Computational biology statistics, bioinformatics and software development (Lukasz Huminiecki, SciLifeLab Stockholm)
Keywords: Computational biology, bioinformatics, software development
Major projects in the lab:
(A). Evolutionary systems biology of cancer genomics data: computational identification of driver mutations. Development of software and statistical methods for cancer mutation analysis.
What is the scientific rationale behind this project? Cancer genomics is generating a flood of data that must be channeled through high-level computational analyses, leading to hypothesis generation, and powerful new knowledge. We propose that applying cancer genomics for the benefit of patients, will require putting cancer mutation data in the context of cellular networks and evolutionary history. To this end, we are applying and developing the principles of two novel scientific disciplines: network medicine and evolutionary systems biology. With the use of freely available open access data on cancer mutations and tumor-associated expression profiles, as well as signalling pathway, genomics, expression, and miRNA databases, we aim at differentiation between driver and passenger mutations in the catalogs of cancer genomics data for thousands of tumors, generated by the US National Institutes of Health Cancer Genome Atlas (NIH-TCGA). Importantly, however, NIH-TCGA is narrowly focused on individual tumor types. In contrast, we conduct a meta-analytical approach which could be termed Comparative Cancer Genomics (CCG), focusing on network features such as duplicated genes which mediate signalling robustness. An R package for “network and duplication aware” analysis of cancer mutation data, named the Duplicator, is nearing its alpha release.
Another goal of the project is to interact with next generation sequencing (NGS) initiatives focusing on cancer, in Sweden. In the educational stream of the VR-BILS activities, Lukasz contributes with the Genome Browsers’ course and now prepares a second course on advanced R/Bioconductor applications in genomics and systems biology.
(B) Linking signalling and miRNA networks with vertebrate evolution
We conduct computational analysis of global patterns of gene and genome duplications in vertebrates, and their consequences for signal transduction, and microRNA (miRNA) network evolution, as well as expression pattern evolution. We use pathway databases and freely available genomic, expression, and miRNA datasets, to infer architectural changes of the animal signal transduction and miRNA networks after small scale duplications (SSDs) and whole genome duplications (WGDs). Quantification of the patterns of nonfunctionalization, subfunctionalization, and neofunctionalization will enhance our understanding of the evolutionary forces driving duplicate retention. The identification of the shared animal developmental toolkit is one of the most significant and fundamental discoveries in biology, and we designate the toolkit to be a focus area investigated besides the global perspective. Rich supply of data generated by the genomics community and freely available in public domain, as well as bioinformatics expertise established over many years through working in several top labs, guarantee feasibility of this study. Proof of feasibility has been already generated with published studies on the evolution of the transforming growth factor-beta pathway (Huminiecki, Goldovsky et al. 2009), and global analysis of the rewiring of the vertebrate signal transduction engine following 2R-WGD (Huminiecki and Heldin 2010).
Huminiecki L, Gavin C. Polyploidy and the evolution of complex traits. Int J Evol Biol. 2012.
Huminiecki L, Heldin CH. 2R and the rewiring of the vertebrate signal transduction engine. BMC Biology 2010 Dec 13;8:146.
As a co-author with the FANTOM Consortium. The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line. Nat Genetics 2009 May;41(5): 553-62.
Huminiecki L, Goldovsky L, Freilich S, Moustakas A, Ouzounis C, Heldin CH. Emergence, Development and Diversification of the TGF-beta Signalling Pathway within the Animal Kingdom. BMC Evol Biol, 2009.
Martin C Frith, Laurens G Wilming, Hideya Kawaji, Alistair Forrest, RIKEN-GERG members, Claes Wahlestedt, Vladimir B Bajic, Lukasz Huminiecki. Pseudo-Messenger RNA: Phantoms of the Transcriptome. PLOS Genetics, 2006.
As a co-author with the FANTOM Consortium. The transcriptional landscape of the mammalian genome. Science. 2005 Sep 2;309(5740):1559-63.
Huminiecki L, Wolfe KH. Divergence of spatial gene expression profiles following species-specific gene duplications in human and mouse. Genome Research, 2004 Oct;14(10A): 1870-9.
Hubbard T, Barker D, Birney E, Cameron G, Chen Y, Clark L, Cox T, Cuff J, Curwen V, Down T, Durbin R, Eyras E, Gilbert J, Hammond M, Huminiecki L, Kasprzyk A, Lehvaslaiho H, Lijnzaad P, Melsopp C, Mongin E, Pettett R, Pocock M, Potter S, Rust A, Schmidt E, Searle S, Slater G, Smith J, Spooner W, Stabenau A, Stalker J, Stupka E, Ureta-Vidal A, Vastrik I, Clamp M. The Ensembl genome database project. Nucleic Acids Res. 2002 Jan 1; 30(1): 38-41.
Huminiecki L, Gorn M, Suchting S, Poulsom R, Bicknell R. Magic roundabout is a new member of the roundabout receptor family that is endothelial specific and expressed at sites of active angiogenesis. Genomics. 2002 Apr; 79(4): 547-52.
Huminiecki L, Bicknell R. In silico cloning of novel endothelial-specific genes. Genome Res. 2000 Nov; 10(11): 1796-806.
SciLifeLab affiliated publications
Open in SciLifeLab PubRefDb