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Dwivedi SL, Heslop-Harrison P, Amas J, Ortiz R, Edwards D. Epistasis and pleiotropy-induced variation for plant breeding. PLANT BIOTECHNOLOGY JOURNAL 2024. [PMID: 38875130 DOI: 10.1111/pbi.14405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 05/07/2024] [Accepted: 05/24/2024] [Indexed: 06/16/2024]
Abstract
Epistasis refers to nonallelic interaction between genes that cause bias in estimates of genetic parameters for a phenotype with interactions of two or more genes affecting the same trait. Partitioning of epistatic effects allows true estimation of the genetic parameters affecting phenotypes. Multigenic variation plays a central role in the evolution of complex characteristics, among which pleiotropy, where a single gene affects several phenotypic characters, has a large influence. While pleiotropic interactions provide functional specificity, they increase the challenge of gene discovery and functional analysis. Overcoming pleiotropy-based phenotypic trade-offs offers potential for assisting breeding for complex traits. Modelling higher order nonallelic epistatic interaction, pleiotropy and non-pleiotropy-induced variation, and genotype × environment interaction in genomic selection may provide new paths to increase the productivity and stress tolerance for next generation of crop cultivars. Advances in statistical models, software and algorithm developments, and genomic research have facilitated dissecting the nature and extent of pleiotropy and epistasis. We overview emerging approaches to exploit positive (and avoid negative) epistatic and pleiotropic interactions in a plant breeding context, including developing avenues of artificial intelligence, novel exploitation of large-scale genomics and phenomics data, and involvement of genes with minor effects to analyse epistatic interactions and pleiotropic quantitative trait loci, including missing heritability.
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Affiliation(s)
| | - Pat Heslop-Harrison
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- Department of Genetics and Genome Biology, Institute for Environmental Futures, University of Leicester, Leicester, UK
| | - Junrey Amas
- Centre for Applied Bioinformatics, School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | - Rodomiro Ortiz
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - David Edwards
- Centre for Applied Bioinformatics, School of Biological Sciences, University of Western Australia, Perth, WA, Australia
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2
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Liu M, Zhang F, Lu H, Xue H, Dong X, Li Z, Xu J, Wang W, Wei C. PPanG: a precision pangenome browser enabling nucleotide-level analysis of genomic variations in individual genomes and their graph-based pangenome. BMC Genomics 2024; 25:405. [PMID: 38658835 PMCID: PMC11044437 DOI: 10.1186/s12864-024-10302-5] [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: 12/08/2023] [Accepted: 04/11/2024] [Indexed: 04/26/2024] Open
Abstract
Graph-based pangenome is gaining more popularity than linear pangenome because it stores more comprehensive information of variations. However, traditional linear genome browser has its own advantages, especially the tremendous resources accumulated historically. With the fast-growing number of individual genomes and their annotations available, the demand for a genome browser to visualize genome annotation for many individuals together with a graph-based pangenome is getting higher and higher. Here we report a new pangenome browser PPanG, a precise pangenome browser enabling nucleotide-level comparison of individual genome annotations together with a graph-based pangenome. Nine rice genomes with annotations were provided by default as potential references, and any individual genome can be selected as the reference. Our pangenome browser provides unprecedented insights on genome variations at different levels from base to gene, and reveals how the structures of a gene could differ for individuals. PPanG can be applied to any species with multiple individual genomes available and it is available at https://cgm.sjtu.edu.cn/PPanG .
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Affiliation(s)
- Mingwei Liu
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Fan Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
- College of Agronomy, Anhui Agricultural University, Hefei, 230036, China
| | - Huimin Lu
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Hongzhang Xue
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Xiaorui Dong
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Zhikang Li
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
- College of Agronomy, Anhui Agricultural University, Hefei, 230036, China
| | - Jianlong Xu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Wensheng Wang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China.
- College of Agronomy, Anhui Agricultural University, Hefei, 230036, China.
