Michael A. Gore

Status and Prospects of Association Mapping in Plants

There is tremendous interest in using association mapping to identify genes responsible for quantitative variation of complex traits with agricultural and evolutionary importance. Recent advances in genomic technology, impetus to exploit natural diversity, and development of robust statistical analysis methods make association mapping appealing and affordable to plant research programs. Association mapping identifies quantitative trait loci (QTLs) by examining the marker‐trait associations that can be attributed to the strength of linkage disequilibrium between markers and functional polymorphisms across a set of diverse germplasm. General understanding of association mapping has increased significantly since its debut in plants. We have seen a more concerted effort in assembling various association‐mapping populations and initiating experiments through either candidate‐gene or genome‐wide approaches in different plant species. In this review, we describe the current status of association mapping in plants and outline opportunities and challenges in complex trait dissection and genomics‐assisted crop improvement.

A First-Generation Haplotype Map of Maize

A-Maize-ing Maize is one of our oldest and most important crops, having been domesticated approximately 9000 years ago in central Mexico. Schnable et al. (p. 1112; see the cover) present the results of sequencing the B73 inbred maize line. The findings elucidate how maize became diploid after an ancestral doubling of its chromosomes and reveals transposable element movement and activity and recombination. Vielle-Calzada et al. (p. 1078) have sequenced the Palomero Toluqueño (Palomero) landrace, a highland popcorn from Mexico, which, when compared to the B73 line, reveals multiple loci impacted by domestication. Swanson-Wagner et al. (p. 1118) exploit possession of the genome to analyze expression differences occurring between lines. The identification of single nucleotide polymorphisms and copy number variations among lines was used by Gore et al. (p. 1115) to generate a Haplotype map of maize. While chromosomal diversity in maize is high, it is likely that recombination is the major force affecting the levels of heterozygosity in maize. The availability of the maize genome will help to guide future agricultural and biofuel applications (see the Perspective by Feuillet and Eversole). In maize, recombination in the genome has been a limiting factor affecting evolution and breeding efforts. Maize is an important crop species of high genetic diversity. We identified and genotyped several million sequence polymorphisms among 27 diverse maize inbred lines and discovered that the genome was characterized by highly divergent haplotypes and showed 10- to 30-fold variation in recombination rates. Most chromosomes have pericentromeric regions with highly suppressed recombination that appear to have influenced the effectiveness of selection during maize inbred development and may be a major component of heterosis. We found hundreds of selective sweeps and highly differentiated regions that probably contain loci that are key to geographic adaptation. This survey of genetic diversity provides a foundation for uniting breeding efforts across the world and for dissecting complex traits through genome-wide association studies.

GAPIT: Genome Association and Prediction Integrated Tool

SUMMARY Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. AVAILABILITY http://www.maizegenetics.net/GAPIT. CONTACT zhiwu.zhang@cornell.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Maize HapMap2 identifies extant variation from a genome in flux

Whereas breeders have exploited diversity in maize for yield improvements, there has been limited progress in using beneficial alleles in undomesticated varieties. Characterizing standing variation in this complex genome has been challenging, with only a small fraction of it described to date. Using a population genetics scoring model, we identified 55 million SNPs in 103 lines across pre-domestication and domesticated Zea mays varieties, including a representative from the sister genus Tripsacum. We find that structural variations are pervasive in the Z. mays genome and are enriched at loci associated with important traits. By investigating the drivers of genome size variation, we find that the larger Tripsacum genome can be explained by transposable element abundance rather than an allopolyploid origin. In contrast, intraspecies genome size variation seems to be controlled by chromosomal knob content. There is tremendous overlap in key gene content in maize and Tripsacum, suggesting that adaptations from Tripsacum (for example, perennialism and frost and drought tolerance) can likely be integrated into maize.

