Reproductive efficiency is a crucial factor in the sustainability and profitability of buffalo production systems. However, genetic improvement of reproductive traits is challenging due to low heritability, environmental sensitivity, limited recording, and shrinking reference populations caused by crossbreeding. This study aimed to estimate genetic parameters and detect the genomic architecture of key reproductive traits in Egyptian buffalo using pedigree-based analyses and genome-wide association studies (GWAS). Over a 44-year period (1980-2024), reproductive records from five Egyptian experimental herds were analysed. The dataset comprised 2843 buffalo cows, sired by 140 bulls and out of 1328 dams. In total, 2359 records were available for age at first calving (AFC), 10,478 for gestation length (GL), 7966 for calving interval (CI), 6705 for days open (DO), and 12,909 for calving ease (CE) and stillbirth (SB). For genome-wide association analysis, 275 Egyptian buffaloes were genotyped using the Affymetrix Buffalo 90 K array, and 66,295 high-quality SNPs were retained after quality control. De-regressed proofs derived from pedigree-based genetic evaluations were used as response variables in a mixed linear model implemented in the rMVP package. Genome-wide association analysis identified putative genomic regions associated with GL, CI, CE, and SB, whereas no genome-wide significant associations were detected for AFC and DO. Functional annotation and QTL enrichment analyses were subsequently used to provide exploratory biological context for the identified genomic regions. Heritability estimates were generally low: 0.16 for AFC, 0.06 for GL, 0.02 for CI, 0.02 for DO, 0.18 for CE, and 0.06 for SB. Manhattan plots revealed that 15 genomic regions containing significant SNPs were identified on chromosomes 2, 4, 10, 12, 13, 15, 19, 20, and 25 for the reproductive traits of GL, CI, CE, and SB. These findings provide preliminary evidence of genomic regions potentially contributing to variation in reproductive traits in Egyptian buffalo, although the relatively small number of genotyped animals limits the power to detect and validate small effect loci. Seven significant genomic regions on chromosomes 10, 13, 15, 20, and 25 were associated with the GL trait. Additionally, three suggestive SNPs mapped to chromosomes 2 and 19 were associated with the CE trait, and three suggestive SNPs mapped on chromosome 12 were significantly associated with the SB trait. The results of KEGG enrichment analyses and QTL classification analyses for reproductive traits in Egyptian buffalo suggest that candidate genes within known QTL may be involved in complex biological networks involving immune competence, cellular homeostasis, and systemic physiological resilience. Among the enriched pathways, Fc gamma R-mediated phagocytosis, protein export, viral myocarditis, and arrhythmogenic right ventricular cardiomyopathy (ARVC) were highlighted. Most annotated genomic regions (QTL) were related to reproductive traits (63.4%), followed by 17.3% for milk production traits, 9.95% for general production traits, 3.47% for meat and carcass traits, 3.71% for body conformation and robustness exterior traits, and 2.08% for health traits.
Although linear type traits have been under selection in the Dairy Gir cattle for the past three decades, there are few studies exploring genetic architecture for these traits. The aim of this study was to identify candidate genes for anogenital distance and linear type traits in the Gir breed. For this study, the body measures of rump length (cm, RL), ilium width (cm, ILW), hip height (cm, HH), body length (cm, BL), thoracic perimeter (cm, TP) and rump area (cm2, RA) along with anogenital distance (cm, AGD) were collected from 604 Gir dairy cows, around 5.69 years old. The pedigree file included 2206 animals, of which 742 were genotyped with different SNP panels and imputed to Illumina BovineHD BeadChip (777 K). Genome-wide association studies were carried out using the blupf90+ program for all traits and for a phenotypic index created to assist selecting candidate genes. The top 5 windows for the traits and top 10 windows for the index explaining the highest percentage of additive genetic variance were selected for gene search. Biological processes and transcription factors were searched from the genes found. In total, 90 genes were identified for all seven traits, of which 17 were pleiotropic, that is, they were common results for pairs or trios of traits. From that, the candidate genes (chromosome) identified from the phenotypic index were CXCL13 (6), CNOT6L (6), MRPL1 (6), CCSER1 (6), CDH26 (13), (8), (8) and (8). For those eight genes, 11 transcription factors and 59 biological processes were identified. In conclusion, BTA6 seems to have a deeper role in linear type traits in the Gir breed. Even though there are few studies confirming the action of those genes on body conformation, all eight candidate genes are recommended for future studies to validate their action on muscle and skeletal development or fat deposition due to their biological process functions, which could be pleiotropically affecting linear traits in cattle.
