Mark H. Wright

Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa

Asian rice, Oryza sativa is a cultivated, inbreeding species that feeds over half of the worlds population. Understanding the genetic basis of diverse physiological, developmental, and morphological traits provides the basis for improving yield, quality and sustainability of rice. Here we show the results of a genome-wide association study based on genotyping 44,100 SNP variants across 413 diverse accessions of O. sativa collected from 82 countries that were systematically phenotyped for 34 traits. Using cross-population-based mapping strategies, we identified dozens of common variants influencing numerous complex traits. Significant heterogeneity was observed in the genetic architecture associated with subpopulation structure and response to environment. This work establishes an open-source translational research platform for genome-wide association studies in rice that directly links molecular variation in genes and metabolic pathways with the germplasm resources needed to accelerate varietal development and crop improvement.

Genetic Architecture of Aluminum Tolerance in Rice (Oryza sativa) Determined through Genome-Wide Association Analysis and QTL Mapping

Aluminum (Al) toxicity is a primary limitation to crop productivity on acid soils, and rice has been demonstrated to be significantly more Al tolerant than other cereal crops. However, the mechanisms of rice Al tolerance are largely unknown, and no genes underlying natural variation have been reported. We screened 383 diverse rice accessions, conducted a genome-wide association (GWA) study, and conducted QTL mapping in two bi-parental populations using three estimates of Al tolerance based on root growth. Subpopulation structure explained 57% of the phenotypic variation, and the mean Al tolerance in Japonica was twice that of Indica. Forty-eight regions associated with Al tolerance were identified by GWA analysis, most of which were subpopulation-specific. Four of these regions co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified QTLs. Three regions corresponding to induced Al-sensitive rice mutants (ART1, STAR2, Nrat1) were identified through bi-parental QTL mapping or GWA to be involved in natural variation for Al tolerance. Haplotype analysis around the Nrat1 gene identified susceptible and tolerant haplotypes explaining 40% of the Al tolerance variation within the aus subpopulation, and sequence analysis of Nrat1 identified a trio of non-synonymous mutations predictive of Al sensitivity in our diversity panel. GWA analysis discovered more phenotype–genotype associations and provided higher resolution, but QTL mapping identified critical rare and/or subpopulation-specific alleles not detected by GWA analysis. Mapping using Indica/Japonica populations identified QTLs associated with transgressive variation where alleles from a susceptible aus or indica parent enhanced Al tolerance in a tolerant Japonica background. This work supports the hypothesis that selectively introgressing alleles across subpopulations is an efficient approach for trait enhancement in plant breeding programs and demonstrates the fundamental importance of subpopulation in interpreting and manipulating the genetics of complex traits in rice.

Global distribution of genomic diversity underscores rich complex history of continental human populations

Characterizing patterns of genetic variation within and among human populations is important for understanding human evolutionary history and for careful design of medical genetic studies. Here, we analyze patterns of variation across 443,434 single nucleotide polymorphisms (SNPs) genotyped in 3845 individuals from four continental regions. This unique resource allows us to illuminate patterns of diversity in previously under-studied populations at the genome-wide scale including Latin America, South Asia, and Southern Europe. Key insights afforded by our analysis include quantifying the degree of admixture in a large collection of individuals from Guadalajara, Mexico; identifying language and geography as key determinants of population structure within India; and elucidating a north-south gradient in haplotype diversity within Europe. We also present a novel method for identifying long-range tracts of homozygosity indicative of recent common ancestry. Application of our approach suggests great variation within and among populations in the extent of homozygosity, suggesting both demographic history (such as population bottlenecks) and recent ancestry events (such as consanguinity) play an important role in patterning variation in large modern human populations.

High-throughput genotyping and mapping of single nucleotide polymorphisms in loblolly pine (Pinus taeda L.)

The development and application of genomic tools to loblolly pine (Pinus taeda L.) offer promising insights into the organization and structure of conifer genomes. The application of a high-throughput genotyping assay across diverse forest tree species, however, is currently limited taxonomically. This is despite the ongoing development of genome-scale projects aiming at the construction of expressed sequence tag (EST) libraries and the resequencing of EST-derived unigenes for a diverse array of forest tree species. In this paper, we report on the application of Illumina’s high-throughput GoldenGate™ SNP genotyping assay to a loblolly pine mapping population. Single nucleotide polymorphisms (SNPs) were identified through resequencing of previously identified wood quality, drought tolerance, and disease resistance candidate genes prior to genotyping. From that effort, a 384 multiplexed SNP assay was developed for high-throughput genotyping. Approximately 67% of the 384 SNPs queried converted into high-quality genotypes for the 48 progeny samples. Of those 257 successfully genotyped SNPs, 70 were segregating within the mapping population. A total of 27 candidate genes were subsequently mapped onto the existing loblolly pine consensus map, which consists of 12 linkage groups spanning a total map distance of 1,227.6xa0cM. The ability of SNPs to be mapped to the same position as fragment-based markers previously developed within the same candidate genes, as well as the pivotal role that SNPs currently play in the dissection of complex phenotypic traits, illustrate the usefulness of high-throughput SNP genotyping technologies to the continued development of pine genomics.

