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

Identification of candidate gene associated with maize northern leaf blight resistance in a multi-parent population

KEY MESSAGE

QTL mapping combined with genome-wide association studies, revealed a potential candidate gene for  resistance to northern leaf blight in the tropical CATETO-related maize line YML226, providing a basis for marker-assisted selection of maize varieties Northern leaf blight (NLB) is a foliar disease that can cause severe yield losses in maize. Identifying and utilizing NLB-resistant genes is the most effective way to prevent and control this disease. In this study, five important inbred lines of maize were used as parental lines to construct a multi-parent population for the identification of NLB-resistant loci. QTL mapping and GWAS analysis revealed that QTL qtl_YML226_1, which had the largest phenotypic variance explanation (PVE) of 9.28%, and SNP 5-49,193,921 were co-located in the CATETO-related line YML226. This locus was associated with the candidate gene Zm00001d014471, which encodes a pentatricopeptide repeat (PPR) protein. In the coding region of Zm00001d014471, YML226 had more specific SNPs than the other parental lines. qRT-PCR showed that the relative expressions of Zm00001d014471 in inoculated and uninoculated leaves of YML226 were significantly higher, indicating that the expression of the candidate gene was correlated with NLB resistance. The analysis showed that the higher expression level in YML226 might be caused by SNP mutations. This study identified NLB resistance candidate loci and genes in the tropical maize inbred line YML226 derived from the CATETO germplasm, thereby providing a theoretical basis for using modern marker-assisted breeding techniques to select genetic resources resistant to NLB.

Comprehensive Evaluation and Selection of 192 Maize Accessions from Different Sources

In the period 2022-2023, an analysis of fourteen phenotypic traits was conducted across 192 maize accessions in the Aral region of Xinjiang. The Shannon-Wiener diversity index was employed to quantify the phenotypic diversity among the accessions. Subsequently, a comprehensive evaluation of the index was performed utilizing correlation analysis, principal component analysis (PCA) and cluster analysis. The results highlighted significant findings: (1) A pronounced diversity was evident across the 192 maize accessions, accompanied by complex interrelationships among the traits. (2) The 14 phenotypic traits were transformed into 3 independent indicators through principal component analysis: spike factor, leaf width factor, and number of spikes per plant. (3) The 192 materials were divided into three groups using cluster analysis. The phenotypes in Group III exhibited the best performance, followed by those in Group I, and finally Group II. The selection of the three groups can vary depending on the breeding objectives. This study analysed the diversity of phenotypic traits in maize germplasm resources. Maize germplasm was categorised based on similar phenotypes. These findings provide theoretical insights for the study of maize accessions under analogous climatic conditions in Alar City, which lay the groundwork for the efficient utilization of existing germplasm as well as the development and selection of new varieties.

Harnessing the predicted maize pan-interactome for putative gene function prediction and prioritization of candidate genes for important traits

The recent assembly and annotation of the 26 maize nested association mapping population founder inbreds have enabled large-scale pan-genomic comparative studies. These studies have expanded our understanding of agronomically important traits by integrating pan-transcriptomic data with trait-specific gene candidates from previous association mapping results. In contrast to the availability of pan-transcriptomic data, obtaining reliable protein-protein interaction (PPI) data has remained a challenge due to its high cost and complexity. We generated predicted PPI networks for each of the 26 genomes using the established STRING database. The individual genome-interactomes were then integrated to generate core- and pan-interactomes. We deployed the PPI clustering algorithm ClusterONE to identify numerous PPI clusters that were functionally annotated using gene ontology (GO) functional enrichment, demonstrating a diverse range of enriched GO terms across different clusters. Additional cluster annotations were generated by integrating gene coexpression data and gene description annotations, providing additional useful information. We show that the functionally annotated PPI clusters establish a useful framework for protein function prediction and prioritization of candidate genes of interest. Our study not only provides a comprehensive resource of predicted PPI networks for 26 maize genomes but also offers annotated interactome clusters for predicting protein functions and prioritizing gene candidates. The source code for the Python implementation of the analysis workflow and a standalone web application for accessing the analysis results are available at https://github.com/eporetsky/PanPPI.

Genomic basis determining root system architecture in maize

KEY MESSAGE

A total of 389 and 344 QTLs were identified by GWAS and QTL mapping explaining accumulatively 32.2-65.0% and 23.7-63.4% of phenotypic variation for 14 shoot-borne root traits using more than 1300 individuals across multiple field trails. Efficient nutrient and water acquisition from soils depends on the root system architecture (RSA). However, the genetic determinants underlying RSA in maize remain largely unexplored. In this study, we conducted a comprehensive genetic analysis for 14 shoot-borne root traits using 513 inbred lines and 800 individuals from four recombinant inbred line (RIL) populations at the mature stage across multiple field trails. Our analysis revealed substantial phenotypic variation for these 14 root traits, with a total of 389 and 344 QTLs identified through genome-wide association analysis (GWAS) and linkage analysis, respectively. These QTLs collectively explained 32.2-65.0% and 23.7-63.4% of the trait variation within each population. Several a priori candidate genes involved in auxin and cytokinin signaling pathways, such as IAA26, ARF2, LBD37 and CKX3, were found to co-localize with these loci. In addition, a total of 69 transcription factors (TFs) from 27 TF families (MYB, NAC, bZIP, bHLH and WRKY) were found for shoot-borne root traits. A total of 19 genes including PIN3, LBD15, IAA32, IAA38 and ARR12 and 19 GWAS signals were overlapped with selective sweeps. Further, significant additive effects were found for root traits, and pyramiding the favorable alleles could enhance maize root development. These findings could contribute to understand the genetic basis of root development and evolution, and provided an important genetic resource for the genetic improvement of root traits in maize.

QTL mapping for plant height and ear height using bi-parental immortalized heterozygous populations in maize

Introduction

Plant height (PH) and ear height (EH) are key plant architectural traits in maize, which will affect the photosynthetic efficiency, high plant density tolerance, suitability for mechanical harvesting.

Methods

QTL mapping were conducted for PH and EH using a recombinant inbred line (RIL) population and two corresponding immortalized backcross (IB) populations obtained from crosses between the RIL population and the two parental lines.

Results

A total of 17 and 15 QTL were detected in the RIL and IB populations, respectively. Two QTL, qPH1-1 (qEH1-1) and qPH1-2 (qEH1-4) in the RIL, were simultaneously identified for PH and EH. Combing reported genome-wide association and cloned PH-related genes, co-expression network analyses were constructed, then five candidate genes with high confidence in major QTL were identified including Zm00001d011117 and Zm00001d011108, whose homologs have been confirmed to play a role in determining PH in maize and soybean.

Discussion

QTL mapping used a immortalized backcross population is a new strategy. These identified genes in this study can provide new insights for improving the plant architecture in maize.

Maize green leaf area index dynamics: genetic basis of a new secondary trait for grain yield in optimal and drought conditions

KEY MESSAGE

Green Leaf Area Index dynamics is a promising secondary trait for grain yield and drought tolerance. Multivariate GWAS is particularly well suited to identify the genetic determinants of the green leaf area index dynamics. Improvement of maize grain yield is impeded by important genotype-environment interactions, especially under drought conditions. The use of secondary traits, that are correlated with yield, more heritable and less prone to genotype-environment interactions, can increase breeding efficiency. Here, we studied the genetic basis of a new secondary trait: the green leaf area index (GLAI) dynamics over the maize life cycle. For this, we used an unmanned aerial vehicle to characterize the GLAI dynamics of a diverse panel in well-watered and water-deficient trials in two years. From the dynamics, we derived 24 traits (slopes, durations, areas under the curve), and showed that six of them were heritable traits representative of the panel diversity. To identify the genetic determinants of GLAI, we compared two genome-wide association approaches: a univariate (single-trait) method and a multivariate (multi-trait) method combining GLAI traits, grain yield, and precocity. The explicit modeling of correlation structure between secondary traits and grain yield in the multivariate mixed model led to 2.5 times more associations detected. A total of 475 quantitative trait loci (QTLs) were detected. The genetic architecture of GLAI traits appears less complex than that of yield with stronger-effect QTLs that are more stable between environments. We also showed that a subset of GLAI QTLs explains nearly one fifth of yield variability across a larger environmental network of 11 water-deficient trials. GLAI dynamics is a promising grain yield secondary trait in optimal and drought conditions, and the detected QTLs could help to increase breeding efficiency through a marker-assisted approach.

