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Machado IP, DoVale JC, Sabadin F, Fritsche-Neto R. On the usefulness of mock genomes to define heterotic pools, testers, and hybrid predictions in orphan crops. FRONTIERS IN PLANT SCIENCE 2023; 14:1164555. [PMID: 37332727 PMCID: PMC10272588 DOI: 10.3389/fpls.2023.1164555] [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: 02/13/2023] [Accepted: 05/10/2023] [Indexed: 06/20/2023]
Abstract
The advances in genomics in recent years have increased the accuracy and efficiency of breeding programs for many crops. Nevertheless, the adoption of genomic enhancement for several other crops essential in developing countries is still limited, especially for those that do not have a reference genome. These crops are more often called orphans. This is the first report to show how the results provided by different platforms, including the use of a simulated genome, called the mock genome, can generate in population structure and genetic diversity studies, especially when the intention is to use this information to support the formation of heterotic groups, choice of testers, and genomic prediction of single crosses. For that, we used a method to assemble a reference genome to perform the single-nucleotide polymorphism (SNP) calling without needing an external genome. Thus, we compared the analysis results using the mock genome with the standard approaches (array and genotyping-by-sequencing (GBS)). The results showed that the GBS-Mock presented similar results to the standard methods of genetic diversity studies, division of heterotic groups, the definition of testers, and genomic prediction. These results showed that a mock genome constructed from the population's intrinsic polymorphisms to perform the SNP calling is an effective alternative for conducting genomic studies of this nature in orphan crops, especially those that do not have a reference genome.
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Affiliation(s)
| | - Júlio César DoVale
- Department of Crop Science, Federal University of Ceará, Fortaleza, Brazil
| | - Felipe Sabadin
- School of Plant and Environmental Sciences, Virginia Tech: Virginia Polytechnic Institute and State University, Blacksburg, VA, United States
| | - Roberto Fritsche-Neto
- LSU AgCenter, Louisiana State University Agricultural Center, Baton Rouge, LA, United States
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Kumar P, Singh J, Kaur G, Adunola PM, Biswas A, Bazzer S, Kaur H, Kaur I, Kaur H, Sandhu KS, Vemula S, Kaur B, Singh V, Tseng TM. OMICS in Fodder Crops: Applications, Challenges, and Prospects. Curr Issues Mol Biol 2022; 44:5440-5473. [PMID: 36354681 PMCID: PMC9688858 DOI: 10.3390/cimb44110369] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 10/27/2022] [Accepted: 10/31/2022] [Indexed: 09/08/2024] Open
Abstract
Biomass yield and quality are the primary targets in forage crop improvement programs worldwide. Low-quality fodder reduces the quality of dairy products and affects cattle's health. In multipurpose crops, such as maize, sorghum, cowpea, alfalfa, and oat, a plethora of morphological and biochemical/nutritional quality studies have been conducted. However, the overall growth in fodder quality improvement is not on par with cereals or major food crops. The use of advanced technologies, such as multi-omics, has increased crop improvement programs manyfold. Traits such as stay-green, the number of tillers per plant, total biomass, and tolerance to biotic and/or abiotic stresses can be targeted in fodder crop improvement programs. Omic technologies, namely genomics, transcriptomics, proteomics, metabolomics, and phenomics, provide an efficient way to develop better cultivars. There is an abundance of scope for fodder quality improvement by improving the forage nutrition quality, edible quality, and digestibility. The present review includes a brief description of the established omics technologies for five major fodder crops, i.e., sorghum, cowpea, maize, oats, and alfalfa. Additionally, current improvements and future perspectives have been highlighted.
