Quantitative trait loci for grain moisture at harvest and field grain drying rate in maize (Zea mays, L.)

Genome-wide association analysis for grain moisture content and dehydration rate on maize hybrids

For mechanized maize production, a low grain water content (GWC) at harvest is necessary. However, as a complex quantitative trait, understand the genetic mechanism of GWC remains a large gap, especially in hybrids. In this study, a hybrid population through two environments including 442 F1 was used for genome-wide association analysis of GWC and the grain dehydration rate (GDR), using the area under the dry down curve (AUDDC) as the index. Then, we identified 19 and 17 associated SNPs for GWC and AUDDC, including 10 co-localized SNPs, along with 64 and 77 pairs of epistatic SNPs for GWC and AUDDC, respectively. These loci could explain 11.39-68.2% of the total phenotypic variation for GWC and 41.07-67.02% for AUDDC at different stages, whose major effect was the additive and epistatic effect. By exploring the candidate genes around the significant sites, a total of 398 and 457 possible protein-coding genes were screened, including autophagy pathway and auxin regulation-related genes, and five inbred lines with the potential to reduce GWC in the combined F1 hybrid were identified. Our research not only provides a certain reference for the genetic mechanism analysis of GWC in hybrids but also provides an added reference for breeding low-GWC materials.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01349-x.

Meta-QTL analysis explores the key genes, especially hormone related genes, involved in the regulation of grain water content and grain dehydration rate in maize

BACKGROUND

Low grain water content (GWC) at harvest of maize (Zea mays L.) is essential for mechanical harvesting, transportation and storage. Grain drying rate (GDR) is a key determinant of GWC. Many quantitative trait locus (QTLs) related to GDR and GWC have been reported, however, the confidence interval (CI) of these QTLs are too large and few QTLs has been fine-mapped or even been cloned. Meta-QTL (MQTL) analysis is an effective method to integrate QTLs information in independent populations, which helps to understand the genetic structure of quantitative traits.

RESULTS

In this study, MQTL analysis was performed using 282 QTLs from 25 experiments related GDR and GWC. Totally, 11 and 34 MQTLs were found to be associated with GDR and GWC, respectively. The average CI of GDR and GWC MQTLs was 24.44 and 22.13 cM which reduced the 57 and 65% compared to the average QTL interval for initial GDR and GWC QTL, respectively. Finally, 1494 and 5011 candidate genes related to GDR and GWC were identified in MQTL intervals, respectively. Among these genes, there are 48 genes related to hormone metabolism.

CONCLUSIONS

Our studies combined traditional QTL analyses, genome-wide association study and RNA-seq to analysis major locus for regulating GWC in maize.

Physiological and omics analysis of maize inbred lines during late grain development

BACKGROUND

There were significant differences in the change of moisture content and grain composition at the late stage of grain development among different maize varieties, but the regulation mechanism is not clear.

OBJECTIVE

To explore the key genes causing the variation in physiological traits of two typical maize inbred lines in late grain development.

METHODS

The grains at different development stages were selected as materials to determine the content of water, sucrose, starch and ABA. Transcriptomic and proteomic analysis of the materials were performed to screen relevant genes.

RESULTS

The grain dehydration rate and the content of sucrose, starch and ABA were showed significant differences between two varieties in the late stage of grain development. The enrichment analysis of common differentially expressed genes (proteins) showed that most of the genes (proteins) were enriched in the extracellular region. The downregulated genes were mainly concentrated in carbohydrate metabolism and lipid metabolism, while the upregulated genes were mainly in response to stress. Furthermore, this study also identified many key candidate genes (dehydrin genes, pathogenesis-related genes, sucrose synthase and secondary metabolites related genes) related to late grain development of maize.

CONCLUSIONS

The suggested genes related to late grain development of maize can be candidates for further functional study.

