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Biomedical subjects

Lars M Steinmetz

Publications and source records attributed to Lars M Steinmetz.

17 recordsLinked to original sources
PubMed2026

Dysregulated Ribonucleoprotein Granules Impair Mitochondrial Function in RBM20-Related Dilated Cardiomyopathy.

BACKGROUND: Pathogenic variants in RBM20 cause severe dilated cardiomyopathy. Loss-of-function variants disrupt splicing; neomorphic gain-of-function (GoF) variants also mislocalize RBM20 to cytoplasmic ribonucleoprotein granules and are associated with more aggressive disease. The mechanism by which RBM20 mislocalization drives cardiac dysfunction remains unknown. METHODS: We investigated the effects of Rbm20 GoF and loss-of-function (LoF) variants using proteomic profiling, protein solubility assays, mitochondrial respiration and calcium flux analyses, and ultrastructural imaging in mouse models. Human induced pluripotent stem cell-derived cardioids were used to validate variant-specific phenotypes. RESULTS: Rbm20 GoF, but not LoF, variants caused posttranscriptional downregulation of soluble mitochondrial proteins, including the calcium efflux regulator TMEM65 (transmembrane protein 65), and reduced solubility of mitochondrial membrane proteins. Electron microscopy revealed enlarged mitochondria with cristae disorganization. Functional assays confirmed impaired oxidative phosphorylation, reduced mitochondrial membrane potential, and abnormal calcium handling in Rbm20 GoF models. Human cardioids reproduced these findings, demonstrating that cytoplasmic mislocalization, rather than splicing deficiency, drives mitochondrial dysfunction. CONCLUSIONS: Cytoplasmic mislocalization of RBM20 disrupts mitochondrial function by reducing mitochondrial protein abundance, leading to oxidative phosphorylation failure and abnormal mitochondrial calcium handling. This mechanism distinguishes RBM20 GoF from LoF variants and may explain the more severe heart failure phenotype observed in patients with RBM20 GoF variants. These insights advance the mechanistic understanding of RBM20-related cardiomyopathy and identify mitochondrial mRNA/protein regulation as a key node in cardiac energetics.

cardiomyopathy, dilated↗
PubMed2026

An encyclopedia of human enhancer-gene regulatory interactions.

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the effect of human genetic variation on disease1-6. Here we create and evaluate a resource of more than 92 million enhancer-gene regulatory interactions across 1,458 biosamples covering 369 cell types and tissues, by integrating predictive models, chromatin states, three-dimensional contacts and large-scale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,356 element-gene pairs measured in CRISPR perturbation experiments, more than 30,000 fine-mapped expression quantitative trait loci and 569 fine-mapped genome-wide association study (GWAS) variants linked to a probable causal gene. Using this framework, we develop ENCODE-rE2G, a predictive model achieving state-of-the-art performance across several prediction tasks, demonstrating that iterative perturbations and supervised machine learning can build increasingly accurate predictive models of enhancer regulation. Using ENCODE-rE2G, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, revealing global properties of enhancer networks, identifying differences in regulatory complexity across genes and improving analyses linking noncoding variants to target genes and cell types for common complex diseases. By interpreting the model, we find that beyond enhancer activity and three-dimensional enhancer-promoter contacts, additional features that guide enhancer-promoter communication include promoter class and enhancer-enhancer synergy. These genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

Humans↗
PubMed2025

Functional phenotyping of genomic variants using joint multiomic single-cell DNA-RNA sequencing.

Genetic variants (both coding and noncoding) can impact gene function and expression, driving disease mechanisms such as cancer progression. The systematic study of endogenous genetic variants is hindered by inefficient precision editing tools, combined with technical limitations in confidently linking genotypes to gene expression at single-cell resolution. We developed single-cell DNA-RNA sequencing (SDR-seq) to simultaneously profile up to 480 genomic DNA loci and genes in thousands of single cells, enabling accurate determination of coding and noncoding variant zygosity alongside associated gene expression changes. Using SDR-seq, we associate coding and noncoding variants with distinct gene expression in human induced pluripotent stem cells. Furthermore, we demonstrate that in primary B cell lymphoma samples, cells with a higher mutational burden exhibit elevated B cell receptor signaling and tumorigenic gene expression. SDR-seq provides a powerful platform to dissect regulatory mechanisms encoded by genetic variants, advancing our understanding of gene expression regulation and its implications for disease.

