Email updates

Keep up to date with the latest news and content from BMC Genomics and BioMed Central.

Open Access Research article

Mapping in an apple (Malus x domestica) F1 segregating population based on physical clustering of differentially expressed genes

Philip J Jensen1, Gennaro Fazio2, Naomi Altman3, Craig Praul4 and Timothy W McNellis1*

Author Affiliations

1 Department of Plant Pathology & Environmental Microbiology, 211 Buckhout Laboratory, The Pennsylvania State University, 16802 University Park, PA, USA

2 United States Department of Agriculture, Agricultural Research Service, Plant Genetics Resources Unit, 630 W. North St., 14456 Geneva, NY, USA

3 Department of Statistics, 323 Thomas Building, The Pennsylvania State University, 16802 University Park, PA, USA

4 Genomics Core Facility, Huck Institutes of the Life Sciences, 412 Chandlee Laboratory, The Pennsylvania State University, 16802, University Park, PA, USA

For all author emails, please log on.

BMC Genomics 2014, 15:261  doi:10.1186/1471-2164-15-261

Published: 4 April 2014

Abstract

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 F1 breeding population, including resistance to powdery mildew (Podosphaera leucotricha) disease and woolly apple aphid (Eriosoma lanigerum).

Results

Transcription profiling was performed for 48 individual F1 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 F1 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.

Keywords:
Powdery mildew disease; Woolly apple aphid; Gene expression marker; DNA microarray; Genetic marker development; Quantitative PCR