Development and evaluation of a field-based high-throughput phenotyping platform

Physiological and developmental traits that vary over time are difficult to phenotype under relevant growing conditions. In this light, we developed a novel system for phenotyping dynamic traits in the field. System performance was evaluated on 25 Pima cotton (Gossypium barbadense L.) cultivars grown in 2011 at Maricopa, Arizona. Field-grown plants were irrigated under well watered and water-limited conditions, with measurements taken at different times on 3 days in July and August. The system carried four sets of sensors to measure canopy height, reflectance and temperature simultaneously on four adjacent rows, enabling the collection of phenotypic data at a rate of 0.84ha h-1. Measurements of canopy height, normalised difference vegetation index and temperature all showed large differences among cultivars and expected interactions of cultivars with water regime and time of day. Broad-sense heritabilities (H2)were highest for canopy height (H2=0.86-0.96), followed by the more environmentally sensitive normalised difference vegetation index (H2=0.28-0.90) and temperature (H2=0.01-0.90) traits. We also found a strong agreement (r2=0.35-0.82) between values obtained by the system, and values from aerial imagery and manual phenotyping approaches. Taken together, these results confirmed the ability of the phenotyping system to measure multiple traits rapidly and accurately.

Recombination Within a Nucleotide-Binding-Site/Leucine-Rich-Repeat Gene Cluster Produces New Variants Conditioning Resistance to Soybean Mosaic Virus in Soybeans

The soybean Rsv1 gene for resistance to soybean mosaic virus (SMV; Potyvirus) has previously been described as a single-locus multi-allelic gene mapping to molecular linkage group (MLG) F. Various Rsv1 alleles condition different responses to the seven (G1–G7) described strains of SMV, including extreme resistance, localized and systemic necrosis, and mosaic symptoms. We describe the cloning of a cluster of NBS-LRR resistance gene candidates from MLG F of the virus-resistant soybean line PI96983 and demonstrate that multiple genes within this cluster interact to condition unique responses to SMV strains. In addition to cloning 3gG2, a strong candidate for the major Rsv1 resistance gene from PI96983, we describe various unique resistant and necrotic reactions coincident with the presence or absence of other members of this gene cluster. Responses of recombinant lines from a high-resolution mapping population of PI96983 (resistant) × Lee 68 (susceptible) demonstrate that more than one gene in this region of the PI96983 chromosome conditions resistance and/or necrosis to SMV. In addition, the soybean cultivars Marshall and Ogden, which carry other previously described Rsv1 alleles, are shown to possess the 3gG2 gene in a NBS-LRR gene cluster background distinct from PI96983. These observations suggest that two or more related non-TIR-NBS-LRR gene products are likely involved in the allelic response of several Rsv1-containing lines to SMV.

The Genetic Architecture of Maize Height

Height is one of the most heritable and easily measured traits in maize (Zea mays L.). Given a pedigree or estimates of the genomic identity-by-state among related plants, height is also accurately predictable. But, mapping alleles explaining natural variation in maize height remains a formidable challenge. To address this challenge, we measured the plant height, ear height, flowering time, and node counts of plants grown in >64,500 plots across 13 environments. These plots contained >7300 inbreds representing most publically available maize inbreds in the United States and families of the maize Nested Association Mapping (NAM) panel. Joint-linkage mapping of quantitative trait loci (QTL), fine mapping in near isogenic lines (NILs), genome-wide association studies (GWAS), and genomic best linear unbiased prediction (GBLUP) were performed. The heritability of maize height was estimated to be >90%. Mapping NAM family-nested QTL revealed the largest explained 2.1 ± 0.9% of height variation. The effects of two tropical alleles at this QTL were independently validated by fine mapping in NIL families. Several significant associations found by GWAS colocalized with established height loci, including brassinosteroid-deficient dwarf1, dwarf plant1, and semi-dwarf2. GBLUP explained >80% of height variation in the panels and outperformed bootstrap aggregation of family-nested QTL models in evaluations of prediction accuracy. These results revealed maize height was under strong genetic control and had a highly polygenic genetic architecture. They also showed that multiple models of genetic architecture differing in polygenicity and effect sizes can plausibly explain a population’s variation in maize height, but they may vary in predictive efficacy.

