QTL Analysis of Kernel-Related Traits in Maize Using an Immortalized F2 Population

Kernel size and weight are important determinants of grain yield in maize. In this study, multivariate conditional and unconditional quantitative trait loci (QTL), and digenic epistatic analyses were utilized in order to elucidate the genetic basis for these kernel-related traits. Five kernel-related traits, including kernel weight (KW), volume (KV), length (KL), thickness (KT), and width (KWI), were collected from an immortalized F2 (IF2) maize population comprising of 243 crosses performed at two separate locations over a span of two years. A total of 54 unconditional main QTL for these five kernel-related traits were identified, many of which were clustered in chromosomal bins 6.04–6.06, 7.02–7.03, and 10.06–10.07. In addition, qKL3, qKWI6, qKV10a, qKV10b, qKW10a, and qKW7a were detected across multiple environments. Sixteen main QTL were identified for KW conditioned on the other four kernel traits (KL, KWI, KT, and KV). Thirteen main QTL were identified for KV conditioned on three kernel-shape traits. Conditional mapping analysis revealed that KWI and KV had the strongest influence on KW at the individual QTL level, followed by KT, and then KL; KV was mostly strongly influenced by KT, followed by KWI, and was least impacted by KL. Digenic epistatic analysis identified 18 digenic interactions involving 34 loci over the entire genome. However, only a small proportion of them were identical to the main QTL we detected. Additionally, conditional digenic epistatic analysis revealed that the digenic epistasis for KW and KV were entirely determined by their constituent traits. The main QTL identified in this study for determining kernel-related traits with high broad-sense heritability may play important roles during kernel development. Furthermore, digenic interactions were shown to exert relatively large effects on KL (the highest AA and DD effects were 4.6% and 6.7%, respectively) and KT (the highest AA effects were 4.3%).

[1]  C. Cockerham,et al.  An Extension of the Concept of Partitioning Hereditary Variance for Analysis of Covariances among Relatives When Epistasis Is Present. , 1954, Genetics.

[2]  T. Young,et al.  Regulation of programmed cell death in maize endosperm by abscisic acid , 2004, Plant Molecular Biology.

[3]  Richard D. Thompson,et al.  rgf1, a mutation reducing grain filling in maize through effects on basal endosperm and pedicel development. , 2000, The Plant journal : for cell and molecular biology.

[4]  Qifa Zhang,et al.  Genetic dissection of an elite rice hybrid revealed that heterozygotes are not always advantageous for performance. , 2002, Genetics.

[5]  Lin Wang,et al.  Wheat kernel dimensions: how do they contribute to kernel weight at an individual QTL level? , 2011, Journal of Genetics.

[6]  Chourey,et al.  A Re-Evaluation of the Relative Roles of Two Invertases, INCW2 and IVR1, in Developing Maize Kernels and Other Tissues. , 1999, Plant physiology.

[7]  M. Westgate,et al.  Control of kernel weight and kernel water relations by post-flowering source-sink ratio in maize. , 2003, Annals of botany.

[8]  Guoying Wang,et al.  Genetic analysis and QTL mapping of maize yield and associate agronomic traits under semi-arid land condition , 2008 .

[9]  Kernel weight per spike: what contributes to it at the individual QTL level? , 2013, Molecular Breeding.

[10]  Si-Shen Li,et al.  Conditional QTL mapping for plant height with respect to the length of the spike and internode in two mapping populations of wheat , 2011, Theoretical and Applied Genetics.

[11]  W. Ecke,et al.  Conditional QTL mapping of oil content in rapeseed with respect to protein content and traits related to plant development and grain yield , 2006, Theoretical and Applied Genetics.

[12]  R. Jung,et al.  The defective kernel 1 (dek1) gene required for aleurone cell development in the endosperm of maize grains encodes a membrane protein of the calpain gene superfamily , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[13]  R. Wu,et al.  Functional mapping — how to map and study the genetic architecture of dynamic complex traits , 2006, Nature Reviews Genetics.

