Dominic Grün

Bio: Dominic Grün is an academic researcher from Max Planck Society. The author has contributed to research in topics: Population & Biology. The author has an hindex of 32, co-authored 62 publications receiving 11476 citations. Previous affiliations of Dominic Grün include University Medical Center Utrecht & Utrecht University.

Combinatorial microRNA target predictions.

Abstract: MicroRNAs are small noncoding RNAs that recognize and bind to partially complementary sites in the 3' untranslated regions of target genes in animals and, by unknown mechanisms, regulate protein production of the target transcript. Different combinations of microRNAs are expressed in different cell types and may coordinately regulate cell-specific target genes. Here, we present PicTar, a computational method for identifying common targets of microRNAs. Statistical tests using genome-wide alignments of eight vertebrate genomes, PicTar's ability to specifically recover published microRNA targets, and experimental validation of seven predicted targets suggest that PicTar has an excellent success rate in predicting targets for single microRNAs and for combinations of microRNAs. We find that vertebrate microRNAs target, on average, roughly 200 transcripts each. Furthermore, our results suggest widespread coordinate control executed by microRNAs. In particular, we experimentally validate common regulation of Mtpn by miR-375, miR-124 and let-7b and thus provide evidence for coordinate microRNA control in mammals.

Single-cell messenger RNA sequencing reveals rare intestinal cell types

Abstract: Understanding the development and function of an organ requires the characterization of all of its cell types. Traditional methods for visualizing and isolating subpopulations of cells are based on messenger RNA or protein expression of only a few known marker genes. The unequivocal identification of a specific marker gene, however, poses a major challenge, particularly if this cell type is rare. Identifying rare cell types, such as stem cells, short-lived progenitors, cancer stem cells, or circulating tumour cells, is crucial to acquire a better understanding of normal or diseased tissue biology. To address this challenge we first sequenced the transcriptome of hundreds of randomly selected cells from mouse intestinal organoids, cultured self-organizing epithelial structures that contain all cell lineages of the mammalian intestine. Organoid buds, like intestinal crypts, harbour stem cells that continuously differentiate into a variety of cell types, occurring at widely different abundances. Since available computational methods can only resolve more abundant cell types, we developed RaceID, an algorithm for rare cell type identification in complex populations of single cells. We demonstrate that this algorithm can resolve cell types represented by only a single cell in a population of randomly sampled organoid cells. We use this algorithm to identify Reg4 as a novel marker for enteroendocrine cells, a rare population of hormone-producing intestinal cells. Next, we use Reg4 expression to enrich for these rare cells and investigate the heterogeneity within this population. RaceID confirmed the existence of known enteroendocrine lineages, and moreover discovered novel subtypes, which we subsequently validated in vivo. Having validated RaceID we then applied the algorithm to ex vivo-isolated Lgr5-positive stem cells and their direct progeny. We find that Lgr5-positive cells represent a homogenous abundant population of stem cells mixed with a rare population of Lgr5-positive secretory cells. We envision broad applicability of our method for discovering rare cell types and the corresponding marker genes in healthy and diseased organs.

A Single-Cell Transcriptome Atlas of the Human Pancreas

Abstract: To understand organ function, it is important to have an inventory of its cell types and of their corresponding marker genes. This is a particularly challenging task for human tissues like the pancreas, because reliable markers are limited. Hence, transcriptome-wide studies are typically done on pooled islets of Langerhans, obscuring contributions from rare cell types and of potential subpopulations. To overcome this challenge, we developed an automated platform that uses FACS, robotics, and the CEL-Seq2 protocol to obtain the transcriptomes of thousands of single pancreatic cells from deceased organ donors, allowing in silico purification of all main pancreatic cell types. We identify cell type-specific transcription factors and a subpopulation of REG3A-positive acinar cells. We also show that CD24 and TM4SF4 expression can be used to sort live alpha and beta cells with high purity. This resource will be useful for developing a deeper understanding of pancreatic biology and pathophysiology of diabetes mellitus.

Spatial and temporal heterogeneity of mouse and human microglia at single-cell resolution.

