Identification and mapping of quantitative trait loci for leaf rust resistance derived from a tetraploid wheat Triticum dicoccum accession

Desiderio, Francesca; Guerra, Davide; Rubiales, Diego; Piarulli, Luciana; Pasquini, Marina; Mastrangelo, Anna Maria; Simeone, Rosanna; Blanco, A.; Cattivelli, Luigi; Valè, Giampiero

doi:10.1007/s11032-014-0186-0

Cited by 17 publications

(16 citation statements)

References 95 publications

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“…In addition to CS × CS5A, nine different maps contributed markers for the construction of the neighbor map. The Lt × MG 90K map (Desiderio et al, 2014) and the consensus map from Wang et al (2014) provided the most important contribution in terms of number of markers. Indeed, approximately 55 and 66% of markers located on these two maps, respectively, were successfully positioned in the neighbor map framework (Supplemental Table S4).…”

Section: Resultsmentioning

confidence: 99%

“…A neighbor mapping approach was undertaken to achieve a densely covered map for an efficient anchoring of the physical map according to the method introduced by Cone et al (2002). The neighbor maps, one for each chromosome arm, were produced integrating the CS × CS5A framework map (Gadaleta et al, 2014) with maps from the following sources: (i) an SSR‐based consensus map developed from four maps (‘Synthetic’ × ‘Opata’, ‘RL4452’ × ‘AC Domain’, ‘Wuhan #1’ × ‘Maringa’, and ‘Superb’ × ‘BW278’; Somers et al, 2004); (ii) six maps developed from biparental populations: ‘Nanda2419’ × ‘Wangshuibai’ (Xue et al, 2008), CS × Re, DV × G3 (both developed in this work), and a Lt × MG map made using the Illumina Infinium 90K SNP array (Desiderio et al, 2014), and (iii) the 90K_SNP‐based consensus map obtained from eight doubled‐haploid populations published by Wang et al (2014).…”

Section: Methodsmentioning

confidence: 99%

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Physical Mapping of Bread Wheat Chromosome 5A: An Integrated Approach

Barabaschi¹,

Magni

Volante³

et al. 2015

The Plant Genome

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The huge size, redundancy, and highly repetitive nature of the bread wheat [Triticum aestivum (L.)] genome, makes it among the most difficult species to be sequenced. To overcome these limitations, a strategy based on the separation of individual chromosomes or chromosome arms and the subsequent production of physical maps was established within the frame of the International Wheat Genome Sequence Consortium (IWGSC). A total of 95,812 bacterial artificial chromosome (BAC) clones of short-arm chromosome 5A (5AS) and longarm chromosome 5A (5AL) arm-specific BAC libraries were fingerprinted and assembled into contigs by complementary analytical approaches based on the FingerPrinted Contig (FPC) and Linear Topological Contig (LTC) tools. Combined anchoring approaches based on polymerase chain reaction (PCR) marker screening, microarray, and sequence homology searches applied to several genomic tools (i.e., genetic maps, deletion bin map, neighbor maps, BAC end sequences (BESs), genome zipper, and chromosome survey sequences) allowed the development of a high-quality physical map with an anchored physical coverage of 75% for 5AS and 53% for 5AL with high portions (64 and 48%, respectively) of contigs ordered along the chromosome. In the genome of grasses, Brachypodium [Brachypodium distachyon (L.) Beauv.], rice (Oryza sativa L.), and sorghum [Sorghum bicolor (L.) Moench] homologs of genes on wheat chromosome 5A were separated into syntenic blocks on different chromosomes as a result of translocations and inversions during evolution. The physical map presented represents an essential resource for fine genetic mapping and map-based cloning of agronomically relevant traits and a reference for the 5A sequencing projects.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Physical Mapping of Bread Wheat Chromosome 5A: An Integrated Approach

Barabaschi¹,

Magni

Volante³

et al. 2015

The Plant Genome

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“…However, many earlier studies are based on SSRs or DArT markers. Therefore, the genetic maps which contain both SSRs and SNPs from Infinium 9K or 90K assays [29, 30, 41] or SSRs and DArT markers were used as a bridge to compare the locations of QTL identified in this study with earlier reported studies. If needed, the information about SSR markers (closely mapped to the QTL associated SSRs) was also obtained from GrainGenes website (http://wheat.pw.usda.gov/cgi-bin/graingenes/browse.cgi?class=marker).…”

