Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping

Quantitative trait locus analysis of gray leaf spot resistance in the maize IBM Syn10 DH population

KEY MESSAGE

The exploration and dissection of a set of QTLs and candidate genes for gray leaf spot disease resistance using two fully assembled parental genomes may help expedite maize resistance breeding. The fungal disease of maize known as gray leaf spot (GLS), caused by Cercospora zeae-maydis and Cercospora zeina, is a significant concern in China, Southern Africa, and the USA. Resistance to GLS is governed by multiple genes with an additive effect and is influenced by both genotype and environment. The most effective way to reduce the cost of production is to develop resistant hybrids. In this study, we utilized the IBM Syn 10 Doubled Haploid (IBM Syn10 DH) population to identify quantitative trait loci (QTLs) associated with resistance to gray leaf spot (GLS) in multiple locations. Analysis of seven distinct environments revealed a total of 58 QTLs, 49 of which formed 12 discrete clusters distributed across chromosomes 1, 2, 3, 4, 8 and 10. By comparing these findings with published research, we identified colocalized QTLs or GWAS loci within eleven clustering intervals. By integrating transcriptome data with genomic structural variations between parental individuals, we identified a total of 110 genes that exhibit both robust disparities in gene expression and structural alterations. Further analysis revealed 19 potential candidate genes encoding conserved resistance gene domains, including putative leucine-rich repeat receptors, NLP transcription factors, fucosyltransferases, and putative xyloglucan galactosyltransferases. Our results provide a valuable resource and linked loci for GLS marker resistance selection breeding in maize.

Combining genome-wide association study and linkage mapping in the genetic dissection of amylose content in maize (Zea mays L.)

KEY MESSAGE

Integrated linkage and association analysis revealed genetic basis across multiple environments. The genes Zm00001d003102 and Zm00001d015905 were further verified to influence amylose content using gene-based association study. Maize kernel amylose is an important source of human food and industrial raw material. However, the genetic basis underlying maize amylose content is still obscure. Herein, we used an intermated B73 × Mo17 (IBM) Syn10 doubled haploid population composed of 222 lines and a germplasm set including 305 inbred lines to uncover the genetic control for amylose content under four environments. Linkage mapping detected 16 unique QTL, among which four were individually repeatedly identified across multiple environments. Genome-wide association study revealed 17 significant (P = 2.24E-06) single-nucleotide polymorphisms, of which two (SYN19568 and PZE-105090500) were located in the intervals of the mapped QTL (qAC2 and qAC5-3), respectively. According to the two population co-localized loci, 20 genes were confirmed as the candidate genes for amylose content. Gene-based association analysis indicated that the variants in Zm00001d003102 (Beta-16-galactosyltransferase GALT29A) and Zm00001d015905 (Sugar transporter 4a) affected amylose content across multi-environment. Tissue expression analysis showed that the two genes were specifically highly expressed in the ear and stem, respectively, suggesting that they might participate in sugar transport from source to sink organs. Our study provides valuable genetic information for breeding maize varieties with high amylose.

DEK219 and HSF17 Collaboratively Regulate the Kernel Length in Maize

The kernel length is a crucial determinant of maize (Zea mays L.) yield; however, only a limited number of genes regulating kernel length have been validated, thus leaving our understanding of the mechanisms governing kernel length incomplete. We previously identified a maize kernel mutant, defective kernel219 (dek219), which encodes the DICER-LIKE1 protein that is essential for miRNA biogenesis. The present study revealed that dek219 consistently exhibits a stable phenotype characterized by a reduced kernel length. Further analysis indicated that dek219 may reduce the kernel length by inhibiting the expression of genes involved in regulating kernel length. By employing miRNA-target gene prediction, expression analysis, and correlation analysis, we successfully identified nine transcription factors that potentially participate in the regulation of kernel length under the control of DEK219. Among them, the upregulation fold change of HEAT SHOCK TRANSCRIPTION FACTOR17 (HSF17) expression was the highest, and the difference was most significant. The results of transient expression analysis and electrophoretic mobility shift assay (EMSA) indicated that HSF17 can inhibit the expression of DEFECTIVE ENDOSPERM18 (DE18), a gene involved in regulating kernel length. Furthermore, the hsf17 mutant exhibited a significant increase in kernel length, suggesting that HSF17 functions as a negative regulator of kernel length. The results of this study provide crucial evidence for further elucidating the molecular regulatory mechanism underlying maize kernel length and also offer valuable genetic resources for breeding high-yielding maize varieties.

A combination of QTL mapping and genome-wide association study revealed the key gene for husk number in maize

KEY MESSAGE

Two key genes Zm00001d021232 and Zm00001d048138 were identified by QTL mapping and GWAS. Additionally, they were verified to be significantly associated with maize husk number (HN) using gene-based association study. As a by-product of maize production, maize husk is an important industrial raw material. Husk layer number (HN) is an important trait that affects the yield of maize husk. However, the genetic mechanism underlying HN remains unclear. Herein, a total of 13 quantitative trait loci (QTL) controlling HN were identified in an IBM Syn 10 DH population across different locations. Among these, three QTL were individually repeatedly detected in at least two environments. Meanwhile, 26 unique single nucleotide polymorphisms (SNPs) were detected to be significantly (p < 2.15 × 10-6) associated with HN in an association pool. Of these SNPs, three were simultaneously detected across multiple environments or environments and best linear unbiased prediction (BLUP). We focused on these environment-stable and population-common genetic loci for excavating the candidate genes responsible for maize HN. Finally, 173 initial candidate genes were identified, of which 22 were involved in both multicellular organism development and single-multicellular organism process and thus confirmed as the candidate genes for HN. Gene-based association analyses revealed that the variants in four genes were significantly (p < 0.01/N) correlated with HN, of which Zm00001d021232 and Zm00001d048138 were highly expressed in husks and early developing ears among different maize tissues. Our study contributes to the understanding of genetic and molecular mechanisms of maize husk yield and industrial development in the future.

Genetic basis of maize stalk strength decoded via linkage and association mapping

Stalk lodging is a severe problem that limits maize production worldwide, although little attention has been given to its genetic basis. Here we measured rind penetrometer resistance (RPR), an effective index for stalk lodging, in a multi-parent population of 1948 recombinant inbred lines (RILs) and an association population of 508 inbred lines (AMP508). Linkage and association mapping identified 53 and 29 single quantitative trait loci (QTLs) and 50 and 19 pairs of epistatic interactions for RPR in the multi-parent population and AMP508 population, respectively. Phenotypic variation explained by all identified epistatic QTLs (up to ~5%) was much less than that explained by all single additive QTLs (up to ~33% in the multi-parent population and ~ 60% in the AMP508 population). Among all detected QTLs, only eight single QTLs explained >10% of phenotypic variation in single RIL populations. Alleles that increased RPR were enriched in tropical/subtropical (TST) groups from the AMP508 population. Based on genome-wide association studies in both populations, we identified 137 candidate genes affecting RPR, which were assigned to multiple biological processes, such as the biosynthesis of cell wall components. Sixty-six candidate genes were cross-validated by multiple methods or populations. Most importantly, 23 candidate genes were upregulated or downregulated in high-RPR lines relative to low-RPR lines, supporting the associations between candidate genes and RPR. These findings reveal the complex nature of the genetic basis underlying RPR and provide loci or candidate genes for developing elite varieties that are resistant to stalk lodging via molecular breeding.

