The inclusion of organic acid to cereal feed improves growth performance in Pigs
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ABSTRACT:
PROVIDER: PRJEB66329 | ENA |
REPOSITORIES: ENA
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Project description:Purpose: RNA-seq method was applied to select genes expressed in feed conversion in pigs and pinpointed genes potentially associated with this feature. Methods: The whole pituitary samples were collected from 16 Puławska pigs (8 pigs per two groups - with high and low feed conversion) maintained at the same environmental and feeding condition. The RNA-seq analysis was performed in 90 single-end cycles on HiScanSQ platform (Illumina) and differentially expressed genes (DEGs) were determined using Deseq2 software. Validation was performed for 10 randomly selected genes using real-time PCR method. Results: The study showed that in pigs characterized by better feed conversion 274 genes were differentially expressed. Genes showed decreased expression encode proteins associated with cholesterol metabolism (APOA1, CH25H, APOE) and regulation of hormone levels (POMC, CTSZ, ADM, AGTR1, SOX8, AGT, CPT1, APOA1, GJA1, MYRIP, CYP1B1, NR1D1). Four genes showed over the 10-fold decrease of expression (CRYM, ISM1 and WNK4), where the CRYM protein binds thyroid hormone for regulatory and developmental roles and WNK4 regulates the balance between NaCl reabsorption and K(+) secretion. In turn, genes showed an increase of expression in the pituitary of pigs having better feed conversion encode proteins were related to cellular response to corticotropin-releasing hormone stimulus (NR4A1, NR4A2, NR4A3) and regulation of type B pancreatic cell proliferation (BIRC5, NR4A3, NR4A1). Conclusions: The present study indicates new genes potentially related to feed conversion, which is one of the most economically important traits in pig breeding. The selected genes should be investigated in future in the terms of their association with fattening traits. The study was financed from funds of the project -BIOSTRATEG, the decision number BIOSTRATEG2/297267/14/NCBR/2016.
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Project description:Interactions among genomic loci have often been overlooked in genome-wide association studies, revealing the combinatorial effects of variants on phenotype or disease manifestation. Unexplained genetic variance, interactions amongst causal genes of small effects, and biological pathways could be identified using a network biology approach. The main objective of this study was to determine the genome-wide epistatic variants affecting feed efficiency traits [feed conversion ratio (FCR) and residual feed intake (RFI)] based on weighted interaction SNP hub (WISH-R) method. Herein, we detected highly interconnected epistatic SNP modules, pathways, and potential biomarkers for the FCR and RFI in Duroc and Landrace purebreds considering the whole population, and separately for low and high feed efficient groups. Highly interacting SNP modules in Duroc (1,247 SNPs) and Landrace (1,215 SNPs) across the population and for low feed efficient (Duroc - 80 SNPs, Landrace - 146 SNPs) and high feed efficient group (Duroc - 198 SNPs, Landrace - 232 SNPs) for FCR and RFI were identified. Gene and pathway analyses identified ABL1, MAP3K4, MAP3K5, SEMA6A, KITLG, and KAT2B from chromosomes 1, 2, 5, and 13 underlying ErbB, Ras, Rap1, thyroid hormone, axon guidance pathways in Duroc. GABBR2, GNA12, and PRKCG genes from chromosomes 1, 3, and 6 pointed towards thyroid hormone, cGMP-PKG and cAMP pathways in Landrace. From Duroc low feed efficient group, the TPK1 gene was found involved with thiamine metabolism, whereas PARD6G, DLG2, CRB1 were involved with the hippo signaling pathway in high feed efficient group. PLOD1 and SETD7 genes were involved with lysine degradation in low feed efficient group in Landrace, while high feed efficient group pointed to genes underpinning valine, leucine, isoleucine degradation, and fatty acid elongation. Some SNPs and genes identified are known for their association with feed efficiency, others are novel and potentially provide new avenues for further research. Further validation of epistatic SNPs and genes identified here in a larger cohort would help to establish a framework for modelling epistatic variance in future methods of genomic prediction, increasing the accuracy of estimated genetic merit for FE and helping the pig breeding industry.
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