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Seay D, Szczepanek A, De La Fuente GN, Votava E, Abdel-Haleem H. Genetic Diversity and Population Structure of a Large USDA Sesame Collection. PLANTS (BASEL, SWITZERLAND) 2024; 13:1765. [PMID: 38999604 PMCID: PMC11243581 DOI: 10.3390/plants13131765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 06/11/2024] [Accepted: 06/24/2024] [Indexed: 07/14/2024]
Abstract
Sesame, Sesamum indicum L., is one of the oldest domesticated crops used for its oil and protein in many parts of the world. To build genomic resources for sesame that could be used to improve sesame productivity and responses to stresses, a USDA sesame germplasm collection of 501 accessions originating from 36 countries was used in this study. The panel was genotyped using genotyping-by-sequencing (GBS) technology to explore its genetic diversity and population structure and the relatedness among its accessions. A total of 24,735 high-quality single-nucleotide polymorphism (SNP) markers were identified over the 13 chromosomes. The marker density was 1900 SNP per chromosome, with an average polymorphism information content (PIC) value of 0.267. The marker polymorphisms and heterozygosity estimators indicated the usefulness of the identified SNPs to be used in future genetic studies and breeding activities. The population structure, principal components analysis (PCA), and unrooted neighbor-joining phylogenetic tree analyses classified two distinct subpopulations, indicating a wide genetic diversity within the USDA sesame collection. Analysis of molecular variance (AMOVA) revealed that 29.5% of the variation in this population was due to subpopulations, while 57.5% of the variation was due to variation among the accessions within the subpopulations. These results showed the degree of differentiation between the two subpopulations as well as within each subpopulation. The high fixation index (FST) between the distinguished subpopulations indicates a wide genetic diversity and high genetic differentiation among and within the identified subpopulations. The linkage disequilibrium (LD) pattern averaged 161 Kbp for the whole sesame genome, while the LD decay ranged from 168 Kbp at chromosome LG09 to 123 Kbp in chromosome LG05. These findings could explain the complications of linkage drag among the traits during selections. The selected accessions and genotyped SNPs provide tools to enhance genetic gain in sesame breeding programs through molecular approaches.
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Affiliation(s)
- Damien Seay
- US Arid Land Agricultural Research Center, USDA ARS, Maricopa, AZ 85138, USA
| | - Aaron Szczepanek
- US Arid Land Agricultural Research Center, USDA ARS, Maricopa, AZ 85138, USA
| | | | - Eric Votava
- Sesaco Corporation, 5405 Bandera Rd. San Antonio, TX 78238, USA
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Ahmed SF, Ahmed JU, Hasan M, Mohi-Ud-Din M. Assessment of genetic variation among wheat genotypes for drought tolerance utilizing microsatellite markers and morpho-physiological characteristics. Heliyon 2023; 9:e21629. [PMID: 38027610 PMCID: PMC10658252 DOI: 10.1016/j.heliyon.2023.e21629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Revised: 09/18/2023] [Accepted: 10/25/2023] [Indexed: 12/01/2023] Open
Abstract
Drought is a major abiotic stress that severely limits sustainable wheat (Triticum aestivum L.) productivity via morphological and physio-biochemical alterations of cellular processes. The complex nature and polygenic control of drought tolerance traits make breeding tolerant genotypes quite challenging. However, naturally occurring variabilities among wheat germplasm resources could potentially help combating drought. The present study was conducted to assess the drought tolerance of 18 Bangladeshi hexaploid wheat genotypes, focusing on the identification of potent sources of diversity by combining microsatellite markers, also known as single sequence repeat markers, and morpho-physiological characteristics that might help accelerating wheat crop improvement programs. Initially, the genotypes were evaluated using 25 microsatellite markers followed by an on-field evaluation of 7 morphological traits (plant height, spike number, spike length, grains per spike, 1000-grain weight, grain yield, biological yield) and 6 physiological traits (SPAD value, membrane stability index, leaf relative water content, proline content, canopy temperature depression, and leaf K+ ion content). The field-trial was conducted in a factorial fashion of 18 wheat genotypes and two water regimes (control and drought) following a split-plot randomized complete block design. Regardless of genotype, drought was significantly damaging for all the tested traits; however, substantial variability in drought stress tolerance was evident among the genotypes. Spike length, 1000-grain weight, SPAD value, leaf relative water content, canopy temperature depression, proline content, and potassium (K+) ion content were the most representative of drought-induced growth and yield impairments and also correlated well with the contrasting ability of genotypic tolerance. Microsatellite markers amplified 244 alleles exhibiting 79% genetic diversity. Out of 25 markers, 23 was highly polymorphic showing 77% average polymorphism. Morpho-physiological trait-based hierarchical clustering and microsatellite marker-based neighbor-jointing clustering both revealed three genotypic clusters with 71% co-linearity between them. In both cases, the genotypes Kanchan, BAW-1147, BINA Gom 1, BARI Gom 22, BARI Gom 26, and BARI Gom 33 were found to be comparatively more tolerant than the other tested genotypes, showing potential for cultivation in water-deficit environments. The findings of this study would contribute to the present understanding of drought tolerance in wheat and would provide a basis for future genotype selection for drought-tolerant wheat breeding programs.