Hotspot Regions of Quantitative Trait Loci and Candidate Genes for Ear-Related Traits in Maize: A Literature Review

In this study, hotspot regions, QTL clusters, and candidate genes for eight ear-related traits of maize (ear length, ear diameter, kernel row number, kernel number per row, kernel length, kernel width, kernel thickness, and 100-kernel weight) were summarized and analyzed over the past three decades. This review aims to (1) comprehensively summarize and analyze previous studies on QTLs associated with these eight ear-related traits and identify hotspot bin regions located on maize chromosomes and key candidate genes associated with the ear-related traits and (2) compile major and stable QTLs and QTL clusters from various mapping populations and mapping methods and techniques providing valuable insights for fine mapping, gene cloning, and breeding for high-yield and high-quality maize. Previous research has demonstrated that QTLs for ear-related traits are distributed across all ten chromosomes in maize, and the phenotypic variation explained by a single QTL ranged from 0.40% to 36.76%. In total, 23 QTL hotspot bins for ear-related traits were identified across all ten chromosomes. The most prominent hotspot region is bin 4.08 on chromosome 4 with 15 QTLs related to eight ear-related traits. Additionally, this study identified 48 candidate genes associated with ear-related traits. Out of these, five have been cloned and validated, while twenty-eight candidate genes located in the QTL hotspots were defined by this study. This review offers a deeper understanding of the advancements in QTL mapping and the identification of key candidates associated with eight ear-related traits. These insights will undoubtedly assist maize breeders in formulating strategies to develop higher-yield maize varieties, contributing to global food security.

Identification of Multiple Genetic Loci Related to Low-Temperature Tolerance during Germination in Maize (Zea maize L.) through a Genome-Wide Association Study

Low-temperature stress during the germination stage is an important abiotic stress that affects the growth and development of northern spring maize and seriously restricts maize yield and quality. Although some quantitative trait locis (QTLs) related to low-temperature tolerance in maize have been detected, only a few can be commonly detected, and the QTL intervals are large, indicating that low-temperature tolerance is a complex trait that requires more in-depth research. In this study, 296 excellent inbred lines from domestic and foreign origins (America and Europe) were used as the study materials, and a low-coverage resequencing method was employed for genome sequencing. Five phenotypic traits related to low-temperature tolerance were used to assess the genetic diversity of maize through a genome-wide association study (GWAS). A total of 14 SNPs significantly associated with low-temperature tolerance were detected (-log10(P) > 4), and an SNP consistently linked to low-temperature tolerance in the field and indoors during germination was utilized as a marker. This SNP, 14,070, was located on chromosome 5 at position 2,205,723, which explained 4.84-9.68% of the phenotypic variation. The aim of this study was to enrich the genetic theory of low-temperature tolerance in maize and provide support for the innovation of low-temperature tolerance resources and the breeding of new varieties.

Genetic architecture of source-sink-regulated senescence in maize

Source and sink interactions play a critical but mechanistically poorly understood role in the regulation of senescence. To disentangle the genetic and molecular mechanisms underlying source-sink-regulated senescence (SSRS), we performed a phenotypic, transcriptomic, and systems genetics analysis of senescence induced by the lack of a strong sink in maize (Zea mays). Comparative analysis of genotypes with contrasting SSRS phenotypes revealed that feedback inhibition of photosynthesis, a surge in reactive oxygen species, and the resulting endoplasmic reticulum (ER) stress were the earliest outcomes of weakened sink demand. Multienvironmental evaluation of a biparental population and a diversity panel identified 12 quantitative trait loci and 24 candidate genes, respectively, underlying SSRS. Combining the natural diversity and coexpression networks analyses identified 7 high-confidence candidate genes involved in proteolysis, photosynthesis, stress response, and protein folding. The role of a cathepsin B like protease 4 (ccp4), a candidate gene supported by systems genetic analysis, was validated by analysis of natural alleles in maize and heterologous analyses in Arabidopsis (Arabidopsis thaliana). Analysis of natural alleles suggested that a 700-bp polymorphic promoter region harboring multiple ABA-responsive elements is responsible for differential transcriptional regulation of ccp4 by ABA and the resulting variation in SSRS phenotype. We propose a model for SSRS wherein feedback inhibition of photosynthesis, ABA signaling, and oxidative stress converge to induce ER stress manifested as programed cell death and senescence. These findings provide a deeper understanding of signals emerging from loss of sink strength and offer opportunities to modify these signals to alter senescence program and enhance crop productivity.

GWAS and Meta-QTL Analysis of Yield-Related Ear Traits in Maize

Maize ear traits are an important component of yield, and the genetic basis of ear traits facilitates further yield improvement. In this study, a panel of 580 maize inbred lines were used as the study material, eight ear-related traits were measured through three years of planting, and whole genome sequencing was performed using the maize 40 K breeding chip based on genotyping by targeted sequencing (GBTS) technology. Five models were used to conduct a genome-wide association study (GWAS) on best linear unbiased estimate (BLUE) of ear traits to find the best model. The FarmCPU (Fixed and random model Circulating Probability Unification) model was the best model for this study; a total of 104 significant single nucleotide polymorphisms (SNPs) were detected, and 10 co-location SNPs were detected simultaneously in more than two environments. Through gene function annotation and prediction, a total of nine genes were identified as potentially associated with ear traits. Moreover, a total of 760 quantitative trait loci (QTL) associated with yield-related traits reported in 37 different articles were collected. Using the collected 760 QTL for meta-QTL analysis, a total of 41 MQTL (meta-QTL) associated with yield-related traits were identified, and 19 MQTL detected yield-related ear trait functional genes and candidate genes that have been reported in maize. Five significant SNPs detected by GWAS were located within these MQTL intervals, and another three significant SNPs were close to MQTL (less than 1 Mb). The results provide a theoretical reference for the analysis of the genetic basis of ear-related traits and the improvement of maize yield.

QTL analysis of traits related to seed size and shape in sesame (Sesamum indicum L.)

Seed size and shape are important traits that determine seed yield in sesame. Understanding the genetic basis of seed size and shape is essential for improving the yield of sesame. In this study, F2 and BC1 populations were developed by crossing the Yuzhi 4 and Bengal small-seed (BS) lines for detecting the quantitative trait loci (QTLs) of traits related to seed size and shape. A total of 52 QTLs, including 13 in F2 and 39 in BC1 populations, for seed length (SL), seed width (SW), and length to width ratio (L/W) were identified, explaining phenotypic variations from 3.68 to 21.64%. Of these QTLs, nine stable major QTLs were identified in the two populations. Notably, three major QTLs qSL-LG3-2, qSW-LG3-2, and qSW-LG3-F2 that accounted for 4.94-16.34% of the phenotypic variations were co-localized in a 2.08 Mb interval on chromosome 1 (chr1) with 279 candidate genes. Three stable major QTLs qSL-LG6-2, qLW-LG6, and qLW-LG6-F2 that explained 8.14-33.74% of the phenotypic variations were co-localized in a 3.27 Mb region on chr9 with 398 candidate genes. In addition, the stable major QTL qSL-LG5 was co-localized with minor QTLs qLW-LG5-3 and qSW-LG5 to a 1.82 Mb region on chr3 with 195 candidate genes. Gene annotation, orthologous gene analysis, and sequence analysis indicated that three genes are likely involved in sesame seed development. These results obtained herein provide valuable in-formation for functional gene cloning and improving the seed yield of sesame.

Integrated genome-wide association study and QTL mapping reveals qSa-3A associated with English grain aphid, Sitobion avenae (Fabricius) resistance in wheat

BACKGROUND

The English grain aphid, Sitobion avenae (Fabricius), is a devastating pest impacts yield and quality in wheat (Triticum aestivum L.). Breeding resistant wheat varieties and detecting resistance genes are important strategies to control aphid.