Genetic mapping of dynamic control of leaf angle across multiple canopy levels in maize

Optimizing leaf angle and other canopy architecture traits has helped modern maize (Zea mays L.) become adapted to higher planting densities over the last 60 years. Traditional investigations into genetic control of leaf angle have focused on one leaf or the average of multiple leaves; as a result, our understanding of genetic control across multiple canopy levels is still limited. To address this, genetic mapping across four canopy levels was conducted in the present study to investigate the genetic control of leaf angle across the canopy. We developed two populations of doubled haploid lines derived from three inbreds with distinct leaf angle phenotypes. These populations were genotyped with genotyping-by-sequencing and phenotyped for leaf angle at four different canopy levels over multiple years. To understand how leaf angle changes across the canopy, the four measurements were used to derive three additional traits. Composite interval mapping was conducted with the leaf-specific measurements and the derived traits. A set of 59 quantitative trait loci (QTLs) were uncovered for seven traits, and two genomic regions were consistently detected across multiple canopy levels. Additionally, seven genomic regions were found to contain consistent QTLs with either relatively stable or dynamic effects at different canopy levels. Prioritizing the selection of QTLs with dynamic effects across the canopy will aid breeders in selecting maize hybrids with the ideal canopy architecture that continues to maximize yield on a per area basis under increasing planting densities.

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.

Joint-GWAS, Linkage Mapping, and Transcriptome Analysis to Reveal the Genetic Basis of Plant Architecture-Related Traits in Maize

Plant architecture is one of the key factors affecting maize yield formation and can be divided into secondary traits, such as plant height (PH), ear height (EH), and leaf number (LN). It is a viable approach for exploiting genetic resources to improve plant density. In this study, one natural panel of 226 inbred lines and 150 family lines derived from the offspring of T32 crossed with Qi319 were genotyped by using the MaizeSNP50 chip and the genotyping by sequence (GBS) method and phenotyped under three different environments. Based on the results, a genome-wide association study (GWAS) and linkage mapping were analyzed by using the MLM and ICIM models, respectively. The results showed that 120 QTNs (quantitative trait nucleotides) and 32 QTL (quantitative trait loci) related to plant architecture were identified, including four QTL and 40 QTNs of PH, eight QTL and 41 QTNs of EH, and 20 QTL and 39 QTNs of LN. One dominant QTL, qLN7-2, was identified in the Zhangye environment. Six QTNs were commonly identified to be related to PH, EH, and LN in different environments. The candidate gene analysis revealed that Zm00001d021574 was involved in regulating plant architecture traits through the autophagy pathway, and Zm00001d044730 was predicted to interact with the male sterility-related gene ms26. These results provide abundant genetic resources for improving maize plant architecture traits by using approaches to biological breeding.

A potential candidate gene associated with the angles of the ear leaf and the second leaf above the ear leaf in maize

BACKGROUND

Leaf angle is a key trait for maize plant architecture that plays a significant role in its morphological development, and ultimately impacting maize grain yield. Although many studies have been conducted on the association and localization of genes regulating leaf angle in maize, most of the candidate genes identified are associated with the regulation of ligule-ear development and phytohormone pathways, and only a few candidate genes have been reported to enhance the mechanical strength of leaf midrib and vascular tissues.

RESULTS

To address this gap, we conducted a genome-wide association study (GWAS) using the leaf angle phenotype and genotyping-by-sequencing data generated from three recombinant inbred line (RIL) populations of maize. Through GWAS analysis, we identified 156 SNPs significantly associated with the leaf angle trait and detected a total of 68 candidate genes located within 10 kb upstream and downstream of these individual SNPs. Among these candidate genes, Zm00001d045408, located on chromosome 9 emerged as a key gene controlling the angles of both the ear leaf and the second leaf above the ear leaf. Notably, this new gene's homolog in Arabidopsis promotes cell division and vascular tissue development. Further analysis revealed that a SNP transversion (G/T) at 7.536 kb downstream of the candidate gene Zm00001d045408 may have caused a reduction in leaf angles of the ear and the second leaf above the ear leaf. Our analysis of the 10 kb region downstream of this candidate gene revealed a 4.337 kb solo long-terminal reverse transcription transposon (solo LTR), located 3.112 kb downstream of Zm00001d045408, with the SNP located 87 bp upstream of the solo LTR.

CONCLUSIONS

In summary, we have identified a novel candidate gene, Zm00001d045408 and a solo LTR that are associated with the angles of both the ear leaf and the second leaf above the ear leaf. The future research holds great potential in exploring the precise role of newly identified candidate gene in leaf angle regulation. Functional characterization of this gene can help in gaining deeper insights into the complex genetic pathways underlying maize plant architecture.

ZmBELL10 interacts with other ZmBELLs and recognizes specific motifs for transcriptional activation to modulate internode patterning in maize

Plant height is an important agronomic trait that affects crop yield. Elucidating the molecular mechanism underlying plant height regulation is also an important question in developmental biology. Here, we report that a BELL transcription factor, ZmBELL10, positively regulates plant height in maize (Zea mays). Loss of ZmBELL10 function resulted in shorter internodes, fewer nodes, and smaller kernels, while ZmBELL10 overexpression increased plant height and hundred-kernel weight. Transcriptome analysis and chromatin immunoprecipitation followed by sequencing showed that ZmBELL10 recognizes specific sequences in the promoter of its target genes and activates cell division- and cell elongation-related gene expression, thereby influencing node number and internode length in maize. ZmBELL10 interacted with several other ZmBELL proteins via a spatial structure in its POX domain to form protein complexes involving ZmBELL10. All interacting proteins recognized the same DNA sequences, and their interaction with ZmBELL10 increased target gene expression. We identified the key residues in the POX domain of ZmBELL10 responsible for its protein-protein interactions, but these residues did not affect its transactivation activity. Collectively, our findings shed light on the functions of ZmBELL10 protein complexes and provide potential targets for improving plant architecture and yield in maize.

QTG-Miner aids rapid dissection of the genetic base of tassel branch number in maize

Genetic dissection of agronomic traits is important for crop improvement and global food security. Phenotypic variation of tassel branch number (TBN), a major breeding target, is controlled by many quantitative trait loci (QTLs). The lack of large-scale QTL cloning methodology constrains the systematic dissection of TBN, which hinders modern maize breeding. Here, we devise QTG-Miner, a multi-omics data-based technique for large-scale and rapid cloning of quantitative trait genes (QTGs) in maize. Using QTG-Miner, we clone and verify seven genes underlying seven TBN QTLs. Compared to conventional methods, QTG-Miner performs well for both major- and minor-effect TBN QTLs. Selection analysis indicates that a substantial number of genes and network modules have been subjected to selection during maize improvement. Selection signatures are significantly enriched in multiple biological pathways between female heterotic groups and male heterotic groups. In summary, QTG-Miner provides a large-scale approach for rapid cloning of QTGs in crops and dissects the genetic base of TBN for further maize breeding.

