Candidate gene screening for lipid deposition using combined transcriptomic and proteomic data from Nanyang black pigs

Abstract

Background: Lower selection intensities in indigenous breeds of Chinese pig have resulted in obvious genetic and phenotypic divergence. One such breed, the Nanyang black pig, is renowned for its high lipid deposition and high genetic divergence, making it an ideal model in which to investigate lipid position trait mechanisms in pigs. An understanding of lipid deposition in pigs might improve pig meat traits in future breeding and promote the selection progress of pigs through modern molecular breeding techniques. Here, transcriptome and tandem mass tag-based quantitative proteome (TMT)-based proteome analyses were carried out using longissimus dorsi (LD) tissues from individual Nanyang black pigs that showed high levels of genetic variation.

Results: A large population of Nanyang black pigs was phenotyped using multi-production trait indexes, and six pigs were selected and divided into relatively high and low lipid deposition groups. The combined transcriptomic and proteomic data identified 15 candidate genes that determine lipid deposition genetic divergence. Among them, FASN, CAT, and SLC25A20 were the main causal candidate genes. The other genes could be divided into lipid deposition-related genes (BDH2, FASN, CAT, DHCR24, ACACA, GK, SQLE, ACSL4, and SCD), PPARA-centered fat metabolism regulatory factors (PPARA, UCP3), transcription or translation regulators (SLC25A20, PDK4, CEBPA), as well as integrin, structural proteins, and signal transduction-related genes (EGFR).

Conclusions: This multi-omics data set has provided a valuable resource for future analysis of lipid deposition traits, which might improve pig meat traits in future breeding and promote the selection progress in pigs, especially in Nanyang black pigs.

Keywords: Genetic divergence; Lipid deposition; Multi-omics; Nanyang black pig; Phenotypic divergence; Proteome; Transcriptome.

Fig. 1

Oil red O staining and fatty acid analysis in longissimus dorsi (LD) tissue. A: Oil red O staining using frozen LD samples from each of the 6 pigs, HF: high-fat deposition group, LF: low-fat deposition group; B: Statistical analysis of the ratio of Oil red O-stained regions using students’ T test. Magnification: 16 ×

Fig. 2

Transcriptome differences between the LD tissue samples from the high and low lipid deposition pigs. A: Plot showing the log2 (fold change HF vs. LF) and the –log2 (q-value), where the red and green circles indicate the up-and down-regulated DEGs (|log2 fold change| > 1), q-value < 0.01); B: Heat map of the DEGs in the different lipid deposition groups

Fig. 3

Gene interaction and functional clustering. A: Gene interactions with pathways, pink circle: relative pathway, green rhombus; gene symbols; B: Gene functional clustering by STRING 11.0, yellow: lipid deposition-related gene; blue: eight PPARA-centered fat metabolism regulatory factors; green: transcription regulators; red: proteolysis-related genes, cyan: integrin genes, structural proteins, and signal transduction-related genes

Fig. 4

iRegulon analysis of the DEGs from the transcriptomic analysis. All genes analyzed were previously identified in Fig. 3B. Analysis of A: 27 proteolysis-related DEGs; B: 19 transcription regulator-related DEGs; C: 16 integrin genes, structural proteins, and signal transduction-related DEGs; D: 24 lipid deposition-related DEGs; E: 8 PPARA-centered fat metabolism regulatory factor gene-related DEGs

Fig. 5

Gene overlapping and validation. A: Genes that overlapped between KEGG and STRING. Yellow: lipid deposition-related gene; blue: eight PPARA-centered fat metabolism regulatory factors; green: transcription regulators; cyan: integrin genes, structural proteins, signal transduction-related genes; B: qRT-PCR of the 14 DEGs from the LD and backfat (BF) tissues

Fig. 6

Differentially expressed protein identification and function analysis. A: GO analysis of the DEPs. B: KEGG analysis of the DEPs

Fig. 7

Venn plot of the candidate proteins and DEGs for lipid deposition