In this study, our primary aim was to explore the genomic landscape of Barka cattle, a breed recognized for high milk production in a semi-arid environment, by focusing on genes with known roles in milk production traits. We employed genome-wide analysis and three selective sweep detection methods (ZFST, θπ ratio, and ZHp) to identify candidate genes associated with milk production and composition traits. Notably, ACAA1, P4HTM, and SLC4A4 were consistently identified by all methods. Functional annotation highlighted their roles in crucial biological processes such as fatty acid metabolism, mammary gland development, and milk protein synthesis. These findings contribute to understanding the genetic basis of milk production in Barka cattle, presenting opportunities for enhancing dairy cattle production in tropical climates. Further validation through genome-wide association studies and transcriptomic analyses is essential to fully exploit these candidate genes for selective breeding and genetic improvement in tropical dairy cattle.

Buffaloes are vital contributors to the global dairy industry. Understanding the genetic basis of milk production traits in buffalo populations is essential for breeding programs and improving productivity. In this study, we conducted whole-genome resequencing on 387 buffalo genomes from 29 diverse Asian breeds, including 132 river buffaloes, 129 swamp buffaloes, and 126 crossbred buffaloes. We identified 36,548 copy number variant (CNVs) spanning 133.29 Mb of the buffalo genome, resulting in 2,100 copy number variant regions (CNVRs), with 1,993 shared CNVRs being found within the studied buffalo types. Analyzing CNVRs highlighted distinct genetic differentiation between river and swamp buffalo subspecies, verified by evolutionary tree and principal component analyses. Admixture analysis grouped buffaloes into river and swamp categories, with crossbred buffaloes displaying mixed ancestry. To identify candidate genes associated with milk production traits, we employed 3 approaches. First, we used Vst-based population differentiation, revealing 11 genes within CNVRs that exhibited significant divergence between different buffalo breeds, including genes linked to milk production traits. Second, expression quantitative loci (eQTL) analysis revealed differential expression of CNVR-driven genes (DECGs) associated with milk production traits. Notably, known milk production-related genes were among these DECGs, validating their relevance. Last, a genome-wide association study (GWAS) identified 3 CNVRs significantly linked to peak milk yield. Our study provides comprehensive genomic insights into buffalo populations and identifies candidate genes associated with milk production traits. These findings facilitate genetic breeding programs aimed at increasing milk yield and improving quality in this economically important livestock species.

Genetic research for the assessment of mastitis and milk production traits simultaneously has a long history. The main issue that arises in this context is the known existence of a positive correlation between the risk of mastitis and lactation performance due to selection. The transcriptome-wide association study (TWAS) approach endeavors to combine the expression quantitative trait loci and genome-wide association study summary statistics to decode complex traits or diseases. Accordingly, we used the farmgtex project results as a complete bovine database for mastitis and milk production. The results of colocalization and TWAS approaches were used for the detection of functional associated candidate genes with milk production and mastitis traits on multiple tissue-based transcriptome records. Also, we used the david database for gene ontology to identify significant terms and associated genes. For the identification of interaction networks, the genemania and string databases were used. Also, the available z-scores in TWAS results were used for the calculation of the correlation between tissues. Therefore, the present results confirm that LYNX1, DGAT1, C14H8orf33, and LY6E were identified as significant genes associated with milk production in eight, six, five, and five tissues, respectively. Also, FBXL6 was detected as a significant gene associated with mastitis trait. CLN3 and ZNF34 genes emerged via both the colocalization and TWAS approaches as significant genes for milk production trait. It is expected that TWAS and colocalization can improve our perception of the potential health status control mechanism in high-yielding dairy cows.