Elucidating the patterns of pleiotropy and its biological relevance in maize

Pleiotropy-when a single gene controls two or more seemingly unrelated traits-has been shown to impact genes with effects on flowering time, leaf architecture, and inflorescence morphology in maize. However, the genome-wide impact of biological pleiotropy across all maize phenotypes is largely unknown. Here, we investigate the extent to which biological pleiotropy impacts phenotypes within maize using GWAS summary statistics reanalyzed from previously published metabolite, field, and expression phenotypes across the Nested Association Mapping population and Goodman Association Panel. Through phenotypic saturation of 120,597 traits, we obtain over 480 million significant quantitative trait nucleotides. We estimate that only 1.56-32.3% of intervals show some degree of pleiotropy. We then assess the relationship between pleiotropy and various biological features such as gene expression, chromatin accessibility, sequence conservation, and enrichment for gene ontology terms. We find very little relationship between pleiotropy and these variables when compared to permuted pleiotropy. We hypothesize that biological pleiotropy of common alleles is not widespread in maize and is highly impacted by nuisance terms such as population structure and linkage disequilibrium. Natural selection on large standing natural variation in maize populations may target wide and large effect variants, leaving the prevalence of detectable pleiotropy relatively low.

Genetic basis of resistance to southern corn leaf blight in the maize multi-parent population and diversity panel

Southern corn leaf blight (SLB), caused by the necrotrophic pathogen Cochliobolus heterostrophus, is one of the maize foliar diseases and poses a great threat to corn production around the world. Identification of genetic variations underlying resistance to SLB is of paramount importance to maize yield and quality. Here, we used a random-open-parent association mapping population containing eight recombinant inbred line populations and one association mapping panel consisting of 513 diversity maize inbred lines with high-density genetic markers to dissect the genetic basis of SLB resistance. Overall, 109 quantitative trait loci (QTLs) with predominantly small or moderate additive effects, and little epistatic effects were identified. We found 35 (32.1%) novel loci in comparison with the reported QTLs. We revealed that resistant alleles were significantly enriched in tropical accessions and the frequency of about half of resistant alleles decreased during the adaptation process owing to the selection of agronomic traits. A large number of annotated genes located in the SLB-resistant QTLs were shown to be involved in plant defence pathways. Integrating genome-wide association study, transcriptomic profiling, resequencing and gene editing, we identified ZmFUT1 and MYBR92 as the putative genes responsible for the major QTLs for resistance to C. heterostrophus. Our results present a comprehensive insight into the genetic basis of SLB resistance and provide resistant loci or genes as direct targets for crop genetic improvement.

Penta-Primer Amplification Refractory Mutation System (PARMS) with Direct PCR-Based SNP Marker-Assisted Selection (D-MAS)

The penta-primer amplification refractory mutation system (PARMS) is a high-throughput, low-cost, and automated genotyping assay system that utilizes competitive allele-specific polymerase chain reaction (AS-PCR) combined with a homogeneous fluorescence-based reporting system to detect genetic variation occurring at single-nucleotide polymorphism (SNP). It is flexible in terms of the number of SNPs and samples to be analyzed, and the whole process only needs standard liquid handling, thermal cycling instruments, and plate reading instruments, which are present in many labs. Its compatibility with DNA samples prepared from a variety of sources and extraction technologies, such as alkaline lysis, makes it suitable for a direct PCR-based SNP marker-assisted selection system (D-MAS), a simple, cost- and labor-saving, and robust SNP genotyping system. It combines rapid and high-throughput DNA extraction through modified alkaline lysis with PARMS to dramatically reduce the time of manual operation and result analysis in the molecular breeding of major crops.

QTL Analysis Reveals Conserved and Differential Genetic Regulation of Maize Lateral Angles above the Ear

Improving the density tolerance and planting density has great importance for increasing maize production. The key to promoting high density planting is breeding maize with a compact canopy architecture, which is mainly influenced by the angles of the leaves and tassel branches above the ear. It is still unclear whether the leaf angles of different stem nodes and tassel branches are controlled by similar genetic regulatory mechanisms, which limits the ability to breed for density-tolerant maize. Here, we developed a population with 571 double haploid lines derived from inbred lines, PHBA6 and Chang7-2, showing significant differences in canopy architecture. Phenotypic and QTL analyses revealed that the genetic regulation mechanism was largely similar for closely adjacent leaves above the ears. In contrast, the regulation mechanisms specifying the angles of distant leaves and the angles of leaves vs. tassel branches are largely different. The liguless1 gene was identified as a candidate gene for QTLs co-regulating the angles of different leaves and the tassel branch, consistent with its known roles in regulating plant architecture. Our findings can be used to develop strategies for the improvement of leaf and tassel architecture through the introduction of trait-specific or pleiotropic genes, thus benefiting the breeding of maize with increased density tolerance in the future.

Genome-Wide Association Study and Genomic Prediction on Plant Architecture Traits in Sweet Corn and Waxy Corn

Sweet corn and waxy corn has a better taste and higher accumulated nutritional value than regular maize, and is widely planted and popularly consumed throughout the world. Plant height (PH), ear height (EH), and tassel branch number (TBN) are key plant architecture traits, which play an important role in improving grain yield in maize. In this study, a genome-wide association study (GWAS) and genomic prediction analysis were conducted on plant architecture traits of PH, EH, and TBN in a fresh edible maize population consisting of 190 sweet corn inbred lines and 287 waxy corn inbred lines. Phenotypic data from two locations showed high heritability for all three traits, with significant differences observed between sweet corn and waxy corn for both PH and EH. The differences between the three subgroups of sweet corn were not obvious for all three traits. Population structure and PCA analysis results divided the whole population into three subgroups, i.e., sweet corn, waxy corn, and the subgroup mixed with sweet and waxy corn. Analysis of GWAS was conducted with 278,592 SNPs obtained from resequencing data; 184, 45, and 68 significantly associated SNPs were detected for PH, EH, and TBN, respectively. The phenotypic variance explained (PVE) values of these significant SNPs ranged from 3.50% to 7.0%. The results of this study lay the foundation for further understanding the genetic basis of plant architecture traits in sweet corn and waxy corn. Genomic selection (GS) is a new approach for improving quantitative traits in large plant breeding populations that uses whole-genome molecular markers. The marker number and marker quality are essential for the application of GS in maize breeding. GWAS can choose the most related markers with the traits, so it can be used to improve the predictive accuracy of GS.

Co-expression pan-network reveals genes involved in complex traits within maize pan-genome

BACKGROUND

With the advances in the high throughput next generation sequencing technologies, genome-wide association studies (GWAS) have identified a large set of variants associated with complex phenotypic traits at a very fine scale. Despite the progress in GWAS, identification of genotype-phenotype relationship remains challenging in maize due to its nature with dozens of variants controlling the same trait. As the causal variations results in the change in expression, gene expression analyses carry a pivotal role in unraveling the transcriptional regulatory mechanisms behind the phenotypes.

RESULTS

To address these challenges, we incorporated the gene expression and GWAS-driven traits to extend the knowledge of genotype-phenotype relationships and transcriptional regulatory mechanisms behind the phenotypes. We constructed a large collection of gene co-expression networks and identified more than 2 million co-expressing gene pairs in the GWAS-driven pan-network which contains all the gene-pairs in individual genomes of the nested association mapping (NAM) population. We defined four sub-categories for the pan-network: (1) core-network contains the highest represented ~ 1% of the gene-pairs, (2) near-core network contains the next highest represented 1-5% of the gene-pairs, (3) private-network contains ~ 50% of the gene pairs that are unique to individual genomes, and (4) the dispensable-network contains the remaining 50-95% of the gene-pairs in the maize pan-genome. Strikingly, the private-network contained almost all the genes in the pan-network but lacked half of the interactions. We performed gene ontology (GO) enrichment analysis for the pan-, core-, and private- networks and compared the contributions of variants overlapping with genes and promoters to the GWAS-driven pan-network.

CONCLUSIONS

Gene co-expression networks revealed meaningful information about groups of co-regulated genes that play a central role in regulatory processes. Pan-network approach enabled us to visualize the global view of the gene regulatory network for the studied system that could not be well inferred by the core-network alone.