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China.
| | - Chaochun Wei
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
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3
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Hu H, Li R, Zhao J, Batley J, Edwards D. Technological Development and Advances for Constructing and Analyzing Plant Pangenomes. Genome Biol Evol 2024; 16:evae081. [PMID: 38669452 PMCID: PMC11058698 DOI: 10.1093/gbe/evae081] [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: 11/06/2023] [Revised: 04/09/2024] [Accepted: 04/11/2024] [Indexed: 04/28/2024] Open
Abstract
A pangenome captures the genomic diversity for a species, derived from a collection of genetic sequences of diverse populations. Advances in sequencing technologies have given rise to three primary methods for pangenome construction and analysis: de novo assembly and comparison, reference genome-based iterative assembly, and graph-based pangenome construction. Each method presents advantages and challenges in processing varying amounts and structures of DNA sequencing data. With the emergence of high-quality genome assemblies and advanced bioinformatic tools, the graph-based pangenome is emerging as an advanced reference for exploring the biological and functional implications of genetic variations.
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Affiliation(s)
- Haifei Hu
- Rice Research Institute, Guangdong Academy of Agricultural Sciences & Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangzhou 510640, China
| | - Risheng Li
- Rice Research Institute, Guangdong Academy of Agricultural Sciences & Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangzhou 510640, China
- College of Agriculture, South China Agricultural University, Guangzhou, Guangdong 510642, China
| | - Junliang Zhao
- Rice Research Institute, Guangdong Academy of Agricultural Sciences & Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangzhou 510640, China
| | - Jacqueline Batley
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | - David Edwards
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
- Centre for Applied Bioinformatics, University of Western Australia, Perth, WA 6009, Australia
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4
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Hu H, Scheben A, Wang J, Li F, Li C, Edwards D, Zhao J. Unravelling inversions: Technological advances, challenges, and potential impact on crop breeding. PLANT BIOTECHNOLOGY JOURNAL 2024; 22:544-554. [PMID: 37961986 PMCID: PMC10893937 DOI: 10.1111/pbi.14224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 10/11/2023] [Accepted: 10/22/2023] [Indexed: 11/15/2023]
Abstract
Inversions, a type of chromosomal structural variation, significantly influence plant adaptation and gene functions by impacting gene expression and recombination rates. However, compared with other structural variations, their roles in functional biology and crop improvement remain largely unexplored. In this review, we highlight technological and methodological advancements that have allowed a comprehensive understanding of inversion variants through the pangenome framework and machine learning algorithms. Genome editing is an efficient method for inducing or reversing inversion mutations in plants, providing an effective mechanism to modify local recombination rates. Given the potential of inversions in crop breeding, we anticipate increasing attention on inversions from the scientific community in future research and breeding applications.
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Affiliation(s)
- Haifei Hu
- Rice Research Institute, Guangdong Academy of Agricultural Sciences & Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co‐construction by Ministry and Province), Ministry of Agriculture and Rural Affairs & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering LaboratoryGuangzhouChina
| | - Armin Scheben
- Simons Center for Quantitative Biology, Cold Spring Harbor LaboratoryCold Spring HarborNew YorkUSA
| | - Jian Wang
- Rice Research Institute, Guangdong Academy of Agricultural Sciences & Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co‐construction by Ministry and Province), Ministry of Agriculture and Rural Affairs & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering LaboratoryGuangzhouChina
| | - Fangping Li
- Guangdong Provincial Key Laboratory of Plant Molecular Breeding, State Key Laboratory for Conservation and Utilization of Subtropical Agro‐BioresourcesSouth China Agricultural UniversityGuangzhouChina
| | - Chengdao Li
- Western Crop Genetics Alliance, Centre for Crop & Food Innovation, Food Futures Institute, College of Science, Health, Engineering and EducationMurdoch UniversityMurdochWestern AustraliaAustralia
