Genome-wide annotation of protein-coding genes in pig

Karlsson, Max; Oksvold, Per; Sivertsson, Åsa; Huang, Jinrong; Álvez, María Bueno; Arif, Muhammad; Li, Xiangyu; Lin, Lin; Yu, Jiaying; Ma, Tao; Xu, Fengping; Han, Peng; Jiang, Hui; Mardinoğlu, Adil; Zhang, Cheng Cheng; Feilitzen, Kalle von; Xu, Xun; Wang, Jian; Yang, Huanming; Bolund, Lars; Zhong, Wen; Fagerberg, Linn; Lindskog, Cecilia; Pontén, Fredrik; Mulder, Jan; Luo, Yonglun; Uhlén, Mathias

doi:10.1186/s12915-022-01229-y

Cited by 19 publications

(20 citation statements)

References 86 publications

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“…Antibodies produced within the HPA project (see Supplementary Data 14 for antibody information) with high reliability (based on human antibody validation 112 , 113 ), and over 80% sequence homology to pig orthologs was used for immunostaining. All antibodies are published on the HPA portal ( www.proteinatlas.org ) with more details about antibody reliability and tissue distribution in humans Formalin-fixed paraffin-embedded (FFPE) pig tissues, previously validated and prepared 30 , was utilized for validating that scRNA-seq is a robust method for the classification of different cell types. The staining protocol follows our previous study by Karlsson et al, as briefly described below.…”

Section: Methodsmentioning

confidence: 99%

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Endothelial cell heterogeneity and microglia regulons revealed by a pig cell landscape at single-cell level

et al. 2022

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Pigs are valuable large animal models for biomedical and genetic research, but insights into the tissue- and cell-type-specific transcriptome and heterogeneity remain limited. By leveraging single-cell RNA sequencing, we generate a multiple-organ single-cell transcriptomic map containing over 200,000 pig cells from 20 tissues/organs. We comprehensively characterize the heterogeneity of cells in tissues and identify 234 cell clusters, representing 58 major cell types. In-depth integrative analysis of endothelial cells reveals a high degree of heterogeneity. We identify several functionally distinct endothelial cell phenotypes, including an endothelial to mesenchymal transition subtype in adipose tissues. Intercellular communication analysis predicts tissue- and cell type-specific crosstalk between endothelial cells and other cell types through the VEGF, PDGF, TGF-β, and BMP pathways. Regulon analysis of single-cell transcriptome of microglia in pig and 12 other species further identifies MEF2C as an evolutionally conserved regulon in the microglia. Our work describes the landscape of single-cell transcriptomes within diverse pig organs and identifies the heterogeneity of endothelial cells and evolutionally conserved regulon in microglia.

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Section: Methodsmentioning

confidence: 99%

“…Recently, the pig BodyMap atlas with the conventional bulk RNA-seq method has been reported 29 . Using similar bulk RNA-seq based transcriptome profiling, we have systematically profiled the protein-coding transcriptome in 98 pig tissues ( www.rnaatlas.org ) 30 .…”

Section: Introductionmentioning

confidence: 99%

Endothelial cell heterogeneity and microglia regulons revealed by a pig cell landscape at single-cell level

et al. 2022

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“…Genes in this cluster were enriched for KEGG pathways including "steroid biosynthesis" (p = 1.91 × 10 -11 ), "aldosterone synthesis and secretion" (p = 7.10 × 10 -6 ), and "cortisol synthesis and secretion" (p = 1.46 × 10 -5 ) (Figure 4B). The expression of STAR and CYP11A1 in chicken adrenal glands differs from human, mouse, pig, and sheep, and is restricted to adrenal glands with specific high expression, in which the expression level of STAR was nearly 500-fold higher than that of ovarian tissue (Karlsson et al, 2022). Adrenal steroidogenesis is carried out by microsomal and mitochondrial enzymes, which are highly conserved among vertebrates (Castillo et al, 2015).…”