[14]  M. Westgate,et al.  Predicting maize kernel sink capacity early in development , 2006 .

[15]  Z. H. Liu,et al.  QTL detected for grain-filling rate in maize using a RIL population , 2010, Molecular Breeding.

[16]  Guodong Zhang,et al.  Mapping QTLs for grain yield and yield components under high and low phosphorus treatments in maize (Zea mays L.) , 2010 .

[17]  T. Young,et al.  Programmed cell death during endosperm development , 2000, Plant Molecular Biology.

[18]  Yang Wang,et al.  QTL analysis for yield components and kernel-related traits in maize across multi-environments , 2011, Theoretical and Applied Genetics.

[19]  J. Prioul,et al.  QTLs for enzyme activities and soluble carbohydrates involved in starch accumulation during grain filling in maize. , 2005, Journal of experimental botany.

[20]  Jun Zhu,et al.  Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics , 2022 .

[21]  M. Westgate,et al.  Characterization of Grain-Filling Patterns in Diverse Maize Germplasm , 2009 .

[22]  J. Roessler,et al.  Kernel Sink Capacity in Maize: Genotypic and Maternal Regulation , 1996 .

[23]  Michael Lee,et al.  Comparative mapping in F2∶3 and F6∶7 generations of quantitative trait loci for grain yield and yield components in maize , 1996, Theoretical and Applied Genetics.

[24]  T. Setter,et al.  Water deficit inhibits cell division and expression of transcripts involved in cell proliferation and endoreduplication in maize endosperm. , 2001, Journal of experimental botany.

[25]  P. Gupta,et al.  Genetic and molecular basis of grain size and grain number and its relevance to grain productivity in higher plants. , 2006, Genome.

[26]  B. S. Dhillon,et al.  Dissection of the genetic basis of heterosis in an elite maize hybrid by QTL mapping in an immortalized F2 population , 2009, Theoretical and Applied Genetics.

[27]  A. Blejec,et al.  Cytometrical Evidence That the Loss of Seed Weight in theminiature1 Seed Mutant of Maize Is Associated with Reduced Mitotic Activity in the Developing Endosperm1 , 2002, Plant Physiology.

[28]  Jianbing Yan,et al.  Epistatic interaction is an important genetic basis of grain yield and its components in maize , 2007, Molecular Breeding.

[29]  M. Tollenaar,et al.  Yield potential, yield stability and stress tolerance in maize , 2002 .

[30]  Jun Zhu,et al.  QTLNetwork: mapping and visualizing genetic architecture of complex traits in experimental populations , 2008, Bioinform..

[31]  Z. Zeng Precision mapping of quantitative trait loci. , 1994, Genetics.

[32]  Y. Fukuta,et al.  Time-related mapping of quantitative trait loci controlling grain-filling in rice (Oryza sativa L.). , 2005, Journal of experimental botany.

[33]  L. Borrás,et al.  Trait dissection of maize kernel weight: Towards integrating hierarchical scales using a plant growth approach , 2010 .

[34]  Jianbing Yan,et al.  Quantitative trait loci mapping and epistatic analysis for grain yield and yield components using molecular markers with an elite maize hybrid , 2006, Euphytica.

[35]  T. Rocheford,et al.  Quantitative trait loci influencing protein and starch concentration in the Illinois Long Term Selection maize strains , 1993, Theoretical and Applied Genetics.

[36]  Chen Wei-cheng QTL Mapping of Ear Traits under Low and High Nitrogen Conditions in Maize , 2007 .

[37]  J. T. Madison,et al.  Influence of water deficit on maize endosperm development : enzyme activities and RNA transcripts of starch and zein synthesis, abscisic Acid, and cell division. , 1991, Plant physiology.

[38]  Bin Wang,et al.  Genetic Analysis of Grain Filling Rate Using Conditional QTL Mapping in Maize , 2013, PloS one.