| | - David Edwards
- School of Biological SciencesUniversity of Western AustraliaPerthWestern AustraliaAustralia
- Australia & Centre for Applied BioinformaticsUniversity of Western AustraliaPerthWestern AustraliaAustralia
| | - Junliang Zhao
- Rice Research Institute, Guangdong Academy of Agricultural Sciences & Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co‐construction by Ministry and Province), Ministry of Agriculture and Rural Affairs & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering LaboratoryGuangzhouChina
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5
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Wang Z, Miao L, Chen Y, Peng H, Ni Z, Sun Q, Guo W. Deciphering the evolution and complexity of wheat germplasm from a genomic perspective. J Genet Genomics 2023; 50:846-860. [PMID: 37611848 DOI: 10.1016/j.jgg.2023.08.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 07/29/2023] [Accepted: 08/09/2023] [Indexed: 08/25/2023]
Abstract
Bread wheat provides an essential fraction of the daily calorific intake for humanity. Due to its huge and complex genome, progress in studying on the wheat genome is substantially trailed behind those of the other two major crops, rice and maize, for at least a decade. With rapid advances in genome assembling and reduced cost of high-throughput sequencing, emerging de novo genome assemblies of wheat and whole-genome sequencing data are leading to a paradigm shift in wheat research. Here, we review recent progress in dissecting the complex genome and germplasm evolution of wheat since the release of the first high-quality wheat genome. New insights have been gained in the evolution of wheat germplasm during domestication and modern breeding progress, genomic variations at multiple scales contributing to the diversity of wheat germplasm, and complex transcriptional and epigenetic regulations of functional genes in polyploid wheat. Genomics databases and bioinformatics tools meeting the urgent needs of wheat genomics research are also summarized. The ever-increasing omics data, along with advanced tools and well-structured databases, are expected to accelerate deciphering the germplasm and gene resources in wheat for future breeding advances.
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Affiliation(s)
- Zihao Wang
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Lingfeng Miao
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Yongming Chen
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Huiru Peng
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Zhongfu Ni
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Qixin Sun
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Weilong Guo
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China.
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6
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Naithani S, Deng CH, Sahu SK, Jaiswal P. Exploring Pan-Genomes: An Overview of Resources and Tools for Unraveling Structure, Function, and Evolution of Crop Genes and Genomes. Biomolecules 2023; 13:1403. [PMID: 37759803 PMCID: PMC10527062 DOI: 10.3390/biom13091403] [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: 07/31/2023] [Revised: 08/29/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
The availability of multiple sequenced genomes from a single species made it possible to explore intra- and inter-specific genomic comparisons at higher resolution and build clade-specific pan-genomes of several crops. The pan-genomes of crops constructed from various cultivars, accessions, landraces, and wild ancestral species represent a compendium of genes and structural variations and allow researchers to search for the novel genes and alleles that were inadvertently lost in domesticated crops during the historical process of crop domestication or in the process of extensive plant breeding. Fortunately, many valuable genes and alleles associated with desirable traits like disease resistance, abiotic stress tolerance, plant architecture, and nutrition qualities exist in landraces, ancestral species, and crop wild relatives. The novel genes from the wild ancestors and landraces can be introduced back to high-yielding varieties of modern crops by implementing classical plant breeding, genomic selection, and transgenic/gene editing approaches. Thus, pan-genomic represents a great leap in plant research and offers new avenues for targeted breeding to mitigate the impact of global climate change. Here, we summarize the tools used for pan-genome assembly and annotations, web-portals hosting plant pan-genomes, etc. Furthermore, we highlight a few discoveries made in crops using the pan-genomic approach and future potential of this emerging field of study.
