A compendium of genetic regulatory effects across pig tissues

Fang, Lingzhao; Teng, Jinyan; Gao, Yahui; Yin, Hongwei; Bai, Zhonghao; Liu, Shuli; Zeng, Haonan; Bai, Lijing; Cai, Zexi; Zhao, Bingru; Li, Xiujin; Xu, Zhiting; Lin, Qing; Pan, Zhangyuan; Yang, Wenjing; Yu, Xiaoshan; Guan, Dailu; Hou, Yali; Keel, Brittney N; Rohrer, Gary A.; Lindholm‐Perry, A. K.; Oliver, W. T.; Ballester, María; Crespo-Piazuelo, Daniel; Quintanilla, Raquel; Canela-Xandri, Oriol; Rawlik, Konrad; Xia, Charley; Yao, Yuelin; Zhao, Qianyi; Wang, Yao; Liu, Yang; Li, Houcheng; Zhang, Huicong; Wang, Liao; Chen, Tianshuo; Karlskov-Mortensen, Peter; Fredholm, Merete; Amills, Marcel; Clop, Alex; Giuffra, Elisabetta; Wu, Jun; Cai, Xiaodian; Diao, Shuqi; Pan, Xiangchun; Chen, Wei; Li, Jinghui; Ho, Cheng; Wang, Sheng; Su, Guosheng; Sahana, Goutam; Lund, Mogens Sandø; Dekkers, Jack C. M.; Kramer, Luke M.; Tuggle, Christopher K.; Corbett, Ryan J.; Groenen, Martien A. M.; Madsen, Ole; Gòdia, Marta; Rocha, Dominique; Charles, Mathieu; Li, Congjun; Pausch, Hubert; Hu, Xiaoxiang; Frantz, Laurent; Luo, Yonglun; Lin, Lin; Zhou, Zhongyin; Zhang, Zhe; Chen, Zitao; Cui, Leilei; Xiang, Ruidong; Shen, Xia; Li, Pinghua; Huang, Ruihua; Tang, Guiqian; Li, Mingzhou; Zhao, Yunxiang; Yi, Guoqiang; Tang, Zhonglin; Jiang, Jicai; Zhao, Fuping; Yuan, Xiaolong; Liu, Xiaohong; Chen, Yaosheng; Xu, Xuewen; Zhao, Shuhong; Zhao, Pengju; Haley, Chris; Zhou, Huaijun; Wang, Qishan; Pan, Yuchun; Ding, Xiangdong; Ma, Li; Li, Jiaqi; Navarro, Pau; Zhang, Qin; Li, B.; Tenesa, Albert; Li, Kui; Liu, George; Zhang, Zhe

doi:10.21203/rs.3.rs-2261680/v1

Cited by 3 publications

(5 citation statements)

References 109 publications

(154 reference statements)

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“…1d), which may be caused by special transcriptome features of the reproductive cells. The above results showed that tissue differentiation is a major factor of transcriptome differentiation, which was consistent with the observation from other species, including humans, cattle, and pigs [10][11][12]34]. These results demonstrate that transcriptome similarity among tissues is associated with tissue biological function similarity.…”

Section: Tissue Differentiation Causes Different Gene Expression Pro Lessupporting

confidence: 90%

“…It has been demonstrated that it can improve the genomics prediction accuracy when integrating TEGs into the genome prediction model for genomic selection breeding [9]. In mammals, genotype-tissue expression projects (GTEx) were characterized by integrating large-scale gene expression pro ling to gain insight into the transcriptions landscape and identify regulatory [10,[10][11][12]. Thus far, a large amount of RNA-Seq data for sorghum has been generated, however, rare efforts were made to comprehensively analyze the large collection of RNA-seq datasets to characterize the expression landscape in sorghum.…”

Section: Introductionmentioning

confidence: 99%

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Transcriptome-Wide Analysis of Gene Expression Landscape And Starch Synthesis Pathway Coexpression Network in Sorghum

Chen

Olatoye

et al. 2023

Preprint

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Background Gene expression landscape across different tissues and developmental stages reflects their biological functions and evolutionary patterns. Integrative and comprehensive analyses of all transcriptomic data in an organism are instrumental to obtaining a complete picture of their expression landscape and tissue specificity. Such studies are still very limited in an important crop plant, sorghum, which has been used as a popular model to study drought and temperature tolerance. It also limits the discovery of the genetic basis underlying complex agricultural traits in sorghum. Results We characterized the genome-wide expression landscape for sorghum using 873 RNA-sequencing (RNA-seq) datasets representing 19 tissues. Our integrative analysis of these RNA-seq data provides the most comprehensive transcriptomic atlas for sorghum, which will be valuable for the sorghum research community for functional characterizations of sorghum genes. Based on the transcriptome atlas, we identified 595 housekeeping genes (HKGs) and 2,080 tissue-specific express genes (TEGs) for the 19 tissues. We identified different gene features between HKGs and TEGs, and we found that HKGs have experienced stronger selective constraints than TEGs. Furthermore, we built a transcriptome-wide co-expression network (TW-CEN) comprising 35 modules with each model having specific Gene Ontology terms enriched. High connectivity genes in TW-CEN tend to express at high levels while undergoing intensive selective pressure. With the TW-CEN, we also built global and seed-preferential co-expression networks of starch synthesis pathways, which showed that several pathways such as photosynthesis, microtubule-based movement, carotenoid biosynthesis, glycerol ether metabolic processes play important roles in starch synthesis. Conclusions The global transcriptome atlas of sorghum generated by this study provides an important functional genomics resource for traits discovery and insight into starch synthesis regulation in sorghum.

