Publications by authors named "Peter J Bradbury"

35 Publications

Conserved noncoding sequences provide insights into regulatory sequence and loss of gene expression in maize.

Genome Res 2021 May 27. Epub 2021 May 27.

Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853, USA.

Thousands of species will be sequenced in the next few years; however, understanding how their genomes work, without an unlimited budget, requires both molecular and novel evolutionary approaches. We developed a sensitive sequence alignment pipeline to identify conserved noncoding sequences (CNSs) in the Andropogoneae tribe (multiple crop species descended from a common ancestor ∼18 million years ago). The Andropogoneae share similar physiology while being tremendously genomically diverse, harboring a broad range of ploidy levels, structural variation, and transposons. These contribute to the potential of Andropogoneae as a powerful system for studying CNSs and are factors we leverage to understand the function of maize CNSs. We found that 86% of CNSs were comprised of annotated features, including introns, UTRs, putative -regulatory elements, chromatin loop anchors, noncoding RNA (ncRNA) genes, and several transposable element superfamilies. CNSs were enriched in active regions of DNA replication in the early S phase of the mitotic cell cycle and showed different DNA methylation ratios compared to the genome-wide background. More than half of putative -regulatory sequences (identified via other methods) overlapped with CNSs detected in this study. Variants in CNSs were associated with gene expression levels, and CNS absence contributed to loss of gene expression. Furthermore, the evolution of CNSs was associated with the functional diversification of duplicated genes in the context of maize subgenomes. Our results provide a quantitative understanding of the molecular processes governing the evolution of CNSs in maize.
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http://dx.doi.org/10.1101/gr.266528.120DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8256870PMC
May 2021

Eleven biosynthetic genes explain the majority of natural variation in carotenoid levels in maize grain.

Plant Cell 2021 May;33(4):882-900

Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824.

Vitamin A deficiency remains prevalent in parts of Asia, Latin America, and sub-Saharan Africa where maize (Zea mays) is a food staple. Extensive natural variation exists for carotenoids in maize grain. Here, to understand its genetic basis, we conducted a joint linkage and genome-wide association study of the US maize nested association mapping panel. Eleven of the 44 detected quantitative trait loci (QTL) were resolved to individual genes. Six of these were correlated expression and effect QTL (ceeQTL), showing strong correlations between RNA-seq expression abundances and QTL allelic effect estimates across six stages of grain development. These six ceeQTL also had the largest percentage of phenotypic variance explained, and in major part comprised the three to five loci capturing the bulk of genetic variation for each trait. Most of these ceeQTL had strongly correlated QTL allelic effect estimates across multiple traits. These findings provide an in-depth genome-level understanding of the genetic and molecular control of carotenoids in plants. In addition, these findings provide a roadmap to accelerate breeding for provitamin A and other priority carotenoid traits in maize grain that should be readily extendable to other cereals.
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http://dx.doi.org/10.1093/plcell/koab032DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8226291PMC
May 2021

Identification of miRNA-eQTLs in maize mature leaf by GWAS.

BMC Genomics 2020 Oct 6;21(1):689. Epub 2020 Oct 6.

Advanced Plant Biotechnology Center, National Chung Hsing University, No 145 Xingda Rd, South Dist, Taichung, 402, Taiwan.

Background: MiRNAs play essential roles in plant development and response to biotic and abiotic stresses through interaction with their target genes. The expression level of miRNAs shows great variations among different plant accessions, developmental stages, and tissues. Little is known about the content within the plant genome contributing to the variations in plants. This study aims to identify miRNA expression-related quantitative trait loci (miR-QTLs) in the maize genome.

Results: The miRNA expression level from next generation sequencing (NGS) small RNA libraries derived from mature leaf samples of the maize panel (200 maize lines) was estimated as phenotypes, and maize Hapmap v3.2.1 was chosen as the genotype for the genome-wide association study (GWAS). A total of four significant miR-eQTLs were identified contributing to miR156k-5p, miR159a-3p, miR390a-5p and miR396e-5p, and all of them are trans-eQTLs. In addition, a strong positive coexpression of miRNA was found among five miRNA families. Investigation of the effects of these miRNAs on the expression levels and target genes provided evidence that miRNAs control the expression of their targets by suppression and enhancement.

Conclusions: These identified significant miR-eQTLs contribute to the diversity of miRNA expression in the maize penal at the developmental stages of mature leaves in maize, and the positive and negative regulation between miRNA and its target genes has also been uncovered.
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http://dx.doi.org/10.1186/s12864-020-07073-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7541240PMC
October 2020

A sorghum practical haplotype graph facilitates genome-wide imputation and cost-effective genomic prediction.

Plant Genome 2020 03 25;13(1):e20009. Epub 2020 Mar 25.

Institute for Genomic Diversity, Cornell University, Ithaca, NY, 14853, USA.

