Qingchun Pan

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

Elucidation of the genetic determinants of maize primary metabolism and a metabolite-metabolite-agronomic trait network will promote efficient use of metabolites in maize improvement. 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, R2 = 2.4 to 15%) to major effects (13.8% of the mapped QTL, R2 >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.

Genetic basis of grain yield heterosis in an "immortalized F 2 " maize population

Key messageGenetic basis of grain yield heterosis relies on the cumulative effects of dominance, overdominance, and epistasis in maize hybrid Yuyu22.AbstractHeterosis, i.e., when F1 hybrid phenotypes are superior to those of the parents, continues to play a critical role in boosting global grain yield. Notwithstanding our limited insight into the genetic and molecular basis of heterosis, it has been exploited extensively using different breeding approaches. In this study, we investigated the genetic underpinnings of grain yield and its components using “immortalized F2” and recombinant inbred line populations derived from the elite hybrid Yuyu22. A high-density linkage map consisting of 3,184 bins was used to assess (1) the additive and additive-by-additive effects determined using recombinant inbred lines; (2) the dominance and dominance-by-dominance effects from a mid-parent heterosis dataset; and (3) the various genetic effects in the “immortalized F2” population. Compared with a low-density simple sequence repeat map, the bin map identified more quantitative trait loci, with higher LOD scores and better accuracy of detecting quantitative trait loci. The bin map showed that, among all traits, dominance was more important to heterosis than other genetic effects. The importance of overdominance/pseudo-overdominance was proportional to the amount of heterosis. In addition, epistasis contributed to heterosis as well. Phenotypic variances explained by the QTLs detected were close to the broad-sense heritabilities of the observed traits. Comparison of the analyzed results obtained for the “immortalized F2” population with those for the mid-parent heterosis dataset indicated identical genetic modes of action for mid-parent heterosis and grain yield performance of the hybrid.

Genome-wide dissection of the maize ear genetic architecture using multiple populations.

Improvement of grain yield is an essential long-term goal of maize (Zea mays) breeding to meet continual and increasing food demands worldwide, but the genetic basis remains unclear. We used 10 different recombination inbred line (RIL) populations genotyped with high-density markers and phenotyped in multiple environments to dissect the genetic architecture of maize ear traits. Three methods were used to map the quantitative trait loci (QTLs) affecting ear traits. We found 17-34 minor- or moderate-effect loci that influence ear traits, with little epistasis and environmental interactions, totally accounting for 55.4-82% of the phenotypic variation. Four novel QTLs were validated and fine mapped using candidate gene association analysis, expression QTL analysis and heterogeneous inbred family validation. The combination of multiple different populations is a flexible and manageable way to collaboratively integrate widely available genetic resources, thereby boosting the statistical power of QTL discovery for important traits in agricultural crops, ultimately facilitating breeding programs.

Combining Quantitative Genetics Approaches with Regulatory Network Analysis to Dissect the Complex Metabolism of the Maize Kernel

A metabolic quantitative trait loci study combined with a regulatory network unraveled the genetic architecture of the natural variation of 155 metabolites in mature maize kernels. Metabolic quantitative trait locus (QTL) studies have allowed us to better understand the genetic architecture underlying naturally occurring plant metabolic variance. Here, we use two recombinant inbred line (RIL) populations to dissect the genetic architecture of natural variation of 155 metabolites measured in the mature maize (Zea mays) kernel. Overall, linkage mapping identified 882 metabolic QTLs in both RIL populations across two environments, with an average of 2.1 QTLs per metabolite. A large number of metabolic QTLs (more than 65%) were identified with moderate effects (r2 = 2.1%–10%), while a small portion (less than 35%) showed major effects (r2 > 10%). Epistatic interactions between these identified loci were detected for more than 30% of metabolites (with the proportion of phenotypic variance ranging from 1.6% to 37.8%), implying that genetic epistasis is not negligible in determining metabolic variation. In total, 57 QTLs were validated by our previous genome-wide association study on the same metabolites that provided clues for exploring the underlying genes. A gene regulatory network associated with the flavonoid metabolic pathway was constructed based on the transcriptional variations of 28,769 genes in kernels (15 d after pollination) of 368 maize inbred lines. A large number of genes (34 of 58) in this network overlapped with previously defined genes controlled by maize PERICARP COLOR1, while three of them were identified here within QTL intervals for multiple flavonoids. The deeply characterized RIL populations, elucidation of metabolic phenotypes, and identification of candidate genes lay the foundation for maize quality improvement.

