@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 {332, title = {microRNAs exhibit high frequency genomic alterations in human cancer.}, journal = {Proc Natl Acad Sci U S A}, volume = {103}, year = {2006}, month = {2006 Jun 13}, pages = {9136-41}, abstract = {

MicroRNAs (miRNAs) are endogenous noncoding RNAs, which negatively regulate gene expression. To determine genomewide miRNA DNA copy number abnormalities in cancer, 283 known human miRNA genes were analyzed by high-resolution array-based comparative genomic hybridization in 227 human ovarian cancer, breast cancer, and melanoma specimens. A high proportion of genomic loci containing miRNA genes exhibited DNA copy number alterations in ovarian cancer (37.1\%), breast cancer (72.8\%), and melanoma (85.9\%), where copy number alterations observed in \>15\% tumors were considered significant for each miRNA gene. We identified 41 miRNA genes with gene copy number changes that were shared among the three cancer types (26 with gains and 15 with losses) as well as miRNA genes with copy number changes that were unique to each tumor type. Importantly, we show that miRNA copy changes correlate with miRNA expression. Finally, we identified high frequency copy number abnormalities of Dicer1, Argonaute2, and other miRNA-associated genes in breast and ovarian cancer as well as melanoma. These findings support the notion that copy number alterations of miRNAs and their regulatory genes are highly prevalent in cancer and may account partly for the frequent miRNA gene deregulation reported in several tumor types.

}, keywords = {Breast Neoplasms, Female, Gene Dosage, Gene Expression Profiling, Humans, MicroRNAs, Neoplasms, Nucleic Acid Hybridization, Oligonucleotide Array Sequence Analysis, Ovarian Neoplasms, Statistics as Topic}, issn = {0027-8424}, doi = {10.1073/pnas.0508889103}, author = {Zhang, Lin and Huang, Jia and Yang, Nuo and Greshock, Joel and Megraw, Molly S and Giannakakis, Antonis and Liang, Shun and Naylor, Tara L and Barchetti, Andrea and Ward, Michelle R and Yao, George and Medina, Angelica and O{\textquoteright}brien-Jenkins, Ann and Katsaros, Dionyssios and Hatzigeorgiou, Artemis and Gimotty, Phyllis A and Weber, Barbara L and Coukos, George} }