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Kalairaj A, Rajendran S, Panda RC, Senthilvelan T. A study on waterlogging tolerance in sugarcane: a comprehensive review. Mol Biol Rep 2024; 51:747. [PMID: 38874798 DOI: 10.1007/s11033-024-09679-z] [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: 03/02/2024] [Accepted: 05/27/2024] [Indexed: 06/15/2024]
Abstract
Sugarcane (Saccharum officinarum) is an important crop, native to tropical and subtropical regions and it is a major source of sugar and Bioenergy in the world. Abiotic stress is defined as environmental conditions that reduce growth and yield below the optimum level. To tolerate these abiotic stresses, plants initiate several molecular, cellular, and physiological changes. These responses to abiotic stresses are dynamic and complex; they may be reversible or irreversible. Waterlogging is an abiotic stress phenomenon that drastically reduces the growth and survival of sugarcane, which leads to a 15-45% reduction in cane's yield. The extent of damage due to waterlogging depends on genotypes, environmental conditions, stage of development and duration of stress. An improved understanding of the physiological, biochemical, and molecular responses of sugarcane to waterlogging stress could help to develop new breeding strategies to sustain high yields against this situation. The present review offers a summary of recent findings on the adaptation of sugarcane to waterlogging stress in terms of growth and development, yield and quality, as well as biochemical and adaptive-molecular processes that may contribute to flooding tolerance.
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Affiliation(s)
- Ashmitha Kalairaj
- Department of Bioinformatics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Thandalam, Chennai, Tamilnadu, 602 105, India
| | - Swethashree Rajendran
- Department of Bioinformatics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Thandalam, Chennai, Tamilnadu, 602 105, India
| | - Rames C Panda
- Chemical Engineering Division, RajaLakshmi Engineering College, Thandalam, Chennai, Tamilnadu, 602 105, India
| | - T Senthilvelan
- Department of Bioinformatics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Thandalam, Chennai, Tamilnadu, 602 105, India.
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Healey AL, Garsmeur O, Lovell JT, Shengquiang S, Sreedasyam A, Jenkins J, Plott CB, Piperidis N, Pompidor N, Llaca V, Metcalfe CJ, Doležel J, Cápal P, Carlson JW, Hoarau JY, Hervouet C, Zini C, Dievart A, Lipzen A, Williams M, Boston LB, Webber J, Keymanesh K, Tejomurthula S, Rajasekar S, Suchecki R, Furtado A, May G, Parakkal P, Simmons BA, Barry K, Henry RJ, Grimwood J, Aitken KS, Schmutz J, D'Hont A. The complex polyploid genome architecture of sugarcane. Nature 2024; 628:804-810. [PMID: 38538783 PMCID: PMC11041754 DOI: 10.1038/s41586-024-07231-4] [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: 02/24/2023] [Accepted: 02/23/2024] [Indexed: 04/06/2024]
Abstract
Sugarcane, the world's most harvested crop by tonnage, has shaped global history, trade and geopolitics, and is currently responsible for 80% of sugar production worldwide1. While traditional sugarcane breeding methods have effectively generated cultivars adapted to new environments and pathogens, sugar yield improvements have recently plateaued2. The cessation of yield gains may be due to limited genetic diversity within breeding populations, long breeding cycles and the complexity of its genome, the latter preventing breeders from taking advantage of the recent explosion of whole-genome sequencing that has benefited many other crops. Thus, modern sugarcane hybrids are the last remaining major crop without a reference-quality genome. Here we take a major step towards advancing sugarcane biotechnology by generating a polyploid reference genome for R570, a typical modern cultivar derived from interspecific hybridization between the domesticated species (Saccharum officinarum) and the wild species (Saccharum spontaneum). In contrast to the existing single haplotype ('monoploid') representation of R570, our 8.7 billion base assembly contains a complete representation of unique DNA sequences across the approximately 12 chromosome copies in this polyploid genome. Using this highly contiguous genome assembly, we filled a previously unsized gap within an R570 physical genetic map to describe the likely causal genes underlying the single-copy Bru1 brown rust resistance locus. This polyploid genome assembly with fine-grain descriptions of genome architecture and molecular targets for biotechnology will help accelerate molecular and transgenic breeding and adaptation of sugarcane to future environmental conditions.
