Genetic resolution and verification of quantitative trait loci for flowering and plant height with recombinant inbred lines of maize

Genome-wide association studies from spoken phenotypic descriptions: a proof of concept from maize field studies

We present a novel approach to genome-wide association studies (GWAS) by leveraging unstructured, spoken phenotypic descriptions to identify genomic regions associated with maize traits. Utilizing the Wisconsin Diversity panel, we collected spoken descriptions of Zea mays ssp. mays traits, converting these qualitative observations into quantitative data amenable to GWAS analysis. First, we determined that visually striking phenotypes could be detected from unstructured spoken phenotypic descriptions. Next, we developed two methods to process the same descriptions to derive the trait plant height, a well-characterized phenotypic feature in maize: (1) a semantic similarity metric that assigns a score based on the resemblance of each observation to the concept of 'tallness' and (2) a manual scoring system that categorizes and assigns values to phrases related to plant height. Our analysis successfully corroborated known genomic associations and uncovered novel candidate genes potentially linked to plant height. Some of these genes are associated with gene ontology terms that suggest a plausible involvement in determining plant stature. This proof-of-concept demonstrates the viability of spoken phenotypic descriptions in GWAS and introduces a scalable framework for incorporating unstructured language data into genetic association studies. This methodology has the potential not only to enrich the phenotypic data used in GWAS and to enhance the discovery of genetic elements linked to complex traits but also to expand the repertoire of phenotype data collection methods available for use in the field environment.

Integration of high-throughput phenotyping, GWAS, and predictive models reveals the genetic architecture of plant height in maize

Plant height (PH) is an essential trait in maize (Zea mays) that is tightly associated with planting density, biomass, lodging resistance, and grain yield in the field. Dissecting the dynamics of maize plant architecture will be beneficial for ideotype-based maize breeding and prediction, as the genetic basis controlling PH in maize remains largely unknown. In this study, we developed an automated high-throughput phenotyping platform (HTP) to systematically and noninvasively quantify 77 image-based traits (i-traits) and 20 field traits (f-traits) for 228 maize inbred lines across all developmental stages. Time-resolved i-traits with novel digital phenotypes and complex correlations with agronomic traits were characterized to reveal the dynamics of maize growth. An i-trait-based genome-wide association study identified 4945 trait-associated SNPs, 2603 genetic loci, and 1974 corresponding candidate genes. We found that rapid growth of maize plants occurs mainly at two developmental stages, stage 2 (S2) to S3 and S5 to S6, accounting for the final PH indicators. By integrating the PH-association network with the transcriptome profiles of specific internodes, we revealed 13 hub genes that may play vital roles during rapid growth. The candidate genes and novel i-traits identified at multiple growth stages may be used as potential indicators for final PH in maize. One candidate gene, ZmVATE, was functionally validated and shown to regulate PH-related traits in maize using genetic mutation. Furthermore, machine learning was used to build predictive models for final PH based on i-traits, and their performance was assessed across developmental stages. Moderate, strong, and very strong correlations between predictions and experimental datasets were achieved from the early S4 (tenth-leaf) stage. Colletively, our study provides a valuable tool for dissecting the spatiotemporal formation of specific internodes and the genetic architecture of PH, as well as resources and predictive models that are useful for molecular design breeding and predicting maize varieties with ideal plant architectures.

Linkage Mapping Reveals QTL for Flowering Time-Related Traits under Multiple Abiotic Stress Conditions in Maize

Variation in flowering plays a major role in maize photoperiod adaptation during long-term domestication. It is of high value to investigate the genetic basis of maize flowering under a wide range of environmental conditions in order to overcome photoperiod sensitivity or enhance stress tolerance. A recombinant inbred line (RIL) population derived from a cross between Huangzaosi and Mo17, composed of 121 lines and genotyped by 8329 specifically developed markers, was field evaluated in two consecutive years under two planting densities (67,500 and 120,000 plants ha−1) and two water treatments (normal irrigation and drought stress at the flowering stage). The days to silking (DTS), days to anthesis (DTA), and anthesis to silking interval (ASI) were all evaluated. Within the RIL population, DTS and DTA expanded as planting density and water deficit increased. For DTA, DTS, ASI, and ASI-delay, a total of 22, 17, 21, and 11 QTLs were identified, respectively. More than two significant QTLs were identified in each of the nine chromosomal intervals. Under diverse conditions and locations, six QTLs (quantitative trait locus) for DTS and DTA were discovered in Chr. 8: 118.13–125.31 Mb. Three chromosome regions, Chr. 3: 196.14–199.89 Mb, Chr. 8: 169.02–172.46 Mb, and Chr. 9: 128.12–137.26 Mb, all had QTLs for ASI-delay under normal and stress conditions, suggesting their possible roles in stress tolerance enhancement. These QTL hotspots will promote early-maturing or multiple abiotic stress-tolerant maize breeding, as well as shed light on the development of maize varieties with a broad range of adaptations.

