48 research outputs found

    Mapping quantitative trait Loci associated with graft (In)compatibility in apricot (Prunus armeniaca L.)

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    Graft incompatibility (GI) between the most popular Prunus rootstocks and apricot cultivars is one of the major problems for rootstock usage and improvement. Failure in producing long-leaving healthy grafts greatly affects the range of available Prunus rootstocks for apricot cultivation. Despite recent advances related to the molecular mechanisms of a graft-union formation between rootstock and scion, information on genetic control of this trait in woody plants is essentially missing because of a lack of hybrid crosses, segregating for the trait. In this study, we have employed the next-generation sequencing technology to generate the single-nucleotide polymorphism (SNP) markers and construct parental linkage maps for an apricot F1 population “Moniqui (Mo)” × “Paviot (Pa)” segregating for ability to form successful grafts with universal Prunus rootstock “Marianna 2624”. To localize genomic regions associated with this trait, we genotyped 138 individuals from the “Mo × Pa” cross and constructed medium-saturated genetic maps. The female “Mo” and male “Pa” maps were composed of 557 and 501 SNPs and organized in eight linkage groups that covered 780.2 and 690.4 cM of genetic distance, respectively. Parental maps were aligned to the Prunus persica v2.0 genome and revealed a high colinearity with the Prunus reference map. Two-year phenotypic data for characters associated with unsuccessful grafting such as necrotic line (NL), bark and wood discontinuities (BD and WD), and an overall estimate of graft (in)compatibility (GI) were collected for mapping quantitative trait loci (QTLs) on both parental maps. On the map of the graft-compatible parent “Pa”, two genomic regions on LG5 (44.9–60.8 cM) and LG8 (33.2–39.2 cM) were associated with graft (in)compatibility characters at different significance level, depending on phenotypic dataset. Of these, the LG8 QTL interval was most consistent between the years and supported by two significant and two putative QTLs. To our best knowledge, this is the first report on QTLs for graft (in)compatibility in woody plants. Results of this work will provide a valuable genomic resource for apricot breeding programs and facilitate future efforts focused on candidate genes discovery for graft (in)compatibility in apricot and other Prunus species

    Grafting versus seed propagated apricot populations: two main gene pools in Tunisia evidenced by SSR markers and model-based Bayesian clustering

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    Apricot was introduced into the Mediterranean Basin from China and Asian mountains through the Middle-East and the Central Europe. Traditionally present in Tunisia, we were interested in accessing the origin of apricot species in the country, and in particular in the number and the location of its introductions. A set of 82 representative apricot accessions including 49 grafted cultivars and 33 seed propagated ‘Bargougs’ were genotyped using 24 microsatellite loci revealing a total of 135 alleles. The model-based Bayesian clustering analysis using both Structure and InStruct programs as well as the multivariate method revealed five distinct genetic clusters. The genetic differentiation among clusters showed that cluster 1, with only four cultivars, was the most differentiated from the four remaining genetic clusters, which constituted the largest part of the studied germplasm. According to their geographic origin, the five identified groups (north, centre, south, Gafsa oasis and other oases groups) enclosed a similar variation within group, with a low level of differentiation. Overall results highlighted the distinction of two apricot gene pools in Tunisia related to the different mode of propagation of the cultivars: grafted and seed propagated apricot, which enclosed a narrow genetic basis. Our findings support the assumption that grafting and seed propagated apricots shared the same origin

    Genome Physical Mapping of Polyploids: A BIBAC Physical Map of Cultivated Tetraploid Cotton, Gossypium hirsutum L

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    Polyploids account for approximately 70% of flowering plants, including many field, horticulture and forage crops. Cottons are a world-leading fiber and important oilseed crop, and a model species for study of plant polyploidization, cellulose biosynthesis and cell wall biogenesis. This study has addressed the concerns of physical mapping of polyploids with BACs and/or BIBACs by constructing a physical map of the tetraploid cotton, Gossypium hirsutum L. The physical map consists of 3,450 BIBAC contigs with an N50 contig size of 863 kb, collectively spanning 2,244 Mb. We sorted the map contigs according to their origin of subgenome, showing that we assembled physical maps for the A- and D-subgenomes of the tetraploid cotton, separately. We also identified the BIBACs in the map minimal tilling path, which consists of 15,277 clones. Moreover, we have marked the physical map with nearly 10,000 BIBAC ends (BESs), making one BES in approximately 250 kb. This physical map provides a line of evidence and a strategy for physical mapping of polyploids, and a platform for advanced research of the tetraploid cotton genome, particularly fine mapping and cloning the cotton agronomic genes and QTLs, and sequencing and assembling the cotton genome using the modern next-generation sequencing technology

    Additive QTLs on three chromosomes control flowering time in woodland strawberry (Fragaria vesca L.)