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Affiliation(s)
- Sushma Naithani
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA;
| | - Cecilia H. Deng
- Molecular & Digital Breeing Group, New Cultivar Innovation, The New Zealand Institute for Plant and Food Research Limited, Private Bag 92169, Auckland 1142, New Zealand;
| | - Sunil Kumar Sahu
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen 518083, China;
| | - Pankaj Jaiswal
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA;
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7
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Rodríguez-Suárez C, Requena-Ramírez MD, Hornero-Méndez D, Atienza SG. Towards carotenoid biofortification in wheat: identification of XAT-7A1, a multicopy tandem gene responsible for carotenoid esterification in durum wheat. BMC PLANT BIOLOGY 2023; 23:412. [PMID: 37674126 PMCID: PMC10481513 DOI: 10.1186/s12870-023-04431-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 08/31/2023] [Indexed: 09/08/2023]
Abstract
Yellow pigment content, mainly due to the accumulation of carotenoids, is a quality trait in durum wheat grain as it confers the bright yellow color to pasta preferred by consumers. Also, carotenoids are essential nutrients exerting important biological functions in human health. Consequently, biofortification strategies have been developed in many crops to increase carotenoid content. In this context, carotenoid esterification is emerging as a new breeding target for wheat biofortification, as carotenoid esters have been found to promote both carotenoid accumulation and stability. Until recently, no carotenoid esters have been identified in significant proportions in durum wheat grains, and interspecific breeding programs have been started to transfer esterification ability from common wheat and Hordeum chilense.In this work, XAT-7A1 is identified as the gene responsible for carotenoid esterification in durum wheat. Sequencing, copy number variation and mapping results show that XAT-7A1 is organized as tandem or proximal GDSL esterase/lipase copies in chromosome 7A. Three XAT-7A1 haplotypes are described: Type 1 copies, associated with high levels of carotenoid esters (diesters and monoesters) production and high expression in grain development; Type 2 copies, present in landraces with low levels of carotenoid esters (monoesters) or no esters; and Type 3 copies, without the signal peptide, resulting in zero-ester phenotypes.The identification of XAT-7A1 is a necessary step to make the carotenoid esterification ability available for durum and bread wheat breeding, which should be focused on the Type 1 XAT-7A1 haplotype, which may be assessed as a single gene since XAT-7A1 copies are inherited together.
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Affiliation(s)
- C Rodríguez-Suárez
- Institute for Sustainable Agriculture, CSIC, Avda, Menéndez Pidal s/n, E-14004, Córdoba, Spain
| | - M D Requena-Ramírez
- Institute for Sustainable Agriculture, CSIC, Avda, Menéndez Pidal s/n, E-14004, Córdoba, Spain
| | - D Hornero-Méndez
- Department of Food Phytochemistry, Instituto de la Grasa, CSIC. Campus Universidad Pablo de Olavide, Edificio 46. Ctra. de Utrera, Km 1, E-41013, Sevilla, Spain
| | - S G Atienza
- Institute for Sustainable Agriculture, CSIC, Avda, Menéndez Pidal s/n, E-14004, Córdoba, Spain.
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8
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Song B, Ning W, Wei D, Jiang M, Zhu K, Wang X, Edwards D, Odeny DA, Cheng S. Plant genome resequencing and population genomics: Current status and future prospects. MOLECULAR PLANT 2023; 16:1252-1268. [PMID: 37501370 DOI: 10.1016/j.molp.2023.07.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 05/30/2023] [Accepted: 07/25/2023] [Indexed: 07/29/2023]
Abstract
Advances in DNA sequencing technology have sparked a genomics revolution, driving breakthroughs in plant genetics and crop breeding. Recently, the focus has shifted from cataloging genetic diversity in plants to exploring their functional significance and delivering beneficial alleles for crop improvement. This transformation has been facilitated by the increasing adoption of whole-genome resequencing. In this review, we summarize the current progress of population-based genome resequencing studies and how these studies affect crop breeding. A total of 187 land plants from 163 countries have been resequenced, comprising 54 413 accessions. As part of resequencing efforts 367 traits have been surveyed and 86 genome-wide association studies have been conducted. Economically important crops, particularly cereals, vegetables, and legumes, have dominated the resequencing efforts, leaving a gap in 49 orders, including Lycopodiales, Liliales, Acorales, Austrobaileyales, and Commelinales. The resequenced germplasm is distributed across diverse geographic locations, providing a global perspective on plant genomics. We highlight genes that have been selected during domestication, or associated with agronomic traits, and form a repository of candidate genes for future research and application. Despite the opportunities for cross-species comparative genomics, many population genomic datasets are not accessible, impeding secondary analyses. We call for a more open and collaborative approach to population genomics that promotes data sharing and encourages contribution-based credit policy. The number of plant genome resequencing studies will continue to rise with the decreasing DNA sequencing costs, coupled with advances in analysis and computational technologies. This expansion, in terms of both scale and quality, holds promise for deeper insights into plant trait genetics and breeding design.
