James B. Holland

A unified mixed-model method for association mapping that accounts for multiple levels of relatedness

As population structure can result in spurious associations, it has constrained the use of association studies in human and plant genetics. Association mapping, however, holds great promise if true signals of functional association can be separated from the vast number of false signals generated by population structure. We have developed a unified mixed-model approach to account for multiple levels of relatedness simultaneously as detected by random genetic markers. We applied this new approach to two samples: a family-based sample of 14 human families, for quantitative gene expression dissection, and a sample of 277 diverse maize inbred lines with complex familial relationships and population structure, for quantitative trait dissection. Our method demonstrates improved control of both type I and type II error rates over other methods. As this new method crosses the boundary between family-based and structured association samples, it provides a powerful complement to currently available methods for association mapping.

Genetic Properties of the Maize Nested Association Mapping Population

Codifying Maize Modifications Maize, one of our most important crop species, has been the target of genetic investigation and experimentation for more than 100 years. Crossing two inbred lines tends to result in “better” offspring, in a process known as heterosis. Attempts to map the genetic loci that control traits important for farming have been made, but few have been successful (see the Perspective by Mackay). Buckler et al. (p. 714) and McMullen et al. (p. 737) produced a genomic map of maize that relates recombination to genome structure. Even tremendous adaptations in very diverse species were produced by numerous, small additive steps. Differences in flowering time in maize among inbred lines were not caused by a few genes with large effects, but by the cumulative effects of numerous quantitative trait loci—each of which has only a small impact on the trait. Outcrossing vigor in maize is most likely due to retained variability in regions around the centromeres. Maize genetic diversity has been used to understand the molecular basis of phenotypic variation and to improve agricultural efficiency and sustainability. We crossed 25 diverse inbred maize lines to the B73 reference line, capturing a total of 136,000 recombination events. Variation for recombination frequencies was observed among families, influenced by local (cis) genetic variation. We identified evidence for numerous minor single-locus effects but little two-locus linkage disequilibrium or segregation distortion, which indicated a limited role for genes with large effects and epistatic interactions on fitness. We observed excess residual heterozygosity in pericentromeric regions, which suggested that selection in inbred lines has been less efficient in these regions because of reduced recombination frequency. This implies that pericentromeric regions may contribute disproportionally to heterosis.

Genetic Design and Statistical Power of Nested Association Mapping in Maize

We investigated the genetic and statistical properties of the nested association mapping (NAM) design currently being implemented in maize (26 diverse founders and 5000 distinct immortal genotypes) to dissect the genetic basis of complex quantitative traits. The NAM design simultaneously exploits the advantages of both linkage analysis and association mapping. We demonstrated the power of NAM for high-power cost-effective genome scans through computer simulations based on empirical marker data and simulated traits with different complexities. With common-parent-specific (CPS) markers genotyped for the founders and the progenies, the inheritance of chromosome segments nested within two adjacent CPS markers was inferred through linkage. Genotyping the founders with additional high-density markers enabled the projection of genetic information, capturing linkage disequilibrium information, from founders to progenies. With 5000 genotypes, 30–79% of the simulated quantitative trait loci (QTL) were precisely identified. By integrating genetic design, natural diversity, and genomics technologies, this new complex trait dissection strategy should greatly facilitate endeavors to link molecular variation with phenotypic variation for various complex traits.

Genome-wide association study of leaf architecture in the maize nested association mapping population

US maize yield has increased eight-fold in the past 80 years, with half of the gain attributed to selection by breeders. During this time, changes in maize leaf angle and size have altered plant architecture, allowing more efficient light capture as planting density has increased. Through a genome-wide association study (GWAS) of the maize nested association mapping panel, we determined the genetic basis of important leaf architecture traits and identified some of the key genes. Overall, we demonstrate that the genetic architecture of the leaf traits is dominated by small effects, with little epistasis, environmental interaction or pleiotropy. In particular, GWAS results show that variations at the liguleless genes have contributed to more upright leaves. These results demonstrate that the use of GWAS with specially designed mapping populations is effective in uncovering the basis of key agronomic traits.

Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population

Nested association mapping (NAM) offers power to resolve complex, quantitative traits to their causal loci. The maize NAM population, consisting of 5,000 recombinant inbred lines (RILs) from 25 families representing the global diversity of maize, was evaluated for resistance to southern leaf blight (SLB) disease. Joint-linkage analysis identified 32 quantitative trait loci (QTLs) with predominantly small, additive effects on SLB resistance. Genome-wide association tests of maize HapMap SNPs were conducted by imputing founder SNP genotypes onto the NAM RILs. SNPs both within and outside of QTL intervals were associated with variation for SLB resistance. Many of these SNPs were within or near sequences homologous to genes previously shown to be involved in plant disease resistance. Limited linkage disequilibrium was observed around some SNPs associated with SLB resistance, indicating that the maize NAM population enables high-resolution mapping of some genome regions.

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.

