Transcriptome analysis of adult Caenorhabditis elegans cells reveals tissue-specific gene and isoform expression

• Published in: PLoS genetics Vol. 14; no. 8; p. e1007559
• Main Authors: Kaletsky, Rachel, Yao, Victoria, Williams, April, Runnels, Alexi M, Tadych, Alicja, Zhou, Shiyi, Troyanskaya, Olga G, Murphy, Coleen T
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 10.08.2018; Public Library of Science (PLoS)
• Subjects: Adults; Aging; Alternative Splicing; Animals; Behavior; Biology and Life Sciences; Caenorhabditis elegans; Caenorhabditis elegans - genetics; Caenorhabditis elegans - metabolism; Caenorhabditis elegans Proteins - genetics; Caenorhabditis elegans Proteins - metabolism; Cellular signal transduction; Collagen; Computer science; Cyclic AMP response element-binding protein; Forkhead protein; Forkhead Transcription Factors - genetics; Forkhead Transcription Factors - metabolism; Gene expression; Gene Expression Profiling; Gene Expression Regulation; Gene Library; Genetic aspects; Genomes; Genomics; Insulin; Insulin - metabolism; Insulin-like growth factor I; Insulin-Like Growth Factor I - metabolism; Isoforms; Learning algorithms; Medicine and Health Sciences; Metabolism; Methods; Models, Molecular; Molecular biology; Molecular modelling; Nematodes; Phenotype; Phenotypes; Protein Isoforms; Research and Analysis Methods; Sequence Analysis, RNA; Signal Transduction; Software; Transcription; Transcription factors; Transforming Growth Factor beta - genetics; Transforming Growth Factor beta - metabolism; Worms; New York; United States > US; New Jersey
• ISSN: 1553-7404; 1553-7390; 1553-7404
• DOI: 10.1371/journal.pgen.1007559

The biology and behavior of adults differ substantially from those of developing animals, and cell-specific information is critical for deciphering the biology of multicellular animals. Thus, adult tissue-specific transcriptomic data are critical for understanding molecular mechanisms that control their phenotypes. We used adult cell-specific isolation to identify the transcriptomes of C. elegans' four major tissues (or "tissue-ome"), identifying ubiquitously expressed and tissue-specific "enriched" genes. These data newly reveal the hypodermis' metabolic character, suggest potential worm-human tissue orthologies, and identify tissue-specific changes in the Insulin/IGF-1 signaling pathway. Tissue-specific alternative splicing analysis identified a large set of collagen isoforms. Finally, we developed a machine learning-based prediction tool for 76 sub-tissue cell types, which we used to predict cellular expression differences in IIS/FOXO signaling, stage-specific TGF-β activity, and basal vs. memory-induced CREB transcription. Together, these data provide a rich resource for understanding the biology governing multicellular adult animals.