Identifying key causal genes is critical for unraveling the genetic basis of complex economic traits, yet it remains a formidable challenge. The advent of large-scale sequencing data and computational algorithms, such as transcriptome-wide association studies (TWASs), offers a promising avenue for identifying potential causal genes. In this study, we harnessed the power of TWAS to identify genes potentially responsible for milk production traits, including daily milk yield (MY), fat percentage (FP), and protein percentage (PP), within a cohort of 100 buffaloes. Our approach began by generating the genotype and expression profiles for these 100 buffaloes through whole-genome resequencing and RNA sequencing, respectively. Through comprehensive genome-wide association studies (GWAS), we pinpointed a total of seven and four single nucleotide polymorphisms (SNPs) significantly associated with MY and FP traits, respectively. By using TWAS, we identified 55, 71, and 101 genes as significant signals for MY, FP, and PP traits, respectively. To delve deeper, we conducted protein-protein interaction (PPI) analysis, revealing the categorization of these genes into distinct PPI networks. Interestingly, several TWAS-identified genes within the PPI network played a vital role in milk performance. These findings open new avenues for identifying potentially causal genes underlying important traits, thereby offering invaluable insights for genomics and breeding in buffalo populations.

Milk production traits are the most important quantitative economic traits in dairy cow production; improving the yield and quality of milk is an important way to ensure the production efficiency of the dairy industry. This study carried out a series of in-depth statistical genetics studies and molecular analyses on the Chinese Holstein cows in the Jiangsu Province, such as descriptive statistics and copy number variation analysis. A genetic correlation, phenotypic correlation, and descriptive statistical analysis of five milk production traits (milk yield, milk fat percentage, milk fat yield, milk protein percentage, and milk protein yield) of the dairy cows were analyzed using the SPSS and DMU software. Through quality control, 4173 cows and their genomes were used for genomic study. Then, SNPs were detected using DNA chips, and a copy number variation (CNV) analysis was carried out to locate the quantitative trait loci (QTL) of the milk production traits by Perl program software Penn CNV and hidden Markov model (HMM). The phenotypic means of the milk yield, milk fat percentage, milk fat mass, milk protein percentage, and milk protein mass at the first trimester were lower than those at the other trimesters by 8.821%, 1.031%, 0.930%, 0.003%, and 0.826%, respectively. The five milk production traits showed a significant phenotypic positive correlation (p < 0.01) and a high genetic positive correlation among the three parities. Based on the GGPBovine 100 K SNP data, QTL-detecting research on the fist-parity milk performance of dairy cows was carried out via the CNV. We identified 1731 CNVs and 236 CNVRs in the 29 autosomes of 984 Holstein dairy cows, and 19 CNVRs were significantly associated with the milk production traits (p < 0.05). These CNVRs were analyzed via a bioinformatics analysis; a total of 13 gene ontology (GO) terms and 20 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were significantly enriched (p < 0.05), and these terms and pathways are mainly related to lipid metabolism, amino acid metabolism, and cellular catabolic processes. This study provided a theoretical basis for the molecular-marker-assisted selection of dairy cows by developing descriptive statistics on the milk production traits of dairy cows and by locating the QTL and functional genes that affect the milk production traits of first-born dairy cows. The results describe the basic status of the milk production traits of the Chinese Holstein cows in Jiangsu and locate the QTL and functional genes that affect the milk production traits of the first-born cows, providing a theoretical basis for the molecular-marker-assisted selection of dairy cows.

Our previous research identified the Kruppel like factor 6 (KLF6) gene as a prospective candidate for milk production traits in dairy cattle. The expression of KLF6 in the livers of Holstein cows during the peak of lactation was significantly higher than that during the dry and early lactation periods. Notably, it plays an essential role in activating peroxisome proliferator-activated receptor α (PPARα) signaling pathways. The primary aim of this study was to further substantiate whether the KLF6 gene has significant genetic effects on milk traits in dairy cattle.
Through direct sequencing of PCR products with pooled DNA, we totally identified 12 single nucleotide polymorphisms (SNPs) within the KLF6 gene. The set of SNPs encompasses 7 located in 5\' flanking region, 2 located in exon 2 and 3 located in 3\' untranslated region (UTR). Of these, the g.44601035G > A is a missense mutation that resulting in the replacement of arginine (CGG) with glutamine (CAG), consequently leading to alterations in the secondary structure of the KLF6 protein, as predicted by SOPMA. The remaining 7 regulatory SNPs significantly impacted the transcriptional activity of KLF6 following mutation (P < 0.005), manifesting as changes in transcription factor binding sites. Additionally, 4 SNPs located in both the UTR and exons were predicted to influence the secondary structure of KLF6 mRNA using the RNAfold web server. Furthermore, we performed the genotype-phenotype association analysis using SAS 9.2 which found all the 12 SNPs were significantly correlated to milk yield, fat yield, fat percentage, protein yield and protein percentage within both the first and second lactations (P < 0.0001 ~ 0.0441). Also, with Haploview 4.2 software, we found the 12 SNPs linked closely and formed a haplotype block, which was strongly associated with five milk traits (P < 0.0001 ~ 0.0203).
In summary, our study represented the KLF6 gene has significant impacts on milk yield and composition traits in dairy cattle. Among the identified SNPs, 7 were implicated in modulating milk traits by impacting transcriptional activity, 4 by altering mRNA secondary structure, and 1 by affecting the protein secondary structure of KLF6. These findings provided valuable molecular insights for genomic selection program of dairy cattle.