Humans↗
PubMed2006

Assessing systems properties of yeast mitochondria through an interaction map of the organelle.

Mitochondria carry out specialized functions; compartmentalized, yet integrated into the metabolic and signaling processes of the cell. Although many mitochondrial proteins have been identified, understanding their functional interrelationships has been a challenge. Here we construct a comprehensive network of the mitochondrial system. We integrated genome-wide datasets to generate an accurate and inclusive mitochondrial parts list. Together with benchmarked measures of protein interactions, a network of mitochondria was constructed in their cellular context, including extra-mitochondrial proteins. This network also integrates data from different organisms to expand the known mitochondrial biology beyond the information in the existing databases. Our network brings together annotated and predicted functions into a single framework. This enabled, for the entire system, a survey of mutant phenotypes, gene regulation, evolution, and disease susceptibility. Furthermore, we experimentally validated the localization of several candidate proteins and derived novel functional contexts for hundreds of uncharacterized proteins. Our network thus advances the understanding of the mitochondrial system in yeast and identifies properties of genes underlying human mitochondrial disorders.

Disease Susceptibility↗
PubMed2006

Transcript mapping with high-density oligonucleotide tiling arrays.

MOTIVATION: High-density DNA tiling microarrays are a powerful tool for the characterization of complete transcriptomes. The two major analytical challenges are the segmentation of the hybridization signal along genomic coordinates to accurately determine transcript boundaries and the adjustment of the sequence-dependent response of the oligonucleotide probes to achieve quantitative comparability of the signal between different probes. RESULTS: We describe a dynamic programming algorithm for finding a globally optimal fit of a piecewise constant expression profile along genomic coordinates. We developed a probe-specific background correction and scaling method that employs empirical probe response parameters determined from reference hybridizations with no need for paired mismatch probes. This combined analysis approach allows the accurate determination of dynamical changes in transcription architectures from hybridization data and will help to study the biological significance of complex transcriptional phenomena in eukaryotic genomes. AVAILABILITY: R package tilingArray at http://www.bioconductor.org.

Algorithms↗
PubMed2006

Capturing cellular machines by systematic screens of protein complexes.

Two recent studies have provided the most complete screen for protein complexes in yeast to date, in which partners were identified for approximately half of the proteome. A comparison shows that these two datasets are complementary. In addition, one of the analyses points to a modular organization of the cellular protein network. These data will prove useful in defining principles and trends that arise when combining large-scale datasets of different natures, and in deriving properties of protein machines in cellular systems.

Models, Biological↗
PubMed2006

A high-resolution map of transcription in the yeast genome.

There is abundant transcription from eukaryotic genomes unaccounted for by protein coding genes. A high-resolution genome-wide survey of transcription in a well annotated genome will help relate transcriptional complexity to function. By quantifying RNA expression on both strands of the complete genome of Saccharomyces cerevisiae using a high-density oligonucleotide tiling array, this study identifies the boundary, structure, and level of coding and noncoding transcripts. A total of 85% of the genome is expressed in rich media. Apart from expected transcripts, we found operon-like transcripts, transcripts from neighboring genes not separated by intergenic regions, and genes with complex transcriptional architecture where different parts of the same gene are expressed at different levels. We mapped the positions of 3' and 5' UTRs of coding genes and identified hundreds of RNA transcripts distinct from annotated genes. These nonannotated transcripts, on average, have lower sequence conservation and lower rates of deletion phenotype than protein coding genes. Many other transcripts overlap known genes in antisense orientation, and for these pairs global correlations were discovered: UTR lengths correlated with gene function, localization, and requirements for regulation; antisense transcripts overlapped 3' UTRs more than 5' UTRs; UTRs with overlapping antisense tended to be longer; and the presence of antisense associated with gene function. These findings may suggest a regulatory role of antisense transcription in S. cerevisiae. Moreover, the data show that even this well studied genome has transcriptional complexity far beyond current annotation.

5' Untranslated Regions↗
PubMed2006

Complex genetic interactions in a quantitative trait locus.

