Identification of Important Proteins and Pathways Affecting Feed Efficiency in DLY Pigs by iTRAQ-Based Proteomic Analysis

Abstract

Feed efficiency is an economically important trait controlled by multiple genes in pigs. The small intestine is the main organ of digestion and nutrient absorption. To explore the biological processes by which small intestine proteomics affects feed efficiency (FE), we investigated the small intestinal tissue proteomes of high-FE and low-FE pigs by the isobaric tag for relative and absolute quantification (iTRAQ) method. In this study, a total of 225 Duroc × (Landrace × Yorkshire) (DLY) commercial pigs were ranked according to feed efficiency, which ranged from 30 kg to 100 kg, and six pigs with extreme phenotypes were selected, three in each of the high and low groups. A total of 1219 differentially expressed proteins (DEPs) were identified between the high-FE and low-FE groups (fold change ≥1.2 or ≤0.84; p ≤ 0.05), of which 785 were upregulated, and 484 were downregulated. Enrichment analysis indicated that the DEPs were mainly enriched in actin filament formation, microvilli formation, and small intestinal movement pathways. Protein functional analysis and protein interaction networks indicated that RHOA, HCLS1, EZR, CDC42, and RAC1 were important proteins that regulate FE in pigs. This study provided new insights into the important pathways and proteins involved in feed efficiency in pigs.

Using nontargeted LC-MS metabolomics to identify the Association of Biomarkers in pig feces with feed efficiency

“…The entire experimental process lasted approximately 12 weeks from an initial weight of approximately 30 kg to 100 kg. The calculation methods for FCR and RFI are based on previously described studies [ 49 ]. In this study, FE was defined as the weight gain from 30 kg to 100 kg of body weight divided by the total feed intake, which is the inverse of the commonly used feed conversion ratio (FCR).…”

Application of Genetic, Genomic and Biological Pathways in Improvement of Swine Feed Efficiency

“…However, identifying biological pathways affecting FE is challenging, and GWAS studies are limited in finding the chromosomal regions or preselected genes that might be related to FE ( Singer, 2009 ). Instead, a growing number of studies have applied omics methods to explore the mechanisms affecting FE in pigs, including transcriptomics ( Vigors et al, 2019 ; Xu et al, 2020a ), 16S rRNA gene sequencing ( Quan et al, 2018 ; Si et al, 2020 ), proteomics ( Wu et al, 2020 ), and metabolomics ( Carmelo et al, 2020 ; Wang and Kadarmideen, 2020 ). By screening and analyzing the differentially expressed genes (DEGs) and related biological pathways derived from transcriptomics studies, candidate genes and pathways affecting FE can be identified ( Nagalakshmi et al, 2008 ; Wilhelm and Landry, 2009 ).…”

Using nontargeted LC-MS metabolomics to identify the association of biomarkers in pig feces with feed efficiency

“…The entire experimental process lasted approximately 12 weeks from an initial weight of approximately 30 kg to 100 kg. The calculation methods for FCR and RFI are based on previously described studies [14]. After ranking the FCR values of 225 pigs, the top 25 highest FCR and 25 lowest FCR were selected as the Low-FE and High-FE groups, respectively.…”

“…This analysis was then performed in the positive and negative ion modes. By calculating the adjacency between metabolic features and merging the closer modules, a total of 14 (14) modules were obtained in positive (negative) modes (Supplemental Figure S3). Then, by constructing the correlation matrix between the modules and the phenotypic data related to feed e ciency, the module with the closest correlation to the sample traits was identi ed.…”