Genome‐wide recombination dynamics are associated with phenotypic variation in maize

Meiotic recombination is a major driver of genetic diversity, species evolution, and agricultural improvement. Thus, an understanding of the genetic recombination landscape across the maize (Zea mays) genome will provide insight and tools for further study of maize evolution and improvement. Here, we used c. 50 000 single nucleotide polymorphisms to precisely map recombination events in 12 artificial maize segregating populations. We observed substantial variation in the recombination frequency and distribution along the ten maize chromosomes among the 12 populations and identified 143 recombination hot regions. Recombination breakpoints were partitioned into intragenic and intergenic events. Interestingly, an increase in the number of genes containing recombination events was accompanied by a decrease in the number of recombination events per gene. This kept the overall number of intragenic recombination events nearly invariable in a given population, suggesting that the recombination variation observed among populations was largely attributed to intergenic recombination. However, significant associations between intragenic recombination events and variation in gene expression and agronomic traits were observed, suggesting potential roles for intragenic recombination in plant phenotypic diversity. Our results provide a comprehensive view of the maize recombination landscape, and show an association between recombination, gene expression and phenotypic variation, which may enhance crop genetic improvement.

The conserved and unique genetic architecture of kernel size and weight in maize and rice

Ten segregating populations yield both conserved and species-specific genetic architecture of kernel size and weight in maize and rice. Maize (Zea mays) is a major staple crop. Maize kernel size and weight are important contributors to its yield. Here, we measured kernel length, kernel width, kernel thickness, hundred kernel weight, and kernel test weight in 10 recombinant inbred line populations and dissected their genetic architecture using three statistical models. In total, 729 quantitative trait loci (QTLs) were identified, many of which were identified in all three models, including 22 major QTLs that each can explain more than 10% of phenotypic variation. To provide candidate genes for these QTLs, we identified 30 maize genes that are orthologs of 18 rice (Oryza sativa) genes reported to affect rice seed size or weight. Interestingly, 24 of these 30 genes are located in the identified QTLs or within 1 Mb of the significant single-nucleotide polymorphisms. We further confirmed the effects of five genes on maize kernel size/weight in an independent association mapping panel with 540 lines by candidate gene association analysis. Lastly, the function of ZmINCW1, a homolog of rice GRAIN INCOMPLETE FILLING1 that affects seed size and weight, was characterized in detail. ZmINCW1 is close to QTL peaks for kernel size/weight (less than 1 Mb) and contains significant single-nucleotide polymorphisms affecting kernel size/weight in the association panel. Overexpression of this gene can rescue the reduced weight of the Arabidopsis (Arabidopsis thaliana) homozygous mutant line in the AtcwINV2 gene (Arabidopsis ortholog of ZmINCW1). These results indicate that the molecular mechanisms affecting seed development are conserved in maize, rice, and possibly Arabidopsis.

The genetic architecture of amino acids dissection by association and linkage analysis in maize

Summary Amino acids are both constituents of proteins, providing the essential nutrition for humans and animals, and signalling molecules regulating the growth and development of plants. Most cultivars of maize are deficient in essential amino acids such as lysine and tryptophan. Here, we measured the levels of 17 different total amino acids, and created 48 derived traits in mature kernels from a maize diversity inbred collection and three recombinant inbred line (RIL) populations. By GWAS, 247 and 281 significant loci were identified in two different environments, 5.1 and 4.4 loci for each trait, explaining 7.44% and 7.90% phenotypic variation for each locus in average, respectively. By linkage mapping, 89, 150 and 165 QTLs were identified in B73/By804, Kui3/B77 and Zong3/Yu87‐1 RIL populations, 2.0, 2.7 and 2.8 QTLs for each trait, explaining 13.6%, 16.4% and 21.4% phenotypic variation for each QTL in average, respectively. It implies that the genetic architecture of amino acids is relative simple and controlled by limited loci. About 43.2% of the loci identified by GWAS were verified by expression QTL, and 17 loci overlapped with mapped QTLs in the three RIL populations. GRMZM2G015534, GRMZM2G143008 and one QTL were further validated using molecular approaches. The amino acid biosynthetic and catabolic pathways were reconstructed on the basis of candidate genes proposed in this study. Our results provide insights into the genetic basis of amino acid biosynthesis in maize kernels and may facilitate marker‐based breeding for quality protein maize.

