Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease

Goede, Olivia M. de; Nachun, Daniel; Ferraro, Nicole M.; Gloudemans, Michael J.; Rao, Abhiram; Smail, Craig; Eulalio, Tiffany; Aguet, François; Ng, Bernard; Xu, Jishu; Barbeira, Alvaro N.; Castel, Stephane E.; Kim-Hellmuth, Sarah; Park, YoSon; Scott, Alexandra J.; Strober, Benjamin J.; Brown, Christopher D.; Wen, Xiaoquan; Hall, Ira M.; Battle, Alexis; Lappalainen, Tuuli; Im, Hae Kyung; Ardlie, Kristin; Mostafavi, Sara; Quertermous, Thomas; Kirkegaard, Karla; Montgomery, S

doi:10.1016/j.cell.2021.03.050

Cited by 122 publications

(65 citation statements)

References 110 publications

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“…Several stable markers of differentially expressed (DE) mRNAs involved in S. aureus infection, such as genes SETD2 , CYP1A1 and SSB1 , have been identified [ 8 ]. Long non-coding RNAs (lncRNAs) are the noncoding transcripts with length longer than 200 nucleotides, widely regulate mRNA expression at the transcription level, and influence the progress of complex diseases [ 9 , 10 ]. However, stable DE lncRNAs among different S. aureus strain infections are yet to be investigated.…”

Section: Introductionmentioning

confidence: 99%

Transcriptome sequencing analysis for the identification of stable lncRNAs associated with bovine Staphylococcus aureus mastitis

Tang

Dari

et al. 2021

J Animal Sci Biotechnol

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Background Staphylococcus aureus (S. aureus) mastitis is one of the most difficult diseases to treat in lactating dairy cows worldwide. S. aureus with different lineages leads to different host immune responses. Long non-coding RNAs (lncRNAs) are reported to be widely involved in the progress of inflammation. However, no research has identified stable lncRNAs among different S. aureus strain infections. In addition, folic acid (FA) can effectively reduce inflammation, and whether the inflammatory response caused by S. aureus can be reduced by FA remains to be explored. Methods lncRNA transcripts were identified from Holstein mammary gland tissues infected with different concentrations of S. aureus (in vivo) and mammary alveolar cells (Mac-T cells, in vitro) challenged with different S. aureus strains. Differentially expressed (DE) lncRNAs were evaluated, and stable DE lncRNAs were identified in vivo and in vitro. On the basis of the gene sequence conservation and function conservation across species, key lncRNAs with the function of potentially immune regulation were retained for further analysis. The function of FA on inflammation induced by S. aureus challenge was also investigated. Then, the association analysis between these keys lncRNA transcripts and hematological parameters (HPs) was carried out. Lastly, the knockdown and overexpression of the important lncRNA were performed to validate the gene function on the regulation of cell immune response. Results Linear regression analysis showed a significant correlation between the expression levels of lncRNA shared by mammary tissue and Mac-T cells (P < 0.001, R2 = 0.3517). lncRNAs PRANCR and TNK2–AS1 could be regarded as stable markers associated with bovine S. aureus mastitis. Several HPs could be influenced by SNPs around lncRNAs PRANCR and TNK2–AS1. The results of gene function validation showed PRANCR regulates the mRNA expression of SELPLG and ITGB2 within the S. aureus infection pathway and the Mac-T cells apoptosis. In addition, FA regulated the expression change of DE lncRNA involved in toxin metabolism and inflammation to fight against S. aureus infection. Conclusions The remarkable association between SNPs around these two lncRNAs and partial HP indicates the potentially important role of PRANCR and TNK2–AS1 in immune regulation. Stable DE lncRNAs PRANCR and TNK2–AS1 can be regarded as potential targets for the prevention of bovine S. aureus mastitis. FA supplementation can reduce the negative effect of S. aureus challenge by regulating the expression of lncRNAs.

