Advanced methods for genome-wide methylation detection reveal novel epigenetic alterations in leukemia
We have developed an enhanced form of reduced representation bisulfite sequencing with extended genomic coverage, which resulted in greater capture of DNA methylation information of regions lying outside of traditional CpG islands. Applying this method to primary human bone marrow specimens from patients with Acute Myelogeneous Leukemia (AML), we demonstrated that genetically distinct AML subtypes display diametrically opposed DNA methylation patterns. As compared to normal controls, we observed widespread hypermethylation in IDH mutant AMLs, preferentially targeting promoter regions and CpG islands neighboring the transcription start sites of genes. In contrast, AMLs harboring translocations affecting the MLL gene displayed extensive loss of methylation of an almost mutually exclusive set of CpGs, which instead affected introns and distal intergenic CpG islands and shores. When analyzed in conjunction with gene expression profiles, it became apparent that these specific patterns of DNA methylation result in differing roles in gene expression regulation. However, despite this subtype-specific DNA methylation patterning, a much smaller set of CpG sites are consistently affected in both AML subtypes. Most CpG sites in this common core of aberrantly methylated CpGs were hypermethylated in both AML subtypes. Therefore, aberrant DNA methylation patterns in AML do not occur in a stereotypical manner but rather are highly specific and associated with specific driving genetic lesions.
Department of Physiology and Biophysics and the Institute for Computational Biomedicine Weill Cornell Medical College of Cornell University
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Marital Status: Married to an EU citizen
Languages: Turkish, English (fluent), Norwegian (basic/intermediate), Polish (basic)
In 2001, became 42nd among 1,500,000 students in annual central university entrance exams and awarded full scholarship to study in Sabanci University, Istanbul, Turkey. In addition, awarded full scholarship from Turkish Ministry of Education for doing undergrad studies abroad.
During undergrad, did research internships in Uppsala University, Sweden and The Ohio State University, USA, which produced a pubmed indexed publication.
In 2010, started working at Weill Cornell Medical College of Cornell University, NY. Currently, working on cancer genomics and developing tools for high-throughput, big data analysis.
2012 – present Senior Research Associate, Department of Physiology and Biophysics and the Institute for Computational Biomedicine, Weill Cornell Medical College, New York, USA Developing analysis pipelines and leading analysis epigenomics of leukemia. PIs: Christopher Mason and Ari Melnick
2010 – 2012 Postdoctoral associate, Department of Physiology and Biophysics and the Institute for Computational Biomedicine, Weill Cornell Medical College, New York, USA Developing analysis pipelines and leading analysis for DNA-methylation and transcriptome assembly using high-throughput sequencing datasets. PIs: Christopher Mason and Ari Melnick
2005 – 2010 Research Assistant /Research Fellow, Computational Biology Unit, Bergen Center for Computational Science, University of Bergen. Bergen, NORWAY Specialized in gene regulation by integrating comparative genomics and high-throughput datasets (HT-sequencing and microarray data)
2007 fall/winter Visiting Student Researcher, RIKEN Omics Science Center, Yokohama, JAPAN. Worked on high-throughput sequencing data analysis under supervision of Dr.Carsten Daub.
2004 summer Research intern, Linnaeus Bioinformatics Centre, Uppsala University, SWEDEN. Worked on de-novo motif finding algorithms using constraint technology under supervision of Dr.Pierre Flener.
2004 summer Research intern, Computer Science Department, Ohio State University, USA. Worked on developing MHC classification algorithms under supervision of Dr.Hakan Ferhatosmanoglu
2003 summer Research intern, Faculty of Engineering and Natural Sciences, Sabanci University, TURKEY. Worked on classification of G-protein coupled receptors using support vector machines.
- Gene regulation and gene regulatory networks in disease
- DNA/RNA sequencing analysis and its application to genome biology Application of machine learning methods to biological problems Big data analysis, applications of low-cost solutions to big data analysis problems
AWARDS AND ACHIEVEMENTS:
2009 Molecular Biology and Computational Biology Research school, University of Bergen, Travel Fellowship
2006 ISMB Travel Fellowship
2001 – 2005 Sabanci University Honor Scholarship (for ranking 42nd at Science-Math score, 65th at Turkish-Math score; among 1.5 million people in annual central nationwide university entrance exam). Scholarship includes exemption from tuition fees, housing, stipend, yearly book costs and exemption from new technology fees.
