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Phillips AR, Seetharam AS, Albert PS, AuBuchon-Elder T, Birchler JA, Buckler ES, Gillespie LJ, Hufford MB, Llaca V, Romay MC, Soreng RJ, Kellogg EA, Ross-Ibarra J. A happy accident: a novel turfgrass reference genome. G3 Genes|Genomes|Genetics 2023:7099442. [DOI: 10.1093/g3journal/jkad073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 08/03/2022] [Accepted: 03/30/2023] [Indexed: 04/04/2023]
Abstract
Abstract
Poa pratensis, commonly known as Kentucky bluegrass, is a popular cool-season grass species used as turf in lawns and recreation areas globally. Despite its substantial economic value, a reference genome had not previously been assembled due to the genome’s relatively large size and biological complexity that includes apomixis, polyploidy, and interspecific hybridization. We report here a fortuitous de novo assembly and annotation of a P. pratensis genome. Instead of sequencing the genome of a C4 grass, we accidentally sampled and sequenced tissue from a weedy P. pratensis whose stolon was intertwined with that of the C4 grass. The draft assembly consists of 6.09 Gbp with an N50 scaffold length of 65.1 Mbp, and a total of 118 scaffolds, generated using PacBio long reads and Bionano optical map technology. We annotated 256 K gene models and found 58% of the genome to be composed of transposable elements. To demonstrate the applicability of the reference genome, we evaluated population structure and estimated genetic diversity in P. pratensis collected from three North American prairies, two in Manitoba, Canada and one in Colorado, USA. Our results support previous studies that found high genetic diversity and population structure within the species. The reference genome and annotation will be an important resource for turfgrass breeding and study of bluegrasses.
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Affiliation(s)
- Alyssa R Phillips
- Department of Evolution and Ecology and Center for Population Biology, University of California , Davis, Davis, CA 95616 , USA
| | - Arun S Seetharam
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University , Ames, IA 50011 , USA
| | - Patrice S Albert
- Division of Biological Sciences, University of Missouri , Columbia, MO 65201 , USA
| | | | - James A Birchler
- Division of Biological Sciences, University of Missouri , Columbia, MO 65201 , USA
| | - Edward S Buckler
- School of Integrative Plant Sciences, Section of Plant Breeding and Genetics, Cornell University , Ithaca, NY 14850 , USA
- Institute for Genomic Diversity, Cornell University , Ithaca, NY 14850 , USA
- Agricultural Research Service, United States Department of Agriculture , Ithaca, NY 14850 , USA
| | - Lynn J Gillespie
- Botany Section, Research and Collections, Canadian Museum of Nature , Ottawa, ON K2P 2R1 , Canada
| | - Matthew B Hufford
- Division of Biological Sciences, University of Missouri , Columbia, MO 65201 , USA
| | | | - M Cinta Romay
- Institute for Genomic Diversity, Cornell University , Ithaca, NY 14850 , USA
| | - Robert J Soreng
- Deptartment of Botany, Smithsonian Institution , Washington, DC 20560 , USA
| | | | - Jeffrey Ross-Ibarra
- Department of Evolution and Ecology and Center for Population Biology, University of California , Davis, Davis, CA 95616 , USA
- Genome Center, University of California , Davis, Davis, CA 95616 , USA
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2
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Khaipho-Burch M, Ferebee T, Giri A, Ramstein G, Monier B, Yi E, Romay MC, Buckler ES. Elucidating the patterns of pleiotropy and its biological relevance in maize. PLoS Genet 2023; 19:e1010664. [PMID: 36943844 PMCID: PMC10030035 DOI: 10.1371/journal.pgen.1010664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 02/09/2023] [Indexed: 03/23/2023] Open
Abstract
Pleiotropy-when a single gene controls two or more seemingly unrelated traits-has been shown to impact genes with effects on flowering time, leaf architecture, and inflorescence morphology in maize. However, the genome-wide impact of biological pleiotropy across all maize phenotypes is largely unknown. Here, we investigate the extent to which biological pleiotropy impacts phenotypes within maize using GWAS summary statistics reanalyzed from previously published metabolite, field, and expression phenotypes across the Nested Association Mapping population and Goodman Association Panel. Through phenotypic saturation of 120,597 traits, we obtain over 480 million significant quantitative trait nucleotides. We estimate that only 1.56-32.3% of intervals show some degree of pleiotropy. We then assess the relationship between pleiotropy and various biological features such as gene expression, chromatin accessibility, sequence conservation, and enrichment for gene ontology terms. We find very little relationship between pleiotropy and these variables when compared to permuted pleiotropy. We hypothesize that biological pleiotropy of common alleles is not widespread in maize and is highly impacted by nuisance terms such as population structure and linkage disequilibrium. Natural selection on large standing natural variation in maize populations may target wide and large effect variants, leaving the prevalence of detectable pleiotropy relatively low.
