The conserved histone deacetylase Rpd3 and its DNA binding subunit Ume6 control dynamic transcript architecture during mitotic growth and meiotic development.

It was recently reported that the sizes of many mRNAs change when budding yeast cells exit mitosis and enter the meiotic differentiation pathway. These differences were attributed to length variations of their untranslated regions. The function of UTRs in protein translation is well established. However, the mechanism controlling the expression of distinct transcript isoforms during mitotic growth and meiotic development is unknown. In this study, we order developmentally regulated transcript isoforms according to their expression at specific stages during meiosis and gametogenesis, as compared to vegetative growth and starvation. We employ regulatory motif prediction, in vivo protein-DNA binding assays, genetic analyses and monitoring of epigenetic amino acid modification patterns to identify a novel role for Rpd3 and Ume6, two components of a histone deacetylase complex already known to repress early meiosis-specific genes in dividing cells, in mitotic repression of meiosis-specific transcript isoforms. Our findings classify developmental stage-specific early, middle and late meiotic transcript isoforms, and they point to a novel HDAC-dependent control mechanism for flexible transcript architecture during cell growth and differentiation. Since Rpd3 is highly conserved and ubiquitously expressed in many tissues, our results are likely relevant for development and disease in higher eukaryotes.

Genome-wide profiling of human cap-independent translation-enhancing elements.

We report an in vitro selection strategy to identify RNA sequences that mediate cap-independent initiation of translation. This method entails mRNA display of trillions of genomic fragments, selection for initiation of translation and high-throughput deep sequencing. We identified >12,000 translation-enhancing elements (TEEs) in the human genome, generated a high-resolution map of human TEE-bearing regions (TBRs), and validated the function of a subset of sequences in vitro and in cultured cells.

Extensive transcript diversity and novel upstream open reading frame regulation in yeast.

To understand the diversity of transcripts in yeast (Saccharomyces cerevisiae) we analyzed the transcriptional landscapes for cells grown under 18 different environmental conditions. Each sample was analyzed using RNA-sequencing, and a total of 670,446,084 uniquely mapped reads and 377,263 poly-adenylated end tags were produced. Consistent with previous studies, we find that the majority of yeast genes are expressed under one or more different conditions. By directly comparing the 5' and 3' ends of the transcribed regions, we find extensive differences in transcript ends across many conditions, especially those of stationary phase, growth in grape juice, and salt stimulation, suggesting differential choice of transcription start and stop sites is pervasive in yeast. Relative to the exponential growth condition (i.e., YPAD), transcripts differing at the 5' ends and 3' ends are predicted to differ in their annotated start codon in 21 genes and their annotated stop codon in 63 genes. Many (431) upstream open reading frames (uORFs) are found in alternate 5' ends and are significantly enriched in transcripts produced during the salt response. Mutational analysis of five genes with uORFs revealed that two sets of uORFs increase the expression of a reporter construct, indicating a role in activation which had not been reported previously, whereas two other uORFs decreased expression. In addition, RNA binding protein motifs are statistically enriched for alternate ends under many conditions. Overall, these results demonstrate enormous diversity of transcript ends, and that this heterogeneity is regulated under different environmental conditions. Moreover, transcript end diversity has important biological implications for the regulation of gene expression. In addition, our data also serve as a valuable resource for the scientific community.

RNA sequencing.

This chapter describes the RNA sequencing (RNA-Seq) protocol, whereby RNA from yeast cells is prepared for sequencing on an Illumina Genome Analyzer. The protocol can easily be altered to use RNA from a different organism. This chapter covers RNA extraction, cDNA synthesis, cDNA fragmentation, and Illumina cDNA library generation and contains some brief remarks on bioinformatic analysis.

RNA-Seq: a method for comprehensive transcriptome analysis.

A recently developed technique called RNA Sequencing (RNA-Seq) uses massively parallel sequencing to allow transcriptome analyses of genomes at a far higher resolution than is available with Sanger sequencing- and microarray-based methods. In the RNA-Seq method, complementary DNAs (cDNAs) generated from the RNA of interest are directly sequenced using next-generation sequencing technologies. The reads obtained from this can then be aligned to a reference genome in order to construct a whole-genome transcriptome map. RNA-Seq has been used successfully to precisely quantify transcript levels, confirm or revise previously annotated 5' and 3' ends of genes, and map exon/intron boundaries. This unit describes protocols for performing RNA-Seq using the Illumina sequencing platform.

The transcriptional landscape of the yeast genome defined by RNA sequencing.

The identification of untranslated regions, introns, and coding regions within an organism remains challenging. We developed a quantitative sequencing-based method called RNA-Seq for mapping transcribed regions, in which complementary DNA fragments are subjected to high-throughput sequencing and mapped to the genome. We applied RNA-Seq to generate a high-resolution transcriptome map of the yeast genome and demonstrated that most (74.5%) of the nonrepetitive sequence of the yeast genome is transcribed. We confirmed many known and predicted introns and demonstrated that others are not actively used. Alternative initiation codons and upstream open reading frames also were identified for many yeast genes. We also found unexpected 3'-end heterogeneity and the presence of many overlapping genes. These results indicate that the yeast transcriptome is more complex than previously appreciated.