Literature DB >> 11882647

Transcript abundance in yeast varies over six orders of magnitude.

Michael J Holland1.   

Abstract

In the current era of functional genomics, it is remarkable that the intracellular range of transcript abundance is largely unknown. For the yeast Saccharomyces cerevisiae, hybridization-based complexity analysis and SAGE analysis showed that the majority of yeast mRNAs are present at one or fewer copies per cell; however, neither method provides an accurate estimate of the full range of low abundance transcripts. Here we examine the range of intracellular transcript abundance in yeast using kinetically monitored, reverse transcriptase-initiated PCR (kRT-PCR). Steady-state transcript levels encoded by all 65 genes on the left arm of chromosome III and 185 transcription factor genes are quantitated. Abundant transcripts encoded by glycolytic genes, previously quantitated by kRT-PCR, are present at a few hundred copies per cell whereas genes encoding physiologically important transcription factors are expressed at levels as low as one-thousandth transcript per cell. Of the genes assessed, only the silent mating type loci, HML and HMR, are transcriptionally silent. The results show that transcript abundance in yeast varies over six orders of magnitude. Finally, kRT-PCR, cDNA microarray, and high density oligonucleotide array assays are compared for their ability to detect and quantitate the complete yeast transcriptome.

Entities:  

Mesh:

Substances:

Year:  2002        PMID: 11882647     DOI: 10.1074/jbc.C200101200

Source DB:  PubMed          Journal:  J Biol Chem        ISSN: 0021-9258            Impact factor:   5.157


  56 in total

1.  RiboSys, a high-resolution, quantitative approach to measure the in vivo kinetics of pre-mRNA splicing and 3'-end processing in Saccharomyces cerevisiae.

Authors:  Ross D Alexander; J David Barrass; Beatriz Dichtl; Martin Kos; Tomasz Obtulowicz; Marie-Cecile Robert; Michal Koper; Iwona Karkusiewicz; Luisa Mariconti; David Tollervey; Bernhard Dichtl; Joanna Kufel; Edouard Bertrand; Jean D Beggs
Journal:  RNA       Date:  2010-10-25       Impact factor: 4.942

2.  Construction and validation of the Rhodobacter sphaeroides 2.4.1 DNA microarray: transcriptome flexibility at diverse growth modes.

Authors:  Christopher T Pappas; Jakub Sram; Oleg V Moskvin; Pavel S Ivanov; R Christopher Mackenzie; Madhusudan Choudhary; Miriam L Land; Frank W Larimer; Samuel Kaplan; Mark Gomelsky
Journal:  J Bacteriol       Date:  2004-07       Impact factor: 3.490

3.  Thousands of corresponding human and mouse genomic regions unalignable in primary sequence contain common RNA structure.

Authors:  Elfar Torarinsson; Milena Sawera; Jakob H Havgaard; Merete Fredholm; Jan Gorodkin
Journal:  Genome Res       Date:  2006-06-02       Impact factor: 9.043

4.  Mutations in the nucleosome core enhance transcriptional silencing.

Authors:  Eugenia Y Xu; Xin Bi; Michael J Holland; Daniel E Gottschling; James R Broach
Journal:  Mol Cell Biol       Date:  2005-03       Impact factor: 4.272

5.  Detecting novel low-abundant transcripts in Drosophila.

Authors:  Sanggyu Lee; Jingyue Bao; Guolin Zhou; Joshua Shapiro; Jinhua Xu; Run Zhang Shi; Xuemei Lu; Terry Clark; Deborah Johnson; Yeong C Kim; Claudia Wing; Charles Tseng; Min Sun; Wei Lin; Jun Wang; Huanming Yang; Jian Wang; Wei Du; Chung-I Wu; Xiuqing Zhang; San Ming Wang
Journal:  RNA       Date:  2005-06       Impact factor: 4.942

Review 6.  Reliability and reproducibility issues in DNA microarray measurements.

Authors:  Sorin Draghici; Purvesh Khatri; Aron C Eklund; Zoltan Szallasi
Journal:  Trends Genet       Date:  2005-12-27       Impact factor: 11.639

7.  RNA expression profiling at the single molecule level.

Authors:  Jan Hesse; Jaroslaw Jacak; Maria Kasper; Gerhard Regl; Thomas Eichberger; Martina Winklmayr; Fritz Aberger; Max Sonnleitner; Robert Schlapak; Stefan Howorka; Leila Muresan; Anna-Maria Frischauf; Gerhard J Schütz
Journal:  Genome Res       Date:  2006-06-29       Impact factor: 9.043

8.  Analysis of microarray experiments of gene expression profiling.

Authors:  Adi L Tarca; Roberto Romero; Sorin Draghici
Journal:  Am J Obstet Gynecol       Date:  2006-08       Impact factor: 8.661

9.  Pan-genome isolation of low abundance transcripts using SAGE tag.

Authors:  Yeong Cheol Kim; Yong-Chul Jung; Zhenyu Xuan; Hui Dong; Michael Q Zhang; San Ming Wang
Journal:  FEBS Lett       Date:  2006-11-14       Impact factor: 4.124

10.  Transcriptome analysis of the Rhodobacter sphaeroides PpsR regulon: PpsR as a master regulator of photosystem development.

Authors:  Oleg V Moskvin; Larissa Gomelsky; Mark Gomelsky
Journal:  J Bacteriol       Date:  2005-03       Impact factor: 3.490

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.