The Genetic Basis of Plant Architecture in 10 Maize Recombinant Inbred Line Populations

A large-scale QTL mapping on 10 plant architecture traits across 10 RIL populations reveals the complex genetic basis of plant architecture in maize. Plant architecture is a key factor affecting planting density and grain yield in maize (Zea mays). However, the genetic mechanisms underlying plant architecture in diverse genetic backgrounds have not been fully addressed. Here, we performed a large-scale phenotyping of 10 plant architecture-related traits and dissected the genetic loci controlling these traits in 10 recombinant inbred line populations derived from 14 diverse genetic backgrounds. Nearly 800 quantitative trait loci (QTLs) with major and minor effects were identified as contributing to the phenotypic variation of plant architecture-related traits. Ninety-two percent of these QTLs were detected in only one population, confirming the diverse genetic backgrounds of the mapping populations and the prevalence of rare alleles in maize. The numbers and effects of QTLs are positively associated with the phenotypic variation in the population, which, in turn, correlates positively with parental phenotypic and genetic variations. A large proportion (38.5%) of QTLs was associated with at least two traits, suggestive of the frequent occurrence of pleiotropic loci or closely linked loci. Key developmental genes, which previously were shown to affect plant architecture in mutant studies, were found to colocalize with many QTLs. Five QTLs were further validated using the segregating populations developed from residual heterozygous lines present in the recombinant inbred line populations. Additionally, one new plant height QTL, qPH3, has been fine-mapped to a 600-kb genomic region where three candidate genes are located. These results provide insights into the genetic mechanisms controlling plant architecture and will benefit the selection of ideal plant architecture in maize breeding.

Contributions of Zea mays subspecies mexicana haplotypes to modern maize

Maize was domesticated from lowland teosinte (Zea mays ssp. parviglumis), but the contribution of highland teosinte (Zea mays ssp. mexicana, hereafter mexicana) to modern maize is not clear. Here, two genomes for Mo17 (a modern maize inbred) and mexicana are assembled using a meta-assembly strategy after sequencing of 10 lines derived from a maize-teosinte cross. Comparative analyses reveal a high level of diversity between Mo17, B73, and mexicana, including three Mb-size structural rearrangements. The maize spontaneous mutation rate is estimated to be 2.17 × 10−8 ~3.87 × 10−8 per site per generation with a nonrandom distribution across the genome. A higher deleterious mutation rate is observed in the pericentromeric regions, and might be caused by differences in recombination frequency. Over 10% of the maize genome shows evidence of introgression from the mexicana genome, suggesting that mexicana contributed to maize adaptation and improvement. Our data offer a rich resource for constructing the pan-genome of Zea mays and genetic improvement of modern maize varieties.Maize was domesticated from wild lowland progenitors that co-existed with upland subspecies in Southwestern Mexico. Here Yang et al. use a meta-assembly approach to assemble an upland mexicana genome and find evidence of introgression suggesting it contributed to modern maize adaptation

Complexity of genetic mechanisms conferring nonuniformity of recombination in maize

Recombinations occur nonuniformly across the maize genome. To dissect the genetic mechanisms underlying the nonuniformity of recombination, we performed quantitative trait locus (QTL) mapping using recombinant inbred line populations. Genome-wide QTL scan identified hundreds of QTLs with both cis-prone and trans- effects for recombination number variation. To provide detailed insights into cis- factors associated with recombination variation, we examined the genomic features around recombination hot regions, including density of genes, DNA transposons, retrotransposons, and some specific motifs. Compared to recombination variation in whole genome, more QTLs were mapped for variations in recombination hot regions. The majority QTLs for recombination hot regions are trans-QTLs and co-localized with genes from the recombination pathway. We also found that recombination variation was positively associated with the presence of genes and DNA transposons, but negatively related to the presence of long terminal repeat retrotransposons. Additionally, 41 recombination hot regions were fine-mapped. The high-resolution genotyping of five randomly selected regions in two F2 populations verified that they indeed have ultra-high recombination frequency, which is even higher than that of the well-known recombination hot regions sh1-bz and a1-sh2. Taken together, our results further our understanding of recombination variation in plants.