RESULTS

In this study, we evaluated the number of aphids per spike, the rate of thousand kernel weight decrease and aphid index based on three classic resistance mechanisms (antibiosis, tolerance and antixenosis), and detected SNPs/QTLs for resistance to S. avenae in a natural population of 163 varieties with 20 689 high-quality single-nucleotide polymorphism (SNP) markers and recombinant inbred line (RIL) population of 164 lines with 3627 diversity arrays technology (DArT) markers. Results showed that 83 loci significantly associated with S. avenae antibiosis and 182 loci significantly associated with S. avenae tolerance were detected by genome-wide association study (GWAS), explaining 6.47-15.82% and 8.36-35.61% of the phenotypic variances, respectively. The wsnp_Ku_c4568_8243646 detected in two periods was localized at 34.52 Mb on chromosome 3AS. Then, we confirmed a stable QSa.haust-3A.2 explained 11.19-20.10% of the phenotypic variances in two periods with S. avenae antixenosis in the physical interval of 37.49-37.50 Mb on chromosome 3A in the RIL population. Therefore, a narrow region in the physical interval of 34.52-37.50 Mb on chromosome 3AS was named as qSa-3A, which was a new locus between wsnp_Ku_c4568_8243646 and QSa.haust-3A.2 associated with S. avenae resistance.

CONCLUSION

We found qSa-3A was a new locus associated with S. avenae resistance. The results could be applied in gene cloning and genetic improvement of S. avenae resistance in wheat. © 2023 Society of Chemical Industry.

Evaluating the Genetic Background Effect on Dissecting the Genetic Basis of Kernel Traits in Reciprocal Maize Introgression Lines

Maize yield is mostly determined by its grain size. Although numerous quantitative trait loci (QTL) have been identified for kernel-related traits, the application of these QTL in breeding programs has been strongly hindered because the populations used for QTL mapping are often different from breeding populations. However, the effect of genetic background on the efficiency of QTL and the accuracy of trait genomic prediction has not been fully studied. Here, we used a set of reciprocal introgression lines (ILs) derived from 417F × 517F to evaluate how genetic background affects the detection of QTLassociated with kernel shape traits. A total of 51 QTL for kernel size were identified by chromosome segment lines (CSL) and genome-wide association studies (GWAS) methods. These were subsequently clustered into 13 common QTL based on their physical position, including 7 genetic-background-independent and 6 genetic-background-dependent QTL, respectively. Additionally, different digenic epistatic marker pairs were identified in the 417F and 517F ILs. Therefore, our results demonstrated that genetic background strongly affected not only the kernel size QTL mapping via CSL and GWAS but also the genomic prediction accuracy and epistatic detection, thereby enhancing our understanding of how genetic background affects the genetic dissection of grain size-related traits.

GWAS across multiple environments and WGCNA suggest the involvement of ZmARF23 in embryonic callus induction from immature maize embryos

Combined GWAS, WGCNA, and gene-based association studies identified the co-expression network and hub genes for maize EC induction. ZmARF23 bound to ZmSAUR15 promoter and regulated its expression, affecting EC induction. Embryonic callus (EC) induction in immature maize embryos shows high genotype dependence, which limits the application of genetic transformation in transgenic breeding and gene function elucidation in maize. Herein, we conducted a genome-wide association mapping (GWAS) for four EC induction-related traits, namely rate of embryonic callus induction (REC), increased callus diameter (ICD), ratio of shoot formation (RSF), and length of shoot (LS) across different environments. A total of 77 SNPs were significantly associated these traits under three environments and using the averages (across environments). Among these significant SNPs, five were simultaneously detected under multiple environments and 11 had respective phenotypic variation explained > 10%. A total of 257 genes were located in the linkage disequilibrium decay of these REC- and ICD-associated SNPs, of which 178 were responsive to EC induction. According to the expression values of the 178 genes, we performed a weighted gene co-expression network analysis (WGCNA) and revealed an EC induction-associated module and five hub genes. Hub gene-based association studies uncovered that the intragenic variations in GRMZM2G105473 and ZmARF23 influenced EC induction efficiency among different maize lines. Dual-luciferase reporter assay indicated that ZmARF23 bound to the promoter of a known causal gene (ZmSAUR15) for EC induction and positively regulated its expression on the transcription level. Our study will deepen the understanding of genetic and molecular mechanisms underlying EC induction and contribute to the use of genetic transformation in maize.

Large-scale population structure and genetic architecture of agronomic traits of garlic

Garlic, an asexually propagated crop, is the second important bulb crop after the onion and is used as a vegetable and medicinal plant. Abundant and diverse garlic resources have been formed over thousands of years of cultivation. However, genome variation, population structure and genetic architecture of garlic agronomic traits were still not well elucidated. Here, 1 100 258 single nucleotide polymorphisms (SNPs) were identified using genotyping-by-sequencing in 606 garlic accessions collected from 43 countries. Population structure, principal component and phylogenetic analysis showed that these accessions were divided into five subpopulations. Twenty agronomic traits, including above-ground growth traits, bulb-related and bolt-related traits in two consecutive years were implemented in a genome-wide association study. In total, 542 SNPs were associated with these agronomic traits, among which 188 SNPs were repeatedly associated with more than two traits. One SNP (chr6: 1896135972) was repeatedly associated with ten traits. These associated SNPs were located within or near 858 genes, 56 of which were transcription factors. Interestingly, one non-synonymous SNP (Chr4: 166524085) in ribosomal protein S5 was repeatedly associated with above-ground growth and bulb-related traits. Additionally, gene ontology enrichment analysis of candidate genes for genomic selection regions between complete-bolting and non-bolting accessions showed that these genes were significantly enriched in 'vegetative to reproductive phase transition of meristem', 'shoot system development', 'reproductive process', etc. These results provide valuable information for the reliable and efficient selection of candidate genes to achieve garlic genetic improvement and superior varieties.

Genetic dissection of embryo size and weight related traits for enhancement of kernel oil in maize

Embryo is a key determinant of kernel-oil in maize. Higher calorific value of maize kernel is attributed to increment in kernel-oil and it stores in specialised structure called embryo. Understanding the genetic behaviour of embryo size and weight related-traits is inevitable task for genetic improvement of kernel-oil. Here, the six-basic generations (P₁, P₂, F₁, F₂, BC₁P₁ and BC₁P₂) of three crosses (CRPBIO-962 × EC932601, CRPBIO-973 × CRPBIO-966 and CRPBIO-966 × CRPBIO-979) between contrasting embryo-sized maize inbreds were field evaluated at three locations to decipher the genetics of twenty embryo, kernel and embryo-to-kernel related-traits through generation-mean-analysis (GMA). Combined ANOVA revealed the significance of all the traits among generations; however, location and generation × location were found to be non-significant (P > 0.05) for most of the traits. Significance (P < 0.05) of scaling and joint-scaling tests revealed the presence of non-allelic interactions. Elucidation of six-parameters disclosed the predominance of dominance main-effect (h) and dominance × dominance interaction-effect (l) for most of traits. The signs of (h) and (l) indicated the prevalence of duplicate-epistasis type across crosses and locations. Thus, the population improvement approaches along with heterosis breeding method could be effective for improvement of these traits. Quantitative inheritance pattern was observed for all the traits with high broad-sense heritability and better-stability across locations. The study also predicted one to three major-gene blocks/QTLs for embryo-traits and up to 11 major-gene blocks/QTLs for embryo-to-kernel traits. These findings could provide deep insights to strategize extensive breeding methods to improve embryo traits for enhancing kernel-oil in sustainable manner.