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Affiliation(s)
- Sheikh Faruk Ahmed
- Department of Crop Botany, Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Gazipur, 1706, Bangladesh
| | - Jalal Uddin Ahmed
- Department of Crop Botany, Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Gazipur, 1706, Bangladesh
| | - Mehfuz Hasan
- Department of Genetics and Plant Breeding, Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Gazipur, 1706, Bangladesh
| | - Mohammed Mohi-Ud-Din
- Department of Crop Botany, Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Gazipur, 1706, Bangladesh
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Yang X, Cai L, Wang M, Zhu W, Xu L, Wang Y, Zeng J, Fan X, Sha L, Wu D, Cheng Y, Zhang H, Jiang Y, Chen G, Zhou Y, Kang H. Genome-Wide Association Study of Asian and European Common Wheat Accessions for Yield-Related Traits and Stripe Rust Resistance. PLANT DISEASE 2023; 107:3085-3095. [PMID: 37079013 DOI: 10.1094/pdis-03-22-0702-re] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Identifying novel loci of yield-related traits and resistance to stripe rust (caused by Puccinia striiformis f. sp. tritici) in wheat will help in breeding wheat that can meet projected demands in diverse environmental and agricultural practices. We performed a genome-wide association study with 24,767 single nucleotide polymorphisms (SNPs) in 180 wheat accessions that originated in 16 Asian or European countries between latitudes 30°N and 45°N. We detected seven accessions with desirable yield-related traits and 42 accessions that showed stable, high degrees of stripe rust resistance in multienvironment field assessments. A marker-trait association analysis of yield-related traits detected 18 quantitative trait loci (QTLs) in at least two test environments and two QTLs related to stripe rust resistance in at least three test environments. Five of these QTLs were identified as potentially novel QTLs by comparing their physical locations with those of known QTLs in the Chinese Spring (CS) reference genome RefSeq v1.1 published by the International Wheat Genome Sequencing Consortium; two were for spike length, one was for grain number per spike, one was for spike number, and one was for stripe rust resistance at the adult plant stage. We also identified 14 candidate genes associated with the five novel QTLs. These QTLs and candidate genes will provide breeders with new germplasm and can be used to conduct marker-assisted selection in breeding wheat with improved yield and stripe rust resistance.
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Affiliation(s)
- Xiu Yang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Li Cai
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Miaomiao Wang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Wei Zhu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Lili Xu
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Yi Wang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Jian Zeng
- College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Xing Fan
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Lina Sha
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Dandan Wu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Yiran Cheng
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Haiqin Zhang
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Yunfeng Jiang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Guoyue Chen
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Yonghong Zhou
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Houyang Kang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
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Kang Y, Choi C, Kim JY, Min KD, Kim C. Optimizing genomic selection of agricultural traits using K-wheat core collection. FRONTIERS IN PLANT SCIENCE 2023; 14:1112297. [PMID: 37389296 PMCID: PMC10303932 DOI: 10.3389/fpls.2023.1112297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 02/02/2023] [Indexed: 07/01/2023]
Abstract
The agricultural traits that constitute basic plant breeding information are usually quantitative or complex in nature. This quantitative and complex combination of traits complicates the process of selection in breeding. This study examined the potential of genome-wide association studies (GWAS) and genomewide selection (GS) for breeding ten agricultural traits by using genome-wide SNPs. As a first step, a trait-associated candidate marker was identified by GWAS using a genetically diverse 567 Korean (K)-wheat core collection. The accessions were genotyped using an Axiom® 35K wheat DNA chip, and ten agricultural traits were determined (awn color, awn length, culm color, culm length, ear color, ear length, days to heading, days to maturity, leaf length, and leaf width). It is essential to sustain global wheat production by utilizing accessions in wheat breeding. Among the traits associated with awn color and ear color that showed a high positive correlation, a SNP located on chr1B was significantly associated with both traits. Next, GS evaluated the prediction accuracy using six predictive models (G-BLUP, LASSO, BayseA, reproducing kernel Hilbert space, support vector machine (SVM), and random forest) and various training populations (TPs). With the exception of the SVM, all statistical models demonstrated a prediction accuracy of 0.4 or better. For the optimization of the TP, the number of TPs was randomly selected (10%, 30%, 50% and 70%) or divided into three subgroups (CC-sub 1, CC-sub 2 and CC-sub 3) based on the subpopulation structure. Based on subgroup-based TPs, better prediction accuracy was found for awn color, culm color, culm length, ear color, ear length, and leaf width. A variety of Korean wheat cultivars were used for validation to evaluate the prediction ability of populations. Seven out of ten cultivars showed phenotype-consistent results based on genomics-evaluated breeding values (GEBVs) calculated by the reproducing kernel Hilbert space (RKHS) predictive model. Our research provides a basis for improving complex traits in wheat breeding programs through genomics assisted breeding. The results of our research can be used as a basis for improving wheat breeding programs by using genomics-assisted breeding.
