# Integrating transcriptomic and genomic studies for the identification of expression quantitative trait loci associated with bovine paratuberculosis

## TL;DR

This paper reviews how combining genomic and transcriptomic data helps identify genetic factors linked to cattle resistance or susceptibility to paratuberculosis.

## Contribution

The paper highlights the integration of transcriptomic and genomic data to identify and interpret cis-eQTLs related to bovine paratuberculosis.

## Key findings

- Most GWAS SNPs are in non-coding regions, complicating functional interpretation.
- Cis-eQTLs offer insights into gene expression changes affecting PTB resistance or susceptibility.
- Validated cis-eQTLs could be used in genomic selection and CRISPR-based editing.

## Abstract

The study of the genetic basis underlying the host response to Mycobacterium avium subsp. paratuberculosis (MAP) is usually performed using genome-wide association studies (GWAS), which assess the individual association between genotyped markers, typically single-nucleotide polymorphisms (SNPs), and phenotypic traits of interest (quantitative or qualitative). However, most SNPs identified through GWAS are located in non-coding regions, making it challenging to determine their functional relevance and to link them to target genes. To date, only a limited number of cis-expression quantitative trait loci (cis-eQTLs) with effects on gene expression and susceptibility or resistance to bovine paratuberculosis (PTB) have been characterized. Cis-QTLs can influence mRNA expression by altering the level, timing, or localization of gene expression, thereby potentially contributing to variability in PTB susceptibility or resistance. This review synthesizes recent efforts to uncover the genetic architecture of resistance or susceptibility to MAP infection by integrating transcriptomic and genomic data, with a particular focus on the identification and functional interpretation of cis-eQTLs. Furthermore, we discuss the potential practical applications of validated cis-eQTLs in genomic selection programs, genetic screening assays, and CRISPR-based genome editing approaches.