Multi-Locus Genome-Wide Association Study and Genomic Selection of Kernel Moisture Content at the Harvest Stage in Maize

Kernel moisture content at the harvest stage (KMC) is an important trait that affects the mechanical harvesting of maize grain, and the identification of genetic loci for KMC is beneficial for maize molecular breeding. In this study, we performed a multi-locus genome-wide association study (ML-GWAS) to identify quantitative trait nucleotides (QTNs) for KMC using an association mapping panel of 251 maize inbred lines that were genotyped with an Affymetrix CGMB56K SNP Array and phenotypically evaluated in three environments. Ninety-eight QTNs for KMC were detected using six ML-GWAS models (mrMLM, FASTmrMLM, FASTmrEMMA, PLARmEB, PKWmEB, and ISIS EM-BLASSO). Eleven of these QTNs were considered to be stable, as they were detected by at least four ML-GWAS models under a uniformed environment or in at least two environments and BLUP using the same ML-GWAS model. With qKMC5.6 removed, the remaining 10 stable QTNs explained <10% of the phenotypic variation, suggesting that KMC is mainly controlled by multiple minor-effect genetic loci. A total of 63 candidate genes were predicted from the 11 stable QTNs, and 10 candidate genes were highly expressed in the kernel at different time points after pollination. High prediction accuracy was achieved when the KMC-associated QTNs were included as fixed effects in genomic selection, and the best strategy was to integrate all KMC QTNs identified by all six ML-GWAS models. These results further our understanding of the genetic architecture of KMC and highlight the potential of genomic selection for KMC in maize breeding.

The genetic architecture of the dynamic changes in grain moisture in maize

Low grain moisture at harvest is crucial for safe production, transport and storage, but the genetic architecture of this trait in maize (Zea mays) remains elusive. Here, we measured the dynamic changes in grain moisture content in an association-mapping panel of 513 diverse maize inbred lines at five successive stages across five geographical environments. Genome-wide association study (GWAS) revealed 71 quantitative trait loci (QTLs) that influence grain moisture in maize. Epistatic effects play vital roles in the variability in moisture levels, even outperforming main-effect QTLs during the early dry-down stages. Distinct QTL-environment interactions influence the spatio-temporal variability of maize grain moisture, which is primarily triggered at specific times. By combining genetic population analysis, transcriptomic profiling and gene editing, we identified GRMZM5G805627 and GRMZM2G137211 as candidate genes underlying major QTLs for grain moisture in maize. Our results provide insights into the genetic architecture of dynamic changes in grain moisture, which should facilitate maize breeding.

Combined linkage mapping and association analysis reveals genetic control of maize kernel moisture content

The free moisture in crop kernels after being naturally dried is referred to as kernel moisture content (KMC). Maize KMC reflects grain quality and influences transportation and storage of seeds. We used an IBM Syn10 DH maize population consisting of 249 lines and an association panel comprising 310 maize inbred lines to identify the genetic loci affecting maize KMC in three environments. Using the IBM population detected 13 QTL on seven chromosomes, which were clustered into nine common QTL. Genome-wide association analysis (GWAS) identified 16 significant SNPs across the 3 environments, which were linked to 158 genes across the three environments. Combined QTL mapping and GWAS found two SNPs that were located in two of the mapped QTL, respectively. Twenty-three genes were linked with the loci co-localized in both populations. Of these 181 genes, five have previously been reported to be associated with KMC or to regulate seed development. These associations were verified by candidate gene association analysis. Two superior alleles and one favorable haplotype for Zm00001d007774 and Zm00001d047868 were found to influence KMC. These findings provide insights into molecular mechanisms underlying maize KMC and contribute to the use of marker-assisted selection for breeding low-KMC maize.

