Genome-Wide Association Analysis Identifies Genomic Regions and Candidate Genes for Growth and Fatness Traits in Diannan Small-Ear (DSE) Pigs

Liu, Mei; Lan, Qun; Yang, Long; Deng, Qiuchun; Wei, Taiyun; Zhao, Heng; Peng, Peiya; Lin, Xiaoding; Chen, Yuhan; Ma, Haiming; Wei, Hong‐Jiang; Yin, Yulong

doi:10.3390/ani13091571

Cited by 3 publications

(1 citation statement)

References 49 publications

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“…During the process of natural selection, Chinese indigenous pig breeds have exhibited numerous outstanding characteristics and significant phenotypic variations (3). Diannan small ears (DSE) pig is a small Chinese indigenous breed with slow growth and low adult weight (4). They are grown in the southern areas of Mengla, Ruili, and Yingjiang in Yunnan Province, which have a subtropical climate (5).…”

Section: Introductionmentioning

confidence: 99%

Comparison of differentially expressed genes in longissimus dorsi muscle of Diannan small ears, Wujin and landrace pigs using RNA-seq

Li,

Hao,

Zhu

et al. 2024

Front. Vet. Sci.

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IntroductionPig growth is an important economic trait that involves the co-regulation of multiple genes and related signaling pathways. High-throughput sequencing has become a powerful technology for establishing the transcriptome profiles and can be used to screen genome-wide differentially expressed genes (DEGs). In order to elucidate the molecular mechanism underlying muscle growth, this study adopted RNA sequencing (RNA-seq) to identify and compare DEGs at the genetic level in the longissimus dorsi muscle (LDM) between two indigenous Chinese pig breeds (Diannan small ears [DSE] pig and Wujin pig [WJ]) and one introduced pig breed (Landrace pig [LP]).MethodsAnimals under study were from two Chinese indigenous pig breeds (DSE pig, n = 3; WJ pig, n = 3) and one introduced pig breed (LP, n = 3) were used for RNA sequencing (RNA-seq) to identify and compare the expression levels of DEGs in the LDM. Then, functional annotation, Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and Protein–Protein Interaction (PPI) network analysis were performed on these DEGs. Then, functional annotation, Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and Protein-Protein Interaction (PPI) network analysis were performed on these DEGs.ResultsThe results revealed that for the DSE, WJ, and LP libraries, more than 66, 65, and 71 million clean reads were generated by transcriptome sequencing, respectively. A total of 11,213 genes were identified in the LDM tissue of these pig breeds, of which 7,127 were co-expressed in the muscle tissue of the three samples. In total, 441 and 339 DEGs were identified between DSE vs. WJ and LP vs. DSE in the study, with 254, 193 up-regulated genes and 187, 193 down-regulated genes in DSE compared to WJ and LP. GO analysis and KEGG signaling pathway analysis showed that DEGs are significantly related to contractile fiber, sarcolemma, and dystrophin-associated glycoprotein complex, myofibril, sarcolemma, and myosin II complex, Glycolysis/Gluconeogenesis, Propanoate metabolism, and Pyruvate metabolism, etc. In combination with functional annotation of DEGs, key genes such as ENO3 and JUN were identified by PPI network analysis.DiscussionIn conclusion, the present study revealed key genes including DES, FLNC, PSMD1, PSMD6, PSME4, PSMB4, RPL11, RPL13A, ROS23, RPS29, MYH1, MYL9, MYL12B, TPM1, TPM4, ENO3, PGK1, PKM2, GPI, and the unannotated new gene ENSSSCG00000020769 and related signaling pathways that influence the difference in muscle growth and could provide a theoretical basis for improving pig muscle growth traits in the future.

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Section: Introductionmentioning

confidence: 99%

Comparison of differentially expressed genes in longissimus dorsi muscle of Diannan small ears, Wujin and landrace pigs using RNA-seq

Li,

Hao,

Zhu

et al. 2024

Front. Vet. Sci.

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Association analysis of the sorting nexin 29 (SNX29) gene copy number variations with growth traits in Diannan small-ear (DSE) pigs

Yang,

Lin,

Chen

et al. 2024

Animal Biotechnology

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Efficient and Intelligent Feature Selection via Maximum Conditional Mutual Information for Microarray Data

Zhang,

Li,

Yang

et al. 2024

Applied Sciences

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The challenge of analyzing microarray datasets is significantly compounded by the curse of dimensionality and the complexity of feature interactions. Addressing this, we propose a novel feature selection algorithm based on maximum conditional mutual information (MCMI) to identify a minimal feature subset that is maximally relevant and non-redundant. This algorithm leverages a greedy search strategy, prioritizing both feature quality and classification performance. Experimental results on high-dimensional microarray datasets demonstrate our algorithm’s superior ability to reduce dimensionality, eliminate redundancy, and enhance classification accuracy. Compared to existing filter feature selection methods, our approach exhibits higher adaptability and intelligence.

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Genome-Wide Association Analysis Identifies Genomic Regions and Candidate Genes for Growth and Fatness Traits in Diannan Small-Ear (DSE) Pigs

Cited by 3 publications

References 49 publications

Comparison of differentially expressed genes in longissimus dorsi muscle of Diannan small ears, Wujin and landrace pigs using RNA-seq

Comparison of differentially expressed genes in longissimus dorsi muscle of Diannan small ears, Wujin and landrace pigs using RNA-seq

Association analysis of the sorting nexin 29 (SNX29) gene copy number variations with growth traits in Diannan small-ear (DSE) pigs

Efficient and Intelligent Feature Selection via Maximum Conditional Mutual Information for Microarray Data

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