Whole genome de novo assemblies of three divergent strains of rice, Oryza sativa, document novel gene space of aus and indica

BackgroundThe use of high throughput genome-sequencing technologies has uncovered a large extent of structural variation in eukaryotic genomes that makes important contributions to genomic diversity and phenotypic variation. When the genomes of different strains of a given organism are compared, whole genome resequencing data are typically aligned to an established reference sequence. However, when the reference differs in significant structural ways from the individuals under study, the analysis is often incomplete or inaccurate.ResultsHere, we use rice as a model to demonstrate how improvements in sequencing and assembly technology allow rapid and inexpensive de novo assembly of next generation sequence data into high-quality assemblies that can be directly compared using whole genome alignment to provide an unbiased assessment. Using this approach, we are able to accurately assess the ‘pan-genome’ of three divergent rice varieties and document several megabases of each genome absent in the other two.ConclusionsMany of the genome-specific loci are annotated to contain genes, reflecting the potential for new biological properties that would be missed by standard reference-mapping approaches. We further provide a detailed analysis of several loci associated with agriculturally important traits, including the S5 hybrid sterility locus, the Sub1 submergence tolerance locus, the LRK gene cluster associated with improved yield, and the Pup1 cluster associated with phosphorus deficiency, illustrating the utility of our approach for biological discovery. All of the data and software are openly available to support further breeding and functional studies of rice and other species.

Natural variation of rice strigolactone biosynthesis is associated with the deletion of two MAX1 orthologs

Significance Strigolactones are a new class of plant hormones regulating plant shoot and root architecture in response to the environment. Also present in root exudates, strigolactones stimulate the germination of parasitic plant seeds. This report describes a genomic polymorphism—associated with the Indica/Japonica subspecies divide in rice that has a major impact on the biosynthesis of strigolactones, plant tillering, and germination of the parasitic plant Striga hermonthica—consisting of the deletion of two strigolactone biosynthetic genes orthologous to Arabidopsis MAX1. Both of these genes rescued the Arabidopsis max1-1 highly branched mutant phenotype and increased the strigolactone level when overexpressed in the Indica rice variety Bala. This finding is of great interest for plant physiologists, plant evolutionary biologists, and breeders. Rice (Oryza sativa) cultivar Azucena—belonging to the Japonica subspecies—exudes high strigolactone (SL) levels and induces high germination of the root parasitic plant Striga hermonthica. Consistent with the fact that SLs also inhibit shoot branching, Azucena is a low-tillering variety. In contrast, Bala, an Indica cultivar, is a low-SL producer, stimulates less Striga germination, and is highly tillered. Using a Bala × Azucena F6 population, a major quantitative trait loci—qSLB1.1—for the exudation of SL, tillering, and induction of Striga germination was detected on chromosome 1. Sequence analysis of the corresponding locus revealed a rearrangement of a 51- to 59-kbp stretch between 28.9 and 29 Mbp in the Bala genome, resulting in the deletion of two cytochrome P450 genes—SLB1 and SLB2—with high homology to the Arabidopsis SL biosynthesis gene, MAX1. Both rice genes rescue the Arabidopsis max1-1 highly branched mutant phenotype and increase the production of the SL, ent-2′-epi-5-deoxystrigol, when overexpressed in Bala. Furthermore, analysis of this region in 367 cultivars of the publicly available Rice Diversity Panel population shows that the rearrangement at this locus is a recurrent natural trait associated with the Indica/Japonica divide in rice.

Development of a research platform for dissecting phenotype-genotype associations in rice (Oryza spp.).

We present an overview of a research platform that provides essential germplasm, genotypic and phenotypic data and analytical tools for dissecting phenotype–genotype associations in rice. These resources include a diversity panel of 400 Oryza sativa and 100 Oryza rufipogon accessions that have been purified by single seed descent, a custom-designed Affymetrix array consisting of 44,100 SNPs, an Illumina GoldenGate assay consisting of 1,536 SNPs, and a suite of low-resolution 384-SNP assays for the Illumina BeadXpress Reader that are designed for applications in breeding, genetics and germplasm management. Our long-term goal is to empower basic research discoveries in rice by linking sequence diversity with physiological, morphological, and agronomic variation. This research platform will also help increase breeding efficiency by providing a database of diversity information that will enable researchers to identify useful DNA polymorphisms in genes and germplasm of interest and convert that information into cost-effective tools for applied plant improvement.