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Affiliation(s)
- Bo Song
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Weidong Ning
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; Huazhong Agricultural University, College of Informatics, Hubei Key Laboratory of Agricultural Bioinformatics, Wuhan, Hubei, China
| | - Di Wei
- Biotechnology Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 53007, China
| | - Mengyun Jiang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - Kun Zhu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - Xingwei Wang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - David Edwards
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA, Australia
| | - Damaris A Odeny
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) - Eastern and Southern Africa, Nairobi, Kenya
| | - Shifeng Cheng
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China.
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Ruperao P, Rangan P, Shah T, Thakur V, Kalia S, Mayes S, Rathore A. The Progression in Developing Genomic Resources for Crop Improvement. Life (Basel) 2023; 13:1668. [PMID: 37629524 PMCID: PMC10455509 DOI: 10.3390/life13081668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/21/2023] [Accepted: 07/25/2023] [Indexed: 08/27/2023] Open
Abstract
Sequencing technologies have rapidly evolved over the past two decades, and new technologies are being continually developed and commercialized. The emerging sequencing technologies target generating more data with fewer inputs and at lower costs. This has also translated to an increase in the number and type of corresponding applications in genomics besides enhanced computational capacities (both hardware and software). Alongside the evolving DNA sequencing landscape, bioinformatics research teams have also evolved to accommodate the increasingly demanding techniques used to combine and interpret data, leading to many researchers moving from the lab to the computer. The rich history of DNA sequencing has paved the way for new insights and the development of new analysis methods. Understanding and learning from past technologies can help with the progress of future applications. This review focuses on the evolution of sequencing technologies, their significant enabling role in generating plant genome assemblies and downstream applications, and the parallel development of bioinformatics tools and skills, filling the gap in data analysis techniques.
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Affiliation(s)
- Pradeep Ruperao
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502324, India
| | - Parimalan Rangan
- ICAR-National Bureau of Plant Genetic Resources, PUSA Campus, New Delhi 110012, India;
| | - Trushar Shah
- International Institute of Tropical Agriculture (IITA), Nairobi 30709-00100, Kenya;
| | - Vivek Thakur
- Department of Systems & Computational Biology, School of Life Sciences, University of Hyderabad, Hyderabad 500046, India;
| | - Sanjay Kalia
- Department of Biotechnology, Ministry of Science and Technology, Government of India, New Delhi 110003, India;
| | - Sean Mayes
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502324, India
| | - Abhishek Rathore
- Excellence in Breeding, International Maize and Wheat Improvement Center (CIMMYT), Hyderabad 502324, India
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10
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Kettenburg AT, Lopez MA, Yogendra K, Prior MJ, Rose T, Bimson S, Heuer S, Roy SJ, Bailey-Serres J. PHOSPHORUS-STARVATION TOLERANCE 1 (OsPSTOL1) is prevalent in upland rice and enhances root growth and hastens low phosphate signaling in wheat. PLANT, CELL & ENVIRONMENT 2023; 46:2187-2205. [PMID: 36946067 DOI: 10.1111/pce.14588] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 03/07/2023] [Accepted: 03/19/2023] [Indexed: 06/08/2023]
Abstract
PHOSPHORUS-STARVATION TOLERANCE 1 (OsPSTOL1) is a variably present gene that benefits crown root growth and phosphorus (P) sufficiency in rice (Oryza sativa). To explore the ecophysiological importance of this gene, we performed a biogeographic survey of landraces and cultivars, confirming that functional OsPSTOL1 alleles prevail in low nutrient and drought-prone rainfed ecosystems, whereas loss-of-function and absence haplotypes predominate in control-irrigated paddy varieties of east Asia. An evolutionary history analysis of OsPSTOL1 and related genes in cereal, determined it and other genes are kinase-only domain derivatives of membrane-associated receptor like kinases. Finally, to evaluate the potential value of this kinase of unknown function in another Gramineae, wheat (Triticum aestivum) lines overexpressing OsPSTOL1 were evaluated under field and controlled low P conditions. OsPSTOL1 enhances growth, crown root number, and overall root plasticity under low P in wheat. Survey of root and shoot crown transcriptomes at two developmental stages identifies transcription factors that are differentially regulated in OsPSTOL1 wheat that are similarly controlled by the gene in rice. In wheat, OsPSTOL1 alters the timing and amplitude of regulators of root development in dry soils and hastens induction of the core P-starvation response. OsPSTOL1 and related genes may aid more sustainable cultivation of cereal crops.
