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Pronozin AY, Karetnikov DI, Shmakov NA, Bocharnikova ME, Afonnikova SD, Afonnikov DA, Kolchanov NA. CropGene: a software package for the analysis of genomic and transcriptomic data of agricultural plants. Vavilovskii Zhurnal Genet Selektsii 2025; 29:320-329. [PMID: 40264806 PMCID: PMC12011622 DOI: 10.18699/vjgb-25-35] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2024] [Revised: 01/15/2025] [Accepted: 01/15/2025] [Indexed: 04/24/2025] Open
Abstract
Currently, the breeding of agricultural plants is increasingly based on the use of molecular biological data on genetic sequences, which makes it possible to significantly accelerate the breeding process, create new plant varieties through genomic editing. These data have a large volume, variety and require a large amount of resources, both labor and computing, to analyze the costs. Data analysis of such volume and complexity can be effective only when using modern bioinformatics methods, which include algorithms for identifying genes, predicting their function, and evaluating the effect of mutation on plant phenotype. Such an analysis has recently become impossible without the use of integrated software systems that solve problems of different levels by executing computational pipelines. The paper describes the CropGene software package developed for the comprehensive analysis of genomic and transcriptomic data of agricultural plants. CropGene includes several blocks of bioinformatic analysis, such as analysis of gene variations, assembly of genomes and transcriptomes, as well as annotation of genes and proteins. CropGene implements new methods for analyzing long non-coding RNAs, protein domains, searching and analyzing polymorphisms, and genome-wide association research. CropGene has a user-friendly interface and supports working with various types of data, which greatly simplifies its use for researchers who do not have deep knowledge in the field of bioinformatics. The paper provides examples of the use of CropGene for the analysis of agricultural organisms such as Solanum tuberosum and Zea mays. With CropGene, genetic markers have been identified that explain up to 50 % of the variability in seed color parameters; potential genes that may become promising material for producing potato varieties; more than 100 thousand new long non-coding RNAs. Orthogroups were also found, the domain structure of which shows a marked similarity with the domain architecture of characteristic secreted A2 phospholipases. Thus, CropGene is an important tool for scientists and practitioners working in the field of agrobiotechnology and plant genetics.
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Affiliation(s)
- A Yu Pronozin
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Kurchatov Genomic Center of ICG SB RAS, Novosibirsk, Russia
| | - D I Karetnikov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Kurchatov Genomic Center of ICG SB RAS, Novosibirsk, Russia
| | - N A Shmakov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Kurchatov Genomic Center of ICG SB RAS, Novosibirsk, Russia
| | - M E Bocharnikova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Kurchatov Genomic Center of ICG SB RAS, Novosibirsk, Russia
| | - S D Afonnikova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Kurchatov Genomic Center of ICG SB RAS, Novosibirsk, Russia
| | - D A Afonnikov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Kurchatov Genomic Center of ICG SB RAS, Novosibirsk, Russia
| | - N A Kolchanov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Kurchatov Genomic Center of ICG SB RAS, Novosibirsk, Russia
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Guo W, Schreiber M, Marosi VB, Bagnaresi P, Jørgensen ME, Braune KB, Chalmers K, Chapman B, Dang V, Dockter C, Fiebig A, Fincher GB, Fricano A, Fuller J, Haaning A, Haberer G, Himmelbach A, Jayakodi M, Jia Y, Kamal N, Langridge P, Li C, Lu Q, Lux T, Mascher M, Mayer KFX, McCallum N, Milne L, Muehlbauer GJ, Nielsen MTS, Padmarasu S, Pedas PR, Pillen K, Pozniak C, Rasmussen MW, Sato K, Schmutzer T, Scholz U, Schüler D, Šimková H, Skadhauge B, Stein N, Thomsen NW, Voss C, Wang P, Wonneberger R, Zhang XQ, Zhang G, Cattivelli L, Spannagl M, Bayer M, Simpson C, Zhang R, Waugh R. A barley pan-transcriptome reveals layers of genotype-dependent transcriptional complexity. Nat Genet 2025; 57:441-450. [PMID: 39901014 PMCID: PMC11821519 DOI: 10.1038/s41588-024-02069-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Accepted: 12/20/2024] [Indexed: 02/05/2025]
Abstract
A pan-transcriptome describes the transcriptional and post-transcriptional consequences of genome diversity from multiple individuals within a species. We developed a barley pan-transcriptome using 20 inbred genotypes representing domesticated barley diversity by generating and analyzing short- and long-read RNA-sequencing datasets from multiple tissues. To overcome single reference bias in transcript quantification, we constructed genotype-specific reference transcript datasets (RTDs) and integrated these into a linear pan-genome framework to create a pan-RTD, allowing transcript categorization as core, shell or cloud. Focusing on the core (expressed in all genotypes), we observed significant transcript abundance variation among tissues and between genotypes driven partly by RNA processing, gene copy number, structural rearrangements and conservation of promotor motifs. Network analyses revealed conserved co-expression module::tissue correlations and frequent functional diversification. To complement the pan-transcriptome, we constructed a comprehensive cultivar (cv.) Morex gene-expression atlas and illustrate how these combined datasets can be used to guide biological inquiry.
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Affiliation(s)
- Wenbin Guo
- International Barley Hub (IBH)/James Hutton Institute (JHI), Dundee, Scotland
- Higentec Breeding Innovation (ZheJiang) Co., Ltd., Lishui, China
| | - Miriam Schreiber
- International Barley Hub (IBH)/James Hutton Institute (JHI), Dundee, Scotland
| | - Vanda B Marosi
- Plant Genome and Systems Biology, Helmholtz Center Munich-German Research Center for Environmental Health (PGSB), Neuherberg, Germany
- School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Paolo Bagnaresi
- Council for Agriculture Research and Economics (CREA) Research Centre for Genomics and Bioinformatics, Fiorenzuola d'Arda, Italy
- CREA Research Centre for Olive, Fruit and Citrus Crops, Forlì, Italy
| | | | | | - Ken Chalmers
- School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Urrbrae, South Australia, Australia
| | - Brett Chapman
- Western Crop Genetics Alliance, Food Futures Institute/School of Agriculture, Murdoch University, Murdoch, Western Australia, Australia
| | - Viet Dang
- Western Crop Genetics Alliance, Food Futures Institute/School of Agriculture, Murdoch University, Murdoch, Western Australia, Australia
| | | | - Anne Fiebig
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Geoffrey B Fincher
- School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Urrbrae, South Australia, Australia
| | - Agostino Fricano
- Council for Agriculture Research and Economics (CREA) Research Centre for Genomics and Bioinformatics, Fiorenzuola d'Arda, Italy
| | - John Fuller
- International Barley Hub (IBH)/James Hutton Institute (JHI), Dundee, Scotland
| | - Allison Haaning
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, USA
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, USA
| | - Georg Haberer
- Plant Genome and Systems Biology, Helmholtz Center Munich-German Research Center for Environmental Health (PGSB), Neuherberg, Germany
| | - Axel Himmelbach
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Murukarthick Jayakodi
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
- Texas A&M AgriLife Research Center at Dallas, Texas A&M University System, Dallas, TX, USA
- Department of Soil & Crop Sciences, Texas A&M University, College Station, TX, USA
| | - Yong Jia
- Western Crop Genetics Alliance, Food Futures Institute/School of Agriculture, Murdoch University, Murdoch, Western Australia, Australia
| | - Nadia Kamal
- Plant Genome and Systems Biology, Helmholtz Center Munich-German Research Center for Environmental Health (PGSB), Neuherberg, Germany
- Department of Molecular Life Sciences, Computational Plant Biology, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Peter Langridge
- School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Urrbrae, South Australia, Australia
| | - Chengdao Li
- Western Crop Genetics Alliance, Food Futures Institute/School of Agriculture, Murdoch University, Murdoch, Western Australia, Australia
- College of Agriculture, Yangtze University, Jinzhou, China
- Department of Primary Industry and Regional Development Western Australia, South Perth, Western Australia, Australia
| | - Qiongxian Lu
- Carlsberg Research Laboratory (CRL), Copenhagen, Denmark
| | - Thomas Lux
- Plant Genome and Systems Biology, Helmholtz Center Munich-German Research Center for Environmental Health (PGSB), Neuherberg, Germany
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Klaus F X Mayer
- Plant Genome and Systems Biology, Helmholtz Center Munich-German Research Center for Environmental Health (PGSB), Neuherberg, Germany
| | - Nicola McCallum
- International Barley Hub (IBH)/James Hutton Institute (JHI), Dundee, Scotland
| | - Linda Milne
- International Barley Hub (IBH)/James Hutton Institute (JHI), Dundee, Scotland
| | - Gary J Muehlbauer
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, USA
| | | | - Sudharsan Padmarasu
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Pai Rosager Pedas
- Carlsberg Research Laboratory (CRL), Copenhagen, Denmark
- DLF, Roskilde, Denmark
| | - Klaus Pillen
- Chair of Plant Breeding, Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Curtis Pozniak
- Department of Plant Sciences and Crop Development Centre, University of Saskatchewan (USASK), Saskatoon, Saskatchewan, Canada
| | | | - Kazuhiro Sato
- Institute of Plant Science and Resources, Okayama University, Kurashiki, Japan
- Kazusa DNA Research Institute, Kisarazu, Japan
| | - Thomas Schmutzer
- Chair of Plant Breeding, Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Uwe Scholz
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Danuta Schüler
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Hana Šimková
- Institute of Experimental Botany of the Czech Academy of Sciences, Olomouc, Czech Republic
| | | | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
- Chair of Crop Plant Genetics, Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Nina W Thomsen
- Carlsberg Research Laboratory (CRL), Copenhagen, Denmark
| | - Cynthia Voss
- Carlsberg Research Laboratory (CRL), Copenhagen, Denmark
| | - Penghao Wang
- Western Crop Genetics Alliance, Food Futures Institute/School of Agriculture, Murdoch University, Murdoch, Western Australia, Australia
| | - Ronja Wonneberger
- International Barley Hub (IBH)/James Hutton Institute (JHI), Dundee, Scotland
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Xiao-Qi Zhang
- Western Crop Genetics Alliance, Food Futures Institute/School of Agriculture, Murdoch University, Murdoch, Western Australia, Australia
| | - Guoping Zhang
- College of Agriculture & Biotechnology, Zhejiang University, Hangzhou, China
| | - Luigi Cattivelli
- Council for Agriculture Research and Economics (CREA) Research Centre for Genomics and Bioinformatics, Fiorenzuola d'Arda, Italy
| | - Manuel Spannagl
- Plant Genome and Systems Biology, Helmholtz Center Munich-German Research Center for Environmental Health (PGSB), Neuherberg, Germany
| | - Micha Bayer
- International Barley Hub (IBH)/James Hutton Institute (JHI), Dundee, Scotland.
| | - Craig Simpson
- International Barley Hub (IBH)/James Hutton Institute (JHI), Dundee, Scotland.
| | - Runxuan Zhang
- International Barley Hub (IBH)/James Hutton Institute (JHI), Dundee, Scotland.
| | - Robbie Waugh
- International Barley Hub (IBH)/James Hutton Institute (JHI), Dundee, Scotland.
- School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Urrbrae, South Australia, Australia.
- School of Life Sciences, University of Dundee, Dundee, UK.
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Chen M, Liu P, An R, He X, Zhao P, Huang D, Yang X. Sugarcane Pan-Transcriptome Identifying a Master Gene ScHCT Regulating Lignin and Sugar Traits. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2025; 73:1739-1755. [PMID: 39761552 DOI: 10.1021/acs.jafc.4c10101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2025]
Abstract
Sugarcane has the most complex polyploid genome in the world, and sugar-related traits are one of the most important aims in sugarcane breeding. It is essential to construct a representative pan-transcriptome that contains all transcripts of a species for studies on genetic diversity, population expression, and omics analyses in sugarcane. In this study, we constructed the first comprehensive pan-transcriptome for sugarcane, and 8434 highly reliable open reading frames were found, which were not aligned with any published sugarcane genome. The core and dispensable gene clusters, as well as high- and low-expression gene clusters of the pan-transcriptome, were identified and analyzed. The integration of two sugar content differential transcriptome data revealed nine key candidate genes, including the ScHCT gene, encoding a crucial enzyme for lignin synthesis. Furthermore, the function of the ScHCT gene was validated inArabidopsis, which was negatively correlated with sugar content and positively correlated with lignin content. The interaction protein of ScHCT, ScABH, was screened via a yeast two-hybrid assay and further validated by point-to-point Y2H and bimolecular fluorescence complementation assays. The phenotype of the Arabidopsis abh mutant line revealed that loss of function of ABH resulted in a decrease of sucrose content in stem tissue. This study provides important reference information and genetic resources for sugarcane research and varietal improvement.
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Affiliation(s)
- Meiyan Chen
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
| | - Peng Liu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
| | - Ruilin An
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
| | - Xinhua He
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
| | - Peifang Zhao
- National Key Laboratory for Biological Breeding of Tropical Crops, Kunming 650221, China
- Sugarcane Research Institute, Yunnan Academy of Agricultural Sciences/Yunnan Key Laboratory of Sugarcane Genetic Improvement, Kaiyuan 661699, China
| | - Dongliang Huang
- Key Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture and Rural Affairs/Guangxi Key Laboratory of Sugarcane Genetic Improvement/Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 530007, China
| | - Xiping Yang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
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Nikhil S, Mohideen HS, Sella RN. Unveiling the Genomic Symphony: Identification Cultivar-Specific Genes and Enhanced Insights on Sweet Sorghum Genomes Through Comprehensive superTranscriptomic Analysis. J Mol Evol 2024; 92:720-743. [PMID: 39261311 DOI: 10.1007/s00239-024-10198-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 08/20/2024] [Indexed: 09/13/2024]
Abstract
Sorghum (Sorghum bicolor (L.) Moench) is a multipurpose crop grown for food, fodder, and bioenergy production. Its cultivated varieties, along with their wild counterparts, contribute to the core genetic pool. Despite the availability of several re-sequenced sorghum genomes, a variable portion of sorghum genomes is not reported during reference genome assembly and annotation. The present analysis used 223 publicly available RNA-seq datasets from seven sweet sorghum cultivars to construct superTranscriptome. This approach yielded 45,864 Representative Transcript Assemblies (RTAs) that showcased intriguing Presence/Absence Variation (PAV) across 15 published sorghum genomes. We found 301 superTranscripts were exclusive to sweet sorghum, including 58 de novo genes encoded core and linker histones, zinc finger domains, glucosyl transferases, cellulose synthase, etc. The superTranscriptome added 2,802 new protein-coding genes to the Sweet Sorghum Reference Genome (SSRG), of which 559 code for different transcription factors (TFs). Our analysis revealed that MULE-like transposases were abundant in the sweet sorghum genome and could play a hidden role in the evolution of sweet sorghum. We observed large deletions in the D locus and terminal deletions in four other NAC encoding loci in the SSRG compared to its wild progenitor (353) suggesting non-functional NAC genes contributed to trait development in sweet sorghum. Moreover, superTranscript-based methods for Differential Exon Usage (DEU) and Differential Gene Expression (DGE) analyses were more accurate than those based on the SSRG. This study demonstrates that the superTranscriptome can enhance our understanding of fundamental sorghum mechanisms, improve genome annotations, and potentially even replace the reference genome.
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Affiliation(s)
- Shinde Nikhil
- Membrane Protein Interaction Lab, Department of Genetic Engineering, SRM Institute of Science and Technology, Chengalpattu District, Tamil Nadu, 603203, India
| | - Habeeb Shaikh Mohideen
- Entomoinformatics Lab, Department of Genetic Engineering, SRM Institute of Science and Technology, Chengalpattu District, Tamil Nadu, 603203, India
| | - Raja Natesan Sella
- Membrane Protein Interaction Lab, Department of Genetic Engineering, SRM Institute of Science and Technology, Chengalpattu District, Tamil Nadu, 603203, India.
