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Genetic Analysis Of Eight Yield Relative Traits In Maize And Verification Of QKRN1

Posted on:2013-12-19Degree:MasterType:Thesis
Country:ChinaCandidate:X L CaoFull Text:PDF
GTID:2233330371963032Subject:Crop Genetics and Breeding
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The dissection of genetic basis for grain yield and its components is a hot area in crop genetic improvement. QTL mapping and epistatic analysis can give us a new understanding on genetic control of grain yield-associated traits of maize, and can provide for molecular design breeding in maize.A population including 200 F2:3 family lines was developed from the crossing of NX531 X SIL8 to detect QTL and epistasis for 8 yield-related traits of maize, such as Kernel Depth (KD), Kernel Width (KW), Kernel Thickness (KT), Kernel Row Number (KRN), Ear Diameter (ED), Cob Diameter (CD) and Kernel Number per Row (KNR). Moreover, a BC-MAS strategy was used for verification of the qKRN1, a QTL affect kernel row number on chromosome 1. The results are as follows:1. A total 34 QTL for the eight traits were detected on 9 maize chromosomes with an expectation of chromosome 8. The phenotype contribution of single QTL ranged from 5.21% to 26.62%. The accumulative phenotypic variance explained by QTL for single trait ranged from 21.33%~74.10%. 7 QTL were detected for KT, 6 for KW, 5 for KRN, 4 for EL and ED, CD and KD were detected 3 QTL, but only 2 for KW. In addition, 15 major-effects QTL (Major-QTL) were detected if the assessment criterion was defined as the phenotype donation is above 10%.2. Sixteen QTL detected were mapped in six QTL clusters on chromosome 1,3,4,5 and 6. Those QTL with the large phenotype contribution for certain trait were located in the QTL clusters. 6 clusters contain 47% QTL that were detected and 73% Main-QTL. Traits relative with each cluster have extreme significant correlations, which may indicate a‘pleiotropism’phenomenon.3. 26 epistasis were identified including only 1 pair QTL x QTL interaction, 8 QTL x minor-effect loci (Minor-QTL) and 17 Minor-QTL x Minor-QTL. The phenotypic variation explained by single interaction pair ranging from 5.98% to 15.93%, accumulatively from 15.93% to 61.64% for each trait. Specially, KRN in eight traits found no prominent interaction while ED has 7 pairs explained phenotypic variation 61.64% accumulatively.4. Most of yield-relative traits display a complex genetic basis and epistasis always plays an important role in the genetic controlling of yield-associated traits of maize. Here we found phenotype of KD and KNR were deeply affected by both environment and interactions. Especially, KD relative interactions correlative interactions had an accumulative phenotypic donation for 61.64%, which was much larger than that of QTL. In comparison, the KRN QTL could explain phenotypic variation for 72.49% with no prominent interaction. The QTL detected for KRN was considered as more available in genetic improvement for maize.5. A BC-MAS strategy was used in the verification of qKRN1, a QTL regulate kernel row number on chromosome 1. The result indicated no co-segregation relationship between phenotype and genotype of target fragment. But the KRN was significant different whether loci of target fragment and bnlg653 on chromosome 5 were both present or not, which implyed interaction between the two may have a large effect on kernel row number.
Keywords/Search Tags:maize (Zea Mays L.), quantitative trait loci (QTL), epistasis, QTL cluster, genetic verification
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