Large-Scale Discovery of Gene-Enriched SNPs

Whole‐genome association studies of complex traits in higher eukaryotes require a high density of single nucleotide polymorphism (SNP) markers at genome‐wide coverage. To design high‐throughput, multiplexed SNP genotyping assays, researchers must first discover large numbers of SNPs by extensively resequencing multiple individuals or lines. For SNP discovery approaches using short read‐lengths that next‐generation DNA sequencing technologies offer, the highly repetitive and duplicated nature of large plant genomes presents additional challenges. Here, we describe a genomic library construction procedure that facilitates pyrosequencing of genic and low‐copy regions in plant genomes, and a customized computational pipeline to analyze and assemble short reads (100–200 bp), identify allelic reference sequence comparisons, and call SNPs with a high degree of accuracy. With maize (Zea mays L.) as the test organism in a pilot experiment, the implementation of these methods resulted in the identification of 126,683 putative SNPs between two maize inbred lines at an estimated false discovery rate (FDR) of 15.1%. We estimated rates of false SNP discovery using an internal control, and we validated these FDR rates with an external SNP dataset that was generated using locus‐specific PCR amplification and Sanger sequencing. These results show that this approach has wide applicability for efficiently and accurately detecting gene‐enriched SNPs in large, complex plant genomes.

ALCHEMY: a reliable method for automated SNP genotype calling for small batch sizes and highly homozygous populations

Motivation: The development of new high-throughput genotyping products requires a significant investment in testing and training samples to evaluate and optimize the product before it can be used reliably on new samples. One reason for this is current methods for automated calling of genotypes are based on clustering approaches which require a large number of samples to be analyzed simultaneously, or an extensive training dataset to seed clusters. In systems where inbred samples are of primary interest, current clustering approaches perform poorly due to the inability to clearly identify a heterozygote cluster. Results: As part of the development of two custom single nucleotide polymorphism genotyping products for Oryza sativa (domestic rice), we have developed a new genotype calling algorithm called ‘ALCHEMY’ based on statistical modeling of the raw intensity data rather than modelless clustering. A novel feature of the model is the ability to estimate and incorporate inbreeding information on a per sample basis allowing accurate genotyping of both inbred and heterozygous samples even when analyzed simultaneously. Since clustering is not used explicitly, ALCHEMY performs well on small sample sizes with accuracy exceeding 99% with as few as 18 samples. Availability: ALCHEMY is available for both commercial and academic use free of charge and distributed under the GNU General Public License at http://alchemy.sourceforge.net/ Contact: mhw6@cornell.edu Supplementary information: Supplementary data are available at Bioinformatics online.

SNP Discovery with EST and NextGen Sequencing in Switchgrass (Panicum virgatum L.)

Although yield trials for switchgrass (Panicum virgatum L.), a potentially high value biofuel feedstock crop, are currently underway throughout North America, the genetic tools for crop improvement in this species are still in the early stages of development. Identification of high-density molecular markers, such as single nucleotide polymorphisms (SNPs), that are amenable to high-throughput genotyping approaches, is the first step in a quantitative genetics study of this model biofuel crop species. We generated and sequenced expressed sequence tag (EST) libraries from thirteen diverse switchgrass cultivars representing both upland and lowland ecotypes, as well as tetraploid and octoploid genomes. We followed this with reduced genomic library preparation and massively parallel sequencing of the same samples using the Illumina Genome Analyzer technology platform. EST libraries were used to generate unigene clusters and establish a gene-space reference sequence, thus providing a framework for assembly of the short sequence reads. SNPs were identified utilizing these scaffolds. We used a custom software program for alignment and SNP detection and identified over 149,000 SNPs across the 13 short-read sequencing libraries (SRSLs). Approximately 25,000 additional SNPs were identified from the entire EST collection available for the species. This sequencing effort generated data that are suitable for marker development and for estimation of population genetic parameters, such as nucleotide diversity and linkage disequilibrium. Based on these data, we assessed the feasibility of genome wide association mapping and genomic selection applications in switchgrass. Overall, the SNP markers discovered in this study will help facilitate quantitative genetics experiments and greatly enhance breeding efforts that target improvement of key biofuel traits and development of new switchgrass cultivars.