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Weighted gene co-expression network analysis reveal gene clusters and pathways related to rumen development in calves

Do D.N., Fomenky B.E., Dudemaine P-L., Bissonnette N. and Ibeagha-Awemu E.M. (2018) Weighted gene co-expression network analysis reveal gene clusters and pathways related to rumen development in calves. Proceedings of the 11th World Congress on Genetics Applied to Livestock Productio, 11.945, February 11 to 16, 2018, Auckland New Zealand. 5 pages.

Abstract

Gene co-expression network analysis of transcriptome data has enabled the identification of key genes and important networks underlying complex production and disease traits. This study used weighted gene co-expression network analysis (WGCNA) approach to (1) detect modules or clusters of differentially expressed genes (DEG) with similar expression patterns in calf rumen transcriptome during pre- and post-weaning periods and (2) identify regulatory mechanisms linking gene modules to relevant phenotypes during the pre-weaning period (day 33 [d33]): weight gain (BWT_d33), average daily gain (ADG_d33), blood glucose (Glucose_d33) and β-hydroxybutyrate (BHB_d33) concentrations and post-weaning period (d96): weight gain (BWT_d96), average daily gain (ADG_d96), blood glucose (Glucose_d96) and β-hydroxybutyrate (BHB_d96) concentrations, dry matter intake (DMI_d96) and feed efficiency (FE_d96). Rumen tissues were collected from 16 calves on d33 and another 16 on d96 for whole transcriptome sequencing followed by bioinformatics processing and DEG analysis. A total of 4,104 DEG between d33 and d96 were used as input for WGCNA analysis. WGCNA identified ten co-expressed gene modules and among them, six were significantly correlated with at least one phenotype (p<0.05). The BLACK module was the most important being significantly correlated with DMI_d96 and ADG_d96. The BLACK module genes (n=269) were significantly enriched for biological processes related to growth and lipid metabolism as well as pathways related to longevity, glucose metabolism and hormone regulation. The BROWN (494 genes) and PINK (508 genes) modules were significantly correlated with BHB_d96 and their genes were significantly enriched for pathways related to rumen functions in response to diet. MAGENTA (155 genes) and ROYALBLUE (40 genes) modules were significantly correlated with Glucose_d33 and their genes were enriched for immune function related pathways. The TURQUOISE module was significantly associated with Glucose_d96 and its genes (n=1,623) were enriched for many processes such as translation, signal transduction, cell communication, protein catabolic process and fatty acid oxidation. In conclusion, this study provides an insight on gene clusters or networks and pathways involved in rumen development. However, further studies are required to characterize the identified gene networks and pathways.

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