Literature DB >> 26711261

The Overlooked Fact: Fundamental Need for Spike-In Control for Virtually All Genome-Wide Analyses.

Kaifu Chen1, Zheng Hu2, Zheng Xia3, Dongyu Zhao1, Wei Li3, Jessica K Tyler4.   

Abstract

Genome-wide analyses of changes in gene expression, transcription factor occupancy on DNA, histone modification patterns on chromatin, genomic copy number variation, and nucleosome positioning have become popular in many modern laboratories, yielding a wealth of information during health and disease states. However, most of these studies have overlooked an inherent normalization problem that must be corrected with spike-in controls. Here we describe the reason why spike-in controls are so important and explain how to appropriately design and use spike-in controls for normalization. We also suggest ways to retrospectively renormalize data sets that were wrongly interpreted due to omission of spike-in controls.
Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Mesh:

Year:  2015        PMID: 26711261      PMCID: PMC4760223          DOI: 10.1128/MCB.00970-14

Source DB:  PubMed          Journal:  Mol Cell Biol        ISSN: 0270-7306            Impact factor:   4.272


  10 in total

1.  Chromosomal landscape of nucleosome-dependent gene expression and silencing in yeast.

Authors:  J J Wyrick; F C Holstege; E G Jennings; H C Causton; D Shore; M Grunstein; E S Lander; R A Young
Journal:  Nature       Date:  1999-11-25       Impact factor: 49.962

2.  The transcriptome of prematurely aging yeast cells is similar to that of telomerase-deficient cells.

Authors:  Isabelle Lesur; Judith L Campbell
Journal:  Mol Biol Cell       Date:  2004-01-12       Impact factor: 4.138

3.  Elevated histone expression promotes life span extension.

Authors:  Jason Feser; David Truong; Chandrima Das; Joshua J Carson; Jeffrey Kieft; Troy Harkness; Jessica K Tyler
Journal:  Mol Cell       Date:  2010-09-10       Impact factor: 17.970

4.  Normalization of RNA-seq data using factor analysis of control genes or samples.

Authors:  Davide Risso; John Ngai; Terence P Speed; Sandrine Dudoit
Journal:  Nat Biotechnol       Date:  2014-08-24       Impact factor: 54.908

5.  Synthetic spike-in standards for RNA-seq experiments.

Authors:  Lichun Jiang; Felix Schlesinger; Carrie A Davis; Yu Zhang; Renhua Li; Marc Salit; Thomas R Gingeras; Brian Oliver
Journal:  Genome Res       Date:  2011-08-04       Impact factor: 9.043

6.  mRNA enrichment protocols determine the quantification characteristics of external RNA spike-in controls in RNA-Seq studies.

Authors:  Tao Qing; Ying Yu; Tingting Du; Leming Shi
Journal:  Sci China Life Sci       Date:  2013-02-08       Impact factor: 6.038

7.  Quantitative ChIP-Seq normalization reveals global modulation of the epigenome.

Authors:  David A Orlando; Mei Wei Chen; Victoria E Brown; Snehakumari Solanki; Yoon J Choi; Eric R Olson; Christian C Fritz; James E Bradner; Matthew G Guenther
Journal:  Cell Rep       Date:  2014-10-30       Impact factor: 9.423

8.  Selective inhibition of tumor oncogenes by disruption of super-enhancers.

Authors:  Jakob Lovén; Heather A Hoke; Charles Y Lin; Ashley Lau; David A Orlando; Christopher R Vakoc; James E Bradner; Tong Ihn Lee; Richard A Young
Journal:  Cell       Date:  2013-04-11       Impact factor: 41.582

Review 9.  Revisiting global gene expression analysis.

Authors:  Jakob Lovén; David A Orlando; Alla A Sigova; Charles Y Lin; Peter B Rahl; Christopher B Burge; David L Levens; Tong Ihn Lee; Richard A Young
Journal:  Cell       Date:  2012-10-26       Impact factor: 41.582

10.  Nucleosome loss leads to global transcriptional up-regulation and genomic instability during yeast aging.

Authors:  Zheng Hu; Kaifu Chen; Zheng Xia; Myrriah Chavez; Sangita Pal; Ja-Hwan Seol; Chin-Chuan Chen; Wei Li; Jessica K Tyler
Journal:  Genes Dev       Date:  2014-02-15       Impact factor: 11.361

  10 in total
  58 in total

Review 1.  Use of the nuclear walk-on methodology to determine sites of RNA polymerase II initiation and pausing and quantify nascent RNAs in cells.

Authors:  Christopher B Ball; Kyle A Nilson; David H Price
Journal:  Methods       Date:  2019-02-08       Impact factor: 3.608

2.  Analysis of Myc Chromatin Binding by Calibrated ChIP-Seq Approach.

Authors:  Donald P Cameron; Vladislav Kuzin; Laura Baranello
Journal:  Methods Mol Biol       Date:  2021

3.  Selecting between-sample RNA-Seq normalization methods from the perspective of their assumptions.

Authors:  Ciaran Evans; Johanna Hardin; Daniel M Stoebel
Journal:  Brief Bioinform       Date:  2018-09-28       Impact factor: 11.622

4.  Transcription Promotes the Interaction of the FAcilitates Chromatin Transactions (FACT) Complex with Nucleosomes in Saccharomyces cerevisiae.

Authors:  Benjamin J E Martin; Adam T Chruscicki; LeAnn J Howe
Journal:  Genetics       Date:  2018-09-20       Impact factor: 4.562

5.  Ssd1 and Gcn2 suppress global translation efficiency in replicatively aged yeast while their activation extends lifespan.

Authors:  Zheng Hu; Bo Xia; Spike Dl Postnikoff; Zih-Jie Shen; Alin S Tomoiaga; Troy A Harkness; Ja Hwan Seol; Wei Li; Kaifu Chen; Jessica K Tyler
Journal:  Elife       Date:  2018-08-17       Impact factor: 8.140

6.  Hyperosmotic stress alters the RNA polymerase II interactome and induces readthrough transcription despite widespread transcriptional repression.

Authors:  Nicolle A Rosa-Mercado; Joshua T Zimmer; Maria Apostolidi; Jesse Rinehart; Matthew D Simon; Joan A Steitz
Journal:  Mol Cell       Date:  2021-01-04       Impact factor: 17.970

7.  A new approach for quantifying epigenetic landscapes.

Authors:  Wolfgang Fischle
Journal:  J Biol Chem       Date:  2020-11-20       Impact factor: 5.157

8.  H2A Monoubiquitination Links Glucose Availability to Epigenetic Regulation of the Endoplasmic Reticulum Stress Response and Cancer Cell Death.

Authors:  Yilei Zhang; Jiejun Shi; Xiaoguang Liu; Zhenna Xiao; Guang Lei; Hyemin Lee; Pranavi Koppula; Weijie Cheng; Chao Mao; Li Zhuang; Li Ma; Wei Li; Boyi Gan
Journal:  Cancer Res       Date:  2020-04-09       Impact factor: 12.701

9.  Targeted in situ genome-wide profiling with high efficiency for low cell numbers.

Authors:  Peter J Skene; Jorja G Henikoff; Steven Henikoff
Journal:  Nat Protoc       Date:  2018-04-12       Impact factor: 13.491

10.  A field guide for the compositional analysis of any-omics data.

Authors:  Thomas P Quinn; Ionas Erb; Greg Gloor; Cedric Notredame; Mark F Richardson; Tamsyn M Crowley
Journal:  Gigascience       Date:  2019-09-01       Impact factor: 6.524

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