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Data-mining the FlyAtlas online resource to identify core functional motifs across transporting epithelia

BACKGROUND: Comparative analysis of tissue-specific transcriptomes is a powerful technique to uncover tissue functions. Our FlyAtlas.org provides authoritative gene expression levels for multiple tissues of Drosophila melanogaster (1). Although the main use of such resources is single gene lookup, t...

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Autores principales: Chintapalli, Venkateswara R, Wang, Jing, Herzyk, Pawel, Davies, Shireen A, Dow, Julian AT
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3734111/
https://www.ncbi.nlm.nih.gov/pubmed/23895496
http://dx.doi.org/10.1186/1471-2164-14-518
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author Chintapalli, Venkateswara R
Wang, Jing
Herzyk, Pawel
Davies, Shireen A
Dow, Julian AT
author_facet Chintapalli, Venkateswara R
Wang, Jing
Herzyk, Pawel
Davies, Shireen A
Dow, Julian AT
author_sort Chintapalli, Venkateswara R
collection PubMed
description BACKGROUND: Comparative analysis of tissue-specific transcriptomes is a powerful technique to uncover tissue functions. Our FlyAtlas.org provides authoritative gene expression levels for multiple tissues of Drosophila melanogaster (1). Although the main use of such resources is single gene lookup, there is the potential for powerful meta-analysis to address questions that could not easily be framed otherwise. Here, we illustrate the power of data-mining of FlyAtlas data by comparing epithelial transcriptomes to identify a core set of highly-expressed genes, across the four major epithelial tissues (salivary glands, Malpighian tubules, midgut and hindgut) of both adults and larvae. METHOD: Parallel hypothesis-led and hypothesis-free approaches were adopted to identify core genes that underpin insect epithelial function. In the former, gene lists were created from transport processes identified in the literature, and their expression profiles mapped from the flyatlas.org online dataset. In the latter, gene enrichment lists were prepared for each epithelium, and genes (both transport related and unrelated) consistently enriched in transporting epithelia identified. RESULTS: A key set of transport genes, comprising V-ATPases, cation exchangers, aquaporins, potassium and chloride channels, and carbonic anhydrase, was found to be highly enriched across the epithelial tissues, compared with the whole fly. Additionally, a further set of genes that had not been predicted to have epithelial roles, were co-expressed with the core transporters, extending our view of what makes a transporting epithelium work. Further insights were obtained by studying the genes uniquely overexpressed in each epithelium; for example, the salivary gland expresses lipases, the midgut organic solute transporters, the tubules specialize for purine metabolism and the hindgut overexpresses still unknown genes. CONCLUSION: Taken together, these data provide a unique insight into epithelial function in this key model insect, and a framework for comparison with other species. They also provide a methodology for function-led datamining of FlyAtlas.org and other multi-tissue expression datasets.
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spelling pubmed-37341112013-08-06 Data-mining the FlyAtlas online resource to identify core functional motifs across transporting epithelia Chintapalli, Venkateswara R Wang, Jing Herzyk, Pawel Davies, Shireen A Dow, Julian AT BMC Genomics Review BACKGROUND: Comparative analysis of tissue-specific transcriptomes is a powerful technique to uncover tissue functions. Our FlyAtlas.org provides authoritative gene expression levels for multiple tissues of Drosophila melanogaster (1). Although the main use of such resources is single gene lookup, there is the potential for powerful meta-analysis to address questions that could not easily be framed otherwise. Here, we illustrate the power of data-mining of FlyAtlas data by comparing epithelial transcriptomes to identify a core set of highly-expressed genes, across the four major epithelial tissues (salivary glands, Malpighian tubules, midgut and hindgut) of both adults and larvae. METHOD: Parallel hypothesis-led and hypothesis-free approaches were adopted to identify core genes that underpin insect epithelial function. In the former, gene lists were created from transport processes identified in the literature, and their expression profiles mapped from the flyatlas.org online dataset. In the latter, gene enrichment lists were prepared for each epithelium, and genes (both transport related and unrelated) consistently enriched in transporting epithelia identified. RESULTS: A key set of transport genes, comprising V-ATPases, cation exchangers, aquaporins, potassium and chloride channels, and carbonic anhydrase, was found to be highly enriched across the epithelial tissues, compared with the whole fly. Additionally, a further set of genes that had not been predicted to have epithelial roles, were co-expressed with the core transporters, extending our view of what makes a transporting epithelium work. Further insights were obtained by studying the genes uniquely overexpressed in each epithelium; for example, the salivary gland expresses lipases, the midgut organic solute transporters, the tubules specialize for purine metabolism and the hindgut overexpresses still unknown genes. CONCLUSION: Taken together, these data provide a unique insight into epithelial function in this key model insect, and a framework for comparison with other species. They also provide a methodology for function-led datamining of FlyAtlas.org and other multi-tissue expression datasets. BioMed Central 2013-07-30 /pmc/articles/PMC3734111/ /pubmed/23895496 http://dx.doi.org/10.1186/1471-2164-14-518 Text en Copyright © 2013 Chintapalli et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Chintapalli, Venkateswara R
Wang, Jing
Herzyk, Pawel
Davies, Shireen A
Dow, Julian AT
Data-mining the FlyAtlas online resource to identify core functional motifs across transporting epithelia
title Data-mining the FlyAtlas online resource to identify core functional motifs across transporting epithelia
title_full Data-mining the FlyAtlas online resource to identify core functional motifs across transporting epithelia
title_fullStr Data-mining the FlyAtlas online resource to identify core functional motifs across transporting epithelia
title_full_unstemmed Data-mining the FlyAtlas online resource to identify core functional motifs across transporting epithelia
title_short Data-mining the FlyAtlas online resource to identify core functional motifs across transporting epithelia
title_sort data-mining the flyatlas online resource to identify core functional motifs across transporting epithelia
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3734111/
https://www.ncbi.nlm.nih.gov/pubmed/23895496
http://dx.doi.org/10.1186/1471-2164-14-518
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