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Dou T, Wang C, Ma Y, Chen Z, Zhang J, Guo G. CoreSNP: an efficient pipeline for core marker profile selection from genome-wide SNP datasets in crops. BMC PLANT BIOLOGY 2023; 23:580. [PMID: 37986037 PMCID: PMC10662547 DOI: 10.1186/s12870-023-04609-w] [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: 09/14/2023] [Accepted: 11/14/2023] [Indexed: 11/22/2023]
Abstract
BACKGROUND DNA marker profiles play a crucial role in the identification and registration of germplasm, as well as in the distinctness, uniformity, and stability (DUS) testing of new plant variety protection. However, selecting minimal marker sets from large-scale SNP dataset can be challenging to distinguish a maximum number of samples. RESULTS Here, we developed the CoreSNP pipeline using a "divide and conquer" strategy and a "greedy" algorithm. The pipeline offers adjustable parameters to guarantee the distinction of each sample pair with at least two markers. Additionally, it allows datasets with missing loci as input. The pipeline was tested in barley, soybean, wheat, rice and maize. A few dozen of core SNPs were efficiently selected in different crops with SNP array, GBS, and WGS dataset, which can differentiate thousands of individual samples. The core SNPs were distributed across all chromosomes, exhibiting lower pairwise linkage disequilibrium (LD) and higher polymorphism information content (PIC) and minor allele frequencies (MAF). It was shown that both the genetic diversity of the population and the characteristics of the original dataset can significantly influence the number of core markers. In addition, the core SNPs capture a certain level of the original population structure. CONCLUSIONS CoreSNP is an efficiency way of core marker sets selection based on Genome-wide SNP datasets of crops. Combined with low-density SNP chip or genotyping technologies, it can be a cost-effective way to simplify and expedite the evaluation of genetic resources and differentiate different crop varieties. This tool is expected to have great application prospects in the rapid comparison of germplasm and intellectual property protection of new varieties.
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Affiliation(s)
- Tingyu Dou
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Chunchao Wang
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Yanling Ma
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Zhaoyan Chen
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Jing Zhang
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Ganggang Guo
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China.
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Zhao Y, Tian H, Li C, Yi H, Zhang Y, Li X, Zhao H, Huo Y, Wang R, Kang D, Lu Y, Liu Z, Liang Z, Xu L, Yang Y, Zhou L, Wang T, Zhao J, Wang F. HTPdb and HTPtools: Exploiting maize haplotype-tag polymorphisms for germplasm resource analyses and genomics-informed breeding. PLANT COMMUNICATIONS 2022; 3:100331. [PMID: 35643087 PMCID: PMC9284292 DOI: 10.1016/j.xplc.2022.100331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 03/11/2022] [Accepted: 04/28/2022] [Indexed: 06/15/2023]
Abstract
Along with rapid advances in high-throughput-sequencing technology, the development and application of molecular markers has been critical for the progress that has been made in crop breeding and genetic research. Desirable molecular markers should be able to rapidly genotype tens of thousands of breeding accessions with tens to hundreds of markers. In this study, we developed a multiplex molecular marker, the haplotype-tag polymorphism (HTP), that integrates Maize6H-60K array data from 3,587 maize inbred lines with 6,375 blocks from the recombination block map. After applying strict filtering criteria, we obtained 6,163 highly polymorphic HTPs, which were evenly distributed in the genome. Furthermore, we developed a genome-wide HTP analysis toolkit, HTPtools, which we used to establish an HTP database (HTPdb) covering the whole genomes of 3,587 maize inbred lines commonly used in breeding. A total of 172,921 non-redundant HTP allelic variations were obtained. Three major HTPtools modules combine seven algorithms (e.g., chain Bayes probability and the heterotic-pattern prediction algorithm) and a new plotting engine named "BCplot" that enables rapid visualization of the background information of multiple backcross groups. HTPtools was designed for big-data analyses such as complex pedigree reconstruction and maize heterotic-pattern prediction. The HTP-based analytical strategy and the toolkit developed in this study are applicable for high-throughput genotyping and for genetic mapping, germplasm resource analyses, and genomics-informed breeding in maize.
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Affiliation(s)
- Yikun Zhao
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Hongli Tian
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Chunhui Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Hongmei Yi
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Yunlong Zhang
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Xiaohui Li
- Jilin Academy of Agricultural Sciences, Maize Research Institute, Gongzhuling 136100, China
| | - Han Zhao
- Provincial Key Laboratory of Agrobiology, Institute of Crop Germplasm and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
| | - Yongxue Huo
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Rui Wang
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Dingming Kang
- College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Yuncai Lu
- College of Advanced Agriculture and Ecological Environment, Heilongjiang University, Harbin 150080, China
| | - Zhihao Liu
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Ziyue Liang
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Liwen Xu
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Yang Yang
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Ling Zhou
- Provincial Key Laboratory of Agrobiology, Institute of Crop Germplasm and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
| | - Tianyu Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - Jiuran Zhao
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China.
| | - Fengge Wang
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China.
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Fiore MC, Marchese A, Mauceri A, Digangi I, Scialabba A. Diversity Assessment and DNA-Based Fingerprinting of Sicilian Hazelnut (Corylus avellana L.) Germplasm. PLANTS 2022; 11:plants11050631. [PMID: 35270101 PMCID: PMC8912283 DOI: 10.3390/plants11050631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 02/23/2022] [Accepted: 02/23/2022] [Indexed: 11/16/2022]
Abstract
The characterization of plant genetic resources is a precondition for genetic improvement and germplasm management. The increasing use of molecular markers for DNA-based genotype signature is crucial for variety identification and traceability in the food supply chain. We collected 75 Sicilian hazelnut accessions from private and public field collections, including widely grown varieties from the Nebrodi Mountains in north east Sicily (Italy). The germplasm was fingerprinted through nine standardized microsatellites (SSR) for hazelnut identification to evaluate the genetic diversity of the collected accessions, validating SSR discrimination power. We identified cases of homonymy and synonymy among acquisitions and the unique profiles. The genetic relationships illustrated by hierarchical clustering, structure, and discriminant analyses revealed a clear distinction between local and commercial varieties. The comparative genetic analysis also showed that the Nebrodi genotypes are significantly different from the Northern Italian, Iberian, and Turkish genotypes. These results highlight the need and urgency to preserve Nebrodi germplasm as a useful and valuable source for traits of interest employable for breeding. Our study demonstrates the usefulness of molecular marker analysis to select a reference germplasm collection of Sicilian hazelnut varieties and to implement certified plants’ production in the supply chain.
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Affiliation(s)
- Maria Carola Fiore
- Council for Agricultural Research and Economics—Research Centre for Plant Protection and Certification, S.S. 113 km 245,500, 90011 Bagheria, Italy
- Correspondence: ; Tel.: +39-091-909-090
| | - Annalisa Marchese
- Department of Agricultural, Food and Forest Sciences, University of Palermo, Viale delle Scienze—Ed. 4, 90128 Palermo, Italy;
| | - Antonio Mauceri
- Department Agraria, University Mediterranea of Reggio Calabria, Loc. Feo di Vito snc, 89065 Reggio Calabria, Italy;
| | - Ignazio Digangi
- Living Plants Germplasm Bank of Nebrodi, Contrada Pirato, 98060 Ucria, Italy;
| | - Anna Scialabba
- Department of Biological, Chemical and Pharmaceutical Science and Technologies (STEBICEF), University of Palermo, Via Archirafi 38, 90123 Palermo, Italy;
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