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Affiliation(s)
- Alek T Kettenburg
- Botany and Plant Sciences Department, Center for Plant Cell Biology, University of California, Riverside, California, USA
| | - Miguel A Lopez
- Botany and Plant Sciences Department, Center for Plant Cell Biology, University of California, Riverside, California, USA
| | - Kalenahalli Yogendra
- School of Agriculture, Food and Wine & Waite Research Institute, The University of Adelaide, Adelaide, South Australia, Australia
- ARC Industrial Transformation Research Hub for Wheat in a Hot and Dry Climate, The University of Adelaide, Adelaide, South Australia, Australia
| | - Matthew J Prior
- Botany and Plant Sciences Department, Center for Plant Cell Biology, University of California, Riverside, California, USA
| | - Teresa Rose
- Department of Plant Science, Rothamsted Research, Harpenden, Hertfordshire, UK
| | - Sabrina Bimson
- Botany and Plant Sciences Department, Center for Plant Cell Biology, University of California, Riverside, California, USA
| | - Sigrid Heuer
- School of Agriculture, Food and Wine & Waite Research Institute, The University of Adelaide, Adelaide, South Australia, Australia
- Department of Plant Science, Rothamsted Research, Harpenden, Hertfordshire, UK
| | - Stuart J Roy
- School of Agriculture, Food and Wine & Waite Research Institute, The University of Adelaide, Adelaide, South Australia, Australia
- ARC Industrial Transformation Research Hub for Wheat in a Hot and Dry Climate, The University of Adelaide, Adelaide, South Australia, Australia
| | - Julia Bailey-Serres
- Botany and Plant Sciences Department, Center for Plant Cell Biology, University of California, Riverside, California, USA
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Wang J, Yang W, Zhang S, Hu H, Yuan Y, Dong J, Chen L, Ma Y, Yang T, Zhou L, Chen J, Liu B, Li C, Edwards D, Zhao J. A pangenome analysis pipeline provides insights into functional gene identification in rice. Genome Biol 2023; 24:19. [PMID: 36703158 PMCID: PMC9878884 DOI: 10.1186/s13059-023-02861-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 01/18/2023] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND A pangenome aims to capture the complete genetic diversity within a species and reduce bias in genetic analysis inherent in using a single reference genome. However, the current linear format of most plant pangenomes limits the presentation of position information for novel sequences. Graph pangenomes have been developed to overcome this limitation. However, bioinformatics analysis tools for graph format genomes are lacking. RESULTS To overcome this problem, we develop a novel strategy for pangenome construction and a downstream pangenome analysis pipeline (PSVCP) that captures genetic variants' position information while maintaining a linearized layout. Using PSVCP, we construct a high-quality rice pangenome using 12 representative rice genomes and analyze an international rice panel with 413 diverse accessions using the pangenome as the reference. We show that PSVCP successfully identifies causal structural variations for rice grain weight and plant height. Our results provide insights into rice population structure and genomic diversity. We characterize a new locus (qPH8-1) associated with plant height on chromosome 8 undetected by the SNP-based genome-wide association study (GWAS). CONCLUSIONS Our results demonstrate that the pangenome constructed by our pipeline combined with a presence and absence variation-based GWAS can provide additional power for genomic and genetic analysis. The pangenome constructed in this study and the associated genome sequence and genetic variants data provide valuable genomic resources for rice genomics research and improvement in future.