Ewe's functional longevity impacts flock profitability by reducing annual ewe replacement costs and increasing ewe outputs over the production cycle. In this context, the main objective of this study was to estimate variance components and genetic parameters of five ewe longevity indicators in South African Merino sheep. The traits evaluated included age at the last lambing (ALL), length of productive life (PL, measured as the number of days between the first and last lambing records), total number of litters (TNL), total number of lambs born (TLB) and total number of lambs weaned (TLW). These traits were recorded on a population of 39,011 ewes. Ewe's own birth type (singletons, twins, or triplets), the concatenated effect of birth flock-year and age at first lambing (3 classes: < 710, 710-743, 744-1095 days) were the fixed effects fitted in the animal models, while the animal and contemporary group (birth flock-year-season) were fitted as random effects. Variance components were estimated based on the Restricted Maximum Likelihood method implemented in the BLUPF90+ family of programmes. The sample size and mean (standard deviation) were 38,929 ewes and 1452.1 (559.3) days for ALL; 30,714 ewes and 918.9 (456.5) days for PL; 38,795 ewes and 2.98 (1.51) litters for TNL; 38,842 ewes and 4.26 (2.49) lambs born for TNB; and 19,322 ewes and 3.87 (2.39) lambs weaned for TNW. The heritability estimates were: 0.061 +/- 0.0074 (ALL), 0.051 +/- 0.0082 (PL), 0.061 +/- 0.0073 (TNL), 0.059 +/- 0.0072 (TNB) and 0.058 +/- 0.0098 (TNW). The genetic correlation estimates ranged from 0.73 +/- 0.056 (PL & times; TNW) to 0.99 +/- 0.0023 (ALL & times; PL), while phenotypic correlation ranged from 0.82 +/- 0.0019 (PL & times; TNB) to 0.99 +/- 0.0001 (ALL & times; PL). Parents of ewes with phenotypic records had estimated breeding value average accuracy above 0.30 for all traits. Positive genetic trends were found for all traits, suggesting genetic gains per year of 0.34 days in ALL, 0.27 days in PL, 0.0082 litters in TNL, 0.0022 lambs born in TNB and 0.002 lambs weaned in TNW. Given similar heritability estimates and high genetic correlation among the traits, TNW is recommended as a selection criterion to improve Merino longevity, as this trait could improve both ewe longevity and reproductive performance.
Reducing methane emissions from dairy cattle has gained considerable attention due to its dual benefits of improving feed efficiency and mitigating climate change. Consequently, phenotyping methane emissions in dairy populations has become increasingly important to enable direct genomic selection for lower methane emissions in breeding programs. Sniffer devices are receiving growing attention and are currently being deployed on commercial farms. However, these devices do not measure airflow and therefore provide methane concentration measurements rather than direct estimates of methane production. In this study, a new method is proposed to estimate individual cow methane production from sniffer device data that does not rely on regression on production traits and can therefore be classified as a Tier 3 approach. This novel methane production trait was derived using sniffer measurements collected in two dairy cattle populations: Spain (n = 1576) and The Netherlands (n = 2470). The proposed trait was compared with two alternative methane production estimates derived from production traits, representing a Tier 2 and an existing Tier 3 method. Phenotypic correlations between the Tier 3 traits were high (R > 0.90), whereas correlations between the Tier 2 and Tier 3 methods were substantially lower, ranging from 0.04 to 0.44. Strong agreement was observed between herd-level averages of the Tier 3 traits, while discrepancies between Tier 2 and Tier 3 estimates were more pronounced. Overall, the Tier 2 equation yielded higher methane production estimates than those obtained from sniffer-based Tier 3 traits. Heritability estimates for the Tier 3 traits ranged from 0.06 to 0.13, whereas a higher heritability (0.18-0.22) was observed for the Tier 2 trait, with standard errors between 0.02 and 0.03. Repeatability estimates were greater for the Tier 3 traits, with values ranging from 0.54 to 0.58 in Spain and from 0.25 to 0.29 in The Netherlands. The Tier 2 trait also exhibited a high repeatability (0.55-0.80). We propose this new sniffer-based Tier 3 trait as an alternative methane production phenotype that is not derived from individual production traits, thereby reducing the risk of spurious associations between methane emissions and yield-related traits. The proposed phenotype showed strong agreement with previously used Tier 3 traits and exhibited comparable heritability estimates. Nevertheless, several limitations must be acknowledged. In particular, this trait provides an estimate of methane production rather than a direct measurement, as current sniffer devices cannot capture the complete expiration or eructation plume. Despite these limitations, the trait enables the estimation of genetic trends and the prediction of breeding values expressed in biologically meaningful units. As such, it represents a valuable tool for supporting mitigation strategies and informing breeding policies aimed at reducing methane emissions from dairy cattle.
Resilience is the capacity of an animal to be minimally affected by disturbances or to rapidly return to its pre-disturbance state. To the best of our knowledge, no previous study has investigated resilience in the giant freshwater prawn (GFP, Macrobrachium rosenbergii). In this study, we aimed to estimate the genetic parameters of resilience indicators, the correlations between resilience and growth and survival traits, and the correlated genetic responses to selection for high growth in the present GFP line. A resilience indicator based on standardised body weight (BW) deviation was analysed in 39,134 individuals (offspring of 810 females and 515 males), specifically the logarithm-transformed variance (LnVar). The heritability estimate for the resilience indicator (LnVar) was low (0.09 +/- 0.03) but statistically significant. The genetic correlations between LnVar and body weight (BW) and total length (TL) were moderate and positive (0.33 +/- 0.04 and 0.18 +/- 0.01, respectively), whereas those between LnVar and body and carapace widths were negative (-0.28 to -0.32). The correlated response of the resilience indicator (LnVar) to selection for high growth was low but favourable, averaging 0.77%-2.89% over eight generations, or only 0.002 and 0.006 phenotypic and genetic standard deviation units, respectively. In conclusion, this study demonstrates the presence of heritable genetic variation in the resilience indicator derived from BW deviations in the giant freshwater prawn. Selection for high body weight has slightly improved resilience in this species, highlighting the potential to enhance resilience through selective breeding, albeit at a slow rate.
