PSIV-5 Prioritizing candidate genes for seminal traits and residual feed intake in cattle: Integrating QTLome Analysis and RNAseq Datasets

• Published in: Journal of animal science Vol. 102; no. Supplement_3; pp. 556 - 557
• Main Authors: Garcia, Emmanuel, Jahuey-Martínez, Francisco Joel, Carrasco V, Julissa, Martinez-Quintana, Jose A A, Rodríguez-Almeida, Felipe A
• Format: Journal Article
• Language: English
• Published: 14.09.2024
• ISSN: 0021-8812; 1525-3163
• DOI: 10.1093/jas/skae234.624

Abstract The QTLome represents the collection of QTLs (quantitative trait loci) documented for each trait within a specific species, detailing the position, effect, and mode of inheritance of each locus. Despite the abundance of known QTLs for productive traits in cattle, only a few genes have been identified as selection markers. This study aimed to prioritize genes within validated QTLs associated with crucial traits in cattle by integrating this information with RNAseq data. Initially, bovine QTLs (n = 161,730) were sourced from the AnimalQTLdb database (version 44), and both graphical and quantitative analyses were conducted using R software. Only annotations within the UMD 3.1 genome were considered, with overlapping QTLs from the same scientific report grouped together. Following quality control measures, the number of QTLs was reduced to 37,146. Validated QTLs were determined by identifying overlapping annotations from various studies or those within a distance of < 1 Mb for the same phenotypic trait, resulting in a total of 3,856 validated QTLs. For gene prioritization, validated QTLs were selected based on semen traits and residual feed intake (RFI). Transcriptomes corresponding to these traits were sourced from NCBI (PRJNA516089 and PRJEB7696). Sequence filtering was performed using the fastp program, and transcript counts were obtained with SALMON software. Sequences were aligned to the Ensembl UMD 3.1 reference genome (version 94), and differential expression analysis was conducted using the R package DESeq2, considering only the group factor (high/low) for each trait (fertility/RFI). Integration of QTLs and transcriptomes utilized the methodology of the cageminer R package, which prioritizes candidate genes within validated QTLs, identifies those grouped in co-expression modules enriched by reference genes, and correlates with the study phenotype (biserial r > 0.2). Reference genes were obtained from Ignatieva et al. (2021 PMID 34290736) and Chen et al. (2021; PMID 33664767). Among the 18 validated QTLs for semen traits, four candidate genes (TSPAN6, QSER1, ADRB2, AKAP4) were identified. Except for ADRB2, these genes exhibited significant differential expression (P < 0.05) in contrasting groups of Holstein cattle. They are associated with semen traits and perform functions such as regulation of spermatogenesis, development, activation, and cell growth. Regarding RFI, 127 validated QTLs yielded 205 prioritized genes, of which 123 showed significant differential expression (P < 0.05) in divergent groups of the Nelore breed. These genes are involved in the immune response and the polymerization and organization of actin filaments, processes that have been reported as biologically relevant to RFI. The implemented strategy was efficient for gene prioritization through the integration of QTLs and RNAseq.