Accurate genome-wide predictions of spatio-temporal gene expression during embryonic development.
In: PLoS Genetics, Jg. 15 (2019-09-25), Heft 9, S. 1-20
Online
academicJournal
Zugriff:
Comprehensive information on the timing and location of gene expression is fundamental to our understanding of embryonic development and tissue formation. While high-throughput in situ hybridization projects provide invaluable information about developmental gene expression patterns for model organisms like Drosophila, the output of these experiments is primarily qualitative, and a high proportion of protein coding genes and most non-coding genes lack any annotation. Accurate data-centric predictions of spatio-temporal gene expression will therefore complement current in situ hybridization efforts. Here, we applied a machine learning approach by training models on all public gene expression and chromatin data, even from whole-organism experiments, to provide genome-wide, quantitative spatio-temporal predictions for all genes. We developed structured in silico nano-dissection, a computational approach that predicts gene expression in >200 tissue-developmental stages. The algorithm integrates expression signals from a compendium of 6,378 genome-wide expression and chromatin profiling experiments in a cell lineage-aware fashion. We systematically evaluated our performance via cross-validation and experimentally confirmed 22 new predictions for four different embryonic tissues. The model also predicts complex, multi-tissue expression and developmental regulation with high accuracy. We further show the potential of applying these genome-wide predictions to extract tissue specificity signals from non-tissue-dissected experiments, and to prioritize tissues and stages for disease modeling. This resource, together with the exploratory tools are freely available at our webserver , which provides a valuable tool for a range of applications, from predicting spatio-temporal expression patterns to recognizing tissue signatures from differential gene expression profiles. [ABSTRACT FROM AUTHOR]
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Accurate genome-wide predictions of spatio-temporal gene expression during embryonic development.
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Autor/in / Beteiligte Person: | Zhou, Jian ; Schor, Ignacio E. ; Yao, Victoria ; Theesfeld, Chandra L. ; Marco-Ferreres, Raquel ; Tadych, Alicja ; Furlong, Eileen E. M. ; Troyanskaya, Olga G. |
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Zeitschrift: | PLoS Genetics, Jg. 15 (2019-09-25), Heft 9, S. 1-20 |
Veröffentlichung: | 2019 |
Medientyp: | academicJournal |
ISSN: | 1553-7390 (print) |
DOI: | 10.1371/journal.pgen.1008382 |
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