Genetic structure and diversity of upland rice germplasm using diversity array technology (DArT)-based single nucleotide polymorphism (SNP) markers

2020 ◽  
pp. 1-8
Author(s):  
Kehinde A. Adeboye ◽  
Olayinka E. Oyedeji ◽  
Ahmad M. Alqudah ◽  
Andreas Börner ◽  
Olusegun Oduwaye ◽  
...  

Abstract Investigating genetic structure and diversity is crucial for rice improvement strategies, including mapping quantitative trait loci with the potential for improved productivity and adaptation to the upland ecology. The present study elucidated the population structure and genetic diversity of 176 rice germplasm adapted to the upland ecology using 7063 genome-wide single nucleotide polymorphism (SNP) markers from the Diversity Array Technology (DArT)-based sequencing platform (DArTseq). The SNPs were reasonably distributed across the rice genome, ranging from 432 SNPs on chromosome 9 to 989 SNPs on chromosome 1. The minimum minor allele frequency was 0.05, while the average polymorphism information content and heterozygosity were 0.25 and 0.03, respectively. The model-based (Bayesian) population structure analysis identified two major groups for the studied rice germplasm. Analysis of molecular variance revealed that all (100%) of the genetic variance was attributable to differences within the population, and none was attributable to the population structure. The estimates of genetic differentiation (PhiPT = 0.001; P = 0.197) further showed a negligible difference among the population structures. The results indicated a high genetic exchange or gene flow (number of migrants, Nm = 622.65) and a substantial level of diversity (number of private alleles, Pa = 1.52 number of different alleles, Na = 2.67; Shannon's information index, I = 0.084; and percentage of polymorphic loci, %PPL = 55.9%) within the population, representing a valuable resource for rice improvement. The findings in this study provide a critical analysis of the genetic diversity of upland rice germplasm that would be useful for rice yield improvement. We suggested further breeding and genetic analyses.

Plants ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 68
Author(s):  
Abdulwahab S. Shaibu ◽  
Hassan Ibrahim ◽  
Zainab L. Miko ◽  
Ibrahim B. Mohammed ◽  
Sanusi G. Mohammed ◽  
...  

Knowledge of the genetic structure and diversity of germplasm collections is crucial for sustainable genetic improvement through hybridization programs and rapid adaptation to changing breeding objectives. The objective of this study was to determine the genetic diversity and population structure of 281 International Institute of Tropical Agriculture (IITA) soybean accessions using diversity array technology (DArT) and single nucleotide polymorphism (SNP) markers for the efficient utilization of these accessions. From the results, the SNP and DArT markers were well distributed across the 20 soybean chromosomes. The cluster and principal component analyses revealed the genetic diversity among the 281 accessions by grouping them into two stratifications, a grouping that was also evident from the population structure analysis, which divided the 281 accessions into two distinct groups. The analysis of molecular variance revealed that 97% and 98% of the genetic variances using SNP and DArT markers, respectively, were within the population. Genetic diversity indices such as Shannon’s diversity index, diversity and unbiased diversity revealed the diversity among the different populations of the soybean accessions. The SNP and DArT markers used provided similar information on the structure, diversity and polymorphism of the accessions, which indicates the applicability of the DArT marker in genetic diversity studies. Our study provides information about the genetic structure and diversity of the IITA soybean accessions that will allow for the efficient utilization of these accessions in soybean improvement programs, especially in Africa.