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Zhu XT, Sanz-Jimenez P, Ning XT, Tahir Ul Qamar M, Chen LL. Direct RNA sequencing in plants: Practical applications and future perspectives. PLANT COMMUNICATIONS 2024; 5:101064. [PMID: 39155503 PMCID: PMC11589328 DOI: 10.1016/j.xplc.2024.101064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 07/17/2024] [Accepted: 08/14/2024] [Indexed: 08/20/2024]
Abstract
The transcriptome serves as a bridge that links genomic variation to phenotypic diversity. A vast number of studies using next-generation RNA sequencing (RNA-seq) over the last 2 decades have emphasized the essential roles of the plant transcriptome in response to developmental and environmental conditions, providing numerous insights into the dynamic changes, evolutionary traces, and elaborate regulation of the plant transcriptome. With substantial improvement in accuracy and throughput, direct RNA sequencing (DRS) has emerged as a new and powerful sequencing platform for precise detection of native and full-length transcripts, overcoming many limitations such as read length and PCR bias that are inherent to short-read RNA-seq. Here, we review recent advances in dissecting the complexity and diversity of plant transcriptomes using DRS as the main technological approach, covering many aspects of RNA metabolism, including novel isoforms, poly(A) tails, and RNA modification, and we propose a comprehensive workflow for processing of plant DRS data. Many challenges to the application of DRS in plants, such as the need for machine learning tools tailored to plant transcriptomes, remain to be overcome, and together we outline future biological questions that can be addressed by DRS, such as allele-specific RNA modification. This technology provides convenient support on which the connection of distinct RNA features is tightly built, sustainably refining our understanding of the biological functions of the plant transcriptome.
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Affiliation(s)
- Xi-Tong Zhu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, College of Life Science and Technology, Guangxi University, Nanning 530004, China.
| | - Pablo Sanz-Jimenez
- National Key Laboratory of Crop Genetic Improvement, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiao-Tong Ning
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, College of Life Science and Technology, Guangxi University, Nanning 530004, China
| | - Muhammad Tahir Ul Qamar
- Integrative Omics and Molecular Modeling Laboratory, Department of Bioinformatics and Biotechnology, Government College University Faisalabad (GCUF), Faisalabad 38000, Pakistan
| | - Ling-Ling Chen
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, College of Life Science and Technology, Guangxi University, Nanning 530004, China.
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Wu H, Liu X, Zong Y, Yang L, Wang J, Tong C, Li H. Leaf morphology related genes revealed by integrating Pan-transcriptome, GWAS and eQTL analyses in a Liriodendron population. PHYSIOLOGIA PLANTARUM 2024; 176:e14392. [PMID: 38887911 DOI: 10.1111/ppl.14392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 05/15/2024] [Accepted: 05/28/2024] [Indexed: 06/20/2024]
Abstract
Leaf plays an indispensable role in plant development and growth. Although many known genes related to leaf morphology development have been identified, elucidating the complex genetic basis of leaf morphological traits remains a challenge. Liriodendron plants are common ornamental trees due to their unique leaf shapes, while the molecular mechanism underlying Liriodendron leaf morphogenesis has remained unknown. Herein, we firstly constructed a population-level pan-transcriptome of Liriodendron from 81 accessions to explore the expression presence or absence variations (ePAVs), global expression differences at the population level, as well as differentially expressed genes (DEGs) between the Liriodendron chinense and Liriodendron tulipifera accessions. Subsequently, we integrated a genome-wide association study (GWAS), expression quantitative trait loci (eQTL), and transcriptome-wide association study (TWAS) to identify candidate genes related to leaf morphology. Through GWAS analysis, we identified 18 and 17 significant allelic loci in the leaf size and leaf shape modules, respectively. In addition, we discerned 16 candidate genes in relation to leaf morphological traits via TWAS. Further, integrating the co-localization results of GWAS and eQTL, we determined two regulatory hotspot regions, hot88 and hot758, related to leaf size and leaf shape, respectively. Finally, co-expression analysis, eQTL, and linkage mapping together demonstrated that Lchi_4g10795 regulate their own expression levels through cis-eQTL to affect the expression of downstream genes and cooperatively participate in the development of Liriodendron leaf morphology. These findings will improve our understanding of the molecular regulatory mechanism of Liriodendron leaf morphogenesis and will also accelerate molecular breeding of Liriodendron.
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Affiliation(s)
- Hainan Wu
- State Key Laboratory of Tree Genetics and Breeding, Nanjing Forestry University, Nanjing, China
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China
| | - Xiao Liu
- State Key Laboratory of Tree Genetics and Breeding, Nanjing Forestry University, Nanjing, China
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China
| | - Yaxian Zong
- State Key Laboratory of Tree Genetics and Breeding, Nanjing Forestry University, Nanjing, China
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China
| | - Lichun Yang
- State Key Laboratory of Tree Genetics and Breeding, Nanjing Forestry University, Nanjing, China
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China
| | - Jing Wang
- State Key Laboratory of Tree Genetics and Breeding, Nanjing Forestry University, Nanjing, China
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China
| | - Chunfa Tong
- State Key Laboratory of Tree Genetics and Breeding, Nanjing Forestry University, Nanjing, China
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China
| | - Huogen Li
- State Key Laboratory of Tree Genetics and Breeding, Nanjing Forestry University, Nanjing, China
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China
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Sarkar B, Varalaxmi Y, Vanaja M, RaviKumar N, Prabhakar M, Yadav SK, Maheswari M, Singh VK. Mapping of QTLs for morphophysiological and yield traits under water-deficit stress and well-watered conditions in maize. FRONTIERS IN PLANT SCIENCE 2023; 14:1124619. [PMID: 37223807 PMCID: PMC10200936 DOI: 10.3389/fpls.2023.1124619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 03/27/2023] [Indexed: 05/25/2023]
Abstract
Maize productivity is significantly impacted by drought; therefore, improvement of drought tolerance is a critical goal in maize breeding. To achieve this, a better understanding of the genetic basis of drought tolerance is necessary. Our study aimed to identify genomic regions associated with drought tolerance-related traits by phenotyping a mapping population of recombinant inbred lines (RILs) for two seasons under well-watered (WW) and water-deficit (WD) conditions. We also used single nucleotide polymorphism (SNP) genotyping through genotyping-by-sequencing to map these regions and attempted to identify candidate genes responsible for the observed phenotypic variation. Phenotyping of the RILs population revealed significant variability in most of the traits, with normal frequency distributions, indicating their polygenic nature. We generated a linkage map using 1,241 polymorphic SNPs distributed over 10 chromosomes (chrs), covering a total genetic distance of 5,471.55 cM. We identified 27 quantitative trait loci (QTLs) associated with various morphophysiological and yield-related traits, with 13 QTLs identified under WW conditions and 12 under WD conditions. We found one common major QTL (qCW2-1) for cob weight and a minor QTL (qCH1-1) for cob height that were consistently identified under both water regimes. We also detected one major and one minor QTL for the Normalized Difference Vegetation Index (NDVI) trait under WD conditions on chr 2, bin 2.10. Furthermore, we identified one major QTL (qCH1-2) and one minor QTL (qCH1-1) on chr 1 that were located at different genomic positions to those identified in earlier studies. We found co-localized QTLs for stomatal conductance and grain yield on chr 6 (qgs6-2 and qGY6-1), while co-localized QTLs for stomatal conductance and transpiration rate were identified on chr 7 (qgs7-1 and qTR7-1). We also attempted to identify the candidate genes responsible for the observed phenotypic variation; our analysis revealed that the major candidate genes associated with QTLs detected under water deficit conditions were related to growth and development, senescence, abscisic acid (ABA) signaling, signal transduction, and transporter activity in stress tolerance. The QTL regions identified in this study may be useful in designing markers that can be utilized in marker-assisted selection breeding. In addition, the putative candidate genes can be isolated and functionally characterized so that their role in imparting drought tolerance can be more fully understood.
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Liu C, Wang YG. Does one subgenome become dominant in the formation and evolution of a polyploid? ANNALS OF BOTANY 2023; 131:11-16. [PMID: 35291007 PMCID: PMC9904339 DOI: 10.1093/aob/mcac024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 03/15/2022] [Indexed: 06/02/2023]
Abstract
BACKGROUND Polyploids are common in flowering plants and they tend to have more expanded ranges of distributions than their diploid progenitors. Possible mechanisms underlying polyploid success have been intensively investigated. Previous studies showed that polyploidy generates novel changes and that subgenomes in allopolyploid species often differ in gene number, gene expression levels and levels of epigenetic alteration. It is widely believed that such differences are the results of conflicts among the subgenomes. These differences have been treated by some as subgenome dominance, and it is claimed that the magnitude of subgenome dominance increases in polyploid evolution. SCOPE In addition to changes which occurred during evolution, differences between subgenomes of a polyploid species may also be affected by differences between the diploid donors and changes which occurred during polyploidization. The variable genome components in many plant species are extensive, which would result in exaggerated differences between a subgenome and its progenitor when a single genotype or a small number of genotypes are used to represent a polyploid or its donors. When artificially resynthesized polyploids are used as surrogates for newly formed genotypes which have not been exposed to evolutionary selection, differences between diploid genotypes available today and those involved in the formation of the natural polyploid genotypes must also be considered. CONCLUSIONS Contrary to the now widely held views that subgenome biases in polyploids are the results of conflicts among the subgenomes and that one of the parental subgenomes generally retains more genes which are more highly expressed, available results show that subgenome biases mainly reflect legacy from the progenitors and that they can be detected before the completion of polyploidization events. Further, there is no convincing evidence that the magnitudes of subgenome biases have significantly changed during evolution for any of the allopolyploid species assessed.
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Affiliation(s)
| | - You-Gan Wang
- Science and Engineering Facility, Queensland University of Technology, Brisbane, Queensland, Australia
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9
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Rowland BE, Henriquez MA, Nilsen KT, Subramaniam R, Walkowiak S. Unraveling Plant-Pathogen Interactions in Cereals Using RNA-seq. Methods Mol Biol 2023; 2659:103-118. [PMID: 37249889 DOI: 10.1007/978-1-0716-3159-1_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Over the past two decades, there have been significant advancements in the realm of transcriptomics, or the study of genes and their expression. Modern RNA sequencing technologies and high-performance computing are creating a "big data" revolution that provides new opportunities to explore the interactions between cereals and pathogens that affect grain yield and food safety. These data are being used to annotate genes and gene variants, as well as identify differentially expressed genes and create global gene co-expression networks. Moreover, these data can unravel the complex interactions between pathogen and host and identify genes and pathways involved in these interactions. This information can then be used for disease mitigation and the development of crops with superior resistance.
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Affiliation(s)
- Bronwyn E Rowland
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
| | - Maria Antonia Henriquez
- Morden Research and Development Centre, Agriculture and Agri-Food Canada, Morden, MB, Canada
| | - Kirby T Nilsen
- Brandon Research and Development Centre, Agriculture and Agri-Food Canada, Brandon, MB, Canada.
| | - Rajagopal Subramaniam
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada.
| | - Sean Walkowiak
- Grain Research Laboratory, Canadian Grain Commission, Winnipeg, MB, Canada.
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10
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Gui S, Wei W, Jiang C, Luo J, Chen L, Wu S, Li W, Wang Y, Li S, Yang N, Li Q, Fernie AR, Yan J. A pan-Zea genome map for enhancing maize improvement. Genome Biol 2022; 23:178. [PMID: 35999561 PMCID: PMC9396798 DOI: 10.1186/s13059-022-02742-7] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 07/27/2022] [Indexed: 12/22/2022] Open
Abstract
Background Maize (Zea mays L.) is at the vanguard facing the upcoming breeding challenges. However, both a super pan-genome for the Zea genus and a comprehensive genetic variation map for maize breeding are still lacking. Results Here, we construct an approximately 6.71-Gb pan-Zea genome that contains around 4.57-Gb non-B73 reference sequences from fragmented de novo assemblies of 721 pan-Zea individuals. We annotate a total of 58,944 pan-Zea genes and find around 44.34% of them are dispensable in the pan-Zea population. Moreover, 255,821 common structural variations are identified and genotyped in a maize association mapping panel. Further analyses reveal gene presence/absence variants and their potential roles during domestication of maize. Combining genetic analyses with multi-omics data, we demonstrate how structural variants are associated with complex agronomic traits. Conclusions Our results highlight the underexplored role of the pan-Zea genome and structural variations to further understand domestication of maize and explore their potential utilization in crop improvement. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-022-02742-7.
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Affiliation(s)
- Songtao Gui
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Wenjie Wei
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Chenglin Jiang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Jingyun Luo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Lu Chen
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Shenshen Wu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Wenqiang Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Yuebin Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Shuyan Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Ning Yang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.,Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Qing Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.,Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Alisdair R Fernie
- Department of Molecular Physiology, Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476, Potsdam, Golm, Germany
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China. .,Hubei Hongshan Laboratory, Wuhan, 430070, China.
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11
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Guo W, Coulter M, Waugh R, Zhang R. The value of genotype-specific reference for transcriptome analyses in barley. Life Sci Alliance 2022; 5:e202101255. [PMID: 35459738 PMCID: PMC9034525 DOI: 10.26508/lsa.202101255] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 04/10/2022] [Accepted: 04/11/2022] [Indexed: 12/31/2022] Open
Abstract
It is increasingly apparent that although different genotypes within a species share "core" genes, they also contain variable numbers of "specific" genes and different structures of "core" genes that are only present in a subset of individuals. Using a common reference genome may thus lead to a loss of genotype-specific information in the assembled Reference Transcript Dataset (RTD) and the generation of erroneous, incomplete or misleading transcriptomics analysis results. In this study, we assembled genotype-specific RTD (sRTD) and common reference-based RTD (cRTD) from RNA-seq data of cultivated Barke and Morex barley, respectively. Our quantitative evaluation showed that the sRTD has a significantly higher diversity of transcripts and alternative splicing events, whereas the cRTD missed 40% of transcripts present in the sRTD and it only has ∼70% accurate transcript assemblies. We found that the sRTD is more accurate for transcript quantification as well as differential expression analysis. However, gene-level quantification is less affected, which may be a reasonable compromise when a high-quality genotype-specific reference is not available.
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Affiliation(s)
- Wenbin Guo
- Information and Computational Sciences, James Hutton Institute, Dundee, UK
| | - Max Coulter
- Plant Sciences Division, School of Life Sciences, University of Dundee at The James Hutton Institute, Dundee, UK
| | - Robbie Waugh
- Plant Sciences Division, School of Life Sciences, University of Dundee at The James Hutton Institute, Dundee, UK
- Cell and Molecular Sciences, James Hutton Institute, Dundee, UK
| | - Runxuan Zhang
- Information and Computational Sciences, James Hutton Institute, Dundee, UK
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12
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Nanni AV, Morse AM, Newman JRB, Choquette NE, Wedow JM, Liu Z, Leakey ADB, Conesa A, Ainsworth EA, McIntyre LM. Variation in leaf transcriptome responses to elevated ozone corresponds with physiological sensitivity to ozone across maize inbred lines. Genetics 2022; 221:iyac080. [PMID: 35579358 PMCID: PMC9339315 DOI: 10.1093/genetics/iyac080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 04/27/2022] [Indexed: 11/13/2022] Open
Abstract
We examine the impact of sustained elevated ozone concentration on the leaf transcriptome of 5 diverse maize inbred genotypes, which vary in physiological sensitivity to ozone (B73, Mo17, Hp301, C123, and NC338), using long reads to assemble transcripts and short reads to quantify expression of these transcripts. More than 99% of the long reads, 99% of the assembled transcripts, and 97% of the short reads map to both B73 and Mo17 reference genomes. Approximately 95% of the genes with assembled transcripts belong to known B73-Mo17 syntenic loci and 94% of genes with assembled transcripts are present in all temperate lines in the nested association mapping pan-genome. While there is limited evidence for alternative splicing in response to ozone stress, there is a difference in the magnitude of differential expression among the 5 genotypes. The transcriptional response to sustained ozone stress in the ozone resistant B73 genotype (151 genes) was modest, while more than 3,300 genes were significantly differentially expressed in the more sensitive NC338 genotype. There is the potential for tandem duplication in 30% of genes with assembled transcripts, but there is no obvious association between potential tandem duplication and differential expression. Genes with a common response across the 5 genotypes (83 genes) were associated with photosynthesis, in particular photosystem I. The functional annotation of genes not differentially expressed in B73 but responsive in the other 4 genotypes (789) identifies reactive oxygen species. This suggests that B73 has a different response to long-term ozone exposure than the other 4 genotypes. The relative magnitude of the genotypic response to ozone, and the enrichment analyses are consistent regardless of whether aligning short reads to: long read assembled transcripts; the B73 reference; the Mo17 reference. We find that prolonged ozone exposure directly impacts the photosynthetic machinery of the leaf.