2001 – 2005 Certificate of High Honor for academic excellence (for 5 semesters)
2001 Full scholarship from Turkish Ministry of Education to study abroad. (Declined this awarded scholarship to study at Sabanci University)
Programming R, Perl, Unix/shell programming, C++, Sicstus Prolog
Database mySQL, Oracle Database Management program
Other tools Machine-learning tools (WEKA, Rapidminer) & bioinformatics tools (Blast, Clustalw, Emboss, BioPerl etc.)
Lab Skills Western-Blot, SDS-PAGE, PCR, Gel electrophoresis, cell culture
Miscellaneous LaTeX, Sweave, Adobe Illustrator, MS Office
Akalin A, Fredman D, Lenhard B. Genome-wide prediction of target genes under complex long-range cis-regulation. (In Preparation)
Akalin A, Kormaksson M, Sheng L, Mason C. methylKit: bisulfite sequencing analysis R package. Genome Biology (In Press)
Akalin A*, Garrett-Bakelman FE*, Kormaksson M, Busuttil J, et al. Base-pair resolution DNA methylation sequencing reveals profoundly divergent epigenetic landscapes in acute myeloid leukemia.. PLoS Genetics 2012;8(6):e1002781.
* (Equal Contribution)
Plessy C*, Pascarella G*, Bertin N*, Akalin A*, Carrieri C, Vassalli A, Lazarevic D, et al. Promoter architecture of mouse olfactory receptor genes. Genome Research. 2011 Dec 22.
* (Equal Contribution)
Taylor MS, Bokil NJ, Le Cao KA, Masterman KA, Labzin LI, Semple CA, Kapetanovic R, Fairbairn L, Akalin A, Faulkner GJ, Baillie JK et al. Conservation and divergence in Toll-like receptor 4-regulated gene expression in primary human versus mouse macrophages. Proc Natl Acad Sci U S A. 2012 Apr 17;109(16):E944-53
Royo JL, Hidalgo C, Roncero Y, Seda MA, Akalin A, Lenhard B, Casares F, Gómez-Skarmeta JL. Dissecting the transcriptional regulatory properties of human chromosome 16 highly conserved non-coding regions. PLoS One. 2011;6(9):e24824
Ravasi T, Suzuki H, Cannistraci CV, Katayama S, Bajic VB, Tan K, Akalin A, Schmeier S et al. An Atlas of Combinatorial Transcriptional Regulation in Mouse and Man. Cell 2010, 140:744-752
Dong X, Akalin A, Sharma Y, Lenhard B. Translog, a web browser for studying the expression divergence of homologous genes. BMC bioinformatics 2010, 11 Suppl 1:S5910.1186
Punnamoottil B, Herrmann C, Anaya JP, D'Aniello S, Garcia-Fernàndez J, Akalin A, Becker TS. Cis-regulatory characterization of sequence conservation surrounding the Hox4 genes. Dev Biol. 2010 Feb 6.
Bessa J, Tena JJ, de la Calle-Mustienes E, Fernández-Miñán A, Naranjo S, Fernández A, Montoliu L, Akalin A, Lenhard B, Casares F, Gómez-Skarmeta JL. Zebrafish enhancer detection (ZED) vector: a new tool to facilitate transgenesis and the functional analysis of cis-regulatory regions in zebrafish. Dev Dyn. 2009 Sep;238(9):2409-17
FANTOM Consortium, Suzuki H, Forrest AR, van Nimwegen E, Daub CO, Balwierz PJ, Irvine KM, Lassmann T, Ravasi T, Hasegawa Y, de Hoon MJ, Katayama S, Schroder K, Carninci P, Tomaru Y, Kanamori-Katayama M, Kubosaki A, Akalin A, Ando Y, Arner E, Asada M, Asahara H, Bailey T, Bajic VB et al. The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line. Nat Genet. 2009 May;41(5):553-62
Akalin A, Fredman D, Arner E, Dong X, Bryne JC, Suzuki H, Daub CO, Hayashizaki Y, Lenhard B. Transcriptional features of genomic regulatory blocks. Genome Biol. 2009;10(4):R38
Mungpakdee S, Seo HC, Angotzi AR, Dong X, Akalin A, Chourrout D. Differential evolution of the 13 Atlantic salmon Hox clusters. Mol Biol Evol. 2008 Jul;25(7):1333-43
Kikuta H, Laplante M, Navratilova P, Komisarczuk AZ, Engström PG, Fredman D, Akalin A, Caccamo M, Sealy I, Howe K, Ghislain J, Pezeron G, Mourrain P, Ellingsen S, Oates AC, Thisse C, Thisse B, Foucher I, Adolf B, Geling A, Lenhard B, Becker TS. Genomic regulatory blocks encompass multiple neighboring genes and maintain conserved synteny in vertebrates. Genome Res. 2007 May;17(5):545-55
