Characterization of a global germplasm collection and its potential utilization for analysis of complex quantitative traits in maize

Yang, Xiaohong; Gao, Shibin; Xu, Shutu; Zhang, Zuxin; Prasanna, Boddupalli M.; Li, Lin; Li, Jiansheng; Yan, Jianbing

doi:10.1007/s11032-010-9500-7

Cited by 321 publications

(317 citation statements)

References 70 publications

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“…A maize association mapping panel consists of 508 inbred lines, including tropical, subtropical and temperate germplasms 47 . All 508 lines were divided into two groups (temperate and tropical/subtropical) based on their pedigree information and planted in one-row plots in an incompletely randomized block design within the group with two replicates in Jingzhou, Hubei province of China in 2010.…”

Section: Methodsmentioning

confidence: 99%

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RNA sequencing reveals the complex regulatory network in the maize kernel

et al. 2013

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RNA sequencing can simultaneously identify exonic polymorphisms and quantitate gene expression. Here we report RNA sequencing of developing maize kernels from 368 inbred lines producing 25.8 billion reads and 3.6 million single-nucleotide polymorphisms. Both the MaizeSNP50 BeadChip and the Sequenom MassArray iPLEX platforms confirm a subset of high-quality SNPs. Of these SNPs, we have mapped 931,484 to gene regions with a mean density of 40.3 SNPs per gene. The genome-wide association study identifies 16,408 expression quantitative trait loci. A two-step approach defines 95.1% of the eQTLs to a 10-kb region, and 67.7% of them include a single gene. The establishment of relationships between eQTLs and their targets reveals a large-scale gene regulatory network, which include the regulation of 31 zein and 16 key kernel genes. These results contribute to our understanding of kernel development and to the improvement of maize yield and nutritional quality.

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Section: Methodsmentioning

confidence: 99%

“…The admixture model was used assuming correlated allele frequencies among groups. Five runs at k ¼ 3 were performed on the panel, previously divided into three subgroups using 884 SNPs 47 . The results of the replicate runs were integrated using the CLUMPP software 56 .…”

Section: Methodsmentioning

confidence: 99%

RNA sequencing reveals the complex regulatory network in the maize kernel

et al. 2013

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“…The fresh shoot biomass (biomass) was recorded at 15 DAP for each line. An association panel containing 513 maize inbred lines (Yang et al, 2011) that was collected previously was grown under the same conditions as described above in 2013.…”

Section: Plant Materials and Growth Conditionsmentioning

confidence: 99%

Genetic Determinants of the Network of Primary Metabolism and Their Relationships to Plant Performance in a Maize Recombinant Inbred Line Population

et al. 2015

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Deciphering the influence of genetics on primary metabolism in plants will provide insights useful for genetic improvement and enhance our fundamental understanding of plant growth and development. Although maize (Zea mays) is a major crop for food and feed worldwide, the genetic architecture of its primary metabolism is largely unknown. Here, we use high-density linkage mapping to dissect large-scale metabolic traits measured in three different tissues (leaf at seedling stage, leaf at reproductive stage, and kernel at 15 d after pollination [DAP]) of a maize recombinant inbred line population. We identify 297 quantitative trait loci (QTLs) with moderate (86.2% of the mapped QTL, R 2 = 2.4 to 15%) to major effects (13.8% of the mapped QTL, R 2 >15%) for 79 primary metabolites across three tissues. Pairwise epistatic interactions between these identified loci are detected for more than 25.9% metabolites explaining 6.6% of the phenotypic variance on average (ranging between 1.7 and 16.6%), which implies that epistasis may play an important role for some metabolites. Key candidate genes are highlighted and mapped to carbohydrate metabolism, the tricarboxylic acid cycle, and several important amino acid biosynthetic and catabolic pathways, with two of them being further validated using candidate gene association and expression profiling analysis. Our results reveal a metabolite-metabolite-agronomic trait network that, together with the genetic determinants of maize primary metabolism identified herein, promotes efficient utilization of metabolites in maize improvement.

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“…Genotypic data collected with the same SNP chip for the 1482 noninducers were obtained for 834 lines from our own database, for 335 lines from Yang et al (2011) and for the remaining 313 lines from and . Quality control of the SNP data encompassed two steps for screening of markers and genotypes.…”

Section: Genotypingmentioning

confidence: 99%

The Genetic Basis of Haploid Induction in Maize Identified with a Novel Genome-Wide Association Method

Schrag

Peis

et al. 2016

Genetics

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In vivo haploid induction (HI) triggered by pollination with special intraspecific genotypes, called inducers, is unique to Zea mays L. within the plant kingdom and has revolutionized maize breeding during the last decade. However, the molecular mechanisms underlying HI in maize are still unclear. To investigate the genetic basis of HI, we developed a new approach for genome-wide association studies (GWAS), termed conditional haplotype extension (CHE) test that allows detection of selective sweeps even under almost perfect confounding of population structure and trait expression. Here, we applied this test to identify genomic regions required for HI expression and dissected the combined support interval (50.34 Mb) of the QTL qhir1, detected in a previous study, into two closely linked genomic segments relevant for HI expression. The first, termed qhir11 (0.54 Mb), comprises an already fine-mapped region but was not diagnostic for differentiating inducers and noninducers. The second segment, termed qhir12 (3.97 Mb), had a haplotype allele common to all 53 inducer lines but not found in any of the 1482 noninducers. By comparing resequencing data of one inducer with 14 noninducers, we detected in the qhir12 region three candidate genes involved in DNA or amino acid binding, however, none for qhir11. We propose that the CHE test can be utilized in introgression breeding and different fields of genetics to detect selective sweeps in heterogeneous genetic backgrounds.KEYWORDS in vivo haploid induction; selective sweep; genome-wide association study; population structure; Zea mays L T HE double haploid (DH) technology based on in vivo haploid induction (HI) has become one of the most important tools in maize breeding during the past decade and is replacing the conventional method of line development by recurrent selfing . The success of this new technology became possible, because dozens of maize inducer lines have been developed worldwide (reviewed in Supplemental Material, File S1) which, when used as pollinators, trigger the production of seeds with haploid embryo at an acceptable rate, i.e., .2% . Double fertilization followed by elimination of the inducer chromosomes in the embryo at later developmental stages (Li et al. 2009;Xu et al. 2013) as well as parthenogenesis (Sarkar and Coe 1966;Beckert et al. 2008) HI in maize, but a proof of these hypotheses requires profound knowledge about the genetic and physiological factors underlying this phenomenon. All previous QTL mapping studies for unraveling the genetic architecture of HI detected a major QTL on chromosome 1 (Röber 1999;Beckert et al. 2008; Prigge et al. 2012). The most comprehensive study with four biparental populations (Prigge et al. 2012) mapped this QTL, termed qhir1, to bin 1.04 and hypothesized that it is required for HI, but QTL positions and 1-LOD support intervals differed substantially among populations. In another study with population 1680 3 UH400, Dong et al. (2013) fine mapped a 3.57-Mb region between markers umc1917 and bnlg1811, w...

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Characterization of a global germplasm collection and its potential utilization for analysis of complex quantitative traits in maize

Cited by 321 publications

References 70 publications

RNA sequencing reveals the complex regulatory network in the maize kernel

RNA sequencing reveals the complex regulatory network in the maize kernel

Genetic Determinants of the Network of Primary Metabolism and Their Relationships to Plant Performance in a Maize Recombinant Inbred Line Population

The Genetic Basis of Haploid Induction in Maize Identified with a Novel Genome-Wide Association Method

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