Martin Kircher: New Junior Group Leader Bioinformatics from March 2017
Martin Kircher has joined BIH in March 2017 as a new Junior Group Leader Bioinformatics. He describes his work and experience in a brief portrait.
For more than five years now, my research focuses on computational approaches of identifying functionally relevant genetic changes in disease and adaptation as well as developing more sensitive methods in diagnostics (especially exome, genome and cell-free DNA sequencing). Generally, my research spans the fields of sequence analysis, data mining and functional genomics.
What are you working on? (With which objectives are you dealing?)
Based on a broad interest in genetics, epigenetics, and human adaptation, my group develops computational solutions to overcome technical and experimental obstacles in high-throughput sequencing-based protocols. With the increasing adoption of sequencing technologies in medical research and practice, my main focus area are computational approaches for identifying functionally relevant genetic.
I develop and maintain a widely used variant effect scoring tool (Combined Annotation Dependent Depletion, CADD), that uses machine learning to integrate more than 80 different gene-based and genome-wide annotations. CADD was the first tool to predict variant deleterious for all possible single base-pair alterations genome-wide, while also allowing to score multi-base and insertion/deletion changes.
More recently, I collaborate with experimental groups to obtain and analyze experimental measures of non-coding sequence activity, specifically from Massively Parallel Reporter Assays (MPRA). Despite the majority of all mutations affecting non-coding sequences and a growing evidence of substantial phenotypic effects as well as clinical relevance, mutations in regulatory sequences remain less well understood than those in coding sequence. The lab uses experimental data to infer computational models of regulatory sequence effects with the goal of integrating regulatory sequence models in the next generation of genome-wide variant scores.
How can patients benefit from your research one day?
With a significant reduction in sequencing costs, whole exome and genome sequencing already became the first line of diagnosis for rare diseases over the last few years. This trend will continue and eventually sequencing will become a standard clinical tool. My group develops computational tools to analyze these sequencing data sets and to provide clinicians with summaries of the information available for identified genetic alterations, thereby directly supporting and improving medical decision making.
The most important thing for me is ...
... to put my computational skills to good use and advance research, for example by devising computational approaches to overcome diverse scientific challenges and push technological limits.
My training (B.Sc. and M.Sc. hon.) is in bioinformatics/computational molecular biology (Saarland University, 2003–2007) and I completed my PhD (Dr. rer. nat.) as a collaboration between the MPI for evolutionary Anthropology and the Mathematics and Computer Sciences Department of Leipzig University (2007–2011) supervised by Janet Kelso, PhD, Prof. Svante Pääbo and Prof. Peter Stadler. Between 2012 and 2016, I held a Senior Research Fellow position with Jay Shendure in the Department of Genome Sciences at the University of Washington, Seattle, USA. I was a member of the analysis group of the University of Washington's Center for Mendelian Genomics and have been actively involved in several studies identifying disease causal variants from exome and whole genome sequencing data.
My interests in overcoming specific technical issues while at same time tackling broader scientific questions provides me with a large diversity of hands-on experiences in different research areas:
(1) epigenetics (e.g. imprinting, microRNAs, and DNA methylation)
(2) high-throughput sequencing (e.g. base calling, multiplex sequencing, quality control, and data processing)
(3) gene expression (e.g. tissue- and cell-type specific, during development and between species)
(4) ancient DNA and human evolution (e.g. species/sub-species differences, missing evolution, genetic admixture)
(5) human genetics and rare diseases (e.g. exome and whole genome analysis, linkage analysis)
(6) functional genomics (e.g. integration of diverse annotations, massively parallel functional assays)
(7) tissue-of-origin composition of cell-free DNA.
Due to this diversity, I have always worked with different people and been a member of several teams; making me a highly collaborative scientist.
F. Inoue, M. Kircher, B. Martin, G.M. Cooper, D.M. Witten, M.T. McManus, N. Ahituv, J. Shendure. A systematic comparison reveals substantial differences in chromosomal versus episomal encoding of enhancer activity, Genome Research, 2016 Nov 9. pii: gr.212092.116.
M.W. Snyder, M. Kircher, A.J. Hill, R.M. Daza, and J. Shendure, Cell-free DNA comprises an in vivo nucleosome footprint that informs its tissues-of-origin, Cell, 2016 Jan 14; 164(1-2):57-68.
M. Kircher, D.M. Witten, P. Jain, B.J. O'Roak, G.M. Cooper, and J. Shendure, A general framework for estimating the relative pathogenicity of human genetic variants, Nature Genetics, 46, 310-315.
M. Meyer, M. Kircher, M. Gansauge, H. Li, F. Racimo, S. Mallick, J.G. Schraiber, F. Jay, K. Prüfer, C. de Filippo, P.H. Sudmant, C. Alkan, Q. Fu, R. Do, N. Rohland, A. Tandon, M. Siebauer, R.E. Green, K. Bryc, A.W. Briggs, U. Stenzel, J. Dabney, J. Shendure, J. Kitzman, M.F. Hammer, M.V. Shunkov, A.P. Derevianko, N. Patterson, A.M. Andrés, E.E. Eichler, M. Slatkin, D. Reich, J. Kelso, and S. Pääbo. A high coverage genome sequence from an archaic Denisovan individual, Science, 2012 Aug 31.
D. Reich, R.E. Green, M. Kircher, J. Krause, N. Patterson, E.Y. Durand, B. Viola, A.W. Briggs, U. Stenzel, P.L.F. Johnson, T. Maricic, J.M. Good, T. Marques-Bonet, C. Alkan, Q. Fu, S. Mallick, H. Li, M. Meyer, E.E. Eichler, M. Stoneking, M. Richards, S. Talamo, M.V. Shunkov, A.P. Derevianko, J.-J. Hublin, J. Kelso, M. Slatkin, and S. Pääbo, Genetic history of an archaic hominin group from Denisova Cave in Siberia, Nature, 468(7327):1053-1060.
M. Kircher, U. Stenzel, and J. Kelso, Improved base calling for the Illumina Genome Analyzer using machine learning strategies, Genome Biology, 10(8):R83.