Genetic Localization and Homologous Genes Mining for Barley Grain Size

Grain size is an important agronomic trait determining barley yield and quality. An increasing number of QTLs (quantitative trait loci) for grain size have been reported due to the improvement in genome sequencing and mapping. Elucidating the molecular mechanisms underpinning barley grain size is vital for producing elite cultivars and accelerating breeding processes. In this review, we summarize the achievements in the molecular mapping of barley grain size over the past two decades, highlighting the results of QTL linkage analysis and genome-wide association studies. We discuss the QTL hotspots and predict candidate genes in detail. Moreover, reported homologs that determine the seed size clustered into several signaling pathways in model plants are also listed, providing the theoretical basis for mining genetic resources and regulatory networks of barley grain size.

QTL mapping of maize (Zea mays L.) kernel traits under low-phosphorus stress

Low-phosphorus stress significantly impacts the development of maize kernels. In this study, the phosphor efficient maize genotype 082 and phosphor deficient maize genotype Ye107, were used to construct an F2:3 population. QTL mapping was then employed to determine the genetic basis of differences in the maize kernel traits of the two parents in a low-phosphorus environment. This analysis revealed several major QTL that control environmental impacts on kernel length, width, thickness, and weight. These QTL were detected in all three environments and were distributed on five genome segments of chromosomes 3, 5, 6, and 9, and some new kernel-trait QTL were also detected (eg: Qkwid6, Qkthi3, Qkwei9, and Qklen3-1). These environmentally insensitive QTL can be stably expressed in low phosphorus environments, indicating that they can lay a foundation for the breeding of high phosphorus utilization efficiency germplasm.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-023-01300-0.

Combined linkage mapping and association analysis uncovers candidate genes for 25 leaf-related traits across three environments in maize

Combined linkage and association analysis revealed five co-localized genetic loci across multiple environments. The key gene Zm00001d026491 was further verified to influence leaf length by candidate gene association analysis. Leaf morphology and number determine the canopy structure and thus affect crop yield. Herein, the genetic basis and key genes for 25 leaf-related traits, including leaf lengths (LL), leaf widths (LW), and leaf areas (LA) of eight continuous leaves under the tassel, and the number of leaves above the primary ear (LAE), were dissected by using an association panel and a biparental population. Using an intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, 290 quantitative trait loci (QTL) controlling these traits were detected across different locations, among which 115 QTL were individually repeatedly identified in at least two environments. Using the association panel, 165 unique significant single-nucleotide polymorphisms (SNPs) were associated with target traits (P < 2.15E-06), of which 35 were separately detected across multiple environments. In total, 42 pleiotropic QTL/SNPs (pQTL/SNPs) were responsible for at least two of the LL, LW, LA, and LAE traits across multiple environments. Combining the QTL mapping and association study, five unique SNPs were located within the confidence intervals of seven QTL, and 77 genes were identified based on the linkage disequilibrium regions of co-localized SNP loci. Gene-based association studies verified that the intragenic variants in the candidate gene Zm00001d026491 influenced LL of the third leaf counted from the top node. These findings will provide vital information to understanding the genetic basis of leaf-related traits and help to cultivate maize varieties with ideal plant architecture.

The role of transposon inverted repeats in balancing drought tolerance and yield-related traits in maize

The genomic basis underlying the selection for environmental adaptation and yield-related traits in maize remains poorly understood. Here we carried out genome-wide profiling of the small RNA (sRNA) transcriptome (sRNAome) and transcriptome landscapes of a global maize diversity panel under dry and wet conditions and uncover dozens of environment-specific regulatory hotspots. Transgenic and molecular studies of Drought-Related Environment-specific Super eQTL Hotspot on chromosome 8 (DRESH8) and ZmMYBR38, a target of DRESH8-derived small interfering RNAs, revealed a transposable element-mediated inverted repeats (TE-IR)-derived sRNA- and gene-regulatory network that balances plant drought tolerance with yield-related traits. A genome-wide scan revealed that TE-IRs associate with drought response and yield-related traits that were positively selected and expanded during maize domestication. These results indicate that TE-IR-mediated posttranscriptional regulation is a key molecular mechanism underlying the tradeoff between crop environmental adaptation and yield-related traits, providing potential genomic targets for the breeding of crops with greater stress tolerance but uncompromised yield.

MicroRNAs modulating nutrient homeostasis: a sustainable approach for developing biofortified crops

During their lifespan, sessile plants have to cope with bioavailability of the suboptimal nutrient concentration and have to constantly sense/evolve the connecting web of signal cascades for efficient nutrient uptake, storage, and translocation for proper growth and metabolism. However, environmental fluctuations and escalating anthropogenic activities are making it a formidable challenge for plants. This is adding to (micro)nutrient-deficient crops and nutritional insecurity. Biofortification is emerging as a sustainable and efficacious approach which can be utilized to combat the micronutrient malnutrition. A biofortified crop has an enriched level of desired nutrients developed using conventional breeding, agronomic practices, or advanced biotechnological tools. Nutrient homeostasis gets hampered under nutrient stress, which involves disturbance in short-distance and long-distance cell-cell/cell-organ communications involving multiple cellular and molecular components. Advanced sequencing platforms coupled with bioinformatics pipelines and databases have suggested the potential roles of tiny signaling molecules and post-transcriptional regulators, the microRNAs (miRNAs) in key plant phenomena including nutrient homeostasis. miRNAs are seen as emerging targets for biotechnology-based biofortification programs. Thus, understanding the mechanistic insights and regulatory role of miRNAs could open new windows for exploring them in developing nutrient-efficient biofortified crops. This review discusses significance and roles of miRNAs in plant nutrition and nutrient homeostasis and how they play key roles in plant responses to nutrient imbalances/deficiencies/toxicities covering major nutrients-nitrogen (N), phosphorus (P), sulfur (S), magnesium (Mg), iron (Fe), and zinc (Zn). A perspective view has been given on developing miRNA-engineered biofortified crops with recent success stories. Current challenges and future strategies have also been discussed.

An Integration of Linkage Mapping and GWAS Reveals the Key Genes for Ear Shank Length in Maize

Ear shank length (ESL) has significant effects on grain yield and kernel dehydration rate in maize. Herein, linkage mapping and genome-wide association study were combined to reveal the genetic architecture of maize ESL. Sixteen quantitative trait loci (QTL) were identified in the segregation population, among which five were repeatedly detected across multiple environments. Meanwhile, 23 single nucleotide polymorphisms were associated with the ESL in the association panel, of which four were located in the QTL identified by linkage mapping and were designated as the population-common loci. A total of 42 genes residing in the linkage disequilibrium regions of these common variants and 12 of them were responsive to ear shank elongation. Of the 12 genes, five encode leucine-rich repeat receptor-like protein kinases, proline-rich proteins, and cyclin11, respectively, which were previously shown to regulate cell division, expansion, and elongation. Gene-based association analyses revealed that the variant located in Cyclin11 promoter affected the ESL among different lines. Cyclin11 showed the highest expression in the ear shank 15 days after silking among diverse tissues of maize, suggesting its role in modulating ESL. Our study contributes to the understanding of the genetic mechanism underlying maize ESL and genetic modification of maize dehydration rate and kernel yield.