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Affiliation(s)
- Yuna Kang
- Department of Crop Science, Chungnam National University, Daejeon, Republic of Korea
| | - Changhyun Choi
- Wheat Research Team, National Institution Crop Sciences, Wanju-gun, Republic of Korea
| | - Jae Yoon Kim
- Department of Plant Resources, Kongju National University, Yesan, Republic of Korea
| | - Kyeong Do Min
- Department of Plant Resources, Kongju National University, Yesan, Republic of Korea
| | - Changsoo Kim
- Department of Crop Science, Chungnam National University, Daejeon, Republic of Korea
- Department of Smart Agriculture Systems, Chungnam National University, Daejeon, Republic of Korea
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Dagnaw T, Mulugeta B, Haileselassie T, Geleta M, Ortiz R, Tesfaye K. Genetic Diversity of Durum Wheat ( Triticum turgidum L. ssp. durum, Desf) Germplasm as Revealed by Morphological and SSR Markers. Genes (Basel) 2023; 14:1155. [PMID: 37372335 DOI: 10.3390/genes14061155] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 05/21/2023] [Accepted: 05/23/2023] [Indexed: 06/29/2023] Open
Abstract
Ethiopia is considered a center of origin and diversity for durum wheat and is endowed with many diverse landraces. This research aimed to estimate the extent and pattern of genetic diversity in Ethiopian durum wheat germplasm. Thus, 104 durum wheat genotypes representing thirteen populations, three regions, and four altitudinal classes were investigated for their genetic diversity, using 10 grain quality- and grain yield-related phenotypic traits and 14 simple sequence repeat (SSR) makers. The analysis of the phenotypic traits revealed a high mean Shannon diversity index (H' = 0.78) among the genotypes and indicated a high level of phenotypic variation. The principal component analysis (PCA) classified the genotypes into three groups. The SSR markers showed a high mean value of polymorphic information content (PIC = 0.50) and gene diversity (h = 0.56), and a moderate number of alleles per locus (Na = 4). Analysis of molecular variance (AMOVA) revealed a high level of variation within populations, regions, and altitudinal classes, accounting for 88%, 97%, and 97% of the total variation, respectively. Pairwise genetic differentiation and Nei's genetic distance analyses identified that the cultivars are distinct from the landrace populations. The distance-based (Discriminant Analysis of Principal Component (DAPC) and Minimum Spanning Network (MSN)) and model-based population stratification (STRUCTURE) methods of clustering grouped the genotypes into two clusters. Both the phenotypic data-based PCA and the molecular data-based DAPC and MSN analyses defined distinct groupings of cultivars and landraces. The phenotypic and molecular diversity analyses highlighted the high genetic variation in the Ethiopian durum wheat gene pool. The investigated SSRs showed significant associations with one or more target phenotypic traits. The markers identify landraces with high grain yield and quality traits. This study highlights the usefulness of Ethiopian landraces for cultivar development, contributing to food security in the region and beyond.
