Marc W. Schmid

Bio: Marc W. Schmid is an academic researcher from University of Zurich. The author has contributed to research in topics: Biodiversity & Gene. The author has an hindex of 21, co-authored 51 publications receiving 1852 citations.

Plant germline formation: common concepts and developmental flexibility in sexual and asexual reproduction

Abstract: The life cycle of flowering plants alternates between two heteromorphic generations: a diploid sporophytic generation and a haploid gametophytic generation. During the development of the plant reproductive lineages - the germlines - typically, single sporophytic (somatic) cells in the flower become committed to undergo meiosis. The resulting spores subsequently develop into highly polarized and differentiated haploid gametophytes that harbour the gametes. Recent studies have provided insights into the genetic basis and regulatory programs underlying cell specification and the acquisition of reproductive fate during both sexual reproduction and asexual (apomictic) reproduction. As we review here, these recent advances emphasize the importance of transcriptional, translational and post-transcriptional regulation, and the role of epigenetic regulatory pathways and hormonal activity.

A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing.

Abstract: The acquisition of distinct cell fates is central to the development of multicellular organisms and is largely mediated by gene expression patterns specific to individual cells and tissues. A spatially and temporally resolved analysis of gene expression facilitates the elucidation of transcriptional networks linked to cellular identity and function. We present an approach that allows cell type-specific transcriptional profiling of distinct target cells, which are rare and difficult to access, with unprecedented sensitivity and resolution. We combined laser-assisted microdissection (LAM), linear amplification starting from <1 ng of total RNA, and RNA-sequencing (RNA-Seq). As a model we used the central cell of the Arabidopsis thaliana female gametophyte, one of the female gametes harbored in the reproductive organs of the flower. We estimated the number of expressed genes to be more than twice the number reported previously in a study using LAM and ATH1 microarrays, and identified several classes of genes that were systematically underrepresented in the transcriptome measured with the ATH1 microarray. Among them are many genes that are likely to be important for developmental processes and specific cellular functions. In addition, we identified several intergenic regions, which are likely to be transcribed, and describe a considerable fraction of reads mapping to introns and regions flanking annotated loci, which may represent alternative transcript isoforms. Finally, we performed a de novo assembly of the transcriptome and show that the method is suitable for studying individual cell types of organisms lacking reference sequence information, demonstrating that this approach can be applied to most eukaryotic organisms.

Contribution of epigenetic variation to adaptation in Arabidopsis.

Abstract: In plants, transgenerational inheritance of some epialleles has been demonstrated but it remains controversial whether epigenetic variation is subject to selection and contributes to adaptation. Simulating selection in a rapidly changing environment, we compare phenotypic traits and epigenetic variation between Arabidopsis thaliana populations grown for five generations under selection and their genetically nearly identical ancestors. Selected populations of two distinct genotypes show significant differences in flowering time and plant architecture, which are maintained for at least 2–3 generations in the absence of selection. While we cannot detect consistent genetic changes, we observe a reduction of epigenetic diversity and changes in the methylation state of about 50,000 cytosines, some of which are associated with phenotypic changes. Thus, we propose that epigenetic variation is subject to selection and can contribute to rapid adaptive responses, although the extent to which epigenetics plays a role in adaptation is still unclear.

Integrative Genomics Viewer

Abstract: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

Juicer provides a one-click system for analyzing loop-resolution Hi-C experiments

Abstract: Hi-C experiments explore the 3D structure of the genome, generating terabases of data to create high-resolution contact maps. Here, we introduce Juicer, an open-source tool for analyzing terabase-scale Hi-C datasets. Juicer allows users without a computational background to transform raw sequence data into normalized contact maps with one click. Juicer produces a hic file containing compressed contact matrices at many resolutions, facilitating visualization and analysis at multiple scales. Structural features, such as loops and domains, are automatically annotated. Juicer is available as open source software at http://aidenlab.org/juicer/.

HiC-Pro: an optimized and flexible pipeline for Hi-C data processing

Abstract: HiC-Pro is an optimized and flexible pipeline for processing Hi-C data from raw reads to normalized contact maps. HiC-Pro maps reads, detects valid ligation products, performs quality controls and generates intra- and inter-chromosomal contact maps. It includes a fast implementation of the iterative correction method and is based on a memory-efficient data format for Hi-C contact maps. In addition, HiC-Pro can use phased genotype data to build allele-specific contact maps. We applied HiC-Pro to different Hi-C datasets, demonstrating its ability to easily process large data in a reasonable time. Source code and documentation are available at http://github.com/nservant/HiC-Pro .

The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads.

Abstract: We present Rsubread, a Bioconductor software package that provides high-performance alignment and read counting functions for RNA-seq reads. Rsubread is based on the successful Subread suite with the added ease-of-use of the R programming environment, creating a matrix of read counts directly as an R object ready for downstream analysis. It integrates read mapping and quantification in a single package and has no software dependencies other than R itself. We demonstrate Rsubread's ability to detect exon-exon junctions de novo and to quantify expression at the level of either genes, exons or exon junctions. The resulting read counts can be input directly into a wide range of downstream statistical analyses using other Bioconductor packages. Using SEQC data and simulations, we compare Rsubread to TopHat2, STAR and HTSeq as well as to counting functions in the Bioconductor infrastructure packages. We consider the performance of these tools on the combined quantification task starting from raw sequence reads through to summary counts, and in particular evaluate the performance of different combinations of alignment and counting algorithms. We show that Rsubread is faster and uses less memory than competitor tools and produces read count summaries that more accurately correlate with true values.