Milk Production Traits Research Articles

Analysis of the Association Between Microsatellite Loci Polymorphisms and Longevity and Lifetime Milk Production Traits in Egyptian Buffalo

Analysis of the Association Between Microsatellite Loci Polymorphisms and Longevity and Lifetime Milk Production Traits in Egyptian Buffalo

Phenotypic and genetic analysis of milking temperament and its correlation with milk production traits in South African Holstein cattle

Milking temperament (MT) is a crucial trait in dairy production; it affects farm profitability as well as animal and human welfare. Furthermore, poor temperament may increase herd costs by compromising the state and durability of the milking system. There is, however, limited knowledge and recording of MT in South African dairy cattle. The purpose of this study was to evaluate factors influencing MT scores and to estimate genetic parameters among MT and milk production traits (milk yield, fat and protein) in South African Holsteins. Data comprised of MT assessments on 2,844 cows from 16 herds collected between September 2020 and November 2021. Non-genetic effects were analysed by general linear models (GLM) procedure, and repeatability of MT scores was estimated using the variance components procedure of the Statistical Analysis Software. Linear animal models were fitted to estimate genetic parameters, using the ASReml software. Herd-test-day and age of cow at calving (p < 0.0001), and lactation stage (p < 0.05), significantly influenced MT. Repeatability estimate was moderate (0.47 ± 0.03), and the heritability estimate was low (0.05 ± 0.04). Heritability estimates were low to moderate for milk yield and composition, varying from 0.11 ± 0.05 for milk yield to 0.24 ± 0.06 for protein percent (%). Genetic correlation for MT with milk yield was moderate (0.60 ± 0.35). Low correlations were observed for MT with fat % (-0.12 ± 0.24) and protein % (-0.30 ± 0.32). There was no discernible genetic trend for MT in animals born from 2009 to 2019, although there was a minimal overall decline over the period. These findings suggest that there was reasonable consistency in the assessment of MT, and that MT may be improved through selection, using multi-trait models including milk yield.

Dairy Cattle Reproduction, Production, and Disease Resistance in the Omics Era: Genome-Wide Selection Signatures Identify Candidate Genes in Sahiwal Cattle.

Climate emergency and ecological sustainability call for new ways of thinking livestock health, including the dairy cattle. This study unpacks the genetic diversity and selection sweeps of Sahiwal cattle in relation to adaptability, production, and disease resistance. Using nucleotide diversity (π) calculated from 10 kb windows across the genome with VCFtools, 716 regions of genetic diversity were identified across 29 chromosomes, and importantly, with chromosome 15 showing the highest density. A total of 92 quantitative trait loci (QTL) linked genes were analyzed, with chromosome 1 harboring the highest number. Trait association analysis using the Cattle QTL database showed that 14 genes were linked to production traits, 10 to reproduction traits, and 8 to disease susceptibility. Notable genes included CSMD2 and EFNA1, which influence milk production traits such as fat percentage and yield, and PCBP3 and SGCD, which affect reproductive traits. Additionally, the genes TBXAS1 and ASTN2 were associated with disease traits such as bovine respiratory disease and sole ulcers. Selection sweeps, identified using Tajima's D, revealed 728 sweeps across the genome, with chromosomes 6 and 8 showing the highest frequencies. These sweeps indicate regions under strong selective pressure, likely due to the breed's adaptation to arid environments and specific trait selection. The present study highlights how genetic diversity and selection sweeps contribute to Sahiwal cattle's adaptability, production efficiency, and disease resistance. The insights reported here provide a foundation for livestock health and targeted breeding strategies in the case of Sahiwal cattle under diverse ecological conditions such as tropical climate.

Effect of Mannose-Binding Lectin (protein A) 1 (MBL1) Gene Polymorphisms on Milk Production Traits and Somatic Cell Count in Holstein Dairy Cattle

Effect of Mannose-Binding Lectin (protein A) 1 (MBL1) Gene Polymorphisms on Milk Production Traits and Somatic Cell Count in Holstein Dairy Cattle

A meta-analysis on the relationship between IGF-1 gene polymorphism and milk production traits in cattle

A meta-analysis on the relationship between IGF-1 gene polymorphism and milk production traits in cattle

Mammary gland multi-omics data reveals new genetic insights into milk production traits in dairy cattle.