Genetic dissection of maize seedling traits in an IBM Syn10 DH population under the combined stress of lead and cadmium

The heavy metals lead and cadmium have become important pollutants in the environment, which exert negative effects on plant morphology, growth and photosynthesis. It is particularly significant to uncover the genetic loci and the causal genes for lead and cadmium tolerance in plants. This study used an IBM Syn10 DH population to identify the quantitative trait loci (QTL) controlling maize seedling tolerance to lead and cadmium by linkage mapping. The broad-sense heritability of these seedling traits ranged from 65.8-97.3% and 32.0-98.8% under control (CK) and treatment (T) conditions, respectively. A total of 53 and 64 QTL were detected under CK and T conditions, respectively. Moreover, 42 QTL were identified using lead and cadmium tolerance coefficient (LCTC). Among these QTL, five and two major QTL that explained > 10% of phenotypic variation were identified under T condition and using LCTC, respectively. Furthermore, eight QTL were simultaneously identified by T and LCTC, explaining 5.23% to 9.21% of the phenotypic variations. Within these major and common QTL responsible for the combined heavy metal tolerance, four candidate genes (Zm00001d048759, Zm00001d004689, Zm00001d004843, Zm00001d033527) were previously reported to correlate with heavy metal transport and tolerance. These findings will contribute to functional gene identification and molecular marker-assisted breeding for improving heavy metal tolerance in maize.

Single-plant GWAS coupled with bulk segregant analysis allows rapid identification and corroboration of plant-height candidate SNPs

BACKGROUND

Genome wide association studies (GWAS) are a powerful tool for identifying quantitative trait loci (QTL) and causal single nucleotide polymorphisms (SNPs)/genes associated with various important traits in crop species. Typically, GWAS in crops are performed using a panel of inbred lines, where multiple replicates of the same inbred are measured and the average phenotype is taken as the response variable. Here we describe and evaluate single plant GWAS (sp-GWAS) for performing a GWAS on individual plants, which does not require an association panel of inbreds. Instead sp-GWAS relies on the phenotypes and genotypes from individual plants sampled from a randomly mating population. Importantly, we demonstrate how sp-GWAS can be efficiently combined with a bulk segregant analysis (BSA) experiment to rapidly corroborate evidence for significant SNPs.

RESULTS

In this study we used the Shoepeg maize landrace, collected as an open pollinating variety from a farm in Southern Missouri in the 1960's, to evaluate whether sp-GWAS coupled with BSA can efficiently and powerfully used to detect significant association of SNPs for plant height (PH). Plant were grown in 8 locations across two years and in total 768 individuals were genotyped and phenotyped for sp-GWAS. A total of 306 k polymorphic markers in 768 individuals evaluated via association analysis detected 25 significant SNPs (P ≤ 0.00001) for PH. The results from our single-plant GWAS were further validated by bulk segregant analysis (BSA) for PH. BSA sequencing was performed on the same population by selecting tall and short plants as separate bulks. This approach identified 37 genomic regions for plant height. Of the 25 significant SNPs from GWAS, the three most significant SNPs co-localize with regions identified by BSA.

CONCLUSION

Overall, this study demonstrates that sp-GWAS coupled with BSA can be a useful tool for detecting significant SNPs and identifying candidate genes. This result is particularly useful for species/populations where association panels are not readily available.