Whether in natural populations or between two unrelated members of a species, most phenotypic variation is quantitative. To analyze such quantitative traits, one must first map the underlying quantitative trait loci. Next, and far more difficult, one must identify the quantitative trait genes (QTGs), characterize QTG interactions, and identify the phenotypically relevant polymorphisms to determine how QTGs contribute to phenotype. In this work, we analyzed three Saccharomyces cerevisiae high-temperature growth (Htg) QTGs (MKT1, END3, and RHO2). We observed a high level of genetic interactions among QTGs and strain background. Interestingly, while the MKT1 and END3 coding polymorphisms contribute to phenotype, it is the RHO2 3'UTR polymorphisms that are phenotypically relevant. Reciprocal hemizygosity analysis of the Htg QTGs in hybrids between S288c and ten unrelated S. cerevisiae strains reveals that the contributions of the Htg QTGs are not conserved in nine other hybrids, which has implications for QTG identification by marker-trait association. Our findings demonstrate the variety and complexity of QTG contributions to phenotype, the impact of genetic background, and the value of quantitative genetic studies in S. cerevisiae.

3' Untranslated Regions↗
PubMed2005

Re-analysis of data and its integration.

To understand a biological process it is clear that a single approach will not be sufficient, just like a single measurement on a protein--such as its expression level--does not describe protein function. Using reference sets of proteins as benchmarks different approaches can be scaled and integrated. Here, we demonstrate the power of data re-analysis and integration by applying it in a case study to data from deletion phenotype screens and mRNA expression profiling.

Computational Biology↗
PubMed2005

Elevated evolutionary rates in the laboratory strain of Saccharomyces cerevisiae.

By using the maximum likelihood method, we made a genome-wide comparison of the evolutionary rates in the lineages leading to the laboratory strain (S288c) and a wild strain (YJM789) of Saccharomyces cerevisiae and found that genes in the laboratory strain tend to evolve faster than in the wild strain. The pattern of elevated evolution suggests that relaxation of selection intensity is the dominant underlying reason, which is consistent with recurrent bottlenecks in the S. cerevisiae laboratory strain population. Supporting this conclusion are the following observations: (i) the increases in nonsynonymous evolutionary rate occur for genes in all functional categories; (ii) most of the synonymous evolutionary rate increases in S288c occur in genes with strong codon usage bias; (iii) genes under stronger negative selection have a larger increase in nonsynonymous evolutionary rate; and (iv) more genes with adaptive evolution were detected in the laboratory strain, but they do not account for the majority of the increased evolution. The present discoveries suggest that experimental and possible industrial manipulations of the laboratory strain of yeast could have had a strong effect on the genetic makeup of this model organism. Furthermore, they imply an evolution of laboratory model organisms away from their wild counterparts, questioning the relevancy of the models especially when extensive laboratory cultivation has occurred. In addition, these results shed light on the evolution of livestock and crop species that have been under human domestication for years.

Biological Evolution↗
PubMed2004

Integrative analysis of the mitochondrial proteome in yeast.

In this study yeast mitochondria were used as a model system to apply, evaluate, and integrate different genomic approaches to define the proteins of an organelle. Liquid chromatography mass spectrometry applied to purified mitochondria identified 546 proteins. By expression analysis and comparison to other proteome studies, we demonstrate that the proteomic approach identifies primarily highly abundant proteins. By expanding our evaluation to other types of genomic approaches, including systematic deletion phenotype screening, expression profiling, subcellular localization studies, protein interaction analyses, and computational predictions, we show that an integration of approaches moves beyond the limitations of any single approach. We report the success of each approach by benchmarking it against a reference set of known mitochondrial proteins, and predict approximately 700 proteins associated with the mitochondrial organelle from the integration of 22 datasets. We show that a combination of complementary approaches like deletion phenotype screening and mass spectrometry can identify over 75% of the known mitochondrial proteome. These findings have implications for choosing optimal genome-wide approaches for the study of other cellular systems, including organelles and pathways in various species. Furthermore, our systematic identification of genes involved in mitochondrial function and biogenesis in yeast expands the candidate genes available for mapping Mendelian and complex mitochondrial disorders in humans.

Chemical Fractionation↗
PubMed2003

Role of duplicate genes in genetic robustness against null mutations.

