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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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2
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Nestor BJ, Bayer PE, Fernandez CGT, Edwards D, Finnegan PM. Approaches to increase the validity of gene family identification using manual homology search tools. Genetica 2023; 151:325-338. [PMID: 37817002 PMCID: PMC10692271 DOI: 10.1007/s10709-023-00196-8] [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: 06/07/2023] [Accepted: 10/01/2023] [Indexed: 10/12/2023]
Abstract
Identifying homologs is an important process in the analysis of genetic patterns underlying traits and evolutionary relationships among species. Analysis of gene families is often used to form and support hypotheses on genetic patterns such as gene presence, absence, or functional divergence which underlie traits examined in functional studies. These analyses often require precise identification of all members in a targeted gene family. Manual pipelines where homology search and orthology assignment tools are used separately are the most common approach for identifying small gene families where accurate identification of all members is important. The ability to curate sequences between steps in manual pipelines allows for simple and precise identification of all possible gene family members. However, the validity of such manual pipeline analyses is often decreased by inappropriate approaches to homology searches including too relaxed or stringent statistical thresholds, inappropriate query sequences, homology classification based on sequence similarity alone, and low-quality proteome or genome sequences. In this article, we propose several approaches to mitigate these issues and allow for precise identification of gene family members and support for hypotheses linking genetic patterns to functional traits.
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Affiliation(s)
- Benjamin J Nestor
- School of Biological Sciences, University of Western Australia, Perth, WA, 6009, Australia.
- Centre for Applied Bioinformatics, University of Western Australia, Perth, WA, 6009, Australia.
| | - Philipp E Bayer
- School of Biological Sciences, University of Western Australia, Perth, WA, 6009, Australia
- Centre for Applied Bioinformatics, University of Western Australia, Perth, WA, 6009, Australia
| | - Cassandria G Tay Fernandez
- School of Biological Sciences, University of Western Australia, Perth, WA, 6009, Australia
- Centre for Applied Bioinformatics, University of Western Australia, Perth, WA, 6009, Australia
| | - David Edwards
- School of Biological Sciences, University of Western Australia, Perth, WA, 6009, Australia
- Centre for Applied Bioinformatics, University of Western Australia, Perth, WA, 6009, Australia
| | - Patrick M Finnegan
- School of Biological Sciences, University of Western Australia, Perth, WA, 6009, Australia
- Centre for Applied Bioinformatics, University of Western Australia, Perth, WA, 6009, Australia
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3
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Abondio P, Cilli E, Luiselli D. Human Pangenomics: Promises and Challenges of a Distributed Genomic Reference. Life (Basel) 2023; 13:1360. [PMID: 37374141 DOI: 10.3390/life13061360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 06/02/2023] [Accepted: 06/08/2023] [Indexed: 06/29/2023] Open
Abstract
A pangenome is a collection of the common and unique genomes that are present in a given species. It combines the genetic information of all the genomes sampled, resulting in a large and diverse range of genetic material. Pangenomic analysis offers several advantages compared to traditional genomic research. For example, a pangenome is not bound by the physical constraints of a single genome, so it can capture more genetic variability. Thanks to the introduction of the concept of pangenome, it is possible to use exceedingly detailed sequence data to study the evolutionary history of two different species, or how populations within a species differ genetically. In the wake of the Human Pangenome Project, this review aims at discussing the advantages of the pangenome around human genetic variation, which are then framed around how pangenomic data can inform population genetics, phylogenetics, and public health policy by providing insights into the genetic basis of diseases or determining personalized treatments, targeting the specific genetic profile of an individual. Moreover, technical limitations, ethical concerns, and legal considerations are discussed.
