Céline Keime

Bio: Céline Keime is an academic researcher from University of Strasbourg. The author has contributed to research in topics: Medicine & Serial analysis of gene expression. The author has an hindex of 26, co-authored 63 publications receiving 3292 citations. Previous affiliations of Céline Keime include Centre national de la recherche scientifique & Commissariat à l'énergie atomique et aux énergies alternatives.

A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis

Abstract: During the last 3 years, a number of approaches for the normalization of RNA sequencing data have emerged in the literature, differing both in the type of bias adjustment and in the statistical strategy adopted. However, as data continue to accumulate, there has been no clear consensus on the appropriate normalization method to be used or the impact of a chosen method on the downstream analysis. In this work, we focus on a comprehensive comparison of seven recently proposed normalization methods for the differential analysis of RNA-seq data, with an emphasis on the use of varied real and simulated datasets involving different species and experimental designs to represent data characteristics commonly observed in practice. Based on this comparison study, we propose practical recommendations on the appropriate normalization method to be used and its impact on the differential analysis of RNA-seq data.

seqMINER: an integrated ChIP-seq data interpretation platform

Abstract: In a single experiment, chromatin immunoprecipitation combined with high throughput sequencing (ChIP-seq) provides genome-wide information about a given covalent histone modification or transcription factor occupancy. However, time efficient bioinformatics resources for extracting biological meaning out of these gigabyte-scale datasets are often a limiting factor for data interpretation by biologists. We created an integrated portable ChIP-seq data interpretation platform called seqMINER, with optimized performances for efficient handling of multiple genome-wide datasets. seqMINER allows comparison and integration of multiple ChIP-seq datasets and extraction of qualitative as well as quantitative information. seqMINER can handle the biological complexity of most experimental situations and proposes methods to the user for data classification according to the analysed features. In addition, through multiple graphical representations, seqMINER allows visualization and modelling of general as well as specific patterns in a given dataset. To demonstrate the efficiency of seqMINER, we have carried out a comprehensive analysis of genome-wide chromatin modification data in mouse embryonic stem cells to understand the global epigenetic landscape and its change through cellular differentiation.

Essential role of microphthalmia transcription factor for DNA replication, mitosis and genomic stability in melanoma

Abstract: Malignant melanoma is an aggressive cancer known for its notorious resistance to most current therapies. The basic helix-loop-helix microphthalmia transcription factor (MITF) is the master regulator determining the identity and properties of the melanocyte lineage, and is regarded as a lineage-specific ‘oncogene’ that has a critical role in the pathogenesis of melanoma. MITF promotes melanoma cell proliferation, whereas sustained supression of MITF expression leads to senescence. By combining chromatin immunoprecipitation coupled to high throughput sequencing (ChIP-seq) and RNA sequencing analyses, we show that MITF directly regulates a set of genes required for DNA replication, repair and mitosis. Our results reveal how loss of MITF regulates mitotic fidelity, and through defective replication and repair induces DNA damage, ultimately ending in cellular senescence. These findings reveal a lineage-specific control of DNA replication and mitosis by MITF, providing new avenues for therapeutic intervention in melanoma. The identification of MITF-binding sites and gene-regulatory networks establish a framework for understanding oncogenic basic helix-loop-helix factors such as N-myc or TFE3 in other cancers.

Genome-wide nucleosome specificity and function of chromatin remodellers in ES cells

Abstract: ATP-dependent chromatin remodellers allow access to DNA for transcription factors and the general transcription machinery, but whether mammalian chromatin remodellers target specific nucleosomes to regulate transcription is unclear. Here we present genome-wide remodeller-nucleosome interaction profiles for the chromatin remodellers Chd1, Chd2, Chd4, Chd6, Chd8, Chd9, Brg1 and Ep400 in mouse embryonic stem (ES) cells. These remodellers bind one or both full nucleosomes that flank micrococcal nuclease (MNase)-defined nucleosome-free promoter regions (NFRs), where they separate divergent transcription. Surprisingly, large CpG-rich NFRs that extend downstream of annotated transcriptional start sites are nevertheless bound by non-nucleosomal or subnucleosomal histone variants (H3.3 and H2A.Z) and marked by H3K4me3 and H3K27ac modifications. RNA polymerase II therefore navigates hundreds of base pairs of altered chromatin in the sense direction before encountering an MNase-resistant nucleosome at the 3' end of the NFR. Transcriptome analysis after remodeller depletion reveals reciprocal mechanisms of transcriptional regulation by remodellers. Whereas at active genes individual remodellers have either positive or negative roles via altering nucleosome stability, at polycomb-enriched bivalent genes the same remodellers act in an opposite manner. These findings indicate that remodellers target specific nucleosomes at the edge of NFRs, where they regulate ES cell transcriptional programs.

Transcription factor MITF and remodeller BRG1 define chromatin organisation at regulatory elements in melanoma cells

Abstract: Microphthalmia-associated transcription factor (MITF) is the master regulator of the melanocyte lineage. To understand how MITF regulates transcription, we used tandem affinity purification and mass spectrometry to define a comprehensive MITF interactome identifying novel cofactors involved in transcription, DNA replication and repair, and chromatin organisation. We show that MITF interacts with a PBAF chromatin remodelling complex comprising BRG1 and CHD7. BRG1 is essential for melanoma cell proliferation in vitro and for normal melanocyte development in vivo. MITF and SOX10 actively recruit BRG1 to a set of MITF-associated regulatory elements (MAREs) at active enhancers. Combinations of MITF, SOX10, TFAP2A, and YY1 bind between two BRG1-occupied nucleosomes thus defining both a signature of transcription factors essential for the melanocyte lineage and a specific chromatin organisation of the regulatory elements they occupy. BRG1 also regulates the dynamics of MITF genomic occupancy. MITF-BRG1 interplay thus plays an essential role in transcription regulation in melanoma.

De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis

Abstract: De novo assembly of RNA-seq data enables researchers to study transcriptomes without the need for a genome sequence; this approach can be usefully applied, for instance, in research on 'non-model organisms' of ecological and evolutionary importance, cancer samples or the microbiome. In this protocol we describe the use of the Trinity platform for de novo transcriptome assembly from RNA-seq data in non-model organisms. We also present Trinity-supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples and approaches to identify protein-coding genes. In the procedure, we provide a workflow for genome-independent transcriptome analysis leveraging the Trinity platform. The software, documentation and demonstrations are freely available from http://trinityrnaseq.sourceforge.net. The run time of this protocol is highly dependent on the size and complexity of data to be analyzed. The example data set analyzed in the procedure detailed herein can be processed in less than 5 h.

Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome

Abstract: Oilseed rape (Brassica napus L.) was formed ~7500 years ago by hybridization between B. rapa and B. oleracea, followed by chromosome doubling, a process known as allopolyploidy. Together with more ancient polyploidizations, this conferred an aggregate 72× genome multiplication since the origin of angiosperms and high gene content. We examined the B. napus genome and the consequences of its recent duplication. The constituent An and Cn subgenomes are engaged in subtle structural, functional, and epigenetic cross-talk, with abundant homeologous exchanges. Incipient gene loss and expression divergence have begun. Selection in B. napus oilseed types has accelerated the loss of glucosinolate genes, while preserving expansion of oil biosynthesis genes. These processes provide insights into allopolyploid evolution and its relationship with crop domestication and improvement.

Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

Abstract: Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.