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    Flowering time is an important trait that affects survival, reproduction and yield in both wild and cultivated plants. Therefore, many studies have focused on the identification of flowering time quantitative trait locus (QTLs) in different crops, and molecular control of this trait has been extensively investigated in model species. Here we report the mapping of QTLs for flowering time and vegetative traits in a large woodland strawberry mapping population that was phenotyped both under field conditions and in a greenhouse after flower induction in the field. The greenhouse experiment revealed additive QTLs in three linkage groups (LG), two on both LG4 and LG7, and one on LG6 that explain about half of the flowering time variance in the population. Three of the QTLs were newly identified in this study, and one co-localized with the previously characterized FvTFL1 gene. An additional strong QTL corresponding to previously mapped PFRU was detected in both field and greenhouse experiments indicating that gene(s) in this locus can control the timing of flowering in different environments in addition to the duration of flowering and axillary bud differentiation to runners and branch crowns. Several putative flowering time genes were identified in these QTL regions that await functional validation. Our results indicate that a few major QTLs may control flowering time and axillary bud differentiation in strawberries. We suggest that the identification of causal genes in the diploid strawberry may enable fine tuning of flowering time and vegetative growth in the closely related octoploid cultivated strawberry.Peer reviewe

    A framework physical map for peach, a model Rosaceae species

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    A genome-wide framework physical map of peach was constructed using high-information content fingerprinting (HICF) and FPC software. The resulting HICF assembly contained 2,138 contigs composed of 15,655 clones (4.3× peach genome equivalents) from two complementary bacterial artificial chromosome libraries. The total physical length of all contigs is estimated at 303 Mb or 104.5% of the peach genome. The framework physical map is anchored on the Prunus genetic reference map and integrated with the peach transcriptome map. The physical length of anchored contigs is estimated at 45.0 Mb or 15.5% of the genome. Altogether, 2,636 markers, i.e., genetic markers, peach unigene expressed sequence tags, and gene-specific and overgo probes, were incorporated into the physical framework and supported the accuracy of contig assembly.This project was supported by the United States Department of Agriculture NRI Award # 2005-35300-15452.Peer reviewe

    A genetically anchored physical framework for Theobroma cacao cv. Matina 1-6

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    <p>Abstract</p> <p>Background</p> <p>The fermented dried seeds of <it>Theobroma cacao </it>(cacao tree) are the main ingredient in chocolate. World cocoa production was estimated to be 3 million tons in 2010 with an annual estimated average growth rate of 2.2%. The cacao bean production industry is currently under threat from a rise in fungal diseases including black pod, frosty pod, and witches' broom. In order to address these issues, genome-sequencing efforts have been initiated recently to facilitate identification of genetic markers and genes that could be utilized to accelerate the release of robust <it>T. cacao </it>cultivars. However, problems inherent with assembly and resolution of distal regions of complex eukaryotic genomes, such as gaps, chimeric joins, and unresolvable repeat-induced compressions, have been unavoidably encountered with the sequencing strategies selected.</p> <p>Results</p> <p>Here, we describe the construction of a BAC-based integrated genetic-physical map of the <it>T. cacao </it>cultivar Matina 1-6 which is designed to augment and enhance these sequencing efforts. Three BAC libraries, each comprised of 10× coverage, were constructed and fingerprinted. 230 genetic markers from a high-resolution genetic recombination map and 96 Arabidopsis-derived conserved ortholog set (COS) II markers were anchored using pooled overgo hybridization. A dense tile path consisting of 29,383 BACs was selected and end-sequenced. The physical map consists of 154 contigs and 4,268 singletons. Forty-nine contigs are genetically anchored and ordered to chromosomes for a total span of 307.2 Mbp. The unanchored contigs (105) span 67.4 Mbp and therefore the estimated genome size of <it>T. cacao </it>is 374.6 Mbp. A comparative analysis with <it>A. thaliana, V. vinifera</it>, and <it>P. trichocarpa </it>suggests that comparisons of the genome assemblies of these distantly related species could provide insights into genome structure, evolutionary history, conservation of functional sites, and improvements in physical map assembly. A comparison between the two <it>T. cacao </it>cultivars Matina 1-6 and Criollo indicates a high degree of collinearity in their genomes, yet rearrangements were also observed.</p> <p>Conclusions</p> <p>The results presented in this study are a stand-alone resource for functional exploitation and enhancement of <it>Theobroma cacao </it>but are also expected to complement and augment ongoing genome-sequencing efforts. This resource will serve as a template for refinement of the <it>T. cacao </it>genome through gap-filling, targeted re-sequencing, and resolution of repetitive DNA arrays.</p