ZmMADS69 functions as a flowering activator through the ZmRap2.7-ZCN8 regulatory module and contributes to maize flowering time adaptation

Flowering time is a major determinant of the local adaptation of plants. Although numerous loci affecting flowering time have been mapped in maize, their underlying molecular mechanisms and roles in adaptation remain largely unknown. Here, we report the identification and characterization of MADS-box transcription factor ZmMADS69 that functions as a flowering activator through the ZmRap2.7-ZCN8 regulatory module and contributes to adaptation. We show that ZmMADS69 underlies a quantitative trait locus controlling the difference in flowering time between maize and its wild ancestor, teosinte. Maize ZmMADS69 allele is expressed at a higher level at floral transition and confers earlier flowering than the teosinte allele under long days and short days. Overexpression of ZmMADS69 causes early flowering, while a transposon insertion mutant of ZmMADS69 exhibits delayed flowering. ZmMADS69 shows pleiotropic effects for multiple traits of agronomic importance. ZmMADS69 functions upstream of the flowering repressor ZmRap2.7 to downregulate its expression, thereby relieving the repression of the florigen gene ZCN8 and causing early flowering. Population genetic analyses showed that ZmMADS69 was a target of selection and may have played an important role as maize spread from the tropics to temperate zones. Our findings provide important insights into the regulation and adaptation of flowering time.

Genome-wide association analysis of stalk biomass and anatomical traits in maize

BACKGROUND

Maize stover is an important source of crop residues and a promising sustainable energy source in the United States. Stalk is the main component of stover, representing about half of stover dry weight. Characterization of genetic determinants of stalk traits provide a foundation to optimize maize stover as a biofuel feedstock. We investigated maize natural genetic variation in genome-wide association studies (GWAS) to detect candidate genes associated with traits related to stalk biomass (stalk diameter and plant height) and stalk anatomy (rind thickness, vascular bundle density and area).

RESULTS

Using a panel of 942 diverse inbred lines, 899,784 RNA-Seq derived single nucleotide polymorphism (SNP) markers were identified. Stalk traits were measured on 800 members of the panel in replicated field trials across years. GWAS revealed 16 candidate genes associated with four stalk traits. Most of the detected candidate genes were involved in fundamental cellular functions, such as regulation of gene expression and cell cycle progression. Two of the regulatory genes (Zmm22 and an ortholog of Fpa) that were associated with plant height were previously shown to be involved in regulating the vegetative to floral transition. The association of Zmm22 with plant height was confirmed using a transgenic approach. Transgenic lines with increased expression of Zmm22 showed a significant decrease in plant height as well as tassel branch number, indicating a pleiotropic effect of Zmm22.

CONCLUSION

Substantial heritable variation was observed in the association panel for stalk traits, indicating a large potential for improving useful stalk traits in breeding programs. Genome-wide association analyses detected several candidate genes associated with multiple traits, suggesting common regulatory elements underlie various stalk traits. Results of this study provide insights into the genetic control of maize stalk anatomy and biomass.

Time dependent genetic analysis links field and controlled environment phenotypes in the model C4 grass Setaria

Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reduced under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development.

Growth is a dynamic process that responds to a changing environment. Most of the methods that we have for measuring are static and collecting information throughout an organisms lifecycle is labor and cost prohibitive. Advances in imaging and robotics technology have enabled novel approaches to understanding how plants adapt to the environment. Using the model grass Setaria and new methods for measuring parameters from images, we investigate the genetic architecture of plant height in response to water availability and planting density. Height is one of the most influential components of plant architecture, determining tradeoffs between competition and resource allocation and is an important trait for boosting yields. The non-destructive nature of plant height measurements has enabled us to monitor growth throughout the plant life cycle in both field and controlled environments. We identified several loci controlling height in a population derived from a wild strain of Setaria viridis and its domesticated relative Setaria italica, as well as the developmental time in which these loci act. In this population, alleles inherited from the wild parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated parent collectively act to increase plant height later in development.

The genetic architecture of leaf number and its genetic relationship to flowering time in maize

The number of leaves and their distributions on plants are critical factors determining plant architecture in maize (Zea mays), and leaf number is frequently used as a measure of flowering time, a trait that is key to local environmental adaptation. Here, using a large set of 866 maize-teosinte BC2 S3 recombinant inbred lines genotyped by using 19,838 single nucleotide polymorphism markers, we conducted a comprehensive genetic dissection to assess the genetic architecture of leaf number and its genetic relationship to flowering time. We demonstrated that the two components of total leaf number, the number of leaves above (LA) and below (LB) the primary ear, were under relatively independent genetic control and might be subject to differential directional selection during maize domestication and improvement. Furthermore, we revealed that flowering time and leaf number are commonly regulated at a moderate level. The pleiotropy of the genes ZCN8, dlf1 and ZmCCT on leaf number and flowering time were validated by near-isogenic line analysis. Through fine mapping, qLA1-1, a major-effect locus that specifically affects LA, was delimited to a region with severe recombination suppression derived from teosinte. This study provides important insights into the genetic basis of traits affecting plant architecture and adaptation. The genetic independence of LA from LB enables the optimization of leaf number for ideal plant architecture breeding in maize.