Biomolecular Strategies for Vascular Bundle Development to Improve Crop Yield

The need to produce crops with higher yields is critical due to a growing global population, depletion of agricultural land, and severe climate change. Compared with the "source" and "sink" transport systems that have been studied a lot, the development and utilization of vascular bundles (conducting vessels in plants) are increasingly important. Due to the complexity of the vascular system, its structure, and its delicate and deep position in the plant body, the current research on model plants remains basic knowledge and has not been repeated for crops and applied to field production. In this review, we aim to summarize the current knowledge regarding biomolecular strategies of vascular bundles in transport systems (source-flow-sink), allocation, helping crop architecture establishment, and influence of the external environment. It is expected to help understand how to use sophisticated and advancing genetic engineering technology to improve the vascular system of crops to increase yield.

Candidate loci for leaf angle in maize revealed by a combination of genome-wide association study and meta-analysis

Leaf angle (LA) is a key component of maize plant architecture that can simultaneously govern planting density and improve final yield. However, the genetic mechanisms underlying LA have not been fully addressed. To broaden our understanding of its genetic basis, we scored three LA-related traits on upper, middle, and low leaves of 492 maize inbred lines in five environments. Phenotypic data revealed that the three LA-related traits were normally distributed, and significant variation was observed among environments and genotypes. A genome-wide association study (GWAS) was then performed to dissect the genetic factors that control natural variation in maize LA. In total, 85 significant SNPs (involving 32 non-redundant QTLs) were detected (p ≤ 2.04 × 10–6), and individual QTL explained 4.80%–24.09% of the phenotypic variation. Five co-located QTL were detected in at least two environments, and two QTLs were co-located with multiple LA-related traits. Forty-seven meta-QTLs were identified based on meta-analysis combing 294 LA-related QTLs extracted from 18 previously published studies, 816 genes were identified within these meta-QTLs, and seven co-located QTLs were jointly identified by both GWAS and meta-analysis. ZmULA1 was located in one of the co-located QTLs, qLA7, and its haplotypes, hap1 and hap2, differed significantly in LA-related traits. Interestingly, the temperate materials with hap2 had smallest LA. Finally, we also performed haplotype analysis using the reported genes that regulate LA, and identified a lot of maize germplasms that aggregated favorable haplotypes. These results will be helpful for elucidating the genetic basis of LA and breeding new maize varieties with ideal plant architecture.

Dynamic Quantitative Trait Loci Mapping for Plant Height in Recombinant Inbred Line Population of Upland Cotton

Plant height (PH) is a key plant architecture trait for improving the biological productivity of cotton. Ideal PH of cotton is conducive to lodging resistance and mechanized harvesting. To detect quantitative trait loci (QTL) and candidate genes of PH in cotton, a genetic map was constructed with a recombinant inbred line (RIL) population of upland cotton. PH phenotype data under nine environments and three best linear unbiased predictions (BLUPs) were used for QTL analyses. Based on restriction-site-associated DNA sequence (RAD-seq), the genetic map contained 5,850 single-nucleotide polymorphism (SNP) markers, covering 2,747.12 cM with an average genetic distance of 0.47 cM. Thirty-seven unconditional QTL explaining 1.03-12.50% of phenotypic variance, including four major QTL and seven stable QTL, were identified. Twenty-eight conditional QTL explaining 3.27-28.87% of phenotypic variance, including 1 major QTL, were identified. Importantly, five QTL, including 4 stable QTL, were both unconditional and conditional QTL. Among the 60 PH QTL (including 39 newly identified), none of them were involved in the whole period of PH growth, indicating that QTL related to cotton PH development have dynamic expression characteristics. Based on the functional annotation of Arabidopsis homologous genes and transcriptome data of upland cotton TM-1, 14 candidate genes were predicted within 10 QTL. Our research provides valuable information for understanding the genetic mechanism of PH development, which also increases the economic production of cotton.

Genetic Structure and Molecular Mechanisms Underlying the Formation of Tassel, Anther, and Pollen in the Male Inflorescence of Maize (Zea mays L.)

Maize tassel is the male reproductive organ which is located at the plant’s apex; both its morphological structure and fertility have a profound impact on maize grain yield. More than 40 functional genes regulating the complex tassel traits have been cloned up to now. However, the detailed molecular mechanisms underlying the whole process, from male inflorescence meristem initiation to tassel morphogenesis, are seldom discussed. Here, we summarize the male inflorescence developmental genes and construct a molecular regulatory network to further reveal the molecular mechanisms underlying tassel-trait formation in maize. Meanwhile, as one of the most frequently studied quantitative traits, hundreds of quantitative trait loci (QTLs) and thousands of quantitative trait nucleotides (QTNs) related to tassel morphology have been identified so far. To reveal the genetic structure of tassel traits, we constructed a consensus physical map for tassel traits by summarizing the genetic studies conducted over the past 20 years, and identified 97 hotspot intervals (HSIs) that can be repeatedly mapped in different labs, which will be helpful for marker-assisted selection (MAS) in improving maize yield as well as for providing theoretical guidance in the subsequent identification of the functional genes modulating tassel morphology. In addition, maize is one of the most successful crops in utilizing heterosis; mining of the genic male sterility (GMS) genes is crucial in developing biotechnology-based male-sterility (BMS) systems for seed production and hybrid breeding. In maize, more than 30 GMS genes have been isolated and characterized, and at least 15 GMS genes have been promptly validated by CRISPR/Cas9 mutagenesis within the past two years. We thus summarize the maize GMS genes and further update the molecular regulatory networks underlying male fertility in maize. Taken together, the identified HSIs, genes and molecular mechanisms underlying tassel morphological structure and male fertility are useful for guiding the subsequent cloning of functional genes and for molecular design breeding in maize. Finally, the strategies concerning efficient and rapid isolation of genes controlling tassel morphological structure and male fertility and their application in maize molecular breeding are also discussed.

Leaf angle: a target of genetic improvement in cereal crops tailored for high-density planting

High-density planting is an effective measure for increasing crop yield per unit land area. Leaf angle (LA) is a key trait of plant architecture and a target for genetic improvement of crops. Upright leaves allow better light capture in canopy under high-density planting, thus enhancing photosynthesis efficiency, ventilation and stress resistance, and ultimately higher grain yield. Here, we summarized the latest progress on the cellular and molecular mechanisms regulating LA formation in rice and maize. We suggest several standing out questions for future studies and then propose some promising strategies to manipulate LA for breeding of cereal crops tailored for high-density planting.

Genetic control of leaf angle in sorghum and its effect on light interception

Developing sorghum genotypes adapted to different light environments requires understanding of a plant's ability to capture light, determined through leaf angle specifically. This study dissected the genetic basis of leaf angle in 3 year field trials at two sites, using a sorghum diversity panel (729 accessions). A wide range of variation in leaf angle with medium heritability was observed. Leaf angle explained 36% variation in canopy light extinction coefficient, highlighting the extent to which variation in leaf angle influences light interception at the whole-canopy level. This study also found that the sorghum races of Guinea and Durra consistently having the largest and smallest leaf angle, respectively, highlighting the potential role of leaf angle in adaptation to distinct environments. The genome-wide association study detected 33 quantitative trait loci (QTLs) associated with leaf angle. Strong synteny was observed with previously detected leaf angle QTLs in maize (70%) and rice (40%) within 10 cM, among which the overlap was significantly enriched according to χ2 tests, suggesting a highly consistent genetic control in grasses. A priori leaf angle candidate genes identified in maize and rice were found to be enriched within a 1-cM window around the sorghum leaf angle QTLs. Additionally, protein domain analysis identified the WD40 protein domain as being enriched within a 1-cM window around the QTLs. These outcomes show that there is sufficient heritability and natural variation in the angle of upper leaves in sorghum which may be exploited to change light interception and optimize crop canopies for different contexts.