Although many sequence variants have been discovered in cattle, deciphering the relationship between genome and phenome remains a significant challenge. In this study, we identified functional classes, including mammary-specific genes, lactation-associated genes, novel long non-coding RNAs, miRNAs, RNA editing sites, DNA methylation, histone modifications, and expression quantitative trait loci. We estimated their contributions to genetic variance for milk production traits using 3 million variants in 23,566 Holstein bulls. Sequence variants in the 5'-UTR, synonymous, and splicing regions disproportionately contributed to genetic variance of milk production traits compared to other genomic regions. Genes specifically expressed in the mammary gland, particularly those active in lactating tissue (e.g., GLYCAM1, DGAT1), account for significantly more genetic variance of milk production traits than specific genes from non-mammary tissues. We identified 8,560 differentially expressed genes (DEGs) between lactating and non-lactating tissues. Among these, both up-regulated and small-fold changes of down-regulated DEGs exhibited greater genetic variance enrichment of milk production traits than other genes. Mammary enhancers (e.g., H3K27ac, H3K4Me1) explained more variance than repressive elements, while small changes in DNA methylation level (≤0.2) contributed more variance than that with larger changes (> 0.2). Notably, lactation-associated RNA editing sites in mammary explained more variance for milk production traits than expected by chance. We proposed a novel miRNA prioritization strategy for selecting candidate miRNAs related to milk production traits, based on the overlaps between significant enrichment tests of miRNA target correlations and the relatively large variance explained by these targets. Additionally, we integrated these nine functional classes into the variance component analysis simultaneously, revealing that sQTLs, histone modification and DEGs showed the highest per-SNP variance enrichment. Finally, we constructed a new 624K SNP panel, which improved the reliabilities of genomic predictions by 0.22%. Dividing routine SNPs into two groups based on functional classes improved the reliabilities by 0.21%, particularly for milk protein percentage (0.68% improvement). Overall, incorporating prior biological knowledge of the mammary gland directly enhances our understanding of milk production's genetic architecture and improves the reliability of genomic predictions for milk production traits. This integrative approach establishes a paradigm for translating biological knowledge into agricultural genomics applications.

Genetic relationships among methane emissions from breath, dry matter intake, body weight, and milk production traits of Dutch dairy cows.

Genetic relationships among methane emissions from breath, dry matter intake, body weight, and milk production traits of Dutch dairy cows.

Genomic insights into selection signatures and candidate genes for milk production traits in buffalo population.

Genomic insights into selection signatures and candidate genes for milk production traits in buffalo population.

Study of the Polymorphism of ACACA Gene and its Effect on Milk Production Traits in Goats

Study of the Polymorphism of ACACA Gene and its Effect on Milk Production Traits in Goats

Comparative genome analysis of international transboundary cattle breeds.

Comparative genome analysis of international transboundary cattle breeds.

Genetic Associations of ACOX2 Gene with Milk Yield and Composition Traits in Chinese Holstein Cows.

In our previous studies on the liver proteome of Holstein cows, the acyl-CoA oxidase 2 (ACOX2) gene was identified as a promising candidate for milk traits, being involved in the processes of fatty acid metabolism and bile acid formation. Herein, we evaluated its genetic effects on milk production traits in 922 Chinese Holstein cows. By sequencing the entire coding region and 2000 bp of the 5' and 3' flanking sequences of the ACOX2 gene, we identified a total of five SNPs, including one SNP in the 5' UTR, one in intron 5, and three in the 3' flanking region. Using an animal model, we found that the SNPs rs109066086, rs109665171, and rs454339362 were significantly associated with at least one of the milk production traits, including 305-day milk yield, milk fat yield, milk protein yield, milk fat percentage, and milk protein percentage in the first lactation (p ≤ 4.03 × 10-2). And in the second lactation, all five SNPs were significantly associated with at least three of the milk production traits (p ≤ 1.17 × 10-2). We also found that in the second lactation, the SNP rs209677248 had a high phenotypic variance rate for milk protein percentage, with a value of 4.90%. With Haploview 4.2, it was observed that the four SNPs formed two haplotype blocks, which were significantly associated with the 305-day milk, fat, and protein yields (p ≤ 1.03 × 10-2; p ≤ 8.60 × 10-3; p ≤ 3.20 × 10-3). In addition, it was predicted that the T allele in the SNP rs109066086 created TFBSs for transcription factors NC2R2 and TFAP4, thereby potentially affecting ACOX2 expression. Overall, our results provide the first confirmation of the genetic effects of the ACOX2 gene on milk yield and composition traits in dairy cattle and revealed the referable molecular markers for genomic selection.

