The development of ISSR-derived SCAR markers around the Seasonal Flowering Locus (SFL) in fragaria vesca

Fragaria vesca is a short-lived perennial with a seasonal-flowering habit. Seasonality of flowering is widespread in the Rosaceae and is also found in the majority of temperate polycarpic perennials. Genetic analysis has shown that seasonal flowering is controlled by a single gene in F. vesca, the SEASONAL FLOWERING LOCUS (SFL). Here, we report progress towards the marker-assisted selection and positional cloning of SFL, in which three ISSR markers linked to SFL were converted to locus-specific sequence-characterized amplified region (SCAR1–SCAR3) markers to allow large-scale screening of mapping progenies. We believe this is the first study describing the development of SCAR markers from ISSR profiles. The work also provides useful insight into the nature of polymorphisms generated by the ISSR marker system. Our results indicate that the ISSR polymorphisms originally detected were probably caused by point mutations in the positions targeted by primer anchors (causing differential PCR failure), by indels within the amplicon (leading to variation in amplicon size) and by internal sequence differences (leading to variation in DNA folding and so in band mobility). The cause of the original ISSR polymorphism was important in the selection of appropriate strategies for SCAR-marker development. The SCAR markers produced were mapped using a F. vesca f. vesca × F. vesca f. semperflorens testcross population. Marker SCAR2 was inseparable from the SFL, whereas SCAR1 mapped 3.0 cM to the north of the gene and SCAR3 1.7 cM to its south.

PCR-based markers diagnostic for spring and winter seasonal growth habit in barley

Toward the ultimate goal of replacing field-based evaluation of seasonal growth habit, we describe the design and validation of a multiplex polymerase chain reaction assay diagnostic for allelic status at the barley (Hordeum vulgare ssp. vulgare L.) vernalization locus, VRN-H1 By assaying for the presence of all known insertion–deletion polymorphisms thought to be responsible for the difference between spring and winter alleles, this assay directly tests for the presence of functional polymorphism at VRN-H1 Four of the nine previously recognized VRN-H1 haplotypes (including both winter alleles) give unique profiles using this assay. The remaining five spring haplotypes share a single profile, indicative of function-altering deletions spanning, or adjacent to, the putative “vernalization critical” region of intron 1. When used in conjunction with a previously published PCR-based assay diagnostic for alleles at VRN-H2, it was possible to predict growth habit in all the 100 contemporary UK spring and winter lines analyzed in this study. This assay is likely to find application in instances when seasonal growth habit needs to be determined without the time and cost of phenotypic assessment and during marker-assisted selection using conventional and multicross population analysis.

Molecular barley breeding

Breeding progress in barley yield in the UK is being sustained at a rate in the order of 1% per annum against a background of declining seed sales. Commercial barley breeders are largely concentrating upon the elite local gene pool but with genotypic evidence suggesting that there is still considerable variation between current recommended cultivars, even those produced as half-sibs by the same breeder. Marker Assisted Selection (MAS) protocols could be substituted for conventional selection for a number of major-gene targets but, in the majority of cases, conventional selection is more resource efficient. Results from current QTL mapping studies have not yet identified sufficiently robust and validated targets for UK barley breeders to adopt MAS to assist in the selection of complex traits such as yield and malting quality. Results from multiple population mapping amongst the elite gene pool being utilised by breeders and from association studies of elite germplasm tested as part of the UK recommended list trial process do, however, show some promise.

Advanced feature selection methods in multinominal dementia classification from structural MRI data

Recent studies showed that features extracted from brain MRIs can well discriminate Alzheimer’s disease from Mild Cognitive Impairment. This study provides an algorithm that sequentially applies advanced feature selection methods for findings the best subset of features in terms of binary classification accuracy. The classifiers that provided the highest accuracies, have been then used for solving a multi-class problem by the one-versus-one strategy. Although several approaches based on Regions of Interest (ROIs) extraction exist, the prediction power of features has not yet investigated by comparing filter and wrapper techniques. The findings of this work suggest that (i) the IntraCranial Volume (ICV) normalization can lead to overfitting and worst the accuracy prediction of test set and (ii) the combined use of a Random Forest-based filter with a Support Vector Machines-based wrapper, improves accuracy of binary classification.