Martin Bonke

Bio: Martin Bonke is an academic researcher from University of Helsinki. The author has contributed to research in topics: Phloem & Xylem. The author has an hindex of 7, co-authored 9 publications receiving 2769 citations. Previous affiliations of Martin Bonke include National Institutes of Health.

Counting absolute numbers of molecules using unique molecular identifiers

Abstract: Unique molecular identifiers (UMIs) associate distinct sequences with every DNA or RNA molecule and can be counted after amplification to quantify molecules in the original sample. Using UMIs, the authors obtain a digital karyotype of an individual with Down's syndrome and quantify mRNA in Drosophila melanogaster cells.

A novel two-component hybrid molecule regulates vascular morphogenesis of the Arabidopsis root

Abstract: The developmental ontogeny of the vascular system (consisting of xylem, phloem and [pro]cambium) is poorly understood despite its central role in plant physiology. We show that in the Arabidopsis root meristem, xylem cell lineages are specified early, whereas phloem and procambium are established through a set of asymmetric cell divisions. These divisions require the WOODEN LEG (WOL) gene. The WOL gene encodes a novel two-component signal transducer with an unusual tandem arrangement of two receiver domains. It is expressed specifically in the vasculature from the early stages of embryogenesis on, consistent with a role as a sensor for vascular morphogenesis.

Genome-Wide Analysis of ETS-Family DNA-Binding In Vitro and In Vivo

Abstract: Members of the large ETS family of transcription factors (TFs) have highly similar DNA-binding domains (DBDs)—yet they have diverse functions and activities in physiology and oncogenesis. Some differences in DNA-binding preferences within this family have been described, but they have not been analysed systematically, and their contributions to targeting remain largely uncharacterized. We report here the DNA-binding profiles for all human and mouse ETS factors, which we generated using two different methods: a high-throughput microwell-based TF DNA-binding specificity assay, and protein-binding microarrays (PBMs). Both approaches reveal that the ETS-binding profiles cluster into four distinct classes, and that all ETS factors linked to cancer, ERG, ETV1, ETV4 and FLI1, fall into just one of these classes. We identify amino-acid residues that are critical for the differences in specificity between all the classes, and confirm the specificities in vivo using chromatin immunoprecipitation followed by sequencing (ChIP-seq) for a member of each class. The results indicate that even relatively small differences in in vitro binding specificity of a TF contribute to site selectivity in vivo.

APL regulates vascular tissue identity in Arabidopsis

Abstract: Vascular plants have a long-distance transport system consisting of two tissue types with elongated cell files, phloem and xylem. Phloem has two basic cell types, enucleate sieve elements and companion cells. Xylem has various lignified cell types, such as tracheary elements, the differentiation of which involves deposition of elaborate cell wall thickenings and programmed cell death. Until now, little has been known about the genetic control of phloem-xylem patterning. Here we identify the ALTERED PHLOEM DEVELOPMENT (APL) gene, which encodes a MYB coiled-coil-type transcription factor that is required for phloem identity in Arabidopsis. Phloem is established through asymmetric cell divisions and subsequent differentiation. We show that both processes are impaired by a recessive apl mutation. This is associated with the formation of cells that have xylem characteristics in the position of phloem. The APL expression profile is consistent with a key role in phloem development. Ectopic APL expression in the vascular bundle inhibits xylem development. Our studies suggest that APL has a dual role both in promoting phloem differentiation and in repressing xylem differentiation during vascular development.