Successful management and utilization of increasingly large genomic datasets is essential for breeding programs to accelerate cultivar development. To help with this, we developed a Sorghum bicolor Practical Haplotype Graph (PHG) pangenome database that stores haplotypes and variant information. We developed two PHGs in sorghum that were used to identify genome-wide variants for 24 founders of the Chibas sorghum breeding program from 0.01x sequence coverage. The PHG called single nucleotide polymorphisms (SNPs) with 5.9% error at 0.01x coverage-only 3% higher than PHG error when calling SNPs from 8x coverage sequence. Additionally, 207 progenies from the Chibas genomic selection (GS) training population were sequenced and processed through the PHG. Missing genotypes were imputed from PHG parental haplotypes and used for genomic prediction. Mean prediction accuracies with PHG SNP calls range from .57-.73 and are similar to prediction accuracies obtained with genotyping-by-sequencing or targeted amplicon sequencing (rhAmpSeq) markers. This study demonstrates the use of a sorghum PHG to impute SNPs from low-coverage sequence data and shows that the PHG can unify genotype calls across multiple sequencing platforms. By reducing input sequence requirements, the PHG can decrease the cost of genotyping, make GS more feasible, and facilitate larger breeding populations. Our results demonstrate that the PHG is a useful research and breeding tool that maintains variant information from a diverse group of taxa, stores sequence data in a condensed but readily accessible format, unifies genotypes across genotyping platforms, and provides a cost-effective option for genomic selection.
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http://dx.doi.org/10.1002/tpg2.20009DOI Listing
March 2020

Maize Introgression Library Provides Evidence for the Involvement of in Resistance to Northern Leaf Blight.

G3 (Bethesda) 2020 10 5;10(10):3611-3622. Epub 2020 Oct 5.

School of Integrative Plant Science, Plant Pathology and Plant-Microbe Biology Section, Cornell University, Ithaca, NY 14853.

Plant disease resistance is largely governed by complex genetic architecture. In maize, few disease resistance loci have been characterized. Near-isogenic lines are a powerful genetic tool to dissect quantitative trait loci. We analyzed an introgression library of maize () near-isogenic lines, termed a nested near-isogenic line library for resistance to northern leaf blight caused by the fungal pathogen The population was comprised of 412 BCF near-isogenic lines that originated from 18 diverse donor parents and a common recurrent parent, B73. Single nucleotide polymorphisms identified through genotyping by sequencing were used to define introgressions and for association analysis. Near-isogenic lines that conferred resistance and susceptibility to northern leaf blight were comprised of introgressions that overlapped known northern leaf blight quantitative trait loci. Genome-wide association analysis and stepwise regression further resolved five quantitative trait loci regions, and implicated several candidate genes, including , a key determinant of leaf architecture in cereals. Two independently-derived mutant alleles of inoculated with showed enhanced susceptibility to northern leaf blight. In the maize nested association mapping population, leaf angle was positively correlated with resistance to northern leaf blight in five recombinant inbred line populations, and negatively correlated with northern leaf blight in four recombinant inbred line populations. This study demonstrates the power of an introgression library combined with high density marker coverage to resolve quantitative trait loci. Furthermore, the role of in leaf architecture and in resistance to northern leaf blight has important applications in crop improvement.
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http://dx.doi.org/10.1534/g3.120.401500DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7534436PMC
October 2020

The genetic architecture of the maize progenitor, teosinte, and how it was altered during maize domestication.

PLoS Genet 2020 05 14;16(5):e1008791. Epub 2020 May 14.

Laboratory of Genetics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.

The genetics of domestication has been extensively studied ever since the rediscovery of Mendel's law of inheritance and much has been learned about the genetic control of trait differences between crops and their ancestors. Here, we ask how domestication has altered genetic architecture by comparing the genetic architecture of 18 domestication traits in maize and its ancestor teosinte using matched populations. We observed a strongly reduced number of QTL for domestication traits in maize relative to teosinte, which is consistent with the previously reported depletion of additive variance by selection during domestication. We also observed more dominance in maize than teosinte, likely a consequence of selective removal of additive variants. We observed that large effect QTL have low minor allele frequency (MAF) in both maize and teosinte. Regions of the genome that are strongly differentiated between teosinte and maize (high FST) explain less quantitative variation in maize than teosinte, suggesting that, in these regions, allelic variants were brought to (or near) fixation during domestication. We also observed that genomic regions of high recombination explain a disproportionately large proportion of heritable variance both before and after domestication. Finally, we observed that about 75% of the additive variance in both teosinte and maize is "missing" in the sense that it cannot be ascribed to detectable QTL and only 25% of variance maps to specific QTL. This latter result suggests that morphological evolution during domestication is largely attributable to very large numbers of QTL of very small effect.
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http://dx.doi.org/10.1371/journal.pgen.1008791DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7266358PMC
May 2020

Dominance Effects and Functional Enrichments Improve Prediction of Agronomic Traits in Hybrid Maize.

