Ning Yang

Genome-wide association study dissects the genetic architecture of oil biosynthesis in maize kernels

Maize kernel oil is a valuable source of nutrition. Here we extensively examine the genetic architecture of maize oil biosynthesis in a genome-wide association study using 1.03 million SNPs characterized in 368 maize inbred lines, including high-oil lines. We identified 74 loci significantly associated with kernel oil concentration and fatty acid composition (P < 1.8 × 10−6), which we subsequently examined using expression quantitative trait loci (QTL) mapping, linkage mapping and coexpression analysis. More than half of the identified loci localized in mapped QTL intervals, and one-third of the candidate genes were annotated as enzymes in the oil metabolic pathway. The 26 loci associated with oil concentration could explain up to 83% of the phenotypic variation using a simple additive model. Our results provide insights into the genetic basis of oil biosynthesis in maize kernels and may facilitate marker-based breeding for oil quantity and quality.

CACTA-like transposable element in ZmCCT attenuated photoperiod sensitivity and accelerated the postdomestication spread of maize

Significance Maize was domesticated from teosinte in Southern Mexico roughly 9,000 years ago. Maize originally was sensitive to photoperiod and required short-day conditions to flower. Thus, the reduced sensitivity to photoperiod is prerequisite for maize spread to long-day temperate regions. A gene encoding a CCT domain-containing protein, ZmCCT, was found by many researchers to modulate photoperiod sensitivity. The current study shows that insertion of a CACTA-like transposon into the ZmCCT promoter can suppress the ZmCCT expression remarkably and thus attenuates maize sensitivity under long-day conditions. The transposable element (TE) insertion event occurred in a tropical maize plant and has been selected for and accumulated as maize adapted to vast long-day environments. This selection leaves behind a TE-related linkage disequilibrium block with the very-low-nucleotide variations. The postdomestication adaptation of maize to longer days required reduced photoperiod sensitivity to optimize flowering time. We performed a genome-wide association study and confirmed that ZmCCT, encoding a CCT domain-containing protein, is associated with the photoperiod response. In early-flowering maize we detected a CACTA-like transposable element (TE) within the ZmCCT promoter that dramatically reduced flowering time. TE insertion likely occurred after domestication and was selected as maize adapted to temperate zones. This process resulted in a strong selective sweep within the TE-related block of linkage disequilibrium. Functional validations indicated that the TE represses ZmCCT expression to reduce photoperiod sensitivity, thus accelerating maize spread to long-day environments.

Genome Wide Association Studies Using a New Nonparametric Model Reveal the Genetic Architecture of 17 Agronomic Traits in an Enlarged Maize Association Panel

Association mapping is a powerful approach for dissecting the genetic architecture of complex quantitative traits using high-density SNP markers in maize. Here, we expanded our association panel size from 368 to 513 inbred lines with 0.5 million high quality SNPs using a two-step data-imputation method which combines identity by descent (IBD) based projection and k-nearest neighbor (KNN) algorithm. Genome-wide association studies (GWAS) were carried out for 17 agronomic traits with a panel of 513 inbred lines applying both mixed linear model (MLM) and a new method, the Anderson-Darling (A-D) test. Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold −log10 (P) >5.74 (αu200a=u200a1). Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold −log10 (P) >7.05 (αu200a=u200a0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test, a few of which were also detected in independent linkage analysis. This study indicates that combining IBD based projection and KNN algorithm is an efficient imputation method for inferring large missing genotype segments. In addition, we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power. The candidate SNPs and associated genes also provide a rich resource for maize genetics and breeding.

