QTLs for Seed Vigor-Related Traits Identified in Maize Seeds Germinated under Artificial Aging ConditionsReportar como inadecuado

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High seed vigor is important for agricultural production due to the associated potential for increased growth and productivity. However, a better understanding of the underlying molecular mechanisms is required because the genetic basis for seed vigor remains unknown. We used single-nucleotide polymorphism SNP markers to map quantitative trait loci QTLs for four seed vigor traits in two connected recombinant inbred line RIL maize populations under four treatment conditions during seed germination. Sixty-five QTLs distributed between the two populations were identified and a meta-analysis was used to integrate genetic maps. Sixty-one initially identified QTLs were integrated into 18 meta-QTLs mQTLs. Initial QTLs with contribution to phenotypic variation values of R2>10% were integrated into mQTLs. Twenty-three candidate genes for association with seed vigor traits coincided with 13 mQTLs. The candidate genes had functions in the glycolytic pathway and in protein metabolism. QTLs with major effects R2>10% were identified under at least one treatment condition for mQTL2, mQTL3-2, and mQTL3-4. Candidate genes included a calcium-dependent protein kinase gene 302810918 involved in signal transduction that mapped in the mQTL3-2 interval associated with germination energy GE and germination percentage GP, and an hsp20-alpha crystallin family protein gene At5g51440 that mapped in the mQTL3-4 interval associated with GE and GP. Two initial QTLs with a major effect under at least two treatment conditions were identified for mQTL5-2. A cucumisin-like Ser protease gene At5g67360 mapped in the mQTL5-2 interval associated with GP. The chromosome regions for mQTL2, mQTL3-2, mQTL3-4, and mQTL5-2 may be hot spots for QTLs related to seed vigor traits. The mQTLs and candidate genes identified in this study provide valuable information for the identification of additional quantitative trait genes.

Autor: Zanping Han, Lixia Ku, Zhenzhen Zhang, Jun Zhang, ShuLei Guo, Haiying Liu, Ruifang Zhao, Zhenzhen Ren, Liangkun Zhang, Huihui Su,

Fuente: http://plos.srce.hr/


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