Study of cell differentiation by phylogenetic analysis using histone modification data

BMC Bioinformatics

Nishanth Ulhas Nair³  Yu Lin²  Ana Manasovska⁴  Jelena Antic⁴  Paulina Grnarova⁴  Avinash Das Sahu¹  Philipp Bucher³  Bernard ME Moret³ 

[1] Department of Computer Science, University of Maryland, College Park, Maryland, USA

[2] Department of Computer Science and Engineering, University of California, San Diego, San Diego, USA

[3] Swiss Institute of Bioinformatics, Lausanne, Switzerland

[4] School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne (EPFL), EPFL IC IIF LCBB, INJ 211 (Batiment INJ), Station 14, CH-1015 Lausanne, Switzerland

关键词: Evolution of cell types;    Phylogenetics;    Histone modifications;    Epigenomics;    Cell-type trees;    Development;    Cell differentiation;   

Others  :  1087524
DOI  :  10.1186/1471-2105-15-269

 received in 2014-01-05, accepted in 2014-07-29,  发布年份 2014

【 摘 要 】

Background

In cell differentiation, a cell of a less specialized type becomes one of a more specialized type, even though all cells have the same genome. Transcription factors and epigenetic marks like histone modifications can play a significant role in the differentiation process.

Results

In this paper, we present a simple analysis of cell types and differentiation paths using phylogenetic inference based on ChIP-Seq histone modification data. We precisely defined the notion of cell-type trees and provided a procedure of building such trees. We propose new data representation techniques and distance measures for ChIP-Seq data and use these together with standard phylogenetic inference methods to build biologically meaningful cell-type trees that indicate how diverse types of cells are related. We demonstrate our approach on various kinds of histone modifications for various cell types, also using the datasets to explore various issues surrounding replicate data, variability between cells of the same type, and robustness. We use the results to get some interesting biological findings like important patterns of histone modification changes during cell differentiation process.

Conclusions

We introduced and studied the novel problem of inferring cell type trees from histone modification data. The promising results we obtain point the way to a new approach to the study of cell differentiation. We also discuss how cell-type trees can be used to study the evolution of cell types.

【 授权许可】

   
2014 Nair et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

【 参考文献 】

• [1]Lee J-H, Hart SR, Skalnik DG: Histone deacetylase activity is required for embryonic stem cell differentiation. Genesis 2004, 38(1):32-38.
• [2]Lister R, Pelizzola M, Kida YS, Hawkins RD, Nery JR, Hon G, Antosiewicz-Bourget J, O’Malley R, Castanon R, Klugman S, Downes M, Yu R, Stewart R, Ren B, Thomson JA, Evans RM, Ecker JR: Hotspots of aberrant epigenomic reprogramming in human induced pluripotent stem cells. Nature 2011, 471(7336):68-73.
• [3]Lobe CG: Transcription factors and mammalian development. Curr Top Dev Biol 1992, 27:351-351.
• [4]Berger SL: Histone modifications in transcriptional regulation. Curr Opin Genet Dev 2002, 12(2):142-148.
• [5]Nelson DL, Cox MM: Lehninger Principles of Biochemistry, 5th edition. W. H. Freeman. 2008. [http://www.amazon.com/Lehninger-Principles-Biochemistry-David-Nelson/dp/071677108X webcite]
• [6]Barski A, Cuddapah S, Cui K, Roh T-Y, Schones DE, Wang Z, Wei G, Chepelev I, Zhao K: High-resolution profiling of histone methylations in the human genome. Cell 2007, 129(4):823-837.
• [7]Mardis ER: ChIP-seq: welcome to the new frontier. Nat Methods 2007, 4(8):613-613.
• [8]Martin C, Zhang Y: Mechanisms of epigenetic inheritance. Curr Opin Cell Biol 2007, 3(19):266-272.
• [9]Frumkin D, Wasserstrom A, Kaplan S, Feige U, Shapiro E: Genomic variability within an organism exposes its cell lineage tree. PLoS Comput Biol 2005, 1(5):50.
• [10]Guenther MG, Frampton GM, Soldner F, Hockemeyer D, Mitalipova M, Jaenisch R, Young RA: Chromatin structure and gene expression programs of human embryonic and induced pluripotent stem cells. Cell Stem Cell 2010, 7(2):249-257.
• [11]Nair NU, Lin Y, Bucher P, Moret BME: Phylogenetic analysis of cell types using histone modifications. Proc. 13th Workshop on Algorithms in Bioinformatics (WABI), in Lecture Notes in Computer Science 8126. Lecture Notes in Computer Science; 2013: 326–337[http://link.springer.com/chapter/10.1007\%2F978-3-642-40453-5_25\# webcite]
• [12]Arendt D: The evolution of cell types in animals: emerging principles from molecular studies. Nat Rev Genet 2008, 9(11):868-882.
• [13]Fishburn PC: Interval Orders and Interval Graphs: A Study of Partially Ordered Sets. New York: Wiley; 1985.
• [14]Saitou N, Nei M: The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 1987, 4(4):406-425.
• [15]Desper R, Gascuel O: Fast and accurate phylogeny reconstruction algorithms based on the minimum-evolution principle. J Comput Biol 2002, 9(5):687-705.
• [16]Goloboff PA: Analyzing large data sets in reasonable times: solutions for composite optima. Cladistics 1999, 15(4):415-428.
• [17]Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W, Liu XS: Model-based Analysis of ChIP-Seq (MACS). Genome Biol 2008, 9(9):137. BioMed Central Full Text
• [18]Project Consortium ENCODE: A user’s guide to the encyclopedia of DNA elements (ENCODE). PLoS Biol 2011, 9(4):1001046.
• [19]Mikkelsen TS, Ku M, Jaffe DB, Issac B, Lieberman E, Giannoukos G, Alvarez P, Brockman W, Kim T-K, Koche RP, Lee W, Mendenhall E, O’Donovan A, Presser A, Russ C, Xie X, Meissner A, Wernig M, Jaenisch R, Nusbaum C, Lander ES, Bernstein BE: Genome-wide maps of chromatin state in pluripotent and lineage-committed cells. Nature 2007, 448(7153):553-560.
• [20]Rosenbloom KR, Sloan CA, Malladi VS, Dreszer TR, Learned K, Kirkup VM, Wong MC, Maddren M, Fang R, Heitner SG, Lee BT, Barber GP, Harte RA, Diekhans M, Long JC, Wilder SP, Zweig AS, Karolchik D, Kuhn RM, Haussler D, Kent WJ: ENCODE Data in the UCSC Genome Browser: year 5 update. Nucleic Acids Res 2013, 41(D1):56-63.
• [21]Li Q, Brown JB, Huang H, Bickel PJ: Measuring reproducibility of high-throughput experiments. Ann Appl Stat 2011, 5(3):1752-1779.
• [22]McLean CY, Bristor D, Hiller M, Clarke SL, Schaar BT, Lowe CB, Wenger AM, Bejerano G: GREAT improves functional interpretation of cis-regulatory regions. Nat Biotechnol 2010, 28(5):495-501.