QTL mapping and GWAS for field kernel water content and kernel dehydration rate before physiological maturity in maize

Kernel water content (KWC) and kernel dehydration rate (KDR) are two main factors affecting maize seed quality and have a decisive influence on the mechanical harvest. It is of great importance to map and mine candidate genes related to KWCs and KDRs before physiological maturity in maize. 120 double-haploid (DH) lines constructed from Si287 with low KWC and JiA512 with high KWC were used as the mapping population. KWCs were measured every 5 days from 10 to 40 days after pollination, and KDRs were calculated. A total of 1702 SNP markers were used to construct a linkage map, with a total length of 1,309.02 cM and an average map distance of 0.77 cM. 10 quantitative trait loci (QTLs) and 27 quantitative trait nucleotides (QTNs) were detected by genome-wide composite interval mapping (GCIM) and multi-locus random-SNP-effect mixed linear model (mrMLM), respectively. One and two QTL hotspot regions were found on Chromosome 3 and 7, respectively. Analysis of the Gene Ontology showed that 2 GO terms of biological processes (BP) were significantly enriched (P ≤ 0.05) and 6 candidate genes were obtained. This study provides theoretical support for marker-assisted breeding of mechanical harvest variety in maize.

Discovery and Fine Mapping of qSCR6.01, a Novel Major QTL Conferring Southern Rust Resistance in Maize

Southern corn rust (SCR), an airborne disease caused by Puccinia polysora, can severely reduce the yield of maize (Zea mays L.). Using recombinant inbred lines (RILs) derived from a cross between susceptible inbred line Ye478 and resistant Qi319 in combination with their high-density genetic map, we located five quantitative trait loci (QTLs) against SCR, designated as qSCR3.04, qSCR5.07, qSCR6.01, qSCR9.03, and qSCR10.01, on chromosomes 3, 5, 6, 9, and 10, respectively. Each QTL could explain 2.84 to 24.15% of the total phenotypic variation. qSCR6.01, detected on chromosome 6, with the highest effect value, accounting for 17.99, 23.47, and 24.15% of total phenotypic variation in two environments and best linear unbiased prediction, was a stably major resistance QTL. The common confidence interval for qSCR6.01 was 2.95 Mb based on the B73 RefGen_v3 sequence. The chromosome segment substitution lines (CSSLs) constructed with Qi319 as the donor parent and Ye478 as the recurrent parent were used to further verify qSCR6.01 resistance to SCR. The line CL183 harboring introgressed qSCR6.01 showed obvious resistance to SCR that was distinctly different from that of Ye478 (P = 0.0038). Further mapping of qSCR6.01 revealed that the resistance QTL was linked to insertion-deletion markers Y6q77 and Y6q79, with physical locations of 77.6 and 79.6 Mb, respectively, on chromosome 6. Different from previous major genes or QTLs against SCR on chromosome 10, qSCR6.01 was a newly identified major QTL resistance to SCR on chromosome 6 for the first time. Using RIL and CSSL populations in combination, the SCR-resistance QTL research can be dissected effectively, which provided important gene resource and genetic information for breeding resistant varieties.

Molecular mapping of quantitative trait loci for grain moisture at harvest and field grain drying rate in maize (Zea mays L.)

Maize (Zea mays L.) grain moisture (GM) at harvest is an important trait that affects seed preservation during storage, grain quality and artificial drying costs. To date, most of the work on understanding GM dynamics in maize has focused on the grain filling period, while the period of postmaturity grain drying remains unexplored. The field grain drying rate (FDR) is one of the most important factors in determining GM at harvest. Therefore, understanding the genetic basis of FDR will be useful for obtaining low-GM varieties. In this study, a single-cross population (330 F_2:3 -generation plants) derived from a cross of two divergent inbred lines was evaluated in two planting environments with a measurement method - Area under the Dry Down Curve (AUDDC). A high-density genetic linkage map of 2491 single nucleotide polymorphism (SNP) loci covering 2415.56 cM was constructed. Using composite interval mapping, four quantitative trait loci (QTL), q45dGM1-1, qHTGM2-2, qAUDDC2-1 and qAUDDC10-1, which were detected on chromosomes 1, 2 and 10, were stable across environments and could explain more than 10% of phenotypic variance. These may be the major QTLs, with non-significant environmental interactions for GM at 45 days, GM at harvest and FDR, respectively. Additionally, several predicted candidate genes for FDR were identified, including several transcription factors, hormone responsive genes, energy-related and DNA replication-related genes. These results will provide useful information for our understanding of the genetic basis of FDR, as well as providing tools for marker-assisted selection in maize breeding.