Plants ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2025
Author(s):  
Shyryn Almerekova ◽  
Yuliya Genievskaya ◽  
Saule Abugalieva ◽  
Kazuhiro Sato ◽  
Yerlan Turuspekov

The genetic relationship and population structure of two-rowed barley accessions from Kazakhstan were assessed using single-nucleotide polymorphism (SNP) markers. Two different approaches were employed in the analysis: (1) the accessions from Kazakhstan were compared with barley samples from six different regions around the world using 1955 polymorphic SNPs, and (2) 94 accessions collected from six breeding programs from Kazakhstan were studied using 5636 polymorphic SNPs using a 9K Illumina Infinium assay. In the first approach, the neighbor-joining tree showed that the majority of the accessions from Kazakhstan were grouped in a separate subcluster with a common ancestral node; there was a sister subcluster that comprised mainly barley samples that originated in Europe. The Pearson’s correlation analysis suggested that Kazakh accessions were genetically close to samples from Africa and Europe. In the second approach, the application of the STRUCTURE package using 5636 polymorphic SNPs suggested that Kazakh barley samples consisted of five subclusters in three major clusters. The principal coordinate analysis plot showed that, among six breeding origins in Kazakhstan, the Krasnovodopad (KV) and Karaganda (KA) samples were the most distant groups. The assessment of the pedigrees in the KV and KA samples showed that the hybridization schemes in these breeding stations heavily used accessions from Ethiopia and Ukraine, respectively. The comparative analysis of the KV and KA samples allowed us to identify 214 SNPs with opposite allele frequencies that were tightly linked to 60 genes/gene blocks associated with plant adaptation traits, such as the heading date and plant height. The identified SNP markers can be efficiently used in studies of barley adaptation and deployed in breeding projects to develop new competitive cultivars.


Author(s):  
Kotaro Dokan ◽  
Sayu Kawamura ◽  
Kosuke M Teshima

Abstract Single nucleotide polymorphism (SNP) data are widely used in research on natural populations. Although they are useful, SNP genotyping data are known to contain bias, normally referred to as ascertainment bias, because they are conditioned by already confirmed variants. This bias is introduced during the genotyping process, including the selection of populations for novel SNP discovery and the number of individuals involved in the discovery panel and selection of SNP markers. It is widely recognized that ascertainment bias can cause inaccurate inferences in population genetics and several methods to address these bias issues have been proposed. However, especially in natural populations, it is not always possible to apply an ideal ascertainment scheme because natural populations tend to have complex structures and histories. In addition, it was not fully assessed if ascertainment bias has the same effect on different types of population structure. Here we examine the effects of bias produced during the selection of population for SNP discovery and consequent SNP marker selection processes under three demographic models: the island, stepping-stone, and population split models. Results show that site frequency spectra and summary statistics contain biases that depend on the joint effect of population structure and ascertainment schemes. Additionally, population structure inferences are also affected by ascertainment bias. Based on these results, it is recommended to evaluate the validity of the ascertainment strategy prior to the actual typing process because the direction and extent of ascertainment bias vary depending on several factors.


2020 ◽  
Author(s):  
TEWODROS TESFAYE NEGASH ◽  
KASSAHUN TESFAYE ◽  
GEMECHU KENENI WAKEYO ◽  
CATHRINE ZIYOMO

Abstract BackgroundSesame is an important oil crop widely cultivated in Africa and Asia continent. Characterization of genetic diversity and population structure of sesame genotypes in these continents can be used to designing breeding methods. In the present study, 300 sesame genotypes comprising 209 local, and 75 exotic collection, and 16 released varieties provided from the Ethiopian Biodiversity Institute and research centers were used in the present study.ResultsThe panel was genotyped using two ultra-high-throughput diversity array technology (DArT) markers (silicoDArT and SNP). Both markers were used to identify the genetic diversity and population structure of sesame germplasm. A total of 6115 silicoDArT and 6474 SNP markers were reported, of which 5002 silicoDArT and 4638 SNP markers were screening with quality control parameters. The average polymorphic information content values of silicoDArT and SNP markers were 0.07 and 0.08, respectively. For further analysis, the allele frequency for each SNP site was calculated and purified with MAF < 0.01 and left 2997 high-quality SNPs evenly distributed across the whole genome that could be used for subsequent analysis. All genotypes used in this study were descended from eight 8 geographical origins. The genetic diversity analysis showed that the average nucleotide diversity of the panel was 0.14. Considering the genotypes based on their geographical origin, Africa collections (0.21) as a whole without Ethiopian collection was more diverse than Asia and when further portioned Africa, North Africa (0.23) collection was more diverse than others, but at the continent level, Asia (0.17) was more diverse than Africa (0.14). The genetic distance among the sesame populations was ranged from 0.015 to 0.394, with an average of 0.165. The sesame populations was clustered into four groups. The structure analysis divided the panel into four subgroups and 21 genotypes were clustered as an admixture. These indicates genotypes from the same origin didn’t classify properly on the premise of the country of origin. ConclusionsThe genetic diversity and population structure revealed in this study should guide the future research work to design association studies and the systematic utilization of the genetic variation characterizing the sesame panel.