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Affiliation(s)
- Pawan Kumar
- Agrotechnology Division, Council of Scientific and Industrial Research-Institute of Himalayan Bioresource Technology, Palampur 176061, India
- Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar 125004, India
| | - Jagmohan Singh
- Division of Plant Pathology, Indian Agricultural Research Institute, New Delhi 110012, India
- Krishi Vigyan Kendra, Guru Angad Dev Veterinary and Animal Science University, Barnala 148107, India
| | - Gurleen Kaur
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32611, USA
| | | | - Anju Biswas
- Agronomy Department, University of Florida, Gainesville, FL 32611, USA
| | - Sumandeep Bazzer
- Department of Agronomy, Horticulture, and Plant Science, South Dakota State University, Brookings, WA 57007, USA
| | - Harpreet Kaur
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM 88001, USA
| | - Ishveen Kaur
- Department of Biological Sciences, Auburn University, Auburn, AL 36849, USA
| | - Harpreet Kaur
- Department of Agricultural and Environmental Sciences, Tennessee State University, Nashville, TN 37209, USA
| | - Karansher Singh Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA 99163, USA
| | - Shailaja Vemula
- Agronomy Department, UF/IFAS Research and Education Center, Belle Glade, FL 33430, USA
| | - Balwinder Kaur
- Department of Entomology, UF/IFAS Research and Education Center, Belle Glade, FL 33430, USA
| | - Varsha Singh
- Department of Plant and Soil Sciences, Mississippi State University, Starkville, MS 39759, USA
| | - Te Ming Tseng
- Department of Plant and Soil Sciences, Mississippi State University, Starkville, MS 39759, USA
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Matova PM, Kamutando CN, Magorokosho C, Kutywayo D, Gutsa F, Labuschagne M. Fall-armyworm invasion, control practices and resistance breeding in Sub-Saharan Africa. CROP SCIENCE 2020; 60:2951-2970. [PMID: 33328691 PMCID: PMC7702106 DOI: 10.1002/csc2.20317] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 08/25/2020] [Accepted: 08/25/2020] [Indexed: 05/02/2023]
Abstract
Fall armyworm [Spodoptera frugiperda (J.E. Smith); FAW] invasion has exacerbated maize (Zea mays L.) crop yield losses in sub-Saharan Africa (SSA), already threatened by other stresses, especially those that are climate-change induced. The FAW is difficult to control, manage, or eradicate, because it is polyphagous and trans-boundary, multiplies fast, has a short life cycle and migrates easily, and lacks the diapause growth phase. In this study, FAW and its impact in Africa was reviewed, as well as past and present control strategies for this pest. Pesticides, cultural practices, natural enemies, host-plant resistance, integrated pest management (IPM), and plant breeding approaches were examined as possible control strategies. It was concluded that an IPM control strategy, guided by cultural approaches already being used by farmers, and what can be adopted from the Americas, coupled with an insect-resistance management strategy, is the best option to manage this pest in Africa. These strategies will be strengthened by breeding for multi-trait host-plant resistance through stacking of genes for different modes of control of the pest.
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Affiliation(s)
- Prince M. Matova
- Department of Research and Specialist ServicesCrop Breeding Institute5th Street ExtensionHarareZimbabwe
- International Maize and Wheat Improvement CentreHarareZimbabwe
- Department of Plant SciencesUniversity of the Free StateBloemfonteinSouth Africa
| | | | | | - Dumisani Kutywayo
- Department of Research and Specialist ServicesCrop Breeding Institute5th Street ExtensionHarareZimbabwe
| | - Freeman Gutsa
- Department of Research and Specialist ServicesCrop Breeding Institute5th Street ExtensionHarareZimbabwe
| | - Maryke Labuschagne
- Department of Plant SciencesUniversity of the Free StateBloemfonteinSouth Africa
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Piereck B, Oliveira-Lima M, Benko-Iseppon AM, Diehl S, Schneider R, Brasileiro-Vidal AC, Barbosa-Silva A. LAITOR4HPC: A text mining pipeline based on HPC for building interaction networks. BMC Bioinformatics 2020; 21:365. [PMID: 32838742 PMCID: PMC7447576 DOI: 10.1186/s12859-020-03620-4] [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: 06/14/2019] [Accepted: 06/19/2020] [Indexed: 11/11/2022] Open
Abstract
Background The amount of published full-text articles has increased dramatically. Text mining tools configure an essential approach to building biological networks, updating databases and providing annotation for new pathways. PESCADOR is an online web server based on LAITOR and NLProt text mining tools, which retrieves protein-protein co-occurrences in a tabular-based format, adding a network schema. Here we present an HPC-oriented version of PESCADOR’s native text mining tool, renamed to LAITOR4HPC, aiming to access an unlimited abstract amount in a short time to enrich available networks, build new ones and possibly highlight whether fields of research have been exhaustively studied. Results By taking advantage of parallel computing HPC infrastructure, the full collection of MEDLINE abstracts available until June 2017 was analyzed in a shorter period (6 days) when compared to the original online implementation (with an estimated 2 years to run the same data). Additionally, three case studies were presented to illustrate LAITOR4HPC usage possibilities. The first case study targeted soybean and was used to retrieve an overview of published co-occurrences in a single organism, retrieving 15,788 proteins in 7894 co-occurrences. In the second case study, a target gene family was searched in many organisms, by analyzing 15 species under biotic stress. Most co-occurrences regarded Arabidopsis thaliana and Zea mays. The third case study concerned the construction and enrichment of an available pathway. Choosing A. thaliana for further analysis, the defensin pathway was enriched, showing additional signaling and regulation molecules, and how they respond to each other in the modulation of this complex plant defense response. Conclusions LAITOR4HPC can be used for an efficient text mining based construction of biological networks derived from big data sources, such as MEDLINE abstracts. Time consumption and data input limitations will depend on the available resources at the HPC facility. LAITOR4HPC enables enough flexibility for different approaches and data amounts targeted to an organism, a subject, or a specific pathway. Additionally, it can deliver comprehensive results where interactions are classified into four types, according to their reliability.