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Affiliation(s)
| | - Taylor Ferebee
- Department of Computational Biology, Cornell University, Ithaca, New York
| | - Anju Giri
- Institute for Genomic Diversity, Cornell University, Ithaca, New York
| | - Guillaume Ramstein
- Institute for Genomic Diversity, Cornell University, Ithaca, New York
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Brandon Monier
- Institute for Genomic Diversity, Cornell University, Ithaca, New York
| | - Emily Yi
- Institute for Genomic Diversity, Cornell University, Ithaca, New York
| | - M Cinta Romay
- Institute for Genomic Diversity, Cornell University, Ithaca, New York
| | - Edward S Buckler
- Section of Plant Breeding and Genetics, Cornell University, Ithaca, New York
- Institute for Genomic Diversity, Cornell University, Ithaca, New York
- USDA-ARS, Ithaca, New York, United States of America
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3
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Bradbury PJ, Casstevens T, Jensen SE, Johnson LC, Miller ZR, Monier B, Romay MC, Song B, Buckler ES. The Practical Haplotype Graph, a platform for storing and using pangenomes for imputation. Bioinformatics 2022; 38:3698-3702. [PMID: 35748708 PMCID: PMC9344836 DOI: 10.1093/bioinformatics/btac410] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 02/28/2022] [Accepted: 06/22/2022] [Indexed: 11/12/2022] Open
Abstract
MOTIVATION Pangenomes provide novel insights for population and quantitative genetics, genomics, and breeding not available from studying a single reference genome. Instead, a species is better represented by a pangenome or collection of genomes. Unfortunately, managing and using pangenomes for genomically diverse species is computationally and practically challenging. We developed a trellis graph representation anchored to the reference genome that represents most pangenomes well and can be used to impute complete genomes from low density sequence or variant data. RESULTS The Practical Haplotype Graph (PHG) is a pangenome pipeline, database (PostGRES & SQLite), data model (Java, Kotlin, or R), and Breeding API (BrAPI) web service. The PHG has already been able to accurately represent diversity in four major crops including maize, one of the most genomically diverse species, with up to 1000-fold data compression. Using simulated data, we show that, at even 0.1X coverage, with appropriate reads and sequence alignment, imputation results in extremely accurate haplotype reconstruction. The PHG is a platform and environment for the understanding and application of genomic diversity. AVAILABILITY All resources listed here are freely available. The PHG Docker used to generate the simulation results is https://hub.docker.com/ as maizegenetics/phg:0.0.27. PHG source code is at https://bitbucket.org/bucklerlab/practicalhaplotypegraph/src/master/. The code used for the analysis of simulated data is at https://bitbucket.org/bucklerlab/phg-manuscript/src/master/. The PHG database of NAM parent haplotypes is in the CyVerse data store (https://de.cyverse.org/de/) and named /iplant/home/shared/panzea/panGenome/PHG_db_maize/phg_v5Assemblies_20200608.db. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- P J Bradbury
- United States Department of Agriculture-Agricultural Research Service, Robert W. Holley Center, Ithaca, NY 14853 USA
| | - T Casstevens
- Institute for Genomic Diversity,Cornell University, Ithaca, NY 14853 USA
| | - S E Jensen
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA
| | - L C Johnson
- Institute for Genomic Diversity,Cornell University, Ithaca, NY 14853 USA
| | - Z R Miller
- Institute for Genomic Diversity,Cornell University, Ithaca, NY 14853 USA
| | - B Monier
- Institute for Genomic Diversity,Cornell University, Ithaca, NY 14853 USA
| | - M C Romay
- Institute for Genomic Diversity,Cornell University, Ithaca, NY 14853 USA
| | - B Song
- Institute for Genomic Diversity,Cornell University, Ithaca, NY 14853 USA
| | - E S Buckler
- United States Department of Agriculture-Agricultural Research Service, Robert W. Holley Center, Ithaca, NY 14853 USA.,Institute for Genomic Diversity,Cornell University, Ithaca, NY 14853 USA.,Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA
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Zhang X, Zhu Y, Kremling KAG, Romay MC, Bukowski R, Sun Q, Gao S, Buckler ES, Lu F. Genome-wide analysis of deletions in maize population reveals abundant genetic diversity and functional impact. Theor Appl Genet 2022; 135:273-290. [PMID: 34661697 DOI: 10.1007/s00122-021-03965-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 09/30/2021] [Indexed: 06/13/2023]
Abstract
Two read depth methods were jointly used in next-generation sequencing data to identify deletions in maize population. GWAS by deletions were analyzed for gene expression pattern and classical traits, respectively. Many studies have confirmed that structural variation (SV) is pervasive throughout the maize genome. Deletion is one type of SV that may impact gene expression and cause phenotypic changes in quantitative traits. In this study, two read count approaches were used to analyze the deletions in the whole-genome sequencing data of 270 maize inbred lines. A total of 19,754 deletion windows overlapped 12,751 genes, which were unevenly distributed across the genome. The deletions explained population structure well and correlated with genomic features. The deletion proportion of genes was determined to be negatively correlated with its expression. The detection of gene expression quantitative trait loci (eQTL) indicated that local eQTL were fewer but had larger effects than distant ones. The common associated genes were related to basic metabolic processes, whereas unique associated genes with eQTL played a role in the stress or stimulus responses in multiple tissues. Compared with the eQTL detected by SNPs derived from the same sequencing data, 89.4% of the associated genes could be detected by both markers. The effect of top eQTL detected by SNPs was usually larger than that detected by deletions for the same gene. A genome-wide association study (GWAS) on flowering time and plant height illustrated that only a few loci could be consistently captured by SNPs, suggesting that combining deletion and SNP for GWAS was an excellent strategy to dissect trait architecture. Our findings will provide insights into characteristic and biological function of genome-wide deletions in maize.
