Identifying the Caenorhabditis elegans vulval transcriptome.
Qi ZhangHeather HrachMarco MangoneDavid J ReinerPublished in: G3 (Bethesda, Md.) (2022)
Development of the Caenorhabditis elegans vulva is a classic model of organogenesis. This system, which starts with 6 equipotent cells, encompasses diverse types of developmental event, including developmental competence, multiple signaling events to control precise and faithful patterning of three cell fates, execution and proliferation of specific cell lineages, and a series of sophisticated morphogenetic events. Early events have been subjected to extensive mutational and genetic investigations and later events to cell biological analyses. We infer the existence of dramatically changing profiles of gene expression that accompanies the observed changes in development. Yet, except from serendipitous discovery of several transcription factors expressed in dynamic patterns in vulval lineages, our knowledge of the transcriptomic landscape during vulval development is minimal. This study describes the composition of a vulva-specific transcriptome. We used tissue-specific harvesting of mRNAs via immunoprecipitation of epitope-tagged poly(A) binding protein, PAB-1, heterologously expressed by a promoter known to express GFP in vulval cells throughout their development. The identified transcriptome was small but tightly interconnected. From this data set, we identified several genes with identified functions in development of the vulva and validated more with promoter-GFP reporters of expression. For one target, lag-1, promoter-GFP expression was limited but a fluorescent tag of the endogenous protein revealed extensive expression. Thus, we have identified a transcriptome of C. elegans vulval lineages as a launching pad for exploration of functions of these genes in organogenesis.
Keyphrases
- single cell
- gene expression
- rna seq
- genome wide
- binding protein
- dna methylation
- poor prognosis
- transcription factor
- induced apoptosis
- cell therapy
- high throughput
- healthcare
- stem cells
- small molecule
- signaling pathway
- mesenchymal stem cells
- cell cycle arrest
- machine learning
- dna binding
- bone marrow
- genome wide identification
- high throughput sequencing