Agronomy ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 604
Author(s):  
Subhash Chander ◽  
Ana Luísa Garcia-Oliveira ◽  
Melaku Gedil ◽  
Trushar Shah ◽  
Gbemisola Oluwayemisi Otusanya ◽  
...  

Soybean productivity in sub-Saharan Africa (SSA) is less than half of the global average yield. To plug the productivity gap, further improvement in grain yield must be attained by enhancing the genetic potential of new cultivars that depends on the genetic diversity of the parents. Hence, our aim was to assess genetic diversity and population structure of elite soybean genotypes, mainly released cultivars and advanced selections in SSA. In this study, a set of 165 lines was genotyped with high-throughput single nucleotide polymorphism (SNP) markers covering the complete genome of soybean. The genetic diversity (0.414) was high considering the bi-allelic nature of SNP markers. The polymorphic information content (PIC) varied from 0.079 to 0.375, with an average of 0.324 and about 49% of the markers had a PIC value above 0.350. Cluster analysis grouped all the genotypes into three major clusters. The model-based STRUCTURE and discriminant analysis of principal components (DAPC) exhibited high consistency in the allocation of lines in subpopulations or groups. Nonetheless, they presented some discrepancy and identified the presence of six and five subpopulations or groups, respectively. Principal coordinate analysis revealed more consistency with subgroups suggested by DAPC analysis. Our results clearly revealed the broad genetic base of TGx (Tropical Glycine max) lines that soybean breeders may select parents for crossing, testing and selection of future cultivars with desirable traits for SSA.


Plants ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 705
Author(s):  
John Carlos I. Ignacio ◽  
Maricris Zaidem ◽  
Carlos Casal ◽  
Shalabh Dixit ◽  
Tobias Kretzschmar ◽  
...  

Direct seeded rice (DSR) is a mainstay for planting rice in the Americas, and it is rapidly becoming more popular in Asia. It is essential to develop rice varieties that are suitable for this type of production system. ASD1, a landrace from India, possesses several traits desirable for direct-seeded fields, including tolerance to anaerobic germination (AG). To map the genetic basis of its tolerance, we examined a population of 200 F2:3 families derived from a cross between IR64 and ASD1 using the restriction site-associated DNA sequencing (RAD-seq) technology. This genotyping platform enabled the identification of 1921 single nucleotide polymorphism (SNP) markers to construct a high-resolution genetic linkage map with an average interval of 0.9 cM. Two significant quantitative trait loci (QTLs) were detected on chromosomes 7 and 9, qAG7 and qAG9, with LOD scores of 7.1 and 15.0 and R2 values of 15.1 and 29.4, respectively. Here, we obtained more precise locations of the QTLs than traditional simple sequence repeat and low-density SNP genotyping methods and may help further dissect the genetic factors of these QTLs.


