Mining Elite Alleles of Growth Duration and Productive Panicle Number per Plant by Association Mapping with Conditional Phenotypic Value in Japonica Rice

Jiang, Jianhua; Cui, Lan; Liu, Qiangming; He, Ying-jun; Hong, Delin

doi:10.1016/s1672-6308(13)60126-2

Cited by 3 publications

(7 citation statements)

References 12 publications

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“…tillering and dwarf 1 (tad1), Xu et al, 2012 qTN5 RM413-RM437 5 2.0-4.0 Yan et al, 1998;Xing et al, 2002, Yang et al (2006. none qTN8 RM447-RM477 8 26.4-end Wang et al, 1994;Yan et al, 1998;Hemamalini et al, 2000;Temnykh et al, 2001;Brondani et al, 2002;Ramalingam et al, 2003;Miyamoto et al, 2004;Jiang et al, 2013;Pinson et al (2015a).…”

Section: Kz-ril Qtl Markersmentioning

confidence: 99%

QTLs for Early Tiller Production and Relationships with Rapid Seedling Growth and Increased Panicle Number in Rice

Pinson

Jia

2016

Crop Science

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Tiller number (TN) is a key determinant of final grain yield in the small grains crops, including rice (Oryza sativa L.), and is desired to enhance competition with weeds. Quantitative trait loci (QTLs) associated with TN were mapped within a set of recombinant inbred lines developed from a cross between the low‐tillering tropical japonica cultivar ‘Kaybonnet‐lpa1‐1’ and the high‐tillering, high‐yielding, early‐maturing indica cultivar ‘Zhe733’ using data collected from greenhouse potted plants evaluated weekly. Relationships between the five identified TN QTLs and related traits including panicle number (PN), flag leaf number, seedling leaf number (SLN), and earliness of tiller production were also evaluated. The three TN QTLs that were linked with early tiller emergence were also associated with PN; two additional TN not associated with PN were also identified. All five TN QTLs were also SLN QTLs, though other loci affecting SLN were also identified. Several of the TN and SLN QTLs identified using data from young plants (e.g., ≤6 wk after planting) were not detectible in data collected just before or after heading. The three TN QTLs also associated with PN showed stronger effects (higher logarithm of the odds ratios and additive effects) on TN as observed in seedling stages than on final TN at heading time, and their effects diminished over time to the point that they were not always detectible in TN data collected at or after heading. However, the three TN QTLs that were also PN QTLs were robust enough that they were detected in the less intensive (one‐fourth the labor and resources) Arkansas trials, where tillers were counted from two single‐plant replications just twice, at 6 wk after planting and after heading. The three loci associated with both TN and PN are the TN loci most likely to increase rice yield, and the markers presently found linked to them can be used for marker assisted breeding.

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Section: Kz-ril Qtl Markersmentioning

confidence: 99%

QTLs for Early Tiller Production and Relationships with Rapid Seedling Growth and Increased Panicle Number in Rice

Pinson

Jia

2016

Crop Science

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“…More than 250 QTLs for various agronomically important traits have been identified in the LT-RILs, but loci affecting TN were not yet determined. Mapping the TN QTLs in TeQing will be very useful in comparing location, trait effect, and parental origin with the reported QTLs associated with panicle and kernel size, a key aspect not fully explored in previous TN QTL studies (Wang et al, 1994;Wu et al, 1995;Lu et al, 1997;Yan et al, 1998;Price et al, 2000;Temnykh et al, 2001;Brondani et al, 2002;Nagata et al, 2002;Xing et al, 2002;Hu et al, 2003;Miyamoto et al, 2004;Ramalingam et al, 2003;Zhang et al, 2005;Li et al, 2006;Huang et al, 2010;Jiang et al, 2013;Lim et al, 2014). Mapping the TN QTLs in TeQing will be very useful in comparing location, trait effect, and parental origin with the reported QTLs associated with panicle and kernel size, a key aspect not fully explored in previous TN QTL studies (Wang et al, 1994;Wu et al, 1995;Lu et al, 1997;Yan et al, 1998;Price et al, 2000;Temnykh et al, 2001;Brondani et al, 2002;Nagata et al, 2002;Xing et al, 2002;Hu et al, 2003;Miyamoto et al, 2004;Ramalingam et al, 2003;Zhang et al, 2005;Li et al, 2006;Huang et al, 2010;Jiang et al, 2013;Lim et al, 2014).…”

Section: Mapping and Validation Of Quantitative Trait Loci Associatedmentioning

confidence: 99%

“…QTLs: Wang et al, 1994;Wu et al, 1995;Xing et al, 2002;Ramalingam et al, 2003;Jiang et al, 2013. 1998 The marker-trait association tool available in JMP Genomics 4.0 was used to identify single-sequence repeat markers significantly associated (p  0.05) with tiller number among a set of 123 TeQing-into-Lemont introgression lines (TiLs). The TiL marker associations were only used to verify putative QTLs identified first among the LT-RiLs; they were not used for de novo QTL identification.…”