Comprehensive genotyping of the USA national maize inbred seed bank

BackgroundGenotyping by sequencing, a new low-cost, high-throughput sequencing technology was used to genotype 2,815 maize inbred accessions, preserved mostly at the National Plant Germplasm System in the USA. The collection includes inbred lines from breeding programs all over the world.ResultsThe method produced 681,257 single-nucleotide polymorphism (SNP) markers distributed across the entire genome, with the ability to detect rare alleles at high confidence levels. More than half of the SNPs in the collection are rare. Although most rare alleles have been incorporated into public temperate breeding programs, only a modest amount of the available diversity is present in the commercial germplasm. Analysis of genetic distances shows population stratification, including a small number of large clusters centered on key lines. Nevertheless, an average fixation index of 0.06 indicates moderate differentiation between the three major maize subpopulations. Linkage disequilibrium (LD) decays very rapidly, but the extent of LD is highly dependent on the particular group of germplasm and region of the genome. The utility of these data for performing genome-wide association studies was tested with two simply inherited traits and one complex trait. We identified trait associations at SNPs very close to known candidate genes for kernel color, sweet corn, and flowering time; however, results suggest that more SNPs are needed to better explore the genetic architecture of complex traits.ConclusionsThe genotypic information described here allows this publicly available panel to be exploited by researchers facing the challenges of sustainable agriculture through better knowledge of the nature of genetic diversity.

Increased food and ecosystem security via perennial grains

Perennial grains hold promise, especially for marginal landscapes or with limited resources where annual versions struggle. Despite doubling of yields of major grain crops since the 1950s, more than one in seven people suffer from malnutrition (1). Global population is growing; demand for food, especially meat, is increasing; much land most suitable for annual crops is already in use; and production of nonfood goods (e.g., biofuels) increasingly competes with food production for land (2). The best lands have soils at low or moderate risk of degradation under annual grain production but make up only 12.6% of global land area (16.5 million km2) (3). Supporting more than 50% of world population is another 43.7 million km2 of marginal lands (33.5% of global land area), at high risk of degradation under annual grain production but otherwise capable of producing crops (3). Global food security depends on annual grains—cereals, oilseeds, and legumes—planted on almost 70% of croplands, which combined supply a similar portion of human calories (4, 5). Annual grain production, though, often compromises essential ecosystem services, pushing some beyond sustainable boundaries (5). To ensure food and ecosystem security, farmers need more options to produce grains under different, generally less favorable circumstances than those under which increases in food security were achieved this past century. Development of perennial versions of important grain crops could expand options.

Genetic Architecture of Maize Kernel Composition in the Nested Association Mapping and Inbred Association Panels

The maize (Zea mays) kernel plays a critical role in feeding humans and livestock around the world and in a wide array of industrial applications. An understanding of the regulation of kernel starch, protein, and oil is needed in order to manipulate composition to meet future needs. We conducted joint-linkage quantitative trait locus mapping and genome-wide association studies (GWAS) for kernel starch, protein, and oil in the maize nested association mapping population, composed of 25 recombinant inbred line families derived from diverse inbred lines. Joint-linkage mapping revealed that the genetic architecture of kernel composition traits is controlled by 21–26 quantitative trait loci. Numerous GWAS associations were detected, including several oil and starch associations in acyl-CoA:diacylglycerol acyltransferase1-2, a gene that regulates oil composition and quantity. Results from nested association mapping were verified in a 282 inbred association panel using both GWAS and candidate gene association approaches. We identified many beneficial alleles that will be useful for improving kernel starch, protein, and oil content.

ZmCCT and the genetic basis of day-length adaptation underlying the postdomestication spread of maize

Teosinte, the progenitor of maize, is restricted to tropical environments in Mexico and Central America. The pre-Columbian spread of maize from its center of origin in tropical Southern Mexico to the higher latitudes of the Americas required postdomestication selection for adaptation to longer day lengths. Flowering time of teosinte and tropical maize is delayed under long day lengths, whereas temperate maize evolved a reduced sensitivity to photoperiod. We measured flowering time of the maize nested association and diverse association mapping panels in the field under both short and long day lengths, and of a maize-teosinte mapping population under long day lengths. Flowering time in maize is a complex trait affected by many genes and the environment. Photoperiod response is one component of flowering time involving a subset of flowering time genes whose effects are strongly influenced by day length. Genome-wide association and targeted high-resolution linkage mapping identified ZmCCT, a homologue of the rice photoperiod response regulator Ghd7, as the most important gene affecting photoperiod response in maize. Under long day lengths ZmCCT alleles from diverse teosintes are consistently expressed at higher levels and confer later flowering than temperate maize alleles. Many maize inbred lines, including some adapted to tropical regions, carry ZmCCT alleles with no sensitivity to day length. Indigenous farmers of the Americas were remarkably successful at selecting on genetic variation at key genes affecting the photoperiod response to create maize varieties adapted to vastly diverse environments despite the hindrance of the geographic axis of the Americas and the complex genetic control of flowering time.