Unveiling Genetic Markers for Milk Yield in Xinjiang Donkeys: A Genome-Wide Association Study and Kompetitive Allele-Specific PCR-Based Approach.

Lactation traits are critical economic attributes in domestic animals. This study investigates genetic markers and functional genes associated with lactation traits in Xinjiang donkeys. We analyzed 112 Xinjiang donkeys using 10× whole genome re-sequencing to obtain genome-wide single nucleotide polymorphisms (SNPs). Genome-wide association analyses were conducted using PLINK 2.0 and GEMMA 0.98.5 software, employing mixed linear models to assess several lactation traits: average monthly milk yield (AY), fat percentage (FP), protein percentage (PP), and lactose percentage (LP). A total of 236 SNPs were significantly associated with one or more milk production traits (p < 0.000001). While the two-software identified distinct SNP associations, they consistently detected the same 11, 95, 5, and 103 SNPs for AY, FP, PP, and LP, respectively. Several of these SNPs are located within potential candidate genes, including glycosylphosphatidylinositol anchored high density lipoprotein binding protein 1 (GPIHBP1), FLII actin remodeling protein (FLII), mitochondrial topoisomerase 1 (TOP1MT), thirty-eight-negative kinase 1 (TNK1), polo like kinase 1 (PLK1), notch homolog 1 (NOTCH1), developmentally regulated GTP-binding protein 2 (DRG2), mitochondrial elongation factor 2 (MIEF2), glutamine-fructose-6-phosphate transaminase 2 (GFPT2), and dual-specificity tyrosine phosphorylation-regulated kinase 2 (DYRK2). Additionally, we validated the polymorphism of 16 SNPs (10 genes) using Kompetitive Allele Specific PCR, revealing that TOP1MT_g.9133371T > C, GPIHBP1_g.38365122C > T, DRG2_g.4912631C > A, FLII_g.5046888C > T, and PLK1_g.23585377T > C were significantly correlated with average daily milk yield and total milk yield in the studied donkeys. This study represents the first genome-wide association analysis of markers and milk components in Xinjiang donkeys, offering valuable insights into the genetic mechanisms underlying milk production traits. Further research with larger sample sizes is essential to confirm these findings and identify potential causal genetic variants.

KANDYDUJĄCE MARKERY GENETYCZNE ZWIĄZANE Z CHARAKTERYSTYKĄ PRODUKCJI MLEKA ORAZ PRZYDATNOŚCIĄ TECHNOLOGICZNĄ MLEKA

Milk yield and composition are key factors for dairy industry, and both are determined by multiple genes. This study contains collective analysis of research on chosen candidate genetic markers associated with milk production traits and its technological suitability. The results of analyzed studies indicate that polymorphisms in the genes GHR, IGF-1, CSN2, CSN3, FASN, and SCD1 affect the composition of milk, and thus its technological suitability. However, studies on BLG polymorphisms show variability in the results across researchers, highlighting the need for further analysis.

Polymorphisms in the GH gene and their influence on milk production traits in local buffaloes

This study was conducted in a private sector buffalo farm in Al-Qurna, located north of Basra Governorate, between December 2023 and November 2024. It covered the summer (July and August 2024), autumn (October and November 2024), and winter (December 2023, January and February 2024) seasons. The purpose of the experiment was to examine the impact of the mid-lactation stage on genetic polymorphism in the growth hormone (GH) gene members (E4, E5, E6, E8) in the blood of buffaloes, and their relationship with serum GH levels during mid-lactation. Thirty blood samples were collected from the same buffaloes (n=30). Polymerase Chain Reaction (PCR) was used to amplify the targeted genes, and nucleotide sequence analysis was performed to detect polymorphisms. The results were compared with GH gene genotypes in the GenBank database. Two genotypes of the GH gene were identified in the mid-lactation buffaloes. DNA sequencing of the GH genes (E4, E5, E6, E8) was carried out, and the sequence data were compared with two references from the NCBI database. The E4 gene showed no differences when compared with Acc. NC_059175, but several mutations were observed compared with Acc. HG738860. The E5 gene sequence revealed polymorphisms when compared with both Acc. KC107765 and Acc. NC_059175 references. Although the E6 gene sequence showed no polymorphisms, the E8 gene sequence displayed a single-point mutation. Additionally, the results indicated significantly higher (P≤0.05) serum growth hormone levels in genotype A compared to genotype B.