Shared Genomic Regions Between Derivatives of a Large Segregating Population of Maize Identified Using Bulked Segregant Analysis Sequencing and Traditional Linkage Analysis

Delayed transition from the vegetative stage to the reproductive stage of development and increased plant height have been shown to increase biomass productivity in grasses. The goal of this project was to detect quantitative trait loci using extremes from a large synthetic population, as well as a related recombinant inbred line mapping population for these two traits. Ten thousand individuals from a B73 × Mo17 noninbred population intermated for 14 generations (IBM Syn14) were grown at a density of approximately 16,500 plants ha(-1). Flowering time and plant height were measured within this population. DNA was pooled from the 46 most extreme individuals from each distributional tail for each of the traits measured and used in bulk segregant analysis (BSA) sequencing. Allelic divergence at each of the ∼1.1 million SNP loci was estimated as the difference in allele frequencies between the selected extremes. Additionally, 224 intermated B73 × Mo17 recombinant inbred lines were concomitantly grown at a similar density adjacent to the large synthetic population and were assessed for flowering time and plant height. Using the BSA sequencing method, 14 and 13 genomic regions were identified for flowering time and plant height, respectively. Linkage mapping with the RIL population identified eight and three regions for flowering time and plant height, respectively. Of the regions identified, three colocalized between the two populations for flowering time and two colocalized for plant height. This study demonstrates the utility of using BSA sequencing for the dissection of complex quantitative traits important for production of lignocellulosic ethanol.

Genetic control of water use efficiency and leaf carbon isotope discrimination in sunflower (Helianthus annuus L.) subjected to two drought scenarios

High water use efficiency (WUE) can be achieved by coordination of biomass accumulation and water consumption. WUE is physiologically and genetically linked to carbon isotope discrimination (CID) in leaves of plants. A population of 148 recombinant inbred lines (RILs) of sunflower derived from a cross between XRQ and PSC8 lines was studied to identify quantitative trait loci (QTL) controlling WUE and CID, and to compare QTL associated with these traits in different drought scenarios. We conducted greenhouse experiments in 2011 and 2012 by using 100 balances which provided a daily measurement of water transpired, and we determined WUE, CID, biomass and cumulative water transpired by plants. Wide phenotypic variability, significant genotypic effects, and significant negative correlations between WUE and CID were observed in both experiments. A total of nine QTL controlling WUE and eight controlling CID were identified across the two experiments. A QTL for phenotypic response controlling WUE and CID was also significantly identified. The QTL for WUE were specific to the drought scenarios, whereas the QTL for CID were independent of the drought scenarios and could be found in all the experiments. Our results showed that the stable genomic regions controlling CID were located on the linkage groups 06 and 13 (LG06 and LG13). Three QTL for CID were co-localized with the QTL for WUE, biomass and cumulative water transpired. We found that CID and WUE are highly correlated and have common genetic control. Interestingly, the genetic control of these traits showed an interaction with the environment (between the two drought scenarios and control conditions). Our results open a way for breeding higher WUE by using CID and marker-assisted approaches and therefore help to maintain the stability of sunflower crop production.

Using near-isogenic barley lines to validate deoxynivalenol (DON) QTL previously identified through association analysis

Fusarium head blight (FHB) and its associated mycotoxin, deoxynivalenol (DON), are the major biotic factors limiting cereal production in many parts of the world. A recent association mapping (AM) study of US six-row spring barley identified several modest effect quantitative trait loci (QTL) for DON and FHB. To date, few studies have attempted to verify the results of association analyses, particularly for complex traits such as DON and FHB resistance in barley. While AM methods use measures to control for the effects of population structure and multiple testing, false positive associations may still occur. A previous AM study used elite breeding germplasm to identify QTL for FHB and DON. To verify the results of that study, we evaluated the effects of the nine DON QTL using near-isogenic lines (NILs). We created families of contrasting homozygous haplotypes from lines in the original AM populations that were heterozygous for the DON QTL. Seventeen NIL families were evaluated for FHB and DON in three field experiments. Significant differences between contrasting NIL haplotypes were detected for three QTL across environments and/or genetic backgrounds, thereby confirming QTL from the original AM study. Several explanations for those QTL that were not confirmed are discussed, including the effect of genetic background and incomplete sampling of relevant haplotypes.