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Affiliation(s)
- Bruna Piereck
- Genetics Department, Laboratório de Genética e Biologia Vegetal, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil
| | - Marx Oliveira-Lima
- Genetics Department, Laboratório de Genética e Biologia Vegetal, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil
| | - Ana Maria Benko-Iseppon
- Genetics Department, Laboratório de Genética e Biologia Vegetal, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil.
| | - Sarah Diehl
- University of Luxembourg, Luxembourg Centre for Systems Biomedicine, Bioinformatics Core, Esch-sur-Alzette, Luxembourg
| | - Reinhard Schneider
- University of Luxembourg, Luxembourg Centre for Systems Biomedicine, Bioinformatics Core, Esch-sur-Alzette, Luxembourg
| | - Ana Christina Brasileiro-Vidal
- Genetics Department, Laboratório de Genética e Biologia Vegetal, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil
| | - Adriano Barbosa-Silva
- University of Luxembourg, Luxembourg Centre for Systems Biomedicine, Bioinformatics Core, Esch-sur-Alzette, Luxembourg. .,Queen Mary University of London, Centre for Translational Bioinformatics, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Charterhouse Square, London, UK.
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Genetic Basis of Maize Resistance to Multiple Insect Pests: Integrated Genome-Wide Comparative Mapping and Candidate Gene Prioritization. Genes (Basel) 2020; 11:genes11060689. [PMID: 32599710 PMCID: PMC7349181 DOI: 10.3390/genes11060689] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 05/30/2020] [Accepted: 06/01/2020] [Indexed: 01/01/2023] Open
Abstract
Several species of herbivores feed on maize in field and storage setups, making the development of multiple insect resistance a critical breeding target. In this study, an association mapping panel of 341 tropical maize lines was evaluated in three field environments for resistance to fall armyworm (FAW), whilst bulked grains were subjected to a maize weevil (MW) bioassay and genotyped with Diversity Array Technology's single nucleotide polymorphisms (SNPs) markers. A multi-locus genome-wide association study (GWAS) revealed 62 quantitative trait nucleotides (QTNs) associated with FAW and MW resistance traits on all 10 maize chromosomes, of which, 47 and 31 were discovered at stringent Bonferroni genome-wide significance levels of 0.05 and 0.01, respectively, and located within or close to multiple insect resistance genomic regions (MIRGRs) concerning FAW, SB, and MW. Sixteen QTNs influenced multiple traits, of which, six were associated with resistance to both FAW and MW, suggesting a pleiotropic genetic control. Functional prioritization of candidate genes (CGs) located within 10-30 kb of the QTNs revealed 64 putative GWAS-based CGs (GbCGs) showing evidence of involvement in plant defense mechanisms. Only one GbCG was associated with each of the five of the six combined resistance QTNs, thus reinforcing the pleiotropy hypothesis. In addition, through in silico co-functional network inferences, an additional 107 network-based CGs (NbCGs), biologically connected to the 64 GbCGs, and differentially expressed under biotic or abiotic stress, were revealed within MIRGRs. The provided multiple insect resistance physical map should contribute to the development of combined insect resistance in maize.
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Expression induction of a class of RD26 genes by drought and salinity stresses in maize. Biologia (Bratisl) 2019. [DOI: 10.2478/s11756-019-00286-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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