Genetics 2020 05 9;215(1):215-230. Epub 2020 Mar 9.

Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853

Single-cross hybrids have been critical to the improvement of maize ( L.), but the characterization of their genetic architectures remains challenging. Previous studies of hybrid maize have shown the contribution of within-locus complementation effects (dominance) and their differential importance across functional classes of loci. However, they have generally considered panels of limited genetic diversity, and have shown little benefit from genomic prediction based on dominance or functional enrichments. This study investigates the relevance of dominance and functional classes of variants in genomic models for agronomic traits in diverse populations of hybrid maize. We based our analyses on a diverse panel of inbred lines crossed with two testers representative of the major heterotic groups in the U.S. (1106 hybrids), as well as a collection of 24 biparental populations crossed with a single tester (1640 hybrids). We investigated three agronomic traits: days to silking (DTS), plant height (PH), and grain yield (GY). Our results point to the presence of dominance for all traits, but also among-locus complementation (epistasis) for DTS and genotype-by-environment interactions for GY. Consistently, dominance improved genomic prediction for PH only. In addition, we assessed enrichment of genetic effects in classes defined by genic regions (gene annotation), structural features (recombination rate and chromatin openness), and evolutionary features (minor allele frequency and evolutionary constraint). We found support for enrichment in genic regions and subsequent improvement of genomic prediction for all traits. Our results suggest that dominance and gene annotations improve genomic prediction across diverse populations in hybrid maize.
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http://dx.doi.org/10.1534/genetics.120.303025DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7198274PMC
May 2020

The genetic architecture of teosinte catalyzed and constrained maize domestication.

Proc Natl Acad Sci U S A 2019 03 6;116(12):5643-5652. Epub 2019 Mar 6.

Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI 53706;

The process of evolution under domestication has been studied using phylogenetics, population genetics-genomics, quantitative trait locus (QTL) mapping, gene expression assays, and archaeology. Here, we apply an evolutionary quantitative genetic approach to understand the constraints imposed by the genetic architecture of trait variation in teosinte, the wild ancestor of maize, and the consequences of domestication on genetic architecture. Using modern teosinte and maize landrace populations as proxies for the ancestor and domesticate, respectively, we estimated heritabilities, additive and dominance genetic variances, genetic-by-environment variances, genetic correlations, and genetic covariances for 18 domestication-related traits using realized genomic relationships estimated from genome-wide markers. We found a reduction in heritabilities across most traits, and the reduction is stronger in reproductive traits (size and numbers of grains and ears) than vegetative traits. We observed larger depletion in additive genetic variance than dominance genetic variance. Selection intensities during domestication were weak for all traits, with reproductive traits showing the highest values. For 17 of 18 traits, neutral divergence is rejected, suggesting they were targets of selection during domestication. Yield (total grain weight) per plant is the sole trait that selection does not appear to have improved in maize relative to teosinte. From a multivariate evolution perspective, we identified a strong, nonneutral divergence between teosinte and maize landrace genetic variance-covariance matrices (G-matrices). While the structure of G-matrix in teosinte posed considerable genetic constraint on early domestication, the maize landrace G-matrix indicates that the degree of constraint is more unfavorable for further evolution along the same trajectory.
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http://dx.doi.org/10.1073/pnas.1820997116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6431195PMC
March 2019

Expanding the BLUP alphabet for genomic prediction adaptable to the genetic architectures of complex traits.

Heredity (Edinb) 2018 12 16;121(6):648-662. Epub 2018 May 16.

Department of Animal Science and Technology, Northeast Agricultural University, Harbin, China.

Improvement of statistical methods is crucial for realizing the potential of increasingly dense genetic markers. Bayesian methods treat all markers as random effects, exhibit an advantage on dense markers, and offer the flexibility of using different priors. In contrast, genomic best linear unbiased prediction (gBLUP) is superior in computing speed, but only superior in prediction accuracy for extremely complex traits. Currently, the existing variety in the BLUP method is insufficient for adapting to new sequencing technologies and traits with different genetic architectures. In this study, we found two ways to change the kinship derivation in the BLUP method that improve prediction accuracy while maintaining the computational advantage. First, using the settlement under progressively exclusive relationship (SUPER) algorithm, we substituted all available markers with estimated quantitative trait nucleotides (QTNs) to derive kinship. Second, we compressed individuals into groups based on kinship, and then used the groups as random effects instead of individuals. The two methods were named as SUPER BLUP (sBLUP) and compressed BLUP (cBLUP). Analyses on both simulated and real data demonstrated that these two methods offer flexibility for evaluating a variety of traits, covering a broadened realm of genetic architectures. For traits controlled by small numbers of genes, sBLUP outperforms Bayesian LASSO (least absolute shrinkage and selection operator). For traits with low heritability, cBLUP outperforms both gBLUP and Bayesian LASSO methods. We implemented these new BLUP alphabet series methods in an R package, Genome Association and Prediction Integrated Tool (GAPIT), available at http://zzlab.net/GAPIT .
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http://dx.doi.org/10.1038/s41437-018-0075-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6221880PMC
December 2018

Increased experimental conditions and marker densities identified more genetic loci associated with southern and northern leaf blight resistance in maize.