Section: Mutations: Nonementioning

confidence: 99%

“…The TN QTLs in TeQing are of particular interest since this trait was pinpointed as critical in enhancing yield in US rice , Samonte et al, 1998. Mapping the TN QTLs in TeQing will be very useful in comparing location, trait effect, and parental origin with the reported QTLs associated with panicle and kernel size, a key aspect not fully explored in previous TN QTL studies (Wang et al, 1994;Wu et al, 1995;Lu et al, 1997;Yan et al, 1998;Price et al, 2000;Temnykh et al, 2001;Brondani et al, 2002;Nagata et al, 2002;Xing et al, 2002;Hu et al, 2003;Miyamoto et al, 2004;Ramalingam et al, 2003;Zhang et al, 2005;Li et al, 2006;Huang et al, 2010;Jiang et al, 2013;Lim et al, 2014).…”

Section: Mapping and Validation Of Quantitative Trait Loci Associatedmentioning

confidence: 99%

“…QTLs: Wang et al, 1994Lu et al, 1997;nagata et al, 2002;Ramalingam et al, 2003;Gao et al, 2013;Lim et al, 2014. 1998 G379 100-kernel weight (Li et al, 1997); grain weight per panicle (Li et al, 1997); disease resistance (Pinson et al, 2005) Mutations: ideal plant architecture 1 (ipa1) Miura et al, 2010. QTLs: Wang et al, 1994Temnykh et al, 2001;Brondani et al, 2002;Ramalingam et al, 2003;Miyamoto et al, 2004;Jiang et al, 2013. 1.4 100-kernel weight (Paterson et al, 1995;Li et al, 1997); grain no. per panicle (Li et al, 1997); disease resistance (Li et al, 1999a;Pinson et al, 2005) Mutations: Lin et al, 2009.…”

Section: 6mentioning

confidence: 99%

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Mapping and Validation of Quantitative Trait Loci Associated with Tiller Production in Rice

Pinson

Wang

Tabien³

2015

Crop Science

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Abbreviations: LOD, logarithm of the odds ratio; LT-RIL, Lemont ´ TeQing recombinant inbred line; Mbp, mega base pair; MIM, multiple-interval mapping; N1T, node of first tiller on the main culm; QTL, quantitative trait locus; RFLP, restriction fragment length polymorphism; RIL, recombinant inbred line; SLN, seedling leaf number; SSR, simple-sequence repeat; TIL, TeQing-into-Lemont backcross introgression line; TN, tiller number.

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Dissecting the Genetic Architecture of Melon Chilling Tolerance at the Seedling Stage by Association Mapping and Identification of the Elite Alleles

et al. 2018

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Low temperature is an important abiotic stress that negatively affects morphological growth and fruit development in melon (Cucumis melo L.). Chilling stress at the seedling stage causes seedling injury and poor stand establishment, prolonging vegetative growth and delaying fruit harvest. In this study, association mapping was performed for chilling tolerance at the seedling stage on an expanded melon core collection containing 212 diverse accessions by 272 SSRs and 27 CAPSs. Chilling tolerance of the melon seedlings was evaluated by calculating the chilling injury index (CII) in 2016 and 2017. Genetic diversity analysis of the whole accession panel presented two main groups, which corresponded to the two subspecies of C. melo, melo, and agrestis. Both the subspecies were sensitive to chilling but with agrestis being more tolerant. Genome-wide association study (GWAS) was conducted, respectively, on the whole panel and the two subspecies, totally detecting 51 loci that contributed to 74 marker-trait associations. Of these associations, 35 were detected in the whole panel, 21 in melo, and 18 in agrestis. About half of the associations identified in the two subspecies were also observed in the whole panel, and seven associations were shared by both the subspecies. CMCT505_Chr.1 was repeatedly detected in different populations with high phenotypic contribution and could be a key locus controlling chilling tolerance in C. melo. Nine loci were selected for evaluation of the phenotypic effects related to their alleles, which identified 11 elite alleles contributing to seedling chilling tolerance. Four such alleles existed in both the subspecies and six in either of the two subspecies. Analysis of 20 parental combinations for their allelic status and phenotypic values showed that the elite alleles collectively contributed to enhancement of the chilling tolerance. Tagging the loci responsible for chilling tolerance may simultaneously favor dissecting the complex adaptability traits and elevate the efficiency to improve chilling tolerance using marker-assisted selection in melon.

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Mining Elite Alleles of Growth Duration and Productive Panicle Number per Plant by Association Mapping with Conditional Phenotypic Value in Japonica Rice

Cited by 3 publications

References 12 publications

QTLs for Early Tiller Production and Relationships with Rapid Seedling Growth and Increased Panicle Number in Rice

QTLs for Early Tiller Production and Relationships with Rapid Seedling Growth and Increased Panicle Number in Rice

Mapping and Validation of Quantitative Trait Loci Associated with Tiller Production in Rice

Dissecting the Genetic Architecture of Melon Chilling Tolerance at the Seedling Stage by Association Mapping and Identification of the Elite Alleles

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