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Affiliation(s)
- A L Healey
- Genome Sequencing Center, HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA.
| | - O Garsmeur
- CIRAD, UMR AGAP Institut, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - J T Lovell
- Genome Sequencing Center, HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - S Shengquiang
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - A Sreedasyam
- Genome Sequencing Center, HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - J Jenkins
- Genome Sequencing Center, HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - C B Plott
- Genome Sequencing Center, HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - N Piperidis
- Sugar Research Australia, Te Kowai, Queensland, Australia
| | - N Pompidor
- CIRAD, UMR AGAP Institut, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - V Llaca
- Corteva Agriscience, Johnston, IA, USA
| | - C J Metcalfe
- CSIRO Agriculture and Food, Queensland Bioscience Precinct, St Lucia, Queensland, Australia
| | - J Doležel
- Institute of Experimental Botany of the Czech Academy of Sciences, Centre of Plant Structural and Functional Genomics, Olomouc, Czech Republic
| | - P Cápal
- Institute of Experimental Botany of the Czech Academy of Sciences, Centre of Plant Structural and Functional Genomics, Olomouc, Czech Republic
| | - J W Carlson
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - J Y Hoarau
- CIRAD, UMR AGAP Institut, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
- ERCANE, Sainte-Clotilde, La Réunion, France
| | - C Hervouet
- CIRAD, UMR AGAP Institut, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - C Zini
- CIRAD, UMR AGAP Institut, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - A Dievart
- CIRAD, UMR AGAP Institut, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - A Lipzen
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - M Williams
- Genome Sequencing Center, HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - L B Boston
- Genome Sequencing Center, HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - J Webber
- Genome Sequencing Center, HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - K Keymanesh
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - S Tejomurthula
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - S Rajasekar
- Arizona Genomics Institute, University of Arizona, Tucson, AZ, USA
| | - R Suchecki
- CSIRO Agriculture and Food, Urrbrae, South Australia, Australia
| | - A Furtado
- Queensland Alliance for Agriculture and Food Innovation, University of Queensland, Brisbane, Queensland, Australia
| | - G May
- Corteva Agriscience, Johnston, IA, USA
| | | | - B A Simmons
- Queensland Alliance for Agriculture and Food Innovation, University of Queensland, Brisbane, Queensland, Australia
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, USA
| | - K Barry
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - R J Henry
- Queensland Alliance for Agriculture and Food Innovation, University of Queensland, Brisbane, Queensland, Australia
- ARC Centre of Excellence for Plant Success in Nature and Agriculture, University of Queensland, Brisbane, Queensland, Australia
| | - J Grimwood
- Genome Sequencing Center, HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - K S Aitken
- CSIRO Agriculture and Food, Queensland Bioscience Precinct, St Lucia, Queensland, Australia
| | - J Schmutz
- Genome Sequencing Center, HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA.
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
| | - A D'Hont
- CIRAD, UMR AGAP Institut, Montpellier, France.
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France.
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Wen Z, Lin YH, Wang S, Fujiwara N, Rong R, Jin KW, Yang DM, Yao B, Yang S, Wang T, Xie Y, Hoshida Y, Zhu H, Xiao G. Deep-Learning-Based Hepatic Ploidy Quantification Using H&E Histopathology Images. Genes (Basel) 2023; 14:921. [PMID: 37107679 PMCID: PMC10137944 DOI: 10.3390/genes14040921] [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: 03/01/2023] [Revised: 03/28/2023] [Accepted: 04/11/2023] [Indexed: 04/29/2023] Open
Abstract
Polyploidy, the duplication of the entire genome within a single cell, is a significant characteristic of cells in many tissues, including the liver. The quantification of hepatic ploidy typically relies on flow cytometry and immunofluorescence (IF) imaging, which are not widely available in clinical settings due to high financial and time costs. To improve accessibility for clinical samples, we developed a computational algorithm to quantify hepatic ploidy using hematoxylin-eosin (H&E) histopathology images, which are commonly obtained during routine clinical practice. Our algorithm uses a deep learning model to first segment and classify different types of cell nuclei in H&E images. It then determines cellular ploidy based on the relative distance between identified hepatocyte nuclei and determines nuclear ploidy using a fitted Gaussian mixture model. The algorithm can establish the total number of hepatocytes and their detailed ploidy information in a region of interest (ROI) on H&E images. This is the first successful attempt to automate ploidy analysis on H&E images. Our algorithm is expected to serve as an important tool for studying the role of polyploidy in human liver disease.