Identification of bioconversion quantitative trait loci in the interspecific cross Sorghum bicolor × Sorghum propinquum

For lignocellulosic bioenergy to be economically viable, genetic improvements must be made in feedstock quality including both biomass total yield and conversion efficiency. Toward this goal, multiple studies have considered candidate genes and discovered quantitative trait loci (QTL) associated with total biomass accumulation and/or grain production in bioenergy grass species including maize and sorghum. However, very little research has been focused on genes associated with increased biomass conversion efficiency. In this study, Trichoderma viride fungal cellulase hydrolysis activity was measured for lignocellulosic biomass (leaf and stem tissue) obtained from individuals in a F5 recombinant inbred Sorghum bicolor × Sorghum propinquum mapping population. A total of 49 QTLs (20 leaf, 29 stem) were associated with enzymatic conversion efficiency. Interestingly, six high-density QTL regions were identified in which four or more QTLs overlapped. In addition to enzymatic conversion efficiency QTLs, two QTLs were identified for biomass crystallinity index, a trait which has been shown to be inversely correlated with conversion efficiency in bioenergy grasses. The identification of these QTLs provides an important step toward identifying specific genes relevant to increasing conversion efficiency of bioenergy feedstocks. DNA markers linked to these QTLs could be useful in marker-assisted breeding programs aimed at increasing overall bioenergy yields concomitant with selection of high total biomass genotypes.

ZmGA3ox2, a candidate gene for a major QTL, qPH3.1, for plant height in maize

Maize plant height is closely associated with biomass, lodging resistance and grain yield. Determining the genetic basis of plant height by characterizing and cloning plant height genes will guide the genetic improvement of crops. In this study, a quantitative trait locus (QTL) for plant height, qPH3.1, was identified on chromosome 3 using populations derived from a cross between Zong3 and its chromosome segment substitution line, SL15. The plant height of the two lines was obviously different, and application of exogenous gibberellin A(3) removed this difference. QTL mapping placed qPH3.1 within a 4.0 cM interval, explaining 32.3% of the phenotypic variance. Furthermore, eight homozygous segmental isolines (SILs) developed from two larger F(2) populations further narrowed down qPH3.1 to within a 12.6 kb interval. ZmGA3ox2, an ortholog of OsGA3ox2, which encodes a GA3 β-hydroxylase, was positionally cloned. Association mapping identified two polymorphisms in ZmGA3ox2 that were significantly associated with plant height across two experiments. Quantitative RT-PCR showed that SL15 had higher ZmGA3ox2 expression relative to Zong3. The resultant higher GA(1) accumulation led to longer internodes in SL15 because of increased cell lengths. Moreover, a large deletion in the coding region of ZmGA3ox2 is responsible for the dwarf mutant d1-6016. The successfully isolated qPH3.1 enriches our knowledge on the genetic basis of plant height in maize, and provides an opportunity for improvement of plant architecture in maize breeding.

Bioenergy grass feedstock: current options and prospects for trait improvement using emerging genetic, genomic, and systems biology toolkits

For lignocellulosic bioenergy to become a viable alternative to traditional energy production methods, rapid increases in conversion efficiency and biomass yield must be achieved. Increased productivity in bioenergy production can be achieved through concomitant gains in processing efficiency as well as genetic improvement of feedstock that have the potential for bioenergy production at an industrial scale. The purpose of this review is to explore the genetic and genomic resource landscape for the improvement of a specific bioenergy feedstock group, the C4 bioenergy grasses. First, bioenergy grass feedstock traits relevant to biochemical conversion are examined. Then we outline genetic resources available bioenergy grasses for mapping bioenergy traits to DNA markers and genes. This is followed by a discussion of genomic tools and how they can be applied to understanding bioenergy grass feedstock trait genetic mechanisms leading to further improvement opportunities.

Detection of QTL for flowering time in multiple families of elite maize

Flowering time is a fundamental quantitative trait in maize that has played a key role in the postdomestication process and the adaptation to a wide range of climatic conditions. Flowering time has been intensively studied and recent QTL mapping results based on diverse founders suggest that the genetic architecture underlying this trait is mainly based on numerous small-effect QTL. Here, we used a population of 684 progenies from five connected families to investigate the genetic architecture of flowering time in elite maize. We used a joint analysis and identified nine main effect QTL explaining approximately 50 % of the genotypic variation of the trait. The QTL effects were small compared with the observed phenotypic variation and showed strong differences between families. We detected no epistasis with the genetic background but four digenic epistatic interactions in a full 2-dimensional genome scan. Our results suggest that flowering time in elite maize is mainly controlled by main effect QTL with rather small effects but that epistasis may also contribute to the genetic architecture of the trait.