Genome-wide association studies for soybean epicotyl length in two environments using 3VmrMLM

Germination of soybean seed is the imminent vital process after sowing. The status of plumular axis and radicle determine whether soybean seed can emerge normally. Epicotyl, an organ between cotyledons and first functional leaves, is essential for soybean seed germination, seedling growth and early morphogenesis. Epicotyl length (EL) is a quantitative trait controlled by multiple genes/QTLs. Here, the present study analyzes the phenotypic diversity and genetic basis of EL using 951 soybean improved cultivars and landraces from Asia, America, Europe and Africa. 3VmrMLM was used to analyze the associations between EL in 2016 and 2020 and 1,639,846 SNPs for the identification of QTNs and QTN-by-environment interactions (QEIs)".A total of 180 QTNs and QEIs associated with EL were detected. Among them, 74 QTNs (ELS_Q) and 16 QEIs (ELS_QE) were identified to be associated with ELS (epicotyl length of single plant emergence), and 60 QTNs (ELT_Q) and 30 QEIs (ELT_QE) were identified to be associated with ELT (epicotyl length of three seedlings). Based on transcript abundance analysis, GO (Gene Ontology) enrichment and haplotype analysis, ten candidate genes were predicted within nine genic SNPs located in introns, upstream or downstream, which were supposed to be directly or indirectly involved in the process of seed germination and seedling development., Of 10 candidate genes, two of them (Glyma.04G122400 and Glyma.18G183600) could possibly affect epicotyl length elongation. These results indicate the genetic basis of EL and provides a valuable basis for specific functional studies of epicotyl traits.

Global transcriptome analysis reveals potential genes associated with genic male sterility of rapeseed (Brassica napus L.)

Rapeseed is the third leading source of edible oil in the world. Genic male sterility (GMS) lines provide crucial material for harnessing heterosis for rapeseed. GMS lines have been widely used successfully for rapeseed hybrid production. The physiological and molecular mechanism of pollen development in GMS lines of rapeseed (Brassica napus L.) need to be determined for the creation of hybrids and cultivation of new varieties. However, limited studies have focused on systematically mining genes that regulate the pollen development of GMS lines in B. napus. In the present study, to determine the stage at which pollen development begins to show abnormality in the GMS lines, we performed semi-thin section analysis of the anthers with five pollen development stages. The results indicated that the abnormal pollen development in DGMS lines might start at the meiotic stage, and abnormal pollen development in RGMS lines probably occurred before the tetrad stage. To investigate the critical genes and pathways involved in pollen development in GMS lines, we constructed and sequenced 24 transcriptome libraries for the flower buds from the fertile and sterile lines of two recessive GMS (RGMS) lines (6251AB and 6284AB) and two dominant GMS (DGMS) lines (4001AB and 4006AB). A total of 23,554 redundant DEGs with over two-fold change between sterile and fertile lines were obtained. A total of 346 DEGs were specifically related to DGMS, while 1,553 DEGs were specifically related to RGMS. A total of 1,545 DEGs were shared between DGMS and RGMS. And 253 transcription factors were found to be differentially expressed between the sterile and fertile lines of GMS. In addition, 6,099 DEGs possibly related to anther, pollen, and microspore development processes were identified. Many of these genes have been reported to be involved in anther and microspore developmental processes. Several DEGs were speculated to be key genes involved in the regulation of fertility. Three differentially expressed genes were randomly selected and their expression levels were verified by quantitative PCR (qRT-PCR). The results of qRT-PCR largely agreed with the transcriptome sequencing results. Our findings provide a global view of genes that are potentially involved in GMS occurrence. The expression profiles and function analysis of these DEGs were provided to expand our understanding of the complex molecular mechanism in pollen and sterility development in B. napus.

Genome wide association analysis for yield related traits in maize

BACKGROUND

Understanding the genetic basis of yield related traits contributes to the improvement of grain yield in maize.

RESULTS

Using 291 excellent maize inbred lines as materials, six yield related traits of maize, including grain yield per plant (GYP), grain length (GL), grain width (GW), kernel number per row (KNR), 100 kernel weight (HKW) and tassel branch number (TBN) were investigated in Jinan, in 2017, 2018 and 2019. The average values of three environments were taken as the phenotypic data of yield related traits, and they were statistically analyzed. Based on 38,683 high-quality SNP markers in the whole genome of the association panel, the MLM with PCA model was used for genome-wide association analysis (GWAS) to obtain 59 significantly associated SNP sites. Moreover, 59 significantly associated SNPs (P < 0.0001) referring to GYP, GL, GW, KNR, HKW and TBN, of which 14 SNPs located in yield related QTLs/QTNs previously reported. A total of 66 candidate genes were identified based on the 59 significantly associated SNPs, of which 58 had functional annotation.

CONCLUSIONS

Using genome-wide association analysis strategy to identify genetic loci related to maize yield, a total of 59 significantly associated SNP were detected. Those results aid in our understanding of the genetic architecture of maize yield and provide useful SNPs for genetic improvement of maize.

Genome-Wide Association Study Reveals the Genetic Basis of Kernel and Cob Moisture Changes in Maize at Physiological Maturity Stage

Low moisture content (MC) and high dehydration rate (DR) at physiological maturity affect grain mechanical harvest, transport, and storage. In this study, we used an association panel composed of 241 maize inbred lines to analyze ear moisture changes at physiological maturity stage. A genome-wide association study revealed nine significant SNPs and 91 candidate genes. One SNP (SYN38588) was repeatedly detected for two traits, and 15 candidate genes were scanned in the linkage disequilibrium regions of this SNP. Of these, genes Zm00001d020615 and Zm00001d020623 were individually annotated as a polygalacturonase (PG) and a copper transporter 5.1 (COPT5.1), respectively. Candidate gene association analysis showed that three SNPs located in the exons of Zm00001d020615 were significantly associated with the dehydration rate, and AATTAA was determined as the superior haplotype. All these findings suggested that Zm00001d020615 was a key gene affecting moisture changes of maize at the physiological maturity stage. These results have demonstrated the genetic basis of ear moisture changes in maize and indicated a superior haplotype for cultivating maize varieties with low moisture content and high dehydration rates.

Genome-Wide Association Analysis for Candidate Genes Contributing to Kernel-Related Traits in Maize

Maize grain size is the main factor determining grain yield. Dissecting the genetic basis of maize grain size may help reveal the regulatory mechanism of maize seed development and yield formation. In this study, two associated populations were used for genome-wide association analysis of kernel length, kernel width, kernel thickness, and hundred-kernel weight from multiple locations in AM122 and AM180, respectively. Then, genome-wide association mapping was performed based on the maize 6H90K SNP chip. A total of 139 loci were identified as associated with the four traits with p < 1 × 10^-4 using two models (FarmCPU and MLM). The transcriptome data showed that 15 of them were expressed differentially in two maize-inbred lines KB182 (small kernel) and KB020 (big kernel) during kernel development. These candidate genes were enriched in regulating peroxidase activity, oxidoreductase, and leaf senescence. The molecular function was major in binding and catalytic activity. This study provided important reference information for exploring maize kernel development mechanisms and applying molecular markers in high-yield breeding.