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Section: Tissue Differentiation Causes Different Gene Expression Pro Lessupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Transcriptome-Wide Analysis of Gene Expression Landscape And Starch Synthesis Pathway Coexpression Network in Sorghum

Chen

Olatoye

et al. 2023

Preprint

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“…Finally, although 24,745 circRNAs were identified in this study, the data volume needs further supplementation. There are a large number of genomic data in pigGTEx, but circRNA research is still lacking [53]. In the future, we hope to include more data, such as pigGTEx data, in the circRNA analysis, aiming to discover more novel circRNAs and thus more comprehensively complement the circRNA data.…”

Section: Discussionmentioning

confidence: 99%

“…However, there are still some limitations in this study. Although Teng et al have demonstrated that tissue-specific factors have a greater influence in transcriptome analysis than sex, breeding, age, and other factors [53], we categorized these factors as batch effects in our study due to the absence of some annotation information in the data. This approach, as compared to individually correcting for each factor, may introduce some deviation.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive Analysis of CircRNA Expression Profiles in Multiple Tissues of Pigs

Shen,

Gong,

Pan

et al. 2023

IJMS

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Circular RNAs (circRNAs) are a class of non-coding RNAs with diverse functions, and previous studies have reported that circRNAs are involved in the growth and development of pigs. However, studies about porcine circRNAs over the past few years have focused on a limited number of tissues. Based on 215 publicly available RNA sequencing (RNA-seq) samples, we conducted a comprehensive analysis of circRNAs in nine pig tissues, namely, the gallbladder, heart, liver, longissimus dorsi, lung, ovary, pituitary, skeletal muscle, and spleen. Here, we identified a total of 82,528 circRNAs and discovered 3818 novel circRNAs that were not reported in the CircAtlas database. Moreover, we obtained 492 housekeeping circRNAs and 3489 tissue-specific circRNAs. The housekeeping circRNAs were enriched in signaling pathways regulating basic biological tissue activities, such as chromatin remodeling, nuclear-transcribed mRNA catabolic process, and protein methylation. The tissue-specific circRNAs were enriched in signaling pathways related to tissue-specific functions, such as muscle system process in skeletal muscle, cilium organization in pituitary, and cortical cytoskeleton in ovary. Through weighted gene co-expression network analysis, we identified 14 modules comprising 1377 hub circRNAs. Additionally, we explored circRNA–miRNA–mRNA networks to elucidate the interaction relationships between tissue-specific circRNAs and tissue-specific genes. Furthermore, our conservation analysis revealed that 19.29% of circRNAs in pigs shared homologous positions with their counterparts in humans. In summary, this extensive profiling of housekeeping, tissue-specific, and co-expressed circRNAs provides valuable insights into understanding the molecular mechanisms of pig transcriptional expression, ultimately deepening our understanding of genetic and biological processes.

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“…Numerous international consortium projects, such as the Genotype-Tissue Expression (GTEx) [3] and the International Human Epigenome Consortium (IHEC) [4], have been initiated with the objective of establishing the correlation between genetic variation and gene expression in human tissues and deciphering the epigenetic regulation of cell states that are relevant to human health and disease. Recently, with technological advancement and data accumulation, integration of large-scale multi-omics data has gradually been applied in the field of agricultural animals, including the CattleGTEx Project [5], the PigGTEx Project [6] and the construction of multi-tissue gene expression atlases in beef cattle [7] and pigs [8].…”

Section: Introductionmentioning

confidence: 99%

A Multi-Tissue Gene Expression Atlas of Water Buffalo (Bubalus bubalis) Reveals Transcriptome Conservation between Buffalo and Cattle

Dai

et al. 2023

Genes

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We generated 73 transcriptomic data of water buffalo, which were integrated with publicly available data in this species, yielding a large dataset of 355 samples representing 20 major tissue categories. We established a multi-tissue gene expression atlas of water buffalo. Furthermore, by comparing them with 4866 cattle transcriptomic data from the cattle genotype–tissue expression atlas (CattleGTEx), we found that the transcriptomes of the two species exhibited conservation in their overall gene expression patterns, tissue-specific gene expression and house-keeping gene expression. We further identified conserved and divergent expression genes between the two species, with the largest number of differentially expressed genes found in the skin, which may be related to structural and functional differences in the skin of the two species. This work provides a source of functional annotation of the buffalo genome and lays the foundations for future genetic and evolutionary studies in water buffalo.

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A compendium of genetic regulatory effects across pig tissues

Cited by 3 publications

References 109 publications

Transcriptome-Wide Analysis of Gene Expression Landscape And Starch Synthesis Pathway Coexpression Network in Sorghum

Transcriptome-Wide Analysis of Gene Expression Landscape And Starch Synthesis Pathway Coexpression Network in Sorghum

Comprehensive Analysis of CircRNA Expression Profiles in Multiple Tissues of Pigs

A Multi-Tissue Gene Expression Atlas of Water Buffalo (Bubalus bubalis) Reveals Transcriptome Conservation between Buffalo and Cattle

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