Biology subjects

Srivatsan, S. N.

Publications and source records attributed to Srivatsan, S. N..

5 recordsLinked to original sources

bioRxiv2026

Long read sequencing reveals novel isoforms and spliceosome-mutant-enriched transcripts in AML and MDS

The alternative splicing landscape of the leukemia transcriptome remains poorly characterized, since short-read sequencing cannot resolve complete transcript structures. Using the Oxford Nanopore cDNA platform, we generated nearly 2 billion long reads (median 25.8 million per sample) from 71 human samples, including 48 acute myeloid leukemia or myelodysplastic syndrome samples, 25 of which had splicing-factor gene mutations (in SRSF2, U2AF1, or SF3B1). An additional 23 samples were from sorted hematopoietic cell populations from healthy individuals. Using this dataset, we created a transcript assembly containing 174,162 novel isoforms that are not described in the reference transcriptome. Deep-scale proteomic validation confirmed that many of these transcripts are translated into protein. We also identified isoforms enriched in spliceosome-mutant samples and found proteomic evidence of frequent nonsense-mediated decay regulation of novel transcripts. This dataset is a valuable community resource, enabling detection of new transcripts in short-read data sets. An interactive portal to explore splicing patterns in these data is available at https://leylab.org/isoforms/. Key PointsLong-read sequencing enables the detection of many novel transcripts in AML, including many from splice-factor-mutant patient samples This expanded transcriptome is a valuable community resource and can be used to improve analyses of short-read RNAseq data

cancer biology↗

bioRxiv2022

A condensate forming tether for lariat debranching enzyme is defective in non-photosensitive trichiothiodystrophy

The pre-mRNA life cycle requires intron processing; yet, how intron processing defects influence splicing and gene expression is unclear. Here, we find TTDN1, which is frequently mutated in non-photosensitive trichothiodystrophy (NP-TTD), functionally links intron lariat processing to the spliceosome. The conserved TTDN1 C-terminal region directly binds lariat debranching enzyme DBR1, while its N-terminal intrinsically disordered region (IDR) binds the intron binding complex (IBC). The IDR forms condensates in vitro and is needed for IBC interaction. TTDN1 loss causes significant intron lariat accumulation, as well as splicing and gene expression defects, mirroring phenotypes observed in NP-TTD patient cells. Ttdn1{Delta}/{Delta} mice recapitulate intron processing defects and neurodevelopmental phenotypes seen in NP-TTD. A DBR1-IDR fusion recruits DBR1 to the IBC and circumvents the requirement for TTDN1, indicating this tethering role as its major molecular function. Collectively, our findings unveil key functional connections between lariat processing, splicing outcomes, and NP-TTD molecular pathology.

biochemistry↗

bioRxiv2021

Nonsense Mediated RNA Decay Is a Unique Vulnerability of Cancer Cells with SF3B1 and U2AF1 Mutations

Nonsense-mediated RNA decay (NMD) is well recognized as an RNA surveillance pathway that targets aberrant mRNAs with premature translation termination codons (PTCs) for degradation; however, its molecular mechanisms and roles in health and disease remain incompletely understood. In this study, we developed a novel reporter system that can accurately measure NMD activity in individual cells. By carrying out a genome-wide CRISPR/Cas9 knockout screen using this reporter system, we identified novel NMD-promoting factors, including multiple components of the SF3B complex and other U2 spliceosome factors. Interestingly, we also found that cells with mutations in the U2 spliceosome genes SF3B1 and U2AF1--which are commonly found in myelodysplastic syndrome (MDS) and cancers--have overall attenuated NMD activity. Furthermore, we found that compared to wild type cells, SF3B1 and U2AF1 mutant cells are more sensitive to NMD inhibition, a phenotype that is accompanied by elevated DNA replication obstruction, DNA damage and chromosomal instability. Remarkably, the sensitivity of spliceosome mutant cells to NMD inhibition could be rescued by overexpression of RNase H1, which removes R-loops in the genome. Together, our findings shed new light on the functional interplay between NMD and RNA splicing and suggest a novel strategy for the treatment of MDS and cancers with spliceosome mutations.

cell biology↗

bioRxiv2020

U2AF1 is a haplo-essential gene required for cancer cell survival

Somatic mutations in the spliceosome gene U2AF1 are common in patients with myelodysplastic syndromes. U2AF1 mutations that code for the most common amino acid substitutions are always heterozygous, and the retained wild-type allele is expressed, suggesting that mutant hematopoietic cells may require the residual wild-type allele to be viable and cause disease. We show that hematopoiesis and RNA splicing in U2af1 heterozygous knock-out mice was similar to control mice, but that deletion of the wild-type allele in U2AF1(S34F) heterozygous mutant expressing hematopoietic cells (i.e., hemizygous mutant) was lethal. These results confirm that U2AF1 mutant hematopoietic cells are dependent on the expression of wild-type U2AF1 for survival in vivo and that U2AF1 is a haplo-essential cancer gene. Mutant U2AF1 (S34F) expressing cells were also more sensitive to reduced, but not absent, expression of wild-type U2AF1 than non-mutant cells. Furthermore, mice transplanted with leukemia cells expressing mutant U2AF1 had significantly reduced tumor burden and improved survival after the wild-type U2af1 allele was deleted compared to when it was not deleted. These results suggest that selectively targeting the wild-type U2AF1 allele in heterozygous mutant cells could induce cancer cell death and be a therapeutic strategy for patients harboring U2AF1 mutations.

cancer biology↗

bioRxiv2018

Mutation detection in thousands of acute myeloid leukemia cells using single cell RNA-sequencing

Virtually all tumors are genetically heterogeneous, containing subclonal populations of cells that are defined by distinct mutations1. Subclones can have unique phenotypes that influence disease progression2, but these phenotypes are difficult to characterize: subclones usually cannot be physically purified, and bulk gene expression measurements obscure interclonal differences. Single-cell RNA-sequencing has revealed transcriptional heterogeneity within a variety of tumor types, but it is unclear how this expression heterogeneity relates to subclonal genetic events - for example, whether particular expression clusters correspond to mutationally defined subclones3,4,5,6-9. To address this question, we developed an approach that integrates enhanced whole genome sequencing (eWGS) with the 10x Genomics Chromium Single Cell 5 Gene Expression workflow (scRNA-seq) to directly link expressed mutations with transcriptional profiles at single cell resolution. Using bone marrow samples from five cases of primary human Acute Myeloid Leukemia (AML), we generated WGS and scRNA-seq data for each case. Duplicate single cell libraries representing a median of 20,474 cells per case were generated from the bone marrow of each patient. Although the libraries were 5 biased, we detected expressed mutations in cDNAs at distances up to 10 kbp from the 5 ends of well-expressed genes, allowing us to identify hundreds to thousands of cells with AML-specific somatic mutations in every case. This data made it possible to distinguish AML cells (including normal-karyotype AML cells) from surrounding normal cells, to study tumor differentiation and intratumoral expression heterogeneity, to identify expression signatures associated with subclonal mutations, and to find cell surface markers that could be used to purify subclones for further study. The data also revealed transcriptional heterogeneity that occurred independently of subclonal mutations, suggesting that additional factors drive epigenetic heterogeneity. This integrative approach for connecting genotype to phenotype in AML cells is broadly applicable for analysis of any sample that is phenotypically and genetically heterogeneous.

cancer biology↗