Altiparmak F, Akalin A, Ferhatosmanoglu H. Predicting the binding affinity of MHC class II peptides. Comput Syst Bioinformatics Conf. 2006:331-4
Engström PG, Suzuki H, Ninomiya N, Akalin A, Sessa L, Lavorgna G, Brozzi A, Luzi L, Tan SL, Yang L, Kunarso G, Ng EL, Batalov S, Wahlestedt C, Kai C, Kawai J, Carninci P, Hayashizaki Y, Wells C, Bajic VB, Orlando V, Reid JF, Lenhard B, Lipovich L. Complex Loci in human and mouse genomes. PLoS Genet. 2006 Apr;2(4):e47
Akalin A, Kasap Z, Kavak E, Sezerman U. Determination of the Selectivity of G-protein Coupled Receptor Ligands Using the Support Vector Machine Classification. Biyomut 2004, Bogazici University, İstanbul, Turkey, May 2004.
LARGE SCALE SOFTWARE PROJECTS
Akalin A. Bisulfite sequencing alignment pipeline.(Stable)
Pipeline aligns bisulfite treated reads and calls methylation status per base. The pipeline is used at epigenomics core of Weill Cornell Medical College regularly.
Akalin A, Kormaksson M. methylKit: bisulfite sequencing analysis R package.(Stable)
The R package helps analyzing DNA methylation from high-throughput bisulfite sequencing experiments. The package can find differentially methylated bases/regions, do basic quality check on data, clustering data and annotating regions/bases of interest.
Akalin A, Franke V. Genomation: R package for graphics and operations for genomic features. (ongoing)
The package will help visualization and annotation of any given genomic feature set. It will have convenience functions to read-in a variety of input types and doing statistical tests on association of given sets of features.
Akalin A, Bryne JC. TFBS over-representation and positional bias Perl module. (Stable, Code available upon request)
A Perl module that finds over-represented putative TFBSes in a given set of sequences. The module also has tools to determine and visualize positional preference of putative TFBSes.
2005 – 2010 PhD, Molecular Biology Department and Computational Biology Unit, Bergen Center for Computational Science, University of Bergen. Bergen, NORWAY.
- Thesis: Analysis of long-range regulatory regions and their target genes in animal genomes, Supervisor Dr.Boris Lenhard
- 2001 - 2005 B.Sc, the Biological Sciences and Bioengineering Program (Bioinformatics Curriculum), the Faculty of Engineering and Natural Sciences (FENS), Sabanci University (SU), Istanbul, TURKEY.
- GPA: 3.7/4.00 Fall
- Graduation Project: Prediction and analysis of transcription factor binding sites on gene upstreams, Supervisor Dr.Ugur Sezerman
1993 – 2001 Ankara Ataturk Anadolu High School, Ankara, TURKEY.
CONFERENCES & WORKSHOPS
Analyzing RRBS data. Weill Cornell Medical College Epigenomics Workshop, New York, NY, 2012. (Invited)
DNA methylation analysis of Acute Myeloid leukemia subtypes. MipTec, Basel, Switzerland, 2011.
Transcriptional features of genomic regulatory blocks. BFYS, Trondheim, Norway, 2009.
Ultra-conserved region analysis and its application in fish genomes. BREW, Cambridge, UK, 2006.
Advanced methods for genome-wide methylation detection reveal novel epigenetic dynamics of leukemia. AGBT, Marco Island, FL, 2012.
Transcriptional features of genomic regulatory blocks. Biology of Genomes, Cold Spring Harbor, NY, 2009.
Regulatory content of vertebrate enhancers. ISMB, Fortaleza, Brazil, 2006.
Structure prediction using homology modeling and functional alignment, European Science Foundation (ESF) Protein Structure Prediction Workshop, Antalya, Turkey, November 2002.
GPCR ligand determination using SVMs. ISMB/ECCB, Glasgow, Scotland, 2004.