Dataset Information

The genetic architecture of maize (Zea mays L.) kernel weight determination.

ABSTRACT: Individual kernel weight is an important trait for maize yield determination. We have identified genomic regions controlling this trait by using the B73xMo17 population; however, the effect of genetic background on control of this complex trait and its physiological components is not yet known. The objective of this study was to understand how genetic background affected our previous results. Two nested stable recombinant inbred line populations (N209xMo17 and R18xMo17) were designed for this purpose. A total of 408 recombinant inbred lines were genotyped and phenotyped at two environments for kernel weight and five other traits related to kernel growth and development. All traits showed very high and significant (P < 0.001) phenotypic variability and medium-to-high heritability (0.60-0.90). When N209xMo17 and R18xMo17 were analyzed separately, a total of 23 environmentally stable quantitative trait loci (QTL) and five epistatic interactions were detected for N209xMo17. For R18xMo17, 59 environmentally stable QTL and 17 epistatic interactions were detected. A joint analysis detected 14 stable QTL regardless of the genetic background. Between 57 and 83% of detected QTL were population specific, denoting medium-to-high genetic background effects. This percentage was dependent on the trait. A meta-analysis including our previous B73xMo17 results identified five relevant genomic regions deserving further characterization. In summary, our grain filling traits were dominated by small additive QTL with several epistatic and few environmental interactions and medium-to-high genetic background effects. This study demonstrates that the number of detected QTL and additive effects for different physiologically related grain filling traits need to be understood relative to the specific germplasm.

SUBMITTER: Alvarez Prado S

PROVIDER: S-EPMC4169153 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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The genetic architecture of maize (Zea mays L.) kernel weight determination.

Alvarez Prado Santiago S López César G CG Senior M Lynn ML Borrás Lucas L

G3 (Bethesda, Md.) 20140918 9

Individual kernel weight is an important trait for maize yield determination. We have identified genomic regions controlling this trait by using the B73xMo17 population; however, the effect of genetic background on control of this complex trait and its physiological components is not yet known. The objective of this study was to understand how genetic background affected our previous results. Two nested stable recombinant inbred line populations (N209xMo17 and R18xMo17) were designed for this pu ...[more]

PMID: 25237113

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Project description:BackgroundKernel weight, controlled by quantitative trait loci (QTL), is an important component of grain yield in maize. Cytokinins (CKs) participate in determining grain morphology and final grain yield in crops. ZmIPT2, which is expressed mainly in the basal transfer cell layer, endosperm, and embryo during maize kernel development, encodes an isopentenyl transferase (IPT) that is involved in CK biosynthesis.ResultsThe coding region of ZmIPT2 was sequenced across a panel of 175 maize inbred lines that are currently used in Chinese maize breeding programs. Only 16 single nucleotide polymorphisms (SNPs) and seven haplotypes were detected among these inbred lines. Nucleotide diversity (π) within the ZmIPT2 window and coding region were 0.347 and 0.0047, respectively, and they were significantly lower than the mean nucleotide diversity value of 0.372 for maize Chromosome 2 (P < 0.01). Association mapping revealed that a single nucleotide change from cytosine (C) to thymine (T) in the ZmIPT2 coding region, which converted a proline residue into a serine residue, was significantly associated with hundred kernel weight (HKW) in three environments (P <0.05), and explained 4.76% of the total phenotypic variation. In vitro characterization suggests that the dimethylallyl diphospate (DMAPP) IPT activity of ZmIPT2-T is higher than that of ZmIPT2-C, as the amounts of adenosine triphosphate (ATP), adenosine diphosphate (ADP), and adenosine monophosphate (AMP) consumed by ZmIPT2-T were 5.48-, 2.70-, and 1.87-fold, respectively, greater than those consumed by ZmIPT2-C. The effects of artificial selection on the ZmIPT2 coding region were evaluated using Tajima's D tests across six subgroups of Chinese maize germplasm, with the most frequent favorable allele identified in subgroup PB (Partner B).ConclusionsThese results showed that ZmIPT2, which is associated with kernel weight, was subjected to artificial selection during the maize breeding process. ZmIPT2-T had higher IPT activity than ZmIPT2-C, and this favorable allele for kernel weight could be used in molecular marker-assisted selection for improvement of grain yield components in Chinese maize breeding programs.

Project description:Maize (Zea mays L.) is an important source of carbohydrates and protein in the diet in sub-Saharan Africa. The objectives of this study were to (i) estimate general (GCA) and specific combining abilities (SCA) of 13 new quality protein maize (QPM) lines in a diallel under stress and non-stress conditions, (ii) compare observed and predicted performance of QPM hybrids, (iii) characterize genetic diversity among the 13 QPM lines using single nucleotide polymorphism (SNP) markers and assess the relationship between genetic distance and hybrid performance, and (iv) assess diversity and population structure in 116 new QPM inbred lines as compared to eight older tropical QPM lines and 15 non-QPM lines. The GCA and SCA effects were significant for most traits under optimal conditions, indicating that both additive and non-additive genetic effects were important for inheritance of the traits. Additive genetic effects appeared to govern inheritance of most traits under optimal conditions and across environments. Non-additive genetic effects were more important for inheritance of grain yield but additive effects controlled most agronomic traits under drought stress conditions. Inbred lines CKL08056, CKL07292, and CKL07001 had desirable GCA effects for grain yield across drought stress and non-stress conditions. Prediction efficiency for grain yield was highest under optimal conditions. The classification of 139 inbred lines with 95 SNPs generated six clusters, four of which contained 10 or fewer lines, and 16 lines of mixed co-ancestry. There was good agreement between Neighbor Joining dendrogram and Structure classification. The QPM lines used in the diallel were nearly uniformly spread throughout the dendrogram. There was no relationship between genetic distance and grain yield in either the optimal or stressed environments in this study. The genetic diversity in mid-altitude maize germplasm is ample, and the addition of the QPM germplasm did not increase it measurably.

Dataset Information

The genetic architecture of maize (Zea mays L.) kernel weight determination.

Publications

The genetic architecture of maize (Zea mays L.) kernel weight determination.

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