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Section: Introductionmentioning

confidence: 99%

Transcriptome sequencing analysis for the identification of stable lncRNAs associated with bovine Staphylococcus aureus mastitis

Tang

Dari

et al. 2021

J Animal Sci Biotechnol

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“…Although previous studies have identified the hereditary nature of TGCT with an estimated 37-49% familial cases (23,24), the only moderate penetrance gene is GHEK2 whose pathogenic variants have been associated with the risk of TGCT (25). The testis expresses the largest number of genes of any mammalian organ (26), especially high numbers of genes predominantly expressed (27). In our study, it also had numerous DEmRNAs in TGCTs.…”

Section: Discussionmentioning

confidence: 47%

Identification of mRNA Prognostic Markers for TGCT by Integration of Co-Expression and CeRNA Network

et al. 2021

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Testicular germ cell tumor (TGCT) is the most common malignant tumor in young men and is associated with poor prognosis. We assessed the RNA expression profiles of 13 TGCT tissues and 4 adjacent normal tissues by transcriptome sequencing to identify novel prognostic biomarkers. We detected several differentially expressed mRNAs in TGCT that were functionally annotated by GO and KEGG enrichment analyses to tumorigenesis-related processes such as immunity and chemotherapeutic resistance. An mRNA-lncRNA-miRNA regulatory network was constructed using RNA-Seq data and public databases, and integrated with TCGA database to develop a prediction model for metastasis and recurrence. Finally, GRK4, PCYT2 and RGSL1 were identified as predictive markers of survival and therapeutic response. In conclusion, we found several potential predictors for TGCT prognosis and immunotherapeutic response by ceRNA network analysis.

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“…To zoom in from the bulk tissue level to a finer resolution of the biological pathways and cell types in which colocalized genes are active, we tested these genes for overlap with cell type-specific genes we inferred from the Human Cell Landscape [31] using pSI [32,33] and for membership in co-expression modules that we generated from GTEx using weighted gene co-expression network analysis [34,35] (Additional Data S5 & S6, see Methods). For example, the LPL (lipoprotein lipase) gene, whose eQTLs colocalize with fasting insulin, WHR, HDL, and TG exclusively in subcutaneous adipose tissue in GTEx, was identified as a cell type-specific gene for adipocytes, in contrast with other adipose-colocalized genes that were specific to mast cells (e.g.…”

Section: Tissue Specificity Dissects Different Components Of Diseasementioning

confidence: 99%

“…GTEx coexpression modules are described in a previous publication [35]. We treated the genes in each module as a gene set, and tested for functional enrichment using clusterprofiler [57] with candidate enrichments from consensusDB [58].…”

Section: Gtex Coexpression Modules and Cell Type Specificitymentioning

confidence: 99%

Integration of genetic colocalizations with physiological and pharmacological perturbations identifies cardiometabolic disease genes

Balliu²,

Nachun

et al. 2021

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BackgroundIdentification of causal genes for polygenic human diseases has been extremely challenging, and our understanding of how physiological and pharmacological stimuli modulate genetic risk at disease-associated loci is limited. Specifically, insulin resistance (IR), a common feature of cardiometabolic disease, including type 2 diabetes, obesity, and dyslipidemia, lacks well-powered GWAS, and therefore few associated loci and causal genes have been identified.ResultsHere, we perform and integrate LD-adjusted colocalization analyses across nine cardiometabolic traits combined with eQTLs and sQTLs from five metabolically relevant human tissues (subcutaneous and visceral adipose, skeletal muscle, liver, and pancreas). We identify 470 colocalized loci and prioritize 207 loci with a single colocalized gene. To elucidate upstream regulators and functional mechanisms for these genes, we integrate their transcriptional responses to 21 physiological and pharmacological cardiometabolic regulators in human adipocytes, hepatocytes, and skeletal muscle cells, and map their protein-protein interactions.ConclusionsOur use of transcriptional responses under metabolic perturbations to contextualize genetic associations from our state-of-the-art colocalization approach provides a list of likely causal genes and their upstream regulators in the context of IR-associated cardiometabolic risk.

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Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease

Cited by 122 publications

References 110 publications

Transcriptome sequencing analysis for the identification of stable lncRNAs associated with bovine Staphylococcus aureus mastitis

Transcriptome sequencing analysis for the identification of stable lncRNAs associated with bovine Staphylococcus aureus mastitis

Identification of mRNA Prognostic Markers for TGCT by Integration of Co-Expression and CeRNA Network

Integration of genetic colocalizations with physiological and pharmacological perturbations identifies cardiometabolic disease genes

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