Genome-wide association mapping of flowering time and northern corn leaf blight (Setosphaeria turcica) resistance in a vast commercial maize germplasm set

BACKGROUND

Setosphaeria turcica is a fungal pathogen that causes northern corn leaf blight (NCLB) which is a serious foliar disease in maize. In order to unravel the genetic architecture of the resistance against this disease, a vast association mapping panel comprising 1487 European maize inbred lines was used to (i) identify chromosomal regions affecting flowering time (FT) and northern corn leaf blight (NCLB) resistance, (ii) examine the epistatic interactions of the identified chromosomal regions with the genetic background on an individual molecular marker basis, and (iii) dissect the correlation between NCLB resistance and FT.

RESULTS

The single marker analyses performed for 8 244 single nucleotide polymorphism (SNP) markers revealed seven, four, and four SNP markers significantly (α=0.05, amplicon wise Bonferroni correction) associated with FT, NCLB, and NCLB resistance corrected for FT, respectively. These markers explained individually between 0.36 and 14.29% of the genetic variance of the corresponding trait.

CONCLUSIONS

The very well interpretable pattern of SNP associations observed for FT suggested that data from applied plant breeding programs can be used to dissect polygenic traits. This in turn indicates that the associations identified for NCLB resistance might be successfully used in marker-assisted selection programs. Furthermore, the associated genes are also of interest for further research concerning the mechanism of resistance to NCLB and plant diseases in general, because some of the associated genes have not been mentioned in this context so far.

Gene discovery in cereals through quantitative trait loci and expression analysis in water-use efficiency measured by carbon isotope discrimination

Drought continues to be a major constraint on cereal production in many areas, and the frequency of drought is likely to increase in most arid and semi-arid regions under future climate change scenarios. Considerable research and breeding efforts have been devoted to investigating crop responses to drought at various levels and producing drought-resistant genotypes. Plant physiology has provided new insights to yield improvement in drought-prone environments. Crop performance could be improved through increases in water use, water-use efficiency (WUE) and harvest index. Greater WUE can be achieved by coordination between photosynthesis and transpiration. Carbon isotope discrimination (Δ(13) C) has been demonstrated to be a simple but reliable measure of WUE, and negative correlation between them has been used to indirectly estimate WUE under selected environments. New tools, such as quantitative trait loci (QTL) mapping and gene expression profiling, are playing vital roles in dissecting drought resistance-related traits. The combination of gene expression and association mapping could help identify candidate genes underlying the QTL of interest and complement map-based cloning and marker-assisted selection. Eventually, improved cultivars can be produced through genetic engineering. Future efficient and effective breeding progress in cereals under targeted drought environments will come from the integrated knowledge of physiology and genomics.

Detailed analysis of a contiguous 22-Mb region of the maize genome

Most of our understanding of plant genome structure and evolution has come from the careful annotation of small (e.g., 100 kb) sequenced genomic regions or from automated annotation of complete genome sequences. Here, we sequenced and carefully annotated a contiguous 22 Mb region of maize chromosome 4 using an improved pseudomolecule for annotation. The sequence segment was comprehensively ordered, oriented, and confirmed using the maize optical map. Nearly 84% of the sequence is composed of transposable elements (TEs) that are mostly nested within each other, of which most families are low-copy. We identified 544 gene models using multiple levels of evidence, as well as five miRNA genes. Gene fragments, many captured by TEs, are prevalent within this region. Elimination of gene redundancy from a tetraploid maize ancestor that originated a few million years ago is responsible in this region for most disruptions of synteny with sorghum and rice. Consistent with other sub-genomic analyses in maize, small RNA mapping showed that many small RNAs match TEs and that most TEs match small RNAs. These results, performed on approximately 1% of the maize genome, demonstrate the feasibility of refining the B73 RefGen_v1 genome assembly by incorporating optical map, high-resolution genetic map, and comparative genomic data sets. Such improvements, along with those of gene and repeat annotation, will serve to promote future functional genomic and phylogenomic research in maize and other grasses.

