Biology subjects

Kretzschmar, W. W.

Publications and source records attributed to Kretzschmar, W. W..

5 recordsLinked to original sources

bioRxiv2023

Erythroid differentiation intensifies RNA mis-splicing in SF3B1-mutant myelodysplastic syndromes with ring sideroblasts

Myelodysplastic syndromes with ring sideroblasts (MDS-RS) commonly originate from mutations in the splicing factor SF3B1 (SF3B1mt). SF3B1mt cause RNA mis-splicing, mechanistically established as the major driver of RS development. However, little is known about RS fate and biology after their initial formation in the human bone marrow. We here achieve isolation of viable RS from patient samples, enabling the first complete investigation of SF3B1mt development from stem cell to RS. We show that RS skew MACS-isolated CD34+ data towards erythroid features not recapitulated in single-cell RNAseq. We demonstrate that RS divide, differentiate, enucleate and actively respond to mis-splicing/oxidative stress, decreasing wildtype stem cell fitness via GDF15 overproduction. We identify circulating RS as a uniform clinical feature associated with disease burden. Finally, we establish that SF3B1mt mis-splicing intensifies during erythroid differentiation and demonstrate through combined transcriptomics/proteomics an uncoupling of RNA/protein biology in RS encompassing severe and dysfunctional mis-splicing of proapoptotic genes. Statement of significanceWe here combine a novel method for RS isolation with state-of-the-art multiomics to perform the first complete investigation of SF3B1mt MDS-RS hematopoiesis from stem cell to RS. We identify the survival mechanisms underlying SF3B1mt erythropoiesis and establish an active role for erythroid differentiation and RS themselves in SF3B1mt MDS-RS pathogenesis.

cancer biology↗

bioRxiv2022

ClusTrast: a short read de novo transcript isoform assembler guided by clustered contigs

BackgroundTranscriptome assembly from RNA-sequencing data in species without a reliable reference genome has to be performed de novo, but studies have shown that de novo methods often have inadequate ability to reconstruct transcript isoforms. We address this issue by constructing an assembly pipeline whose main purpose is to produce a comprehensive set of transcript isoforms. ResultsWe present the de novo transcript isoform assembler ClusTrast, which takes short read RNA-seq data as input, constructs a primary assembly, clusters a set of guiding contigs, aligns the short reads to the guiding contigs, assembles each clustered set of short reads individually, and merges the primary and clusterwise assemblies into the final assembly. We tested ClusTrast on real datasets from six eukaryotic species, and showed that Clus-Trast reconstructed more expressed known isoforms than any of the other tested de novo assemblers, at a moderate reduction in precision. For recall, ClusTrast was on top in the lower end of expression levels (<15% percentile) for all tested datasets, and over the entire range for almost all datasets. Reference transcripts were often (35-69% for the six datasets) reconstructed to at least 95% of their length by ClusTrast, and more than half of reference transcripts (58-81%) were reconstructed with contigs that exhibited polymorphism, measuring on a subset of reliably predicted contigs. ClusTrast recall increased when using a union of assembled transcripts from more than one assembly tool as primary assembly. ConclusionWe suggest that ClusTrast can be a useful tool for studying isoforms in species without a reliable reference genome, in particular when the goal is to produce a comprehensive transcriptome set with polymorphic variants.

bioinformatics↗

bioRxiv2021

Efficient ancestry and mutation simulation with msprime 1.0

Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this necessity, a large number of specialised simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and tskit library. We summarise msprimes many features, and show that its performance is excellent, often many times faster and more memory efficient than specialised alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.

genetics↗

bioRxiv2019

Radiation resistant cancer cells enhance the survival and resistance of sensitive cells in prostate spheroids

Intratumoural heterogeneity contributes to local tumour recurrence and variable responses to radiotherapy in prostate cancer. Despite the multiclonal nature of the disease, tumour control probability for conventional treatment plans is modelled on the assumption that tumour cells in the target region respond identically and independently. Here, using tumour cell subpopulations with different radiation sensitivities from prostate tumour cell lines, we show that radiation resistant cells enhance the survival and radiation resistance of radio-sensitive cells in spheroids but not in monolayer culture. Mathematical modelling indicates that these phenotypic changes result from both competitive and antagonistic cellular interactions in spheroids. Interactions mediated by oxygen constraints define the spatial localisation of the cell populations in spheroids and in xenografts, while those mediated by paracrine signals further modify the microenvironment. Our results show new mechanisms of radiotherapy resistance mediated by cellular interactions and by the microenvironment.

cancer biology↗

bioRxiv2017

A comprehensive map of genetic variation in the world’s largest ethnic group - Han Chinese

As are most non-European populations around the globe, the Han Chinese are relatively understudied in population and medical genetics studies. From low-coverage whole-genome sequencing of 11,670 Han Chinese women we present a catalog of 25,057,223 variants, including 548,401 novel variants that are seen at least 10 times in our dataset. Individuals from our study come from 19 out of 22 provinces across China, allowing us to study population structure, genetic ancestry, and local adaptation in Han Chinese. We identify previously unrecognized population structure along the East-West axis of China and report unique signals of admixture across geographical space, such as European influences among the Northwestern provinces of China. Finally, we identified a number of highly differentiated loci, indicative of local adaptation in the Han Chinese. In particular, we detected extreme differentiation among the Han Chinese at MTHFR, ADH7, and FADS loci, suggesting that these loci may not be specifically selected in Tibetan and Inuit populations as previously suggested. On the other hand, we find that Neandertal ancestry does not vary significantly across the provinces, consistent with admixture prior to the dispersal of modern Han Chinese. Furthermore, contrary to a previous report, Neandertal ancestry does not explain a significant amount of heritability in depression. Our findings provide the largest genetic data set so far made available for Han Chinese and provide insights into the history and population structure of the worlds largest ethnic group.

genetics↗