Genomic interrogation of a MAGIC population highlights genetic factors controlling fiber quality traits in cotton

Cotton (Gossypium hirsutum L.) fiber is the most important resource of natural and renewable fiber for the textile industry. However, the understanding of genetic components and their genome-wide interactions controlling fiber quality remains fragmentary. Here, we sequenced a multiple-parent advanced-generation inter-cross (MAGIC) population, consisting of 550 individuals created by inter-crossing 11 founders, and established a mosaic genome map through tracing the origin of haplotypes that share identity-by-descent (IBD). We performed two complementary GWAS methods—SNP-based GWAS (sGWAS) and IBD-based haplotype GWAS (hGWAS). A total of 25 sQTLs and 14 hQTLs related to cotton fiber quality were identified, of which 26 were novel QTLs. Two major QTLs detected by both GWAS methods were responsible for fiber strength and length. The gene Ghir_D11G020400 (GhZF14) encoding the MATE efflux family protein was identified as a novel candidate gene for fiber length. Beyond the additive QTLs, we detected prevalent epistatic interactions that contributed to the genetics of fiber quality, pinpointing another layer for trait variance. This study provides new targets for future molecular design breeding of superior fiber quality.

Wang and colleagues use a complementary GWAS approach to identify genetic loci associated with cotton fiber quality. Using a multiparent advanced-generation inter-cross population, 26 new QTLs related to cotton fiber quality were found.

Plasticity of root anatomy during domestication of a maize-teosinte derived population

Maize (Zea mays L.) has undergone profound changes in root anatomy for environmental adaptation during domestication. However, the genetic mechanism of plasticity of maize root anatomy during the domestication process remains unclear. In this study, high-resolution mapping was performed for nine root anatomical traits using a maize-teosinte population (mexicana × Mo17) across three environments. Large genetic variations were detected for different root anatomical traits. The cortex, stele, aerenchyma areas, xylem vessel number, and cortical cell number had large variations across three environments, indicating high plasticity. Sixteen quantitative trait loci (QTL) were identified, including seven QTL with QTL × environment interaction (EIQTL) for high plasticity traits and nine QTL without QTL × environment interaction (SQTL). Most of the root loci were consistent with shoot QTL depicting domestication signals. Combining transcriptome and genome-wide association studies revealed that AUXIN EFFLUX CARRIER PIN-FORMED LIKE 4 (ZmPILS4) serves as a candidate gene underlying a major QTL of xylem traits. The near-isogenic lines (NILs) with lower expression of ZmPILS4 had 18-24% more auxin concentration in the root tips and 8-15% more xylem vessels. Nucleotide diversity values analysis in the promoter region suggested that ZmPILS4 was involved in maize domestication and adaptation. These results revealed the potential genetic basis of root anatomical plasticity during domestication.

Genetic basis of kernel starch content decoded in a maize multi-parent population

Starch is the most abundant storage carbohydrate in maize kernels and provides calories for humans and other animals as well as raw materials for various industrial applications. Decoding the genetic basis of natural variation in kernel starch content is needed to manipulate starch quantity and quality via molecular breeding to meet future needs. Here, we identified 50 unique single quantitative trait loci (QTLs) for starch content with 18 novel QTLs via single linkage mapping, joint linkage mapping and a genome-wide association study in a multi-parent population containing six recombinant inbred line populations. Only five QTLs explained over 10% of phenotypic variation in single populations. In addition to a few large-effect and many small-effect additive QTLs, limited pairs of epistatic QTLs also contributed to the genetic basis of the variation in kernel starch content. A regional association study identified five non-starch-pathway genes that were the causal candidate genes underlying the identified QTLs for starch content. The pathway-driven analysis identified ZmTPS9, which encodes a trehalose-6-phosphate synthase in the trehalose pathway, as the causal gene for the QTL qSTA4-2, which was detected by all three statistical analyses. Knockout of ZmTPS9 increased kernel starch content and, in turn, kernel weight in maize, suggesting potential applications for ZmTPS9 in maize starch and yield improvement. These findings extend our knowledge about the genetic basis of starch content in maize kernels and provide valuable information for maize genetic improvement of starch quantity and quality.

Genome-wide association studies of yield-related traits in high-latitude japonica rice

BACKGROUND

Heilongjiang Province is a high-quality japonica rice cultivation area in China. One in ten bowls of Chinese rice is produced here. Increasing yield is one of the main aims of rice production in this area. However, yield is a complex quantitative trait composed of many factors. The purpose of this study was to determine how many genetic loci are associated with yield-related traits. Genome-wide association studies (GWAS) were performed on 450 accessions collected from northeast Asia, including Russia, Korea, Japan and Heilongjiang Province of China. These accessions consist of elite varieties and landraces introduced into Heilongjiang Province decade ago.

RESULTS

After resequencing of the 450 accessions, 189,019 single nucleotide polymorphisms (SNPs) were used for association studies by two different models, a general linear model (GLM) and a mixed linear model (MLM), examining four traits: days to heading (DH), plant height (PH), panicle weight (PW) and tiller number (TI). Over 25 SNPs were found to be associated with each trait. Among them, 22 SNPs were selected to identify candidate genes, and 2, 8, 1 and 11 SNPs were found to be located in 3' UTR region, intron region, coding region and intergenic region, respectively.

CONCLUSIONS

All SNPs detected in this research may become candidates for further fine mapping and may be used in the molecular breeding of high-latitude rice.

Genetic basis of maize kernel oil-related traits revealed by high-density SNP markers in a recombinant inbred line population

BACKGROUND

Maize (Zea mays ssp. mays) is the most abundantly cultivated and highly valued food commodity in the world. Oil from maize kernels is highly nutritious and important for the diet and health of humans, and it can be used as a source of bioenergy. A better understanding of genetic basis for maize kernel oil can help improve the oil content and quality when applied in breeding.

RESULTS

In this study, a KUI3/SC55 recombinant inbred line (RIL) population, consisting of 180 individuals was constructed from a cross between inbred lines KUI3 and SC55. We phenotyped 19 oil-related traits and subsequently dissected the genetic architecture of oil-related traits in maize kernels based on a high-density genetic map. In total, 62 quantitative trait loci (QTLs), with 2 to 5 QTLs per trait, were detected in the KUI3/SC55 RIL population. Each QTL accounted for 6.7% (qSTOL1) to 31.02% (qBELI6) of phenotypic variation and the total phenotypic variation explained (PVE) of all detected QTLs for each trait ranged from 12.5% (OIL) to 52.5% (C16:0/C16:1). Of all these identified QTLs, only 5 were major QTLs located in three genomic regions on chromosome 6 and 9. In addition, two pairs of epistatic QTLs with additive effects were detected and they explained 3.3 and 2.4% of the phenotypic variation, respectively. Colocalization with a previous GWAS on oil-related traits, identified 19 genes. Of these genes, two important candidate genes, GRMZM2G101515 and GRMZM2G022558, were further verified to be associated with C20:0/C22:0 and C18:0/C20:0, respectively, according to a gene-based association analysis. The first gene encodes a kinase-related protein with unknown function, while the second gene encodes fatty acid elongase 2 (fae2) and directly participates in the biosynthesis of very long chain fatty acids in Arabidopsis.

CONCLUSIONS

Our results provide insights on the genetic basis of oil-related traits and a theoretical basis for improving maize quality by marker-assisted selection.

Correlation analysis of the transcriptome and metabolome reveals the role of the flavonoid biosynthesis pathway in regulating axillary buds in upland cotton (Gossypium hirsutum L.)

Flavonoids are involved in axillary bud development in upland cotton. The phenylpropanoid and flavonoid biosynthesis pathways regulate axillary bud growth by promoting the transport of auxin in upland cotton. In cotton production, simplified cultivation and mechanical harvesting are emerging trends that depend on whether the cotton plant type meets production requirements. The axillary bud is an important index of cotton plant-type traits, and the molecular mechanism of axillary bud development in upland cotton has not yet been completely studied. Here, a combined investigation of transcriptome and metabolome analyses in G. hirsutum CCRI 117 at the fourth week (stage 1), fifth week (stage 2) and sixth week (stage 3) after seedling emergence was performed. The metabolome results showed that the total lipid, amino acid and organic acid contents in the first stalk node decreased during axillary bud development. The abundance of 71 metabolites was altered between stage 2 and stage 1, and 32 metabolites exhibited significantly altered abundance between stage 3 and stage 2. According to the correlation analysis of metabolome and transcriptome profiles, we found that phenylpropanoid and flavonoid biosynthesis pathways exhibit high enrichment degrees of both differential metabolites and differential genes in three stages. Based on the verification of hormone, soluble sugar and flavonoid detection, we propose a model for flavonoid-mediated regulation of axillary bud development in upland cotton, revealing that the decrease in secondary metabolites of phenylpropanoid and flavonoid biosynthesis is an essential factor to promote the transport of auxin and subsequently promote the growth of axillary buds. Our findings provide novel insights into the regulation of phenylpropanoid and flavonoid biosynthesis in axillary bud development and could prove useful for cultivating machine-harvested cotton varieties with low axillary buds.

