Genetic structure and association mapping of cold tolerance in improved japonica rice germplasm at the booting stage

Cui, Di; Xu, Chang-ying; Tang, Cuifeng; Chun-gang, Yang; Yu, Tong; A, Xinxiang; Cao, Guilan; Xu, Fei; Zhang, Junguo; Han, Longzhi

doi:10.1007/s10681-013-0935-x

Cited by 40 publications

(41 citation statements)

References 63 publications

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“…In case of linseed different types of DNA based markers includingAFLP,RAPD,retrotransposon,ISSR,SSRs,SNPetc. havebeenusedforevaluatingthegenetic diversityandlinkage mapping (Cloutier et al 2010;Oh et al 2000;Spielmeyer et al 1998).OverothertypesofDNAmarkers,SSRsarewidelyused forgeneticdiversityandstructureanalysisinseveralcropplants (Cheng et al 2015;Yan et al 2009;Cane et al 2014;Cui et al 2013). In the present investigation, we applied 50 widely distributed SSRs to evaluate the genetic diversity and identify diverseaccessions/groupofaccessionsamongalargesetof168 accessionsoflinseed.Atotalof337allelesweredetectedfrom50 SSRswithanaverageof6.74allelesperSSRs.Thisaverageallele numberwasfoundtobehigherthanthatreportedearlier (RooseAmsalegetal.2006;Dengetal.2011;Palietal.2014;Soto-Cerda etal.2012Cloutieretal.2012b).Thehigherallelenumber mightbeduetothelargeanddiversesetofaccessionsandwidely distributed SSRs used in the present study.…”

Section: Discussionmentioning

confidence: 99%

Genetic diversity, population structure and association analysis in linseed (Linum usitatissimum L.)

Chandrawati

Singh

Kumar³

et al. 2017

Physiol Mol Biol Plants

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The present investigation aimed to explore the level of genetic diversity, determine the population structure in a larger set of germplasm of linseed using microsatellite marker and identify linked markers through association mapping. A total of 168 accessions of linseed were evaluated for major agro-economic traits and SSRs markers deployed for diversity assessment. A total of 337 alleles were amplified by 50 SSRs ranging from 2 to 13 with an average of 6.74 ± 2.8 alleles per loci. The neighbor joining based clustering grouped all the accessions into three major clusters that were also confirmed by scatter plot of PCoA. While model based clustering determined four sub-populations (K = 4). Further, analysis of molecular variance analysis considering three population showed that maximum variation (79%) was within the population. We identified one putative SSR marker (Lu_3043) linked with days to 50% flowering through both GLM and MLM analysis of association mapping. The results of this preliminary study revealed genetic diversity, population structure in linseed and linked marker which could be utilized in future breeding program.

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Section: Discussionmentioning

confidence: 99%

Genetic diversity, population structure and association analysis in linseed (Linum usitatissimum L.)

Chandrawati

Singh

Kumar³

et al. 2017

Physiol Mol Biol Plants

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“…For example, two distinct subgroups, which were in accordance with the differentiation of indica and japonica rice, were detected within a rice core collection consisting of 150 cultivars genotyped with 274 SSR markers (Zhang et al, 2011). Population structure analysis using 148 SSRs markers identified three major subpopulations (corresponding to major geographic origins) for 347 rice accessions from a worldwide collection (Cui et al, 2013). A selected sample of 540 rice cultivars (419 from China and 121 from Vietnam) was divided into seven subpopulations on the basis of 262 SSR markers (Dang et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

“…The CLUMPP software ( Jakobsson and Rosenberg, 2007) was used to integrate the population structure matrix (Q matrix) of replicate runs from Structure 2.2.3, and the integrated Q matrix was adopted for association mapping. Using the k calculated above, each accession was assigned to a subpopulation if its corresponding membership value in integrated Q matrix was >0.65 (Cui et al, 2013). When an accession had no membership values >0.65 for any of the subpopulations, it was assigned to the mixed subpopulation.…”

