QTL Mapping for Field Germination Rate Using an Introgression Line Population from a Cross between Maize and Teosinte
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College of Agronomy, Hunan Agricultural University

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Excellent Youth Project of Scientific ResearchProject of Hunan Provincial Department of Education (18B117), OpenFoundation of Hunan Provincial KeyLaboratory for GermplasmInnovation and Utilization ofCrop (19KFXM10), DoubleFirst-Class Construction Project of Hunan Agricultural University (SYL2019004)

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    Abstract:

    The field germination rate of maize seeds, which is controlled by the genetic factors that interact with environmental factors (i.e. temperature, water), directly affects yield production and severs as one of the important targets in maize breeding. In this study, we performed a high-resolution QTL mapping for field germination rate using the multiple QTL model implemented in R/qtl. The introgression line population including 866 lines was derived from a cross between a maize inbred line W22 and a typical accession of teosinte, the wild progenitor of maize, followed by genotyping with 19,838 SNP markers. Three QTL were detected including qFGR4-1, qFGR5-1 and qFGR8-1, which were flanked by the markers m20780 and m21277 on chromosome 4, m29418 and m29680 on chromesome 5, as well as m44383 and m44706 on chromosome 8, respectively. Three loci attributed to 11.2% of the phenotypic variation, with the phenotypic contribution rate and additive effect of each QTL ranged from 2.8% to 4.8% and from 4.5% to 7.4%, respectively. These results indicated that the field germination rate is a typical quantitative trait, which is controlled by multiple micro-effect genes. In addition, the W22 alleles at three loci showed positive additive effects, suggesting that field germination rate might have experienced a directional selection during maize domestication and improvement. Collectively, this study might provide important reference for future elucidating the genetic basis of field germination rate, cloning key genes and improving field germination rate using molecular marker-assisted selection in maize.

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History
  • Received:June 03,2020
  • Revised:June 23,2020
  • Adopted:July 21,2020
  • Online: November 05,2020
  • Published:
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