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Affiliation(s)
- Paolo Abondio
- Laboratory of Ancient DNA, Department of Cultural Heritage, University of Bologna, Via degli Ariani 1, 48121 Ravenna, Italy
| | - Elisabetta Cilli
- Laboratory of Ancient DNA, Department of Cultural Heritage, University of Bologna, Via degli Ariani 1, 48121 Ravenna, Italy
| | - Donata Luiselli
- Laboratory of Ancient DNA, Department of Cultural Heritage, University of Bologna, Via degli Ariani 1, 48121 Ravenna, Italy
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Cooper M, Messina CD. Breeding crops for drought-affected environments and improved climate resilience. THE PLANT CELL 2023; 35:162-186. [PMID: 36370076 PMCID: PMC9806606 DOI: 10.1093/plcell/koac321] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 11/01/2022] [Indexed: 05/12/2023]
Abstract
Breeding climate-resilient crops with improved levels of abiotic and biotic stress resistance as a response to climate change presents both opportunities and challenges. Applying the framework of the "breeder's equation," which is used to predict the response to selection for a breeding program cycle, we review methodologies and strategies that have been used to successfully breed crops with improved levels of drought resistance, where the target population of environments (TPEs) is a spatially and temporally heterogeneous mixture of drought-affected and favorable (water-sufficient) environments. Long-term improvement of temperate maize for the US corn belt is used as a case study and compared with progress for other crops and geographies. Integration of trait information across scales, from genomes to ecosystems, is needed to accurately predict yield outcomes for genotypes within the current and future TPEs. This will require transdisciplinary teams to explore, identify, and exploit novel opportunities to accelerate breeding program outcomes; both improved germplasm resources and improved products (cultivars, hybrids, clones, and populations) that outperform and replace the products in use by farmers, in combination with modified agronomic management strategies suited to their local environments.
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Affiliation(s)
| | - Carlos D Messina
- Horticultural Sciences Department, University of Florida, Gainesville, Florida 32611, USA
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5
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Zandberg JD, Fernandez CT, Danilevicz MF, Thomas WJW, Edwards D, Batley J. The Global Assessment of Oilseed Brassica Crop Species Yield, Yield Stability and the Underlying Genetics. PLANTS (BASEL, SWITZERLAND) 2022; 11:2740. [PMID: 36297764 PMCID: PMC9610009 DOI: 10.3390/plants11202740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 10/08/2022] [Accepted: 10/09/2022] [Indexed: 06/16/2023]
Abstract
The global demand for oilseeds is increasing along with the human population. The family of Brassicaceae crops are no exception, typically harvested as a valuable source of oil, rich in beneficial molecules important for human health. The global capacity for improving Brassica yield has steadily risen over the last 50 years, with the major crop Brassica napus (rapeseed, canola) production increasing to ~72 Gt in 2020. In contrast, the production of Brassica mustard crops has fluctuated, rarely improving in farming efficiency. The drastic increase in global yield of B. napus is largely due to the demand for a stable source of cooking oil. Furthermore, with the adoption of highly efficient farming techniques, yield enhancement programs, breeding programs, the integration of high-throughput phenotyping technology and establishing the underlying genetics, B. napus yields have increased by >450 fold since 1978. Yield stability has been improved with new management strategies targeting diseases and pests, as well as by understanding the complex interaction of environment, phenotype and genotype. This review assesses the global yield and yield stability of agriculturally important oilseed Brassica species and discusses how contemporary farming and genetic techniques have driven improvements.
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Affiliation(s)
- Jaco D. Zandberg
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
| | | | - Monica F. Danilevicz
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
| | - William J. W. Thomas
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
| | - David Edwards
- Center for Applied Bioinformatics, School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
| | - Jacqueline Batley
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
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Pangenomics and Crop Genome Adaptation in a Changing Climate. PLANTS 2022; 11:plants11151949. [PMID: 35956427 PMCID: PMC9370458 DOI: 10.3390/plants11151949] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 07/18/2022] [Accepted: 07/19/2022] [Indexed: 12/15/2022]
Abstract
During crop domestication and breeding, wild plant species have been shaped into modern high-yield crops and adapted to the main agro-ecological regions. However, climate change will impact crop productivity in these regions, and agriculture needs to adapt to support future food production. On a global scale, crop wild relatives grow in more diverse environments than crop species, and so may host genes that could support the adaptation of crops to new and variable environments. Through identification of individuals with increased climate resilience we may gain a greater understanding of the genomic basis for this resilience and transfer this to crops. Pangenome analysis can help to identify the genes underlying stress responses in individuals harbouring untapped genomic diversity in crop wild relatives. The information gained from the analysis of these pangenomes can then be applied towards breeding climate resilience into existing crops or to re-domesticating crops, combining environmental adaptation traits with crop productivity.
