Cytogenetics of Legumes in the Phaseoloid Clade

Iwata, Akihisa; Greenland, Christopher M.; Jackson, Scott A.

doi:10.3835/plantgenome2013.03.0004

Cited by 21 publications

(9 citation statements)

References 132 publications

(120 reference statements)

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“…Cowpea [ Vigna unguiculata (L.) Walp. 2X = 2N = 22], ~587 Mb in genome size, is an important drought-tolerant legume crop (Iwata et al, 2013 ). It is one of the top five food legumes or pulses grown worldwide (Smýkal et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

“…Due to its symbiotic nitrogen fixation, the crop is a valuable component of rotations and intercrops with sorghum and millets. The nitrogen fixation level of cowpea is less than soybean, but more than common bean (Quaye et al, 2009 ; Iwata et al, 2013 ). Cowpea is widely grown throughout tropical and subtropical regions, including Africa and some Asian, South European, Central and South American countries (Tosti and Negri, 2005 ).…”

Section: Introductionmentioning

confidence: 99%

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A High Density Genetic Map Derived from RAD Sequencing and Its Application in QTL Analysis of Yield-Related Traits in Vigna unguiculata

Pan

Wang

et al. 2017

Front. Plant Sci.

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Cowpea [Vigna unguiculata (L.) Walp.] is an annual legume of economic importance and widely grown in the semi-arid tropics. However, high-density genetic maps of cowpea are still lacking. Here, we identified 34,868 SNPs (single nucleotide polymorphisms) that were distributed in the cowpea genome based on the RAD sequencing (restriction-site associated DNA sequencing) technique using a population of 170 individuals (two cowpea parents and 168 F2:3 progenies). Of these, 17,996 reliable SNPs were allotted to 11 consensus linkage groups (LGs). The length of the genetic map was 1,194.25 cM in total with a mean distance of 0.066 cM/SNP marker locus. Using this map and the F2:3 population, combined with the CIM (composite interval mapping) method, eleven quantitative trait loci (QTL) of yield-related trait were detected on seven LGs (LG4, 5, 6, 7, 9, 10, and 11) in cowpea. These QTL explained 0.05–17.32% of the total phenotypic variation. Among these, four QTL were for pod length, four QTL for thousand-grain weight (TGW), two QTL for grain number per pod, and one QTL for carpopodium length. Our results will provide a foundation for understanding genes related to grain yield in the cowpea and genus Vigna.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A High Density Genetic Map Derived from RAD Sequencing and Its Application in QTL Analysis of Yield-Related Traits in Vigna unguiculata

Pan

Wang

et al. 2017

Front. Plant Sci.

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“…Cicer is also in the Galegoid clade, but it falls in the Cicereae subclade. Arachis is from the Dalbergia clade, which has the smallest number of cultivated legumes (Iwata, Greenland, & Jackson, 2013; Smýkal et al., 2015). Legumes are in the Fabaceae family, and the majority of grain legumes are in the Papilonaceae subfamily (Smýkal et al., 2015; simplified phlogenetic diagram in Supplemental Figure S1).…”

Section: Methodsmentioning

confidence: 99%

Comparative phenomics of annual grain legume root architecture

2020

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Suboptimal water and P availability are primary limitations to grain legume production. Root architecture influences water and P acquisition, but tradeoffs need to be better understood and mitigated. We hypothesized that tradeoffs in root class investment and resource acquisition strategy would be observable in a variety of grain legumes. Diversity panels of common bean (Phaseolus vulgaris L.), tepary bean (Phaseolus acutifolius A. Gray), cowpea [Vigna unguiculata (L.) Walp.], soybean [Glycine max (L.) Merr.], chickpea (Cicer arietinum L.), groundnut (Arachis hypogaea L.), and single accessions of other legumes were phenotyped in the field. We identified inverse relationships among investments in different root classes in most species, and between indicators of deep and shallow exploration in all species. Bean and tepary bean showed particularly strong tradeoffs in investment patterns among root classes, whereas chickpea and groundnut show less pronounced tradeoffs. We found that legume root architectural phenotypes can be placed on a root system architecture (RSA) spectrum, and that root phenotypes of epigeal and hypogeal taxa present distinct adaptive mechanisms. These life strategies integrating resource acquisition, use, and phenology are exemplified by contrasting chickpea, with many root axes, to tepary bean with few root axes and a contrasting water use strategy. We propose several RSA ideotypes and highlight how dimorphic root architecture may co‐optimize resource acquisition.

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“…The second article by Iwata et al (2013) is another review that focuses on the need to unravel the complex genomic organization of crop species to use genomics more efficiently in breeding strategies. Genomic resources along with molecular cytogenetics may help to facilitate a better understanding of legume genomes and chromosomes.…”

Section: Genomic Resourcesmentioning

confidence: 99%