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Ji Q, Li F, Huang X, Li S, Wang Z, Liu Z, Huang L, Yang Y, Zhu H, Ke W. Assessment of phylogenetic relationships and genetic diversity of Sagittaria trifolia using phenotypic traits and SNP markers. PLoS One 2024; 19:e0302313. [PMID: 38829862 PMCID: PMC11146740 DOI: 10.1371/journal.pone.0302313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 04/01/2024] [Indexed: 06/05/2024] Open
Abstract
The aquatic perennial herb Sagittaria trifolia L. commonly known as arrowhead, has been utilized in China both as a culinary vegetable and in traditional medicines. Characterizing the phylogenetic relationships and genetic diversity of arrowheads is crucial for improved management, conservation, and efficient utilization of the germplasm resources associated with this species. Herein, we presented the phenotypic traits and genome-wide DNA marker-based analyses of 111 arrowhead accessions, most of which were from China. Cluster analysis revealed that arrowhead could be categorized into two clusters based on 11 phenotypic traits, with Cluster 1 comprising two subclusters. All accessions were clustered into three sub-clusters based primarily on leaf shape and tuber weight. A set of 759,237 high-quality single-nucleotide polymorphisms was identified and used to assess the phylogenetic relationships. Population structure and phylogenetic tree analyses suggested that the accessions could be classified into two major groups, Group I was further subdivided into two subgroups, aligning with the clusters identified through morphological classification. By employing Sagittaria lichuanensis as an outgroup, the rooted tree revealed that the evolutionary relationships within the three groups followed a progression from Group I-1 to Group I-2 and finally to Group II. The landraces were clustered into one group along with the remaining wild accessions. The level of genetic diversity for Group I (π = 0.26) was slightly lower than that which was estimated for Group II (π = 0.29). The lowest pairwise differentiation levels (Fst, 0.008) were obtained from the comparison between groups I-2 and II, indicating that the two groups were the most closely related. This study provides novel insights into germplasm classification, evolutionary relationships, genomics and arrowhead breeding.
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Affiliation(s)
- Qun Ji
- Institute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan, Hubei, China
| | - Feng Li
- Institute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan, Hubei, China
| | - Xinfang Huang
- Institute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan, Hubei, China
| | - Shuangmei Li
- Institute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan, Hubei, China
| | - Zhixin Wang
- Institute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan, Hubei, China
| | - Zhengwei Liu
- Institute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan, Hubei, China
| | - Laichun Huang
- Institute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan, Hubei, China
| | - Yingnan Yang
- Institute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan, Hubei, China
| | - Honglian Zhu
- Institute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan, Hubei, China
| | - Weidong Ke
- Institute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan, Hubei, China
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Younessi-Hamzekhanlu M, Gailing O. Genome-Wide SNP Markers Accelerate Perennial Forest Tree Breeding Rate for Disease Resistance through Marker-Assisted and Genome-Wide Selection. Int J Mol Sci 2022; 23:ijms232012315. [PMID: 36293169 PMCID: PMC9604372 DOI: 10.3390/ijms232012315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 10/05/2022] [Accepted: 10/07/2022] [Indexed: 11/30/2022] Open
Abstract
The ecological and economic importance of forest trees is evident and their survival is necessary to provide the raw materials needed for wood and paper industries, to preserve the diversity of associated animal and plant species, to protect water and soil, and to regulate climate. Forest trees are threatened by anthropogenic factors and biotic and abiotic stresses. Various diseases, including those caused by fungal pathogens, are one of the main threats to forest trees that lead to their dieback. Genomics and transcriptomics studies using next-generation sequencing (NGS) methods can help reveal the architecture of resistance to various diseases and exploit natural genetic diversity to select elite genotypes with high resistance to diseases. In the last two decades, QTL mapping studies led to the identification of QTLs related to disease resistance traits and gene families and transcription factors involved in them, including NB-LRR, WRKY, bZIP and MYB. On the other hand, due to the limitation of recombination events in traditional QTL mapping in families derived from bi-parental crosses, genome-wide association studies (GWAS) that are based on linkage disequilibrium (LD) in unstructured populations overcame these limitations and were able to narrow down QTLs to single genes through genotyping of many individuals using high-throughput markers. Association and QTL mapping studies, by identifying markers closely linked to the target trait, are the prerequisite for marker-assisted selection (MAS) and reduce the breeding period in perennial forest trees. The genomic selection (GS) method uses the information on all markers across the whole genome, regardless of their significance for development of a predictive model for the performance of individuals in relation to a specific trait. GS studies also increase gain per unit of time and dramatically increase the speed of breeding programs. This review article is focused on the progress achieved in the field of dissecting forest tree disease resistance architecture through GWAS and QTL mapping studies. Finally, the merit of methods such as GS in accelerating forest tree breeding programs is also discussed.
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Affiliation(s)
- Mehdi Younessi-Hamzekhanlu
- Department of Forestry and Medicinal Plants, Ahar Faculty of Agriculture and Natural Resources, University of Tabriz, 29 Bahman Blvd., Tabriz P.O. Box 5166616471, Iran
- Correspondence: (M.Y.-H.); (O.G.)
| | - Oliver Gailing
- Department of Forest Genetics and Forest Tree Breeding, University of Göttingen, Büsgenweg 2, D-37077 Göttingen, Germany
- Correspondence: (M.Y.-H.); (O.G.)
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