Section: Methodsmentioning

confidence: 99%

Genome wide genetic dissection of wheat quality and yield related traits and their relationship with grain shape and size traits in an elite × non-adapted bread wheat cross

Kumar¹,

Mantovani²,

Şimşek³

et al. 2019

PLoS ONE

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The genetic gain in yield and quality are two major targets of wheat breeding programs around the world. In this study, a high density genetic map consisting of 10,172 SNP markers identified a total of 43 genomic regions associated with three quality traits, three yield traits and two agronomic traits in hard red spring wheat (HRSW). When compared with six grain shape and size traits, the quality traits showed mostly independent genetic control (~18% common loci), while the yield traits showed moderate association (~53% common loci). Association of genomic regions for grain area (GA) and thousand-grain weight (TGW), with yield suggests that targeting an increase in GA may help enhancing wheat yield through an increase in TGW. Flour extraction (FE), although has a weak positive phenotypic association with grain shape and size, they do not share any common genetic loci. A major contributor to plant height was the Rht8 locus and the reduced height allele was associated with significant increase in grains per spike (GPS) and FE, and decrease in number of spikes per square meter and test weight. Stable loci were identified for almost all the traits. However, we could not find any QTL in the region of major known genes like GPC-B1, Ha, Rht-1, and Ppd-1. Epistasis also played an important role in the genetics of majority of the traits. In addition to enhancing our knowledge about the association of wheat quality and yield with grain shape and size, this study provides novel loci, genetic information and pre-breeding material (combining positive alleles from both parents) to enhance the cultivated gene pool in wheat germplasm. These resources are valuable in facilitating molecular breeding for wheat quality and yield improvement.

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“…The parental lines were screened with a total of 360 SSR markers selected from the published wheat map (Röder et al, 1998; Eujayl et al, 2002; Gupta et al, 2002; Guyomarc'h et al, 2002; Sourdille et al, 2003; Peng and Lapitan, 2005; Song et al, 2005; Xue et al, 2008). The PCR and fragment analysis were carried out as described in Desiderio et al (2014).…”

Section: Methodsmentioning

confidence: 99%

Genomic Regions From an Iranian Landrace Increase Kernel Size in Durum Wheat

Desiderio¹,

Zarei

Licciardello

et al. 2019

Front. Plant Sci.

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Kernel size and shape are important parameters determining the wheat profitability, being main determinants of yield and its technological quality. In this study, a segregating population of 118 recombinant inbred lines, derived from a cross between the Iranian durum landrace accession “Iran_249” and the Iranian durum cultivar “Zardak”, was used to investigate durum wheat kernel morphology factors and their relationships with kernel weight, and to map the corresponding QTLs. A high density genetic map, based on wheat 90k iSelect Infinium SNP assay, comprising 6,195 markers, was developed and used to perform the QTL analysis for kernel length and width, traits related to kernel shape and weight, and heading date, using phenotypic data from three environments. Overall, a total of 31 different QTLs and 9 QTL interactions for kernel size, and 21 different QTLs and 5 QTL interactions for kernel shape were identified. The landrace Iran_249 contributed the allele with positive effect for most of the QTLs related to kernel length and kernel weight suggesting that the landrace might have considerable potential toward enhancing the existing gene pool for grain shape and size traits and for further yield improvement in wheat. The correlation among traits and co-localization of corresponding QTLs permitted to define 11 clusters suggesting causal relationships between simplest kernel size trait, like kernel length and width, and more complex secondary trait, like kernel shape and weight related traits. Lastly, the recent release of the T. durum reference genome sequence allowed to define the physical interval of our QTL/clusters and to hypothesize novel candidate genes inspecting the gene content of the genomic regions associated to target traits.

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Identification and mapping of quantitative trait loci for leaf rust resistance derived from a tetraploid wheat Triticum dicoccum accession

Cited by 17 publications

References 95 publications

Physical Mapping of Bread Wheat Chromosome 5A: An Integrated Approach

Physical Mapping of Bread Wheat Chromosome 5A: An Integrated Approach

Genome wide genetic dissection of wheat quality and yield related traits and their relationship with grain shape and size traits in an elite × non-adapted bread wheat cross

Genomic Regions From an Iranian Landrace Increase Kernel Size in Durum Wheat

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