Sci Rep 2018 05 1;8(1):6848. Epub 2018 May 1.

Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.

Southern leaf blight (SLB) and northern leaf blight (NLB) are the two major foliar diseases limiting maize production worldwide. Upon previous study with the nested association mapping (NAM) population, which consist of 5,000 recombinant inbred lines from 25 parents crossed with B73, we expanded the phenotyping environments from the United States (US) to China, and increased the marker densities from 1106 to 7386 SNPs for linkage mapping, and from 1.6 to 28.5 million markers for association mapping. We identified 49 SLB and 48 NLB resistance-related unique QTLs in linkage mapping, and multiple loci in association mapping with candidate genes involved in known plant disease-resistance pathways. Furthermore, an independent natural population with 282 diversified inbred lines were sequenced for four candidate genes selected based on their biological functions. Three of them demonstrated significant associations with disease resistance. These findings provided valuable resources for further implementations to develop varieties with superior resistance for NLB and SLB.
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http://dx.doi.org/10.1038/s41598-018-25304-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5931595PMC
May 2018

Dysregulation of expression correlates with rare-allele burden and fitness loss in maize.

Nature 2018 03 14;555(7697):520-523. Epub 2018 Mar 14.

Section of Plant Breeding and Genetics, 175 Biotechnology Building, Cornell University, Ithaca, New York 14853, USA.

Here we report a multi-tissue gene expression resource that represents the genotypic and phenotypic diversity of modern inbred maize, and includes transcriptomes in an average of 255 lines in seven tissues. We mapped expression quantitative trait loci and characterized the contribution of rare genetic variants to extremes in gene expression. Some of the new mutations that arise in the maize genome can be deleterious; although selection acts to keep deleterious variants rare, their complete removal is impeded by genetic linkage to favourable loci and by finite population size. Modern maize breeders have systematically reduced the effects of this constant mutational pressure through artificial selection and self-fertilization, which have exposed rare recessive variants in elite inbred lines. However, the ongoing effect of these rare alleles on modern inbred maize is unknown. By analysing this gene expression resource and exploiting the extreme diversity and rapid linkage disequilibrium decay of maize, we characterize the effect of rare alleles and evolutionary history on the regulation of expression. Rare alleles are associated with the dysregulation of expression, and we correlate this dysregulation to seed-weight fitness. We find enrichment of ancestral rare variants among expression quantitative trait loci mapped in modern inbred lines, which suggests that historic bottlenecks have shaped regulation. Our results suggest that one path for further genetic improvement in agricultural species lies in purging the rare deleterious variants that have been associated with crop fitness.
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http://dx.doi.org/10.1038/nature25966DOI Listing
March 2018

Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain.

Plant Cell 2017 Oct 2;29(10):2374-2392. Epub 2017 Oct 2.

Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824

Tocopherols, tocotrienols, and plastochromanols (collectively termed tocochromanols) are lipid-soluble antioxidants synthesized by all plants. Their dietary intake, primarily from seed oils, provides vitamin E and other health benefits. Tocochromanol biosynthesis has been dissected in the dicot , which has green, photosynthetic seeds, but our understanding of tocochromanol accumulation in major crops, whose seeds are nonphotosynthetic, remains limited. To understand the genetic control of tocochromanols in grain, we conducted a joint linkage and genome-wide association study in the 5000-line U.S. maize () nested association mapping panel. Fifty-two quantitative trait loci for individual and total tocochromanols were identified, and of the 14 resolved to individual genes, six encode novel activities affecting tocochromanols in plants. These include two chlorophyll biosynthetic enzymes that explain the majority of tocopherol variation, which was not predicted given that, like most major cereal crops, maize grain is nonphotosynthetic. This comprehensive assessment of natural variation in vitamin E levels in maize establishes the foundation for improving tocochromanol and vitamin E content in seeds of maize and other major cereal crops.
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http://dx.doi.org/10.1105/tpc.17.00475DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5774569PMC
October 2017

Maize Genes and Regulate Plant Architecture.

Plant Cell 2017 Jul 11;29(7):1622-1641. Epub 2017 Jul 11.

