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Miten Jain

Publications and source records attributed to Miten Jain.

4 recordsLinked to original sources
PubMed2026

Characterization of METTL3/14-mediated m6A modification in human transcriptome using Nanopore direct RNA sequencing.

Post-transcriptional RNA modifications modulate diverse aspects of RNA metabolism. N6-methyladenosine (m6A), one of the most abundant internal RNA modifications, is deposited by the core methyltransferase complex, METTL3 and METTL14. Oxford Nanopore Technologies (ONT) platform permits direct, single RNA molecule sequencing while preserving native modifications. However, without rigorous benchmarking, the accuracy and reproducibility of modification detection remain uncertain. Here, we leveraged ONT to comprehensively profile bona fide m6A modifications in cellular RNAs at single-nucleotide resolution by integrating two direct RNA sequencing chemistries (RNA002 and RNA004) with the m6Anet and Dorado modification-detection models. We independently depleted METTL3 and METTL14 in human cells and rigorously validated modification calls through several assays and independent orthogonal methods (GLORI and miCLIP). We find that Dorado detected a higher number of m6A events and enabled simultaneous detection of other RNA modifications (5-methylcytosine, pseudouridine, and inosine). Pairing Dorado with an in vitro transcribed, unmodified control under stringent filtering, we provide compelling evidence supporting a global reduction in m6A sites and stoichiometry within coding sequences and across genes, particularly in highly modified genes and sites, and at consensus DRACH motifs. We report a differential and complex regulation of modified transcripts, accompanied by a global reduction in poly(A) tail length. Notably, METTL3 and METTL14 depletion produced distinct transcript-specific effects, supporting non-redundant roles within the m6A writer complex. Together, our study illustrates a notable advancement of ONT capabilities and establishes a robust transcriptome-wide framework for RNA modification detection, thereby laying the groundwork for exploring the contribution of METTL3/METTL14 to cellular functions and disease.

Humans↗
PubMed2025

Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair.

The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from seventeen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, Hi-C, and karyotyping. These data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic variants. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology.

Humans↗
PubMed2025

Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair.

The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first to be explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from seventeen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, and Hi-C, and karyotyping. In future publications, these data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic mutations. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology.

Journal Article↗