Multiplexed massively parallel SELEX for characterization of human transcription factor binding specificities

Abstract: The genetic code-the binding specificity of all transfer-RNAs--defines how protein primary structure is determined by DNA sequence. DNA also dictates when and where proteins are expressed, and this information is encoded in a pattern of specific sequence motifs that are recognized by transcription factors. However, the DNA-binding specificity is only known for a small fraction of the approximately 1400 human transcription factors (TFs). We describe here a high-throughput method for analyzing transcription factor binding specificity that is based on systematic evolution of ligands by exponential enrichment (SELEX) and massively parallel sequencing. The method is optimized for analysis of large numbers of TFs in parallel through the use of affinity-tagged proteins, barcoded selection oligonucleotides, and multiplexed sequencing. Data are analyzed by a new bioinformatic platform that uses the hundreds of thousands of sequencing reads obtained to control the quality of the experiments and to generate binding motifs for the TFs. The described technology allows higher throughput and identification of much longer binding profiles than current microarray-based methods. In addition, as our method is based on proteins expressed in mammalian cells, it can also be used to characterize DNA-binding preferences of full-length proteins or proteins requiring post-translational modifications. We validate the method by determining binding specificities of 14 different classes of TFs and by confirming the specificities for NFATC1 and RFX3 using ChIP-seq. Our results reveal unexpected dimeric modes of binding for several factors that were thought to preferentially bind DNA as monomers.

Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position

Abstract: We describe an assay for transposase-accessible chromatin using sequencing (ATAC-seq), based on direct in vitro transposition of sequencing adaptors into native chromatin, as a rapid and sensitive method for integrative epigenomic analysis. ATAC-seq captures open chromatin sites using a simple two-step protocol with 500-50,000 cells and reveals the interplay between genomic locations of open chromatin, DNA-binding proteins, individual nucleosomes and chromatin compaction at nucleotide resolution. We discovered classes of DNA-binding factors that strictly avoided, could tolerate or tended to overlap with nucleosomes. Using ATAC-seq maps of human CD4(+) T cells from a proband obtained on consecutive days, we demonstrated the feasibility of analyzing an individual's epigenome on a timescale compatible with clinical decision-making.

Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets

Abstract: Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution. VIDEO ABSTRACT.

Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq

Abstract: The mammalian cerebral cortex supports cognitive functions such as sensorimotor integration, memory, and social behaviors. Normal brain function relies on a diverse set of differentiated cell types, including neurons, glia, and vasculature. Here, we have used large-scale single-cell RNA sequencing (RNA-seq) to classify cells in the mouse somatosensory cortex and hippocampal CA1 region. We found 47 molecularly distinct subclasses, comprising all known major cell types in the cortex. We identified numerous marker genes, which allowed alignment with known cell types, morphology, and location. We found a layer I interneuron expressing Pax6 and a distinct postmitotic oligodendrocyte subclass marked by Itpr2. Across the diversity of cortical cell types, transcription factors formed a complex, layered regulatory code, suggesting a mechanism for the maintenance of adult cell type identity.

Annotation of functional variation in personal genomes using RegulomeDB

Abstract: As the sequencing of healthy and disease genomes becomes more commonplace, detailed annotation provides interpretation for individual variation responsible for normal and disease phenotypes. Current approaches focus on direct changes in protein coding genes, particularly nonsynonymous mutations that directly affect the gene product. However, most individual variation occurs outside of genes and, indeed, most markers generated from genome-wide association studies (GWAS) identify variants outside of coding segments. Identification of potential regulatory changes that perturb these sites will lead to a better localization of truly functional variants and interpretation of their effects. We have developed a novel approach and database, RegulomeDB, which guides interpretation of regulatory variants in the human genome. RegulomeDB includes high-throughput, experimental data sets from ENCODE and other sources, as well as computational predictions and manual annotations to identify putative regulatory potential and identify functional variants. These data sources are combined into a powerful tool that scores variants to help separate functional variants from a large pool and provides a small set of putative sites with testable hypotheses as to their function. We demonstrate the applicability of this tool to the annotation of noncoding variants from 69 full sequenced genomes as well as that of a personal genome, where thousands of functionally associated variants were identified. Moreover, we demonstrate a GWAS where the database is able to quickly identify the known associated functional variant and provide a hypothesis as to its function. Overall, we expect this approach and resource to be valuable for the annotation of human genome sequences.