Genetic dissection of grain water content and dehydration rate related to mechanical harvest in maize

BACKGROUND

The low grain water content (GWC) at harvest is a prerequisite to mechanical harvesting in maize, or otherwise would cause massive broken kernels and increase drying costs. The GWC at harvest in turn depends on GWC at the physiological maturity (PM) stage and grain dehydration rate (GDR). Both GWC and GDR are very complex traits, governed by multiple quantitative trait loci (QTL) and easily influenced by environmental conditions. So far, a number of experiments have been conducted to reveal numbers of GWC and GDR QTL, however, very few QTL have been confirmed, and no QTL has been fine-mapped or even been cloned.

RESULTS

We demonstrated that GWCs after PM were positively correlated with GWC at PM, whereas negatively with GDRs after PM. With a recombinant inbred line (RIL) population, we identified totally 31 QTL related to GWC and 17 QTL related to GDR in three field trials. Seven GWC QTL were consistently detected in at least two of the three field trials, each of which could explain 6.92-24.78% of the total GWC variation. Similarly, one GDR QTL was consistently detected, accounting for 9.44-14.46% of the total GDR variation. Three major GWC QTL were found to overlap with three GDR QTL in bins 1.05/06, 2.06/07, and 3.05, respectively. One of the consistent GWC QTL, namely qGwc1.1, was fine-mapped from a 27.22 Mb to a 2.05 Mb region by using recombinant-derived progeny test. The qGwc1.1 acted in a semi-dominant manner to reduce GWC by 1.49-3.31%.

CONCLUSIONS

A number of consistent GWC and GDR QTL have been identified, and one of them, QTL-qGwc1.1, was successfully refined into a 2.05 Mb region. Hence, it is realistic to clone the genes underlying the GWC and GDR QTL and to make use of them in breeding of maize varieties with low GWC at harvest.

Integrating a genome-wide association study with transcriptomic analysis to detect genes controlling grain drying rate in maize (Zea may, L.)

Candidate genes on grain drying rate (GDR) were identified, and drying molecular mechanism of grain was explored by integrating genome-wide association with transcriptomic analysis in maize. Grain drying rate (GDR) is a key determinant of grain moisture at harvest. Here, a genome-wide association study (GWAS) of 309 inbred maize lines was used to identify single-nucleotide polymorphisms (SNPs) associated with drying rates of grain, cob and bract. Out of 217,933 SNPs, seven significant SNPs were repeatedly identified in four environments (P < 10^-4). Based on genomic position of significant SNPs, six candidate genes were identified, one of which (Zm00001d047468) was verified by transcriptomic data between inbred lines with high and low GDR, indicating stable and reliable correlation with GDR. To further detect more genes correlated with GDR and explore drying molecular mechanism of grain, expression profile of all GWAS-identified genes (4941) detected from different environments, tissues and developmental stage was evaluated by transcriptomic data of six inbred lines with high or low GDR. Results revealed 162 genes exhibit up-regulated expression and another 123 down-regulated in three higher-GDR inbred lines. Based on GO enrichment, 162 up-regulated genes were significantly enriched into grain primary metabolic process, nitrogen compound metabolic process and macromolecule metabolic process (P < 0.05), which indicated grain filling imposes notable influence on GDR before and after physiological maturity. Our results lay foundation in accelerating development of higher-GDR maize germplasm through marker-assisted selection and clarifying genetic mechanism of GDR in maize.