2021 ◽  
Vol 22 (7) ◽  
pp. 3477
Author(s):  
Julia Zaborowska ◽  
Bartosz Łabiszak ◽  
Annika Perry ◽  
Stephen Cavers ◽  
Witold Wachowiak

Mountain plants, challenged by vegetation time contractions and dynamic changes in environmental conditions, developed adaptations that help them to balance their growth, reproduction, survival, and regeneration. However, knowledge regarding the genetic basis of species adaptation to higher altitudes remain scarce for most plant species. Here, we attempted to identify such corresponding genomic regions of high evolutionary importance in two closely related European pines, Pinus mugo and P. uncinata, contrasting them with a reference lowland relative—P. sylvestris. We genotyped 438 samples at thousands of single nucleotide polymorphism (SNP) markers, tested their genetic differentiation and population structure followed by outlier detection and gene ontology annotations. Markers clearly differentiated the species and uncovered patterns of population structure in two of them. In P. uncinata three Pyrenean sites were grouped together, while two outlying populations constituted a separate cluster. In P. sylvestris, Spanish population appeared distinct from the remaining four European sites. Between mountain pines and the reference species, 35 candidate genes for altitude-dependent selection were identified, including such encoding proteins responsible for photosynthesis, photorespiration and cell redox homeostasis, regulation of transcription, and mRNA processing. In comparison between two mountain pines, 75 outlier SNPs were found in proteins involved mainly in the gene expression and metabolism.


2021 ◽  
Vol 19 (1) ◽  
pp. 20-28
Author(s):  
Abush Tesfaye Abebe ◽  
Adesike Oladoyin Kolawole ◽  
Nnanna Unachukwu ◽  
Godfree Chigeza ◽  
Hailu Tefera ◽  
...  

AbstractSoybean (Glycine max (L.) Merr.) is an important legume crop with high commercial value widely cultivated globally. Thus, the genetic characterization of the existing soybean germplasm will provide useful information for enhanced conservation, improvement and future utilization. This study aimed to assess the extent of genetic diversity of soybean elite breeding lines and varieties developed by the soybean breeding programme of the International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria. The genetic diversity of 65 soybean genotypes was studied using single-nucleotide polymorphism (SNP) markers. The result revealed that 2446 alleles were detected, and the indicators for allelic richness and diversity had good differentiating power in assessing the diversity of the genotypes. The three complementary approaches used in the study grouped the germplasm into three major clusters based on genetic relatedness. The analysis of molecular variance revealed that 71% (P < 0.001) variation was due to among individual genotypes, while 11% (P < 0.001) was ascribed to differences among the three clusters, and the fixation index (FST) was 0.11 for the SNP loci, signifying moderate genetic differentiation among the genotypes. The identified private alleles indicate that the soybean germplasm contains diverse variability that is yet to be exploited. The SNP markers revealed high diversity in the studied germplasm and found to be efficient for assessing genetic diversity in the crop. These results provide valuable information that might be utilized for assessing the genetic variability of soybean and other legume crops germplasm by breeding programmes.


2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Weifan Gao ◽  
Sukumar Saha ◽  
Din-Pow Ma ◽  
Yufang Guo ◽  
Johnie N. Jenkins ◽  
...  

A cotton fiber cDNA and its genomic sequences encoding an A-type cyclin-dependent kinase (GhCDKA) were cloned and characterized. The encoded GhCDKA protein contains the conserved cyclin-binding, ATP binding, and catalytic domains. Northern blot and RT-PCR analysis revealed that the GhCDKA transcript was high in 5–10 DPA fibers, moderate in 15 and 20 DPA fibers and roots, and low in flowers and leaves. GhCDKA protein levels in fibers increased from 5–15 DPA, peaked at 15 DPA, and decreased from 15 t0 20 DPA. The differential expression of GhCDKA suggested that the gene might play an important role in fiber development. The GhCDKA sequence data was used to develop single nucleotide polymorphism (SNP) markers specific for the CDKA gene in cotton. A primer specific to one of the SNPs was used to locate the CDKA gene to chromosome 16 by deletion analysis using a series of hypoaneuploid interspecific hybrids.


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