Genome-wide temporal gene expression reveals a post-reproductive shift in the nematode C. briggsae
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ABSTRACT:
PROVIDER: PRJNA1205553 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR31870158_1.fastq.gz | Fastqsanger.gz | |||
| SRR31870158_2.fastq.gz | Fastqsanger.gz | |||
| SRR31870159_1.fastq.gz | Fastqsanger.gz | |||
| SRR31870159_2.fastq.gz | Fastqsanger.gz | |||
| SRR31870160_1.fastq.gz | Fastqsanger.gz |
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Project description:C. briggsae offers a robust system for comparative investigations of genetic pathways that affect physiological processes. One of these, namely reproduction, directly impacts longevity due to its significant energetic demands. Long-lived mutants often exhibit reproductive impairments, and studies in C. elegans have demonstrated that removal of the germline can promote longevity, underscoring the link between reproduction and aging. Our study focuses on identifying gene expression changes during reproductive and post-reproductive phases in C. briggsae. We conducted whole-genome transcriptome profiling at various adult stages and found that the majority of differentially expressed (DE) genes were downregulated during the reproductive period. Interestingly, this trend reversed post-reproduction, with three-quarters of the genes upregulated—a phenomenon we termed the 'post-reproductive shift'. A similar analysis in C. elegans also showed a downregulation bias during the reproductive period, but the post-reproductive shift was absent. In C. briggsae, DE genes were enriched in processes related to the matrisome, muscle development and function during the reproductive period. Post-reproductive downregulated genes were enriched in DNA damage repair, stress response, and immune response. Additionally, terms related to fatty acid metabolism, catabolism, and transcriptional regulation exhibited complex patterns. Experimental manipulations of the reproductive status of animals predictably altered gene expression, providing in vivo support for the post-reproductive shift. Overall, our study reveals novel gene expression patterns during reproductive and post-reproductive changes in C. briggsae. The data provide a valuable resource for cross-sectional comparative studies in nematodes and other animal models to understand evolution of genetic pathways affecting reproduction and aging.
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Project description:Yeast (Saccharomyces cerevisea) has served as a key model system in biology and as a benchmark for “omics” technology. Although near-complete proteomes of log phase yeast have been measured, protein abundance in yeast is dynamic, particularly during the transition from log to stationary phase. Defining the dynamics of proteomic changes during this transition, termed the diauxic shift, is important to understand the basic biology of proliferative versus quiescent cells. Here, we perform temporal quantitative proteomics to fully capture protein induction and repression during the diauxic shift. Accurate and sensitive quantitation at a high temporal resolution and depth of proteome coverage was achieved using TMT10 reagents and LC-MS3 analysis on an Orbitrap Fusion tribrid mass spectrometer deploying synchronous precursor selection (SPS). We devised a simple template matching strategy to reveal temporal patterns of protein induction and repression. Within these groups are functionally distinct groups of proteins such as those of glyoxylate metabolism, as well as many proteins of unknown function not previously associated with the diauxic shift (e.g. YNR034W-A and FMP16). We also perform a dual time-course to determine Hap2-dependent proteins during the diauxic shift. These data serve as an important basic model for fermentative versus respiratory growth of yeast and other eukaryotes and are a benchmark for temporal quantitative proteomics.st (Saccharomyces cerevisea) has served as a key model system in biology and as a benchmark for “omics” technology. Although near-complete proteomes of log phase yeast have been measured, protein abundance in yeast is dynamic, particularly during the transition from log to stationary phase. Defining the dynamics of proteomic changes during this transition, termed the diauxic shift, is important to understand the basic biology of proliferative versus quiescent cells. Here, we perform temporal quantitative proteomics to fully capture protein induction and repression during the diauxic shift. Accurate and sensitive quantitation at a high temporal resolution and depth of proteome coverage was achieved using TMT10 reagents and LC-MS3 analysis on an Orbitrap Fusion tribrid mass spectrometer deploying synchronous precursor selection (SPS). We devised a simple template matching strategy to reveal temporal patterns of protein induction and repression. Within these groups are functionally distinct groups of proteins such as those of glyoxylate metabolism, as well as many proteins of unknown function not previously associated with the diauxic shift (e.g. YNR034W-A and FMP16). We also perform a dual time-course to determine Hap2-dependent proteins during the diauxic shift. These data serve as an important basic model for fermentative versus respiratory growth of yeast and other eukaryotes and are a benchmark for temporal quantitative proteomics.
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Project description:Yeast (Saccharomyces cerevisea) has served as a key model system in biology and as a benchmark for “omics” technology. Although near-complete proteomes of log phase yeast have been measured, protein abundance in yeast is dynamic, particularly during the transition from log to stationary phase. Defining the dynamics of proteomic changes during this transition, termed the diauxic shift, is important to understand the basic biology of proliferative versus quiescent cells. Here, we perform temporal quantitative proteomics to fully capture protein induction and repression during the diauxic shift. Accurate and sensitive quantitation at a high temporal resolution and depth of proteome coverage was achieved using TMT10 reagents and LC-MS3 analysis on an Orbitrap Fusion tribrid mass spectrometer deploying synchronous precursor selection (SPS). We devised a simple template matching strategy to reveal temporal patterns of protein induction and repression. Within these groups are functionally distinct groups of proteins such as those of glyoxylate metabolism, as well as many proteins of unknown function not previously associated with the diauxic shift (e.g. YNR034W-A and FMP16). We also perform a dual time-course to determine Hap2-dependent proteins during the diauxic shift. These data serve as an important basic model for fermentative versus respiratory growth of yeast and other eukaryotes and are a benchmark for temporal quantitative proteomics.st (Saccharomyces cerevisea) has served as a key model system in biology and as a benchmark for “omics” technology. Although near-complete proteomes of log phase yeast have been measured, protein abundance in yeast is dynamic, particularly during the transition from log to stationary phase. Defining the dynamics of proteomic changes during this transition, termed the diauxic shift, is important to understand the basic biology of proliferative versus quiescent cells. Here, we perform temporal quantitative proteomics to fully capture protein induction and repression during the diauxic shift. Accurate and sensitive quantitation at a high temporal resolution and depth of proteome coverage was achieved using TMT10 reagents and LC-MS3 analysis on an Orbitrap Fusion tribrid mass spectrometer deploying synchronous precursor selection (SPS). We devised a simple template matching strategy to reveal temporal patterns of protein induction and repression. Within these groups are functionally distinct groups of proteins such as those of glyoxylate metabolism, as well as many proteins of unknown function not previously associated with the diauxic shift (e.g. YNR034W-A and FMP16). We also perform a dual time-course to determine Hap2-dependent proteins during the diauxic shift. These data serve as an important basic model for fermentative versus respiratory growth of yeast and other eukaryotes and are a benchmark for temporal quantitative proteomics.
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