Polymorphism of exon 2 of BoLA-DRB3 gene and its relationship with somatic cell score in Beijing Holstein cows

A comprehensive review on genomic insights and advanced technologies for mastitis prevention in dairy animals

Mastitis is a multi-etiological disease that significantly impacts milk production and reproductive efficiency. It is highly prevalent in dairy populations subjected to intensive selection for higher milk yield and where inbreeding is common. The issue is amplified by climate change and poor hygiene management, making disease control challenging. Key obstacles include antibiotic resistance, maximum residue levels, horizontal gene transfer, and limited success in breeding for resistance. Predictive genomics offers a promising solution for mastitis prevention by identifying genetic traits linked with susceptibility to mastitis. This review compiles the research and findings on genomics and its allied approaches, such as pan-genomics, epigenetics, proteomics, and transcriptomics, for diagnosing, understanding, and treating mastitis. In dairy production, artificial intelligence (AI), particularly deep learning (DL) techniques like convolutional neural networks (CNNs), has demonstrated significant potential to enhance milk production and improve farm profitability. It highlights the integration of advanced technologies like machine learning (ML), CRISPR, and pan-genomics to improve our knowledge of mastitis epidemiology, pathogen evolution, and the development of more effective diagnostic, preventive and therapeutic strategies for dairy herds. Genomic advancements provide critical insights into the complexities of mastitis, offering new avenues for understanding its dynamics. Integrating these findings with key predisposing factors can drive targeted prevention and more effective disease management.

Genetic polymorphisms in immune- and inflammation-associated genes and their association with bovine mastitis resistance/susceptibility

Bovine mastitis, the inflammation of the mammary gland, is a contagious disease characterized by chemical and physical changes in milk and pathological changes in udder tissues. Depressed immunity and higher expression of inflammatory cytokines with an elevated milk somatic cell count can be observed during mastitis in dairy cattle. The use of somatic cell count (SCC) and somatic cell score (SCS) as correlated traits in the indirect selection of animals against mastitis resistance is in progress globally. Traditional breeding for mastitis resistance seems difficult because of the low heritability (0.10-0.16) of SCC/SCS and clinical mastitis. Thus, genetic-marker-selective breeding to improve host genetics has attracted considerable attention worldwide. Moreover, genomic selection has been found to be an effective and fast method of screening for dairy cattle that are genetically resistant and susceptible to mastitis at a very early age. The current review discusses and summarizes the candidate gene approach using polymorphisms in immune- and inflammation-linked genes (CD4, CD14, CD46, TRAPPC9, JAK2, Tf, Lf, TLRs, CXCL8, CXCR1, CXCR2, C4A, C5, MASP2, MBL1, MBL2, LBP, NCF1, NCF4, MASP2, A2M, and CLU, etc.) and their related signaling pathways (Staphylococcus aureus infection signaling, Toll-like receptor signaling, NF-kappa B signaling pathway, Cytokine-cytokine receptor, and Complement and coagulation cascades, etc.) associated with mastitis resistance and susceptibility phenotypic traits (IL-6, interferon-gamma (IFN-γ), IL17, IL8, SCS, and SCC) in dairy cattle.

Polymorphisms of the IL-17A Gene Influence Milk Production Traits and Somatic Cell Score in Chinese Holstein Cows

The cow’s milk production characteristics are a significant economic indicator in the livestock industry. Serum cytokines such as interleukin-17 (IL-17) may be potential indicators for bovine mastitis concerning the milk somatic cell count (SCC) and somatic cell score (SCS). The current study aims to find previously undiscovered single nucleotide polymorphisms in the bovine (IL-17A) gene and further investigates their associations with milk production traits in Chinese Holstein cows. Twenty Chinese Holstein cows were randomly chosen from six farms in Jiangsu Province, China. The DNA was extracted from selected samples of bloods for PCR amplification Sequence analyses were used to find SNPs in the bovine (IL-17A) gene. The discovered five SNPs are g-1578A>G, g-1835G>A, and g-398T>A in the 5′UTR; g3164T>C and g3409G>C in the exon region. The genotyping of Holstein cows (n = 992) was performed based on Sequenom Mass ARRAY and SNP data. The connection between SNPs, milk production variables, and the somatic cell score was investigated using the least-squares method. Based on the results, SNP g-398T>A had a significant linkage disequilibrium with g3164T>C. SNPs were found to have significant (p < 0.05) correlations with the test-day milk yield. In conclusion, IL-17A affects cow’s milk production traits significantly.