Genome-wide scan for SNPs and selective sweeps reveals candidate genes and QTLs for milk production and reproduction traits in Indian Kankrej cattle.

The online version contains supplementary material available at 10.1007/s13205-025-04263-z.

Genome-Wide Association Study for the Capacity to Skip the Dry Period in Dairy Goats

Lactation is a challenging life stage for dairy animals, as they need to cope with milk production and, in most cases, simultaneous pregnancy. The dry period between two consecutive lactations can be a producer choice, based on, for instance, animal performance or a physiological requirement when animals dry off spontaneously. The goals of this research were to estimate genetic parameters and perform a genome-wide association study in Saanen goats for the capacity to skip the dry period between lactations to identify genes and QTLs underlying this trait. A total of 249 Saanen dairy goats had the length of their dry period determined over lactations, with some (n = 54) showing the capacity to skip the dry period, i.e., having a dry period of a single day. The estimated heritability for the capacity to skip the dry period was moderate (0.25, SE = 0.13). Three SNPs significantly associated with the capacity to skip dry period were identified, which are located close to the OSMR gene, reported to be associated with mammary involution, and a known QTL for cannon bone circumference. The three SNPs were also confined to a very conserved region on chromosome 20, which harbors several genes associated with milk-related traits. The OSMR gene seems to be a good candidate gene for the capacity to skip the dry period, and the genomic region where it is located appears to also be important for milk production traits.

Investigation of selection signatures of dairy goats using whole-genome sequencing data

Dairy goats, a livestock species with a long history of milk production, are essential for the economic advancement of nations, particularly in regions experiencing growth. In this study, we gathered whole-genome resequencing data of 58 goats, including 34 dairy goats and 24 wild goats (Bezoar), to explore the selection signatures linked to milk production traits using ROH (Runs of homozygosity), CLR (composite likelihood ratio), Fst (Fixation index), XP-EHH (Ex-tended haplotype homozygosity across populations) and XP-CLR(Cross-population composite likelihood ratio test) methods. Analysis of five tests of selection signatures for dairy goats revealed a total of 210 genes, with 24 genes consistently identified in at least two approaches. These genes are associated with milk fat, milk protein, and fat yield. Gene enrichment analysis highlighted important GO and KEGG pathways related to milk production, such as the “acyl-CoA metabolic process”, “glycerolipid biosynthetic process”, “cellular response to fatty ac-id”, “hormone metabolic process”, “Galactose metabolism”. Additionally, genes linked to repro-duction, immune response, and environmental adaptation were identified in dairy goats. The findings from our study offer profound understanding into the critical economic features of dairy goats and offer practical guidance for the improvement and development of crossbreeding initiatives across different dairy goat breeds.

Genetic Relationships Among Resilience, Fertility and Milk Production Traits in Crossbred Dairy Cows Performing in Sub-Saharan Africa.

