Understanding the genomic architecture of clinical mastitis in Bos indicus

Methylome-wide analysis of milk somatic cells upon subclinical mastitis in dairy cattle

Better understanding of the molecular mechanisms behind bovine mastitis is fundamental for improving the management of this disease, which continues to be of major concern for the dairy industry, especially in its subclinical form. Disease severity and progression depend on numerous aspects, such as livestock genetics, and the interaction between the causative agent, the host, and the environment. In this context, epigenetic mechanisms have proven to have a role in controlling the response of the animal to inflammation. Therefore, in this study we aimed to explore genome-wide DNA methylation of milk somatic cells (SC) in healthy cows (n = 15) and cows affected by naturally occurring subclinical mastitis by Streptococcus agalactiae (n = 12) and Prototheca spp. (n = 11), to better understand the role of SC methylome in the host response to disease. Differentially methylated regions (DMR) were evaluated comparing: (1) Strep. agalactiae-infected versus healthy; (2) Prototheca-infected versus healthy, and (3) mastitis versus healthy and (4) Strep. agalactiae-infected versus Prototheca-infected. The functional analysis was performed at 2 levels. To begin with, we extracted differentially methylated genes (DMG) from promoter DMR, which were analyzed using the Cytoscape ClueGO plug-in. Coupled with this DMG-driven approach, all the genes associated with promoter-methylated regions were fed to the Pathifier algorithm. From the DMR analysis, we identified 1,081 hypermethylated and 361 hypomethylated promoter regions in Strep. agalactiae-infected animals, while 1,514 hypermethylated and 358 hypomethylated promoter regions were identified in Prototheca-infected animals, when compared with the healthy controls. When considering infected animals as a whole group (regardless of the pathogen), we found 1,576 hypermethylated and 460 hypomethylated promoter regions. Both pathogens were associated with methylation differences in genes involved in pathways related to meiosis, reproduction and tissue remodeling. Exploring the whole methylome, in subclinically infected cows we observed a strong deregulation of immune-related pathways, such as nuclear factor kB and toll-like receptors signaling pathways, and of energy-related pathways such as the tricarboxylic acid cycle and unsaturated fatty acid biosynthesis. In conclusion, no evident pathogen-specific SC methylome signature was detected in the present study. Overall, we observed a clear regulation of host immune response driven by DNA methylation upon subclinical mastitis. Further studies on a larger cohort of animals are needed to validate our results and to possibly identify a unique SC methylome that signifies pathogen-specific alterations.

Progress and future perspectives of livestock genomics in India: a mini review

The field of genetics has evolved a lot after the emergence of molecular and advanced genomic technologies. The advent of Next Generation Sequencing, SNP genotyping platforms and simultaneous reduction in the cost of sequencing had opened the door to genomic research in farm animals. There are various applications of genomics in livestock, such as the use of genomic data: (i) to investigate genetic diversity and breed composition/population structure (ii) to identify genetic variants and QTLs related to economically important and ecological traits, genome-wide association studies (GWAS) and genomic signatures of selection; (iii) to enhance breeding programs by genomic selection. Compared to traditional methods, genomic selection is expected to improve selection response by increasing selection accuracy and reducing the generation interval due to early selection. Genomic selection (GS) in developed countries has led to rapid genetic gains, especially in dairy cattle, due to a well-established genetic evaluation system. Indian livestock system is still lagging behind developed nations in adopting these technologies. This review discusses the current status, challenges, and future perspectives of livestock genomics in India.

Transcriptomic Analysis of Circulating Leukocytes Obtained during the Recovery from Clinical Mastitis Caused by Escherichia coli in Holstein Dairy Cows

Simple Summary

Escherichia coli is a bacterium which infects cow udders causing clinical mastitis, a potentially severe disease with welfare and economic consequences. During an infection, white blood cells (leukocytes) enter the udder to provide immune defence and assist tissue repair. We sequenced RNA derived from circulating leukocytes to investigate which genes are up- or down-regulated in dairy cows with naturally occurring cases of clinical mastitis in comparison with healthy control cows from the same farm. We also looked for genetic variations between infected and healthy cows. Blood samples were taken either EARLY (around 10 days) or LATE (after 4 weeks) during the recovery phase after diagnosis. Many genes (1090) with immune and inflammatory functions were up-regulated during the EARLY phase. By the LATE phase only 29 genes were up-regulated including six haemoglobin subunits, possibly important for the production of new red blood corpuscles. Twelve genetic variations which were associated with an increased or decreased expression of some important immune genes were identified between the infected and control cows. These results show that the initial inflammatory response to E. coli continued for at least 10 days despite the cows having received prompt veterinary treatment, but they had largely recovered within 4 weeks. Genetic differences between cows may predispose some animals to infection.

