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Mapping in an apple (Malus x domestica) F(1) segregating population based on physical clustering of differentially expressed genes

BACKGROUND: Apple tree breeding is slow and difficult due to long generation times, self-incompatibility, and complex genetics. The identification of molecular markers linked to traits of interest is a way to expedite the breeding process. In the present study, we aimed to identify genes whose stead...

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Autores principales: Jensen, Philip J, Fazio, Gennaro, Altman, Naomi, Praul, Craig, McNellis, Timothy W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4051173/
https://www.ncbi.nlm.nih.gov/pubmed/24708064
http://dx.doi.org/10.1186/1471-2164-15-261
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author Jensen, Philip J
Fazio, Gennaro
Altman, Naomi
Praul, Craig
McNellis, Timothy W
author_facet Jensen, Philip J
Fazio, Gennaro
Altman, Naomi
Praul, Craig
McNellis, Timothy W
author_sort Jensen, Philip J
collection PubMed
description BACKGROUND: Apple tree breeding is slow and difficult due to long generation times, self-incompatibility, and complex genetics. The identification of molecular markers linked to traits of interest is a way to expedite the breeding process. In the present study, we aimed to identify genes whose steady-state transcript abundance was associated with inheritance of specific traits segregating in an apple (Malus × domestica) rootstock F(1) breeding population, including resistance to powdery mildew (Podosphaera leucotricha) disease and woolly apple aphid (Eriosoma lanigerum). RESULTS: Transcription profiling was performed for 48 individual F(1) apple trees from a cross of two highly heterozygous parents, using RNA isolated from healthy, actively-growing shoot tips and a custom apple DNA oligonucleotide microarray representing 26,000 unique transcripts. Genome-wide expression profiles were not clear indicators of powdery mildew or woolly apple aphid resistance phenotype. However, standard differential gene expression analysis between phenotypic groups of trees revealed relatively small sets of genes with trait-associated expression levels. For example, thirty genes were identified that were differentially expressed between trees resistant and susceptible to powdery mildew. Interestingly, the genes encoding twenty-four of these transcripts were physically clustered on chromosome 12. Similarly, seven genes were identified that were differentially expressed between trees resistant and susceptible to woolly apple aphid, and the genes encoding five of these transcripts were also clustered, this time on chromosome 17. In each case, the gene clusters were in the vicinity of previously identified major quantitative trait loci for the corresponding trait. Similar results were obtained for a series of molecular traits. Several of the differentially expressed genes were used to develop DNA polymorphism markers linked to powdery mildew disease and woolly apple aphid resistance. CONCLUSIONS: Gene expression profiling and trait-associated transcript analysis using an apple F(1) population readily identified genes physically linked to powdery mildew disease resistance and woolly apple aphid resistance loci. This result was especially useful in apple, where extreme levels of heterozygosity make the development of reliable DNA markers quite difficult. The results suggest that this approach could prove effective in crops with complicated genetics, or for which few genomic information resources are available.
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spelling pubmed-40511732014-06-17 Mapping in an apple (Malus x domestica) F(1) segregating population based on physical clustering of differentially expressed genes Jensen, Philip J Fazio, Gennaro Altman, Naomi Praul, Craig McNellis, Timothy W BMC Genomics Research Article BACKGROUND: Apple tree breeding is slow and difficult due to long generation times, self-incompatibility, and complex genetics. The identification of molecular markers linked to traits of interest is a way to expedite the breeding process. In the present study, we aimed to identify genes whose steady-state transcript abundance was associated with inheritance of specific traits segregating in an apple (Malus × domestica) rootstock F(1) breeding population, including resistance to powdery mildew (Podosphaera leucotricha) disease and woolly apple aphid (Eriosoma lanigerum). RESULTS: Transcription profiling was performed for 48 individual F(1) apple trees from a cross of two highly heterozygous parents, using RNA isolated from healthy, actively-growing shoot tips and a custom apple DNA oligonucleotide microarray representing 26,000 unique transcripts. Genome-wide expression profiles were not clear indicators of powdery mildew or woolly apple aphid resistance phenotype. However, standard differential gene expression analysis between phenotypic groups of trees revealed relatively small sets of genes with trait-associated expression levels. For example, thirty genes were identified that were differentially expressed between trees resistant and susceptible to powdery mildew. Interestingly, the genes encoding twenty-four of these transcripts were physically clustered on chromosome 12. Similarly, seven genes were identified that were differentially expressed between trees resistant and susceptible to woolly apple aphid, and the genes encoding five of these transcripts were also clustered, this time on chromosome 17. In each case, the gene clusters were in the vicinity of previously identified major quantitative trait loci for the corresponding trait. Similar results were obtained for a series of molecular traits. Several of the differentially expressed genes were used to develop DNA polymorphism markers linked to powdery mildew disease and woolly apple aphid resistance. CONCLUSIONS: Gene expression profiling and trait-associated transcript analysis using an apple F(1) population readily identified genes physically linked to powdery mildew disease resistance and woolly apple aphid resistance loci. This result was especially useful in apple, where extreme levels of heterozygosity make the development of reliable DNA markers quite difficult. The results suggest that this approach could prove effective in crops with complicated genetics, or for which few genomic information resources are available. BioMed Central 2014-04-04 /pmc/articles/PMC4051173/ /pubmed/24708064 http://dx.doi.org/10.1186/1471-2164-15-261 Text en Copyright © 2014 Jensen 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 credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Jensen, Philip J
Fazio, Gennaro
Altman, Naomi
Praul, Craig
McNellis, Timothy W
Mapping in an apple (Malus x domestica) F(1) segregating population based on physical clustering of differentially expressed genes
title Mapping in an apple (Malus x domestica) F(1) segregating population based on physical clustering of differentially expressed genes
title_full Mapping in an apple (Malus x domestica) F(1) segregating population based on physical clustering of differentially expressed genes
title_fullStr Mapping in an apple (Malus x domestica) F(1) segregating population based on physical clustering of differentially expressed genes
title_full_unstemmed Mapping in an apple (Malus x domestica) F(1) segregating population based on physical clustering of differentially expressed genes
title_short Mapping in an apple (Malus x domestica) F(1) segregating population based on physical clustering of differentially expressed genes
title_sort mapping in an apple (malus x domestica) f(1) segregating population based on physical clustering of differentially expressed genes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4051173/
https://www.ncbi.nlm.nih.gov/pubmed/24708064
http://dx.doi.org/10.1186/1471-2164-15-261
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