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 association mapping reveals novel sources of resistance to northern corn leaf blight in maize

BackgroundNorthern corn leaf blight (NCLB) caused by Exserohilum turcicum is a destructive disease in maize. Using host resistance to minimize the detrimental effects of NCLB on maize productivity is the most cost-effective and appealing disease management strategy. However, this requires the identification and use of stable resistance genes that are effective across different environments.ResultsWe evaluated a diverse maize population comprised of 999 inbred lines across different environments for resistance to NCLB. To identify genomic regions associated with NCLB resistance in maize, a genome-wide association analysis was conducted using 56,110 single-nucleotide polymorphism markers. Single-marker and haplotype-based associations, as well as Anderson-Darling tests, identified alleles significantly associated with NCLB resistance. The single-marker and haplotype-based association mappings identified twelve and ten loci (genes), respectively, that were significantly associated with resistance to NCLB. Additionally, by dividing the population into three subgroups and performing Anderson-Darling tests, eighty one genes were detected, and twelve of them were related to plant defense. Identical defense genes were identified using the three analyses.ConclusionAn association panel including 999 diverse lines was evaluated for resistance to NCLB in multiple environments, and a large number of resistant lines were identified and can be used as reliable resistance resource in maize breeding program. Genome-wide association study reveals that NCLB resistance is a complex trait which is under the control of many minor genes with relatively low effects. Pyramiding these genes in the same background is likely to result in stable resistance to NCLB.

MODD mediates deactivation and degradation of OsbZIP46 to negatively regulate ABA signaling and drought resistance in rice

MODD negatively regulates OsbZIP46 activity and stability through HDAC-related chromatin remodeling and PUB70-mediated ubiquitination, respectively, to fine-tune ABA signaling and drought resistance. Plants have evolved complicated protective mechanisms to survive adverse conditions. Previously, we reported that the transcription factor OsbZIP46 regulates abscisic acid (ABA) signaling-mediated drought tolerance in rice (Oryza sativa) by modulating stress-related genes. An intrinsic D domain represses OsbZIP46 activity, but the detailed mechanism for the repression of OsbZIP46 activation remains unknown. Here, we report an OsbZIP46-interacting protein, MODD (Mediator of OsbZIP46 deactivation and degradation), which is homologous to the Arabidopsis thaliana ABSCISIC ACID-INSENSITIVE5 binding protein AFP. MODD was induced by ABA and drought stress, but the induction was much slower than that of OsbZIP46. In contrast to OsbZIP46, MODD negatively regulates ABA signaling and drought tolerance, and inhibits the expression of OsbZIP46 target genes. We found that MODD negatively regulates OsbZIP46 activity and stability. MODD represses OsbZIP46 activity via interaction with the OsTPR3-HDA702 corepressor complex and downregulation of the histone acetylation level at OsbZIP46 target genes. MODD promotes OsbZIP46 degradation via interaction with the U-box type ubiquitin E3 ligase OsPUB70. Interestingly, the D domain is required for both deactivation and degradation of OsbZIP46 via its interaction with MODD. These findings show that plants fine-tune their drought responses by elaborate regulatory mechanisms, including the coordination of activity and stability of key transcription factors.

Genome-wide association studies of drought-related metabolic changes in maize using an enlarged SNP panel

Key messageGenetic determinants of metabolites related to drought tolerance in maize.AbstractWater deficit or drought is one of the most serious abiotic stresses of plant development and greatly reduces crop production, and the plant’s response to this deficit leads to many metabolic changes. To dissect the genetic basis of these metabolic traits in maize, we performed a genome-wide association analysis of drought-related traits using 156,599 SNPs in 318 maize inbred lines. In total, 123 significant SNP/trait associations (Pxa0≤xa06.39E−6) involving 63 loci were identified for related metabolic and physiological traits in multiple tissues and different environments under two irrigation conditions. Of the 63, 23 loci demonstrated a significant interaction effect between QTL and water status, indicating that these metabolite-associated loci were probably related to drought stress tolerance. To evaluate the potential utility of metabolite-associated loci appliedxa0in hybrid maize breeding, we assembled two groups of hybrid entries with high or low drought tolerance and measured the metabolic and physiological traits. In the hybrid pools, a set of 10 metabolite-associated loci identified in leaf and ear were validated as responsive to drought stress. The favorable alleles of these ten loci were significantly enriched in hybrids with high drought tolerance, which jointly explained almost 18.4xa0% of the variation in drought tolerance using a multivariate logistic regression model. These results provide clues to understanding the genetic basis of metabolic and physiological changes related to drought tolerance, potentially facilitating the genetic improvement of varieties with high drought tolerance in maize breeding programs.