Microsatellite marker development, mapping and applications in rice genetics and breeding

McCouch, Susan R.; Chen, Xiuli; Panaud, Olivier; Temnykh, Svetlana V.; Xu, Yunbi; Cho, Yong Gu; Huang, Ning; Ishii, Takashige; Blair, Matthew W.

doi:10.1007/978-94-011-5794-0_9

Cited by 272 publications

(194 citation statements)

References 63 publications

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“…1, DChangfei22B; 2, Changfei22B; 3, Djin23B; 4, Jin23B; 5, DCB; 6, CB; 7, D32B; 8, II-32B; 9, D46B; 10, Gang46B;11, DTB;12, TB;13, DCDR22;14, CDR22;15, Dchenghui149;16, Chenghui149;17, Dminghui63;18, Minghui63;19, D2248;20, 2248;21, Dhaitian;22, Haitian;23, D193;24, IR36;25, Dwuxuenuo;26, Wuxuenuo;27, D46A;28, 46A;29, H5409;30, D6039;31, H5815;32, H5905;33, H5776;34, H5609;35, H5647;36, D19B;37, DTP-3;38, DTP-4;39, Dguangshi;40, D6043;41, Dbaxi;42, D237;43, D2204;44, D89-37;45, DAc27;46, DErjiuai;47, D187;48, D64;49, Dshixiang;50, DL10 Biochem Genet (2008) 46:248-266 261 codominance, and cost-effectiveness (Xiao et al 2006;McCouch et al 1997;Ni et al 2002), which were clearly demonstrated in this study. In our study, 36 SSRs distributed across the 12 chromosomes in rice were used to detect genetic diversity among 36 autotetraploid and 14 original diploid rices.…”

Section: Differentiation Of Dna Genetic Structure Of Autotetraploids mentioning

confidence: 99%

Microsatellite Analysis of Genetic Variation and Population Genetic Differentiation in Autotetraploid and Diploid Rice

et al. 2008

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Genetic diversity and population genetic structure of autotetraploid and diploid populations of rice collected from Chengdu Institute of Biology, Chinese Academy of Sciences, were studied based on 36 microsatellite loci. Among 50 varieties, a moderate to high level of genetic diversity was observed at the population level, with the number of alleles per locus (A e ) ranging from 2 to 6 (mean 3.028) and polymorphism information content ranging from 0.04 to 0.76 (mean 0.366). The expected heterozygosity (H e ) varied from 0.04 to 0.76 (mean 0.370) and Shannon's index (I) from 0.098 to 1.613 (mean 0.649). The autotetraploid populations showed slightly higher levels of A e , H e , and I than the diploid populations. Rare alleles were observed at most of the simple sequence repeat loci in one or more of the 50 accessions, and a core fingerprint database of the autotetraploid and diploid rice was constructed. The F-statistics showed genetic variability mainly among autotetraploid populations rather than diploid populations (F st = 0.066). Cluster analysis of the 50 accessions showed four major groups. Group I contained all of the autotetraploid and diploid indica maintainer lines and an autotetraploid and its original diploid indica male sterile lines. Group II contained only the original IR accessions. Group III was more diverse than either Group II or Group IV, comprising both autotetraploid and diploid indica restoring lines. Group IV included a japonica cluster of the autotetraploid and diploid rices. Furthermore, genetic differences at the single-locus and two-locus levels, as well as components due to allelic and gametic differentiation, were revealed between autotetraploid and diploid varieties. This analysis indicated that the gene pools of diploid and autotetraploid rice were somewhat dissimilar, as variation exists that distinguishes autotetraploid 123Biochem Genet (2008) 46:248-266 DOI 10.1007 from diploid rices. Using this variation, we can breed new autotetraploid varieties with some important agricultural characters that were not found in the original diploid rice varieties.

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Section: Differentiation Of Dna Genetic Structure Of Autotetraploids mentioning

confidence: 99%

Microsatellite Analysis of Genetic Variation and Population Genetic Differentiation in Autotetraploid and Diploid Rice

et al. 2008

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“…Leaves fully cupped (U-shaped) 7 Leaves margins touching (O-shaped) 9 Leaves tightly rolled 2.4 Evaluation genetic diversity using SSR markers DNA extraction was prepared according to a method described by McCouch et al [14]. A piece of young rice leaf (2 cm) was collected and placed in a 1.5 ml centrifuge tube sitting on ice.…”

Section: Agro-morphological Character Evaluationmentioning

confidence: 99%

“…These include restriction fragment length polymorphism (RFLP) [9], random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), and microsatellites or simple sequence repeats (SSRs) [10]- [13]. Commonly, SSR markers have been extensively used in genetic diversity in rice because of their high level of polymorphism to establish relationships among individuals even with fewer number markers [14].…”

Section: Introductionmentioning

confidence: 99%

Correlation among Agro-Morphological Variation and Genetic Diversity of Rice (<i>Oryza sativa </i>L.) under Drought Stress

Khang

Tuyen

et al. 2016

ILNS

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Abstract. In this study, the correlation coefficients among agro-morphological variation, genetic diversity, and drought tolerance in 44 rice cultivars were analyzed. The drought tolerance at seeding stage (DTS) was significantly proportional to drought tolerance at vegetative stage (DTV) (r = 0.60). In addition, DTS and DTV had strong significant positive correlation to leaf roll (r = 0.87 and 0.54, respectively). Means of unfilled grains and tilling per panicle were proportionally correlated to DTS (r = 0.22 and 0.25, respectively), and DTV (r = 0.20 and 0.36, respectively). However, weight of 1000 grains and filled grains were recorded no correlation to DTS and DTV. At a homologous coefficient of 16.85 integrated from cluster analysis of agro-morphological, quantitative characteristics and drought tolerant scores, the rice cultivars were divided into five groups. Maximum polymorphic information content (PIC) values were detected in three markers including RM11125, RM21, and RM5629, which were from 0.78 to 0.79. Cluster analysis of microsatellite markers revealed that by a genetic distance of 0.63, the rice varieties were separated into three clusters. The results provide valuable information for rice breeders to select donors in breeding rice integrated with drought tolerance and good agronomic characteristics.

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“…Microsatellite methods employing fluorescent labeling and automated band calling with precise softwarebased allele detection are considered the most accurate way of genotyping (McCouch et al 1997, Blair et al 2002. Additionally, this sort of labeling organizes markers into distinct dye color panels allowing multiplexing during band separation, with advantages of high throughput genotyping and simultaneous analysis of multiple loci (Coburn et al 2002, Oblessuc et al 2009).…”

Section: Genic Microsatellites From Est Databasementioning

confidence: 99%

Development and application of microsatellites in plant breeding

Gonçalves‐Vidigal

Rubiano²

2011

Crop Breed. Appl. Biotechnol.

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Microsatellite marker development, mapping and applications in rice genetics and breeding

Cited by 272 publications

References 63 publications

Microsatellite Analysis of Genetic Variation and Population Genetic Differentiation in Autotetraploid and Diploid Rice

Microsatellite Analysis of Genetic Variation and Population Genetic Differentiation in Autotetraploid and Diploid Rice

Correlation among Agro-Morphological Variation and Genetic Diversity of Rice (<i>Oryza sativa </i>L.) under Drought Stress

Development and application of microsatellites in plant breeding

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