H2020Индивидуална стипендия2016–2018

MoDATS · Model-based Data Analysis of Transcription and Splicing

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2016-01-05 → 2018-01-19
Финансиране от ЕС: 195 455 €
Участници: 1
Схема: MSCA-IF-EF-ST

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Накратко на български

Процесите на транскрипция и сплайсинг анализират как ДНК се превръща в протеини чрез посредничеството на РНК. Разбирането на тези механизми помага при лечението на болести, биоинженерството и обработката на биологични данни.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Model-based Data Analysis of Transcription and Splicing

Gene expression is the fundamental process that in all cells produces functional protein from a genomic DNA template using a messenger RNA intermediate. We used computational tools applied to large datasets of gene expression to understand how several steps of gene expression are co-ordinated. This is important because understanding the basic workings of cells is curcial for treating disease and also for bio-engineering. It’s also important because we are developing computational approaches that help other biologists better understand their data.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

Gene expression is the fundamental process that in all cells produces functional protein from a genomic DNA template using a messenger RNA (mRNA) intermediate. Eukaryotic gene expression involves transcription--the polymerization of mRNA--and splicing--the removal of non-coding regions from the mRNA. Recent evidence shows that nascent mRNAs are spliced while still being transcribed, not after completion of transcription, and that splicing machinery regulates transcription. This cross-talk complicates understanding of gene expression, as its mechanism and consequences are not understood. This project proposes using model-based data analysis, applied to multiple types of data, to study the kinetics of coupled transcription and splicing. Model-based data analysis is a statistical framework in which models are formulated as probability distributions encoding the stochastic interactions between components, including observed data. Knowledge of the underlying mechanism--here, biological--is used to quantify both the phenomenon, and the uncertainty resulting from partial knowledge and noisy observations. The need for such analysis is acute in modern biology: decades of molecular biology have yielded detailed information on specific molecules and pathways, and now next-generation sequencing (NGS) allows scientists to collect gigabytes of data on thousands of distinct molecules simultaneously. Yet, integrating these approaches is challenging: biologists struggle to analyze NGS data in ways that give insight into known--and previously unknown--biological mechanisms.Here, the model-based data analysis paradigm will be used to interrogate the interplay of transcription and splicing, using state-of the art data including time-resolved NGS measurements of RNA processing. Working with experimentalists, we will quantify the kinetics of splicing in constitutive genes by labeling nascent transcripts, and estimate the effect of splicing on polymerase elongation genome-wide.

Оригинален текст от CORDIS (на английски).

Участници

THE UNIVERSITY OF EDINBURGH · EdinburghКоординаторОбединеното кралство