Abstract: Microglia have critical roles not only in neural development and homeostasis, but also in neurodegenerative and neuroinflammatory diseases of the central nervous system1-4. These highly diverse and specialized functions may be executed by subsets of microglia that already exist in situ, or by specific subsets of microglia that develop from a homogeneous pool of cells on demand. However, little is known about the presence of spatially and temporally restricted subclasses of microglia in the central nervous system during development or disease. Here we combine massively parallel single-cell analysis, single-molecule fluorescence in situ hybridization, advanced immunohistochemistry and computational modelling to comprehensively characterize subclasses of microglia in multiple regions of the central nervous system during development and disease. Single-cell analysis of tissues of the central nervous system during homeostasis in mice revealed specific time- and region-dependent subtypes of microglia. Demyelinating and neurodegenerative diseases evoked context-dependent subtypes of microglia with distinct molecular hallmarks and diverse cellular kinetics. Corresponding clusters of microglia were also identified in healthy human brains, and the brains of patients with multiple sclerosis. Our data provide insights into the endogenous immune system of the central nervous system during development, homeostasis and disease, and may also provide new targets for the treatment of neurodegenerative and neuroinflammatory pathologies.

Validation of noise models for single-cell transcriptomics

Abstract: Single-cell transcriptomics has recently emerged as a powerful technology to explore gene expression heterogeneity among single cells. Here we identify two major sources of technical variability: sampling noise and global cell-to-cell variation in sequencing efficiency. We propose noise models to correct for this, which we validate using single-molecule FISH. We demonstrate that gene expression variability in mouse embryonic stem cells depends on the culture condition.

Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells

Abstract: Exosomes are vesicles of endocytic origin released by many cells. These vesicles can mediate communication between cells, facilitating processes such as antigen presentation. Here, we show that exosomes from a mouse and a human mast cell line (MC/9 and HMC-1, respectively), as well as primary bone marrow-derived mouse mast cells, contain RNA. Microarray assessments revealed the presence of mRNA from approximately 1300 genes, many of which are not present in the cytoplasm of the donor cell. In vitro translation proved that the exosome mRNAs were functional. Quality control RNA analysis of total RNA derived from exosomes also revealed presence of small RNAs, including microRNAs. The RNA from mast cell exosomes is transferable to other mouse and human mast cells. After transfer of mouse exosomal RNA to human mast cells, new mouse proteins were found in the recipient cells, indicating that transferred exosomal mRNA can be translated after entering another cell. In summary, we show that exosomes contain both mRNA and microRNA, which can be delivered to another cell, and can be functional in this new location. We propose that this RNA is called "exosomal shuttle RNA" (esRNA).

Most mammalian mRNAs are conserved targets of microRNAs

Abstract: MicroRNAs (miRNAs) are small endogenous RNAs that pair to sites in mRNAs to direct post-transcriptional repression. Many sites that match the miRNA seed (nucleotides 2–7), particularly those in 3 untranslated regions (3UTRs), are preferentially conserved. Here, we overhauled our tool for finding preferential conservation of sequence motifs and applied it to the analysis of human 3UTRs, increasing by nearly threefold the detected number of preferentially conserved miRNA target sites. The new tool more efficiently incorporates new genomes and more completely controls for background conservation by accounting for mutational biases, dinucleotide conservation rates, and the conservation rates of individual UTRs. The improved background model enabled preferential conservation of a new site type, the “offset 6mer,” to be detected. In total, >45,000 miRNA target sites within human 3UTRs are conserved above background levels, and >60% of human protein-coding genes have been under selective pressure to maintain pairing to miRNAs. Mammalian-specific miRNAs have far fewer conserved targets than do the more broadly conserved miRNAs, even when considering only more recently emerged targets. Although pairing to the 3 end of miRNAs can compensate for seed mismatches, this class of sites constitutes less than 2% of all preferentially conserved sites detected. The new tool enables statistically powerful analysis of individual miRNA target sites, with the probability of preferentially conserved targeting (PCT) correlating with experimental measurements of repression. Our expanded set of target predictions (including conserved 3-compensatory sites), are available at the TargetScan website, which displays the PCT for each site and each predicted target.

Oncomirs : microRNAs with a role in cancer

Abstract: I MicroRNAs (miRNAs) are an abundant class of small non-protein-coding RNAs that function as negative gene regulators. They regulate diverse biological processes, and bioinformatic data indicates that each miRNA can control hundreds of gene targets, underscoring the potential influence of miRNAs on almost every genetic pathway. Recent evidence has shown that miRNA mutations or mis-expression correlate with various human cancers and indicates that miRNAs can function as tumour suppressors and oncogenes. miRNAs have been shown to repress the expression of important cancer-related genes and might prove useful in the diagnosis and treatment of cancer.