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Affiliation(s)
- Adalena V Nanni
- Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL 32611, USA
- Genetics Institute, University of Florida, Gainesville, FL 32611, USA
| | - Alison M Morse
- Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL 32611, USA
- Genetics Institute, University of Florida, Gainesville, FL 32611, USA
| | - Jeremy R B Newman
- Genetics Institute, University of Florida, Gainesville, FL 32611, USA
- Department of Pathology, University of Florida, Gainesville, FL 32611, USA
| | - Nicole E Choquette
- Department of Plant Biology, Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Department of Crop Sciences, Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Jessica M Wedow
- Department of Plant Biology, Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Department of Crop Sciences, Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Zihao Liu
- Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL 32611, USA
- Genetics Institute, University of Florida, Gainesville, FL 32611, USA
| | - Andrew D B Leakey
- Department of Plant Biology, Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Department of Crop Sciences, Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Ana Conesa
- Department of Cell and Microbial Sciences, University of Florida, Gainesville, FL 32611, USA
- Institute for Integrative Systems Biology, Spanish National Research Council, 46980 Paterna, Spain
| | - Elizabeth A Ainsworth
- Department of Plant Biology, Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Department of Crop Sciences, Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- USDA ARS Global Change and Photosynthesis Research Unit, Urbana, IL 61801, USA
| | - Lauren M McIntyre
- Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL 32611, USA
- Genetics Institute, University of Florida, Gainesville, FL 32611, USA
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13
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Baldauf JA, Liu M, Vedder L, Yu P, Piepho HP, Schoof H, Nettleton D, Hochholdinger F. Single-parent expression complementation contributes to phenotypic heterosis in maize hybrids. PLANT PHYSIOLOGY 2022; 189:1625-1638. [PMID: 35522211 PMCID: PMC9237695 DOI: 10.1093/plphys/kiac180] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 03/23/2022] [Indexed: 06/14/2023]
Abstract
The dominance model of heterosis explains the superior performance of F1-hybrids via the complementation of deleterious alleles by beneficial alleles in many genes. Genes active in one parent but inactive in the second lead to single-parent expression (SPE) complementation in maize (Zea mays L.) hybrids. In this study, SPE complementation resulted in approximately 700 additionally active genes in different tissues of genetically diverse maize hybrids on average. We established that the number of SPE genes is significantly associated with mid-parent heterosis (MPH) for all surveyed phenotypic traits. In addition, we highlighted that maternally (SPE_B) and paternally (SPE_X) active SPE genes enriched in gene co-expression modules are highly correlated within each SPE type but separated between these two SPE types. While SPE_B-enriched co-expression modules are positively correlated with phenotypic traits, SPE_X-enriched modules displayed a negative correlation. Gene ontology term enrichment analyses indicated that SPE_B patterns are associated with growth and development, whereas SPE_X patterns are enriched in defense and stress response. In summary, these results link the degree of phenotypic MPH to the prevalence of gene expression complementation observed by SPE, supporting the notion that hybrids benefit from SPE complementation via its role in coordinating maize development in fluctuating environments.
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Affiliation(s)
- Jutta A Baldauf
- Institute of Crop Science and Resource Conservation, Crop Functional Genomics, University of Bonn, 53113 Bonn, Germany
| | | | - Lucia Vedder
- Institute of Crop Science and Resource Conservation, Crop Bioinformatics, University of Bonn, 53115 Bonn, Germany
| | - Peng Yu
- Emmy Noether Group Root Functional Biology, Institute of Crop Science and Resource Conservation, University of Bonn, 53113 Bonn, Germany
| | - Hans-Peter Piepho
- Institute of Crop Science, Biostatistics Unit, University of Hohenheim, 70599 Stuttgart, Germany
| | - Heiko Schoof
- Institute of Crop Science and Resource Conservation, Crop Bioinformatics, University of Bonn, 53115 Bonn, Germany
| | - Dan Nettleton
- Department of Statistics, Iowa State University, Ames, Iowa 50011-1210, USA
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14
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Huang YS, Lin CY. Stimulatory Effects of Androgens on Eel Primary Ovarian Development - from Phenotypes to Genotypes. Vet Med Sci 2022. [DOI: 10.5772/intechopen.99582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Androgens stimulate primary ovarian development in Vertebrate. Japanese eels underwent operation to sample the pre- and post-treated ovarian tissues from the same individual. Ovarian phenotypic or genotypic data were mined in a pair. A correlation between the initial ovarian status (determined by kernel density estimation (KDE), presented as a probability density of oocyte size) and the consequence of androgen (17MT) treatment (change in ovary) has been showed. The initial ovarian status appeared to be important to influence ovarian androgenic sensitivity. The initial ovary was important to the outcomes of androgen treatments, and ePAV (expression presence-absence variation) is existing in Japanese eel by analyze DEGs; core, unique, or accessory genes were identified, the sensitivities of initial ovaries were correlated with their gene expression profiles. We speculated the importance of genetic differential expression on the variations of phenotypes by 17MT, and transcriptomic approach seems to allow extracting multiple layers of genomic data.
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15
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Danilevicz MF, Gill M, Anderson R, Batley J, Bennamoun M, Bayer PE, Edwards D. Plant Genotype to Phenotype Prediction Using Machine Learning. Front Genet 2022; 13:822173. [PMID: 35664329 PMCID: PMC9159391 DOI: 10.3389/fgene.2022.822173] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 03/07/2022] [Indexed: 12/13/2022] Open
Abstract
Genomic prediction tools support crop breeding based on statistical methods, such as the genomic best linear unbiased prediction (GBLUP). However, these tools are not designed to capture non-linear relationships within multi-dimensional datasets, or deal with high dimension datasets such as imagery collected by unmanned aerial vehicles. Machine learning (ML) algorithms have the potential to surpass the prediction accuracy of current tools used for genotype to phenotype prediction, due to their capacity to autonomously extract data features and represent their relationships at multiple levels of abstraction. This review addresses the challenges of applying statistical and machine learning methods for predicting phenotypic traits based on genetic markers, environment data, and imagery for crop breeding. We present the advantages and disadvantages of explainable model structures, discuss the potential of machine learning models for genotype to phenotype prediction in crop breeding, and the challenges, including the scarcity of high-quality datasets, inconsistent metadata annotation and the requirements of ML models.
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Affiliation(s)
- Monica F. Danilevicz
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA, Australia
| | - Mitchell Gill
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA, Australia
| | - Robyn Anderson
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA, Australia
| | - Jacqueline Batley
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA, Australia
| | - Mohammed Bennamoun
- School of Physics, Mathematics and Computing, University of Western Australia, Perth, WA, Australia
| | - Philipp E. Bayer
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA, Australia
| | - David Edwards
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA, Australia
- *Correspondence: David Edwards,
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16
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Wu PY, Stich B, Weisweiler M, Shrestha A, Erban A, Westhoff P, Inghelandt DV. Improvement of prediction ability by integrating multi-omic datasets in barley. BMC Genomics 2022; 23:200. [PMID: 35279073 PMCID: PMC8917753 DOI: 10.1186/s12864-022-08337-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 01/20/2022] [Indexed: 11/10/2022] Open
Abstract
Background Genomic prediction (GP) based on single nucleotide polymorphisms (SNP) has become a broadly used tool to increase the gain of selection in plant breeding. However, using predictors that are biologically closer to the phenotypes such as transcriptome and metabolome may increase the prediction ability in GP. The objectives of this study were to (i) assess the prediction ability for three yield-related phenotypic traits using different omic datasets as single predictors compared to a SNP array, where these omic datasets included different types of sequence variants (full-SV, deleterious-dSV, and tolerant-tSV), different types of transcriptome (expression presence/absence variation-ePAV, gene expression-GE, and transcript expression-TE) sampled from two tissues, leaf and seedling, and metabolites (M); (ii) investigate the improvement in prediction ability when combining multiple omic datasets information to predict phenotypic variation in barley breeding programs; (iii) explore the predictive performance when using SV, GE, and ePAV from simulated 3’end mRNA sequencing of different lengths as predictors. Results The prediction ability from genomic best linear unbiased prediction (GBLUP) for the three traits using dSV information was higher than when using tSV, all SV information, or the SNP array. Any predictors from the transcriptome (GE, TE, as well as ePAV) and metabolome provided higher prediction abilities compared to the SNP array and SV on average across the three traits. In addition, some (di)-similarity existed between different omic datasets, and therefore provided complementary biological perspectives to phenotypic variation. Optimal combining the information of dSV, TE, ePAV, as well as metabolites into GP models could improve the prediction ability over that of the single predictors alone. Conclusions The use of integrated omic datasets in GP model is highly recommended. Furthermore, we evaluated a cost-effective approach generating 3’end mRNA sequencing with transcriptome data extracted from seedling without losing prediction ability in comparison to the full-length mRNA sequencing, paving the path for the use of such prediction methods in commercial breeding programs. Supplementary Information The online version contains supplementary material available at (10.1186/s12864-022-08337-7).
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Hu H, Scheben A, Verpaalen B, Tirnaz S, Bayer PE, Hodel RGJ, Batley J, Soltis DE, Soltis PS, Edwards D. Amborella gene presence/absence variation is associated with abiotic stress responses that may contribute to environmental adaptation. THE NEW PHYTOLOGIST 2022; 233:1548-1555. [PMID: 34328223 PMCID: PMC9292397 DOI: 10.1111/nph.17658] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 07/26/2021] [Indexed: 05/03/2023]
Affiliation(s)
- Haifei Hu
- School of Biological Sciences and Institute of AgricultureUniversity of Western AustraliaPerthWA6009Australia
| | - Armin Scheben
- School of Biological Sciences and Institute of AgricultureUniversity of Western AustraliaPerthWA6009Australia
- Simons Center for Quantitative BiologyCold Spring Harbor LaboratoryCold Spring Harbor,NY11724USA
| | - Brent Verpaalen
- School of Biological Sciences and Institute of AgricultureUniversity of Western AustraliaPerthWA6009Australia
| | - Soodeh Tirnaz
- School of Biological Sciences and Institute of AgricultureUniversity of Western AustraliaPerthWA6009Australia
| | - Philipp E. Bayer
- School of Biological Sciences and Institute of AgricultureUniversity of Western AustraliaPerthWA6009Australia
| | - Richard G. J. Hodel
- Department of BotanyNational Museum of Natural HistorySmithsonian InstitutionWashingtonDC20013‐7012USA
| | - Jacqueline Batley
- School of Biological Sciences and Institute of AgricultureUniversity of Western AustraliaPerthWA6009Australia
| | - Douglas E. Soltis
- Department of BiologyUniversity of FloridaGainesvilleFL32611USA
- Florida Museum of Natural HistoryUniversity of FloridaGainesvilleFL32611USA
- The Genetics InstituteUniversity of FloridaGainesvilleFL32610USA
- The Biodiversity InstituteUniversity of FloridaGainesvilleFL32611USA
| | - Pamela S. Soltis
- Florida Museum of Natural HistoryUniversity of FloridaGainesvilleFL32611USA
- The Genetics InstituteUniversity of FloridaGainesvilleFL32610USA
- The Biodiversity InstituteUniversity of FloridaGainesvilleFL32611USA
| | - David Edwards
- School of Biological Sciences and Institute of AgricultureUniversity of Western AustraliaPerthWA6009Australia
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Kong W, Jiang M, Wang Y, Chen S, Zhang S, Lei W, Chai K, Wang P, Liu R, Zhang X. Pan-transcriptome assembly combined with multiple association analysis provides new insights into the regulatory network of specialized metabolites in the tea plant Camellia sinensis. HORTICULTURE RESEARCH 2022; 9:uhac100. [PMID: 35795389 PMCID: PMC9251601 DOI: 10.1093/hr/uhac100] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 04/15/2022] [Indexed: 05/07/2023]
Abstract
Specialized metabolites not only play important roles in biotic and abiotic stress adaptation of tea plants (Camellia sinensis (L.) O. Kuntze) but also contribute to the unique flavor of tea, the most important nonalcoholic beverage. However, the molecular networks and major genes that regulate specialized metabolites in tea plants are not well understood. Here, we constructed a population-level pan-transcriptome of the tea plant leaf using second-leaf transcriptome data from 134 accessions to investigate global expression differences in the population, expression presence or absence variations (ePAVs), and differentially expressed genes (DEGs) between pure Camellia sinensis var. assamica (CSA) and pure Camellia sinensis var. sinensis (CSS) accessions. Next, we used a genome-wide association study, a quantitative trait transcript study, and a transcriptome-wide association study to integrate genotypes, accumulation levels of specialized metabolites, and expression levels of pan-transcriptome genes to identify candidate regulatory genes for flavor-related metabolites and to construct a regulatory network for specialized metabolites in tea plants. The pan-transcriptome contains 30 482 expressed genes, 4940 and 5506 of which were newly annotated from a de novo transcriptome assembly without a reference and a genome reference-based assembly, respectively. DEGs and ePAVs indicated that CSA and CSS were clearly differentiated at the population transcriptome level, and they were closely related to abiotic tolerance and secondary metabolite synthesis phenotypes of CSA and CSS based on gene annotations. The regulatory network contained 212 specialized metabolites, 3843 candidate genes, and 3407 eQTLs, highlighting many pleiotropic candidate genes, candidate gene-rich eQTLs, and potential regulators of specialized metabolites. These included important transcription factors in the AP2/ERF-ERF, MYB, WD40, and bHLH families. CsTGY14G0001296, an ortholog of AtANS, appeared to be directly related to variation in proanthocyanins in the tea plant population, and the CsTGY11G0002074 gene encoding F3'5'H was found to contribute to the biased distribution of catechins between pure CSAs and pure CSSs. Together, these results provide a new understanding of the metabolite diversity in tea plants and offer new insights for more effective breeding of better-flavored tea varieties.
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Affiliation(s)
- Weilong Kong
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Mengwei Jiang
- Center for Genomics and Biotechnology, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Yibin Wang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Shuai Chen
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Shengcheng Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Wenlong Lei
- Center for Genomics and Biotechnology, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Kun Chai
- Center for Genomics and Biotechnology, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Pengjie Wang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
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Pronozin AY, Bragina MK, Salina EA. Crop pangenomes. Vavilovskii Zhurnal Genet Selektsii 2021; 25:57-63. [PMID: 34901703 PMCID: PMC8629360 DOI: 10.18699/vj21.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 12/27/2020] [Accepted: 01/03/2021] [Indexed: 11/19/2022] Open
Abstract
Progress in genome sequencing, assembly and analysis allows for a deeper study of agricultural plants' chromosome structures, gene identification and annotation. The published genomes of agricultural plants proved to be a valuable tool for studing gene functions and for marker-assisted and genomic selection. However, large structural genome changes, including gene copy number variations (CNVs) and gene presence/absence variations (PAVs), prevail in crops. These genomic variations play an important role in the functional set of genes and the gene composition in individuals of the same species and provide the genetic determination of the agronomically important crops properties. A high degree of genomic variation observed indicates that single reference genomes do not represent the diversity within a species, leading to the pangenome concept. The pangenome represents information about all genes in a taxon: those that are common to all taxon members and those that are variable and are partially or completely specific for particular individuals. Pangenome sequencing and analysis technologies provide a large-scale study of genomic variation and resources for an evolutionary research, functional genomics and crop breeding. This review provides an analysis of agricultural plants' pangenome studies. Pangenome structural features, methods and programs for bioinformatic analysis of pangenomic data are described.