Linkage and association analyses reveal that hub genes in energy-flow and lipid biosynthesis pathways form a cluster in upland cotton

Upland cotton is an important allotetraploid crop that provides both natural fiber for the textile industry and edible vegetable oil for the food or feed industry. To better understand the genetic mechanism that regulates the biosynthesis of storage oil in cottonseed, we identified the genes harbored in the major quantitative trait loci/nucleotides (QTLs/QTNs) of kernel oil content (KOC) in cottonseed via both multiple linkage analyses and genome-wide association studies (GWAS). In ‘CCRI70′ RILs, six stable QTLs were simultaneously identified by linkage analysis of CHIP and SLAF-seq strategies. In ‘0-153′ RILs, eight stable QTLs were detected by consensus linkage analysis integrating multiple strategies. In the natural panel, thirteen and eight loci were associated across multiple environments with two algorithms of GWAS. Within the confidence interval of a major common QTL on chromosome 3, six genes were identified as participating in the interaction network highly correlated with cottonseed KOC. Further observations of gene differential expression showed that four of the genes, LtnD, PGK, LPLAT1, and PAH2, formed hub genes and two of them, FER and RAV1, formed the key genes in the interaction network. Sequence variations in the coding regions of LtnD, FER, PGK, LPLAT1, and PAH2 genes may support their regulatory effects on oil accumulation in mature cottonseed. Taken together, clustering of the hub genes in the lipid biosynthesis interaction network provides new insights to understanding the mechanism of fatty acid biosynthesis and TAG assembly and to further genetic improvement projects for the KOC in cottonseeds.

Genetic Architecture of Grain Yield-Related Traits in Sorghum and Maize

Grain size, grain number per panicle, and grain weight are crucial determinants of yield-related traits in cereals. Understanding the genetic basis of grain yield-related traits has been the main research object and nodal in crop science. Sorghum and maize, as very close C4 crops with high photosynthetic rates, stress tolerance and large biomass characteristics, are extensively used to produce food, feed, and biofuels worldwide. In this review, we comprehensively summarize a large number of quantitative trait loci (QTLs) associated with grain yield in sorghum and maize. We placed great emphasis on discussing 22 fine-mapped QTLs and 30 functionally characterized genes, which greatly hinders our deep understanding at the molecular mechanism level. This review provides a general overview of the comprehensive findings on grain yield QTLs and discusses the emerging trend in molecular marker-assisted breeding with these QTLs.

Global Analysis of the Genetic Variations in miRNA-Targeted Sites and Their Correlations With Agronomic Traits in Rapeseed

MicroRNAs (miRNAs) and their target genes play vital roles in crops. However, the genetic variations in miRNA-targeted sites that affect miRNA cleavage efficiency and their correlations with agronomic traits in crops remain unexplored. On the basis of a genome-wide DNA re-sequencing of 210 elite rapeseed (Brassica napus) accessions, we identified the single nucleotide polymorphisms (SNPs) and insertions/deletions (INDELs) in miRNA-targeted sites complementary to miRNAs. Variant calling revealed 7.14 million SNPs and 2.89 million INDELs throughout the genomes of 210 rapeseed accessions. Furthermore, we detected 330 SNPs and 79 INDELs in 357 miRNA target sites, of which 33.50% were rare variants. We also analyzed the correlation between the genetic variations in miRNA target sites and 12 rapeseed agronomic traits. Eleven SNPs in miRNA target sites were significantly correlated with phenotypes in three consecutive years. More specifically, three correlated SNPs within the miRNA-binding regions of BnSPL9-3, BnSPL13-2, and BnCUC1-2 were in the loci associated with the branch angle, seed weight, and silique number, respectively; expression profiling suggested that the variation at these 3 miRNA target sites significantly affected the expression level of the corresponding target genes. Taken together, the results of this study provide researchers and breeders with a global view of the genetic variations in miRNA-targeted sites in rapeseed and reveal the potential effects of these genetic variations on elite agronomic traits.

The miR164-GhCUC2-GhBRC1 module regulates plant architecture through abscisic acid in cotton

Branching determines cotton architecture and production, but the underlying regulatory mechanisms remain unclear. Here, we report that the miR164-GhCUC2 (CUP-SHAPED COTYLEDON2) module regulates lateral shoot development in cotton and Arabidopsis. We generated OE-GhCUC2m (overexpression GhCUC2m) and STTM164 (short tandem target mimic RNA of miR164) lines in cotton and heterologous expression lines for gh-miR164, GhCUC2 and GhCUC2m in Arabidopsis to study the mechanisms controlling lateral branching. GhCUC2m overexpression resulted in a short-branch phenotype similar to STTM164. In addition, heterologous expression of GhCUC2m led to decreased number and length of branches compared with wild type, opposite to the effects of the OE-gh-pre164 line in Arabidopsis. GhCUC2 interacted with GhBRC1 and exhibited similar negative regulation of branching. Overexpression of GhBRC1 in the brc1-2 mutant partially rescued the mutant phenotype and decreased branch number. GhBRC1 directly bound to the NCED1 promoter and activated its transcription, leading to local abscisic acid (ABA) accumulation and response. Mutation of the NCED1 promoter disrupted activation by GhBRC1. This finding demonstrates a direct relationship between BRC1 and ABA signalling and places ABA downstream of BRC1 in the control of branching development. The miR164-GhCUC2-GhBRC1-GhNCED1 module provides a clear regulatory axis for ABA signalling to control plant architecture.

GWAS with a PCA uncovers candidate genes for accumulations of microelements in maize seedlings

Microelements are necessary for plant growth and development, they control key processes of physiological metabolism. Herein, we evaluated three accumulation-related performances for each of the four microelements (Fe, Zn, Cu, and Mn) among 305 inbred maize lines. Quantification of these microelements in maize roots and shoots revealed abundant phenotypic variations in the association panel, with the variation coefficients ranging from 0.31 to 0.76. Principal component analysis (PCA) of the three related traits (concentration in root, concentration in shoot, and transport coefficient) showed that PC1 and PC2 explained >95% of phenotypic variations for each element. The scores of PC1 and PC2 were thereby used for a genome-wide association study by combining 44,134 SNPs of this panel. A total of 27, 1, 5, and 3 SNPs were significantly (P < .05) associated with Zn-PC1, Zn-PC2, Cu-PC1, and Mn-PC2, respectively, with 11 genes closely linked (r²  > 0.8) to these SNPs. Of them, GRMZM2G142870, GRMZM2G045531, and GRMZM2G143512 were individually annotated as ABC transporter C family member 14, zinc transporter 3, and heavy metal ATPase10. A candidate gene association analysis further verified that GRMZM2G142870 and GRMZM2G045531 affect Zn and Mn accumulations, respectively. Evaluation of contrasting allele ratios in elite lines indicated that the majority of the alleles correlating with higher Zn or Cu had not been utilized in maize breeding. Integration of more "higher-accumulation" alleles in the elite lines will be practical for improving Zn and Cu accumulations in maize. Our findings contribute to genetic revelation and molecular marker-assisted selection of microelement accumulations in maize.

A C-terminal encoded peptide, ZmCEP1, is essential for kernel development in maize

C-terminal encoded peptides (CEPs) are peptide hormones which act as mobile signals coordinating important developmental programs. Previous studies have unraveled that CEPs are able to regulate plant growth and abiotic stress via cell-to-cell communication in Arabidopsis and rice; however, little is known about their roles in maize. Here, we examined the spatiotemporal expression pattern of ZmCEP1 and showed that ZmCEP1 is highly expressed in young ears and tassels of maize, particularly in the vascular bundles of ears. Heterologous expression of ZmCEP1 in Arabidopsis results in smaller plants and seed size. Similarly, overexpression of ZmCEP1 in maize decreased the plant and ear height, ear length, kernel size, and 100-kernel weight. Consistently, exogenous application of the synthesized ZmCEP1 peptide to the roots of Arabidopsis and maize inhibited root elongation. Knock-out of ZmCEP1 through CRISPR/Cas9 significantly increased plant and ear height, kernel size and 100-kernel weight. Transcriptome analysis revealed that knock-out of ZmCEP1 up-regulated a subset of genes involved in nitrogen metabolism, nitrate transport, sugar transport and auxin response. Thus, these results provide new insights into the genetic and molecular function of ZmCEP1 in regulating kernel development and plant growth, providing novel opportunities for maize breeding.

