An introduction to transcription and gene regulation

Visualizing the phage T4 activated transcription complex of DNA and E. coli RNA polymerase

The ability of RNA polymerase (RNAP) to select the right promoter sequence at the right time is fundamental to the control of gene expression in all organisms. However, there is only one crystallized structure of a complete activator/RNAP/DNA complex. In a process called σ appropriation, bacteriophage T4 activates a class of phage promoters using an activator (MotA) and a co-activator (AsiA), which function through interactions with the σ⁷⁰ subunit of RNAP. We have developed a holistic, structure-based model for σ appropriation using multiple experimentally determined 3D structures (Escherichia coli RNAP, the Thermus aquaticus RNAP/DNA complex, AsiA /σ⁷⁰ Region 4, the N-terminal domain of MotA [MotA^NTD], and the C-terminal domain of MotA [MotA^CTD]), molecular modeling, and extensive biochemical observations indicating the position of the proteins relative to each other and to the DNA. Our results visualize how AsiA/MotA redirects σ, and therefore RNAP activity, to T4 promoter DNA, and demonstrate at a molecular level how the tactful interaction of transcriptional factors with even small segments of RNAP can alter promoter specificity. Furthermore, our model provides a rational basis for understanding how a mutation within the β subunit of RNAP (G1249D), which is far removed from AsiA or MotA, impairs σ appropriation.

YeATS - a tool suite for analyzing RNA-seq derived transcriptome identifies a highly transcribed putative extensin in heartwood/sapwood transition zone in black walnut

The transcriptome provides a functional footprint of the genome by enumerating the molecular components of cells and tissues. The field of transcript discovery has been revolutionized through high-throughput mRNA sequencing (RNA-seq). Here, we present a methodology that replicates and improves existing methodologies, and implements a workflow for error estimation and correction followed by genome annotation and transcript abundance estimation for RNA-seq derived transcriptome sequences (YeATS - Yet Another Tool Suite for analyzing RNA-seq derived transcriptome). A unique feature of YeATS is the upfront determination of the errors in the sequencing or transcript assembly process by analyzing open reading frames of transcripts. YeATS identifies transcripts that have not been merged, result in broken open reading frames or contain long repeats as erroneous transcripts. We present the YeATS workflow using a representative sample of the transcriptome from the tissue at the heartwood/sapwood transition zone in black walnut. A novel feature of the transcriptome that emerged from our analysis was the identification of a highly abundant transcript that had no known homologous genes (GenBank accession: KT023102). The amino acid composition of the longest open reading frame of this gene classifies this as a putative extensin. Also, we corroborated the transcriptional abundance of proline-rich proteins, dehydrins, senescence-associated proteins, and the DNAJ family of chaperone proteins. Thus, YeATS presents a workflow for analyzing RNA-seq data with several innovative features that differentiate it from existing software.

YeATS - a tool suite for analyzing RNA-seq derived transcriptome identifies a highly transcribed putative extensin in heartwood/sapwood transition zone in black walnut

The transcriptome provides a functional footprint of the genome by enumerating the molecular components of cells and tissues. The field of transcript discovery has been revolutionized through high-throughput mRNA sequencing (RNA-seq). Here, we present a methodology that replicates and improves existing methodologies, and implements a workflow for error estimation and correction followed by genome annotation and transcript abundance estimation for RNA-seq derived transcriptome sequences (YeATS - Yet Another Tool Suite for analyzing RNA-seq derived transcriptome). A unique feature of YeATS is the upfront determination of the errors in the sequencing or transcript assembly process by analyzing open reading frames of transcripts. YeATS identifies transcripts that have not been merged, result in broken open reading frames or contain long repeats as erroneous transcripts. We present the YeATS workflow using a representative sample of the transcriptome from the tissue at the heartwood/sapwood transition zone in black walnut. A novel feature of the transcriptome that emerged from our analysis was the identification of a highly abundant transcript that had no known homologous genes (GenBank accession: KT023102). The amino acid composition of the longest open reading frame of this gene classifies this as a putative extensin. Also, we corroborated the transcriptional abundance of proline-rich proteins, dehydrins, senescence-associated proteins, and the DNAJ family of chaperone proteins. Thus, YeATS presents a workflow for analyzing RNA-seq data with several innovative features that differentiate it from existing software.