title: Genomic and transcriptomic approaches to investigating candidate genes associated with tick resistance in cattle
Creators: name: Chooyoung, Kamonchanok
Publisher: name: University of Glasgow
Year: 2024

description: The cattle tick, Rhipicephalus (Boophilus) microplus, is able to transmit tick-borne diseases in cattle, which causes major production and welfare implications, particularly in tropical and subtropical areas. Problems associated with cattle ticks, such as decreased production yield, mortality, and costs of treatment are economically significant. Although resistance to ticks in cattle is moderately heritable (0.4), there are no genes or biomarkers commercially available that could be used for genomic selection. The aim of this study was to identify genes and pathways associated with tick resistance in cattle using a meta-analysis of previous studies, combined with single nucleotide polymorphism (SNP) based genotyping and long-read sequence-based transcriptomics. 

Previous gene expression (GEX) and genome-wide association studies (GWAS) have identified a large number of potential genes or quantitative trait loci (QTLs) associated with tick resistance in cattle. However, different studies have found different sets of genes, using different experimental procedures and platforms. In Chapter 2, I aimed to integrate results from differential expression genes (DEGs) and QTLs from GWAS associated with host resistance to infestation with R. microplus in order to generate a list of genes which showed supporting evidence from multiple sources. I identified a set of 37 genes that were found in multiple studies, based on blood or skin gene expression and GWAS, including three transcription factors, 12 genes associated with immune function, nine with the extracellular matrix, six structural genes, and 13 other biological processes. This subset of genes was then used to investigate whether there was sufficient variability that they could potentially be used as targets of selection (Chapter 3). 

To develop animals breed to be resilient to foreign invasion (pathogens and ectoparasites), it may be necessary to focus not only on genes associated with immune function but also on other types of pathways. The aim of Chapter 3 was to determine whether any of the genes shortlisted from Chapter 2 showed significant differences in genotypes between Scottish breed groups, including British (n=14), European (Continental) (n=10), and Hill (n=10) cattle. Focusing on breeds within Scotland provided a conservative estimate of variability of these genes. The genotyping was investigated from DNA extracted from spleen tissue samples from individuals collected from a single abattoir, by using the GeneSeek Genomic Profile (GGP) Bovine 100K SNP chip. A total of 88 SNPs were identified from the list of candidate genes, with 14 spread across six genes (HOXD1, SATB2, GIMAP7, ITGA11, PLA2G7, and PRKG1) presenting significant differences in genotype frequencies between the breed groups. Although most of the SNPs were located in introns that were not close enough to exons to expect linkage to mutations under selection, only a single amino acid changing variant was identified in PLA2G7-1 (missense mutation), with the other 13 being either synonymous changes within an exon (ITGA11) or located in introns. This list of SNPs was then used to classify gene expression patterns from skin and spleen samples from the same individuals in Chapter 4. 

All of the previous studies identifying genes showing differential expression associated with resistance to ticks in cattle have focused on skin or blood samples in Chapter 2; however, immune functions are more pronounced in tissues such as spleen or lymph nodes. Chapter 4 was a pilot study aimed at identifying genome-wide patterns of gene expression (transcriptome profiles) in both skin and spleen tissue samples using GridION from Oxford Nanopore Technology (ONT). The data were analysed using a weighted gene co-expression network analysis (WGCNA) correlated with variation in the 14 significant SNPs from Chapter 3. In skin datasets, seven modules showed significant correlations with at least one of the SNPs in the skin dataset, which contained 2,297 genes, whereas there were ten modules in the spleen dataset (3,265 genes). Overall, I found different sets of co-expressed gene modules associated with variation in the SNPs in the two tissue types, with a wider range of modules associated with the spleen but also more pathways directly related to immune function. Nevertheless, both tissues identified multiple biological pathways and interactions between pathways correlated with genotype variation at the focal genes. From the large set of genes identified in these pathways, I found three genes (FN1, ATP9A, and ECM1) from the skin dataset and five (CR2, RHOT1, SRGN, GIMAP7, and LAPTM5 ) from the spleen dataset that overlapped with the list of 37 candidate genes identified in Chapter 2. Only one of these (GIMAP7) also showed significant variation on the SNP genotyping panel, suggesting that it could make a useful candidate to consider further. Here I provided preliminary evidence about candidate genes connecting the genotype and phenotype (gene expression) across different tissues (skin and spleen) and developed predictions about potential biomarkers. Further analyses to identify tissue-specific novel isoforms, alternative splicing and their respective biological functions in cattle could provide additional support for the utility of the genes identified for marker-based selection. 

The integration of the genes or QTLs from multiple resources, the SNP genotype variation, and the transcriptome profiling in this study offer a potential panel of biomarkers which could be evaluated in pathogen and ectoparasite resistance in cattle studies and develop improvements for the future selection and breeding programs in cattle. The understanding of the genetic basis for resistance in cattle offers preliminary evidence that could impact beef and dairy production efficiency and product quality, especially in tropical and subtropical regions.