Genetic diversity,population structure,and linkage disequilibrium of elite and local apple accessions from Belgium using the IRSC array

The identification of molecular markers associated with economic and quality traits will help improve breeding for new apple (Malus × domestica Borkh.) cultivars. Tools such as the 8K apple SNP array developed by the RosBREED consortium allow for high-throughput genotyping of SNP polymorphisms within collections. However, genetic characterization and the identification of population stratification and kinship within germplasm collections is a fundamental prerequisite for identifying robust marker–trait associations. In this study, a collection of apple germplasm originally developed for plant architectural studies and consisting of both non-commercial/local and elite accessions was genotyped using the 8K apple SNP array to identify cryptic relationships between accessions, to analyze population structure and to calculate the linkage disequilibrium (LD). A total of nine pairs of synonyms and several triploids accessions were identified within the 130 accessions genotyped. In addition, most of the known parent-child relations were confirmed, and several putative, previously unknown parent-child relations were identified among the local accessions. No clear subgroups could be identified although some separation between local and elite accessions was evident. The study of LD showed a rapid decay in our collection, indicating that a larger number of SNPs is necessary to perform whole genome association mapping. Finally, an association mapping effort for architectural traits was carried out on a small number of accessions to estimate the feasibility of this approach.     

Detecting microRNA binding and siRNA off-target effects from expression data

Sylamer is a method for detecting microRNA target and small interfering RNA off-target signals in 3' untranslated regions from a ranked gene list, sorted from upregulated to downregulated, after a microRNA perturbation or RNA interference experiment. The output is a landscape plot that tracks occurrence biases using hypergeometric P-values for all words across the gene ranking. We demonstrated the utility, speed and accuracy of this approach on several datasets.     

Combining disease models to test for gene-environment interaction in nuclear families

It is useful to have robust gene-environment interaction tests that can utilize a variety of family structures in an efficient way. This article focuses on tests for gene-environment interaction in the presence of main genetic and environmental effects. The objective is to develop powerful tests that can combine trio data with parental genotypes and discordant sibships when parents' genotypes are missing. We first make a modest improvement on a method for discordant sibs (discordant on phenotype), but the approach does not allow one to use families when all offspring are affected, e.g., trios. We then make a modest improvement on a Mendelian transmission-based approach that is inefficient when discordant sibs are available, but can be applied to any nuclear family. Finally, we propose a hybrid approach that utilizes the most efficient method for a specific family type, then combines over families. We utilize this hybrid approach to analyze a chronic obstructive pulmonary disorder dataset to test for gene-environment interaction in the Serpine2 gene with smoking. The methods are freely available in the R package fbati.     

Whole organ, venation and epidermal cell morphological variations are correlated in the leaves of Arabidopsis mutants

Despite the large number of genes known to affect leaf shape or size, we still have a relatively poor understanding of how leaf morphology is established. For example, little is known about how cell division and cell expansion are controlled and coordinated within a growing leaf to eventually develop into a laminar organ of a definite size. To obtain a global perspective of the cellular basis of variations in leaf morphology at the organ, tissue and cell levels, we studied a collection of 111 non-allelic mutants with abnormally shaped and/or sized leaves, which broadly represent the mutational variations in Arabidopsis thaliana leaf morphology not associated with lethality. We used image-processing techniques on these mutants to quantify morphological parameters running the gamut from the palisade mesophyll and epidermal cells to the venation, whole leaf and rosette levels. We found positive correlations between epidermal cell size and leaf area, which is consistent with long-standing Avery's hypothesis that the epidermis drives leaf growth. In addition, venation parameters were positively correlated with leaf area, suggesting that leaf growth and vein patterning share some genetic controls. Positional cloning of the genes affected by the studied mutations will eventually establish functional links between genotypes, molecular functions, cellular parameters and leaf phenotypes.