combining computational prediction of cis-regulatory elements with a new enhancer assay to efficiently label neuronal structures in the medaka fish计算预测基因的元素结合新的增强剂测定有效标签青鳉鱼的神经结构.pdfVIP

Combining Computational Prediction of Cis-Regulatory Elements with a New Enhancer Assay to Efficiently Label Neuronal Structures in the Medaka Fish 1. 2. 3 2 4 Emmanuel Mongin , Thomas O. Auer , Franck Bourrat , Franziska Gruhl , Ken Dewar , Mathieu 1 2,5 2 Blanchette *, Joachim Wittbrodt *, Laurence Ettwiller * ´ 1 McGill Centre for Bioinformatics, McGill University, Montreal, Canada, 2 Centre for Organismal Studies COS, University of Heidelberg, Heidelberg, Germany, 3 MSNC INRA Group, UPR2197 DEPSN Institut Fessard, CNRS, Gif-sur-Yvette, France, 4 McGill University and Genome Quebec Innovation Centre, Montreal, Canada, 5 Karlsruhe Institute for Technology KIT, Institute for Toxicology and Genetics, Eggenstein-Leopoldshafen, Germany Abstract The developing vertebrate nervous system contains a remarkable array of neural cells organized into complex, evolutionarily conserved structures. The labeling of living cells in these structures is key for the understanding of brain development and function, yet the generation of stable lines expressing reporter genes in specific spatio-temporal patterns remains a limiting step. In this study we present a fast and reliable pipeline to efficiently generate a set of stable lines expressing a reporter gene in multiple neuronal structures in the developing nervous system in medaka. The pipeline combines both the accurate computational genome-wide prediction of neuronal specific cis-regulatory modules (CRMs) and a newly developed experimental setup to ra