Department of Genetics, Development and Cell Biology, Iowa State University, Ames, Iowa 50011

Leaf architecture directly influences canopy structure, consequentially affecting yield. We discovered a maize () mutant with aberrant leaf architecture, which we named (). Pleiotropic mutations in affect leaf length and width, leaf angle, and internode length and diameter. These phenotypes are enhanced by natural variation at the enhancer locus, including reduced expression of the allele in the Mo17 inbred. A second allele, produced by transposon mutagenesis, interacted synergistically with mutants and reduced transcript levels. The genes are required for proper leaf patterning, development and cell proliferation of leaf support tissues, and for restricting auricle expansion at the midrib. The paralogous loci encode maize CRABS CLAW co-orthologs in the YABBY family of transcriptional regulators. The genes are coexpressed in incipient and emergent leaf primordia at the shoot apex, but not in the vegetative meristem or stem. Genome-wide association studies using maize NAM-RIL (nested association mapping-recombinant inbred line) populations indicated that the loci reside within quantitative trait locus regions for leaf angle, leaf width, and internode length and identified rare single nucleotide polymorphisms with large phenotypic effects for the latter two traits. This study demonstrates that genes control the development of key agronomic traits in maize.
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http://dx.doi.org/10.1105/tpc.16.00477DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5559738PMC
July 2017

Genetic Architecture of Domestication-Related Traits in Maize.

Genetics 2016 09 13;204(1):99-113. Epub 2016 Jul 13.

U.S. Department of Agriculture-Agricultural Research Service Plant Science Research Unit and Department of Crop Science, North Carolina State University, Raleigh, North Carolina 27695-7620

Strong directional selection occurred during the domestication of maize from its wild ancestor teosinte, reducing its genetic diversity, particularly at genes controlling domestication-related traits. Nevertheless, variability for some domestication-related traits is maintained in maize. The genetic basis of this could be sequence variation at the same key genes controlling maize-teosinte differentiation (due to lack of fixation or arising as new mutations after domestication), distinct loci with large effects, or polygenic background variation. Previous studies permit annotation of maize genome regions associated with the major differences between maize and teosinte or that exhibit population genetic signals of selection during either domestication or postdomestication improvement. Genome-wide association studies and genetic variance partitioning analyses were performed in two diverse maize inbred line panels to compare the phenotypic effects and variances of sequence polymorphisms in regions involved in domestication and improvement to the rest of the genome. Additive polygenic models explained most of the genotypic variation for domestication-related traits; no large-effect loci were detected for any trait. Most trait variance was associated with background genomic regions lacking previous evidence for involvement in domestication. Improvement sweep regions were associated with more trait variation than expected based on the proportion of the genome they represent. Selection during domestication eliminated large-effect genetic variants that would revert maize toward a teosinte type. Small-effect polygenic variants (enriched in the improvement sweep regions of the genome) are responsible for most of the standing variation for domestication-related traits in maize.
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http://dx.doi.org/10.1534/genetics.116.191106DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5012408PMC
September 2016

Identification of genetic variants associated with maize flowering time using an extremely large multi-genetic background population.

Plant J 2016 06 20;86(5):391-402. Epub 2016 Jun 20.

Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 10008, China.

Flowering time is one of the major adaptive traits in domestication of maize and an important selection criterion in breeding. To detect more maize flowering time variants we evaluated flowering time traits using an extremely large multi- genetic background population that contained more than 8000 lines under multiple Sino-United States environments. The population included two nested association mapping (NAM) panels and a natural association panel. Nearly 1 million single-nucleotide polymorphisms (SNPs) were used in the analyses. Through the parallel linkage analysis of the two NAM panels, both common and unique flowering time regions were detected. Genome wide, a total of 90 flowering time regions were identified. One-third of these regions were connected to traits associated with the environmental sensitivity of maize flowering time. The genome-wide association study of the three panels identified nearly 1000 flowering time-associated SNPs, mainly distributed around 220 candidate genes (within a distance of 1 Mb). Interestingly, two types of regions were significantly enriched for these associated SNPs - one was the candidate gene regions and the other was the approximately 5 kb regions away from the candidate genes. Moreover, the associated SNPs exhibited high accuracy for predicting flowering time.
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http://dx.doi.org/10.1111/tpj.13174DOI Listing
June 2016

Construction of high-quality recombination maps with low-coverage genomic sequencing for joint linkage analysis in maize.

BMC Biol 2015 Sep 21;13:78. Epub 2015 Sep 21.

Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.

Background: A genome-wide association study (GWAS) is the foremost strategy used for finding genes that control human diseases and agriculturally important traits, but it often reports false positives. In contrast, its complementary method, linkage analysis, provides direct genetic confirmation, but with limited resolution. A joint approach, using multiple linkage populations, dramatically improves resolution and statistical power. For example, this approach has been used to confirm that many complex traits, such as flowering time controlling adaptation in maize, are controlled by multiple genes with small effects. In addition, genotyping by sequencing (GBS) at low coverage not only produces genotyping errors, but also results in large datasets, making the use of high-throughput sequencing technologies computationally inefficient or unfeasible.

