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Deep Sequencing of Chicken microRNAs

BACKGROUND: The use of new, deep sequencing technologies has greatly accelerated microRNA discovery. We have applied this approach to the identification of chicken microRNAs and to the comparison of microRNAs in chicken embryo fibroblasts (CEF) infected with Marek's disease virus (MDV) to those...

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Autores principales: Burnside, Joan, Ouyang, Ming, Anderson, Amy, Bernberg, Erin, Lu, Cheng, Meyers, Blake C, Green, Pamela J, Markis, Milos, Isaacs, Grace, Huang, Emily, Morgan, Robin W
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2375912/
https://www.ncbi.nlm.nih.gov/pubmed/18430245
http://dx.doi.org/10.1186/1471-2164-9-185
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author Burnside, Joan
Ouyang, Ming
Anderson, Amy
Bernberg, Erin
Lu, Cheng
Meyers, Blake C
Green, Pamela J
Markis, Milos
Isaacs, Grace
Huang, Emily
Morgan, Robin W
author_facet Burnside, Joan
Ouyang, Ming
Anderson, Amy
Bernberg, Erin
Lu, Cheng
Meyers, Blake C
Green, Pamela J
Markis, Milos
Isaacs, Grace
Huang, Emily
Morgan, Robin W
author_sort Burnside, Joan
collection PubMed
description BACKGROUND: The use of new, deep sequencing technologies has greatly accelerated microRNA discovery. We have applied this approach to the identification of chicken microRNAs and to the comparison of microRNAs in chicken embryo fibroblasts (CEF) infected with Marek's disease virus (MDV) to those present in uninfected CEF. RESULTS: We obtained 125,463 high quality reads that showed an exact match to the chicken genome. The majority of the reads corresponded to previously annotated chicken microRNAs; however, the sequences of many potential novel microsRNAs were obtained. A comparison of the reads obtained in MDV-infected and uninfected CEF indicates that infection does not significantly perturb the expression profile of microRNAs. Frequently sequenced microRNAs include miR-221/222, which are thought to play a role in growth and proliferation. A number of microRNAs (e.g., let-7, miR-199a-1, 26a) are expressed at lower levels in MDV-induced tumors, highlighting the potential importance of this class of molecules in tumorigenesis. CONCLUSION: Deep sequencing technology is highly suited for small RNA discovery. This approach is independent of comparative sequence analysis, which has been the primary method used to identify chicken microRNAs. Our results have confirmed the expression of many microRNAs identified by sequence similarity and identified a pool of candidate novel microRNAs.
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spelling pubmed-23759122008-05-10 Deep Sequencing of Chicken microRNAs Burnside, Joan Ouyang, Ming Anderson, Amy Bernberg, Erin Lu, Cheng Meyers, Blake C Green, Pamela J Markis, Milos Isaacs, Grace Huang, Emily Morgan, Robin W BMC Genomics Research Article BACKGROUND: The use of new, deep sequencing technologies has greatly accelerated microRNA discovery. We have applied this approach to the identification of chicken microRNAs and to the comparison of microRNAs in chicken embryo fibroblasts (CEF) infected with Marek's disease virus (MDV) to those present in uninfected CEF. RESULTS: We obtained 125,463 high quality reads that showed an exact match to the chicken genome. The majority of the reads corresponded to previously annotated chicken microRNAs; however, the sequences of many potential novel microsRNAs were obtained. A comparison of the reads obtained in MDV-infected and uninfected CEF indicates that infection does not significantly perturb the expression profile of microRNAs. Frequently sequenced microRNAs include miR-221/222, which are thought to play a role in growth and proliferation. A number of microRNAs (e.g., let-7, miR-199a-1, 26a) are expressed at lower levels in MDV-induced tumors, highlighting the potential importance of this class of molecules in tumorigenesis. CONCLUSION: Deep sequencing technology is highly suited for small RNA discovery. This approach is independent of comparative sequence analysis, which has been the primary method used to identify chicken microRNAs. Our results have confirmed the expression of many microRNAs identified by sequence similarity and identified a pool of candidate novel microRNAs. BioMed Central 2008-04-22 /pmc/articles/PMC2375912/ /pubmed/18430245 http://dx.doi.org/10.1186/1471-2164-9-185 Text en Copyright © 2008 Burnside 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 Research Article
Burnside, Joan
Ouyang, Ming
Anderson, Amy
Bernberg, Erin
Lu, Cheng
Meyers, Blake C
Green, Pamela J
Markis, Milos
Isaacs, Grace
Huang, Emily
Morgan, Robin W
Deep Sequencing of Chicken microRNAs
title Deep Sequencing of Chicken microRNAs
title_full Deep Sequencing of Chicken microRNAs
title_fullStr Deep Sequencing of Chicken microRNAs
title_full_unstemmed Deep Sequencing of Chicken microRNAs
title_short Deep Sequencing of Chicken microRNAs
title_sort deep sequencing of chicken micrornas
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2375912/
https://www.ncbi.nlm.nih.gov/pubmed/18430245
http://dx.doi.org/10.1186/1471-2164-9-185
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