Key impact of Vgt1 on flowering time adaptation in maize: evidence from association mapping and ecogeographical information

An association study conducted on 375 maize inbred lines indicates a strong relationship between Vgt1 polymorphisms and flowering time, extending former quantitative trait loci (QTL) mapping results. Analysis of allele frequencies in a landrace collection supports a key role of Vgt1 in maize altilatitudinal adaptation.

Conserved noncoding genomic sequences associated with a flowering-time quantitative trait locus in maize

Flowering time is a fundamental trait of maize adaptation to different agricultural environments. Although a large body of information is available on the map position of quantitative trait loci for flowering time, little is known about the molecular basis of quantitative trait loci. Through positional cloning and association mapping, we resolved the major flowering-time quantitative trait locus, Vegetative to generative transition 1 (Vgt1), to an approximately 2-kb noncoding region positioned 70 kb upstream of an Ap2-like transcription factor that we have shown to be involved in flowering-time control. Vgt1 functions as a cis-acting regulatory element as indicated by the correlation of the Vgt1 alleles with the transcript expression levels of the downstream gene. Additionally, within Vgt1, we identified evolutionarily conserved noncoding sequences across the maize-sorghum-rice lineages. Our results support the notion that changes in distant cis-acting regulatory regions are a key component of plant genetic adaptation throughout breeding and evolution.

The genetic relationship among plant-height traits found using multiple-trait QTL mapping of a dent corn and popcorn cross

Plant height (PH) is one of the most important traits in maize breeding programs. In popcorn, inferior plant traits can be improved with the dent/flint corn germplasm. In the current study, a total of 259 F2:3families, developed from a cross between a dent corn inbred and a popcorn inbred, were evaluated for 4 PH traits. Quantitative trait loci (QTLs) for each trait were detected using composite interval mapping methods. In addition, genetic interrelationships were investigated using multiple-trait joint analysis for PH with ear height (EH), and for PH with top height (TH). In total, 6, 5, 2, and 6 QTLs were identified for PH, EH, TH, and TH/PH in single-trait analysis, respectively. Joint-analysis data suggest a strong and complex genetic relationship between PH and EH, and between PH and EH, with no QTLs controlling any single trait independently. In addition, 4 kinds of QTLs detected were classified as closely linked QTLs, pleiotropic QTLs, QTLs with opposite effects, and additional QTLs. It was, consequently, difficult to improve lodge resistance through selection on any individual PH trait. The current study demonstrates that multiple-trait joint analysis not only identified additional QTLs, but also revealed the genetic relationship among different highly correlated traits at the molecular level.

Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome

Genetic architecture of flowering time in maize was addressed by synthesizing a total of 313 quantitative trait loci (QTL) available for this trait. These were analyzed first with an overview statistic that highlighted regions of key importance and then with a meta-analysis method that yielded a synthetic genetic model with 62 consensus QTL. Six of these displayed a major effect. Meta-analysis led in this case to a twofold increase in the precision in QTL position estimation, when compared to the most precise initial QTL position within the corresponding region. The 62 consensus QTL were compared first to the positions of the few flowering-time candidate genes that have been mapped in maize. We then projected rice candidate genes onto the maize genome using a synteny conservation approach based on comparative mapping between the maize genetic map and japonica rice physical map. This yielded 19 associations between maize QTL and genes involved in flowering time in rice and in Arabidopsis. Results suggest that the combination of meta-analysis within a species of interest and synteny-based projections from a related model plant can be an efficient strategy for identifying new candidate genes for trait variation.

Evaluating genetic relationships between tropical maize inbred lines by means of AFLP profiling

Diversity among tropical maize inbred lines that compose breeding programs, is not well known. The lack of this information has made the arrangement of heterotic groups to be used for breeding purposes difficult. Methods of molecular analysis have been used as efficient alternatives for evaluating genetic diversity, aiming at heterotic group arrangement and acquisition of new hybrids. In this study, AFLP (amplified fragment length polymorphism) was used to investigate the genetic relationships among 96 tropical maize inbred lines from two different origins. The polymorphism level among the genotypes and the possibility of their allocation in heterotic groups were evaluated. Besides, correlations among genetic diversity and flowering time were analyzed. Nine primer combinations were used to obtain AFLP markers, producing 638 bands, 569 of which were polymorphic. Genetic similarities (GS), determined by Jaccard's similarity coefficient, varied from 0.345 to 0.891, with an average of 0.543. The dendrogram based on the GS and on the UPGMA cluster method did not separate the inbred lines in well-defined groups. Aiming at separating the lines into more accurate groups, Tocher's optimization procedure was carried out, 17 groups being identified. Association between flowering time and germplasm pools was detected. AFLP showed itself to be a robust assay, revealing a great power of detection of genetic variability in the tropical germplasm, and also demonstrated to be very useful for guiding breeding programs.