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Affiliation(s)
- Temesgen Dagnaw
- Department of Microbial, Cellular and Molecular Biology, Addis Ababa University, Addis Ababa P.O. Box 1176, Ethiopia
| | - Behailu Mulugeta
- Institute of Biotechnology, Addis Ababa University, Addis Ababa P.O. Box 1176, Ethiopia
- Department of Plant Breeding, Swedish University of Agricultural Sciences, P.O. Box 190, SE-23422 Lomma, Sweden
| | | | - Mulatu Geleta
- Department of Plant Breeding, Swedish University of Agricultural Sciences, P.O. Box 190, SE-23422 Lomma, Sweden
| | - Rodomiro Ortiz
- Department of Plant Breeding, Swedish University of Agricultural Sciences, P.O. Box 190, SE-23422 Lomma, Sweden
| | - Kassahun Tesfaye
- Department of Microbial, Cellular and Molecular Biology, Addis Ababa University, Addis Ababa P.O. Box 1176, Ethiopia
- Ethiopian Bio and Emerging Technology Institute, Addis Ababa P.O. Box 5954, Ethiopia
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Park S, Park YO, Park Y. Population Genetic Analysis in Persimmons ( Diospyros kaki Thunb.) Based on Genome-Wide Single-Nucleotide Polymorphisms. PLANTS (BASEL, SWITZERLAND) 2023; 12:plants12112097. [PMID: 37299077 DOI: 10.3390/plants12112097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 04/13/2023] [Accepted: 05/19/2023] [Indexed: 06/12/2023]
Abstract
This study investigated the genetic diversity and population structure of a persimmon (Diospyros kaki Thunb., 2n = 6x = 90) collection in South Korea by evaluating 9751 genome-wide single-nucleotide polymorphisms (SNPs) detected using genotyping-by-sequencing in 93 cultivars. The results of neighbor-joining clustering, principal component analysis, and STRUCTURE analysis based on SNPs indicated clear separation between cultivar groups (pollination-constant nonastringent (PCNA, 40 cultivars), pollination-constant astringent (PCA, 19), pollination-variant nonastringent (PVNA, 23), and the pollination-variant astringent type (PVA, 9)) based on the astringency types, while separation between PVA and PVNA-type cultivars was unclear. Population genetic diversity based on SNPs showed that the proportions of polymorphic SNPs within each group ranged from 99.01% (PVNA) to 94.08% (PVA), and the PVNA group exhibited the highest genetic diversity (He = 3.86 and uHe = 0.397). F (fixation index) values were low ranging from -0.024 (PVA) to 0.176 (PCA) with an average of 0.089, indicating a deficiency of heterozygosity. Analysis of molecular variance (AMOVA) and Fst among cultivar groups indicated that variation within individuals was higher than that among the groups. Pairwise Fst values among the groups ranged from 0.01566 (between PVA and PVNA) to 0.09416 (between PCA and PCNA), indicating a low level of cultivar type differentiation. These findings highlight the potential application of biallelic SNPs in population genetics studies of allopolyploids species and provide valuable insights that may have significant implications for breeding and cultivar identification in persimmon.
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Affiliation(s)
- Seoyeon Park
- Department of Horticultural Science, Pusan National University, Miryang 50463, Republic of Korea
| | - Ye-Ok Park
- Sweet Persimmon Research Institute, Gyeongsangnam-do Agricultural Research and Extension Services, Gimhae 50871, Republic of Korea
| | - Younghoon Park
- Department of Horticultural Science, Pusan National University, Miryang 50463, Republic of Korea
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Genetic diversity and population structure of wild and cultivated Crotalaria species based on genotyping-by-sequencing. PLoS One 2022; 17:e0272955. [PMID: 36048841 PMCID: PMC9436042 DOI: 10.1371/journal.pone.0272955] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 07/28/2022] [Indexed: 11/19/2022] Open
Abstract
Crotalaria is a plant genus that is found all over the world, with over 700 species of herbs and shrubs. The species are potential alternative food and industrial crops due to their adaptability to different environments. Currently, information on the genetic diversity and population structure of these species is scanty. Genotyping-by-sequencing (GBS) is a cost-effective high-throughput technique in diversity evaluation of plant species that have not been fully sequenced. In the current study, de novo GBS was used to characterize 80 Crotalaria accessions from five geographical regions in Kenya. A total of 9820 single nucleotide polymorphism (SNP) markers were obtained after thinning and filtering, which were then used for the analysis of genetic diversity and population structure in Crotalaria. The proportion of SNPs with a minor allele frequency (maf) > = 0.05 was 45.08%, while the Guanine-Cytosine (GC) content was 0.45, from an average sequence depth of 455,909 reads per base. The transition vs transversion ratio was 1.81 and Heterozygosity (He) ranged between 0.01–0.07 in all the sites and 0.04 to 0.52 in the segregating sites. The mean Tajima’s D value for the population was -0.094, suggesting an excess of rare alleles. The fixation index (Fst) between the different populations based on the Wright Fst (1943) ranged from 0.0119 to 0.066 for the Eastern-Western and Nairobi-Western populations. Model based techniques of population structure analysis including structure, k-means and cross-entropy depicted eight clusters in the study accessions. Non-model based techniques especially DAPC depicted poor population stratification. Correspondence Analysis (CA), Principal coordinate analyses (PCoA) and phylogenetic analysis identified a moderate level of population stratification. Results from this study will help conservationists and breeders understand the genetic diversity of Crotalaria. The study also provides valuable information for genetic improvement of domesticated species.