Section: Population Structurementioning

confidence: 99%

Markers Associated with Culm Length and Elongated Internode Length in Japonica Rice

et al. 2017

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Culm length (CL) is composed of different elongated internode lengths (EILs) and is closely correlated to the lodging resistance in rice (Oryza sativa L.). The objective of this study was to identify quantitative trait loci (QTLs) stably associated with CL and the first to fourth EIL from panicle base, which were abbreviated as FIL (first), SIL (second), TIL (third), and FOIL (fourth) in japonica rice, respectively. Association mapping was conducted using the genotypes determined by 154 simple sequence repeat markers and the phenotypes in 2010, 2011, and 2015 of 331 japonica rice accessions. The study mapped 6, 5, 15, 2, and 2 QTLs tagged by 22 markers on eight chromosomes and stably associated with CL, FIL, SIL, TIL, and FOIL, respectively. Five QTLs, qCL‐6‐2, qFIL‐6‐5, qSIL‐6‐2, qTIL‐6‐3, and qFOIL‐7‐5, explained the largest phenotypic variance of CL, FIL, SIL, TIL, and FOIL, respectively. RM1340, RM1374, RM281, RM233, and RM225 were stably and specifically associated with CL, FIL, SIL, TIL, and FOIL, respectively. Forty‐three effective alleles were identified. Four and three donors with negative and positive alleles were recommended. There was a highly significant phenotypic difference between accessions with or without effective alleles. These QTLs, associated markers, effective alleles, and their donors could be used to improve CL and specific EIL in japonica rice.

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“…The PIC values of the rice accessions ranged from 0.0233 to 0.8441 with an average of 0.5366 in japonica rice varieties. It was higher than the collection of 416 rice accessions including landrace, cultivars and breeding lines (Jin et al 2010, PIC = 0.4214) and 347 improved japonica rice varieties (Cui et al 2013, PIC = 0.3137), but lower than the collection of 236 rice materials (Xu et al 2005, PIC = 0.74). The differences of genetic diversity in different reports are related with the number of rice accessions analyzed and the choice of rice germplasm, the number of SSR loci and the SSR repeat type.…”

Section: Discussionmentioning

confidence: 73%

“…The CLUMPP software (Jakobsson and Rosenberg 2007) was used to integrate the results of replicate runs from STRUCTURE. Based on the correct K, each accession was assigned to a subpopulation for which the membership value (Q value) was[0.65 (Cui et al 2013) and the population structure matrix (Q) was adopted for the association analysis. Using inferred subpopulations, an analysis of molecular variance (AMOVA) was performed under GenAlEx6.2 (Peakall and Smouse 2006), genetic distance and pair-wise F ST among subpopulations were estimated with POPGENE version 1.31 developed by Yeh et al (1999).…”

Section: Population Structure and Differentiation Analysesmentioning

confidence: 99%

Genetic structure, linkage disequilibrium and association mapping of salt tolerance in japonica rice germplasm at the seedling stage

et al. 2015

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Soil salinity is a major constraint to rice production. Understanding the genetic basis of salt tolerance is crucial for the improvement of salt tolerance through breeding. Previous quantitative trait locus (QTL) studies for salt tolerance were mainly derived from bi-parental segregating populations and relatively little is known about the results from natural populations. Understanding the genetic diversity, population structure and linkage disequilibrium (LD) in an association panel can effectively avoid spurious associations in association mapping. In this study, 341 japonica rice (Oryza sativa L. subsp. japonica) accessions worldwide were genotyped with 160 simple sequence repeat (SSR) markers to identify marker-trait associations with salt tolerance at the seedling stage. Salt tolerance was evaluated by survival days of seedlings and shoot K ? / Na ? ratio. A total of 872 alleles ranging from 2 to 9 per locus were identified from all collections. Population structure analysis identified three main subpopulations for the accessions. Of the SSR pairs in these accessions, 40.05 % marker pairs showed significant LD (P \ 0.01). The LD level for linked markers is significantly higher than that for unlinked markers, and LD level was elevated when the panel was classified into subpopulations. The LD decayed to the background at approximately 20-50 cM within the total panel and each subpopulation. A total of ten marker loci associated with salt tolerance were identified using MLM (Q ? K) models in TASSEL 3.0. Among which nine marker loci confirmed or narrowed the genomic region reported to harbor QTLs for salt tolerance by linkage mapping in previous reports, and four salt tolerance-related genes were located in the QTL regions in the present study. According to phenotypic effects for alleles of the detected QTLs, favorable alleles were mined. These favorable alleles could be used to design parental combinations and the expected results would be obtained by pyramiding or substituting the favorable alleles per QTL (apart from possible epistatic effects). Our results demonstrate that association mapping can complement and enhance previous QTL information for marker-assisted selection and breeding by design.

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Genetic structure and association mapping of cold tolerance in improved japonica rice germplasm at the booting stage

Cited by 40 publications

References 63 publications

Genetic diversity, population structure and association analysis in linseed (Linum usitatissimum L.)

Genetic diversity, population structure and association analysis in linseed (Linum usitatissimum L.)

Markers Associated with Culm Length and Elongated Internode Length in Japonica Rice

Genetic structure, linkage disequilibrium and association mapping of salt tolerance in japonica rice germplasm at the seedling stage

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