Genome-wide association study uncovers new genetic loci and candidate genes underlying seed chilling-germination in maize

As one of the major crops, maize (Zea mays L.) is mainly distributed in tropical and temperate regions. However, with the changes of the environments, chilling stress has become a significantly abiotic stress affecting seed germination and thus the reproductive and biomass accumulation of maize. Herein, we investigated five seed germination-related phenotypes among 300 inbred lines under low-temperature condition (10 °C). By combining 43,943 single nucleotide polymorphisms (SNPs), a total of 15 significant (P < 2.03 ×  10^-6) SNPs were identified to correlate with seed germination under cold stress based on the FarmCPU model in GWAS, among which three loci were repeatedly associated with multiple traits. Ten gene models were closely linked to these three variations, among which Zm00001d010454, Zm00001d010458, Zm00001d010459, and Zm00001d050021 were further verified by candidate gene association study and expression pattern analysis. Importantly, these candidate genes were previously reported to involve plant tolerance to chilling stress and other abiotic stress. Our findings contribute to the understanding of the genetic and molecular mechanisms underlying chilling germination in maize.

Angular Leaf Spot Resistance Loci Associated With Different Plant Growth Stages in Common Bean

Angular leaf spot (ALS) is a disease that causes major yield losses in the common bean crop. Studies based on different isolates and populations have already been carried out to elucidate the genetic mechanisms of resistance to ALS. However, understanding of the interaction of this resistance with the reproductive stages of common bean is lacking. The aim of the present study was to identify ALS resistance loci at different plant growth stages (PGS) by association and linkage mapping approaches. An BC₂F₃ inter-gene pool cross population (AND 277 × IAC-Milênio - AM population) profiled with 1,091 SNPs from genotyping by sequencing (GBS) was used for linkage mapping, and a carioca diversity panel (CDP) genotyped by 5,398 SNPs from BeadChip assay technology was used for association mapping. Both populations were evaluated for ALS resistance at the V2 and V3 PGSs (controlled conditions) and R8 PGS (field conditions). Different QTL (quantitative trait loci) were detected for the three PGSs and both populations, showing a different quantitative profile of the disease at different plant growth stages. For the three PGS, multiple interval mapping (MIM) identified seven significant QTL, and the Genome-wide association study (GWAS) identified fourteen associate SNPs. Several loci validated regions of previous studies, and Phg-1, Phg-2, Phg-4, and Phg-5, among the 5 loci of greatest effects reported in the literature, were detected in the CDP. The AND 277 cultivar contained both the Phg-1 and the Phg-5 QTL, which is reported for the first time in the descendant cultivar CAL143 as ALS10.1^UC. The novel QTL named ALS11.1^AM was located at the beginning of chromosome Pv11. Gene annotation revealed several putative resistance genes involved in the ALS response at the three PGSs, and with the markers and loci identified, new specific molecular markers can be developed, representing a powerful tool for common bean crop improvement and for gain in ALS resistance.

MicroRNA-mediated regulation of agronomically important seed traits: a treasure trove with shades of grey!

Seed development is an intricate process with multiple levels of regulation. MicroRNAs (miRNAs) have emerged as one of the crucial components of molecular networks underlying agronomically important seed traits in diverse plant species. In fact, loss of function of the genes regulating miRNA biogenesis also exhibits defects in seed development. A total of 21 different miRNAs have experimentally been shown to regulate seed size, nutritional content, vigor, and shattering, and have been reviewed here. The mechanism details of the associated regulatory cascades mediated through transcriptional regulators, phytohormones, basic metabolic machinery, and secondary siRNAs are elaborated. Co-localization of miRNAs and their target regions with seed-related QTLs provides new avenues for engineering these traits using conventional breeding programs or biotechnological interventions. While global analysis of miRNAs using small RNA sequencing studies are expanding the repertoire of candidate miRNAs, recent revelations on their inheritance, transport, and mechanism of action would be instrumental in designing better strategies for optimizing agronomically relevant seed traits.

Maize kernel development

Maize (Zea mays) is a leading cereal crop in the world. The maize kernel is the storage organ and the harvest portion of this crop and is closely related to its yield and quality. The development of maize kernel is initiated by the double fertilization event, leading to the formation of a diploid embryo and a triploid endosperm. The embryo and endosperm are then undergone independent developmental programs, resulting in a mature maize kernel which is comprised of a persistent endosperm, a large embryo, and a maternal pericarp. Due to the well-characterized morphogenesis and powerful genetics, maize kernel has long been an excellent model for the study of cereal kernel development. In recent years, with the release of the maize reference genome and the development of new genomic technologies, there has been an explosive expansion of new knowledge for maize kernel development. In this review, we overviewed recent progress in the study of maize kernel development, with an emphasis on genetic mapping of kernel traits, transcriptome analysis during kernel development, functional gene cloning of kernel mutants, and genetic engineering of kernel traits.

Association Mapping and Transcriptome Analysis Reveal the Genetic Architecture of Maize Kernel Size

Kernel length, kernel width, and kernel thickness are important traits affecting grain yield and product quality. Here, the genetic architecture of the three kernel size traits was dissected in an association panel of 309 maize inbred lines using four statistical methods. Forty-two significant single nucleotide polymorphisms (SNPs; p < 1.72E-05) and 70 genes for the three traits were identified under five environments. One and eight SNPs were co-detected in two environments and by at least two methods, respectively, and they explained 5.87-9.59% of the phenotypic variation. Comparing the transcriptomes of two inbred lines with contrasting seed size, three and eight genes identified in the association panel showed significantly differential expression between the two genotypes at 15 and 39 days after pollination, respectively. Ten and 17 genes identified by a genome-wide association study were significantly differentially expressed between the two development stages in the two genotypes. Combining environment-/method-stable SNPs and differential expression analysis, ribosomal protein L7, jasmonate-regulated gene 21, serine/threonine-protein kinase RUNKEL, AP2-EREBP-transcription factor 16, and Zm00001d035222 (cell wall protein IFF6-like) were important candidate genes for maize kernel size and development.

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 Analysis and Fine Mapping of a Major QTL Conferring Kernel Size in Maize (Zea mays)

Kernel size is an important agronomic trait for grain yield in maize. The purpose of this study is to map QTLs and predict candidate genes for kernel size in maize. A total of 199 F2 and its F2 : 3 lines from the cross between SG5/SG7 were developed. A composite interval mapping (CIM) method was used to detect QTLs in three environments of F2 and F2 : 3 populations. The result showed that a total of 10 QTLs for kernel size were detected, among which were five QTLs for kernel length (KL) and five QTLs for kernel width (KW). Two stable QTLs, qKW-1, and qKL-2, were mapped in all three environments. Three QTLs, qKL-1, qKW-1, and qKW-2, were overlapped with the QTLs identified from previous studies. In order to validate and fine map qKL-2, near-isogenic lines (NILs) were developed by continuous backcrossing between SG5 as the donor parent and SG7 as the recurrent parent. Marker-assisted selection was conducted from BC2F1 generation with molecular markers near qKL-2. A secondary linkage map with six markers around the qKL-2 region was developed and used for fine mapping of qKL-2. Finally, qKL-2 was confirmed in a 1.95 Mb physical interval with selected overlapping recombinant chromosomes on maize chromosome 9 by blasting with the Zea_Mays_B73 v4 genome. Transcriptome analysis showed that a total of 11 out of 40 protein-coding genes differently expressed between the two parents were detected in the identified qKL-2 interval. GRMZM2G006080 encoding a receptor-like protein kinase FERONIA, was predicted as a candidate gene to control kernel size. The work will not only help to understand the genetic mechanisms of kernel size of maize but also lay a foundation for further fine mapping and even cloning of the promising loci.