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A Neural Network-Based Spectral Approach for the Assignment of Individual Trees to Genetically Differentiated Subpopulations. REMOTE SENSING 2022. [DOI: 10.3390/rs14122898] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Studying population structure has made an essential contribution to understanding evolutionary processes and demographic history in forest ecology research. This inference process basically involves the identification of common genetic variants among individuals, then grouping the similar individuals into subpopulations. In this study, a spectral-based classification of genetically differentiated groups was carried out using a provenance–progeny trial of Eucalyptus cladocalyx. First, the genetic structure was inferred through a Bayesian analysis using single-nucleotide polymorphisms (SNPs). Then, different machine learning models were trained with foliar spectral information to assign individual trees to subpopulations. The results revealed that spectral-based classification using the multilayer perceptron method was very successful at classifying individuals into their respective subpopulations (with an average of 87% of correct individual assignments), whereas 85% and 81% of individuals were assigned to their respective classes correctly by convolutional neural network and partial least squares discriminant analysis, respectively. Notably, 93% of individual trees were assigned correctly to the class with the smallest size using the spectral data-based multi-layer perceptron classification method. In conclusion, spectral data, along with neural network models, are able to discriminate and assign individuals to a given subpopulation, which could facilitate the implementation and application of population structure studies on a large scale.
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Tehseen MM, Tonk FA, Tosun M, Istipliler D, Amri A, Sansaloni CP, Kurtulus E, Mubarik MS, Nazari K. Exploring the Genetic Diversity and Population Structure of Wheat Landrace Population Conserved at ICARDA Genebank. Front Genet 2022; 13:900572. [PMID: 35783289 PMCID: PMC9240388 DOI: 10.3389/fgene.2022.900572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 05/05/2022] [Indexed: 11/13/2022] Open
Abstract
Landraces are considered a valuable source of potential genetic diversity that could be used in the selection process in any plant breeding program. Here, we assembled a population of 600 bread wheat landraces collected from eight different countries, conserved at the ICARDA's genebank, and evaluated the genetic diversity and the population structure of the landraces using single nucleotide polymorphism (SNP) markers. A total of 11,830 high-quality SNPs distributed across the genomes A (40.5%), B (45.9%), and D (13.6%) were used for the final analysis. The population structure analysis was evaluated using the model-based method (STRUCTURE) and distance-based methods [discriminant analysis of principal components (DAPC) and principal component analysis (PCA)]. The STRUCTURE method grouped the landraces into two major clusters, with the landraces from Syria and Turkey forming two clusters with high proportions of admixture, whereas the DAPC and PCA analysis grouped the population into three subpopulations mostly according to the geographical information of the landraces, i.e., Syria, Iran, and Turkey with admixture. The analysis of molecular variance revealed that the majority of the variation was due to genetic differences within the populations as compared with between subpopulations, and it was the same for both the cluster-based and distance-based methods. Genetic distance analysis was also studied to estimate the differences between the landraces from different countries, and it was observed that the maximum genetic distance (0.389) was between the landraces from Spain and Palestine, whereas the minimum genetic distance (0.013) was observed between the landraces from Syria and Turkey. It was concluded from the study that the model-based methods (DAPC and PCA) could dissect the population structure more precisely when compared with the STRUCTURE method. The population structure and genetic diversity analysis of the bread wheat landraces presented here highlight the complex genetic architecture of the landraces native to the Fertile Crescent region. The results of this study provide useful information for the genetic improvement of hexaploid wheat and facilitate the use of landraces in wheat breeding programs.