Natural Variation in Crops: Realized Understanding, Continuing Promise

Crops feed the world's population and shape human civilization. The improvement of crop productivity has been ongoing for almost 10,000 years and has evolved from an experience-based to a knowledge-driven practice over the past three decades. Natural alleles and their reshuffling are long-standing genetic changes that affect how crops respond to various environmental conditions and agricultural practices. Decoding the genetic basis of natural variation is central to understanding crop evolution and, in turn, improving crop breeding. Here, we review current advances in the approaches used to map the causal alleles of natural variation, provide refined insights into the genetics and evolution of natural variation, and outline how this knowledge promises to drive the development of sustainable agriculture under the dome of emerging technologies.

Genetic architecture affecting maize agronomic traits identified by variance heterogeneity association mapping

Conventional genome-wide association studies (GWAS) focused on the phenotypic mean differences (mGWAS) but often ignored genetic variants influencing differences in the variance between genotypes. In this study, we performed variance heterogeneity GWAS (vGWAS) analysis for 13 previously measured agronomic traits in a maize population. We discovered a total of 129 significant SNPs. We demonstrated that the genetic loci influencing mean differences and variance heterogeneity formed distinct groups, suggesting that breeders were able to independently select for phenotype mean and variance values. Moreover, vGWAS served as a tractable approach to effectively identify 214 epistatic interaction pairs. In addition, we documented four agronomic traits with decreasing phenotype variance during modern maize breeding history and identified the potential genetic variants influencing this process. In summary, we discovered additional non-additive effects contributing to missing heritability and valuable genetic variants used for breeding varieties with desired phenotypic variance.

New genomic approaches for enhancing maize genetic improvement

Maize (Zea mays) is one of the most widely grown crops in the world, with an annual global production of over 1147 million tons. Genomics approaches are thought to be the best solution for accelerating yield improvement to meet the challenges of a growing population and global climate change. Here, we review current approaches to the exploration of novel genetic variation in genomes, DNA modifications, and transcription levels of cultivated maize, landraces, and wild relatives. We discuss applications of genetic engineering to maize yield improvement and highlight future directions for maize genomics studies.

Identifying quantitative trait loci for the general combining ability of yield-relevant traits in maize

Maize is the most important staple crop worldwide. Many of its agronomic traits present with a high level of heterosis. Combining ability was proposed to exploit the rule of heterosis, and general combining ability (GCA) is a crucial measure of parental performance. In this study, a recombinant inbred line population was used to construct testcross populations by crossing with four testers based on North Carolina design II. Six yield-relevant traits were investigated as phenotypic data. GCA effects were estimated for three scenarios based on the heterotic group and the number of tester lines. These estimates were then used to identify quantitative trait loci (QTL) and dissect genetic basis of GCA. A higher heritability of GCA was obtained for each trait. Thus, testing in early generation of breeding may effectively select candidate lines with relatively superior GCA performance. The GCA QTL detected in each scenario was slightly different according to the linkage mapping. Most of the GCA-relevant loci were simultaneously detected in all three datasets. Therefore, the genetic basis of GCA was nearly constant although discrepant inbred lines were appointed as testers. In addition, favorable alleles corresponding to GCA could be pyramided via marker-assisted selection and made available for maize hybrid breeding.

Genome-wide association studies of plant architecture-related traits and 100-seed weight in soybean landraces

BACKGROUND

Plant architecture-related traits (e.g., plant height (PH), number of nodes on main stem (NN), branch number (BN) and stem diameter (DI)) and 100-seed weight (100-SW) are important agronomic traits and are closely related to soybean yield. However, the genetic basis and breeding potential of these important agronomic traits remain largely ambiguous in soybean (Glycine max (L.) Merr.).

RESULTS

In this study, we collected 133 soybean landraces from China, phenotyped them in two years at two locations for the above five traits and conducted a genome-wide association study (GWAS) using 82,187 single nucleotide polymorphisms (SNPs). As a result, we found that a total of 59 SNPs were repeatedly detected in at least two environments. There were 12, 12, 4, 4 and 27 SNPs associated with PH, NN, BN, DI and 100-SW, respectively. Among these markers, seven SNPs (AX-90380587, AX-90406013, AX-90387160, AX-90317160, AX-90449770, AX-90460927 and AX-90520043) were large-effect markers for PH, NN, BN, DI and 100-SW, and 15 potential candidate genes were predicted to be in linkage disequilibrium (LD) decay distance or LD block. In addition, real-time quantitative PCR (qRT-PCR) analysis was performed on four 100-SW potential candidate genes, three of them showed significantly different expression levels between the extreme materials at the seed development stage. Therefore, Glyma.05 g127900, Glyma.05 g128000 and Glyma.05 g129000 were considered as candidate genes with 100-SW in soybean.

CONCLUSIONS

These findings shed light on the genetic basis of plant architecture-related traits and 100-SW in soybean, and candidate genes could be used for further positional cloning.

Developmental genetics of maize vegetative shoot architecture

More than 1.1 billion tonnes of maize grain were harvested across 197 million hectares in 2019 (FAOSTAT 2020). The vast global productivity of maize is largely driven by denser planting practices, higher yield potential per area of land, and increased yield potential per plant. Shoot architecture, the three-dimensional structural arrangement of the above-ground plant body, is critical to maize grain yield and biomass. Structure of the shoot is integral to all aspects of modern agronomic practices. Here, the developmental genetics of the maize vegetative shoot is reviewed. Plant architecture is ultimately determined by meristem activity, developmental patterning, and growth. The following topics are discussed: shoot apical meristem, leaf architecture, axillary meristem and shoot branching, and intercalary meristem and stem activity. Where possible, classical and current studies in maize developmental genetics, as well as recent advances leveraged by "-omics" analyses, are highlighted within these sections.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01208-1.

Multi-Trait Genome-Wide Association Studies Reveal Loci Associated with Maize Inflorescence and Leaf Architecture

Maize inflorescence is a complex phenotype that involves the physical and developmental interplay of multiple traits. Given the evidence that genes could pleiotropically contribute to several of these traits, we used publicly available maize data to assess the ability of multivariate genome-wide association study (GWAS) approaches to identify pleiotropic quantitative trait loci (pQTL). Our analysis of 23 publicly available inflorescence and leaf-related traits in a diversity panel of n = 281 maize lines genotyped with 376,336 markers revealed that the two multivariate GWAS approaches we tested were capable of identifying pQTL in genomic regions coinciding with similar associations found in previous studies. We then conducted a parallel simulation study on the same individuals, where it was shown that multivariate GWAS approaches yielded a higher true-positive quantitative trait nucleotide (QTN) detection rate than comparable univariate approaches for all evaluated simulation settings except for when the correlated simulated traits had a heritability of 0.9. We therefore conclude that the implementation of state-of-the-art multivariate GWAS approaches is a useful tool for dissecting pleiotropy and their more widespread implementation could facilitate the discovery of genes and other biological mechanisms underlying maize inflorescence.

Transcriptome analyses provide insights into the homeostatic regulation of axillary buds in upland cotton (G. hirsutum L.)

