Mapping QTLs for Tissue Culture Response in Soybean (Glycine max (L.) Merr.)

Yang, Chao; Zhao, Tuanjie; Yu, Deyue; Gai, Junyi

doi:10.1007/s10059-011-0063-1

Cited by 15 publications

(9 citation statements)

References 36 publications

(31 reference statements)

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“…Several studies have targeted the genetic control of in vitro responsiveness in a variety of plants. Many have involved QTL identification [34,65,[79][80][81][82][83], and more recently, GWAS [31,36,84]. These studies have identified several genetic loci and candidate genes associated with various aspects of in vitro responsiveness.…”

Section: Albino Regenerationmentioning

confidence: 99%

Comparative Analysis of In Vitro Responses and Regeneration between Diverse Bioenergy Sorghum Genotypes

Flinn

Dale

Disharoon

et al. 2020

Plants

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Sorghum has been considered a recalcitrant plant in vitro and suffers from a lack of regeneration protocols that function broadly and efficiently across a range of genotypes. This study was initiated to identify differential genotype-in vitro protocol responses across a range of bioenergy sorghum parental lines and the common grain sorghum genotype Tx430 in order to characterize response profiles for use in future genetic studies. Two different in vitro protocols, LG and WU, were used for comparisons. Distinct genotype-protocol responses were observed, and the WU protocol performed significantly better for plantlet regeneration. Most bioenergy genotypes performed as well, if not better than Tx430, with Rio and PI329311 as the top regenerating lines. Genotypes displayed protocol-dependent, differential phenolic exudation responses, as indicated by medium browning. During the callus induction phase, genotypes prone to medium browning exhibited a response on WU medium which was either equal or greater than on LG medium. Genotype- and protocol-dependent albino plantlet regeneration was also noted, with three of the bioenergy genotypes showing albino plantlet regeneration. Grassl, Rio and Pink Kafir were susceptible to albino plantlet regeneration, with the response strongly associated with the WU protocol. These bioenergy parental genotypes, and their differential responses under two in vitro protocols, provide tools to further explore and assess the role of genetic loci, candidate genes, and allelic variants in the regulation of in vitro responsiveness in sorghum.

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Section: Albino Regenerationmentioning

confidence: 99%

Comparative Analysis of In Vitro Responses and Regeneration between Diverse Bioenergy Sorghum Genotypes

Flinn

Dale

Disharoon

et al. 2020

Plants

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“…It is believed that genetic control of plant regeneration ability could be either qualitative (Reisch and Bingham 1980 ) or quantitative (Taguchi-Shiobara et al 2006 ). A large number of studies have been reported on quantitative trait loci (QTLs) analysis for tissue culture response (TCR) in soybean (Yang et al 2011 ), rice (Li et al 2013a ; Nishimura et al 2005 ; Zhao et al 2009 ), maize (Murigneux et al 1994 ; Wan et al 1992 ), barley (Bregitzer and Campbell 2001 ; Manninen 2000 ; Mano and Komatsuda 2002 ), rye (Bolibok et al 2007 ), and wheat (Jia et al 2007 ; Nielsen et al 2015 ; Torp et al 2001 ).…”

Section: Introductionmentioning

confidence: 99%

Identification of QTLs associated with tissue culture response of mature wheat embryos

Deng

et al. 2016

SpringerPlus

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Mature embryo is an excellent explant for tissue culture as it is convenient to be obtained without limitation of growing seasons and development stages. However, regeneration ability of the calli from wheat mature embryos is limited, thus hindering its application. To identify genes associated with the tissue culture response (TCR) of wheat, QTLs for callus induction from mature embryos and callus regeneration were detected using a recombinant inbred lines (RILs) population derived from the cross between a synthetic hexaploid wheat genotype, SHW-L1 and a commercial cultivar Chuanmai 32. Three QTLs for callus rate were identified and they were located on chromosomes 1D, 5A, and 6D, respectively, with explained phenotypic variation ranging from 10.16 to 11.82 %. One QTL for differentiation rate was detected only with 10.96 % of the phenotypic variation explained. Two QTLs for emergence rate were identified and they were located on 3B and 4A, respectively, with 9.88 and 10.30 % of phenotypic variation. The results presented in this study with those reported previously indicated that group 1, 3, and 5 chromosomes are likely to play important roles in TCR of wheat.

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“…Especially due to the advanced sequencing technique, much more gene-based molecular markers could be exploited from transcriptome data from massively-parallel next-generation sequencing (NGS) (Lu et al, 2011;Metzker, 2010). Researchers have benefited from the availability of techniques for the rapid and costeffective development of molecular marker-based linkage maps (Yang et al, 2011). Four genetic maps were provided on Solanaceae Genomics Network (http://solgenomics.net/), of which pepper-FAO3 contained the most 720 markers with an averaged 1.89 cM interval (Mueller et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

SNP Marker Integration and QTL Analysis of 12 Agronomic and Morphological Traits in F8RILs of Pepper (Capsicum annuum L.)

Kwon

Yoon

et al. 2012

Molecules and Cells

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Red pepper, Capsicum annuum L., has been attracting geneticists' and breeders' attention as one of the important agronomic crops. This study was to integrate 41 SNP markers newly developed from comparative transcriptomes into a previous linkage map, and map 12 agronomic and morphological traits into the integrated map. A total of 39 markers found precise position and were assigned to 13 linkage groups (LGs) as well as the unassigned LGe, leading to total 458 molecular markers present in this genetic map. Linkage mapping was supported by the physical mapping to tomato and potato genomes using BLAST retrieving, revealing at least two-thirds of the markers mapped to the corresponding LGs. A sum of 23 quantitative trait loci from 11 traits was detected using the composite interval mapping algorithm. A consistent interval between a035_1 and a170_1 on LG5 was detected as a main-effect locus among the resistance QTLs to Phytophthora capsici at high-, intermediate- and low-level tests, and interactions between the QTLs for high-level resistance test were found. Considering the epistatic effect, those QTLs could explain up to 98.25% of the phenotype variations of resistance. Moreover, 17 QTLs for another eight traits were found to locate on LG3, 4, and 12 mostly with varying phenotypic contribution. Furthermore, the locus for corolla color was mapped to LG10 as a marker. The integrated map and the QTLs identified would be helpful for current genetics research and crop breeding, especially in the Solanaceae family.

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Mapping QTLs for Tissue Culture Response in Soybean (Glycine max (L.) Merr.)

Cited by 15 publications

References 36 publications

Comparative Analysis of In Vitro Responses and Regeneration between Diverse Bioenergy Sorghum Genotypes

Comparative Analysis of In Vitro Responses and Regeneration between Diverse Bioenergy Sorghum Genotypes

Identification of QTLs associated with tissue culture response of mature wheat embryos

SNP Marker Integration and QTL Analysis of 12 Agronomic and Morphological Traits in F8RILs of Pepper (Capsicum annuum L.)

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