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Affiliation(s)
- Muhammad Massub Tehseen
- Department of Field Crops, Ege University, Bornova, Turkey
- *Correspondence: Muhammad Massub Tehseen, ; Kumarse Nazari,
| | | | - Muzaffer Tosun
- Department of Field Crops, Ege University, Bornova, Turkey
| | | | - Ahmed Amri
- ICARDA-PreBreeding and Genebank Operations, Biodiversity and Crop Improvement Program, Rabat, Morocco
| | | | - Ezgi Kurtulus
- Turkey-ICARDA Regional Cereal Rust Research Center (RCRRC), Menemen, Izmir, Turkey
| | | | - Kumarse Nazari
- Turkey-ICARDA Regional Cereal Rust Research Center (RCRRC), Menemen, Izmir, Turkey
- *Correspondence: Muhammad Massub Tehseen, ; Kumarse Nazari,
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Hussain S, Habib M, Ahmed Z, Sadia B, Bernardo A, Amand PS, Bai G, Ghori N, Khan AI, Awan FS, Maqbool R. Genotyping-by-Sequencing Based Molecular Genetic Diversity of Pakistani Bread Wheat ( Triticum aestivum L.) Accessions. Front Genet 2022; 13:772517. [PMID: 35464861 PMCID: PMC9019749 DOI: 10.3389/fgene.2022.772517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 01/07/2022] [Indexed: 11/29/2022] Open
Abstract
Spring wheat (Triticum aestivum L.) is one of the most imperative staple food crops, with an annual production of 765 million tons globally to feed ∼40% world population. Genetic diversity in available germplasm is crucial for sustainable wheat improvement to ensure global food security. A diversity panel of 184 Pakistani wheat accessions was genotyped using 123,596 high-quality single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing with 42% of the SNPs mapped on B, 36% on A, and 22% on D sub-genomes of wheat. Chromosome 2B contains the most SNPs (9,126), whereas 4D has the least (2,660) markers. The mean polymorphic information content, genetic diversity, and major allele frequency of the population were 0.157, 0.1844, and 0.87, respectively. Analysis of molecular variance revealed a higher genetic diversity (80%) within the sub-population than among the sub-populations (20%). The genome-wide linkage disequilibrium was 0.34 Mbp for the whole wheat genome. Among the three subgenomes, A has the highest LD decay value (0.29 Mbp), followed by B (0.2 Mbp) and D (0.07 Mbp) genomes, respectively. The results of population structure, principal coordinate analysis, phylogenetic tree, and kinship analysis also divided the whole population into three clusters comprising 31, 33, and 120 accessions in group 1, group 2, and group 3, respectively. All groups were dominated by the local wheat accessions. Estimation of genetic diversity will be a baseline for the selection of breeding parents for mutations and the genome-wide association and marker-assisted selection studies.
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Affiliation(s)
- Shabbir Hussain
- Center of Agricultural Biochemistry and Biotechnology, University of Agriculture, Faisalabad, Pakistan
| | - Madiha Habib
- Center of Agricultural Biochemistry and Biotechnology, University of Agriculture, Faisalabad, Pakistan
| | - Zaheer Ahmed
- Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan
| | - Bushra Sadia
- Center of Agricultural Biochemistry and Biotechnology, University of Agriculture, Faisalabad, Pakistan
| | - Amy Bernardo
- USDA, Hard Winter Wheat Genetics Research Unit, Manhattan, KS, United States
| | - Paul St Amand
- USDA, Hard Winter Wheat Genetics Research Unit, Manhattan, KS, United States
| | - Guihua Bai
- USDA, Hard Winter Wheat Genetics Research Unit, Manhattan, KS, United States
| | - Nida Ghori
- USDA, Hard Winter Wheat Genetics Research Unit, Manhattan, KS, United States
| | - Azeem I Khan
- Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan
| | - Faisal S Awan
- Center of Agricultural Biochemistry and Biotechnology, University of Agriculture, Faisalabad, Pakistan
| | - Rizwana Maqbool
- Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan
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11
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Li L, Yang X, Wang Z, Ren M, An C, Zhu S, Xu R. Genetic mapping of powdery mildew resistance genes in wheat landrace Guizi 1 via genotyping by sequencing. Mol Biol Rep 2022; 49:4461-4468. [PMID: 35244868 DOI: 10.1007/s11033-022-07287-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 02/18/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND Wheat (Triticum aestivum L.) powdery mildew (Pm), which caused by Blumeria graminis f. sp. tritici (Bgt), is a destructive disease worldwide that causes severe yield losses in wheat. Resistant wheat cultivars easily lose their ability to effectively resist newly emerged Bgt strains; therefore, identifying new resistance genes is necessary for breeding resistant cultivars. METHODS AND RESULTS Guizi 1 (GZ1) is a Chinese wheat cultivar with moderate and stable resistance to Pm. Genetic analysis indicated that the Pm resistance of GZ1 was controlled by a single dominant gene, designated PmGZ1. In total, 110 F2 individual plants and their 2 parents were subjected to genotyping by sequencing (GBS), which yielded 23,134 high-quality single-nucleotide polymorphisms (SNPs). The SNP distributions across the 21 chromosomes ranged from 134 on chromosome 6D to 6288 on chromosome 3B. Chromosome 6A has 1866 SNPs, among which 16 are physically located between positions 307,802,221 and 309,885,836 in an approximate 2.3-cM region; this region also had the greatest SNP density. The average map distance between SNP markers was 0.1 cM. A quantitative trait locus (QTL) with a significant epistatic effect on Pm resistance was mapped to chromosome 6A. The logarithm of odds (LOD) value of PmGZ1 was 34.8, and PmGZ1 was located within the confidence interval marked by chr6a-307802221 and chr6a-309885836. Moreover, 74.7% of the phenotypic variance was explained by PmGZ1. Four candidate genes (which encoded two TaAP2-A and two actin proteins) were annotated maybe as resistance genes. CONCLUSIONS The present results provide valuable information for wheat genetic improvement, QTL fine mapping, and candidate gene validation.