Section: The Adrenal Glandmentioning

confidence: 99%

A Gene Expression Atlas of Lohmann White Chickens

Zhang

Wang

et al. 2022

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Chicken (Gallus gallus domesticus) as one of the most economically important farm animals plays a major role in human food production and has been widely used as a key animal model that is presumed to be typical of avian and generally applicable to mammals in studies of developmental biology, virology, oncogenesis, and immunology. To get a better understanding of avian biology, global analysis of gene expression across multiple tissues is needed, which will aid genome annotation and support functional annotation of avian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult Lohmann White domesticus chickens. An open-access chicken tissue gene expression atlas (TGEA) (chickenatlas.avianscu.com) is presented based on the expression of 224 samples across 38 well-defined chicken tissues. Network-based cluster analysis of this dataset grouped genes according to dimensionality reduction and whole-body co-expression patterns, which were used to infer the function of uncharacterized genes from their co-expression with genes of known function. We describe the distribution and tissue specificity of 21,430 genes present in the chicken gene expression atlas and assign those signatures, where possible, to specific tissue populations or pathways. To better understand the functions of GPCRs in avian, we quantified the transcript levels of 254 nonodorant GPCRs in all tissues. Cluster analysis placed many GPCRs into expected anatomical and functional groups and predicted previously unidentified roles for less-studied receptors. We also produced this atlas to analyze male and female mRNA expression profiles in chicken somatic and gonad tissues. Our analyses uncovered numerous cases of somatic sex-biased mRNA expression, with the largest proportion found in the chicken pineal body, pituitary, and liver. This high-resolution gene expression atlas for chickens is, to our knowledge, the largest transcriptomic dataset of any avian to date. It provides a resource to improve the annotation of the current reference genome for chicken, presenting a model transcriptome for avian, and can be used as a resource for predicting roles for incompletely characterized GPCRs, exploring sex-biased specific gene expression, and for other purposes.

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“…Investigating region-specific gene expression can help to understand life processes and physiological functions. The region-specific transcriptomic analyses have been reported in many farm animals, for instance, water buffalo [ 17 ], sheep [ 18 ], pigs [ 19 ], cattle [ 20 ], which provide valuable insights into understanding the expression regulation involved with functional differences among regions. Our study identified a total of 80 RSGs in multiple beef cuts from different regions based on the previously described method [ 13 ].…”

Section: Discussionmentioning

confidence: 99%

Comparative transcriptomic analysis reveals region-specific expression patterns in different beef cuts

et al. 2022

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Background Beef cuts in different regions of the carcass have different meat quality due to their distinct physiological function. The objective of this study was to characterize the region-specific expression differences using comparative transcriptomics analysis among five representative beef cuts (tenderloin, longissimus lumborum, rump, neck, chuck). Results We obtained 15,701 expressed genes in 30 muscle samples across five regions from carcass meat. We identified a total of 80 region-specific genes (RSGs), ranging from three (identified in the rump cut) to thirty (identified in the longissimus lumborum cut), and detected 25 transcription factors (TFs) for RSGs. Using a co-expression network analysis, we detected seven region-specific modules, including three positively correlated modules and four negatively correlated modules. We finally obtained 91 candidate genes related to meat quality, and the functional enrichment analyses showed that these genes were mainly involved in muscle fiber structure (e.g., TNNI1, TNNT1), fatty acids (e.g., SCD, LPL), amino acids (ALDH2, IVD, ACADS), ion channel binding (PHPT1, SNTA1, SUMO1, CNBP), protein processing (e.g., CDC37, GAPDH, NRBP1), as well as energy production and conversion (e.g., ATP8, COX8B, NDUFB6). Moreover, four candidate genes (ALDH2, CANX, IVD, PHPT1) were validated using RT-qPCR analyses which further supported our RNA-seq results. Conclusions Our results provide valuable insights into understanding the transcriptome regulation of meat quality in different beef cuts, and these findings may further help to improve the selection for health-beneficial meat in beef cattle.

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Genome-wide annotation of protein-coding genes in pig

Cited by 19 publications

References 86 publications

Endothelial cell heterogeneity and microglia regulons revealed by a pig cell landscape at single-cell level

Endothelial cell heterogeneity and microglia regulons revealed by a pig cell landscape at single-cell level

A Gene Expression Atlas of Lohmann White Chickens

Comparative transcriptomic analysis reveals region-specific expression patterns in different beef cuts

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