Unknown,Transcriptomics,Genomics,Proteomics

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Strand-specific transcriptomes of Saccharomyces cerevisiae and Saccharomyces paradoxus

ABSTRACT: Background: Recent studies have demonstrated that antisense transcription is pervasive in budding yeasts and is conserved between Saccharomyces cerevisiae and S. paradoxus. While studies have examined antisense transcripts of S. cerevisiae for inverse transcription in stationary phase and stress conditions, there is a lack of comprehensive analysis of the conditional specific evolutionary characteristics of antisense transcription between yeasts. Here we attempt to decipher the evolutionary relationship of antisense transcription of S. cerevisiae and S. paradoxus cultured in mid log, early stationary phase, and heat shock conditions. Results: Massively parallel sequencing of sequence strand-specific cDNA library was performed from RNA isolated from S. cerevisiae and S. paradoxus cells at mid log, stationary phase and heat shock conditions. We performed this analysis using a stringent set of sense ORF transcripts and non-coding antisense transcripts that were expressed in all the three conditions, as well as in both species. We found the divergence of the condition specific anti-sense transcription levels is higher than that in condition specific sense transcription levels, suggesting that antisense transcription played a potential role in adapting to different conditions. Furthermore, 43% of sense-antisense pairs demonstrated inverse transcription in either stationary phase or heat shock conditions relative to the mid log conditions. In addition, a large part of sense-antisense pairs (67%), which demonstrated inverse transcription, were highly conserved between the two species. Our results were also concordant with known functional analyses from previous studies and with the evidence from mechanistic experiments of role of individual genes. Conclusions: This study provides a comprehensive picture of the role of antisense transcription mediating sense transcription in different conditions across yeast species. We can conclude from our findings that antisense regulation could act like an on-off switch on sense regulation in different conditions. Transcriptomes of two yeast species under mid-log phase, early stationary phase, and after heat shock treatment were generated by Illumina HiSeq 2000 paired-end sequencing

ORGANISM(S): Saccharomyces cerevisiae

SUBMITTER: Daryi Wang

PROVIDER: E-GEOD-58319 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Background: Recent studies have demonstrated that antisense transcription is pervasive in budding yeasts and is conserved between Saccharomyces cerevisiae and S. paradoxus. While studies have examined antisense transcripts of S. cerevisiae for inverse transcription in stationary phase and stress conditions, there is a lack of comprehensive analysis of the conditional specific evolutionary characteristics of antisense transcription between yeasts. Here we attempt to decipher the evolutionary relationship of antisense transcription of S. cerevisiae and S. paradoxus cultured in mid log, early stationary phase, and heat shock conditions. Results: Massively parallel sequencing of sequence strand-specific cDNA library was performed from RNA isolated from S. cerevisiae and S. paradoxus cells at mid log, stationary phase and heat shock conditions. We performed this analysis using a stringent set of sense ORF transcripts and non-coding antisense transcripts that were expressed in all the three conditions, as well as in both species. We found the divergence of the condition specific anti-sense transcription levels is higher than that in condition specific sense transcription levels, suggesting that antisense transcription played a potential role in adapting to different conditions. Furthermore, 43% of sense-antisense pairs demonstrated inverse transcription in either stationary phase or heat shock conditions relative to the mid log conditions. In addition, a large part of sense-antisense pairs (67%), which demonstrated inverse transcription, were highly conserved between the two species. Our results were also concordant with known functional analyses from previous studies and with the evidence from mechanistic experiments of role of individual genes. Conclusions: This study provides a comprehensive picture of the role of antisense transcription mediating sense transcription in different conditions across yeast species. We can conclude from our findings that antisense regulation could act like an on-off switch on sense regulation in different conditions.

Project description:Over the past decade, genome-wide assays have underscored the broad sweep of circadian gene expression. A substantial fraction of the transcriptome undergoes oscillations in many organisms and tissues, which governs the many biochemical, physiological and behavioral functions under circadian control. Based predominantly on the transcription feedback loops important for core circadian timekeeping, it is commonly assumed that this widespread mRNA cycling reflects circadian transcriptional cycling. To address this issue, we directly measured dynamic changes in mouse liver transcription using Nascent-Seq. Many genes are rhythmically transcribed over the 24h day, which include precursors of several non-coding RNAs as well as the expected set of core clock genes. Surprisingly however, nascent RNA rhythms overlap poorly with mRNA abundance rhythms assayed by RNA-seq. This is because most mouse liver genes with rhythmic mRNA expression manifest poor transcriptional rhythms, indicating a prominent role of post-transcriptional regulation in setting mRNA cycling amplitude. To gain further insight into circadian transcriptional regulation, we also characterized the rhythmic transcription of liver genes targeted by the transcription factors CLOCK and BMAL1; they directly target other core clock genes and sit at the top of the molecular circadian clock hierarchy in mammals. CLK:BMAL1 rhythmically bind at the same discrete phase of the circadian cycle to all target genes, which not surprisingly have a much higher percentage of rhythmic transcription than the genome as a whole. However, there is a surprisingly heterogeneous set of cycling transcription phases of direct target genes, which even include core clock genes. This indicates a disconnect between rhythmic DNA binding and the peak of transcription, which is likely due to other transcription factors that collaborate with CLK:BMAL1. In summary, the application of Nascent-Seq to a mammalian tissue provides surprising insights into the rhythmic control of gene expression and should have broad applications beyond the analysis of circadian rhythms. Mouse liver nascent RNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina GAII (Nascent-Seq); Mouse liver mRNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina HiSeq2000 (RNA-Seq); CLK and BMAL1 DNA binding profile in the mouse liver at ZT8, sequenced along an Input sample using GAII (ChIP-Seq); Mouse liver strand-specific nascent RNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina HiSeq2000 (Strand-specific Nascent-Seq); Supplementary file RNASeq_Mouse_Liver_NormalizedGeneSignal.txt represents mRNA abundance (reads per base pair) for each sample.

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Strand-specific transcriptomes of Saccharomyces cerevisiae and Saccharomyces paradoxus

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