BACKGROUND

The axillary bud is an important index of cotton plant-type traits, and the molecular mechanism of axillary bud development in upland cotton has not yet been reported. We obtained a mutant (designated mZ571) with a high-budding phenotype in axillary bud development from the low-budding phenotype variety G. hirsutum Z571 (CCRI 9A02), which provided ideal materials for the study of complex regulatory networks of axillary bud development. In this study, RNA sequencing was carried out to detect gene expression levels during three stages of axillary buds in Z571 (LB, low budding) and mZ571 mutant (HB, high budding).

RESULTS

A total of 7162 DEGs were identified in the three groups (HB-E vs. LB-E, HB-G1 vs. LB-G1, HB-G2 vs. LB-G2), including 4014 downregulated and 3184 upregulated DEGs. Additionally, 221 DEGs were commonly identified in all three groups, accounting for approximately 3.09% of the total DEGs. These DEGs were identified, annotated and classified. A significant number of DEGs were related to hormone metabolism, hormone signal transduction, and starch and sucrose metabolism. In addition, 45, 22 and 9 DEGs involved in hormone metabolic pathways and 67, 22 and 19 DEGs involved in hormone signal transduction pathwayspathway were identified in HB-E vs. LB-E, HB-G1 vs. LB-G1, and HB-G2 vs. LB-G2, respectively, suggesting that endogenous hormones are the primary factors influencing cotton axillary bud growth. Hormone and soluble sugar content measurements revealed that mZ571 exhibited higher concentrations of zeatin, gibberellins and soluble sugar in all three stages, which confirmed that these hormone metabolism-, hormone signal transduction- and starch metabolism-related genes showed interaction effects contributing to the divergence of axillary bud growth between mZ571 and Z571.

CONCLUSIONS

Our results confirmed the importance of endogenous hormones and sugars in the development of axillary buds, and we found that mZ571 plants, with a high-budding phenotype of axillary buds, exhibited higher endogenous hormone and sugar concentrations. Overall, we present a model for the emergence and development of cotton axillary buds that provides insights into the complexity and dynamic nature of the regulatory network during axillary bud emergence and development.

Breeding Maize Maternal Haploid Inducers

Maize doubled haploid (DH) lines are usually created in vivo, through crosses with maternal haploid inducers. These inducers have the inherent ability of generating seeds with haploid embryos when used to pollinate other genotypes. The resulting haploid plants are treated with a doubling agent and self-pollinated, producing completely homozygous seeds. This rapid method of inbred line production reduces the length of breeding cycles and, consequently, increases genetic gain. Such advantages explain the wide adoption of this technique by large, well-established maize breeding programs. However, a slower rate of adoption was observed in medium to small-scale breeding programs. The high price and/or lack of environmental adaptation of inducers available for licensing, or the poor performance of those free of cost, might explain why smaller operations did not take full advantage of this technique. The lack of adapted inducers is especially felt in tropical countries, where inducer breeding efforts are more recent. Therefore, defining optimal breeding approaches for inducer development could benefit many breeding programs which are in the process of adopting the DH technique. In this manuscript, we review traits important to maize maternal haploid inducers, explain their genetic basis, listing known genes and quantitative trait loci (QTL), and discuss different breeding approaches for inducer development. The performance of haploid inducers has an important impact on the cost of DH line production.

Genetic mapping and genomic selection for maize stalk strength

BACKGROUND

Maize is one of the most important staple crops and is widely grown throughout the world. Stalk lodging can cause enormous yield losses in maize production. However, rind penetrometer resistance (RPR), which is recognized as a reliable measurement to evaluate stalk strength, has been shown to be efficient and useful for improving stalk lodging-resistance. Linkage mapping is an acknowledged approach for exploring the genetic architecture of target traits. In addition, genomic selection (GS) using whole genome markers enhances selection efficiency for genetically complex traits. In the present study, two recombinant inbred line (RIL) populations were utilized to dissect the genetic basis of RPR, which was evaluated in seven growth stages.

RESULTS

The optimal stages to measure stalk strength are the silking phase and stages after silking. A total of 66 and 45 quantitative trait loci (QTL) were identified in each RIL population. Several potential candidate genes were predicted according to the maize gene annotation database and were closely associated with the biosynthesis of cell wall components. Moreover, analysis of gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway further indicated that genes related to cell wall formation were involved in the determination of RPR. In addition, a multivariate model of genomic selection efficiently improved the prediction accuracy relative to a univariate model and a model considering RPR-relevant loci as fixed effects.

CONCLUSIONS

The genetic architecture of RPR is highly genetically complex. Multiple minor effect QTL are jointly involved in controlling phenotypic variation in RPR. Several pleiotropic QTL identified in multiple stages may contain reliable genes and can be used to develop functional markers for improving the selection efficiency of stalk strength. The application of genomic selection to RPR may be a promising approach to accelerate breeding process for improving stalk strength and enhancing lodging-resistance.

Marginal Lands to Grow Novel Bio-Based Crops: A Plant Breeding Perspective

The biomass demand to fuel a growing global bio-based economy is expected to tremendously increase over the next decades, and projections indicate that dedicated biomass crops will satisfy a large portion of it. The establishment of dedicated biomass crops raises huge concerns, as they can subtract land that is required for food production, undermining food security. In this context, perennial biomass crops suitable for cultivation on marginal lands (MALs) raise attraction, as they could supply biomass without competing for land with food supply. While these crops withstand marginal conditions well, their biomass yield and quality do not ensure acceptable economic returns to farmers and cost-effective biomass conversion into bio-based products, claiming genetic improvement. However, this is constrained by the lack of genetic resources for most of these crops. Here we first review the advantages of cultivating novel perennial biomass crops on MALs, highlighting management practices to enhance the environmental and economic sustainability of these agro-systems. Subsequently, we discuss the preeminent breeding targets to improve the yield and quality of the biomass obtainable from these crops, as well as the stability of biomass production under MALs conditions. These targets include crop architecture and phenology, efficiency in the use of resources, lignocellulose composition in relation to bio-based applications, and tolerance to abiotic stresses. For each target trait, we outline optimal ideotypes, discuss the available breeding resources in the context of (orphan) biomass crops, and provide meaningful examples of genetic improvement. Finally, we discuss the available tools to breed novel perennial biomass crops. These comprise conventional breeding methods (recurrent selection and hybridization), molecular techniques to dissect the genetics of complex traits, speed up selection, and perform transgenic modification (genetic mapping, QTL and GWAS analysis, marker-assisted selection, genomic selection, transformation protocols), and novel high-throughput phenotyping platforms. Furthermore, novel tools to transfer genetic knowledge from model to orphan crops (i.e., universal markers) are also conceptualized, with the belief that their development will enhance the efficiency of plant breeding in orphan biomass crops, enabling a sustainable use of MALs for biomass provision.

The Past, Present, and Future of Maize Improvement: Domestication, Genomics, and Functional Genomic Routes toward Crop Enhancement

After being domesticated from teosinte, cultivated maize (Zea mays ssp. mays) spread worldwide and now is one of the most important staple crops. Due to its tremendous phenotypic and genotypic diversity, maize also becomes to be one of the most widely used model plant species for fundamental research, with many important discoveries reported by maize researchers. Here, we provide an overview of the history of maize domestication and key genes controlling major domestication-related traits, review the currently available resources for functional genomics studies in maize, and discuss the functions of most of the maize genes that have been positionally cloned and can be used for crop improvement. Finally, we provide some perspectives on future directions regarding functional genomics research and the breeding of maize and other crops.

Network trade-offs and homeostasis in Arabidopsis shoot architectures

Understanding the optimization objectives that shape shoot architectures remains a critical problem in plant biology. Here, we performed 3D scanning of 152 Arabidopsis shoot architectures, including wildtype and 10 mutant strains, and we uncovered a design principle that describes how architectures make trade-offs between competing objectives. First, we used graph-theoretic analysis to show that Arabidopsis shoot architectures strike a Pareto optimal that can be captured as maximizing performance in transporting nutrients and minimizing costs in building the architecture. Second, we identify small sets of genes that can be mutated to shift the weight prioritizing one objective over the other. Third, we show that this prioritization weight feature is significantly less variable across replicates of the same genotype compared to other common plant traits (e.g., number of rosette leaves, total volume occupied). This suggests that this feature is a robust descriptor of a genotype, and that local variability in structure may be compensated for globally in a homeostatic manner. Overall, our work provides a framework to understand optimization trade-offs made by shoot architectures and provides evidence that these trade-offs can be modified genetically, which may aid plant breeding and selection efforts.