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Affiliation(s)
- Zhuoyu Wen
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Yu-Hsuan Lin
- Children’s Research Institute, Departments of Pediatrics and Internal Medicine, Center for Regenerative Science and Medicine, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Shidan Wang
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Naoto Fujiwara
- Division of Digestive and Liver Diseases, Department of Internal Medicine, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Ruichen Rong
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Kevin W. Jin
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Donghan M. Yang
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Bo Yao
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Shengjie Yang
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Tao Wang
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Center for the Genetics of Host Defense, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Yang Xie
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Hamon Center for Regenerative Medicine, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Department of Bioinformatics, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Yujin Hoshida
- Division of Digestive and Liver Diseases, Department of Internal Medicine, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Hao Zhu
- Children’s Research Institute, Departments of Pediatrics and Internal Medicine, Center for Regenerative Science and Medicine, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Children’s Research Institute Mouse Genome Engineering Core, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Guanghua Xiao
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Hamon Center for Regenerative Medicine, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Department of Bioinformatics, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
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Cápal P, Said M, Molnár I, Doležel J. Flow Cytometric Analysis and Sorting of Plant Chromosomes. Methods Mol Biol 2023; 2672:177-200. [PMID: 37335476 DOI: 10.1007/978-1-0716-3226-0_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2023]
Abstract
Flow cytometry offers a unique way of analyzing and manipulating plant chromosomes. During a rapid movement in a liquid stream, large populations can be classified in a short time according to their fluorescence and light scatter properties. Chromosomes whose optical properties differ from other chromosomes in a karyotype can be purified by flow sorting and used in a range of applications in cytogenetics, molecular biology, genomics, and proteomics. As the samples for flow cytometry must be liquid suspensions of single particles, intact chromosomes must be released from mitotic cells. This protocol describes a procedure for preparation of suspensions of mitotic metaphase chromosomes from meristem root tips and their flow cytometric analysis and sorting for various downstream applications.
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Affiliation(s)
- Petr Cápal
- Institute of Experimental Botany of the Czech Academy of Sciences, Centre of Plant Structural and Functional Genomics, Olomouc, Czech Republic
| | - Mahmoud Said
- Institute of Experimental Botany of the Czech Academy of Sciences, Centre of Plant Structural and Functional Genomics, Olomouc, Czech Republic
- Field Crops Research Institute, Agricultural Research Centre, Giza, Cairo, Egypt
| | - István Molnár
- Institute of Experimental Botany of the Czech Academy of Sciences, Centre of Plant Structural and Functional Genomics, Olomouc, Czech Republic
- Agricultural Institute, Centre for Agricultural Research, ELKH, Martonvásár, Hungary
| | - Jaroslav Doležel
- Institute of Experimental Botany of the Czech Academy of Sciences, Centre of Plant Structural and Functional Genomics, Olomouc, Czech Republic.
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Metcalfe CJ, Li J, Zheng B, Stiller J, Healey A, Piperidis N, Aitken KS. Isolation and sequencing of a single copy of an introgressed chromosome from a complex genome for gene and SNP identification. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:1279-1292. [PMID: 35275251 DOI: 10.1007/s00122-022-04030-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 12/31/2021] [Indexed: 06/14/2023]
Abstract
This manuscript describes the identification, isolation and sequencing of a single chromosome containing high value resistance genes from a complex polyploid where sequencing the whole genome is too costly. The large complex genomes of many crops constrain the use of new technologies for genome-assisted selection and genetic improvement. One method to simplify a genome is to break it into individual chromosomes by flow cytometry; however, in many crop species most chromosomes cannot be isolated individually. Flow sorting of a single copy of a chromosome has been developed in wheat, and here we demonstrate its use to identify markers of interest in an Erianthus/Sacchurum hybrid. Erianthus/Saccharum hybrids are of interest because Erianthus is known to be highly resistant to soil borne diseases which cause extensive sugarcane yield losses in Australia. Sugarcane (Saccharum) cultivars are autopolyploids with a highly complex genome and over 100 chromosomes. Flow cytometry for sugarcane, as in most crops, does not resolve individual chromosomes to a karyotype peak for sorting. To isolate a single chromosome, we used genomic in situ hybridization (GISH) to identify the flow karyotype region containing the Erianthus chromosomes, flow sorted single chromosomes from this region, PCR screened for the Erianthus chromosomes and sequenced them. One Erianthus chromosome amplified and sequenced well, and from this data we could identify 57 resistant type genes and SNPs in nearly half of these genes. We developed KASP SNP assays and demonstrated that the identified SNP markers segregated as expected in a small introgression population. The pipeline we developed here to flow sort and sequence single chromosomes could be used in any crop with a large complex genome to rapidly discover and develop markers to important loci.
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Affiliation(s)
- Cushla J Metcalfe
- CSIRO Agriculture and Food, Queensland Biosciences Precinct, 306 Carmody Rd, St. Lucia, QLD, 4067, Australia
| | - Jingchuan Li
- CSIRO Agriculture and Food, Queensland Biosciences Precinct, 306 Carmody Rd, St. Lucia, QLD, 4067, Australia
| | - Bangyou Zheng
- CSIRO Agriculture and Food, Queensland Biosciences Precinct, 306 Carmody Rd, St. Lucia, QLD, 4067, Australia
| | - Jiri Stiller
- CSIRO Agriculture and Food, Queensland Biosciences Precinct, 306 Carmody Rd, St. Lucia, QLD, 4067, Australia
| | - Adam Healey
- HudsonAlpha Institute for Biotechnology, 601 Genome Way, Huntsville, AL, 35806, USA
| | | | - Karen S Aitken
- CSIRO Agriculture and Food, Queensland Biosciences Precinct, 306 Carmody Rd, St. Lucia, QLD, 4067, Australia.
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