Spearman correlations and percentages of individuals selected in common ranging from 0.95 to 1.00 and 93 to 100, respectively. Week 11 presented the highest Spearman correlations (ranging from 0.94 to 0.98) and percentages of individuals selected in common (ranging from 85 to 94) of BWG and RWG with the average GEBV of the entire period of the test. In conclusion, the RRM using linear B-splines is a feasible alternative for the genomic evaluation of feed efficiency. Heritability estimates of DMI, RFI, BWG and RWG indicate enough additive genetic variance to achieve a moderate response to selection. A new selection strategy can be adopted by reducing the performance test to 56 days for DMI and RFI selection and 77 days for BWG and RWG selection.