Results: In this study, we converted raw SNPs into effective recombination bins. The reduced bins not only retain the original information, but also correct sequencing errors from low-coverage genomic sequencing. To further increase the statistical power and resolution, we merged a new temperate maize nested association mapping (NAM) population derived in China (CN-NAM) with the existing maize NAM population developed in the US (US-NAM). Together, the two populations contain 36 families and 7,000 recombinant inbred lines (RILs). One million SNPs were generated for all the RILs with GBS at low coverage. We developed high-quality recombination maps for each NAM population to correct genotyping errors and improve the computational efficiency of the joint linkage analysis. The original one million SNPs were reduced to 4,932 and 5,296 recombination bins with average interval distances of 0.34 cM and 0.28 cM for CN-NAM and US-NAM, respectively. The quantitative trait locus (QTL) mapping for flowering time (days to tasseling) indicated that the high-density, recombination bin map improved resolution of QTL mapping by 50 % compared with that using a medium-density map. We also demonstrated that combining the CN-NAM and US-NAM populations improves the power to detect QTL by 50 % compared to single NAM population mapping. Among the QTLs mapped by joint usage of the US-NAM and CN-NAM maps, 25 % of the QTLs overlapped with known flowering-time genes in maize.

Conclusion: This study provides directions and resources for the research community, especially maize researchers, for future studies using the recombination bin strategy for joint linkage analysis. Available resources include efficient usage of low-coverage genomic sequencing, detailed positions for genes controlling maize flowering, and recombination bin maps and flowering- time data for both CN and US NAMs. Maize researchers even have the opportunity to grow both CN and US NAM populations to study the traits of their interest, as the seeds of both NAM populations are available from the seed repository in China and the US.
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http://dx.doi.org/10.1186/s12915-015-0187-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4578237PMC
September 2015

Genome-wide association of carbon and nitrogen metabolism in the maize nested association mapping population.

Plant Physiol 2015 Jun 27;168(2):575-83. Epub 2015 Apr 27.

Institute for Genomic Diversity (N.Z., J.G.W., K.K., E.S.B.), Boyce Thompson Institute for Plant Research (P.L., L.D., T.B.), Department of Plant Breeding and Genetics (C.C., K.K., E.S.B.), and Department of Plant Biology (T.B.), Cornell University, Ithaca, New York 14853;Max Planck Institute of Molecular Plant Physiology, 14476 Golm-Potsdam, Germany (Y.G., M.S.);United States Department of Agriculture-Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (N.L., P.J.B., E.S.B.); andDepartment of Crop Science, North Carolina State University, Raleigh, North Carolina 27695 (Y.-S.S.)

Carbon (C) and nitrogen (N) metabolism are critical to plant growth and development and are at the basis of crop yield and adaptation. We performed high-throughput metabolite analyses on over 12,000 samples from the nested association mapping population to identify genetic variation in C and N metabolism in maize (Zea mays ssp. mays). All samples were grown in the same field and used to identify natural variation controlling the levels of 12 key C and N metabolites, namely chlorophyll a, chlorophyll b, fructose, fumarate, glucose, glutamate, malate, nitrate, starch, sucrose, total amino acids, and total protein, along with the first two principal components derived from them. Our genome-wide association results frequently identified hits with single-gene resolution. In addition to expected genes such as invertases, natural variation was identified in key C4 metabolism genes, including carbonic anhydrases and a malate transporter. Unlike several prior maize studies, extensive pleiotropy was found for C and N metabolites. This integration of field-derived metabolite data with powerful mapping and genomics resources allows for the dissection of key metabolic pathways, providing avenues for future genetic improvement.
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http://dx.doi.org/10.1104/pp.15.00025DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4453775PMC
June 2015

High-resolution genetic mapping of maize pan-genome sequence anchors.

Nat Commun 2015 Apr 16;6:6914. Epub 2015 Apr 16.

1] Institute for Genomic Diversity, Cornell University, Ithaca, New York 14850, USA [2] United States Department of Agriculture/Agricultural Research Service, Ithaca, New York 14850, USA.

In addition to single-nucleotide polymorphisms, structural variation is abundant in many plant genomes. The structural variation across a species can be represented by a 'pan-genome', which is essential to fully understand the genetic control of phenotypes. However, the pan-genome's complexity hinders its accurate assembly via sequence alignment. Here we demonstrate an approach to facilitate pan-genome construction in maize. By performing 18 trillion association tests we map 26 million tags generated by reduced representation sequencing of 14,129 maize inbred lines. Using machine-learning models we select 4.4 million accurately mapped tags as sequence anchors, 1.1 million of which are presence/absence variations. Structural variations exhibit enriched association with phenotypic traits, indicating that it is a significant source of adaptive variation in maize. The ability to efficiently map ultrahigh-density pan-genome sequence anchors enables fine characterization of structural variation and will advance both genetic research and breeding in many crops.
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http://dx.doi.org/10.1038/ncomms7914DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4411285PMC
April 2015

From association to prediction: statistical methods for the dissection and selection of complex traits in plants.