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Affiliation(s)
- Xiao Zhang
- Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China.
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Ministry of Agriculture, Chengdu, Sichuan, China.
- Institute for Genomic Diversity, Cornell University, 175 Biotechnology Building, Ithaca, NY, USA.
| | - Yonghui Zhu
- Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, Sichuan, China
| | - Karl A G Kremling
- Institute for Genomic Diversity, Cornell University, 175 Biotechnology Building, Ithaca, NY, USA
| | - M Cinta Romay
- Institute for Genomic Diversity, Cornell University, 175 Biotechnology Building, Ithaca, NY, USA
| | - Robert Bukowski
- Bioinformatics Facility, Institute of Biotechnology, Cornell University, Ithaca, NY, USA
| | - Qi Sun
- Bioinformatics Facility, Institute of Biotechnology, Cornell University, Ithaca, NY, USA
| | - Shibin Gao
- Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Ministry of Agriculture, Chengdu, Sichuan, China
| | - Edward S Buckler
- Institute for Genomic Diversity, Cornell University, 175 Biotechnology Building, Ithaca, NY, USA
- USDA-ARS, R. W. Holley Center, Cornell University, Ithaca, NY, USA
| | - Fei Lu
- Institute for Genomic Diversity, Cornell University, 175 Biotechnology Building, Ithaca, NY, USA.
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China.
- CAS-JIC Centre of Excellence for Plant and Microbial Science (CEPAMS), Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
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5
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Long EM, Romay MC, Ramstein G, Buckler ES, Robbins KR. Utilizing evolutionary conservation to detect deleterious mutations and improve genomic prediction in cassava. Front Plant Sci 2022; 13:1041925. [PMID: 37082510 PMCID: PMC10112518 DOI: 10.3389/fpls.2022.1041925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Accepted: 12/06/2022] [Indexed: 05/03/2023]
Abstract
Introduction Cassava (Manihot esculenta) is an annual root crop which provides the major source of calories for over half a billion people around the world. Since its domestication ~10,000 years ago, cassava has been largely clonally propagated through stem cuttings. Minimal sexual recombination has led to an accumulation of deleterious mutations made evident by heavy inbreeding depression. Methods To locate and characterize these deleterious mutations, and to measure selection pressure across the cassava genome, we aligned 52 related Euphorbiaceae and other related species representing millions of years of evolution. With single base-pair resolution of genetic conservation, we used protein structure models, amino acid impact, and evolutionary conservation across the Euphorbiaceae to estimate evolutionary constraint. With known deleterious mutations, we aimed to improve genomic evaluations of plant performance through genomic prediction. We first tested this hypothesis through simulation utilizing multi-kernel GBLUP to predict simulated phenotypes across separate populations of cassava. Results Simulations showed a sizable increase of prediction accuracy when incorporating functional variants in the model when the trait was determined by<100 quantitative trait loci (QTL). Utilizing deleterious mutations and functional weights informed through evolutionary conservation, we saw improvements in genomic prediction accuracy that were dependent on trait and prediction. Conclusion We showed the potential for using evolutionary information to track functional variation across the genome, in order to improve whole genome trait prediction. We anticipate that continued work to improve genotype accuracy and deleterious mutation assessment will lead to improved genomic assessments of cassava clones.
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Affiliation(s)
- Evan M. Long
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, United States
- *Correspondence: Evan M. Long,
| | - M. Cinta Romay
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, United States
| | - Guillaume Ramstein
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Edward S. Buckler
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, United States
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, United States
- United States Department of Agriculture-Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, NY, United States
| | - Kelly R. Robbins
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, United States
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6
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Long EM, Bradbury PJ, Romay MC, Buckler ES, Robbins KR. Genome-wide Imputation Using the Practical Haplotype Graph in the Heterozygous Crop Cassava. G3 (Bethesda) 2021; 12:6423990. [PMID: 34751380 PMCID: PMC8728015 DOI: 10.1093/g3journal/jkab383] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 10/14/2021] [Indexed: 11/13/2022]
Abstract
Genomic applications such as genomic selection and genome-wide association have become increasingly common since the advent of genome sequencing. The cost of sequencing has decreased in the past two decades; however, genotyping costs are still prohibitive to gathering large datasets for these genomic applications, especially in nonmodel species where resources are less abundant. Genotype imputation makes it possible to infer whole-genome information from limited input data, making large sampling for genomic applications more feasible. Imputation becomes increasingly difficult in heterozygous species where haplotypes must be phased. The practical haplotype graph (PHG) is a recently developed tool that can accurately impute genotypes, using a reference panel of haplotypes. We showcase the ability of the PHG to impute genomic information in the highly heterozygous crop cassava (Manihot esculenta). Accurately phased haplotypes were sampled from runs of homozygosity across a diverse panel of individuals to populate PHG, which proved more accurate than relying on computational phasing methods. The PHG achieved high imputation accuracy, using sparse skim-sequencing input, which translated to substantial genomic prediction accuracy in cross-validation testing. The PHG showed improved imputation accuracy, compared to a standard imputation tool Beagle, especially in predicting rare alleles.