Deleting a gene in an organism often has little phenotypic effect, owing to two mechanisms of compensation. The first is the existence of duplicate genes: that is, the loss of function in one copy can be compensated by the other copy or copies. The second mechanism of compensation stems from alternative metabolic pathways, regulatory networks, and so on. The relative importance of the two mechanisms has not been investigated except for a limited study, which suggested that the role of duplicate genes in compensation is negligible. The availability of fitness data for a nearly complete set of single-gene-deletion mutants of the Saccharomyces cerevisiae genome has enabled us to carry out a genome-wide evaluation of the role of duplicate genes in genetic robustness against null mutations. Here we show that there is a significantly higher probability of functional compensation for a duplicate gene than for a singleton, a high correlation between the frequency of compensation and the sequence similarity of two duplicates, and a higher probability of a severe fitness effect when the duplicate copy that is more highly expressed is deleted. We estimate that in S. cerevisiae at least a quarter of those gene deletions that have no phenotype are compensated by duplicate genes.

Evolution, Molecular↗
PubMed2002

Gene function on a genomic scale.

The ability to obtain experimental measurements for thousands of genes has revolutionized our view of biological systems. While traditional studies of gene function evaluated many different properties for a single gene, genomic approaches can measure a single property for thousands of genes. Over the last years, genomic approaches have been developed to measure many different properties, including gene expression, deletion phenotype, and protein characteristics. The promise of integrating these datasets has made it attractive to test whether genomic approaches can determine gene function with accuracy comparable to single gene approaches.

Genome↗
PubMed2002

Systematic screen for human disease genes in yeast.

High similarity between yeast and human mitochondria allows functional genomic study of Saccharomyces cerevisiae to be used to identify human genes involved in disease. So far, 102 heritable disorders have been attributed to defects in a quarter of the known nuclear-encoded mitochondrial proteins in humans. Many mitochondrial diseases remain unexplained, however, in part because only 40-60% of the presumed 700-1,000 proteins involved in mitochondrial function and biogenesis have been identified. Here we apply a systematic functional screen using the pre-existing whole-genome pool of yeast deletion mutants to identify mitochondrial proteins. Three million measurements of strain fitness identified 466 genes whose deletions impaired mitochondrial respiration, of which 265 were new. Our approach gave higher selection than other systematic approaches, including fivefold greater selection than gene expression analysis. To apply these advantages to human disorders involving mitochondria, human orthologs were identified and linked to heritable diseases using genomic map positions.

Biological Transport↗
PubMed2002

Evolutionary rate in the protein interaction network.

High-throughput screens have begun to reveal the protein interaction network that underpins most cellular functions in the yeast Saccharomyces cerevisiae. How the organization of this network affects the evolution of the proteins that compose it is a fundamental question in molecular evolution. We show that the connectivity of well-conserved proteins in the network is negatively correlated with their rate of evolution. Proteins with more interactors evolve more slowly not because they are more important to the organism, but because a greater proportion of the protein is directly involved in its function. At sites important for interaction between proteins, evolutionary changes may occur largely by coevolution, in which substitutions in one protein result in selection pressure for reciprocal changes in interacting partners. We confirm one predicted outcome of this process-namely, that interacting proteins evolve at similar rates.

Amino Acid Substitution↗
PubMed2002

Dissecting the architecture of a quantitative trait locus in yeast.

Most phenotypic diversity in natural populations is characterized by differences in degree rather than in kind. Identification of the actual genes underlying these quantitative traits has proved difficult. As a result, little is known about their genetic architecture. The failures are thought to be due to the different contributions of many underlying genes to the phenotype and the ability of different combinations of genes and environmental factors to produce similar phenotypes. This study combined genome-wide mapping and a new genetic technique named reciprocal-hemizygosity analysis to achieve the complete dissection of a quantitative trait locus (QTL) in Saccharomyces cerevisiae. A QTL architecture was uncovered that was more complex than expected. Functional linkages both in cis and in trans were found between three tightly linked quantitative trait genes that are neither necessary nor sufficient in isolation. This arrangement of alleles explains heterosis (hybrid vigour), the increased fitness of the heterozygote compared with homozygotes. It also demonstrates a deficiency in current approaches to QTL dissection with implications extending to traits in other organisms, including human genetic diseases.

Alleles↗