Genome-wide association study of kernel moisture content at harvest stage in maize

Kernel moisture content at harvest stage (KMC) is an important factor affecting maize production, especially for mechanical harvesting. We investigated the genetic basis of KMC using an association panel comprising of 144 maize inbred lines that were phenotypically evaluated at two field trial locations. Significant positive or negative correlations were identified between KMC and a series of other agronomic traits, indicating that KMC is associated with other such traits. Combining phenotypic values and the Maize SNP3K Beadchip to perform a genome-wide association study revealed eight single nucleotide polymorphisms (SNPs) associated with KMC at P ≤ 0.001 using a mixed linear model (PCA+K). These significant SNPs could be converted into five quantitative trait loci (QTLs) distributed on chromosomes 1, 5, 8, and 9. Of these QTLs, three were colocalized with genomic regions previously reported. Based on the phenotypic values of the alleles corresponding to significant SNPs, the favorable alleles were mined. Eight maize inbred lines with low KMC and harboring favorable alleles were identified. These QTLs and elite maize inbred lines with low KMC will be useful in maize breeding.

Redefining Agricultural Residues as Bioenergy Feedstocks

The use of plant biomass is a sustainable alternative to the reduction of CO₂ emissions. Agricultural residues are interesting bioenergy feedstocks because they do not compete with food and add extra value to the crop, which might help to manage these residues in many regions. Breeding crops for dual production of food and bioenergy has been reported previously, but the ideal plant features are different when lignocellulosic residues are burnt for heat or electricity, or fermented for biofuel production. Stover moisture is one of the most important traits in the management of agricultural waste for bioenergy production which can be modified by genetic improvement. A delayed leaf senescence or the stay-green characteristic contributes to higher grain and biomass yield in standard, low nutrient, and drought-prone environments. In addition, the stay-green trait could be favorable for the development of dual purpose varieties because this trait could be associated with a reduction in biomass losses and lodging. On the other hand, the stay-green trait could be detrimental for the management of agricultural waste if it is associated with higher stover moisture at harvest, although this hypothesis has been insufficiently tested. In this paper, a review of traits relevant to the development of dual purpose varieties is presented with particular emphasis on stover moisture and stay-green, because less attention has been paid to these important traits in the literature. The possibility of developing new varieties for combined production is discussed from a breeding perspective.

Stability and genetic control of morphological, biomass and biofuel traits under temperate maritime and continental conditions in sweet sorghum (Sorghum bicolour)

Eight morphological, biomass and biofuel traits were found with high broad-sense heritability and 18 significant QTLs discovered including one locus controlling the stem juice trait for sorghum grown in Denmark and China. Sweet sorghum with tall plant, fast maturation and high stem Brix content can be bred as a biofuel crop for Northern Europe. Sweet sorghum (Sorghum bicolour), a native tropical C4 crop, has attracted interest as a bioenergy crop in northern countries due to its juice-rich stem and high biomass production. Little is known about the traits important for its adaptation to high altitude climatic conditions and their genetic controls. Recombinant inbred lines derived from a cross between a sweet and a grain kaoliang sorghum were used in five field trials in Denmark and in China to identify the stability and genetic controls of morphological, biomass and biofuel traits during three consecutive summers with short duration, cool temperatures and long days. Eight out of 15 traits were found with high broad-sense heritability. Strong positive correlations between plant height and biomass traits were observed, while Brix and juice content were under different genetic controls. Using newly developed PAV (presence and absence variant) markers, 53 QTLs were detected, of which 18 were common for both countries, including a locus controlling stem juice (LOD score = 20.5, r (2) = 37.5 %). In Denmark, the heading stage correlated significantly with biomass and morphology traits, and two significant maturity QTLs detected on chromosomes SBI01 and SBI02 co-localised with QTLs previously associated with early-stage chilling tolerance, suggesting that accelerating maturation might be a means of coping with low-temperature stress. Our results suggest that selection for tall and fast maturating sorghum plants combined with high Brix content represents a high potential for breeding bioenergy crop for Northern Europe.

