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Transcription initiation is finely regulated to ensure proper expression and function of genes. The regulated transcription initiation in response to various environmental stimuli in a classic model organism Saccharomyces cerevisiae has not been systematically investigated. In this study, we generated quantitative maps of transcription start sites (TSSs) at a single-nucleotide resolution for S. cerevisiae grown in nine different conditions using no-amplification nontagging Cap analysis of gene expression (nAnT-iCAGE) sequencing. We mapped ∼1 million well-supported TSSs, suggesting highly pervasive transcription initiation in the compact genome of the budding yeast. The comprehensive TSS maps allowed us to identify core promoters for ∼96% verified protein-coding genes. We corrected misannotation of translation start codon for 122 genes and suggested an alternative start codon for 57 genes. We found that 56% of yeast genes are controlled by multiple core promoters, and alternative core promoter usage by a gene is widespread in response to changing environments. Most core promoter shifts are coupled with altered gene expression, indicating that alternative core promoter usage might play an important role in controlling gene transcriptional activities. Based on their activities in responding to environmental cues, we divided core promoters into constitutive class (55%) and inducible class (45%). The two classes of core promoters display distinctive patterns in transcriptional abundance, chromatin structure, promoter shape, and sequence context. In summary, our study improved the annotation of the yeast genome and demonstrated a much more pervasive and dynamic nature of transcription initiation in yeast than previously recognized.
Pubmed ID: 31076411 RIS Download
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Web server that summarizes lists of Gene Ontology terms by removing redundant terms and visualizing the remaining ones in scatterplots, interactive graphs, treemaps, or tag clouds. Platform: Online tool
View all literature mentionsA powerful toolset for genome arithmetic allowing one to address common genomics tasks such as finding feature overlaps and computing coverage. Bedtools allows one to intersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g., intersect two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line.
View all literature mentionsExpression profiling and promoter identification software tool for transcriptional network analysis and transcriptome characterization. DeepCAGE, the combination of next-generation sequencing with next generation expression profiling provides unsurpassed solutions for expression profiling and genome annotation. CAGE will be the experimental approach at need to link gene expression and control regions in the genome. With the availability of next-generation sequencing methods, DNAFORM now offers DeepCAGE services. DeepCAGE libraries are prepared for direct analysis by an Illumina/Solexa Sequencer. One sequencing run using one channel on an Illumina/Solexa Sequencer can yield in over 4,000,000 reads per sample. CAGE is based on our full-length cDNA library technology, where an adaptor is ligated to the 5''''-end of full-length cDNAs, which introduces a recognition site for a Class IIs restriction endonuclease adjacent to the 5''''-end of the cDNA. The Class IIs restriction endonuclease, here MmeI, allows for the cloning of short tags as derived from the 5''''-end of transcripts into concatemers for high-throughput sequencing. CAGE tags are further characterized by mapping to genomic sequences, which enables the identification of transcriptional start sites. As such CAGE can contribute to projects in Gene Discovery, Gene Expression, and Promoter Identification. After the genome sequencing projects have provided us with the genetic blueprints for many organisms, new questions have to be answered on how to correlate the observed genotypes with related phenotypes, and how to understand the regulation of genetic information in time and space. The dynamics of living systems and the functional behavior of cells in multicellular organisms has thus become the subject of the emerging field of system biology. Integration of experimental approaches and computer aided theories on a system level will be the fundamental principle to drive systems biology in order to understand the principles behind complex regulatory networks, which will be an ambitious goal requiring new approaches in life sciences. For ordering and additional information, please contact us under contact_at_dnaform.jp
View all literature mentionsSoftware tools for Motif Discovery and next-gen sequencing analysis. Used for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets. Collection of command line programs for unix style operating systems written in Perl and C++.
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