External Scientific Member, Max-Planck-Institute for Mathematics in the Sciences, Leipzig, Germany
Predicting the Past: Two recent applications of phylogenetic-network construction regarding the evolution of the HOX-gene cluster and the placental mammals
Director and Klaus Tschira Chair of Systems Biology, Max-Planck-Institute of Molecular Cell Biology and Genetics, Dresden, Germany
Light-Based Systems Biology
We are now at a time when we can systematically alter animals genetically so that any given protein or its expression can be observed in a targeted set of cells. Combined with new modalities of light microscopy, this allows us to observe molecular mechanisms within the cell, observe the developmental trajectory of growing organs, and to map the cellular anatomy of organisms and organs such as a fly brain. Several brief examples from our work will be presented: on the biophysics of cell division, on C.elegans lineage tracking, and on the reconstruction of every neuron in a fly brain. To end, we give a vision of microscopes and software that we hope will lead to an understand of how complex tissues and shapes develop in cellular terms.
Nobel laureate 1991, Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany
Blind source separation applied to multiply labeled fluorescence images
Methods of blind source separation are used in many contexts to separate composite data sets according to their sources. Multiply labeled fluorescence microscopy images represent such sets, in which the sources are the individual labels. Their distributions are the quantities of interest and have to be extracted from the images. This is often challenging, since the recorded emission spectra of fluorescent dyes are environment- and instrument-specific. We have developed a nonnegative matrix factorization (NMF) algorithm to detect and separate spectrally distinct components of multiply labeled fluorescence images. It operates on spectrally resolved images and delivers both the emission spectra of the identified components and images of their abundance. We tested the proposed method using biological samples labeled with up to four spectrally overlapping fluorescent labels. In most cases, NMF accurately decomposed the images into contributions of individual dyes. However, the solutions are not unique when spectra overlap strongly or when images are diffuse in their structure. We also describe several strategies how to remove the degeneracy using prior information [see Neher R.A., Mitkovski M., Kirchhoff F., Neher E., Theis F.J., Zeug A. (2009) Blind source separation techniques for the decomposition of multiply labeled fluorescence images. Biophysical J (96):3791-3800.]
Head of Bioinformatics division, Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia
Normalization of RNA-Seq Data: Are the ERCC Spike-In Controls Reliable?
Joint work with Sandrine Dudoit, Davide Risso and John Ngai, all from UC Berkeley.
The External RNA Control Consortium (ERCC) developed a set of 92 synthetic polyadenylated RNA standards that mimic natural eukaryotic mRNA (Jiang et al., 2011). The standards are designed to have a wide range of lengths (250-2,000 nucleotides) and GC-contents (5-51%). The ERCC standards can be spiked into RNA at various concentrations prior to the library preparation step and serve as negative and positive controls in RNA-Seq. Ambion commercializes spike-in control mixes, ERCC ExFold RNA Spike-in Control Mix 1 and 2, each containing the same set of 92 standards, but at different concentrations.
We investigate the use of the ERCC spike-in controls for two main purposes: (a) Quality assessment/quality control (QA/QC) of RNA-Seq data and benchmarking of normalization and differential expression (DE) methods, and (b) Direct inclusion in between-sample normalization procedures.
We have two RNA-seq data sets which make use of the ERCC controls: a local one concerning treated and untreated zebrafish tissue, and some of the SEQC samples.
A variety of normalization methods will be compared, both using and not using the ERCC controls.
Group leader, Wellcome Trust Sanger Institute, and European Bioinformatics Institute, Cambridge, UK
Gene expression genomics in T cells
T helper cells are central to mammalian adaptive immunity, as the different subtypes modulate the immune system by either activating or repressing it. These cells are easily experimentally accessible as they are non-adherent, and can be studied ex vivo or in vitro. We have used this system to study basic principles of the global regulation of gene expression using next generation sequencing technologies, both at the level of populations of cells (Hebenstreit et al., 2011, Mol Sys Biol; Hebenstreit et al., 2011, Nucleic Acids Res) and at the level of single cells (Brennecke et al., Nature Methods, in press). Our bulk and single cell RNA-sequencing data has also directed our attention to a potential new signalling system in T helper cells based on steroid production by these cells, illustrating the power of this genomic approach for providing specific biological insights.