In both engineered and biological systems, there is often no single structure that performs optimally on all tasks. For example, a transport system that can very quickly shuttle people to and from work will often not be very cheap to build, and vice-versa. Thus, trade-offs are born, and it is natural to ask how well evolution has resolved trade-offs between competing tasks. Here, we use 3D laser scanning and network analysis to show that Arabidopsis plant architectures make Pareto optimal trade-offs, which means that improving upon one task requires a sacrifice in the other task. In other words, an architecture that performs better on both tasks cannot be built. We also identify a small set of genes that can change how the architecture prioritizes one task versus the other, which may allow for better crop design in the future. Finally, we show that two replicate architectures that look visually diverse (e.g., variation in size, number of leaves, number of branches, etc.) often prioritize each task similarly. This suggests that despite local variability in the architecture, there may be a homeostatic drive to maintain globally balanced trade-offs.

Genetic dissection of yield-related traits and mid-parent heterosis for those traits in maize (Zea mays L.)

BACKGROUND

Utilization of heterosis in maize could be critical in maize breeding for boosting grain yield. However, the genetic architecture of heterosis is not fully understood. To dissect the genetic basis of yield-related traits and heterosis in maize, 301 recombinant inbred lines derived from 08 to 641 × YE478 and 298 hybrids from the immortalized F₂ (IF₂) population were used to map quantitative trait loci (QTLs) for nine yield-related traits and mid-parent heterosis.

RESULTS

We observed 156 QTLs, 28 pairs of loci with epistatic interaction, and 10 significant QTL × environment interactions in the inbred and hybrid mapping populations. The high heterosis in F₁ and IF₂ populations for kernel weight per ear (KWPE), ear weight per ear (EWPE), and kernel number per row (KNPR) matched the high percentages of QTLs (over 50%) for those traits exhibiting overdominance, whereas a notable predominance of loci with dominance effects (more than 70%) was observed for traits that show low heterosis such as cob weight per ear (CWPE), rate of kernel production (RKP), ear length (EL), ear diameter (ED), cob diameter, and row number (RN). The environmentally stable QTL qRKP3-2 was identified across two mapping populations, while qKWPE9, affecting the trait mean and the mid-parent heterosis (MPH) level, explained over 18% of phenotypic variations. Nine QTLs, qEWPE9-1, qEWPE10-1, qCWPE6, qEL8, qED2-2, qRN10-1, qKWPE9, qKWPE10-1, and qRKP4-3, accounted for over 10% of phenotypic variation. In addition, QTL mapping identified 95 QTLs that were gathered together and integrated into 33 QTL clusters on 10 chromosomes.

CONCLUSIONS

The results revealed that (1) the inheritance of yield-related traits and MPH in the heterotic pattern improved Reid (PA) × Tem-tropic I (PB) is trait-dependent; (2) a large proportion of loci showed dominance effects, whereas overdominance also contributed to MPH for KNPR, EWPE, and KWPE; (3) marker-assisted selection for markers at genomic regions 1.09-1.11, 2.04, 3.08-3.09, and 10.04-10.05 contributed to hybrid performance per se and heterosis and were repeatedly reported in previous studies using different heterotic patterns is recommended.

Natural Variation and Domestication Selection of ZmPGP1 Affects Plant Architecture and Yield-Related Traits in Maize

ZmPGP1, involved in the polar auxin transport, has been shown to be associated with plant height, leaf angle, yield traits, and root development in maize. To explore natural variation and domestication selection of ZmPGP1, we re-sequenced the ZmPGP1 gene in 349 inbred lines, 68 landraces, and 32 teosintes. Sequence polymorphisms, nucleotide diversity, and neutral tests revealed that ZmPGP1 might be selected during domestication and improvement processes. Marker–trait association analysis in inbred lines identified 11 variants significantly associated with 4 plant architecture and 5 ear traits. SNP1473 was the most significant variant for kernel length and ear grain weight. The frequency of an increased allele T was 40.6% in teosintes, and it was enriched to 60.3% and 89.1% during maize domestication and improvement. This result revealed that ZmPGP1 may be selected in the domestication and improvement process, and significant variants could be used to develop functional markers to improve plant architecture and ear traits in maize.

A SNP-Based High-Density Genetic Map of Leaf and Fruit Related Quantitative Trait Loci in Wolfberry (Lycium Linn.)

Wolfberry (Lycium Linn. 2n = 24) fruit, Gouqizi, is a perennial shrub, traditional food and medicinal plant resource in China. Leaf and fruit related characteristics are economically important traits that are the focus for genetic improvement, but few studies into the molecular genetics of this crop have been reported to date. Here, an F₁ population (302 individuals) derived from a cross between "NO.1 Ningqi" (Lycium barbarum L.) and "Chinese gouqi" (Lycium chinese Mill.) was constructed. We recorded fruit weight, longitude, diameter and index along with leaf length, width and index for three consecutive years from 2015 to 2017. Based on this population and these phenotypic data, we constructed the first high-density genetic map of Lycium using specific length amplified fragment sequencing (SLAF-seq) and analyzed quantitative trait loci (QTLs). The map contains 6733 single nucleotide polymorphisms and 12 linkage groups (LG) with a total map distance of 1702.45 cM and an average map distance of 0.253 cM. A total of 55 QTLs were mapped for more than 2 years, of which 18 stable QTLs for fruit index on LG 11, spanning an interval of 73.492-90.945 cM, were detected. qFI11-15 for fruit index was an impressive QTL with logarithm of odds (LOD) and proportion of variance explained (PEV) values reaching 11.07 and 19.7%, respectively. The QTLs on LG 11 were gathered tightly, having an average interval of less than 1 cM per QTL, suggesting that there might be a cluster region controlling fruit index. Remarkably, qLI10-2 and qLI11-2 for leaf index were detectable for 3 years. These results give novel insight into the genetic control of leaf and fruit related traits in Lycium and provide robust support for undertaking further positional cloning studies and implementing marker-assisted selection in seedlings.

Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics

BACKGROUND

Trait ontology (TO) analysis is a powerful system for functional annotation and enrichment analysis of genes. However, given the complexity of the molecular mechanisms underlying phenomes, only a few hundred gene-to-TO relationships in plants have been elucidated to date, limiting the pace of research in this "big data" era.

RESULTS

Here, we curated all the available trait associated sites (TAS) information from 79 association mapping studies of maize (Zea mays L.) and rice (Oryza sativa L.) lines with diverse genetic backgrounds and built a large-scale TAS-derived TO system for functional annotation of genes in various crops. Our TO system contains information for up to 18,042 genes (6345 in maize at the 25 k level and 11,697 in rice at the 50 k level), including gene-to-TO relationships, which covers over one fifth of the annotated gene sets for maize and rice. A comparison of Gene Ontology (GO) vs. TO analysis demonstrated that the TAS-derived TO system is an efficient alternative tool for gene functional annotation and enrichment analysis. We therefore combined information from the TO, GO, metabolic pathway, and co-expression network databases and constructed the TAS system, which is publicly available at http://tas.hzau.edu.cn . TAS provides a user-friendly interface for functional annotation of genes, enrichment analysis, genome-wide extraction of trait-associated genes, and crosschecking of different functional annotation databases.

CONCLUSIONS

TAS bridges the gap between genomic and phenomic information in crops. This easy-to-use tool will be useful for geneticists, biologists, and breeders in the agricultural community, as it facilitates the dissection of molecular mechanisms conferring agronomic traits in an easy, genome-wide manner.