Change in climate over the past years and its impact on the environment have necessitated the inclusion of resilience traits in the breeding objectives of dairy cattle. However, the relationship between resilience and other traits of economic importance in dairy production is currently not well known. This study examined the genetic parameters and relationships among resilience, fertility and milk production traits in dairy cattle in Kenya. Indicators of general resilience and heat tolerance were defined from the first parity test-day milk yield records. Indicators of general resilience included variance of actual deviations (LnVar1), variance of standardised deviations (LnVar2), lag-1 autocorrelation (rauto) and skewness (Skew) of standardised deviations in milk yield. Heat tolerance indicators at temperature-humidity index 80 included the slope of the reaction norm (Slope), absolute slope of the reaction norm (Absolute), and the intercept of the reaction norm model (Intercept). Cows with > 50% taurine genes had lower age at first calving (AFC), longer calving intervals (CI) and higher test-day milk yield (MY). The heritability estimates of AFC, CI and MY were 0.17 ± 0.033, 0.06 ± 0.012 and 0.35 ± 0.021, respectively. The repeatability estimates of CI and MY were 0.06 ± 0.012 and 0.47 ± 0.009, respectively. The low heritability and non-significant permanent environmental variance of CI showed that CI is heavily influenced by external factors, such as management practices. AFC was negatively genetically correlated with both CI (-0.88 ± 0.077) and MY (-0.53 ± 0.059) showing that animals that attain sexual maturity earlier exhibit longer CI and higher milk production. A positive genetic correlation (0.62 ± 0.077) between CI and MY shows that high-yielding cows face challenges in maintaining shorter calving intervals. Heritability estimates of nearly all resilience indicators were significant and ranged from 0.05 to 0.34. Heat tolerance indicators showed low to non-significant genetic correlations with general resilience indicators, suggesting that different genetic factors are involved in responses to different types of disturbances. There was a generally positive genetic correlation between resilience and fertility, implying that resilient animals might have better fertility. All indicators, except LnVar1 and LnVar2, revealed an antagonistic genetic relationship between resilience and milk production. The findings present an opportunity for including resilience in the development and application of selection indices in dairy cattle, especially for the tropics.

COL6A1 Promotes Milk Production and Fat Synthesis Through the PI3K-Akt/Insulin/AMPK/PPAR Signaling Pathways in Dairy Cattle.

Exploring functional genes/sites and the molecular regulatory mechanisms underlying milk production traits in dairy cattle is crucial for improving the development of the dairy industry and human health. In our previous work, the gene collagen type VI alpha 1 (COL6A1) was found to be involved in milk fat metabolism from liver transcriptome data across various lactation periods of cows. Through the integration of Cattle QTLdb, FarmGTEx and qPCR data, the COL6A1 gene was found to be located within known quantitative trait loci (QTLs), adjacent to single-nucleotide polymorphisms (SNPs) associated with milk traits, and highly expressed in the mammary gland. After employing RNA interference technology, cell function and phenotype tests in bovine mammary epithelial cells revealed that the COL6A1 gene accelerated cell proliferation, cell cycle progression, and the synthesis of lipids and triglycerides by regulating the PI3K-Akt, insulin, AMPK, and PPAR signaling pathways. Notably, 22 SNPs within COL6A1 had potential breeding value because they were significantly associated with milk production traits, especially with milk fat. In summary, our findings demonstrate that the COL6A1 gene promotes milk production and fat synthesis via the PI3K-Akt/insulin/AMPK/PPAR signaling pathways, providing valuable genetic information for molecular breeding programs for dairy cattle.

Modelling heat stress effects on milk production traits in Tunisian Holsteins using a random regression approach.

This study investigated the impact of temperature and humidity on milk production traits in Tunisian dairy cows, analysing population-level trends and individual cow responses using various modelling techniques and heat stress (HS) indices. Two distinct datasets were used for this purpose: the first included 551,139; 331,654 and 302,396 test-day records for milk, fat and protein yields, respectively. The second supplemented the production information with daily average (THIavg) and maximum (THImax) temperature-humidity index (THI) data. Three main parts of analyses were conducted simultaneously: classical least squares, identification of HS thresholds and associated production losses and assessment of individual cow responses using random regression models (RRM) fitting various continuous functions that include/exclude individual effects. The best model, determined by goodness-of-fit measurements, was a cubic polynomial function that accounted for individual variation and THIavg as a heat load measure. HS thresholds were established at THIavg/THImax of 70/74 for milk yield, 50/55 for fat percentage, 59/66 for protein percentage, 54/63 for fat yield and 56/66 for protein yield. According to the fitted polynomial models, daily milk production traits showed a curvilinear decline with accelerated loss rates beyond the established thermal thresholds. However, for all models and thermal indices, maximum daily production losses remained below 164 g/day, 4.4 g/day and 6.1 g/day for milk, fat and protein yields, respectively. Despite these losses, the relatively high thermal thresholds and lower associated production losses suggest that Tunisian dairy cows can tolerate high heat loads. Moreover, observed variations in response patterns indicate potential for selecting heat-tolerant individuals within this population.