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Title:   Author  item
                                            JENSEN, PHILIP - Pennsylvania State Universityitem
                                            Fazio, Gennaroitem
                                            ALTMAN, NAOMI - Pennsylvania State Universityitem
                                            CRAIG, PRAUL - Pennsylvania State Universityitem
                                            MCNELLIS, TIMOTHY - Pennsylvania State University
  Submitted to: BMC Genomics
                                    Publication Type: Peer Reviewed Journal
                                    Publication Acceptance Date: 2/19/2014
                                    Publication  Date: 4/4/2014
                                    Citation: Jensen, P., Fazio, G., Altman, N., Craig, P., Mcnellis, T. 2014. Mapping in an apple (Malus x domestica) F1 segregating population based on physical clustering of differentially expressed genes. Biomed Central (BMC) Genomics. 15:261.Interpretive Summary: Apple tree breeding is a slow and difficult process.  The identification and implementation of molecular markers linked to important traits can speed up the process and make it more efficient.  In this research we describe a method that leverages steady state gene expression differences between groups of progeny that differ in disease or insect resistance to identify genomic regions that harbor useful polymorphisms for marker development and implementation.
                                Technical 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.


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