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Affiliation(s)
- A Yu Pronozin
- Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - M K Bragina
- Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Kurchatov Genomic Center of the Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - E A Salina
- Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Kurchatov Genomic Center of the Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
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20
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Huang YS, Lin CY, Cheng WC. Investigating the Transcriptomic and Expression Presence-Absence Variation Exist in Japanese Eel (Anguilla japonica), a Primitive Teleost. MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2021; 23:943-954. [PMID: 34714446 DOI: 10.1007/s10126-021-10077-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 09/28/2021] [Indexed: 06/13/2023]
Abstract
The pan-genome was defined as the complete gene set across strains, and it is built upon genes displaying presence-absence variations (PAVs); the pan-transcriptome is defined by recalling the pan-genome. Indeed, a PAV is reflected from the expression presence-absence variation (ePAV). In this study, treated with androgen, eels, which are a primitive fish from the basal lineage of Teleost, with different ovarian developments were chosen and submitted to RAN-sequencing. Transcriptomes were the assembly against eel genome scaffolds; a pair was the unit (the same eel before and after treatment) to analyze DEGs (differentially expressed genes); the core, unique, or accessory genes were identified, and the list of DEGs was analyzed to investigate ePAV. The results suggest that there was ePAV in Japanese eel, and the ePAV of eel was analyzed by pathway enrichment. These results signify the importance of genetic differential expression on the variations of phenotypes by androgen, and a transcriptomic approach appears to enable extracting multiple layers of genomic data.
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Affiliation(s)
- Yung-Sen Huang
- Department of Life Science, National University of Kaohsiung, Kaohsiung University Road, Nan Tzu Dist, No.700, 811, Kaohsiung, Taiwan.
| | - Chung-Yen Lin
- Institute of Information Science, Academia Sinica, Nankang Dist, No. 128 Academia Road, section 2, 115, Taipei, Taiwan
| | - Wen-Chih Cheng
- Institute of Information Science, Academia Sinica, Nankang Dist, No. 128 Academia Road, section 2, 115, Taipei, Taiwan
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21
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Chen S, Ren C, Zhai J, Yu J, Zhao X, Li Z, Zhang T, Ma W, Han Z, Ma C. CAFU: a Galaxy framework for exploring unmapped RNA-Seq data. Brief Bioinform 2021; 21:676-686. [PMID: 30815667 PMCID: PMC7299299 DOI: 10.1093/bib/bbz018] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Revised: 01/23/2019] [Accepted: 01/27/2019] [Indexed: 12/13/2022] Open
Abstract
A widely used approach in transcriptome analysis is the alignment of short reads to a reference genome. However, owing to the deficiencies of specially designed analytical systems, short reads unmapped to the genome sequence are usually ignored, resulting in the loss of significant biological information and insights. To fill this gap, we present Comprehensive Assembly and Functional annotation of Unmapped RNA-Seq data (CAFU), a Galaxy-based framework that can facilitate the large-scale analysis of unmapped RNA sequencing (RNA-Seq) reads from single- and mixed-species samples. By taking advantage of machine learning techniques, CAFU addresses the issue of accurately identifying the species origin of transcripts assembled using unmapped reads from mixed-species samples. CAFU also represents an innovation in that it provides a comprehensive collection of functions required for transcript confidence evaluation, coding potential calculation, sequence and expression characterization and function annotation. These functions and their dependencies have been integrated into a Galaxy framework that provides access to CAFU via a user-friendly interface, dramatically simplifying complex exploration tasks involving unmapped RNA-Seq reads. CAFU has been validated with RNA-Seq data sets from wheat and Zea mays (maize) samples. CAFU is freely available via GitHub: https://github.com/cma2015/CAFU.
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Affiliation(s)
- Siyuan Chen
- State Key Laboratory of Crop Stress Biology for Arid Areas, Center of Bioinformatics, College of Life Sciences, Northwest Agriculture and Forestry University
| | - Chengzhi Ren
- State Key Laboratory of Crop Stress Biology for Arid Areas, Center of Bioinformatics, College of Life Sciences, Northwest Agriculture and Forestry University
| | - Jingjing Zhai
- State Key Laboratory of Crop Stress Biology for Arid Areas, Center of Bioinformatics, College of Life Sciences, Northwest Agriculture and Forestry University
| | - Jiantao Yu
- College of Information Engineering, Northwest Agriculture and Forestry University
| | - Xuyang Zhao
- College of Information Engineering, Northwest Agriculture and Forestry University
| | - Zelong Li
- State Key Laboratory of Crop Stress Biology for Arid Areas, Center of Bioinformatics, College of Life Sciences, Northwest Agriculture and Forestry University
| | - Ting Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, Center of Bioinformatics, College of Life Sciences, Northwest Agriculture and Forestry University
| | - Wenlong Ma
- State Key Laboratory of Crop Stress Biology for Arid Areas, Center of Bioinformatics, College of Life Sciences, Northwest Agriculture and Forestry University
| | - Zhaoxue Han
- State Key Laboratory of Crop Stress Biology for Arid Areas, Center of Bioinformatics, College of Life Sciences, Northwest Agriculture and Forestry University
| | - Chuang Ma
- State Key Laboratory of Crop Stress Biology for Arid Areas, Center of Bioinformatics, College of Life Sciences, Northwest Agriculture and Forestry University
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22
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Hufford MB, Seetharam AS, Woodhouse MR, Chougule KM, Ou S, Liu J, Ricci WA, Guo T, Olson A, Qiu Y, Della Coletta R, Tittes S, Hudson AI, Marand AP, Wei S, Lu Z, Wang B, Tello-Ruiz MK, Piri RD, Wang N, Kim DW, Zeng Y, O'Connor CH, Li X, Gilbert AM, Baggs E, Krasileva KV, Portwood JL, Cannon EKS, Andorf CM, Manchanda N, Snodgrass SJ, Hufnagel DE, Jiang Q, Pedersen S, Syring ML, Kudrna DA, Llaca V, Fengler K, Schmitz RJ, Ross-Ibarra J, Yu J, Gent JI, Hirsch CN, Ware D, Dawe RK. De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes. Science 2021; 373:655-662. [PMID: 34353948 PMCID: PMC8733867 DOI: 10.1126/science.abg5289] [Citation(s) in RCA: 327] [Impact Index Per Article: 81.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 06/24/2021] [Indexed: 12/24/2022]
Abstract
We report de novo genome assemblies, transcriptomes, annotations, and methylomes for the 26 inbreds that serve as the founders for the maize nested association mapping population. The number of pan-genes in these diverse genomes exceeds 103,000, with approximately a third found across all genotypes. The results demonstrate that the ancient tetraploid character of maize continues to degrade by fractionation to the present day. Excellent contiguity over repeat arrays and complete annotation of centromeres revealed additional variation in major cytological landmarks. We show that combining structural variation with single-nucleotide polymorphisms can improve the power of quantitative mapping studies. We also document variation at the level of DNA methylation and demonstrate that unmethylated regions are enriched for cis-regulatory elements that contribute to phenotypic variation.
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Affiliation(s)
- Matthew B Hufford
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Arun S Seetharam
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
- Genome Informatics Facility, Iowa State University, Ames, IA 50011, USA
| | - Margaret R Woodhouse
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | | | - Shujun Ou
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Jianing Liu
- Department of Genetics, University of Georgia, Athens, GA 30602, USA
| | - William A Ricci
- Department of Plant Biology, University of Georgia, Athens, GA 30602, USA
| | - Tingting Guo
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
| | - Andrew Olson
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Yinjie Qiu
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Rafael Della Coletta
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Silas Tittes
- Center for Population Biology, University of California, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
| | - Asher I Hudson
- Center for Population Biology, University of California, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
| | | | - Sharon Wei
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Zhenyuan Lu
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Bo Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | | | - Rebecca D Piri
- Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
| | - Na Wang
- Department of Plant Biology, University of Georgia, Athens, GA 30602, USA
| | - Dong Won Kim
- Department of Plant Biology, University of Georgia, Athens, GA 30602, USA
| | - Yibing Zeng
- Department of Genetics, University of Georgia, Athens, GA 30602, USA
| | - Christine H O'Connor
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
- Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN 55108, USA
| | - Xianran Li
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
| | - Amanda M Gilbert
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Erin Baggs
- Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA
| | - Ksenia V Krasileva
- Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA
| | - John L Portwood
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | - Ethalinda K S Cannon
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | - Carson M Andorf
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | - Nancy Manchanda
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Samantha J Snodgrass
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - David E Hufnagel
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
- Virus and Prion Research Unit, National Animal Disease Center, USDA-ARS, Ames, IA, 50010, USA
| | - Qiuhan Jiang
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Sarah Pedersen
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Michael L Syring
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - David A Kudrna
- Arizona Genomics Institute, School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA
| | | | | | - Robert J Schmitz
- Department of Genetics, University of Georgia, Athens, GA 30602, USA
| | - Jeffrey Ross-Ibarra
- Center for Population Biology, University of California, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
- Genome Center, University of California, Davis, CA 95616, USA
| | - Jianming Yu
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
| | - Jonathan I Gent
- Department of Plant Biology, University of Georgia, Athens, GA 30602, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Doreen Ware
- USDA-ARS NAA Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, Ithaca, NY 14853, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - R Kelly Dawe
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA.
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23
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Ye X, Hu H, Zhou H, Jiang Y, Gao S, Yuan Z, Stiller J, Li C, Chen G, Liu Y, Wei Y, Zheng YL, Wang YG, Liu C. Differences between diploid donors are the main contributing factor for subgenome asymmetry measured in either gene ratio or relative diversity in allopolyploids. Genome 2021; 64:847-856. [PMID: 33661713 DOI: 10.1139/gen-2020-0024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Subgenome asymmetry (SA) has routinely been attributed to different responses between the subgenomes of a polyploid to various stimuli during evolution. Here, we compared subgenome differences in gene ratio and relative diversity between artificial and natural genotypes of several allopolyploid species. Surprisingly, consistent differences were not detected between these two types of polyploid genotypes, although they differ in times exposed to evolutionary selection. The estimated ratio of shared genes between a subgenome and its diploid donor was invariably higher for the artificial allopolyploid genotypes than those for the natural genotypes, which is expected as it is now well-known that many genes in a species are not shared among all individuals. As the exact diploid parent for a given subgenome is unknown, the estimated ratios of shared genes for the natural genotypes would also include difference among individual genotypes of the diploid donor species. Further, we detected the presence of SA in genotypes before the completion of the polyploidization events as well as in those which were not formed via polyploidization. These results indicate that SA may, to a large degree, reflect differences between its diploid donors or that changes occurred during polyploid evolution are defined by their donor genomes.
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Affiliation(s)
- Xueling Ye
- CSIRO Agriculture and Food, St Lucia, QLD 4067, Australia.,Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu 611130, China
| | - Haiyan Hu
- CSIRO Agriculture and Food, St Lucia, QLD 4067, Australia.,College of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, Henan 453003, China
| | - Hong Zhou
- CSIRO Agriculture and Food, St Lucia, QLD 4067, Australia.,Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu 611130, China
| | - Yunfeng Jiang
- CSIRO Agriculture and Food, St Lucia, QLD 4067, Australia.,Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu 611130, China
| | - Shang Gao
- CSIRO Agriculture and Food, St Lucia, QLD 4067, Australia
| | - Zhongwei Yuan
- CSIRO Agriculture and Food, St Lucia, QLD 4067, Australia.,Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu 611130, China
| | - Jiri Stiller
- CSIRO Agriculture and Food, St Lucia, QLD 4067, Australia
| | - Chengwei Li
- College of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, Henan 453003, China
| | - Guoyue Chen
- Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu 611130, China
| | - Yaxi Liu
- Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu 611130, China
| | - Yuming Wei
- Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu 611130, China
| | - You-Liang Zheng
- Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu 611130, China
| | - You-Gan Wang
- Science and Engineering Facility, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Chunji Liu
- CSIRO Agriculture and Food, St Lucia, QLD 4067, Australia
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24
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Tian Z, Wang JW, Li J, Han B. Designing future crops: challenges and strategies for sustainable agriculture. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2021; 105:1165-1178. [PMID: 33258137 DOI: 10.1111/tpj.15107] [Citation(s) in RCA: 77] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 11/22/2020] [Accepted: 11/26/2020] [Indexed: 05/26/2023]
Abstract
Crop production is facing unprecedented challenges. Despite the fact that the food supply has significantly increased over the past half-century, ~8.9 and 14.3% people are still suffering from hunger and malnutrition, respectively. Agricultural environments are continuously threatened by a booming world population, a shortage of arable land, and rapid changes in climate. To ensure food and ecosystem security, there is a need to design future crops for sustainable agriculture development by maximizing net production and minimalizing undesirable effects on the environment. The future crops design projects, recently launched by the National Natural Science Foundation of China and Chinese Academy of Sciences (CAS), aim to develop a roadmap for rapid design of customized future crops using cutting-edge technologies in the Breeding 4.0 era. In this perspective, we first introduce the background and missions of these projects. We then outline strategies to design future crops, such as improvement of current well-cultivated crops, de novo domestication of wild species and redomestication of current cultivated crops. We further discuss how these ambitious goals can be achieved by the recent development of new integrative omics tools, advanced genome-editing tools and synthetic biology approaches. Finally, we summarize related opportunities and challenges in these projects.
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Affiliation(s)
- Zhixi Tian
- State Key Laboratory of Plant Cell and Chromosome Engineering, Innovation Academy for Seed Design, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jia-Wei Wang
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200032, China
- ShanghaiTech University, Shanghai, 200031, China
| | - Jiayang Li
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Plant Genomics, and National Center for Plant Gene Research (Beijing), Innovation Academy for Seed Design, Institute of Genetics and Developmental Biology Chinese Academy of Sciences, Beijing, 100101, China
| | - Bin Han
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200032, China
- ShanghaiTech University, Shanghai, 200031, China
- National Center for Gene Research, Shanghai, 200233, China
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25
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Monroe JG, McKay JK, Weigel D, Flood PJ. The population genomics of adaptive loss of function. Heredity (Edinb) 2021; 126:383-395. [PMID: 33574599 PMCID: PMC7878030 DOI: 10.1038/s41437-021-00403-2] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 12/28/2020] [Accepted: 01/01/2021] [Indexed: 12/23/2022] Open
Abstract
Discoveries of adaptive gene knockouts and widespread losses of complete genes have in recent years led to a major rethink of the early view that loss-of-function alleles are almost always deleterious. Today, surveys of population genomic diversity are revealing extensive loss-of-function and gene content variation, yet the adaptive significance of much of this variation remains unknown. Here we examine the evolutionary dynamics of adaptive loss of function through the lens of population genomics and consider the challenges and opportunities of studying adaptive loss-of-function alleles using population genetics models. We discuss how the theoretically expected existence of allelic heterogeneity, defined as multiple functionally analogous mutations at the same locus, has proven consistent with empirical evidence and why this impedes both the detection of selection and causal relationships with phenotypes. We then review technical progress towards new functionally explicit population genomic tools and genotype-phenotype methods to overcome these limitations. More broadly, we discuss how the challenges of studying adaptive loss of function highlight the value of classifying genomic variation in a way consistent with the functional concept of an allele from classical population genetics.
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Affiliation(s)
- J Grey Monroe
- Department of Molecular Biology, Max Planck Institute for Developmental Biology, 72076, Tübingen, Germany.