QTLs and candidate genes for desiccation and abscisic acid content in maize kernels

BACKGROUND

Kernel moisture at harvest is an important trait since a low value is required to prevent unexpected early germination and ensure seed preservation. It is also well known that early germination occurs in viviparous mutants, which are impaired in abscisic acid (ABA) biosynthesis. To provide some insight into the genetic determinism of kernel desiccation in maize, quantitative trait loci (QTLs) were detected for traits related to kernel moisture and ABA content in both embryo and endosperm during kernel desiccation. In parallel, the expression and mapping of genes involved in kernel desiccation and ABA biosynthesis, were examined to detect candidate genes.

RESULTS

The use of an intermated recombinant inbred line population allowed for precise QTL mapping. For 29 traits examined in an unreplicated time course trial of days after pollination, a total of 78 QTLs were detected, 43 being related to kernel desiccation, 15 to kernel weight and 20 to ABA content. Multi QTL models explained 35 to 50% of the phenotypic variation for traits related to water status, indicating a large genetic control amenable to breeding. Ten of the 20 loci controlling ABA content colocated with previously detected QTLs controlling water status and ABA content in water stressed leaves. Mapping of candidate genes associated with kernel desiccation and ABA biosynthesis revealed several colocations between genes with putative functions and QTLs. Parallel investigation via RT-PCR experiments showed that the expression patterns of the ABA-responsive Rab17 and Rab28 genes as well as the late embryogenesis abundant Emb5 and aquaporin genes were related to desiccation rate and parental allele effect. Database searches led to the identification and mapping of two zeaxanthin epoxidase (ZEP) and five novel 9-cis-epoxycarotenoid dioxygenase (NCED) related genes, both gene families being involved in ABA biosynthesis. The expression of these genes appeared independent in the embryo and endosperm and not correlated with ABA content in either tissue.

CONCLUSIONS

A high resolution QTL map for kernel desiccation and ABA content in embryo and endosperm showed several precise colocations between desiccation and ABA traits. Five new members of the maize NCED gene family and another maize ZEP gene were identified and mapped. Among all the identified candidates, aquaporins and members of the Responsive to ABA gene family appeared better candidates than NCEDs and ZEPs.

Mapping quantitative trait loci using the experimental designs of recombinant inbred populations

In the data collection of the QTL experiments using recombinant inbred (RI) populations, when individuals are genotyped for markers in a population, the trait values (phenotypes) can be obtained from the genotyped individuals (from the same population) or from some progeny of the genotyped individuals (from the different populations). Let Fu be the genotyped population and Fv (v>or=u) be the phenotyped population. The experimental designs that both marker genotypes and phenotypes are recorded on the same populations can be denoted as (Fu/Fv, u=v) designs and that genotypes and phenotypes are obtained from the different populations can be denoted as (Fu/Fv, v>u) designs. Although most of the QTL mapping experiments have been conducted on the backcross and F2(F2/F2) designs, the other (Fu/Fv, v>or=u) designs are also very popular. The great benefits of using the other (Fu/Fv, v>or=u) designs in QTL mapping include reducing cost and environmental variance by phenotyping several progeny for the genotyped individuals and taking advantages of the changes in population structures of other RI populations. Current QTL mapping methods including those for the (Fu/Fv, u=v) designs, mostly for the backcross or F2/F2 design, and for the F2/F3 design based on a one-QTL model are inadequate for the investigation of the mapping properties in the (Fu/Fv, uor=u) designs. In addition, the QTL mapping properties of the proposed and approximate methods in different designs are discussed. Simulations were performed to evaluate the performance of the proposed and approximate methods. The proposed method is proven to be able to correct the problems of the approximate and current methods for improving the resolution of genetic architecture of quantitative traits and can serve as an effective tool to explore the QTL mapping study in the system of RI populations.