Biology subjects

Deplancke, B.

Publications and source records attributed to Deplancke, B..

5 recordsLinked to original sources

bioRxiv2018

Commensal bacteria act as a broad genetic buffer in Drosophila during chronic under-nutrition

Eukaryotic genomes encode several well-studied buffering mechanisms that robustly maintain invariant phenotypic outcome despite fluctuating environmental conditions. Here we show that the gut microbiota, represented by a single Drosophila facultative symbiont, Lactobacillus plantarum (LpWJL), acts also as a broad genetic buffer that masks the contribution of the cryptic genetic variations in the host under nutritional stress. During chronic under-nutrition, LpWJL consistently reduces variation in different host phenotypic traits and ensures robust organ patterning; LpWJL also decreases genotype-dependent expression variation, particularly for development-associated genes. We further demonstrate that LpWJL buffers via reactive oxygen species (ROS) signaling whose inhibition severely impairs microbiota-mediated phenotypic robustness. We thus identified an unexpected contribution of facultative symbionts to Drosophila fitness by assuring developmental robustness and phenotypic homogeneity in times of nutritional stress.

developmental biology↗

bioRxiv2018

Genomic analysis of European Drosophila melanogaster populations on a dense spatial scale reveals longitudinal population structure and continent-wide selection

Genetic variation is the fuel of evolution, with standing genetic variation especially important for short-term evolution and local adaptation. To date, studies of spatio-temporal patterns of genetic variation in natural populations have been challenging, as comprehensive sampling is logistically difficult, and sequencing of entire populations costly. Here, we address these issues using a collaborative approach, sequencing 48 pooled population samples from 32 locations, and perform the first continent-wide genomic analysis of genetic variation in European Drosophila melanogaster. Our analyses uncover longitudinal population structure, provide evidence for continent-wide selective sweeps, identify candidate genes for local climate adaptation, and document clines in chromosomal inversion and transposable element frequencies. We also characterise variation among populations in the composition of the fly microbiome, and identify five new DNA viruses in our samples.

evolutionary biology↗

bioRxiv2018

Time- and cost-efficient high-throughput transcriptomics enabled by Bulk RNA Barcoding and sequencing

Genome-wide gene expression analyses by RNA sequencing (RNA-seq) have quickly become a standard in molecular biology because of the widespread availability of high throughput sequencing technologies. While powerful, RNA-seq still has several limitations, including the time and cost of library preparation, which makes it difficult to profile many samples simultaneously. To deal with these constraints, the single-cell transcriptomics field has implemented the early multiplexing principle, making the library preparation of hundreds of samples (cells) markedly more affordable. However, the current standard methods for bulk transcriptomics (such as TruSeq Stranded mRNA) remain expensive, and relatively little effort has been invested to develop cheaper, but equally robust methods. Here, we present a novel approach, Bulk RNA Barcoding and sequencing (BRB-seq), that combines the multiplexing-driven cost-effectiveness of a single-cell RNA-seq workflow with the performance of a bulk RNA-seq procedure. BRB-seq produces 3 enriched cDNA libraries that exhibit similar gene expression quantification to TruSeq and that maintain this quality, also in terms of number of detected differentially expressed genes, even with low quality RNA samples. We show that BRB-seq is about 25 times less expensive than TruSeq, enabling the generation of ready to sequence libraries for up to 192 samples in a day with only 2 hours of hands-on time. We conclude that BRB-seq constitutes a powerful alternative to TruSeq as a standard bulk RNA-seq approach. Moreover, we anticipate that this novel method will eventually replace RT-qPCR-based gene expression screens given its capacity to generate genome-wide transcriptomic data at a cost that is comparable to profiling 4 genes using RT-qPCR.\n\n SoftwareWe developed a suite of open source tools (BRB-seqTools) to aid with processing BRB-seq data and generating count matrices that are used for further analyses. This suite can perform demultiplexing, generate count/UMI matrices and trim BRB-seq constructs and is freely available at http://github.com/DeplanckeLab/BRB-seqTools\n\nHighlightsO_LIRapid (~2h hands on time) and low-cost approach to perform transcriptomics on hundreds of RNA samples\nC_LIO_LIStrand specificity preserved\nC_LIO_LIPerformance: number of detected genes is equal to Illumina TruSeq Stranded mRNA at same sequencing depth\nC_LIO_LIHigh capacity: low cost allows increasing the number of biological replicates\nC_LIO_LIProduces reliable data even with low quality RNA samples (down to RIN value = 2)\nC_LIO_LIComplete user-friendly sequencing data pre-processing and analysis pipeline allowing result acquisition in a day\nC_LI

genomics↗

bioRxiv2017

The Human Cell Atlas

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body, by undertaking a Human Cell Atlas Project as an international collaborative effort. The aim would be to define all human cell types in terms of distinctive molecular profiles (e.g., gene expression) and connect this information with classical cellular descriptions (e.g., location and morphology). A comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, as well as provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas.

cell biology↗

bioRxiv2016

ASAP: a Web-based platform for the analysis and inter-active visualization of single-cell RNA-seq data

MotivationSingle-cell RNA-sequencing (scRNA-seq) allows whole transcriptome profiling of thousands of individual cells, enabling the molecular exploration of tissues at the cellular level. Such analytical capacity is of great interest to many research groups in the world, yet, these groups often lack the expertise to handle complex scRNA-seq data sets.\n\nResultsWe developed a fully integrated, web-based platform aimed at the complete analysis of scRNA-seq data post genome alignment: from the parsing, filtering, and normalization of the input count data files, to the visual representation of the data, identification of cell clusters, differentially expressed genes (including cluster-specific marker genes), and functional gene set enrichment. This Automated Single-cell Analysis Pipeline (ASAP) combines a wide range of commonly used algorithms with sophisticated visualization tools. Compared with existing scRNA-seq analysis platforms, researchers (including those lacking computational expertise) are able to interact with the data in a straightforward fashion and in real time. Furthermore, given the overlap between scRNA-seq and bulk RNA-seq analysis workflows, ASAP should conceptually be broadly applicable to any RNA-seq dataset. As a validation, we demonstrate how we can use ASAP to simply reproduce the results from a single-cell study of 91 mouse cells involving five distinct cell types.\n\nAvailabilityThe tool is freely available at http://asap.epfl.ch\n\nContactbart.deplancke@epfl.ch

bioinformatics↗