Detection of quantitative trait loci and putative causal variants affecting somatic cell score in dairy sheep by using a 50K SNP chip and whole-genome sequencing

This study presents a scan of the ovine genome to identify quantitative trait loci (QTL) influencing the somatic cell score (SCS), a classical indicator of subclinical mastitis in sheep, and a subsequent high-resolution analysis of one of the identified QTL regions based on the analysis of whole-genome sequence data sets. A half-sib commercial population of Churra sheep genotyped with a 50K SNP chip was analyzed using linkage analysis (LA) and combined linkage and linkage disequilibrium analysis (LDLA). By LA, 2 5% chromosome-wide significant QTL on OAR5 and OAR25 and one 5% genome-wide significant QTL on ovine chromosome 20 (OAR20) were detected, whereas 22 significant associations were identified by LDLA. Two of the associations detected by LDLA replicated LA-detected effects (OAR20, OAR25). We compared the detected associations with previously reported QTL in sheep and cattle, and functional candidate genes were identified within the estimated confidence intervals. We then performed a high-resolution analysis of the OAR20 QTL region, the most significant QTL region identified by LA that replicated a QTL previously described in Churra sheep for SCS using microsatellite markers. For that, 2 segregating trios of 2 segregating families for the OAR20 QTL (each including the Qq sire and 2 daughters, QQ and qq) were selected for whole-genome sequencing. The bioinformatic analysis of the 6 sequenced samples performed across the genomic interval considered (14.2-41.7 Mb) identified a total of 227,030 variants commonly identified by 2 independent software packages. For the 3 different concordance tests considered, due to discrepancies regarding the QTL peak in the segregating families, the list of mutations concordant with the QTL segregating pattern was processed to identify the variants identified in immune-related genes that show a moderate/high impact on the encoded protein function. Among a list of 85 missense variants concordant with the QTL segregation pattern that were within candidate immune-related genes, 13 variants distributed across 7 genes [PKHD1, NOTCH4, AGER, ENSOARG00000009395 (HLA-C, Homo sapiens), ENSOARG00000015002 (HLA-B, H. sapiens), MOG, and ENSOARG00000018075 (BoLA, Bos taurus, orthologous to human HLA-A] were predicted to cause deleterious effects on protein function. Future studies should assess the possible associations of the candidate variants identified herein in commercial populations with indicator traits of udder inflammation (SCS, clinical mastitis).

Novel SNPs in IL-17F and IL-17A genes associated with somatic cell count in Chinese Holstein and Inner-Mongolia Sanhe cattle

Background

Bovine mastitis is the most common and costly disease of lactating cattle worldwide. Apart from milk somatic cell count (SCC) and somatic cell score (SCS), serum cytokines such as interleukin-17 (IL-17) and interleukin-4 (IL-4) may also be potential indicators for bovine mastitis. The present study was designed to investigate the effects of single nucleotide polymorphisms (SNPs) in bovine IL-17F and IL-17A genes on SCC, SCS and serum cytokines in Chinese Holstein and Inner-Mongolia Sanhe cattle, and to compare the mRNA expression variations of the cows with different genotypes.

Results

A total of 464 lactating cows (337 Holstein and 127 Inner-Mongolia Sanhe cattle) were screened for SNPs identification and the data were analyzed using fixed effects of herd, parity, season and year of calving by general linear model procedure. The results revealed that SNP g.24392436C > T in IL-17F and SNP g.24345410A > G in IL-17A showed significant effects on SCC and IL-4 in Holstein (n = 337) and on IL-17 and IL-4 in Sanhe cattle (n = 127). The homozygous GG genotype of SNP g.24345410A > G had significantly higher mRNA expression compared with the heterozygous AG genotype.

Conclusions

The results indicate that IL-17F and IL-17A could be powerful candidate genes of mastitis resistance and the significant SNPs might be useful genetic markers against mastitis in both dairy and dual purpose cattle.