Comparative analysis of QTLs affecting plant height and flowering among closely-related diploid and polyploid genomes

Quantitative trait loci (QTLs) affecting plant height and flowering were studied in the two Saccharum species from which modern sugarcane cultivars are derived. Two segregating populations derived from interspecific crosses between Saccharum officinarum and Saccharum spontaneum were genotyped with 735 DNA markers. Among the 65 significant associations found between these two traits and DNA markers, 35 of the loci were linked to sugarcane genetic maps and 30 were unlinked DNA markers. Twenty-one of the 35 mapped QTLs were clustered in eight genomic regions of six sugarcane homologous groups. Some of these could be divergent alleles at homologous loci, making the actual number of genes implicated in these traits much less than 35. Four QTL clusters controlling plant height in sugarcane corresponded closely to four of the six plant-height QTLs previously mapped in sorghum. One QTL controlling flowering in sugarcane corresponded to one of three flowering QTLs mapped in sorghum. The correspondence in locations of QTLs affecting plant height and flowering in sugarcane and sorghum reinforce the notion that the simple sorghum genome is a valuable "template" for molecular dissection of the much more complex sugarcane genome.

Effects of Phaseolus vulgaris QTL in controlling host-bacteria interactions under two levels of nitrogen fertilization

Molecular markers were used to estimate the effect of mineral nitrogen on the phenotypic expression of quantitative trait loci (QTL) controlling the number of Rhizobium nodules (NN) and resistance to Xanthomonas axonopodis pv. phaseoli in the common bean. Recombinant inbred lines derived from a BAT-93 x Jalo EEP558 cross were grown in a greenhouse in the absence or presence (5 mM NH4NO3) of nitrogen. Resistance to Xanthomonas was assessed as diseased leaf area (DLA) and the number of nodules was obtained by direct counting. Analyses of variance were used to detect significant associations between 85 marker loci from 12 linkage groups (LG) and quantitative traits. In the absence of nitrogen, 15 and 11 markers, distributed over 7 and 5 LG, showed a significant association with NN and DLA, respectively. The combined percentage of phenotypic variance explained by the marker-loci and QTL associations was 34% for NN and 42% for DLA. In the presence of nitrogen, there were only five significant associations for NN and eight for DLA, which explained 28 and 26% of the total phenotypic variance, respectively. The effects of some QTL were detected only at a certain level of nitrogen. The contribution of parental alleles at two NN QTL was dependent on the level of nitrogen. Four QTL were associated with both the number of Rhizobium nodules and resistance to Xanthomonas, suggesting a common genetic control of responses to bacterial infections in the common bean. Despite the dramatic environmental interactions noted with some QTL, in other cases the phenotypic effects were not affected by the amount of nitrogen. The stability of the latter QTL may be relevant when breeding cultivars adapted to variable soil fertility.

A maize map standard with sequenced core markers, grass genome reference points and 932 expressed sequence tagged sites (ESTs) in a 1736-locus map

We have constructed a 1736-locus maize genome map containing1156 loci probed by cDNAs, 545 probed by random genomic clones, 16 by simple sequence repeats (SSRs), 14 by isozymes, and 5 by anonymous clones. Sequence information is available for 56% of the loci with 66% of the sequenced loci assigned functions. A total of 596 new ESTs were mapped from a B73 library of 5-wk-old shoots. The map contains 237 loci probed by barley, oat, wheat, rice, or tripsacum clones, which serve as grass genome reference points in comparisons between maize and other grass maps. Ninety core markers selected for low copy number, high polymorphism, and even spacing along the chromosome delineate the 100 bins on the map. The average bin size is 17 cM. Use of bin assignments enables comparison among different maize mapping populations and experiments including those involving cytogenetic stocks, mutants, or quantitative trait loci. Integration of nonmaize markers in the map extends the resources available for gene discovery beyond the boundaries of maize mapping information into the expanse of map, sequence, and phenotype information from other grass species. This map provides a foundation for numerous basic and applied investigations including studies of gene organization, gene and genome evolution, targeted cloning, and dissection of complex traits.