BACKGROUND: Milk production traits are complex traits with vital economic importance in the camel industry. However, the genetic mechanisms regulating milk production traits in camels remain poorly understood. Therefore, we aimed to identify candidate genes and metabolic pathways that affect milk production traits in Bactrian camels.
METHODS: We classified camels (fourth parity) as low- or high-yield, examined pregnant camels using B-mode ultrasonography, observed the microscopic changes in the mammary gland using hematoxylin and eosin (HE) staining, and used RNA sequencing to identify differentially expressed genes (DEGs) and pathways.
RESULTS: The average standard milk yield over the 300 days during parity was recorded as 470.18 ± 9.75 and 978.34 ± 3.80 kg in low- and high-performance camels, respectively. Nine female Junggar Bactrian camels were subjected to transcriptome sequencing, and 609 and 393 DEGs were identified in the low-yield vs. high-yield (WDL vs. WGH) and pregnancy versus colostrum period (RSQ vs. CRQ) comparison groups, respectively. The DEGs were compared with genes associated with milk production traits in the Animal Quantitative Trait Loci database and in Alashan Bactrian camels, and 65 and 46 overlapping candidate genes were obtained, respectively. Functional enrichment and protein-protein interaction network analyses of the DEGs and candidate genes were conducted. After comparing our results with those of other livestock studies, we identified 16 signaling pathways and 27 core candidate genes associated with maternal parturition, estrogen regulation, initiation of lactation, and milk production traits. The pathways suggest that emerged milk production involves the regulation of multiple complex metabolic and cellular developmental processes in camels. Finally, the RNA sequencing results were validated using quantitative real-time PCR; the 15 selected genes exhibited consistent expression changes.
CONCLUSIONS: This study identified DEGs and metabolic pathways affecting maternal parturition and milk production traits. The results provides a theoretical foundation for further research on the molecular mechanism of genes related to milk production traits in camels. Furthermore, these findings will help improve breeding strategies to achieve the desired milk yield in camels.