- Department of Plant Sciences, University of California Davis, Davis, CA, 95616, USA.
| | - John K McKay
- College of Agriculture, Colorado State University, Fort Collins, CO, 80523, USA
| | - Detlef Weigel
- Department of Molecular Biology, Max Planck Institute for Developmental Biology, 72076, Tübingen, Germany
| | - Pádraic J Flood
- Department of Plant Developmental Biology, Max Planck Institute for Plant Breeding Research, 50829, Cologne, Germany
- Department of Plant Breeding, Wageningen University, Wageningen, The Netherlands
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26
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Mohd Saad NS, Severn-Ellis AA, Pradhan A, Edwards D, Batley J. Genomics Armed With Diversity Leads the Way in Brassica Improvement in a Changing Global Environment. Front Genet 2021; 12:600789. [PMID: 33679880 PMCID: PMC7930750 DOI: 10.3389/fgene.2021.600789] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 01/15/2021] [Indexed: 12/14/2022] Open
Abstract
Meeting the needs of a growing world population in the face of imminent climate change is a challenge; breeding of vegetable and oilseed Brassica crops is part of the race in meeting these demands. Available genetic diversity constituting the foundation of breeding is essential in plant improvement. Elite varieties, land races, and crop wild species are important resources of useful variation and are available from existing genepools or genebanks. Conservation of diversity in genepools, genebanks, and even the wild is crucial in preventing the loss of variation for future breeding efforts. In addition, the identification of suitable parental lines and alleles is critical in ensuring the development of resilient Brassica crops. During the past two decades, an increasing number of high-quality nuclear and organellar Brassica genomes have been assembled. Whole-genome re-sequencing and the development of pan-genomes are overcoming the limitations of the single reference genome and provide the basis for further exploration. Genomic and complementary omic tools such as microarrays, transcriptomics, epigenetics, and reverse genetics facilitate the study of crop evolution, breeding histories, and the discovery of loci associated with highly sought-after agronomic traits. Furthermore, in genomic selection, predicted breeding values based on phenotype and genome-wide marker scores allow the preselection of promising genotypes, enhancing genetic gains and substantially quickening the breeding cycle. It is clear that genomics, armed with diversity, is set to lead the way in Brassica improvement; however, a multidisciplinary plant breeding approach that includes phenotype = genotype × environment × management interaction will ultimately ensure the selection of resilient Brassica varieties ready for climate change.
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Affiliation(s)
| | | | | | | | - Jacqueline Batley
- School of Biological Sciences Western Australia and UWA Institute of Agriculture, University of Western Australia, Perth, WA, Australia
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27
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Scossa F, Alseekh S, Fernie AR. Integrating multi-omics data for crop improvement. JOURNAL OF PLANT PHYSIOLOGY 2021; 257:153352. [PMID: 33360148 DOI: 10.1016/j.jplph.2020.153352] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Revised: 12/13/2020] [Accepted: 12/14/2020] [Indexed: 05/26/2023]
Abstract
Our agricultural systems are now in urgent need to secure food for a growing world population. To meet this challenge, we need a better characterization of plant genetic and phenotypic diversity. The combination of genomics, transcriptomics and metabolomics enables a deeper understanding of the mechanisms underlying the complex architecture of many phenotypic traits of agricultural relevance. We review the recent advances in plant genomics to see how these can be integrated with broad molecular profiling approaches to improve our understanding of plant phenotypic variation and inform crop breeding strategies.
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Affiliation(s)
- Federico Scossa
- Max-Planck-Institut für Molekulare Pflanzenphysiologie, 14476, Potsdam, Golm, Germany; Council for Agricultural Research and Economics (CREA), Research Centre for Genomics and Bioinformatics (CREA-GB), 00178, Rome, Italy.
| | - Saleh Alseekh
- Max-Planck-Institut für Molekulare Pflanzenphysiologie, 14476, Potsdam, Golm, Germany; Center of Plant Systems Biology and Biotechnology (CPSBB), Plovdiv, Bulgaria
| | - Alisdair R Fernie
- Max-Planck-Institut für Molekulare Pflanzenphysiologie, 14476, Potsdam, Golm, Germany; Center of Plant Systems Biology and Biotechnology (CPSBB), Plovdiv, Bulgaria.
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28
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Lu X, Wang J, Wang Y, Wen W, Zhang Y, Du J, Zhao Y, Guo X. Genome-Wide Association Study of Maize Aboveground Dry Matter Accumulation at Seedling Stage. Front Genet 2021; 11:571236. [PMID: 33519889 PMCID: PMC7838602 DOI: 10.3389/fgene.2020.571236] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 11/30/2020] [Indexed: 11/13/2022] Open
Abstract
Dry matter accumulation and partitioning during the early phases of development could significantly affect crop growth and productivity. In this study, the aboveground dry matter (DM), the DM of different organs, and partition coefficients of a maize association mapping panel of 412 inbred lines were evaluated at the third and sixth leaf stages (V3 and V6). Further, the properties of these phenotypic traits were analyzed. Genome-wide association studies (GWAS) were conducted on the total aboveground biomass and the DM of different organs. Analysis of GWAS results identified a total of 1,103 unique candidate genes annotated by 678 significant SNPs (P value < 1.28e-6). A total of 224 genes annotated by SNPs at the top five of each GWAS method and detected by multiple GWAS methods were regarded as having high reliability. Pathway enrichment analysis was also performed to explore the biological significance and functions of these candidate genes. Several biological pathways related to the regulation of seed growth, gibberellin-mediated signaling pathway, and long-day photoperiodism were enriched. The results of our study could provide new perspectives on breeding high-yielding maize varieties.
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Affiliation(s)
- Xianju Lu
- Beijing Key Laboratory of Digital Plant, Beijing Research Center for Information Technology in Agriculture, National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Jinglu Wang
- Beijing Key Laboratory of Digital Plant, Beijing Research Center for Information Technology in Agriculture, National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Yongjian Wang
- Beijing Key Laboratory of Digital Plant, Beijing Research Center for Information Technology in Agriculture, National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Weiliang Wen
- Beijing Key Laboratory of Digital Plant, Beijing Research Center for Information Technology in Agriculture, National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Ying Zhang
- Beijing Key Laboratory of Digital Plant, Beijing Research Center for Information Technology in Agriculture, National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Jianjun Du
- Beijing Key Laboratory of Digital Plant, Beijing Research Center for Information Technology in Agriculture, National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Yanxin Zhao
- Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Maize Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Xinyu Guo
- Beijing Key Laboratory of Digital Plant, Beijing Research Center for Information Technology in Agriculture, National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
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Gao S, Wu J, Stiller J, Zheng Z, Zhou M, Wang YG, Liu C. Identifying barley pan-genome sequence anchors using genetic mapping and machine learning. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:2535-2544. [PMID: 32448920 DOI: 10.1007/s00122-020-03615-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 05/16/2020] [Indexed: 06/11/2023]
Abstract
We identified 1.844 million barley pan-genome sequence anchors from 12,306 genotypes using genetic mapping and machine learning. There is increasing evidence that genes from a given crop genotype are far to cover all genes in that species; thus, building more comprehensive pan-genomes is of great importance in genetic research and breeding. Obtaining a thousand-genotype scale pan-genome using deep-sequencing data is currently impractical for species like barley which has a huge and highly repetitive genome. To this end, we attempted to identify barley pan-genome sequence anchors from a large quantity of genotype-by-sequencing (GBS) datasets by combining genetic mapping and machine learning algorithms. Based on the GBS sequences from 11,166 domesticated and 1140 wild barley genotypes, we identified 1.844 million pan-genome sequence anchors. Of them, 532,253 were identified as presence/absence variation (PAV) tags. Through aligning these PAV tags to the genome of hulless barley genotype Zangqing320, our analysis resulted in a validation of 83.6% of them from the domesticated genotypes and 88.6% from the wild barley genotypes. Association analyses against flowering time, plant height and kernel size showed that the relative importance of the PAV and non-PAV tags varied for different traits. The pan-genome sequence anchors based on GBS tags can facilitate the construction of a comprehensive pan-genome and greatly assist various genetic studies including identification of structural variation, genetic mapping and breeding in barley.
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Affiliation(s)
- Shang Gao
- Agriculture and Food, CSIRO, St Lucia, QLD, 4067, Australia
- Tasmanian Institute of Agriculture, University of Tasmania, Prospect, TAS, 7250, Australia
| | - Jinran Wu
- School of Mathematical Science, Queensland University of Technology, Brisbane, QLD, 4001, Australia
| | - Jiri Stiller
- Agriculture and Food, CSIRO, St Lucia, QLD, 4067, Australia
| | - Zhi Zheng
- Agriculture and Food, CSIRO, St Lucia, QLD, 4067, Australia
| | - Meixue Zhou
- Tasmanian Institute of Agriculture, University of Tasmania, Prospect, TAS, 7250, Australia
| | - You-Gan Wang
- School of Mathematical Science, Queensland University of Technology, Brisbane, QLD, 4001, Australia.
| | - Chunji Liu
- Agriculture and Food, CSIRO, St Lucia, QLD, 4067, Australia.
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30
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Petek M, Zagorščak M, Ramšak Ž, Sanders S, Tomaž Š, Tseng E, Zouine M, Coll A, Gruden K. Cultivar-specific transcriptome and pan-transcriptome reconstruction of tetraploid potato. Sci Data 2020; 7:249. [PMID: 32709858 PMCID: PMC7382494 DOI: 10.1038/s41597-020-00581-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Accepted: 06/19/2020] [Indexed: 01/25/2023] Open
Abstract
Although the reference genome of Solanum tuberosum Group Phureja double-monoploid (DM) clone is available, knowledge on the genetic diversity of the highly heterozygous tetraploid Group Tuberosum, representing most cultivated varieties, remains largely unexplored. This lack of knowledge hinders further progress in potato research. In conducted investigation, we first merged and manually curated the two existing partially-overlapping DM genome-based gene models, creating a union of genes in Phureja scaffold. Next, we compiled available and newly generated RNA-Seq datasets (cca. 1.5 billion reads) for three tetraploid potato genotypes (cultivar Désirée, cultivar Rywal, and breeding clone PW363) with diverse breeding pedigrees. Short-read transcriptomes were assembled using several de novo assemblers under different settings to test for optimal outcome. For cultivar Rywal, PacBio Iso-Seq full-length transcriptome sequencing was also performed. EvidentialGene redundancy-reducing pipeline complemented with in-house developed scripts was employed to produce accurate and complete cultivar-specific transcriptomes, as well as to attain the pan-transcriptome. The generated transcriptomes and pan-transcriptome represent a valuable resource for potato gene variability exploration, high-throughput omics analyses, and breeding programmes. Measurement(s) | genome • RNA • sequence_assembly • transcriptome | Technology Type(s) | digital curation • RNA sequencing • sequence assembly process | Factor Type(s) | cultivar | Sample Characteristic - Organism | Solanum tuberosum |
Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12562733
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Affiliation(s)
- Marko Petek
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia.
| | - Maja Zagorščak
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia.
| | - Živa Ramšak
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
| | - Sheri Sanders
- National Center for Genome Analysis and Support (NCGAS), Indiana University, Bloomington, USA
| | - Špela Tomaž
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia.,Jožef Stefan International Postgraduate School, Ljubljana, Slovenia
| | | | - Mohamed Zouine
- Laboratoire Génomique et Biotechnologie des Fruits, INRA-INP/ENSAT, Castanet-Tolosan, France
| | - Anna Coll
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
| | - Kristina Gruden
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
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31
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Nia AM, Khanipov K, Barnette BL, Ullrich RL, Golovko G, Emmett MR. Comparative RNA-Seq transcriptome analyses reveal dynamic time-dependent effects of 56Fe, 16O, and 28Si irradiation on the induction of murine hepatocellular carcinoma. BMC Genomics 2020; 21:453. [PMID: 32611366 PMCID: PMC7329445 DOI: 10.1186/s12864-020-06869-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Accepted: 06/24/2020] [Indexed: 01/04/2023] Open
Abstract
Background One of the health risks posed to astronauts during deep space flights is exposure to high charge, high-energy (HZE) ions (Z > 13), which can lead to the induction of hepatocellular carcinoma (HCC). However, little is known on the molecular mechanisms of HZE irradiation-induced HCC. Results We performed comparative RNA-Seq transcriptomic analyses to assess the carcinogenic effects of 600 MeV/n 56Fe (0.2 Gy), 1 GeV/n 16O (0.2 Gy), and 350 MeV/n 28Si (0.2 Gy) ions in a mouse model for irradiation-induced HCC. C3H/HeNCrl mice were subjected to total body irradiation to simulate space environment HZE-irradiation, and liver tissues were extracted at five different time points post-irradiation to investigate the time-dependent carcinogenic response at the transcriptomic level. Our data demonstrated a clear difference in the biological effects of these HZE ions, particularly immunological, such as Acute Phase Response Signaling, B Cell Receptor Signaling, IL-8 Signaling, and ROS Production in Macrophages. Also seen in this study were novel unannotated transcripts that were significantly affected by HZE. To investigate the biological functions of these novel transcripts, we used a machine learning technique known as self-organizing maps (SOMs) to characterize the transcriptome expression profiles of 60 samples (45 HZE-irradiated, 15 non-irradiated control) from liver tissues. A handful of localized modules in the maps emerged as groups of co-regulated and co-expressed transcripts. The functional context of these modules was discovered using overrepresentation analysis. We found that these spots typically contained enriched populations of transcripts related to specific immunological molecular processes (e.g., Acute Phase Response Signaling, B Cell Receptor Signaling, IL-3 Signaling), and RNA Transcription/Expression. Conclusions A large number of transcripts were found differentially expressed post-HZE irradiation. These results provide valuable information for uncovering the differences in molecular mechanisms underlying HZE specific induced HCC carcinogenesis. Additionally, a handful of novel differentially expressed unannotated transcripts were discovered for each HZE ion. Taken together, these findings may provide a better understanding of biological mechanisms underlying risks for HCC after HZE irradiation and may also have important implications for the discovery of potential countermeasures against and identification of biomarkers for HZE-induced HCC.
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Affiliation(s)
- Anna M Nia
- Biochemistry and Molecular Biology, University of Texas Medical Branch, 301 University Blvd, Galveston, TX, 77550, USA
| | - Kamil Khanipov
- Pharmacology and Toxicology, University of Texas Medical Branch, 301 University Blvd, Galveston, TX, 77550, USA
| | - Brooke L Barnette
- Biochemistry and Molecular Biology, University of Texas Medical Branch, 301 University Blvd, Galveston, TX, 77550, USA
| | - Robert L Ullrich
- The Radiation Effects Research Foundation (RERF), Hiroshima, Japan
| | - George Golovko
- Pharmacology and Toxicology, University of Texas Medical Branch, 301 University Blvd, Galveston, TX, 77550, USA
| | - Mark R Emmett
- Biochemistry and Molecular Biology, University of Texas Medical Branch, 301 University Blvd, Galveston, TX, 77550, USA. .,Pharmacology and Toxicology, University of Texas Medical Branch, 301 University Blvd, Galveston, TX, 77550, USA.
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32
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Baldauf JA, Vedder L, Schoof H, Hochholdinger F. Robust non-syntenic gene expression patterns in diverse maize hybrids during root development. JOURNAL OF EXPERIMENTAL BOTANY 2020; 71:865-876. [PMID: 31638701 DOI: 10.1093/jxb/erz452] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Accepted: 09/30/2019] [Indexed: 06/10/2023]
Abstract
Distantly related maize (Zea mays L.) inbred lines exhibit an exceptional degree of structural genomic diversity, which is probably unique among plants. This study systematically investigated the developmental and genotype-dependent regulation of the primary root transcriptomes of a genetically diverse panel of maize F1-hybrids and their parental inbred lines. While we observed substantial transcriptomic changes during primary root development, we demonstrated that hybrid-associated gene expression patterns, including differential, non-additive, and allele-specific transcriptome profiles, are particularly robust to these developmental fluctuations. For instance, differentially expressed genes with preferential expression in hybrids were highly conserved during development in comparison to their parental counterparts. Similarly, in hybrids a major proportion of non-additively expressed genes with expression levels between the parental values were particularly conserved during development. Importantly, in these expression patterns non-syntenic genes that evolved after the separation of the maize and sorghum lineages were systemically enriched. Furthermore, non-syntenic genes were substantially linked to the conservation of all surveyed gene expression patterns during primary root development. Among all F1-hybrids, between ~40% of the non-syntenic genes with unexpected allelic expression ratios and ~60% of the non-syntenic differentially and non-additively expressed genes were conserved and therefore robust to developmental changes. Hence, the enrichment of non-syntenic genes during primary root development might be involved in the developmental adaptation of maize roots and thus the superior performance of hybrids.
