Comprehensive Characterization of Long Non-Coding RNAs in Porcine Tissues: Expression Patterns and Functional Insights During Oocyte Development

Long non-coding RNAs (lncRNAs) are essential regulatory molecules involved in various biological processes in mammals. However, their expression patterns across multiple porcine tissues have not been systematically characterized. We analyzed 607 RNA-seq datasets derived from 14 porcine tissues, including backfat, gallbladder, heart, ileum, jejunum, kidney, longissimus dorsi, liver, lung, skeletal muscle, ovary, pituitary, skeletal muscle, and spleen. Additionally, we examined 63 single-cell RNA-seq datasets from porcine primary oocytes at five developmental stages. For comparative analysis, we included 20 human and 17 mouse oocyte RNA-seq datasets. We identified 52,798 porcine lncRNAs, with tissue-specific expression patterns most prominent in oocytes and least in skeletal muscle. Among them, 2169 were classified as housekeeping and 14,469 as tissue-specific lncRNAs. Cross-species analysis revealed that a small subset of oocyte-expressed lncRNAs is conserved in humans and mice, associated with catalytic activity and circadian regulation. Additionally, 44 lncRNAs were differentially expressed during oocyte development, implicating them in neurogenesis, vesicle transport, and protein modification. Our findings not only contribute to the growing body of knowledge regarding lncRNAs in porcine biology but also pave the way for future research aimed at elucidating their functional roles in reproductive biology and other physiological processes.

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Publication Details

Journal
Cells
Published
2025-09-09
DOI
https://doi.org/10.3390/cells14181409
Citations
1
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
0.94

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article

Comprehensive Characterization of Long Non-Coding RNAs in Porcine Tissues: Expression Patterns and Functional Insights During Oocyte Development

Bin Ma, Xiaolong Yuan, Fei Gao, Qingpeng Shen et al.
1 citations
Cells
Cancer-related molecular mechanisms research
0.94
article

Comprehensive Characterization of Long Non-Coding RNAs in Porcine Tissues: Expression Patterns and Functional Insights During Oocyte Development

Bin Ma, Xiaolong Yuan, Fei Gao, Qingpeng Shen, Yao Jiang, Yipeng Li
article en
1 citations

Abstract

Long non-coding RNAs (lncRNAs) are essential regulatory molecules involved in various biological processes in mammals. However, their expression patterns across multiple porcine tissues have not been systematically characterized. We analyzed 607 RNA-seq datasets derived from 14 porcine tissues, including backfat, gallbladder, heart, ileum, jejunum, kidney, longissimus dorsi, liver, lung, skeletal muscle, ovary, pituitary, skeletal muscle, and spleen. Additionally, we examined 63 single-cell RNA-seq datasets from porcine primary oocytes at five developmental stages. For comparative analysis, we included 20 human and 17 mouse oocyte RNA-seq datasets. We identified 52,798 porcine lncRNAs, with tissue-specific expression patterns most prominent in oocytes and least in skeletal muscle. Among them, 2169 were classified as housekeeping and 14,469 as tissue-specific lncRNAs. Cross-species analysis revealed that a small subset of oocyte-expressed lncRNAs is conserved in humans and mice, associated with catalytic activity and circadian regulation. Additionally, 44 lncRNAs were differentially expressed during oocyte development, implicating them in neurogenesis, vesicle transport, and protein modification. Our findings not only contribute to the growing body of knowledge regarding lncRNAs in porcine biology but also pave the way for future research aimed at elucidating their functional roles in reproductive biology and other physiological processes.

CellsVol. 14(18)
South China Agricultural University (CN), Murdoch University (AU), Agricultural Genomics Institute at Shenzhen (CN), Chinese Academy of Agricultural Sciences (CN), Avenir Health (US)
National Supercomputer Centre in Guangzhou
Openalex Percentile: Top 21%
Cancer-related molecular mechanisms research
0.94
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