A combination of linkage mapping and GWAS brings new elements on the genetic basis of yield-related traits in maize across multiple environments

Using GWAS and QTL mapping identified 100 QTL and 138 SNPs, which control yield-related traits in maize. The candidate gene GRMZM2G098557 was further validated to regulate ear row number by using a segregation population. Understanding the genetic basis of yield-related traits contributes to the improvement of grain yield in maize. This study used an inter-mated B73 × Mo17 (IBM) Syn10 doubled-haploid (DH) population and an association panel to identify the genetic loci responsible for nine yield-related traits in maize. Using quantitative trait loci (QTL) mapping, 100 QTL influencing these traits were detected across different environments in the IBM Syn10 DH population, with 25 co-detected in multiple environments. Using a genome-wide association study (GWAS), 138 single-nucleotide polymorphisms (SNPs) were identified as correlated with these traits (P < 2.04E-06) in the association panel. Twenty-one pleiotropic QTL/SNPs were identified to control different traits in both populations. A combination of QTL mapping and GWAS uncovered eight significant SNPs (PZE-101097575, PZE-103169263, ZM011204-0763, PZE-104044017, PZE-104123110, SYN8062, PZE-108060911, and PZE-102043341) that were co-located within seven QTL confidence intervals. According to the eight co-localized SNPs by the two populations, 52 candidate genes were identified, among which the ear row number (ERN)-associated SNP SYN8062 was closely linked to SBP-transcription factor 7 (GRMZM2G098557). Several SBP-transcription factors were previously demonstrated to modulate maize ERN. We then validated the phenotypic effects of SYN8062 in the IBM Syn10 DH population, indicating that the ERN of the lines with the A-allele in SYN8062 was significantly (P < 0.05) larger than that of the lines with the G-allele in SYN8062 in each environment. These findings provide valuable information for understanding the genetic mechanisms of maize grain yield formation and for improving molecular marker-assisted selection for the high-yield breeding of maize.

Genome-wide association studies and QTL mapping uncover the genetic architecture of ear tip-barrenness in maize

Ear tip-barrenness (ETB) phenotype threatens crop yield, because it reduces the kernel number per ear. The genetic basis of ETB in maize remains largely unknown. Herein, a genome-wide association study (GWAS) and quantitative trait loci (QTL) mapping were jointly applied to identify the significant genetic loci interrelated with ETB. Six significant SNPs were detected at a stringent P-value threshold (1.95 × 10^-6 ). Additionally, four environment-stable SNPs were co-detected across a single environment and best linear unbiased prediction (BLUP) model at a less stringent P-value threshold (1 × 10^-4 ). The above 10 SNPs were closely linked to 6 candidate genes, which mainly involved seed development, photosynthesis and ethylene response. Moreover, the ratio of superior allele at each significant SNP ranged from 0 to 83.33% in 30 investigated maize elite lines. QTL mapping identified 14 QTL with phenotypic variation explained (PVE) ranging from 3.64 to 7.09%, of which one QTL (qETB2-1) was repeatedly identified in two environments. Combined analysis of GWAS and QTL mapping showed that one SNP (PZE-102175229, chromosome 2: 217 66 Mb) was located in the QTL (qETB2-2, chromosome 2: 215 90-217 82 Mb). Eighteen gene models situated in the linkage disequilibrium (LD) region of the co-localized SNP were further used to evaluate their correlation with ETB by candidate gene association analysis. Two superior haplotypes and two superior alleles were detected among 74 lines for Zm00001d007195, Zm00001d007197 and Zm00001d007201. These results provide more information for clarifying the molecular mechanism of ETB and for speeding up the genetic improvement of maize varieties.

Large-scale GWAS in sorghum reveals common genetic control of grain size among cereals

Grain size is a key yield component of cereal crops and a major quality attribute. It is determined by a genotype's genetic potential and its capacity to fill the grains. This study aims to dissect the genetic architecture of grain size in sorghum. An integrated genome-wide association study (GWAS) was conducted using a diversity panel (n = 837) and a BC-NAM population (n = 1421). To isolate genetic effects associated with genetic potential of grain size, rather than the genotype's capacity to fill the grains, a treatment of removing half of the panicle was imposed during flowering. Extensive and highly heritable variation in grain size was observed in both populations in 5 field trials, and 81 grain size QTL were identified in subsequent GWAS. These QTL were enriched for orthologues of known grain size genes in rice and maize, and had significant overlap with SNPs associated with grain size in rice and maize, supporting common genetic control of this trait among cereals. Grain size genes with opposite effect on grain number were less likely to overlap with the grain size QTL from this study, indicating the treatment facilitated identification of genetic regions related to the genetic potential of grain size. These results enhance understanding of the genetic architecture of grain size in cereal, and pave the way for exploration of underlying molecular mechanisms and manipulation of this trait in breeding practices.

Combined GWAS and QTL analysis for dissecting the genetic architecture of kernel test weight in maize

Kernel weight in a unit volume is referred to as kernel test weight (KTW) that directly reflects maize (Zea mays L.) grain quality. In this study, an inter-mated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population and an association panel were used to identify loci responsible for KTW of maize across multiple environments. A total of 18 significant KTW-related single-nucleotide polymorphisms (SNPs) were identified using genome-wide association study (GWAS); they were closely linked to 12 candidate genes. In the IBM Syn10 DH population, linkage analysis detected 19 common quantitative trait loci (QTL), five of which were repeatedly detected among multiple environments. Several verified genes that regulate maize seed development were found in the confidence intervals of the mapped QTL and the LD regions of GWAS, such as ZmYUC1, BAP2, ZmTCRR-1, dek36 and ZmSWEET4c. Combined QTL mapping and GWAS identified one significant SNP that was co-identified in the both populations. Based on the co-localized SNP across the both populations, 17 candidate genes were identified. Of them, Zm00001d044075, Zm00001d044086, and Zm00001d044081 were further identified by candidate gene association study for KTW. Zm00001d044081 encodes homeobox-leucine zipper protein ATHB-4, which has been demonstrated to control apical embryo development in Arabidopsis. Our findings provided insights into the mechanism underlying maize KTW and contributed to the application of molecular-assisted selection of high KTW breeding in maize.

Genome-Wide Association Analysis of Plant Height Using the Maize F1 Population

Drastic changes in plant height (PH) are observed when maize adapt to a higher plant density. Most importantly, PH is an important factor affecting maize yield. Although the genetic basis of PH has been extensively studied using different populations during the past decades, genetic basis remains unclear in the F1 population, which was a widely used population in production. In this study, a genome-wide association study (GWAS) was conducted using an F1 population consisting of 300 maize hybrids with 17,652 single nucleotide polymorphisms (SNPs) makers to identify candidate genes for controlling PH. A total of nine significant SNPs makers and two candidate genes were identified for PH. The candidate genes, Zm00001d018617 and Zm00001d023659, were the genes most probable to be involved in the development of PH. Our results provide new insights into the genetic basis of PH in maize.