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Affiliation(s)
- Jutta A Baldauf
- Institute for Crop Science and Resource Conservation, Crop Functional Genomics, University of Bonn, Bonn, Germany
| | - Lucia Vedder
- Institute for Crop Science and Resource Conservation, Crop Bioinformatics, University of Bonn, Bonn, Germany
| | - Heiko Schoof
- Institute for Crop Science and Resource Conservation, Crop Bioinformatics, University of Bonn, Bonn, Germany
| | - Frank Hochholdinger
- Institute for Crop Science and Resource Conservation, Crop Functional Genomics, University of Bonn, Bonn, Germany
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Liu J, Fernie AR, Yan J. The Past, Present, and Future of Maize Improvement: Domestication, Genomics, and Functional Genomic Routes toward Crop Enhancement. PLANT COMMUNICATIONS 2020; 1:100010. [PMID: 33404535 PMCID: PMC7747985 DOI: 10.1016/j.xplc.2019.100010] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Revised: 11/07/2019] [Accepted: 11/22/2019] [Indexed: 05/14/2023]
Abstract
After being domesticated from teosinte, cultivated maize (Zea mays ssp. mays) spread worldwide and now is one of the most important staple crops. Due to its tremendous phenotypic and genotypic diversity, maize also becomes to be one of the most widely used model plant species for fundamental research, with many important discoveries reported by maize researchers. Here, we provide an overview of the history of maize domestication and key genes controlling major domestication-related traits, review the currently available resources for functional genomics studies in maize, and discuss the functions of most of the maize genes that have been positionally cloned and can be used for crop improvement. Finally, we provide some perspectives on future directions regarding functional genomics research and the breeding of maize and other crops.
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Affiliation(s)
- Jie Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
- Corresponding author
| | - Alisdair R. Fernie
- Department of Molecular Physiology, Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
- Corresponding author
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Welgemoed T, Pierneef R, Sterck L, Van de Peer Y, Swart V, Scheepers KD, Berger DK. De novo Assembly of Transcriptomes From a B73 Maize Line Introgressed With a QTL for Resistance to Gray Leaf Spot Disease Reveals a Candidate Allele of a Lectin Receptor-Like Kinase. FRONTIERS IN PLANT SCIENCE 2020; 11:191. [PMID: 32231673 PMCID: PMC7083176 DOI: 10.3389/fpls.2020.00191] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Accepted: 02/07/2020] [Indexed: 05/03/2023]
Abstract
Gray leaf spot (GLS) disease in maize, caused by the fungus Cercospora zeina, is a threat to maize production globally. Understanding the molecular basis for quantitative resistance to GLS is therefore important for food security. We developed a de novo assembly pipeline to identify candidate maize resistance genes. Near-isogenic maize lines with and without a QTL for GLS resistance on chromosome 10 from inbred CML444 were produced in the inbred B73 background. The B73-QTL line showed a 20% reduction in GLS disease symptoms compared to B73 in the field (p = 0.01). B73-QTL leaf samples from this field experiment conducted under GLS disease pressure were RNA sequenced. The reads that did not map to the B73 or C. zeina genomes were expected to contain novel defense genes and were de novo assembled. A total of 141 protein-coding sequences with B73-like or plant annotations were identified from the B73-QTL plants exposed to C. zeina. To determine whether candidate gene expression was induced by C. zeina, the RNAseq reads from C. zeina-challenged and control leaves were mapped to a master assembly of all of the B73-QTL reads, and differential gene expression analysis was conducted. Combining results from both bioinformatics approaches led to the identification of a likely candidate gene, which was a novel allele of a lectin receptor-like kinase named L-RLK-CML that (i) was induced by C. zeina, (ii) was positioned in the QTL region, and (iii) had functional domains for pathogen perception and defense signal transduction. The 817AA L-RLK-CML protein had 53 amino acid differences from its 818AA counterpart in B73. A second "B73-like" allele of L-RLK was expressed at a low level in B73-QTL. Gene copy-specific RT-qPCR confirmed that the l-rlk-cml transcript was the major product induced four-fold by C. zeina. Several other expressed defense-related candidates were identified, including a wall-associated kinase, two glutathione s-transferases, a chitinase, a glucan beta-glucosidase, a plasmodesmata callose-binding protein, several other receptor-like kinases, and components of calcium signaling, vesicular trafficking, and ethylene biosynthesis. This work presents a bioinformatics protocol for gene discovery from de novo assembled transcriptomes and identifies candidate quantitative resistance genes.
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Affiliation(s)
- Tanya Welgemoed
- Centre for Bioinformatics and Computational Biology, University of Pretoria, Pretoria, South Africa
- Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria, South Africa
- Forestry and Agricultural Biotechnology Institute, University of Pretoria, Pretoria, South Africa
| | - Rian Pierneef
- Centre for Bioinformatics and Computational Biology, University of Pretoria, Pretoria, South Africa
- Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria, South Africa
| | - Lieven Sterck
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- Department of Plant Systems Biology, VIB, Ghent, Belgium
| | - Yves Van de Peer
- Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria, South Africa
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- Department of Plant Systems Biology, VIB, Ghent, Belgium
- Genomics Research Institute, University of Pretoria, Pretoria, South Africa
| | - Velushka Swart
- Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria, South Africa
- Forestry and Agricultural Biotechnology Institute, University of Pretoria, Pretoria, South Africa
| | - Kevin Daniel Scheepers
- Forestry and Agricultural Biotechnology Institute, University of Pretoria, Pretoria, South Africa
- Department of Plant and Soil Sciences, University of Pretoria, Pretoria, South Africa
| | - Dave K. Berger
- Forestry and Agricultural Biotechnology Institute, University of Pretoria, Pretoria, South Africa
- Department of Plant and Soil Sciences, University of Pretoria, Pretoria, South Africa
- *Correspondence: Dave K. Berger,
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Cuello C, Baldy A, Brunaud V, Joets J, Delannoy E, Jacquemot MP, Botran L, Griveau Y, Guichard C, Soubigou-Taconnat L, Martin-Magniette ML, Leroy P, Méchin V, Reymond M, Coursol S. A systems biology approach uncovers a gene co-expression network associated with cell wall degradability in maize. PLoS One 2019; 14:e0227011. [PMID: 31891625 PMCID: PMC6938352 DOI: 10.1371/journal.pone.0227011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Accepted: 12/09/2019] [Indexed: 11/18/2022] Open
Abstract
Understanding the mechanisms triggering variation of cell wall degradability is a prerequisite to improving the energy value of lignocellulosic biomass for animal feed or biorefinery. Here, we implemented a multiscale systems approach to shed light on the genetic basis of cell wall degradability in maize. We demonstrated that allele replacement in two pairs of near-isogenic lines at a region encompassing a major quantitative trait locus (QTL) for cell wall degradability led to phenotypic variation of a similar magnitude and sign to that expected from a QTL analysis of cell wall degradability in the F271 × F288 recombinant inbred line progeny. Using DNA sequences within the QTL interval of both F271 and F288 inbred lines and Illumina RNA sequencing datasets from internodes of the selected near-isogenic lines, we annotated the genes present in the QTL interval and provided evidence that allelic variation at the introgressed QTL region gives rise to coordinated changes in gene expression. The identification of a gene co-expression network associated with cell wall-related trait variation revealed that the favorable F288 alleles exploit biological processes related to oxidation-reduction, regulation of hydrogen peroxide metabolism, protein folding and hormone responses. Nested in modules of co-expressed genes, potential new cell-wall regulators were identified, including two transcription factors of the group VII ethylene response factor family, that could be exploited to fine-tune cell wall degradability. Overall, these findings provide new insights into the regulatory mechanisms by which a major locus influences cell wall degradability, paving the way for its map-based cloning in maize.
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Affiliation(s)
- Clément Cuello
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, Versailles, France
| | - Aurélie Baldy
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, Versailles, France
| | - Véronique Brunaud
- Institute of Plant Sciences Paris-Saclay, CNRS, INRA, Université Paris-Sud, Université Evry, Université Paris-Saclay, Gif-sur-Yvette, France
- Institute of Plant Sciences Paris-Saclay, CNRS, INRA, Université Paris-Diderot, Sorbonne Paris-Cité, Gif-sur-Yvette, France
| | - Johann Joets
- Génétique Quantitative et Evolution—Le Moulon, INRA, Université Paris-Sud, CNRS, AgroParisTech, Université Paris-Saclay, Gif-Sur-Yvette, France
| | - Etienne Delannoy
- Institute of Plant Sciences Paris-Saclay, CNRS, INRA, Université Paris-Sud, Université Evry, Université Paris-Saclay, Gif-sur-Yvette, France
- Institute of Plant Sciences Paris-Saclay, CNRS, INRA, Université Paris-Diderot, Sorbonne Paris-Cité, Gif-sur-Yvette, France
| | - Marie-Pierre Jacquemot
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, Versailles, France
| | - Lucy Botran
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, Versailles, France
| | - Yves Griveau
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, Versailles, France
| | - Cécile Guichard
- Institute of Plant Sciences Paris-Saclay, CNRS, INRA, Université Paris-Sud, Université Evry, Université Paris-Saclay, Gif-sur-Yvette, France
- Institute of Plant Sciences Paris-Saclay, CNRS, INRA, Université Paris-Diderot, Sorbonne Paris-Cité, Gif-sur-Yvette, France
| | - Ludivine Soubigou-Taconnat
- Institute of Plant Sciences Paris-Saclay, CNRS, INRA, Université Paris-Sud, Université Evry, Université Paris-Saclay, Gif-sur-Yvette, France
- Institute of Plant Sciences Paris-Saclay, CNRS, INRA, Université Paris-Diderot, Sorbonne Paris-Cité, Gif-sur-Yvette, France
| | - Marie-Laure Martin-Magniette
- Institute of Plant Sciences Paris-Saclay, CNRS, INRA, Université Paris-Sud, Université Evry, Université Paris-Saclay, Gif-sur-Yvette, France
- Institute of Plant Sciences Paris-Saclay, CNRS, INRA, Université Paris-Diderot, Sorbonne Paris-Cité, Gif-sur-Yvette, France
- UMR MIA-Paris, AgroParisTech, INRA, Université Paris-Saclay, Paris, France
| | | | - Valérie Méchin
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, Versailles, France
| | - Matthieu Reymond
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, Versailles, France
| | - Sylvie Coursol
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, Versailles, France
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Weisweiler M, Montaigu AD, Ries D, Pfeifer M, Stich B. Transcriptomic and presence/absence variation in the barley genome assessed from multi-tissue mRNA sequencing and their power to predict phenotypic traits. BMC Genomics 2019; 20:787. [PMID: 31664921 PMCID: PMC6819542 DOI: 10.1186/s12864-019-6174-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Accepted: 10/06/2019] [Indexed: 02/04/2023] Open
Abstract
Background Barley is the world’s fourth most cultivated cereal and is an important crop model for genetic studies. One layer of genomic information that remains poorly explored in barley is presence/absence variation (PAV), which has been suggested to contribute to phenotypic variation of agronomic importance in various crops. Results An mRNA sequencing approach was used to study genomic PAV and transcriptomic variation in 23 spring barley inbreds. 1502 new genes identified here were physically absent from the Morex reference sequence, and 11,523 previously unannotated genes were not expressed in Morex. The procedure applied to detect expression PAV revealed that more than 50% of all genes of our data set are not expressed in all inbreds. Interestingly, expression PAV were not in strong linkage disequilibrium with neighboring sequence variants (SV), and therefore provided an additional layer of genetic information. Optimal combinations of expression PAV, SV, and gene abundance data could enhance the prediction accuracy of predicting three different agronomic traits. Conclusions Our results highlight the advantage of mRNA sequencing for genomic prediction over other technologies, as it allows extracting multiple layers of genomic data from a single sequencing experiment. Finally, we propose low coverage mRNA sequencing based characterization of breeding material harvested as seedlings in petri dishes as a powerful and cost efficient approach to replace current single nucleotide polymorphism (SNP) based characterizations.
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Affiliation(s)
- Marius Weisweiler
- Institute for Quantitative Genetics and Genomics of Plants, Universitätsstraße 1, Düsseldorf, 40225, Germany
| | - Amaury de Montaigu
- Institute for Quantitative Genetics and Genomics of Plants, Universitätsstraße 1, Düsseldorf, 40225, Germany
| | - David Ries
- Institute for Quantitative Genetics and Genomics of Plants, Universitätsstraße 1, Düsseldorf, 40225, Germany
| | - Mara Pfeifer
- Institute for Quantitative Genetics and Genomics of Plants, Universitätsstraße 1, Düsseldorf, 40225, Germany
| | - Benjamin Stich
- Institute for Quantitative Genetics and Genomics of Plants, Universitätsstraße 1, Düsseldorf, 40225, Germany. .,Cluster of Excellence on Plant Sciences, From Complex Traits towards Synthetic Modules, Universitätsstraße 1, Düsseldorf, 40225, Germany.
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37
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Ma Y, Liu M, Stiller J, Liu C. A pan-transcriptome analysis shows that disease resistance genes have undergone more selection pressure during barley domestication. BMC Genomics 2019; 20:12. [PMID: 30616511 PMCID: PMC6323845 DOI: 10.1186/s12864-018-5357-7] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Accepted: 12/09/2018] [Indexed: 11/12/2022] Open
Abstract
Background It has become clear in recent years that many genes in a given species may not be found in a single genotype thus using sequences from a single genotype as reference may not be adequate for various applications. Results In this study we constructed a pan-transcriptome for barley by de novo assembling 288 sets of RNA-seq data from 32 cultivated barley genotypes and 31 wild barley genotypes. The pan-transcriptome consists of 756,632 transcripts with an average N50 length of 1240 bp. Of these, 289,697 (38.2%) were not found in the genome of the international reference genotype Morex. The novel transcripts are enriched with genes associated with responses to different stresses and stimuli. At the pan-transcriptome level, genotypes of wild barley have a higher proportion of disease resistance genes than cultivated ones. Conclusions We demonstrate that the use of the pan-transcriptome dramatically improved the efficiency in detecting variation in barley. Analysing the pan-transcriptome also found that, compared with those in other categories, disease resistance genes have gone through stronger selective pressures during domestication. Electronic supplementary material The online version of this article (10.1186/s12864-018-5357-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yanling Ma
- CSIRO Agriculture & Food, 306 Carmody Road, St Lucia, QLD, 4067, Australia
| | - Miao Liu
- CSIRO Agriculture & Food, 306 Carmody Road, St Lucia, QLD, 4067, Australia.,Crop Research Institute of Sichuan Academy of Agricultural Sciences, Chengdu, 610066, China
| | - Jiri Stiller
- CSIRO Agriculture & Food, 306 Carmody Road, St Lucia, QLD, 4067, Australia
| | - Chunji Liu
- CSIRO Agriculture & Food, 306 Carmody Road, St Lucia, QLD, 4067, Australia.
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Lyra DH, Galli G, Alves FC, Granato ÍSC, Vidotti MS, Bandeira E Sousa M, Morosini JS, Crossa J, Fritsche-Neto R. Modeling copy number variation in the genomic prediction of maize hybrids. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:273-288. [PMID: 30382311 DOI: 10.1007/s00122-018-3215-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Accepted: 10/20/2018] [Indexed: 06/08/2023]
Abstract
Our study indicates that copy variants may play an essential role in the phenotypic variation of complex traits in maize hybrids. Moreover, predicting hybrid phenotypes by combining additive-dominance effects with copy variants has the potential to be a viable predictive model. Non-additive effects resulting from the actions of multiple loci may influence trait variation in single-cross hybrids. In addition, complementation of allelic variation could be a valuable contributor to hybrid genetic variation, especially when crossing inbred lines with higher contents of copy gains. With this in mind, we aimed (1) to study the association between copy number variation (CNV) and hybrid phenotype, and (2) to compare the predictive ability (PA) of additive and additive-dominance genomic best linear unbiased prediction model when combined with the effects of CNV in two datasets of maize hybrids (USP and HELIX). In the USP dataset, we observed a significant negative phenotypic correlation of low magnitude between copy number loss and plant height, revealing a tendency that more copy losses lead to lower plants. In the same set, when CNV was combined with the additive plus dominance effects, the PA significantly increased only for plant height under low nitrogen. In this case, CNV effects explicitly capture relatedness between individuals and add extra information to the model. In the HELIX dataset, we observed a pronounced difference in PA between additive (0.50) and additive-dominance (0.71) models for predicting grain yield, suggesting a significant contribution of dominance. We conclude that copy variants may play an essential role in the phenotypic variation of complex traits in maize hybrids, although the inclusion of CNVs into datasets does not return significant gains concerning PA.
