Literature DB >> 30014809

Stage-specific differential DNA methylation data analysis during human erythropoiesis in chromosome 16.

Najyah A Garoot1, Byung Guk Kim1.   

Abstract

Previous studies have generated controversial findings regarding the correlation between DNA methylation in the human genome and gene expression. Some reports have indicated that promoter methylation is negatively correlated with gene expression levels; however, in some cases, a poor or positive correlation was reported. Most previous findings were based on general trends observed with whole-genome data analysis. Here, we present a novel chromosome-specific statistical analysis design of empirical Bayes differential tests for five phases of erythroid development. To better understand the common methylation patterns of differentially methylated regions (DMRs) during specific stages, we defined differential phases for each CpG locus, based on a maximum log2 fold change. Analyzing hypermethylated and hypomethylated CpG loci separately showed variations in methylation patterns during erythropoiesis in the gene body, promoter and enhancer regions. Hypomethylated DMRs showed stronger associations with erythroid-specific enhancers at the differentiation start phase and with exons in the intermediate phase. To investigate the hypomethylated DMRs further, transcription factor binding site-enrichment analysis was conducted. This analysis highlighted novel transcription factors during each differentiation stage that were not detected by previous differential methylation data analysis. In contrast, hypermethylated DMRs showed a consistent methylation pattern over the different genomic regions. Thus, a closer examination of DNA methylation patterns in a single chromosome during each developmental stage can contribute to verify the association nature between gene expression and DNA methylation.

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Year:  2018        PMID: 30014809      PMCID: PMC6865142          DOI: 10.1017/S0016672318000022

Source DB:  PubMed          Journal:  Genet Res (Camb)        ISSN: 0016-6723            Impact factor:   1.588


  21 in total

1.  Abnormal erythroid differentiation in neonatal bcl-6-deficient mice.

Authors:  Sadaki Asari; Akemi Sakamoto; Seiji Okada; Yusuke Ohkubo; Masafumi Arima; Masahiko Hatano; Yoshikazu Kuroda; Takeshi Tokuhisa
Journal:  Exp Hematol       Date:  2005-01       Impact factor: 3.084

2.  A bivalent chromatin structure marks key developmental genes in embryonic stem cells.

Authors:  Bradley E Bernstein; Tarjei S Mikkelsen; Xiaohui Xie; Michael Kamal; Dana J Huebert; James Cuff; Ben Fry; Alex Meissner; Marius Wernig; Kathrin Plath; Rudolf Jaenisch; Alexandre Wagschal; Robert Feil; Stuart L Schreiber; Eric S Lander
Journal:  Cell       Date:  2006-04-21       Impact factor: 41.582

Review 3.  Transcription factor networks in erythroid cell and megakaryocyte development.

Authors:  Louis C Doré; John D Crispino
Journal:  Blood       Date:  2011-05-26       Impact factor: 22.113

4.  Retinoic acid is a negative regulator for the differentiation of cord blood-derived human mast cell progenitors.

Authors:  T Kinoshita; K Koike; H H Mwamtemi; S Ito; S Ishida; Y Nakazawa; Y Kurokawa; K Sakashita; T Higuchi; K Takeuchi; N Sawai; M Shiohara; T Kamijo; S Kawa; T Yamashita; A Komiyama
Journal:  Blood       Date:  2000-05-01       Impact factor: 22.113

5.  limma powers differential expression analyses for RNA-sequencing and microarray studies.

Authors:  Matthew E Ritchie; Belinda Phipson; Di Wu; Yifang Hu; Charity W Law; Wei Shi; Gordon K Smyth
Journal:  Nucleic Acids Res       Date:  2015-01-20       Impact factor: 16.971

6.  Genome-wide DNA methylation profiles in hematopoietic stem and progenitor cells reveal overrepresentation of ETS transcription factor binding sites.

Authors:  Amber Hogart; Jens Lichtenberg; Subramanian S Ajay; Stacie Anderson; Elliott H Margulies; David M Bodine
Journal:  Genome Res       Date:  2012-06-08       Impact factor: 9.043

7.  Functional DNA methylation differences between tissues, cell types, and across individuals discovered using the M&M algorithm.

Authors:  Bo Zhang; Yan Zhou; Nan Lin; Rebecca F Lowdon; Chibo Hong; Raman P Nagarajan; Jeffrey B Cheng; Daofeng Li; Michael Stevens; Hyung Joo Lee; Xiaoyun Xing; Jia Zhou; Vasavi Sundaram; Ginell Elliott; Junchen Gu; Taoping Shi; Philippe Gascard; Mahvash Sigaroudinia; Thea D Tlsty; Theresa Kadlecek; Arthur Weiss; Henriette O'Geen; Peggy J Farnham; Cécile L Maire; Keith L Ligon; Pamela A F Madden; Angela Tam; Richard Moore; Martin Hirst; Marco A Marra; Baoxue Zhang; Joseph F Costello; Ting Wang
Journal:  Genome Res       Date:  2013-06-26       Impact factor: 9.043

8.  Comparison of DNA methylation profiles in human fetal and adult red blood cell progenitors.

Authors:  Samuel Lessard; Mélissa Beaudoin; Karim Benkirane; Guillaume Lettre
Journal:  Genome Med       Date:  2015-01-20       Impact factor: 11.117

Review 9.  Zinc finger proteins in cancer progression.

Authors:  Jayu Jen; Yi-Ching Wang
Journal:  J Biomed Sci       Date:  2016-07-13       Impact factor: 8.410

10.  The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores.

Authors:  Rafael A Irizarry; Christine Ladd-Acosta; Andrew P Feinberg; Bo Wen; Zhijin Wu; Carolina Montano; Patrick Onyango; Hengmi Cui; Kevin Gabo; Michael Rongione; Maree Webster; Hong Ji; James Potash; Sarven Sabunciyan
Journal:  Nat Genet       Date:  2009-01-18       Impact factor: 38.330

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