@article {318, title = {A comparative study of ripening among berries of the grape cluster reveals an altered transcriptional programme and enhanced ripening rate in delayed berries.}, journal = {J Exp Bot}, volume = {65}, year = {2014}, month = {2014 Nov}, pages = {5889-902}, abstract = {

Transcriptional studies in relation to fruit ripening generally aim to identify the transcriptional states associated with physiological ripening stages and the transcriptional changes between stages within the ripening programme. In non-climacteric fruits such as grape, all ripening-related genes involved in this programme have not been identified, mainly due to the lack of mutants for comparative transcriptomic studies. A feature in grape cluster ripening (Vitis vinifera cv. Pinot noir), where all berries do not initiate the ripening at the same time, was exploited to study their shifted ripening programmes in parallel. Berries that showed marked ripening state differences in a v{\'e}raison-stage cluster (ripening onset) ultimately reached similar ripeness states toward maturity, indicating the flexibility of the ripening programme. The expression variance between these v{\'e}raison-stage berry classes, where 11\% of the genes were found to be differentially expressed, was reduced significantly toward maturity, resulting in the synchronization of their transcriptional states. Defined quantitative expression changes (transcriptional distances) not only existed between the v{\'e}raison transitional stages, but also between the v{\'e}raison to maturity stages, regardless of the berry class. It was observed that lagging berries complete their transcriptional programme in a shorter time through altered gene expressions and ripening-related hormone dynamics, and enhance the rate of physiological ripening progression. Finally, the reduction in expression variance of genes can identify new genes directly associated with ripening and also assess the relevance of gene activity to the phase of the ripening programme.

}, keywords = {Fruit, Gene Expression Profiling, Gene Expression Regulation, Plant, Oligonucleotide Array Sequence Analysis, Plant Growth Regulators, Time Factors, Transcription, Genetic, Vitis}, issn = {1460-2431}, doi = {10.1093/jxb/eru329}, author = {Gouthu, Satyanarayana and O{\textquoteright}Neil, Shawn T and Di, Yanming and Ansarolia, Mitra and Megraw, Molly and Deluc, Laurent G} } @article {326, title = {A transcription factor affinity-based code for mammalian transcription initiation.}, journal = {Genome Res}, volume = {19}, year = {2009}, month = {2009 Apr}, pages = {644-56}, abstract = {

The recent arrival of large-scale cap analysis of gene expression (CAGE) data sets in mammals provides a wealth of quantitative information on coding and noncoding RNA polymerase II transcription start sites (TSS). Genome-wide CAGE studies reveal that a large fraction of TSS exhibit peaks where the vast majority of associated tags map to a particular location ( approximately 45\%), whereas other active regions contain a broader distribution of initiation events. The presence of a strong single peak suggests that transcription at these locations may be mediated by position-specific sequence features. We therefore propose a new model for single-peaked TSS based solely on known transcription factors (TFs) and their respective regions of positional enrichment. This probabilistic model leads to near-perfect classification results in cross-validation (auROC = 0.98), and performance in genomic scans demonstrates that TSS prediction with both high accuracy and spatial resolution is achievable for a specific but large subgroup of mammalian promoters. The interpretable model structure suggests a DNA code in which canonical sequence features such as TATA-box, Initiator, and GC content do play a significant role, but many additional TFs show distinct spatial biases with respect to TSS location and are important contributors to the accurate prediction of single-peak transcription initiation sites. The model structure also reveals that CAGE tag clusters distal from annotated gene starts have distinct characteristics compared to those close to gene 5\&$\#$39;-ends. Using this high-resolution single-peak model, we predict TSS for approximately 70\% of mammalian microRNAs based on currently available data.

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}, keywords = {Base Composition, Databases, Genetic, DNA, Gene Expression Regulation, Genome, Human, Humans, Promoter Regions, Genetic, RNA Polymerase II, TATA Box, Transcription Factors, Transcription Initiation Site, Transcription, Genetic}, issn = {1088-9051}, doi = {10.1101/gr.085449.108}, author = {Megraw, Molly and Pereira, Fernando and Jensen, Shane T and Ohler, Uwe and Hatzigeorgiou, Artemis G} }