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Affiliation(s)
- Danilo Hottis Lyra
- Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo (ESALQ/USP), Piracicaba, São Paulo, Brazil.
- Department of Computational and Analytical Sciences, Rothamsted Research, West Common, Harpenden, AL52JQ, UK.
| | - Giovanni Galli
- Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo (ESALQ/USP), Piracicaba, São Paulo, Brazil
| | - Filipe Couto Alves
- Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo (ESALQ/USP), Piracicaba, São Paulo, Brazil
| | - Ítalo Stefanine Correia Granato
- Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo (ESALQ/USP), Piracicaba, São Paulo, Brazil
| | - Miriam Suzane Vidotti
- Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo (ESALQ/USP), Piracicaba, São Paulo, Brazil
| | - Massaine Bandeira E Sousa
- Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo (ESALQ/USP), Piracicaba, São Paulo, Brazil
| | - Júlia Silva Morosini
- Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo (ESALQ/USP), Piracicaba, São Paulo, Brazil
| | - José Crossa
- Biometrics and Statistics Unit, International Maize and Wheat Improvement Center (CIMMYT), 06600, Texcoco, D.F, Mexico
| | - Roberto Fritsche-Neto
- Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo (ESALQ/USP), Piracicaba, São Paulo, Brazil
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Owens GL, Baute GJ, Hubner S, Rieseberg LH. Genomic sequence and copy number evolution during hybrid crop development in sunflowers. Evol Appl 2019; 12:54-65. [PMID: 30622635 PMCID: PMC6304689 DOI: 10.1111/eva.12603] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2017] [Accepted: 01/18/2018] [Indexed: 01/21/2023] Open
Abstract
Hybrid crops, an important part of modern agriculture, rely on the development of male and female heterotic gene pools. In sunflowers, heterotic gene pools were developed through the use of crop-wild relatives to produce cytoplasmic male sterile female and branching, fertility restoring male lines. Here, we use genomic data from a diversity panel of male, female, and open-pollinated lines to explore the genetic changes brought during modern improvement. We find the male lines have diverged most from their open-pollinated progenitors and that genetic differentiation is concentrated in chromosomes, 8, 10 and 13, due to introgressions from wild relatives. Ancestral variation from open-pollinated varieties almost universally evolved in parallel for both male and female lines suggesting little or no selection for heterotic overdominance. Furthermore, we show that gene content differs between the male and female lines and that differentiation in gene content is concentrated in high FST regions. This means that the introgressions that brought branching and fertility restoration to the male lines, brought with them different gene content from the ancestral haplotypes, including the removal of some genes. Although we find no evidence that gene complementation genomewide is responsible for heterosis between male and female lines, several of the genes that are largely absent in either the male or female lines are associated with pathogen defense, suggesting complementation may be functionally relevant for crop breeders.
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Affiliation(s)
- Gregory L. Owens
- Department of Botany and Biodiversity Research CentreUniversity of British ColumbiaVancouverBCCanada
| | - Gregory J. Baute
- Department of Botany and Biodiversity Research CentreUniversity of British ColumbiaVancouverBCCanada
| | - Sariel Hubner
- Department of Botany and Biodiversity Research CentreUniversity of British ColumbiaVancouverBCCanada
- Department of BiotechnologyTel‐Hai Academic CollegeUpper GalileeIsrael
- MIGAL ‐ Galilee Research InstituteKiryat ShmonaIsrael
| | - Loren H. Rieseberg
- Department of Botany and Biodiversity Research CentreUniversity of British ColumbiaVancouverBCCanada
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40
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Owens GL, Baute GJ, Hubner S, Rieseberg LH. Genomic sequence and copy number evolution during hybrid crop development in sunflowers. Evol Appl 2019. [PMID: 30622635 DOI: 10.111/eva.12603] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/24/2023] Open
Abstract
Hybrid crops, an important part of modern agriculture, rely on the development of male and female heterotic gene pools. In sunflowers, heterotic gene pools were developed through the use of crop-wild relatives to produce cytoplasmic male sterile female and branching, fertility restoring male lines. Here, we use genomic data from a diversity panel of male, female, and open-pollinated lines to explore the genetic changes brought during modern improvement. We find the male lines have diverged most from their open-pollinated progenitors and that genetic differentiation is concentrated in chromosomes, 8, 10 and 13, due to introgressions from wild relatives. Ancestral variation from open-pollinated varieties almost universally evolved in parallel for both male and female lines suggesting little or no selection for heterotic overdominance. Furthermore, we show that gene content differs between the male and female lines and that differentiation in gene content is concentrated in high FST regions. This means that the introgressions that brought branching and fertility restoration to the male lines, brought with them different gene content from the ancestral haplotypes, including the removal of some genes. Although we find no evidence that gene complementation genomewide is responsible for heterosis between male and female lines, several of the genes that are largely absent in either the male or female lines are associated with pathogen defense, suggesting complementation may be functionally relevant for crop breeders.
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Affiliation(s)
- Gregory L Owens
- Department of Botany and Biodiversity Research Centre University of British Columbia Vancouver BC Canada
| | - Gregory J Baute
- Department of Botany and Biodiversity Research Centre University of British Columbia Vancouver BC Canada
| | - Sariel Hubner
- Department of Botany and Biodiversity Research Centre University of British Columbia Vancouver BC Canada
- Department of Biotechnology Tel-Hai Academic College Upper Galilee Israel
- MIGAL - Galilee Research Institute Kiryat Shmona Israel
| | - Loren H Rieseberg
- Department of Botany and Biodiversity Research Centre University of British Columbia Vancouver BC Canada
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Massonnet M, Morales-Cruz A, Minio A, Figueroa-Balderas R, Lawrence DP, Travadon R, Rolshausen PE, Baumgartner K, Cantu D. Whole-Genome Resequencing and Pan-Transcriptome Reconstruction Highlight the Impact of Genomic Structural Variation on Secondary Metabolite Gene Clusters in the Grapevine Esca Pathogen Phaeoacremonium minimum. Front Microbiol 2018; 9:1784. [PMID: 30150972 PMCID: PMC6099105 DOI: 10.3389/fmicb.2018.01784] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Accepted: 07/16/2018] [Indexed: 12/30/2022] Open
Abstract
The Ascomycete fungus Phaeoacremonium minimum is one of the primary causal agents of Esca, a widespread and damaging grapevine trunk disease. Variation in virulence among Pm. minimum isolates has been reported, but the underlying genetic basis of the phenotypic variability remains unknown. The goal of this study was to characterize intraspecific genetic diversity and explore its potential impact on virulence functions associated with secondary metabolism, cellular transport, and cell wall decomposition. We generated a chromosome-scale genome assembly, using single molecule real-time sequencing, and resequenced the genomes and transcriptomes of multiple isolates to identify sequence and structural polymorphisms. Numerous insertion and deletion events were found for a total of about 1 Mbp in each isolate. Structural variation in this extremely gene dense genome frequently caused presence/absence polymorphisms of multiple adjacent genes, mostly belonging to biosynthetic clusters associated with secondary metabolism. Because of the observed intraspecific diversity in gene content due to structural variation we concluded that a transcriptome reference developed from a single isolate is insufficient to represent the virulence factor repertoire of the species. We therefore compiled a pan-transcriptome reference of Pm. minimum comprising a non-redundant set of 15,245 protein-coding sequences. Using naturally infected field samples expressing Esca symptoms, we demonstrated that mapping of meta-transcriptomics data on a multi-species reference that included the Pm. minimum pan-transcriptome allows the profiling of an expanded set of virulence factors, including variable genes associated with secondary metabolism and cellular transport.
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Affiliation(s)
- Mélanie Massonnet
- Department of Viticulture and Enology, University of California, Davis, Davis, CA, United States
| | - Abraham Morales-Cruz
- Department of Viticulture and Enology, University of California, Davis, Davis, CA, United States
| | - Andrea Minio
- Department of Viticulture and Enology, University of California, Davis, Davis, CA, United States
| | - Rosa Figueroa-Balderas
- Department of Viticulture and Enology, University of California, Davis, Davis, CA, United States
| | - Daniel P. Lawrence
- Department of Plant Pathology, University of California, Davis, Davis, CA, United States
| | - Renaud Travadon
- Department of Plant Pathology, University of California, Davis, Davis, CA, United States
| | - Philippe E. Rolshausen
- Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA, United States
| | - Kendra Baumgartner
- Crops Pathology and Genetics Research Unit, Agricultural Research Service, United States Department of Agriculture, Davis, CA, United States
| | - Dario Cantu
- Department of Viticulture and Enology, University of California, Davis, Davis, CA, United States
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Extensive gene content variation in the Brachypodium distachyon pan-genome correlates with population structure. Nat Commun 2017; 8:2184. [PMID: 29259172 PMCID: PMC5736591 DOI: 10.1038/s41467-017-02292-8] [Citation(s) in RCA: 214] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Accepted: 11/17/2017] [Indexed: 12/17/2022] Open
Abstract
While prokaryotic pan-genomes have been shown to contain many more genes than any individual organism, the prevalence and functional significance of differentially present genes in eukaryotes remains poorly understood. Whole-genome de novo assembly and annotation of 54 lines of the grass Brachypodium distachyon yield a pan-genome containing nearly twice the number of genes found in any individual genome. Genes present in all lines are enriched for essential biological functions, while genes present in only some lines are enriched for conditionally beneficial functions (e.g., defense and development), display faster evolutionary rates, lie closer to transposable elements and are less likely to be syntenic with orthologous genes in other grasses. Our data suggest that differentially present genes contribute substantially to phenotypic variation within a eukaryote species, these genes have a major influence in population genetics, and transposable elements play a key role in pan-genome evolution. The role of differential gene content in the evolution and function of eukaryotic genomes remains poorly explored. Here the authors assemble and annotate the Brachypodium distachyon pan-genome consisting of 54 diverse lines and reveal the differential present genes as a major driver of phenotypic variation.
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Tsai WC, Dievart A, Hsu CC, Hsiao YY, Chiou SY, Huang H, Chen HH. Post genomics era for orchid research. BOTANICAL STUDIES 2017; 58:61. [PMID: 29234904 PMCID: PMC5727007 DOI: 10.1186/s40529-017-0213-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Accepted: 12/01/2017] [Indexed: 05/05/2023]
Abstract
Among 300,000 species in angiosperms, Orchidaceae containing 30,000 species is one of the largest families. Almost every habitats on earth have orchid plants successfully colonized, and it indicates that orchids are among the plants with significant ecological and evolutionary importance. So far, four orchid genomes have been sequenced, including Phalaenopsis equestris, Dendrobium catenatum, Dendrobium officinale, and Apostaceae shengen. Here, we review the current progress and the direction of orchid research in the post genomics era. These include the orchid genome evolution, genome mapping (genome-wide association analysis, genetic map, physical map), comparative genomics (especially receptor-like kinase and terpene synthase), secondary metabolomics, and genome editing.
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Affiliation(s)
- Wen-Chieh Tsai
- Institute of Tropical Plant Sciences, National Cheng Kung University, Tainan, 701 Taiwan
- Orchid Research and Development Center, National Cheng Kung University, Tainan, 701 Taiwan
- Department of Life Sciences, National Cheng Kung University, Tainan, 701 Taiwan
| | - Anne Dievart
- CIRAD, UMR AGAP, TA A 108/03, Avenue Agropolis, 34398 Montpellier, France
- Present Address: School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Life Sciences Building, Room 3-117, Shanghai, 200240 People’s Republic of China
| | - Chia-Chi Hsu
- Department of Life Sciences, National Cheng Kung University, Tainan, 701 Taiwan
| | - Yu-Yun Hsiao
- Orchid Research and Development Center, National Cheng Kung University, Tainan, 701 Taiwan
- Department of Life Sciences, National Cheng Kung University, Tainan, 701 Taiwan
| | - Shang-Yi Chiou
- Department of Life Sciences, National Cheng Kung University, Tainan, 701 Taiwan
| | - Hsin Huang
- Department of Life Sciences, National Cheng Kung University, Tainan, 701 Taiwan
| | - Hong-Hwa Chen
- Institute of Tropical Plant Sciences, National Cheng Kung University, Tainan, 701 Taiwan
- Orchid Research and Development Center, National Cheng Kung University, Tainan, 701 Taiwan
- Department of Life Sciences, National Cheng Kung University, Tainan, 701 Taiwan
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Lin HY, Liu Q, Li X, Yang J, Liu S, Huang Y, Scanlon MJ, Nettleton D, Schnable PS. Substantial contribution of genetic variation in the expression of transcription factors to phenotypic variation revealed by eRD-GWAS. Genome Biol 2017; 18:192. [PMID: 29041960 PMCID: PMC5645915 DOI: 10.1186/s13059-017-1328-6] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2017] [Accepted: 09/27/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND There are significant limitations in existing methods for the genome-wide identification of genes whose expression patterns affect traits. RESULTS The transcriptomes of five tissues from 27 genetically diverse maize inbred lines were deeply sequenced to identify genes exhibiting high and low levels of expression variation across tissues or genotypes. Transcription factors are enriched among genes with the most variation in expression across tissues, as well as among genes with higher-than-median levels of variation in expression across genotypes. In contrast, transcription factors are depleted among genes whose expression is either highly stable or highly variable across genotypes. We developed a Bayesian-based method for genome-wide association studies (GWAS) in which RNA-seq-based measures of transcript accumulation are used as explanatory variables (eRD-GWAS). The ability of eRD-GWAS to identify true associations between gene expression variation and phenotypic diversity is supported by analyses of RNA co-expression networks, protein-protein interaction networks, and gene regulatory networks. Genes associated with 13 traits were identified using eRD-GWAS on a panel of 369 maize inbred lines. Predicted functions of many of the resulting trait-associated genes are consistent with the analyzed traits. Importantly, transcription factors are significantly enriched among trait-associated genes identified with eRD-GWAS. CONCLUSIONS eRD-GWAS is a powerful tool for associating genes with traits and is complementary to SNP-based GWAS. Our eRD-GWAS results are consistent with the hypothesis that genetic variation in transcription factor expression contributes substantially to phenotypic diversity.
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Affiliation(s)
- Hung-Ying Lin
- Department of Agronomy, Iowa State University, 2035 B Roy J Carver Co-Lab, Ames, IA, 50011-3650, USA.,Interdepartmental Genetics and Genomics Graduate Program, Iowa State University, Ames, IA, 50011-3650, USA
| | - Qiang Liu
- Department of Agronomy, Iowa State University, 2035 B Roy J Carver Co-Lab, Ames, IA, 50011-3650, USA.,Interdepartmental Genetics and Genomics Graduate Program, Iowa State University, Ames, IA, 50011-3650, USA
| | - Xiao Li
- Interdepartmental Genetics and Genomics Graduate Program, Iowa State University, Ames, IA, 50011-3650, USA.,Department of Genetics, Developmental and Cellular Biology, Iowa State University, Ames, IA, 50011-3650, USA.,The Broad Institute of MIT and Harvard, 75 Ames Street, Cambridge, MA, 02142-1403, USA
| | - Jinliang Yang
- Department of Agronomy, Iowa State University, 2035 B Roy J Carver Co-Lab, Ames, IA, 50011-3650, USA.,Interdepartmental Genetics and Genomics Graduate Program, Iowa State University, Ames, IA, 50011-3650, USA.,Department of Plant Sciences, University of California, Davis, CA, 95616-5270, USA.,Department of Agronomy and Horticulture, University of Nebraska, Lincoln, Nebraska, 68583-0660, USA
| | - Sanzhen Liu
- Department of Agronomy, Iowa State University, 2035 B Roy J Carver Co-Lab, Ames, IA, 50011-3650, USA.,Interdepartmental Genetics and Genomics Graduate Program, Iowa State University, Ames, IA, 50011-3650, USA.,Department of Plant Pathology, Kansas State University, Manhattan, KS, 66506-5502, USA
| | - Yinlian Huang
- Department of Plant Genetics & Breeding, China Agricultural University, Beijing, 100193, China.,DATA Biotechnology Beijing Co. Ltd, Beijing, 102206, China
| | - Michael J Scanlon
- Plant Biology Section, Cornell University, Ithaca, New York, 14850, USA
| | - Dan Nettleton
- Department of Statistics, Iowa State University, Ames, IA, 50011-1210, USA
| | - Patrick S Schnable
- Department of Agronomy, Iowa State University, 2035 B Roy J Carver Co-Lab, Ames, IA, 50011-3650, USA. .,Interdepartmental Genetics and Genomics Graduate Program, Iowa State University, Ames, IA, 50011-3650, USA. .,Department of Genetics, Developmental and Cellular Biology, Iowa State University, Ames, IA, 50011-3650, USA. .,Department of Plant Genetics & Breeding, China Agricultural University, Beijing, 100193, China.
