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Khan M.A.,Urbana University | Han Y.,CAS Wuhan Botanical Garden | Zhao Y.F.,Urbana University | Troggio M.,Istituto Agrario San Michele allAdige Research and Innovation Center | Korban S.S.,Urbana University
PLoS ONE | Year: 2012

Genetic maps serve as frameworks for determining the genetic architecture of quantitative traits, assessing structure of a genome, as well as aid in pursuing association mapping and comparative genetic studies. In this study, a dense genetic map was constructed using a high-throughput 1,536 EST-derived SNP GoldenGate genotyping platform and a global consensus map established by combining the new genetic map with four existing reliable genetic maps of apple. The consensus map identified markers with both major and minor conflicts in positioning across all five maps. These major inconsistencies among marker positions were attributed either to structural variations within the apple genome, or among mapping populations, or genotyping technical errors. These also highlighted problems in assembly and anchorage of the reference draft apple genome sequence in regions with known segmental duplications. Markers common across all five apple genetic maps resulted in successful positioning of 2875 markers, consisting of 2033 SNPs and 843 SSRs as well as other specific markers, on the global consensus map. These markers were distributed across all 17 linkage groups, with an average of 169±33 marker per linkage group and with an average distance of 0.70±0.14 cM between markers. The total length of the consensus map was 1991.38 cM with an average length of 117.14±24.43 cM per linkage group. A total of 569 SNPs were mapped onto the genetic map, consisting of 140 recombinant individuals, from our recently developed apple Oligonucleotide pool assays (OPA). The new functional SNPs, along with the dense consensus genetic map, will be useful for high resolution QTL mapping of important traits in apple and for pursuing comparative genetic studies in Rosaceae. © 2012 Khan et al. Source


Chagne D.,The New Zealand Institute for Plant and Food Research Ltd | Crowhurst R.N.,Mount Albert Research Center | Pindo M.,Istituto Agrario San Michele allAdige Research and Innovation Center | Thrimawithana A.,Mount Albert Research Center | And 39 more authors.
PLoS ONE | Year: 2014

We present a draft assembly of the genome of European pear (Pyrus communis) 'Bartlett'. Our assembly was developed employing second generation sequencing technology (Roche 454), from single-end, 2 kb, and 7 kb insert paired-end reads using Newbler (version 2.7). It contains 142,083 scaffolds greater than 499 bases (maximum scaffold length of 1.2 Mb) and covers a total of 577.3 Mb, representing most of the expected 600 Mb Pyrus genome. A total of 829,823 putative single nucleotide polymorphisms (SNPs) were detected using re-sequencing of 'Louise Bonne de Jersey' and 'Old Home'. A total of 2,279 genetically mapped SNP markers anchor 171 Mb of the assembled genome. Ab initio gene prediction combined with prediction based on homology searching detected 43,419 putative gene models. Of these, 1219 proteins (556 clusters) are unique to European pear compared to 12 other sequenced plant genomes. Analysis of the expansin gene family provided an example of the quality of the gene prediction and an insight into the relationships among one class of cell wall related genes that control fruit softening in both European pear and apple (Malusxdomestica). The 'Bartlett' genome assembly v1.0 (http://www.rosaceae.org/species/pyrus/ pyrus-communis/genome-v1.0) is an invaluable tool for identifying the genetic control of key horticultural traits in pear and will enable the wide application of marker-assisted and genomic selection that will enhance the speed and efficiency of pear cultivar development. © 2014 Chagné et al. Source


Radivojac P.,Indiana University Bloomington | Clark W.T.,Indiana University Bloomington | Oron T.R.,Buck Institute for Research on Aging | Schnoes A.M.,University of California at San Francisco | And 107 more authors.
Nature Methods | Year: 2013

Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. Two findings stand out: (i) today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools. © 2013 Nature America, Inc. All rights reserved. Source


Khan S.A.,Wageningen University | Chibon P.-Y.,Wageningen University | De Vos R.C.H.,Wageningen University | De Vos R.C.H.,Netherlands Metabolomics Center | And 16 more authors.
Journal of Experimental Botany | Year: 2012

Apple (Malus×domestica Borkh) is among the main sources of phenolic compounds in the human diet. The genetic basis of the quantitative variations of these potentially beneficial phenolic compounds was investigated. A segregating F1 population was used to map metabolite quantitative trait loci (mQTLs). Untargeted metabolic profiling of peel and flesh tissues of ripe fruits was performed using liquid chromatography-mass spectrometry (LC-MS), resulting in the detection of 418 metabolites in peel and 254 in flesh. In mQTL mapping using MetaNetwork, 669 significant mQTLs were detected: 488 in the peel and 181 in the flesh. Four linkage groups (LGs), LG1, LG8, LG13, and LG16, were found to contain mQTL hotspots, mainly regulating metabolites that belong to the phenylpropanoid pathway. The genetics of annotated metabolites was studied in more detail using MapQTL®. A number of quercetin conjugates had mQTLs on LG1 or LG13. The most important mQTL hotspot with the largest number of metabolites was detected on LG16: mQTLs for 33 peel-related and 17 flesh-related phenolic compounds. Structural genes involved in the phenylpropanoid biosynthetic pathway were located, using the apple genome sequence. The structural gene leucoanthocyanidin reductase (LAR1) was in the mQTL hotspot on LG16, as were seven transcription factor genes. The authors believe that this is the first time that a QTL analysis was performed on such a high number of metabolites in an outbreeding plant species. © 2012 The Author. Source


Moreira F.M.,Istituto Agrario San Michele allAdige Research and Innovation Center | Madini A.,Istituto Agrario San Michele allAdige Research and Innovation Center | Madini A.,Resnova S.r.l. | Marino R.,Istituto Agrario San Michele allAdige Research and Innovation Center | And 6 more authors.
Tree Genetics and Genomes | Year: 2011

Two populations (Pop) segregating quantitatively for resistance to downy mildew (DM), caused by Plasmopara viticola, were used to construct genetic maps and to carry out quantitative trait locus (QTL) analysis. Pop1 comprised of 174 F1 individuals from a cross of 'Moscato Bianco', a susceptible Vitis vinifera cultivar, and a resistant individual of Vitis riparia. Pop2 consisted of 94 progeny from a cross of two interspecific hybrids, 'VRH3082 1-42' and 'SK77 5/3', with resistance traits inherited from Vitis rotundifolia and Vitis amurensis, respectively. Resistance of progeny was measured in field and greenhouse conditions by visual evaluation of disease symptoms on leaves. Linkage maps of 1037.2 and 651 cM were built essentially with simple sequence repeat markers and were enriched with gene-derived single-strand conformational polymorphism and single-nucleotide polymorphism markers. Simple interval mapping and Kruskall-Wallis analysis detected a stable QTL involved in field resistance to DM on linkage group (LG) 7 of the Pop1 integrated map co-localized with a putative Caffeoyl-CoA O-methyltransferase-derived marker. Additional QTLs were detected on LGs 8, 12 and 17. We were able to identify genetic factors correlated with resistance to P. viticola with lower statistical significance on LGs 1, 6 and 7 of the Pop2 map. Finally, no common QTLs were found between the two crosses analyzed. A search of the grapevine genome sequence revealed either homologues to non-host-, host- or defense-signalling genes within the QTL intervals. These positional candidate genes may provide new information about chromosomal regions hosting phenotypic loci. © 2010 Springer-Verlag. Source

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