    Identification of a major QTL for Xanthomonas arboricola pv. pruni resistance in apricot

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    Xanthomonas arboricola pv. pruni causes bacterial spot of stone fruit resulting in severe yield losses in apricot production systems. Present on all continents, the pathogen is regulated in Europe as a quarantine organism. Host resistance is an important component of integrated pest management; however, little work has been done describing resistance against X. arboricola pv. pruni. In this study, an apricot population derived from the cross “Harostar” × “Rouge de Mauves” was used to construct two parental genetic maps and to perform a quantitative trait locus analysis of resistance to X. arboricola pv. pruni. A population of 101 F1 individuals was inoculated twice for two consecutive years in a quarantine greenhouse with a mixture of bacterial strains, and disease incidence and resistance index data were collected. A major QTL for disease incidence and resistance index accounting respectively for 53 % (LOD score of 15.43) and 46 % (LOD score of 12.26) of the phenotypic variation was identified at the same position on linkage group 5 of “Rouge de Mauves.” Microsatellite marker UDAp-452 co-segregated with the resistance, and two flanking microsatellites, namely BPPCT037 and BPPCT038A, were identified. When dividing the population according to the alleles of UDAp-452, the subgroup with unfavorable allele had a disease incidence of 32.6 % whereas the group with favorable allele had a disease incidence of 21 %, leading to a reduction of 35.6 % in disease incidence. This study is a first step towards the marker-assisted breeding of new apricot varieties with an increased tolerance to X. arboricola pv. pruni

    Integrated physical, genetic and genome map of chickpea (Cicer arietinum L.)

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    Physical map of chickpea was developed for the reference chickpea genotype (ICC 4958) using bacterial artificial chromosome (BAC) libraries targeting 71,094 clones (~12× coverage). High information content fingerprinting (HICF) of these clones gave high-quality fingerprinting data for 67,483 clones, and 1,174 contigs comprising 46,112 clones and 3,256 singletons were defined. In brief, 574 Mb genome size was assembled in 1,174 contigs with an average of 0.49 Mb per contig and 3,256 singletons represent 407 Mb genome. The physical map was linked with two genetic maps with the help of 245 BAC-end sequence (BES)-derived simple sequence repeat (SSR) markers. This allowed locating some of the BACs in the vicinity of some important quantitative trait loci (QTLs) for drought tolerance and reistance to Fusarium wilt and Ascochyta blight. In addition, fingerprinted contig (FPC) assembly was also integrated with the draft genome sequence of chickpea. As a result, ~965 BACs including 163 minimum tilling path (MTP) clones could be mapped on eight pseudo-molecules of chickpea forming 491 hypothetical contigs representing 54,013,992 bp (~54 Mb) of the draft genome. Comprehensive analysis of markers in abiotic and biotic stress tolerance QTL regions led to identification of 654, 306 and 23 genes in drought tolerance “QTL-hotspot” region, Ascochyta blight resistance QTL region and Fusarium wilt resistance QTL region, respectively. Integrated physical, genetic and genome map should provide a foundation for cloning and isolation of QTLs/genes for molecular dissection of traits as well as markers for molecular breeding for chickpea improvement
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