Curr Opin Plant Biol 2015 Apr 17;24:110-8. Epub 2015 Mar 17.

Cornell University, Plant Breeding and Genetics Section, School of Integrative Plant Science, Ithaca, NY 14853, USA.

Quantification of genotype-to-phenotype associations is central to many scientific investigations, yet the ability to obtain consistent results may be thwarted without appropriate statistical analyses. Models for association can consider confounding effects in the materials and complex genetic interactions. Selecting optimal models enables accurate evaluation of associations between marker loci and numerous phenotypes including gene expression. Significant improvements in QTL discovery via association mapping and acceleration of breeding cycles through genomic selection are two successful applications of models using genome-wide markers. Given recent advances in genotyping and phenotyping technologies, further refinement of these approaches is needed to model genetic architecture more accurately and run analyses in a computationally efficient manner, all while accounting for false positives and maximizing statistical power.
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http://dx.doi.org/10.1016/j.pbi.2015.02.010DOI Listing
April 2015

Recombination in diverse maize is stable, predictable, and associated with genetic load.

Proc Natl Acad Sci U S A 2015 Mar 9;112(12):3823-8. Epub 2015 Mar 9.

Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853; US Department of Agriculture-Agricultural Research Service, Ithaca, NY 14853; and.

Among the fundamental evolutionary forces, recombination arguably has the largest impact on the practical work of plant breeders. Varying over 1,000-fold across the maize genome, the local meiotic recombination rate limits the resolving power of quantitative trait mapping and the precision of favorable allele introgression. The consequences of low recombination also theoretically extend to the species-wide scale by decreasing the power of selection relative to genetic drift, and thereby hindering the purging of deleterious mutations. In this study, we used genotyping-by-sequencing (GBS) to identify 136,000 recombination breakpoints at high resolution within US and Chinese maize nested association mapping populations. We find that the pattern of cross-overs is highly predictable on the broad scale, following the distribution of gene density and CpG methylation. Several large inversions also suppress recombination in distinct regions of several families. We also identify recombination hotspots ranging in size from 1 kb to 30 kb. We find these hotspots to be historically stable and, compared with similar regions with low recombination, to have strongly differentiated patterns of DNA methylation and GC content. We also provide evidence for the historical action of GC-biased gene conversion in recombination hotspots. Finally, using genomic evolutionary rate profiling (GERP) to identify putative deleterious polymorphisms, we find evidence for reduced genetic load in hotspot regions, a phenomenon that may have considerable practical importance for breeding programs worldwide.
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http://dx.doi.org/10.1073/pnas.1413864112DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4378432PMC
March 2015

Association mapping across numerous traits reveals patterns of functional variation in maize.

PLoS Genet 2014 Dec 4;10(12):e1004845. Epub 2014 Dec 4.

Institute for Genomic Diversity, Cornell University, Ithaca, New York, United States of America; United States Department of Agriculture-Agricultural Research Service, Ithaca, New York, United States of America; Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, United States of America.

Phenotypic variation in natural populations results from a combination of genetic effects, environmental effects, and gene-by-environment interactions. Despite the vast amount of genomic data becoming available, many pressing questions remain about the nature of genetic mutations that underlie functional variation. We present the results of combining genome-wide association analysis of 41 different phenotypes in ∼ 5,000 inbred maize lines to analyze patterns of high-resolution genetic association among of 28.9 million single-nucleotide polymorphisms (SNPs) and ∼ 800,000 copy-number variants (CNVs). We show that genic and intergenic regions have opposite patterns of enrichment, minor allele frequencies, and effect sizes, implying tradeoffs among the probability that a given polymorphism will have an effect, the detectable size of that effect, and its frequency in the population. We also find that genes tagged by GWAS are enriched for regulatory functions and are ∼ 50% more likely to have a paralog than expected by chance, indicating that gene regulation and gene duplication are strong drivers of phenotypic variation. These results will likely apply to many other organisms, especially ones with large and complex genomes like maize.
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http://dx.doi.org/10.1371/journal.pgen.1004845DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4256217PMC
December 2014

The genetic architecture of maize height.

Genetics 2014 Apr 10;196(4):1337-56. Epub 2014 Feb 10.

Department of Genetics, Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina 27695.

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.
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http://dx.doi.org/10.1534/genetics.113.159152DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3982682PMC
April 2014

Aluminum tolerance in maize is associated with higher MATE1 gene copy number.

Proc Natl Acad Sci U S A 2013 Mar 11;110(13):5241-6. Epub 2013 Mar 11.

Robert W. Holley Center for Agriculture and Health, US Department of Agriculture-Agricultural Research Service, Cornell University, Ithaca, NY 14853, USA.