Electronic supplementary material

The online version of this article (doi:10.1186/s40104-016-0137-1) contains supplementary material, which is available to authorized users.

Genotypic to expression profiling of bovine calcium channel, voltage-dependent, alpha-2/delta subunit 1 gene, and their association with bovine mastitis among Frieswal (HFX Sahiwal) crossbred cattle of Indian origin

Calcium channel, voltage-dependent, alpha-2/delta subunit 1 (CACNA2D1) gene is considered to be an important noncytokine candidate gene influencing mastitis. Scanty of reports are available until today regarding the role play of CACNA2D1 gene on the susceptibility of bovine mastitis. We interrogated the CACNA2D1 G519663A [A>G] SNP by PCR-RFLP among two hundreds Frieswal (HF X Sahiwal) crossbred cattle of Indian origin. Genotypic frequency of AA (51.5, n=101) was comparatively higher than AG (35, n=70) and GG (14.5, n=29). Association of Somatic cell score (SCS) with genotypes revealed that, GG genotypes showing lesser count (less susceptible to mastitis) compare to AA and AG. Relative expression of CACNA2D1 transcript (in milk samples) was significantly higher among GG than AG and AA. Further we have also isolated blood sample from the all groups and PBMCs were cultured from each blood sample as per the standard protocol. They were treated with Calcium channel blocker and the expression level of the CACNA2D1 gene was evaluated by Real Time PCR. Results show that expression level decline in each genotypic group after treatment and expression level of GG are again significantly higher than AA and AG. Thus, it may be concluded that GG genotypic animals are favorable for selecting disease resistant breeds.

Bovine mastitis: frontiers in immunogenetics

Mastitis is one of the most prevalent and costly diseases in the dairy industry with losses attributable to reduced milk production, discarded milk, early culling, veterinary services, and labor costs. Typically, mastitis is an inflammation of the mammary gland most often, but not limited to, bacterial infection, and is characterized by the movement of leukocytes and serum proteins from the blood to the site of infection. It contributes to compromised milk quality and the potential spread of antimicrobial resistance if antibiotic treatment is not astutely applied. Despite the implementation of management practises and genetic selection approaches, bovine mastitis control continues to be inadequate. However, some novel genetic strategies have recently been demonstrated to reduce mastitis incidence by taking advantage of a cow's natural ability to make appropriate immune responses against invading pathogens. Specifically, dairy cattle with enhanced and balanced immune responses have a lower occurrence of disease, including mastitis, and they can be identified and selected for using the high immune response (HIR) technology. Enhanced immune responsiveness is also associated with improved response to vaccination, increased milk, and colostrum quality. Since immunity is an important fitness trait, beneficial associations with longevity and reproduction are also often noted. This review highlights the genetic regulation of the bovine immune system and its vital contributions to disease resistance. Genetic selection approaches currently used in the dairy industry to reduce the incidence of disease are reviewed, including the HIR technology, genomics to improve disease resistance or immune response, as well as the Immunity(+)™ sire line. Improving the overall immune responsiveness of cattle is expected to provide superior disease resistance, increasing animal welfare and food quality while maintaining favorable production levels to feed a growing population.

BRCA1: a new candidate gene for bovine mastitis and its association analysis between single nucleotide polymorphisms and milk somatic cell score

Bovine mastitis is a very complex and common disease of dairy cattle and a major source of economic losses to the dairy industry worldwide. In this study, the bovine breast cancer 1, early onset gene (BRCA1) was taken as a candidate gene for mastitis resistance. The main object of this study was to investigate whether the BRCA1 gene was associated with mastitis in cattle. Through DNA sequencing, Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) and Created Restriction Site PCR (CRS-PCR) methods, three SNPs (G22231T, T25025A, and C28300A) were detected and twenty-four combinations of these SNPs were observed. The single SNP and their genetic effects on somatic cell score (SCS) were evaluated and a significant association with SCS was found in C28300A. The mean of genotype EE was significantly lower than those of genotypes EF and FF. The results of combined genotypes analysis of three SNPs showed that BBDDFF genotype with the highest SCS were easily for the mastitis susceptibility, whereas AACCEE genotype with the lowest SCS were favorable for the mastitis resistance. The information provided in the present study will be very useful for improving mastitis resistance in dairy cattle by marker-assisted selection.