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Affiliation(s)
- Evan M Long
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA
| | - Peter J Bradbury
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853, USA.,United States Department of Agriculture-Agricultural Research Service, Robert W. Holley, Center for Agriculture and Health, Ithaca, NY 14853, USA
| | - M Cinta Romay
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853, USA
| | - Edward S Buckler
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA.,Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853, USA.,United States Department of Agriculture-Agricultural Research Service, Robert W. Holley, Center for Agriculture and Health, Ithaca, NY 14853, USA
| | - Kelly R Robbins
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA
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7
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Adak A, Murray SC, Anderson SL, Popescu SC, Malambo L, Romay MC, de Leon N. Unoccupied aerial systems discovered overlooked loci capturing the variation of entire growing period in maize. Plant Genome 2021; 14:e20102. [PMID: 34009740 DOI: 10.1002/tpg2.20102] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 03/29/2021] [Indexed: 06/12/2023]
Abstract
Traditional phenotyping methods, coupled with genetic mapping in segregating populations, have identified loci governing complex traits in many crops. Unoccupied aerial systems (UAS)-based phenotyping has helped to reveal a more novel and dynamic relationship between time-specific associated loci with complex traits previously unable to be evaluated. Over 1,500 maize (Zea mays L.) hybrid row plots containing 280 different replicated maize hybrids from the Genomes to Fields (G2F) project were evaluated agronomically and using UAS in 2017. Weekly UAS flights captured variation in plant heights during the growing season under three different management conditions each year: optimal planting with irrigation (G2FI), optimal dryland planting without irrigation (G2FD), and a stressed late planting (G2LA). Plant height of different flights were ranked based on importance for yield using a random forest (RF) algorithm. Plant heights captured by early flights in G2FI trials had higher importance (based on Gini scores) for predicting maize grain yield (GY) but also higher accuracies in genomic predictions which fluctuated for G2FD (-0.06∼0.73), G2FI (0.33∼0.76), and G2LA (0.26∼0.78) trials. A genome-wide association analysis discovered 52 significant single nucleotide polymorphisms (SNPs), seven were found consistently in more than one flights or trial; 45 were flight or trial specific. Total cumulative marker effects for each chromosome's contributions to plant height also changed depending on flight. Using UAS phenotyping, this study showed that many candidate genes putatively play a role in the regulation of plant architecture even in relatively early stages of maize growth and development.
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Affiliation(s)
- Alper Adak
- Dept. of Soil and Crop Sciences, Texas A&M Univ., College Station, TX, 77843-2474, USA
| | - Seth C Murray
- Dept. of Soil and Crop Sciences, Texas A&M Univ., College Station, TX, 77843-2474, USA
| | - Steven L Anderson
- Dept. of Environmental Hort., Institute of Food and Agricultural Sciences, Mid-Florida Research and Education Center, University of Florida, Apopka, FL, USA
| | - Sorin C Popescu
- Dept. of Ecosystem Science and Management, Texas A&M Univ., College Station, TX, 77843-2120, USA
| | - Lonesome Malambo
- Dept. of Ecosystem Science and Management, Texas A&M Univ., College Station, TX, 77843-2120, USA
| | - M Cinta Romay
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, USA
| | - Natalia de Leon
- Department of Agronomy, University of Wisconsin, 1575 Linden Drive, Madison, WI, 53706, USA
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8
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Song B, Buckler ES, Wang H, Wu Y, Rees E, Kellogg EA, Gates DJ, Khaipho-Burch M, Bradbury PJ, Ross-Ibarra J, Hufford MB, Romay MC. Conserved noncoding sequences provide insights into regulatory sequence and loss of gene expression in maize. Genome Res 2021; 31:1245-1257. [PMID: 34045362 PMCID: PMC8256870 DOI: 10.1101/gr.266528.120] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 05/21/2021] [Indexed: 01/16/2023]
Abstract
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 cis-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 cis-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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Affiliation(s)
- Baoxing Song
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853, USA
| | - Edward S Buckler
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853, USA
- Section of Plant Breeding and Genetics, Cornell University, Ithaca, New York 14853, USA
- Agricultural Research Service, United States Department of Agriculture, Ithaca, New York 14853, USA
| | - Hai Wang
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853, USA
- National Maize Improvement Center, Key Laboratory of Crop Heterosis and Utilization, Joint Laboratory for International Cooperation in Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Yaoyao Wu
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853, USA