Genetic association mapping identifies single nucleotide polymorphisms in genes that affect abscisic acid levels in maize floral tissues during drought

In maize, water stress at flowering causes loss of kernel set and productivity. While changes in the levels of sugars and abscisic acid (ABA) are thought to play a role in this stress response, the mechanistic basis and genes involved are not known. A candidate gene approach was used with association mapping to identify loci involved in accumulation of carbohydrates and ABA metabolites during stress. A panel of single nucleotide polymorphisms (SNPs) in genes from these metabolic pathways and in genes for reproductive development and stress response was used to genotype 350 tropical and subtropical maize inbred lines that were well watered or water stressed at flowering. Pre-pollination ears, silks, and leaves were analysed for sugars, starch, proline, ABA, ABA-glucose ester, and phaseic acid. ABA and sugar levels in silks and ears were negatively correlated with their growth. Association mapping with 1229 SNPs in 540 candidate genes identified an SNP in the maize homologue of the Arabidopsis MADS-box gene, PISTILLATA, which was significantly associated with phaseic acid in ears of well-watered plants, and an SNP in pyruvate dehydrogenase kinase, a key regulator of carbon flux into respiration, that was associated with silk sugar concentration. An SNP in an aldehyde oxidase gene was significantly associated with ABA levels in silks of water-stressed plants. Given the short range over which decay of linkage disequilibrium occurs in maize, the results indicate that allelic variation in these genes affects ABA and carbohydrate metabolism in floral tissues during drought.

CAROTENOID CLEAVAGE DIOXYGENASE4 Is a Negative Regulator of β-Carotene Content in Arabidopsis Seeds

Analysis of natural variation in Arabidopsis identified CAROTENOID CLEAVAGE DIOXYGENASE4 (CCD4) as a major negative regulator of β-carotene content in seeds and senescing leaves. Given that global vitamin A deficiency is due in part to low β-carotene levels in seeds of major food crops, this study suggests that CCDs may be critical targets for enhancing the provitamin A carotenoid levels of food crops. Experimental approaches targeting carotenoid biosynthetic enzymes have successfully increased the seed β-carotene content of crops. However, linkage analysis of seed carotenoids in Arabidopsis thaliana recombinant inbred populations showed that only 21% of quantitative trait loci, including those for β-carotene, encode carotenoid biosynthetic enzymes in their intervals. Thus, numerous loci remain uncharacterized and underutilized in biofortification approaches. Linkage mapping and genome-wide association studies of Arabidopsis seed carotenoids identified CAROTENOID CLEAVAGE DIOXYGENASE4 (CCD4) as a major negative regulator of seed carotenoid content, especially β-carotene. Loss of CCD4 function did not affect carotenoid homeostasis during seed development but greatly reduced carotenoid degradation during seed desiccation, increasing β-carotene content 8.4-fold relative to the wild type. Allelic complementation of a ccd4 null mutant demonstrated that single-nucleotide polymorphisms and insertions and deletions at the locus affect dry seed carotenoid content, due at least partly to differences in CCD4 expression. CCD4 also plays a major role in carotenoid turnover during dark-induced leaf senescence, with β-carotene accumulation again most strongly affected in the ccd4 mutant. These results demonstrate that CCD4 plays a major role in β-carotene degradation in drying seeds and senescing leaves and suggest that CCD4 orthologs would be promising targets for stabilizing and increasing the level of provitamin A carotenoids in seeds of major food crops.

Chemical-inducible, ecdysone receptor-based gene expression system for plants.

We have developed an inducible gene expression system with potential for field application using the ecdysone receptor (EcR) from the spruce budworm and the non-steroidal EcR agonist, methoxyfenozide. Chimeric transcription activators were constructed with EcR ligand binding domain, GAL4 and LexA DNA binding domains, and VP16 activation domain. In the presence of methoxyfenozide, the transcription activators induced expression of the luciferase reporter gene cloned downstream of a promoter containing GAL4- or LexA-response element and a minimal 35S promoter. Low basal and high induced luciferase expression was optimized by cloning the activator and the reporter genes in different tandem orientations. Many transgenic Arabidopsis and tobacco plants were obtained with little or no basal expression in the absence of methoxyfenozide and inducible expression that was several fold higher than that observed with the constitutive 35S promoter. Moreover, gene expression was controlled over a wide range of methoxyfenozide concentration. Our results demonstrate that the inducible gene expression system based on the spruce budworm EcR ligand binding domain with methoxyfenozide as a ligand is very effective in regulating transgenes in plants. It is suitable for field applications because methoxyfenozide is commercially available and has an exceptional health and environmental safety profile.