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Affiliation(s)
- Jian Wang
- grid.135769.f0000 0001 0561 6611Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640 China
| | - Wu Yang
- grid.135769.f0000 0001 0561 6611Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640 China
| | - Shaohong Zhang
- grid.135769.f0000 0001 0561 6611Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640 China
| | - Haifei Hu
- grid.135769.f0000 0001 0561 6611Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640 China ,grid.1025.60000 0004 0436 6763Western Crop Genetics Alliance, Murdoch University, Murdoch, Western Australia 6150 Australia
| | - Yuxuan Yuan
- grid.10784.3a0000 0004 1937 0482School of Life Sciences and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong, SAR China
| | - Jingfang Dong
- grid.135769.f0000 0001 0561 6611Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640 China
| | - Luo Chen
- grid.135769.f0000 0001 0561 6611Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640 China
| | - Yamei Ma
- grid.135769.f0000 0001 0561 6611Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640 China
| | - Tifeng Yang
- grid.135769.f0000 0001 0561 6611Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640 China
| | - Lian Zhou
- grid.135769.f0000 0001 0561 6611Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640 China
| | - Jiansong Chen
- grid.135769.f0000 0001 0561 6611Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640 China
| | - Bin Liu
- grid.135769.f0000 0001 0561 6611Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640 China
| | - Chengdao Li
- grid.1025.60000 0004 0436 6763Western Crop Genetics Alliance, Murdoch University, Murdoch, Western Australia 6150 Australia
| | - David Edwards
- grid.1012.20000 0004 1936 7910School of Biological Sciences and Centre for Applied Bioinformatics, University of Western Australia, Perth, WA Australia
| | - Junliang Zhao
- grid.135769.f0000 0001 0561 6611Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640 China
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Bayer PE, Edwards D. Investigating Pangenome Graphs Using Wheat Panache. Methods Mol Biol 2023; 2703:23-29. [PMID: 37646934 DOI: 10.1007/978-1-0716-3389-2_2] [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] [Indexed: 09/01/2023]
Abstract
Pangenome graphs quickly become the central data structure representing the diversity of variation we see across related genomes. Pangenome graphs have been published for some species, including plants of agronomic interest. However, visualizing these graphs is not easy as the graphs are large, and variants within these graphs are complex. Tools are needed to visualize graph data structures. Here, we present a workflow to search and visualize a wheat pangenome graph using Wheat Panache. The approach presented assists researchers interested in wheat genomics.
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Affiliation(s)
- Philipp E Bayer
- Centre for Applied Bioinformatics and School of Biological Sciences, The University of Western Australia, Perth, WA, Australia
| | - David Edwards
- Centre for Applied Bioinformatics and School of Biological Sciences, The University of Western Australia, Perth, WA, Australia.
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13
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Wang S, Qian YQ, Zhao RP, Chen LL, Song JM. Graph-based pan-genomes: increased opportunities in plant genomics. JOURNAL OF EXPERIMENTAL BOTANY 2023; 74:24-39. [PMID: 36255144 DOI: 10.1093/jxb/erac412] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 10/17/2022] [Indexed: 06/16/2023]
Abstract
Due to the development of sequencing technology and the great reduction in sequencing costs, an increasing number of plant genomes have been assembled, and numerous genomes have revealed large amounts of variations. However, a single reference genome does not allow the exploration of species diversity, and therefore the concept of pan-genome was developed. A pan-genome is a collection of all sequences available for a species, including a large number of consensus sequences, large structural variations, and small variations including single nucleotide polymorphisms and insertions/deletions. A simple linear pan-genome does not allow these structural variations to be intuitively characterized, so graph-based pan-genomes have been developed. These pan-genomes store sequence and structural variation information in the form of nodes and paths to store and display species variation information in a more intuitive manner. The key role of graph-based pan-genomes is to expand the coordinate system of the linear reference genome to accommodate more regions of genetic diversity. Here, we review the origin and development of graph-based pan-genomes, explore their application in plant research, and further highlight the application of graph-based pan-genomes for future plant breeding.