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7
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Li W, Liu J, Zhang H, Liu Z, Wang Y, Xing L, He Q, Du H. Plant pan-genomics: recent advances, new challenges, and roads ahead. J Genet Genomics 2022; 49:833-846. [PMID: 35750315 DOI: 10.1016/j.jgg.2022.06.004] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 06/09/2022] [Accepted: 06/10/2022] [Indexed: 10/18/2022]
Abstract
Pan-genomics can encompass most of the genetic diversity of a species or population and has proved to be a powerful tool for studying genomic evolution and the origin and domestication of species, and for providing information for plant improvement. Plant genomics has greatly progressed because of improvements in sequencing technologies and the rapid reduction of sequencing costs. Nevertheless, pan-genomics still presents many challenges, including computationally intensive assembly methods, high costs with large numbers of samples, ineffective integration of big data, and difficulty in applying it to downstream multi-omics analysis and breeding research. In this review, we summarize the definition and recent achievements of plant pan-genomics, computational technologies used for pan-genome construction, and the applications of pan-genomes in plant genomics and molecular breeding. We also discuss challenges and perspectives for future pan-genomics studies and provide a detailed pipeline for sample selection, genome assembly and annotation, structural variation identification, and construction and application of graph-based pan-genomes. The aim is to provide important guidance for plant pan-genome research and a better understanding of the genetic basis of genome evolution, crop domestication, and phenotypic diversity for future studies.
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Affiliation(s)
- Wei Li
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China
| | - Jianan Liu
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China
| | - Hongyu Zhang
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China
| | - Ze Liu
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China
| | - Yu Wang
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China
| | - Longsheng Xing
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China
| | - Qiang He
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China
| | - Huilong Du
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China.
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8
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Mohd Saad NS, Neik TX, Thomas WJW, Amas JC, Cantila AY, Craig RJ, Edwards D, Batley J. Advancing designer crops for climate resilience through an integrated genomics approach. CURRENT OPINION IN PLANT BIOLOGY 2022; 67:102220. [PMID: 35489163 DOI: 10.1016/j.pbi.2022.102220] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 03/15/2022] [Accepted: 03/25/2022] [Indexed: 06/14/2023]
Abstract
Climate change and exponential population growth are exposing an immediate need for developing future crops that are highly resilient and adaptable to changing environments to maintain global food security in the next decade. Rigorous selection from long domestication history has rendered cultivated crops genetically disadvantaged, raising concerns in their ability to adapt to these new challenges and limiting their usefulness in breeding programmes. As a result, future crop improvement efforts must rely on integrating various genomic strategies ranging from high-throughput sequencing to machine learning, in order to exploit germplasm diversity and overcome bottlenecks created by domestication, expansive multi-dimensional phenotypes, arduous breeding processes, complex traits and big data.
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Affiliation(s)
- Nur Shuhadah Mohd Saad
- UWA School of Biological Sciences and the UWA Institute of Agriculture, University of Western Australia, Crawley, WA, Australia
| | - Ting Xiang Neik
- Sunway College Kuala Lumpur, Bandar Sunway, 47500, Selangor, Malaysia
| | - William J W Thomas
- UWA School of Biological Sciences and the UWA Institute of Agriculture, University of Western Australia, Crawley, WA, Australia
| | - Junrey C Amas
- UWA School of Biological Sciences and the UWA Institute of Agriculture, University of Western Australia, Crawley, WA, Australia
| | - Aldrin Y Cantila
- UWA School of Biological Sciences and the UWA Institute of Agriculture, University of Western Australia, Crawley, WA, Australia
| | - Ryan J Craig
- UWA School of Biological Sciences and the UWA Institute of Agriculture, University of Western Australia, Crawley, WA, Australia
| | - David Edwards
- UWA School of Biological Sciences and the UWA Institute of Agriculture, University of Western Australia, Crawley, WA, Australia
| | - Jacqueline Batley
- UWA School of Biological Sciences and the UWA Institute of Agriculture, University of Western Australia, Crawley, WA, Australia.
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