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Liu J, Huang J, Guo H, Lan L, Wang H, Xu Y, Yang X, Li W, Tong H, Xiao Y, Pan Q, Qiao F, Raihan MS, Liu H, Zhang X, Yang N, Wang X, Deng M, Jin M, Zhao L, Luo X, Zhou Y, Li X, Zhan W, Liu N, Wang H, Chen G, Li Q, Yan J. The Conserved and Unique Genetic Architecture of Kernel Size and Weight in Maize and Rice. PLANT PHYSIOLOGY 2017; 175:774-785. [PMID: 28811335 PMCID: PMC5619898 DOI: 10.1104/pp.17.00708] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Accepted: 08/12/2017] [Indexed: 05/18/2023]
Abstract
Maize (Zea mays) is a major staple crop. Maize kernel size and weight are important contributors to its yield. Here, we measured kernel length, kernel width, kernel thickness, hundred kernel weight, and kernel test weight in 10 recombinant inbred line populations and dissected their genetic architecture using three statistical models. In total, 729 quantitative trait loci (QTLs) were identified, many of which were identified in all three models, including 22 major QTLs that each can explain more than 10% of phenotypic variation. To provide candidate genes for these QTLs, we identified 30 maize genes that are orthologs of 18 rice (Oryza sativa) genes reported to affect rice seed size or weight. Interestingly, 24 of these 30 genes are located in the identified QTLs or within 1 Mb of the significant single-nucleotide polymorphisms. We further confirmed the effects of five genes on maize kernel size/weight in an independent association mapping panel with 540 lines by candidate gene association analysis. Lastly, the function of ZmINCW1, a homolog of rice GRAIN INCOMPLETE FILLING1 that affects seed size and weight, was characterized in detail. ZmINCW1 is close to QTL peaks for kernel size/weight (less than 1 Mb) and contains significant single-nucleotide polymorphisms affecting kernel size/weight in the association panel. Overexpression of this gene can rescue the reduced weight of the Arabidopsis (Arabidopsis thaliana) homozygous mutant line in the AtcwINV2 gene (Arabidopsis ortholog of ZmINCW1). These results indicate that the molecular mechanisms affecting seed development are conserved in maize, rice, and possibly Arabidopsis.
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Affiliation(s)
- Jie Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Juan Huang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Huan Guo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Liu Lan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Hongze Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Yuancheng Xu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiaohong Yang
- National Maize Improvement Center of China, MOA Key Laboratory of Maize Biology, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Wenqiang Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Hao Tong
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Yingjie Xiao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Qingchun Pan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Feng Qiao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Mohammad Sharif Raihan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Haijun Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Xuehai Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Ning Yang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiaqing Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Min Deng
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Minliang Jin
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Lijun Zhao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Xin Luo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Yang Zhou
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiang Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Wei Zhan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Nannan Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Hong Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Gengshen Chen
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Qing Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
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Xu Y, Li P, Zou C, Lu Y, Xie C, Zhang X, Prasanna BM, Olsen MS. Enhancing genetic gain in the era of molecular breeding. JOURNAL OF EXPERIMENTAL BOTANY 2017; 68:2641-2666. [PMID: 28830098 DOI: 10.1093/jxb/erx135] [Citation(s) in RCA: 108] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Accepted: 04/03/2017] [Indexed: 05/20/2023]
Abstract
As one of the important concepts in conventional quantitative genetics and breeding, genetic gain can be defined as the amount of increase in performance that is achieved annually through artificial selection. To develop pro ducts that meet the increasing demand of mankind, especially for food and feed, in addition to various industrial uses, breeders are challenged to enhance the potential of genetic gain continuously, at ever higher rates, while they close the gaps that remain between the yield potential in breeders' demonstration trials and the actual yield in farmers' fields. Factors affecting genetic gain include genetic variation available in breeding materials, heritability for traits of interest, selection intensity, and the time required to complete a breeding cycle. Genetic gain can be improved through enhancing the potential and closing the gaps, which has been evolving and complemented with modern breeding techniques and platforms, mainly driven by molecular and genomic tools, combined with improved agronomic practice. Several key strategies are reviewed in this article. Favorable genetic variation can be unlocked and created through molecular and genomic approaches including mutation, gene mapping and discovery, and transgene and genome editing. Estimation of heritability can be improved by refining field experiments through well-controlled and precisely assayed environmental factors or envirotyping, particularly for understanding and controlling spatial heterogeneity at the field level. Selection intensity can be significantly heightened through improvements in the scale and precision of genotyping and phenotyping. The breeding cycle time can be shortened by accelerating breeding procedures through integrated breeding approaches such as marker-assisted selection and doubled haploid development. All the strategies can be integrated with other widely used conventional approaches in breeding programs to enhance genetic gain. More transdisciplinary approaches, team breeding, will be required to address the challenge of maintaining a plentiful and safe food supply for future generations. New opportunities for enhancing genetic gain, a high efficiency breeding pipeline, and broad-sense genetic gain are also discussed prospectively.
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Affiliation(s)
- Yunbi Xu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, CP 56130, México
| | - Ping Li
- Nantong Xinhe Bio-Technology, Nantong 226019, PR China
| | - Cheng Zou
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yanli Lu
- Maize Research Institute, Sichuan Agricultural University, Wenjiang 611130, Sichuan, China
| | - Chuanxiao Xie
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xuecai Zhang
- International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, CP 56130, México
| | - Boddupalli M Prasanna
- CIMMYT (International Maize and Wheat Improvement Center), ICRAF campus, United Nations Avenue, Nairobi, Kenya
| | - Michael S Olsen
- CIMMYT (International Maize and Wheat Improvement Center), ICRAF campus, United Nations Avenue, Nairobi, Kenya
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Xiao Y, Liu H, Wu L, Warburton M, Yan J. Genome-wide Association Studies in Maize: Praise and Stargaze. MOLECULAR PLANT 2017; 10:359-374. [PMID: 28039028 DOI: 10.1016/j.molp.2016.12.008] [Citation(s) in RCA: 237] [Impact Index Per Article: 29.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2016] [Revised: 12/02/2016] [Accepted: 12/20/2016] [Indexed: 05/18/2023]
Abstract
Genome-wide association study (GWAS) has become a widely accepted strategy for decoding genotype-phenotype associations in many species thanks to advances in next-generation sequencing (NGS) technologies. Maize is an ideal crop for GWAS and significant progress has been made in the last decade. This review summarizes current GWAS efforts in maize functional genomics research and discusses future prospects in the omics era. The general goal of GWAS is to link genotypic variations to corresponding differences in phenotype using the most appropriate statistical model in a given population. The current review also presents perspectives for optimizing GWAS design and analysis. GWAS analysis of data from RNA, protein, and metabolite-based omics studies is discussed, along with new models and new population designs that will identify causes of phenotypic variation that have been hidden to date. The joint and continuous efforts of the whole community will enhance our understanding of maize quantitative traits and boost crop molecular breeding designs.
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Affiliation(s)
- Yingjie Xiao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Haijun Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Liuji Wu
- Synergetic Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Marilyn Warburton
- United States of Department of Agriculture, Agricultural Research Service, Corn Host Plant Resistance Research Unit, Box 9555, MS 39762, Mississippi, USA
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China.
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Brandenburg JT, Mary-Huard T, Rigaill G, Hearne SJ, Corti H, Joets J, Vitte C, Charcosset A, Nicolas SD, Tenaillon MI. Independent introductions and admixtures have contributed to adaptation of European maize and its American counterparts. PLoS Genet 2017; 13:e1006666. [PMID: 28301472 PMCID: PMC5373671 DOI: 10.1371/journal.pgen.1006666] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Revised: 03/30/2017] [Accepted: 03/01/2017] [Indexed: 12/27/2022] Open
Abstract
Through the local selection of landraces, humans have guided the adaptation of crops to a vast range of climatic and ecological conditions. This is particularly true of maize, which was domesticated in a restricted area of Mexico but now displays one of the broadest cultivated ranges worldwide. Here, we sequenced 67 genomes with an average sequencing depth of 18x to document routes of introduction, admixture and selective history of European maize and its American counterparts. To avoid the confounding effects of recent breeding, we targeted germplasm (lines) directly derived from landraces. Among our lines, we discovered 22,294,769 SNPs and between 0.9% to 4.1% residual heterozygosity. Using a segmentation method, we identified 6,978 segments of unexpectedly high rate of heterozygosity. These segments point to genes potentially involved in inbreeding depression, and to a lesser extent to the presence of structural variants. Genetic structuring and inferences of historical splits revealed 5 genetic groups and two independent European introductions, with modest bottleneck signatures. Our results further revealed admixtures between distinct sources that have contributed to the establishment of 3 groups at intermediate latitudes in North America and Europe. We combined differentiation- and diversity-based statistics to identify both genes and gene networks displaying strong signals of selection. These include genes/gene networks involved in flowering time, drought and cold tolerance, plant defense and starch properties. Overall, our results provide novel insights into the evolutionary history of European maize and highlight a major role of admixture in environmental adaptation, paralleling recent findings in humans.
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Affiliation(s)
- Jean-Tristan Brandenburg
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
| | - Tristan Mary-Huard
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
- UMR 518 AgroParisTech/INRA, France
| | - Guillem Rigaill
- Institute of Plant Sciences Paris-Saclay, UMR 9213/UMR1403, CNRS, INRA, Université Paris-Sud, Université d’Evry, Université Paris-Diderot, Sorbonne Paris-Cité, France
| | - Sarah J. Hearne
- CIMMYT (International Maize and Wheat Improvement Centre), El Batan, Texcoco, Edo de Mexico, Mexico
| | - Hélène Corti
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
| | - Johann Joets
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
| | - Clémentine Vitte
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
| | - Alain Charcosset
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
| | - Stéphane D. Nicolas
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
| | - Maud I. Tenaillon
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
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49
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Liu S, Zheng J, Migeon P, Ren J, Hu Y, He C, Liu H, Fu J, White FF, Toomajian C, Wang G. Unbiased K-mer Analysis Reveals Changes in Copy Number of Highly Repetitive Sequences During Maize Domestication and Improvement. Sci Rep 2017; 7:42444. [PMID: 28186206 PMCID: PMC5301235 DOI: 10.1038/srep42444] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Accepted: 01/10/2017] [Indexed: 12/15/2022] Open
Abstract
The major component of complex genomes is repetitive elements, which remain recalcitrant to characterization. Using maize as a model system, we analyzed whole genome shotgun (WGS) sequences for the two maize inbred lines B73 and Mo17 using k-mer analysis to quantify the differences between the two genomes. Significant differences were identified in highly repetitive sequences, including centromere, 45S ribosomal DNA (rDNA), knob, and telomere repeats. Genotype specific 45S rDNA sequences were discovered. The B73 and Mo17 polymorphic k-mers were used to examine allele-specific expression of 45S rDNA in the hybrids. Although Mo17 contains higher copy number than B73, equivalent levels of overall 45S rDNA expression indicates that transcriptional or post-transcriptional regulation mechanisms operate for the 45S rDNA in the hybrids. Using WGS sequences of B73xMo17 doubled haploids, genomic locations showing differential repetitive contents were genetically mapped, which displayed different organization of highly repetitive sequences in the two genomes. In an analysis of WGS sequences of HapMap2 lines, including maize wild progenitor, landraces, and improved lines, decreases and increases in abundance of additional sets of k-mers associated with centromere, 45S rDNA, knob, and retrotransposons were found among groups, revealing global evolutionary trends of genomic repeats during maize domestication and improvement.
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Affiliation(s)
- Sanzhen Liu
- Department of Plant Pathology, Kansas State University, Manhattan, KS, 66506, USA
| | - Jun Zheng
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China
| | - Pierre Migeon
- Department of Plant Pathology, Kansas State University, Manhattan, KS, 66506, USA
| | - Jie Ren
- Department of Plant Pathology, Kansas State University, Manhattan, KS, 66506, USA
| | - Ying Hu
- Department of Plant Pathology, Kansas State University, Manhattan, KS, 66506, USA
| | - Cheng He
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China
| | - Hongjun Liu
- State Key Laboratory of Crop Biology, Shandong Key Laboratory of Crop Biology, Taian 271018, P.R. China.,College of Life Sciences, Shandong Agricultural University, Taian 271018, P.R. China
| | - Junjie Fu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China
| | - Frank F White
- Department of Plant Pathology, University of Florida, Gainesville, FL, 32611, USA
| | | | - Guoying Wang
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China
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50
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Contreras-Moreira B, Cantalapiedra CP, García-Pereira MJ, Gordon SP, Vogel JP, Igartua E, Casas AM, Vinuesa P. Analysis of Plant Pan-Genomes and Transcriptomes with GET_HOMOLOGUES-EST, a Clustering Solution for Sequences of the Same Species. FRONTIERS IN PLANT SCIENCE 2017; 8:184. [PMID: 28261241 PMCID: PMC5306281 DOI: 10.3389/fpls.2017.00184] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Accepted: 01/30/2017] [Indexed: 05/22/2023]
Abstract
The pan-genome of a species is defined as the union of all the genes and non-coding sequences found in all its individuals. However, constructing a pan-genome for plants with large genomes is daunting both in sequencing cost and the scale of the required computational analysis. A more affordable alternative is to focus on the genic repertoire by using transcriptomic data. Here, the software GET_HOMOLOGUES-EST was benchmarked with genomic and RNA-seq data of 19 Arabidopsis thaliana ecotypes and then applied to the analysis of transcripts from 16 Hordeum vulgare genotypes. The goal was to sample their pan-genomes and classify sequences as core, if detected in all accessions, or accessory, when absent in some of them. The resulting sequence clusters were used to simulate pan-genome growth, and to compile Average Nucleotide Identity matrices that summarize intra-species variation. Although transcripts were found to under-estimate pan-genome size by at least 10%, we concluded that clusters of expressed sequences can recapitulate phylogeny and reproduce two properties observed in A. thaliana gene models: accessory loci show lower expression and higher non-synonymous substitution rates than core genes. Finally, accessory sequences were observed to preferentially encode transposon components in both species, plus disease resistance genes in cultivated barleys, and a variety of protein domains from other families that appear frequently associated with presence/absence variation in the literature. These results demonstrate that pan-genome analyses are useful to explore germplasm diversity.
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Affiliation(s)
- Bruno Contreras-Moreira
- Estación Experimental de Aula Dei - Consejo Superior de Investigaciones CientíficasZaragoza, Spain; Fundación ARAIDZaragoza, Spain
| | - Carlos P Cantalapiedra
- Estación Experimental de Aula Dei - Consejo Superior de Investigaciones Científicas Zaragoza, Spain
| | - María J García-Pereira
- Estación Experimental de Aula Dei - Consejo Superior de Investigaciones Científicas Zaragoza, Spain
| | | | - John P Vogel
- DOE Joint Genome Institute, Walnut Creek CA, USA
| | - Ernesto Igartua
- Estación Experimental de Aula Dei - Consejo Superior de Investigaciones Científicas Zaragoza, Spain
| | - Ana M Casas
- Estación Experimental de Aula Dei - Consejo Superior de Investigaciones Científicas Zaragoza, Spain
| | - Pablo Vinuesa
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México Cuernavaca, Mexico
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