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Affiliation(s)
- Shuo Wang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, College of Life Science and Technology, Guangxi University, Nanning, 530004, China
- National Key Laboratory of Crop Genetic Improvement, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China
| | - Yong-Qing Qian
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, College of Life Science and Technology, Guangxi University, Nanning, 530004, China
| | - Ru-Peng Zhao
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, College of Life Science and Technology, Guangxi University, Nanning, 530004, China
| | - 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
| | - Jia-Ming Song
- 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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Mahmood U, Li X, Fan Y, Chang W, Niu Y, Li J, Qu C, Lu K. Multi-omics revolution to promote plant breeding efficiency. FRONTIERS IN PLANT SCIENCE 2022; 13:1062952. [PMID: 36570904 PMCID: PMC9773847 DOI: 10.3389/fpls.2022.1062952] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 11/24/2022] [Indexed: 06/17/2023]
Abstract
Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under increasing pressure from the rising food demand of the rapidly growing world population and changing climate. To address these issues, improving high-yield and climate-resilient related-traits in crop breeding is an effective strategy. In recent years, advances in omics techniques, including genomics, transcriptomics, proteomics, and metabolomics, paved the way for accelerating plant/crop breeding to cope with the changing climate and enhance food production. Optimized omics and phenotypic plasticity platform integration, exploited by evolving machine learning algorithms will aid in the development of biological interpretations for complex crop traits. The precise and progressive assembly of desire alleles using precise genome editing approaches and enhanced breeding strategies would enable future crops to excel in combating the changing climates. Furthermore, plant breeding and genetic engineering ensures an exclusive approach to developing nutrient sufficient and climate-resilient crops, the productivity of which can sustainably and adequately meet the world's food, nutrition, and energy needs. This review provides an overview of how the integration of omics approaches could be exploited to select crop varieties with desired traits.
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Affiliation(s)
- Umer Mahmood
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
| | - Xiaodong Li
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
| | - Yonghai Fan
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
| | - Wei Chang
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
| | - Yue Niu
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
| | - Jiana Li
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
- Academy of Agricultural Sciences, Southwest University, Chongqing, China
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Chongqing, China
| | - Cunmin Qu
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
- Academy of Agricultural Sciences, Southwest University, Chongqing, China
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Chongqing, China
| | - Kun Lu
- Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City and Southwest University, College of Agronomy and Biotechnology, Southwest University, Chongqing, China
- Academy of Agricultural Sciences, Southwest University, Chongqing, China
- Engineering Research Center of South Upland Agriculture, Ministry of Education, Chongqing, China
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15
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Graph Pangenomes Track Genetic Variants for Crop Improvement. Int J Mol Sci 2022; 23:ijms232113420. [DOI: 10.3390/ijms232113420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/28/2022] [Accepted: 10/29/2022] [Indexed: 11/06/2022] Open
Abstract
Global climate change and the urgency to transform crops require an exhaustive genetic evaluation. The large polyploid genomes of food crops, such as cereals, make it difficult to identify candidate genes with confirmed hereditary. Although genome-wide association studies (GWAS) have been proficient in identifying genetic variants that are associated with complex traits, the resolution of acquired heritability faces several significant bottlenecks such as incomplete detection of structural variants (SV), genetic heterogeneity, and/or locus heterogeneity. Consequently, a biased estimate is generated with respect to agronomically complex traits. The graph pangenomes have resolved this missing heritability and provide significant details in terms of specific loci segregating among individuals and evolving to variations. The graph pangenome approach facilitates crop improvements through genome-linked fast breeding.
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