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Evan Rees
- Section of Plant Breeding and Genetics, Cornell University, Ithaca, New York 14853, USA
| | | | - Daniel J Gates
- Department of Evolution and Ecology, University of California Davis, Davis, California 95616, USA
| | - Merritt Khaipho-Burch
- Section of Plant Breeding and Genetics, Cornell University, Ithaca, New York 14853, USA
| | - Peter J Bradbury
- Agricultural Research Service, United States Department of Agriculture, Ithaca, New York 14853, USA
| | - Jeffrey Ross-Ibarra
- Department of Evolution and Ecology, University of California Davis, Davis, California 95616, USA
- Center for Population Biology and Genome Center, University of California Davis, Davis, California 95616, USA
| | - Matthew B Hufford
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, Iowa 50011, USA
| | - M Cinta Romay
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853, USA
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9
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Yi Q, Álvarez-Iglesias L, Malvar RA, Romay MC, Revilla P. A worldwide maize panel revealed new genetic variation for cold tolerance. Theor Appl Genet 2021; 134:1083-1094. [PMID: 33582854 DOI: 10.1007/s00122-020-03753-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 12/12/2020] [Indexed: 05/21/2023]
Abstract
A large association panel of 836 maize inbreds revealed a broader genetic diversity of cold tolerance, as predominantly favorable QTL with small effects were identified, indicating that genomic selection is the most promising option for breeding maize for cold tolerance. Maize (Zea mays L.) has limited cold tolerance, and breeding for cold tolerance is a noteworthy bottleneck for reaching the high potential of maize production in temperate areas. In this study, we evaluate a large panel of 836 maize inbred lines to detect genetic loci and candidate genes for cold tolerance at the germination and seedling stages. Genetic variation for cold tolerance was larger than in previous reports with moderately high heritability for most traits. We identified 187 significant single-nucleotide polymorphisms (SNPs) that were integrated into 159 quantitative trait loci (QTL) for emergence and traits related to early growth. Most of the QTL have small effects and are specific for each environment, with the majority found under control conditions. Favorable alleles are more frequent in 120 inbreds including all germplasm groups, but mainly from Minnesota and Spain. Therefore, there is a large, potentially novel, genetic variability in the germplasm groups represented by these inbred lines. Most of the candidate genes are involved in metabolic processes and intracellular membrane-bounded organelles. We expect that further evaluations of germplasm with broader genetic diversity could identify additional favorable alleles for cold tolerance. However, it is not likely that further studies will find favorable alleles with large effects for improving cold tolerance in maize.
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Affiliation(s)
- Q Yi
- Misión Biológica de Galicia (CSIC), Apartado 28, E-36080, Pontevedra, Spain
- College of Agriculture, Guizhou University, Guiyang, 550025, China
| | - L Álvarez-Iglesias
- Misión Biológica de Galicia (CSIC), Apartado 28, E-36080, Pontevedra, Spain
| | - R A Malvar
- Misión Biológica de Galicia (CSIC), Apartado 28, E-36080, Pontevedra, Spain
| | - M C Romay
- Institute for Genomic Diversity, Cornell University, Ithaca, NY14853, USA
| | - Pedro Revilla
- Misión Biológica de Galicia (CSIC), Apartado 28, E-36080, Pontevedra, Spain.
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10
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Chen SY, Su MH, Kremling KA, Lepak NK, Romay MC, Sun Q, Bradbury PJ, Buckler ES, Ku HM. Identification of miRNA-eQTLs in maize mature leaf by GWAS. BMC Genomics 2020; 21:689. [PMID: 33023467 PMCID: PMC7541240 DOI: 10.1186/s12864-020-07073-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 09/14/2020] [Indexed: 11/28/2022] Open
Abstract
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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Affiliation(s)
- Shu-Yun Chen
- Department of Life Science, National Cheng Kung University, Tainan, 701, Taiwan
| | - Mei-Hsiu Su
- Agricultural Biotechnology Research Center, Academia Sinica, Taipei, 115, Taiwan
| | - Karl A Kremling
- Department of Plant Breeding and Genetics, Cornell University, Ithaca, 14850, NY, USA
| | - Nicholas K Lepak
- United States Department of Agriculture-Agricultural Research Service, Ithaca, NY, USA
| | - M Cinta Romay
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, USA
| | - Qi Sun
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, USA
| | - Peter J Bradbury
- United States Department of Agriculture-Agricultural Research Service, Ithaca, NY, USA
| | - Edward S Buckler
- Department of Plant Breeding and Genetics, Cornell University, Ithaca, 14850, NY, USA.,United States Department of Agriculture-Agricultural Research Service, Ithaca, NY, USA.,Institute for Genomic Diversity, Cornell University, Ithaca, NY, USA
| | - Hsin-Mei Ku
- Advanced Plant Biotechnology Center, National Chung Hsing University, No 145 Xingda Rd, South Dist, Taichung, 402, Taiwan.