Genome structure variation, including copy number variation and presence/absence variation, comprises a large extent of maize genetic diversity; however, its effect on phenotypes remains largely unexplored. Here, we describe how copy number variation underlies a rare allele that contributes to maize aluminum (Al) tolerance. Al toxicity is the primary limitation for crop production on acid soils, which make up 50% of the world's potentially arable lands. In a recombinant inbred line mapping population, copy number variation of the Al tolerance gene multidrug and toxic compound extrusion 1 (MATE1) is the basis for the quantitative trait locus of largest effect on phenotypic variation. This expansion in MATE1 copy number is associated with higher MATE1 expression, which in turn results in superior Al tolerance. The three MATE1 copies are identical and are part of a tandem triplication. Only three maize inbred lines carrying the three-copy allele were identified from maize and teosinte diversity panels, indicating that copy number variation for MATE1 is a rare, and quite likely recent, event. These maize lines with higher MATE1 copy number are also Al-tolerant, have high MATE1 expression, and originate from regions of highly acidic soils. Our findings show a role for copy number variation in the adaptation of maize to acidic soils in the tropics and suggest that genome structural changes may be a rapid evolutionary response to new environments.
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http://dx.doi.org/10.1073/pnas.1220766110DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3612656PMC
March 2013

GAPIT: genome association and prediction integrated tool.

Bioinformatics 2012 Sep 13;28(18):2397-9. Epub 2012 Jul 13.

Computational Biologist with the United States Department of Agriculture - Agricultural Research Service, Ithaca, NY 14853, USA.

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: [email protected]

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/bts444DOI Listing
September 2012

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

Proc Natl Acad Sci U S A 2012 Jul 18;109(28):E1913-21. Epub 2012 Jun 18.

Department of Crop Science, North Carolina State University, Raleigh, NC 27695, USA.

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.
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http://dx.doi.org/10.1073/pnas.1203189109DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3396540PMC
July 2012

Maize HapMap2 identifies extant variation from a genome in flux.

Nat Genet 2012 Jun 3;44(7):803-7. Epub 2012 Jun 3.

Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA.

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.
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http://dx.doi.org/10.1038/ng.2313DOI Listing
June 2012

Distinct genetic architectures for male and female inflorescence traits of maize.

PLoS Genet 2011 Nov 17;7(11):e1002383. Epub 2011 Nov 17.

Institute for Genomic Diversity, Cornell University, Ithaca, New York, USA.

We compared the genetic architecture of thirteen maize morphological traits in a large population of recombinant inbred lines. Four traits from the male inflorescence (tassel) and three traits from the female inflorescence (ear) were measured and studied using linkage and genome-wide association analyses and compared to three flowering and three leaf traits previously studied in the same population. Inflorescence loci have larger effects than flowering and leaf loci, and ear effects are larger than tassel effects. Ear trait models also have lower predictive ability than tassel, flowering, or leaf trait models. Pleiotropic loci were identified that control elongation of ear and tassel, consistent with their common developmental origin. For these pleiotropic loci, the ear effects are larger than tassel effects even though the same causal polymorphisms are likely involved. This implies that the observed differences in genetic architecture are not due to distinct features of the underlying polymorphisms. Our results support the hypothesis that genetic architecture is a function of trait stability over evolutionary time, since the traits that changed most during the relatively recent domestication of maize have the largest effects.
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http://dx.doi.org/10.1371/journal.pgen.1002383DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3219606PMC
November 2011

Genome-wide nested association mapping of quantitative resistance to northern leaf blight in maize.

Proc Natl Acad Sci U S A 2011 Apr 11;108(17):6893-8. Epub 2011 Apr 11.

Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853, USA.

Quantitative resistance to plant pathogens, controlled by multiple loci of small effect, is important for food production, food security, and food safety but is poorly understood. To gain insights into the genetic architecture of quantitative resistance in maize, we evaluated a 5,000-inbred-line nested association mapping population for resistance to northern leaf blight, a maize disease of global economic importance. Twenty-nine quantitative trait loci were identified, and most had multiple alleles. The large variation in resistance phenotypes could be attributed to the accumulation of numerous loci of small additive effects. Genome-wide nested association mapping, using 1.6 million SNPs, identified multiple candidate genes related to plant defense, including receptor-like kinase genes similar to those involved in basal defense. These results are consistent with the hypothesis that quantitative disease resistance in plants is conditioned by a range of mechanisms and could have considerable mechanistic overlap with basal resistance.
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http://dx.doi.org/10.1073/pnas.1010894108DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3084105PMC
April 2011

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

Nat Genet 2011 Feb 9;43(2):163-8. Epub 2011 Jan 9.

Department of Crop Science, North Carolina State University, Raleigh, North Carolina, USA.

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.
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http://dx.doi.org/10.1038/ng.747DOI Listing
February 2011

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

Nat Genet 2011 Feb 9;43(2):159-62. Epub 2011 Jan 9.

Institute for Genomic Diversity, Cornell University, Ithaca, New York, USA.

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.
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http://dx.doi.org/10.1038/ng.746DOI Listing
February 2011
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