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Affiliation(s)
- Luhua Li
- College of Agriculture, Guizhou University, Guiyang, 550025, China.,Guizhou Sub-center of National Wheat Improvement Center, Guiyang, 550025, China
| | - Xicui Yang
- Guizhou Agricultural Technology Extension Station, Guiyang, 550001, China
| | - Zhongni Wang
- Guizhou Rice Research Institute, Guizhou Academy of Agricultural Science, Guiyang, 550006, China
| | - Mingjian Ren
- College of Agriculture, Guizhou University, Guiyang, 550025, China.,Guizhou Sub-center of National Wheat Improvement Center, Guiyang, 550025, China
| | - Chang An
- College of Agriculture, Guizhou University, Guiyang, 550025, China.,Guizhou Sub-center of National Wheat Improvement Center, Guiyang, 550025, China
| | - Susong Zhu
- Guizhou Rice Research Institute, Guizhou Academy of Agricultural Science, Guiyang, 550006, China
| | - Ruhong Xu
- College of Agriculture, Guizhou University, Guiyang, 550025, China. .,Guizhou Sub-center of National Wheat Improvement Center, Guiyang, 550025, China.
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12
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Zhao Z, Song Q, Bai D, Niu S, He Y, Qiao D, Chen Z, Li C, Luo J, Li F. Population structure analysis to explore genetic diversity and geographical distribution characteristics of cultivated-type tea plant in Guizhou Plateau. BMC PLANT BIOLOGY 2022; 22:55. [PMID: 35086484 PMCID: PMC8793275 DOI: 10.1186/s12870-022-03438-7] [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: 10/12/2021] [Accepted: 01/12/2022] [Indexed: 05/17/2023]
Abstract
BACKGROUND Tea plants originated in southwestern China. Guizhou Plateau is an original center of tea plants, and is rich in germplasm resources. However, the genetic diversity, population structure and distribution characteristics of cultivated-type tea plants in the region are unknown. In this study, we explored the genetic diversity and geographical distribution of cultivated-type tea accessions in Guizhou Plateau. RESULTS We used 112,072 high-quality genotyping-by-sequencing to analyze the genetic diversity, principal components, phylogeny, population structure, and linkage disequilibrium, and develop a core collection of 253 cultivated-type tea plant accessions from Guizhou Plateau. The results showed Genetic diversity of the cultivated-type tea accessions of the Pearl River Basin was significantly higher than that of the cultivated-type tea accessions of the Yangtze River Basin. Three inferred pure groups (CG-1, CG-2 and CG-3) and one inferred admixture group (CG-4), were identified by a population structure analysis, and verified by principal component and phylogenetic analyses. The highest genetic distance and differentiation coefficients were determined for CG-2 vs CG-3. The lower genetic distance and differentiation coefficients were determined for CG-4 vs CG-2 and CG-4 vs CG-3, respectively. We developed a core set and a primary set. The primary and core sets contained 77.0 and 33.6% of all individuals in the initial set, respectively. The primary set may serve as the primary population in genome-wide association studies, while the core collection may serve as the core population in multiple treatment setting studies. CONCLUSIONS The present study demonstrated the genetic diversity and geographical distribution characteristics of cultivated-type tea plants in Guizhou Plateau. Significant differences in genetic diversity and evolutionary direction were detected between the ancient landraces of the Pearl River Basin and the those of the Yangtze River Basin. Major rivers and ancient hubs were largely responsible for the genetic exchange between the Pearl River Basin and the Yangtze River Basin ancient landraces as well as the formation of the ancient hubs evolutionary group. Genetic diversity, population structure and core collection elucidated by this study will facilitate further genetic studies, germplasm protection, and breeding of tea plants.