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11
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Ramstein GP, Larsson SJ, Cook JP, Edwards JW, Ersoz ES, Flint-Garcia S, Gardner CA, Holland JB, Lorenz AJ, McMullen MD, Millard MJ, Rocheford TR, Tuinstra MR, Bradbury PJ, Buckler ES, Romay MC. Dominance Effects and Functional Enrichments Improve Prediction of Agronomic Traits in Hybrid Maize. Genetics 2020; 215:215-230. [PMID: 32152047 PMCID: PMC7198274 DOI: 10.1534/genetics.120.303025] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Accepted: 02/26/2020] [Indexed: 01/04/2023] Open
Abstract
Single-cross hybrids have been critical to the improvement of maize (Zea mays 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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Affiliation(s)
| | - Sara J Larsson
- Section of Plant Breeding and Genetics, Cornell University, Ithaca, New York 14853
| | - Jason P Cook
- Division of Plant Science, University of Missouri, Columbia, Missouri 56211
| | - Jode W Edwards
- U.S. Department of Agriculture-Agricultural Research Service, Ames, Iowa 50011
| | | | - Sherry Flint-Garcia
- U.S. Department of Agriculture-Agricultural Research Service, University of Missouri, Columbia, Missouri 56211
| | - Candice A Gardner
- U.S. Department of Agriculture-Agricultural Research Service, Ames, Iowa 50011
| | - James B Holland
- U.S. Department of Agriculture-Agricultural Research Service, Department of Crop and Soil Sciences, North Carolina State University, Raleigh, North Carolina 27695
| | - Aaron J Lorenz
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, Nebraska 68588
| | - Michael D McMullen
- U.S. Department of Agriculture-Agricultural Research Service, University of Missouri, Columbia, Missouri 56211
| | - Mark J Millard
- U.S. Department of Agriculture-Agricultural Research Service, Ames, Iowa 50011
| | | | | | - Peter J Bradbury
- U.S. Department of Agriculture-Agricultural Research Service, Ithaca, New York 14853
| | - Edward S Buckler
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853
- U.S. Department of Agriculture-Agricultural Research Service, Ithaca, New York 14853
| | - M Cinta Romay
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853
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12
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Jensen SE, Charles JR, Muleta K, Bradbury PJ, Casstevens T, Deshpande SP, Gore MA, Gupta R, Ilut DC, Johnson L, Lozano R, Miller Z, Ramu P, Rathore A, Romay MC, Upadhyaya HD, Varshney RK, Morris GP, Pressoir G, Buckler ES, Ramstein GP. A sorghum practical haplotype graph facilitates genome-wide imputation and cost-effective genomic prediction. Plant Genome 2020; 13:e20009. [PMID: 33016627 DOI: 10.1002/tpg2.20009] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 01/04/2020] [Indexed: 05/22/2023]
Abstract
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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Affiliation(s)
- Sarah E Jensen
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853, USA
| | - Jean Rigaud Charles
- Chibas and Department of Agriculture and Environmental Sciences, Quisqueya University, Port-au-Prince, Haiti
| | - Kebede Muleta
- Department of Agronomy, Kansas State University, Manhattan, KS, 66506, USA
| | - Peter J Bradbury
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, 14853, USA
- United States Department of Agriculture-Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, NY, 14853, USA
| | - Terry Casstevens
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, 14853, USA
| | - Santosh P Deshpande
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, 502324, India
| | - Michael A Gore
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853, USA
| | - Rajeev Gupta
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, 502324, India
| | - Daniel C Ilut
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853, USA
| | - Lynn Johnson
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, 14853, USA
| | - Roberto Lozano
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853, USA
| | - Zachary Miller
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, 14853, USA
| | - Punna Ramu
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, 14853, USA
| | - Abhishek Rathore
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, 502324, India
| | - M Cinta Romay
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, 14853, USA
| | - Hari D Upadhyaya
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, 502324, India
| | - Rajeev K Varshney
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, 502324, India
| | - Geoffrey P Morris
- Department of Agronomy, Kansas State University, Manhattan, KS, 66506, USA
| | - Gael Pressoir
- Chibas and Department of Agriculture and Environmental Sciences, Quisqueya University, Port-au-Prince, Haiti
| | - Edward S Buckler
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853, USA
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, 14853, USA
- United States Department of Agriculture-Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, NY, 14853, USA
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13
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Bukowski R, Guo X, Lu Y, Zou C, He B, Rong Z, Wang B, Xu D, Yang B, Xie C, Fan L, Gao S, Xu X, Zhang G, Li Y, Jiao Y, Doebley JF, Ross-Ibarra J, Lorant A, Buffalo V, Romay MC, Buckler ES, Ware D, Lai J, Sun Q, Xu Y. Construction of the third-generation Zea mays haplotype map. Gigascience 2018; 7:1-12. [PMID: 29300887 PMCID: PMC5890452 DOI: 10.1093/gigascience/gix134] [Citation(s) in RCA: 150] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2017] [Accepted: 12/22/2017] [Indexed: 12/30/2022] Open
Abstract
Background Characterization of genetic variations in maize has been challenging, mainly due to deterioration of collinearity between individual genomes in the species. An international consortium of maize research groups combined resources to develop the maize haplotype version 3 (HapMap 3), built from whole-genome sequencing data from 1218 maize lines, covering predomestication and domesticated Zea mays varieties across the world. Results A new computational pipeline was set up to process more than 12 trillion bp of sequencing data, and a set of population genetics filters was applied to identify more than 83 million variant sites. Conclusions We identified polymorphisms in regions where collinearity is largely preserved in the maize species. However, the fact that the B73 genome used as the reference only represents a fraction of all haplotypes is still an important limiting factor.