Abstract

The risk and severity of clinical infection with Escherichia coli as a causative pathogen for bovine mastitis is influenced by the hosts’ phenotypic and genotypic variables. We used RNA-Seq analysis of circulating leukocytes to investigate global transcriptomic profiles and genetic variants from Holstein cows with naturally occurring cases of clinical mastitis, diagnosed using clinical symptoms and milk microbiology. Healthy lactation-matched cows served as controls (CONT, n = 6). Blood samples were collected at two time periods during the recovery phase post diagnosis: EARLY (10.3 ± 1.8 days, n = 6) and LATE (46.7 ± 11 days, n = 3). Differentially expressed genes (DEGs) between the groups were identified using CLC Genomics Workbench V21 and subjected to enrichment analysis. Variant calling was performed following GATKv3.8 best practice. The comparison of E. coli(+) EARLY and CONT cows found the up-regulation of 1090 DEGs, mainly with immune and inflammatory functions. The key signalling pathways involved NOD-like and interleukin-1 receptors and chemokines. Many up-regulated DEGs encoded antimicrobial peptides including cathelicidins, beta-defensins, S100 calcium binding proteins, haptoglobin and lactoferrin. Inflammation had largely resolved in the E. coli(+) LATE group, with only 29 up-regulated DEGs. Both EARLY and LATE cows had up-regulated DEGs encoding ATP binding cassette (ABC) transporters and haemoglobin subunits were also up-regulated in LATE cows. Twelve candidate genetic variants were identified in DEGs between the infected and CONT cows. Three were in contiguous genes WIPI1, ARSG and SLC16A6 on BTA19. Two others (RAC2 and ARHGAP26) encode a Rho-family GTPase and Rho GTPase-activating protein 26. These results show that the initial inflammatory response to E. coli continued for at least 10 days despite prompt treatment and provide preliminary evidence for genetic differences between cows that may predispose them to infection.

Genome-Wide Association Study for Lactation Performance in the Early and Peak Stages of Lactation in Holstein Dairy Cows

Simple Summary

Although genome-wide association studies (GWAS) have been carried out within a variety of cattle breeds, they are mainly based on the accumulated 305-day lactation yield traits estimated by summing the test-day recorded every day during the lactation period, or combining the weekly or monthly test-day records by linear interpolation. Since the additive genetic variance for milk yield and composition changes during lactation, the genetic effects of QTL related to these traits are not constant during the lactation period. Therefore, a better understanding of the genetic architecture of milk production traits in different lactation stages (e.g., beginning, peak, and end stages of lactation) is needed. The aim of this study was to detect genomic loci associated with lactation performance during 9 to 50 days in milk (DIM) in Holstein dairy cows. Candidate genes identified for milk production traits showed contrasting results between the EARLY and PEAK stages of lactation. Based on the results of this study, it can be concluded that in any genomic study it should be taken into account that the genetic effects of genes related to the lactation performance are not constant during the lactation period.

Abstract

This study aimed to detect genomic loci associated with the lactation performance during 9 to 50 days in milk (DIM) in Holstein dairy cows. Daily milk yield (MY), fat yield (FY), and protein yield (PY) during 9 to 50 DIM were recorded on 134 multiparous Holstein dairy cows distributed in four research herds. Fat- and protein-corrected milk (FPCM), fat-corrected milk (FCM), and energy-corrected milk (ECM) were predicted. The records collected during 9 to 25 DIM were put into the early stage of lactation (EARLY) and those collected during 26 to 50 DIM were put into the peak stage of lactation (PEAK). Then, the mean of traits in each cow included in each lactation stage (EARLY and PEAK) were estimated and used as phenotypic observations for the genome-wide association study. The included animals were genotyped with the Illumina BovineHD Genotyping BeadChip (Illumina Inc., San Diego, CA, USA) for a total of 777,962 single nucleotide polymorphisms (SNPs). After quality control, 585,109 variants were analyzed using GEMMA software in a mixed linear model. Although there was no SNP associated with traits included at the 5% genome-wide significance threshold, 18 SNPs were identified to be associated with milk yield and composition at the suggestive genome-wide significance threshold. Candidate genes identified for milk production traits showed contrasting results between the EARLY and PEAK stages of lactation. This suggests that differential sets of candidate genes underlie the phenotypic expression of the considered traits in the EARLY and PEAK stages of lactation. Although further functional studies are needed to validate our findings in independent populations, it can be concluded that in any genomic study it should be taken into account that the genetic effects of genes related to the lactation performance are not constant during the lactation period.