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Mathew, R. J.

Publications and source records attributed to Mathew, R. J..

3 recordsLinked to original sources

Developmental functions of rapgef1b in neural crest specification and presomitic mesoderm patterning

RAPGEF1, a guanine nucleotide exchange factor, regulates signaling and cytoskeletal dynamics in mammalian cells, yet its role in development remains unclear as Rapgef1 null mouse embryos do not survive beyond implantation. We demonstrate that zebrafish rapgef1 is maternally expressed, and its paralogs, rapgef1a and rapgef1b, exhibit tissue and developmental stage-specific splicing. Disruption of rapgef1b caused brain and somite defects, impaired cranial neural crest specification, and microcephaly-like phenotypes, uncovering its previously uncharacterized functions in morphogenesis and tissue patterning. Transcriptomic analyses and differential gene expression provide fresh insights into the developmental functions of rapgef1b in presomitic mesoderm and somitogenesis by modulating the Wnt/{beta} catenin signaling. Rapgef1b deficient embryos also showed spindle pole disorganization and chromosome mis-congression, linking Rapgef1 to centrosome-mediated mitotic fidelity. Together, our findings identify Rapgef1b as a key regulator of neural crest development, mesodermal morphogenesis, and early mitoses, highlighting its tissue-specific functions during vertebrate embryogenesis. TeaserIn this study, we show that rapgef1b is essential for shaping the embryonic brain, somites, and body axis by regulating gene expression, cell division, survival, and differentiation. Our findings reveal a new dimension of signaling-mediated cell fate specification during early vertebrate development.

developmental biology↗

Comprehensive benchmarking of tools for nanopore-based detection of DNA methylation

Long read sequencing technologies such as Oxford Nanopore (ONT) offer direct, simultaneous detection of DNA base modifications. The recent migration of ONT to the upgraded R10 chemistry has spurred the development of diverse methylation detection models. However, their performance and accuracy remain unclear. Here, leveraging diverse bacterial, plant, and mammalian datasets, we systematically evaluate the current landscape of tools and models for studying DNA methylation using nanopore sequencing. Our results demonstrate that the older models remain the best choice for studying CpG methylation. We note substantial improvement of newer tools in identifying 5-methylcytosine in non-CG contexts, 6-methyladenine, and 4-methylcytosine. We highlight the sensitivity of various tools to confounding methylation nearby. We also assess the computational performance of various tools, and effects of sequencing depth, methylation abundance, read quality, and basecalling mode. Our reusable pipelines and fully open access datasets provide a framework of resources to empower future benchmarking efforts. Our work thus details the strengths and limitations of the state-of-the-art methylation models and outlines practical guidelines for researchers using nanopore sequencing to study DNA modifications.

genomics↗

NEMO: Improved and accurate models for identification of 6mA using Nanopore sequencing

DNA methylation plays a key role in epigenetic regulation across lifeforms. Nanopore sequencing enables direct detection of base modifications. While multiple tools are currently available for studying 5-methylcytosine (5mC), there is a paucity of models that can detect 6-methyladenine (6mA) from raw nanopore data. Leveraging the motif-driven nature of bacterial methylation systems, we generated 6mA identification models that vastly surpass the accuracy of the current best model. Our work enables the study of 6mA at a single-base resolution in new as well as existing nanopore datasets.

genomics↗