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Affiliation(s)
- Robert Bukowski
- Bioinformatics Facility, Institute of Biotechnology, Cornell University, Ithaca, NY, 14853, USA
| | - Xiaosen Guo
- BGI-Shenzhen, Shenzhen 518083, China
- Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, DK-2200 Copenhagen, Denmark
| | - Yanli Lu
- Maize Research Institute, Sichuan Agricultural University, Wenjiang 611130, Sichuan, China
| | - Cheng Zou
- Institute of Crop Science, Chinese Academy of Agricultural Sciences/National Key Facilities for Crop Gene Resource and Genetic Improvement, Beijing 100081, China
| | - Bing He
- BGI-Shenzhen, Shenzhen 518083, China
| | | | - Bo Wang
- BGI-Shenzhen, Shenzhen 518083, China
| | - Dawen Xu
- BGI-Shenzhen, Shenzhen 518083, China
| | | | - Chuanxiao Xie
- Institute of Crop Science, Chinese Academy of Agricultural Sciences/National Key Facilities for Crop Gene Resource and Genetic Improvement, Beijing 100081, China
| | - Longjiang Fan
- Institute of Crop Science and Institute of Bioinformatics, Department of Agronomy, Zhejiang University, Hangzhou 310058, China
| | - Shibin Gao
- Maize Research Institute, Sichuan Agricultural University, Wenjiang 611130, Sichuan, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen 518083, China
| | | | | | - Yinping Jiao
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - John F Doebley
- Department of Genetics, University of Wisconsin, Madison, WI 53706, USA
| | - Jeffrey Ross-Ibarra
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - Anne Lorant
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - Vince Buffalo
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - M Cinta Romay
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853, USA
| | - Edward S Buckler
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853, USA
- US Department of Agriculture-Agricultural Research Service, Ithaca, NY 14853, USA
| | - Doreen Ware
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Jinsheng Lai
- National Maize Improvement Center, China Agricultural University, Beijing 100193, China
| | - Qi Sun
- Bioinformatics Facility, Institute of Biotechnology, Cornell University, Ithaca, NY, 14853, USA
- Correspondence address. Qi Sun, Bioinformatics Facility, Institute of Biotechnology, Cornell University, Ithaca, NY 14853. Tel: 1-607-254-6768; Fax: 1-607-254-8888; E-mail:
| | - Yunbi Xu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences/National Key Facilities for Crop Gene Resource and Genetic Improvement, Beijing 100081, China
- International Maize and Wheat Improvement Center (CIMMYT), El Batan 56130, Texcoco, Mexico
- Correspondence address. Yunbi Xu, Institute of Crop Science, Chinese Academy of Agricultural Sciences/National Key Facilities for Crop Gene Resource and Genetic Improvement, Beijing 100081, China. Tel: +86-10-82105801; Fax: +86-10-82105802; E-mail:
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14
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Bukowski R, Guo X, Lu Y, Zou C, He B, Rong Z, Wang B, Xu D, Yang B, Xie C, Fan L, Gao S, Xu X, Zhang G, Li Y, Jiao Y, Doebley JF, Ross-Ibarra J, Lorant A, Buffalo V, Romay MC, Buckler ES, Ware D, Lai J, Sun Q, Xu Y. Construction of the third-generation Zea mays haplotype map. Gigascience 2018; 7:1-12. [PMID: 29300887 DOI: 10.1101/026963] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2017] [Accepted: 12/22/2017] [Indexed: 05/25/2023] Open
Abstract
BACKGROUND Characterization of genetic variations in maize has been challenging, mainly due to deterioration of collinearity between individual genomes in the species. An international consortium of maize research groups combined resources to develop the maize haplotype version 3 (HapMap 3), built from whole-genome sequencing data from 1218 maize lines, covering predomestication and domesticated Zea mays varieties across the world. RESULTS A new computational pipeline was set up to process more than 12 trillion bp of sequencing data, and a set of population genetics filters was applied to identify more than 83 million variant sites. CONCLUSIONS We identified polymorphisms in regions where collinearity is largely preserved in the maize species. However, the fact that the B73 genome used as the reference only represents a fraction of all haplotypes is still an important limiting factor.
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Affiliation(s)
- Robert Bukowski
- Bioinformatics Facility, Institute of Biotechnology, Cornell University, Ithaca, NY, 14853, USA
| | - Xiaosen Guo
- BGI-Shenzhen, Shenzhen 518083, China
- Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, DK-2200 Copenhagen, Denmark
| | - Yanli Lu
- Maize Research Institute, Sichuan Agricultural University, Wenjiang 611130, Sichuan, China
| | - Cheng Zou
- Institute of Crop Science, Chinese Academy of Agricultural Sciences/National Key Facilities for Crop Gene Resource and Genetic Improvement, Beijing 100081, China
| | - Bing He
- BGI-Shenzhen, Shenzhen 518083, China
| | | | - Bo Wang
- BGI-Shenzhen, Shenzhen 518083, China
| | - Dawen Xu
- BGI-Shenzhen, Shenzhen 518083, China
| | | | - Chuanxiao Xie
- Institute of Crop Science, Chinese Academy of Agricultural Sciences/National Key Facilities for Crop Gene Resource and Genetic Improvement, Beijing 100081, China
| | - Longjiang Fan
- Institute of Crop Science and Institute of Bioinformatics, Department of Agronomy, Zhejiang University, Hangzhou 310058, China
| | - Shibin Gao
- Maize Research Institute, Sichuan Agricultural University, Wenjiang 611130, Sichuan, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen 518083, China
| | | | | | - Yinping Jiao
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - John F Doebley
- Department of Genetics, University of Wisconsin, Madison, WI 53706, USA
| | - Jeffrey Ross-Ibarra