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Affiliation(s)
- Zhifei Zhao
- College of Tea Science / Tea Engineering Technology Research Center, Guizhou University, Guiyang, 550025 Guizhou Province PR China
| | - Qinfei Song
- College of Tea Science / Tea Engineering Technology Research Center, Guizhou University, Guiyang, 550025 Guizhou Province PR China
| | - Dingchen Bai
- College of Tea Science / Tea Engineering Technology Research Center, Guizhou University, Guiyang, 550025 Guizhou Province PR China
| | - Suzhen Niu
- College of Tea Science / Tea Engineering Technology Research Center, Guizhou University, Guiyang, 550025 Guizhou Province PR China
- lnstitute of Tea Science, Guizhou Academy of Agricultural Sciences, Guiyang, 550006 Guizhou Province PR China
| | - Yingqin He
- College of Tea Science / Tea Engineering Technology Research Center, Guizhou University, Guiyang, 550025 Guizhou Province PR China
| | - Dahe Qiao
- lnstitute of Tea Science, Guizhou Academy of Agricultural Sciences, Guiyang, 550006 Guizhou Province PR China
| | - Zhengwu Chen
- lnstitute of Tea Science, Guizhou Academy of Agricultural Sciences, Guiyang, 550006 Guizhou Province PR China
| | - Caiyun Li
- College of Tea Science / Tea Engineering Technology Research Center, Guizhou University, Guiyang, 550025 Guizhou Province PR China
| | - Jing Luo
- College of Tea Science / Tea Engineering Technology Research Center, Guizhou University, Guiyang, 550025 Guizhou Province PR China
| | - Fang Li
- College of Tea Science / Tea Engineering Technology Research Center, Guizhou University, Guiyang, 550025 Guizhou Province PR China
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13
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Yang X, Tan B, Yang Y, Zhang X, Zhu W, Xu L, Wang Y, Zeng J, Fan X, Sha L, Zhang H, Wu D, Ma J, Chen G, Zhou Y, Kang H. Genetic diversity of Asian and European common wheat lines assessed by fluorescence in situ hybridization. Genome 2021; 64:959-968. [PMID: 33852810 DOI: 10.1139/gen-2020-0161] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Understanding the genetic diversity of wheat is important for wheat breeding and improvement. However, there have been limited attempts to evaluate wheat diversity using fluorescence in situ hybridization (FISH). In this study, the chromosomal structures of 149 wheat accessions from 13 countries located between the latitudes of 30°N and 45°N, the principal growing region for wheat, were characterized using FISH with pTa535 and pSc119.2 probes. The ranges of the numbers of FISH types in the A-, B-, and D-genome chromosomes were 2-8, 3-7, and 2-4, respectively, and the average numbers in the A and B genomes were greater than in the D genome. Chromosomal translocations were detected by these probes, and previously undescribed translocations were also observed. Using the FISH, the genetic relationships among the 149 common wheat lines were divided into three groups (G1, G2, and G3). G1 mainly consisted of southern European lines, G2 consisted of most lines from Japan and some lines from western Asia, China, and Korea, and G3 consisted of the other lines from southern Europe and most of the lines from western Asia, China, and Korea. FISH karyotypes of wheat chromosomes distinguished chromosomal structural variations, revealing the genetic diversity among wheat varieties. Furthermore, these results provide valuable information for the further genetic improvement of wheat in China.
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Affiliation(s)
- Xiu Yang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Binwen Tan
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Yulu Yang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Xiaohui Zhang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Wei Zhu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Lili Xu
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Yi Wang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Jian Zeng
- College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Xing Fan
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Lina Sha
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Haiqin Zhang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Dandan Wu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Jian Ma
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Guoyue Chen
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Yonghong Zhou
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Houyang Kang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
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14
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Tsonev S, Christov NK, Mihova G, Dimitrova A, Todorovska EG. Genetic diversity and population structure of bread wheat varieties grown in Bulgaria based on microsatellite and phenotypic analyses. BIOTECHNOL BIOTEC EQ 2021. [DOI: 10.1080/13102818.2021.1996274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
Affiliation(s)
- Stefan Tsonev
- Department of Functional Genetics, AgroBioInstitute, Agricultural Academy, Sofia, Bulgaria
| | | | - Gallina Mihova
- Department of Cereal and Legumes Breeding, Dobrudzha Agricultural Institute, Agricultural Academy, General Toshevo, Bulgaria
| | - Anna Dimitrova
- Department of Regulation of Gene Expression, Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Sofia, Bulgaria
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