Milk production traits as the most important economic traits of dairy cows, they directly reflect the benefits of breeding and the economic benefits of pasture. In this study, A disintegrin and metalloproteinase-12 (ADAM12), Parkinson\'s disease gene 2 (PRKN) and dipeptidyl peptidase-like protein subtype 6 (DPP6) polymorphism in 384 Chinese Holstein cows were detected by time-of-flight mass spectrometry and through statistical analysis using software such as Popgene 32, SAS 9.4 and Origin 2022, the relationship between single nucleotide polymorphisms (SNPs) of three genes with four milk production traits such as daily milk yield (DMY), milk fat percentage (MFP), milk protein percentage (MPP) and somatic cell score (SCS) was verified at molecular level. The results showed that four polymorphic loci (116,467,133, 116,604,487, 116,618,268 and 116,835,111) of DPP6 gene, two polymorphic loci (97,665,052 and 97,159,837) of PRKN gene and two polymorphic loci (45,542,714 and 45,553,888) of ADAM12 gene were detected. PRKN-97665052, DPP6-116467133, ADAM12-45553888, DPP6-116604487 and DPP6-116835111 were all in Hardy-Weinberg equilibrium state (p > .05). ADAM12-45542714, PRKN-97159837 and PRKN-97665052 were moderately polymorphic (0.25 ≤ PIC <0.50) in Holstein. It is evident that the selection potential and genetic variation of these five loci are relatively large, and the genetic richness is relatively high. The correlation analysis of different genotypes between these eight loci and milk production traits of Holstein showed that ADAM12-45542714 and DPP6-116835111 (p < .01) had an extremely significant effects on the DMY of Chinese Holstein in Ningxia, while PRKN-97665052 had an extremely significant effect on MFP (p < .01). The effect of PRKN-97665052 and DPP6-116467133 on MPP of Holstein were extremely significant (p < .01). DPP6-116618268 had an extremely significant effect on the SCS of Holstein in Ningxia (p < .01), and AA genotype individuals showed a higher SCS than GG genotype individuals; the other two loci (ADAM12-45553888 and DPP6-116604487) had no significant effects on milk production traits of Holstein (p > .05). In addition, through the joint analysis of DPP6, PRKN and ADAM12 gene loci, it was found that the interaction effect between the three gene loci could significantly affect the DMY, SCS (p < .01) and MPP (p < .05). In conclusion, several different loci of DPP6, PRKN and ADAM12 genes can affect the milk production traits of Holstein to different degrees. PRKN, DPP6 and ADAM12 genes can be used as potential candidate genes for milk production traits of Holstein for marker-assisted selection, providing theoretical basis for breeding of Holstein.

Pyruvate kinase (PKLR) is a potential candidate gene for milk production traits in cows. The main aim of this work is to investigate the potentially deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in the PKLR gene by using several computational tools. In silico tools including SIFT, Polyphen-2, SNAP2 and Panther indicated only 18 nsSNPs out of 170 were considered deleterious. The analysis of proteins\' stability change due to amino acid substitution performed by the use of the I-mutant, MUpro, CUPSTAT, SDM and Dynamut confirmed that 9 nsSNPs decreased protein stability. ConSurf analysis predicted that all 18 nsSNPs were evolutionary moderately or highly conserved. Two different domains of PKLR protein were revealed by the InterPro tool with 12 nsSNPs positioned in the Pyruvate Kinase barrel domain and 6 nsSNP present in the Pyruvate Kinase C Terminal. The PKLR 3D model was predicted by MODELLER software and validated via Ramachandran plot and Prosa which indicated a good quality model. The analysis of energy minimizations for the native and mutated structures was performed by SWISS PDB viewer with GROMOS 96 program and showed that 3 structural and 4 functional residues had total energy higher than the native model. These findings indicate that these mutant structures (rs441424814, rs449326723, rs476805413, rs472263384, rs474320860, rs475521477, rs441633284) were less stable than the native model. Molecular Dynamics simulations were performed to confirm the impact of nsSNPs on the protein structure and function. The present study provides useful information about functional SNPs that have an impact on PKLR protein in cattle.Communicated by Ramaswamy H. Sarma.

UNASSIGNED: Antimicrobial peptides, including cathelicidins, play a significant role in farm animals, influencing animal welfare, immunity, and thus the quality of animal products.
UNASSIGNED: The study used amplification-created restriction site and PCR-restriction fragment length polymorphism to analyse single nucleotide polymorphisms of the CATHL7 gene encoding the BMAP-34 protein in cattle, at positions 2,383 G > C and 2,468 G > C. The material was collected from 279 Polish Black-and-White Holstein-Friesian dairy cows.
UNASSIGNED: There were statistically significant differences between milk performance parameters in cows with the CATHL7/HhaI and CATHL7/HinfI genotypes. In the case of the CATHL7/HhaI polymorphism, the highest milk yield and protein and lactose content and the lowest somatic cell count in milk were observed for the CC genotype, while the fat content was the highest in milk from cows with the GG genotype. In the case of the CATHL7/HinfI polymorphism, the highest protein and lactose content in milk was observed for the CC genotype.
UNASSIGNED: The results were statistically significant, which suggests that the search for relationships can be continued, and that the results can be used to improve selection programmes supporting dairy farming.