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - Anne Lorant
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - Vince Buffalo
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - M Cinta Romay
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853, USA
| | - Edward S Buckler
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853, USA
- US Department of Agriculture-Agricultural Research Service, Ithaca, NY 14853, USA
| | - Doreen Ware
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Jinsheng Lai
- National Maize Improvement Center, China Agricultural University, Beijing 100193, China
| | - Qi Sun
- Bioinformatics Facility, Institute of Biotechnology, Cornell University, Ithaca, NY, 14853, USA
| | - Yunbi Xu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences/National Key Facilities for Crop Gene Resource and Genetic Improvement, Beijing 100081, China
- International Maize and Wheat Improvement Center (CIMMYT), El Batan 56130, Texcoco, Mexico
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15
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Kremling KAG, Chen SY, Su MH, Lepak NK, Romay MC, Swarts KL, Lu F, Lorant A, Bradbury PJ, Buckler ES. Dysregulation of expression correlates with rare-allele burden and fitness loss in maize. Nature 2018. [PMID: 29539638 DOI: 10.1038/nature25966] [Citation(s) in RCA: 118] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
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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Affiliation(s)
- Karl A G Kremling
- Section of Plant Breeding and Genetics, 175 Biotechnology Building, Cornell University, Ithaca, New York 14853, USA
| | - Shu-Yun Chen
- Institute for Genomic Diversity, 175 Biotechnology Building, Cornell University, Ithaca, New York 14853, USA.,Institute of Plant and Microbial Biology, Academia Sinica 128, Sec 2nd, Academia road, Taipei, 11529, Taiwan
| | - Mei-Hsiu Su
- Institute for Genomic Diversity, 175 Biotechnology Building, Cornell University, Ithaca, New York 14853, USA
| | - Nicholas K Lepak
- USDA-ARS, R. W. Holley Center, Cornell University, Ithaca, New York 14853, USA
| | - M Cinta Romay
- Institute for Genomic Diversity, 175 Biotechnology Building, Cornell University, Ithaca, New York 14853, USA
| | - Kelly L Swarts
- Section of Plant Breeding and Genetics, 175 Biotechnology Building, Cornell University, Ithaca, New York 14853, USA.,Research Group for Ancient Genomics and Evolution, Department of Molecular Biology, Max Planck Institute for Developmental Biology, Spemannstr. 35, 72076 Tübingen, Germany
| | - Fei Lu
- Institute for Genomic Diversity, 175 Biotechnology Building, Cornell University, Ithaca, New York 14853, USA.,The State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Anne Lorant
- Department of Plant Sciences, University of California Davis, Davis, California 95616, USA
| | - Peter J Bradbury
- USDA-ARS, R. W. Holley Center, Cornell University, Ithaca, New York 14853, USA
| | - Edward S Buckler
- Section of Plant Breeding and Genetics, 175 Biotechnology Building, Cornell University, Ithaca, New York 14853, USA.,Institute for Genomic Diversity, 175 Biotechnology Building, Cornell University, Ithaca, New York 14853, USA.,USDA-ARS, R. W. Holley Center, Cornell University, Ithaca, New York 14853, USA
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16
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Swarts K, Gutaker RM, Benz B, Blake M, Bukowski R, Holland J, Kruse-Peeples M, Lepak N, Prim L, Romay MC, Ross-Ibarra J, Sanchez-Gonzalez JDJ, Schmidt C, Schuenemann VJ, Krause J, Matson RG, Weigel D, Buckler ES, Burbano HA. Genomic estimation of complex traits reveals ancient maize adaptation to temperate North America. Science 2017; 357:512-515. [DOI: 10.1126/science.aam9425] [Citation(s) in RCA: 127] [Impact Index Per Article: 18.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Accepted: 06/29/2017] [Indexed: 01/24/2023]
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17
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Buckler ES, Holland JB, Bradbury PJ, Acharya CB, Brown PJ, Browne C, Ersoz E, Flint-Garcia S, Garcia A, Glaubitz JC, Goodman MM, Harjes C, Guill K, Kroon DE, Larsson S, Lepak NK, Li H, Mitchell SE, Pressoir G, Peiffer JA, Rosas MO, Rocheford TR, Romay MC, Romero S, Salvo S, Sanchez Villeda H, da Silva HS, Sun Q, Tian F, Upadyayula N, Ware D, Yates H, Yu J, Zhang Z, Kresovich S, McMullen MD. The genetic architecture of maize flowering time. Science 2009; 325:714-8. [PMID: 19661422 DOI: 10.1126/science.1174276] [Citation(s) in RCA: 793] [Impact Index Per Article: 52.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Flowering time is a complex trait that controls adaptation of plants to their local environment in the outcrossing species Zea mays (maize). We dissected variation for flowering time with a set of 5000 recombinant inbred lines (maize Nested Association Mapping population, NAM). Nearly a million plants were assayed in eight environments but showed no evidence for any single large-effect quantitative trait loci (QTLs). Instead, we identified evidence for numerous small-effect QTLs shared among families; however, allelic effects differ across founder lines. We identified no individual QTLs at which allelic effects are determined by geographic origin or large effects for epistasis or environmental interactions. Thus, a simple additive model accurately predicts flowering time for maize, in contrast to the genetic architecture observed in the selfing plant species rice and Arabidopsis.
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Affiliation(s)
- Edward S Buckler
- U.S. Department of Agriculture (USDA)-Agricultural Research Service (USDA-ARS), USA.
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