scholarly journals High-throughput genotype based population structure analysis of selected buffalo breeds

2018 ◽  
Author(s):  
Prakash B. Thakor ◽  
Ankit T. Hinsu ◽  
Dhruv R. Bhatiya ◽  
Tejas M. Shah ◽  
Nilesh Nayee ◽  
...  
Keyword(s):  
Population Structure ◽  
Genetic Structure ◽  
Structure Analysis ◽  
Milk Production ◽  
High Throughput ◽  
Snp Markers ◽  
High Density ◽  
Sequence Information ◽  
Snp Chip ◽  
Geographical Regions

AbstractThe water buffalo (Bubalus bubalis) has shown enormous milk production potential in many Asian countries. India is considered as the home tract of some of the best buffalo breeds. However, genetic structure of the Indian river buffalo is poorly understood. Hence, for selection and breeding strategies, there is a need to characterize the populations and understand the genetic structure of various buffalo breeds. In this study, we have analysed genetic variability and population structure of seven buffalo breeds from their respective geographical regions using Axiom® Buffalo Genotyping Array having 124,030 Single Nucleotide Polymorphisms (SNPs). Blood samples were obtained from 302 buffaloes comprising Murrah, Nili-Ravi, Mehsana, Jaffarabadi, Banni, Pandharpuri and Surti breeds. Diversity, as measured by expected heterozygosity (He) ranged from 0.364 in the Surti to 0.384 in the Murrah breed. All the breeds showed negligible inbreeding coefficient. Pair-wise FST values revealed the lowest genetic distance between Mehsana and Nili-Ravi (0.0022) while highest between Surti and Pandharpuri (0.030). Principal component analysis and structure analysis unveiled the differentiation of Surti, Pandharpuri and Jaffarabadi in first two PCs, while remaining breeds were grouped together as a separate single cluster. Murrah and Mehsana showed early linkage disequilibrium decay while Surti breed showed late decay, similarly LD based Ne was drastically declined for Murrah and Mehsana since last 100 generations. In LD blocks to QTLs concordance analysis, 14.19 per cent of concordance was observed with 873 (out of 1144) LD blocks overlapped with 8912 (out of 67804) QTLs. Overall, total 4090 markers were identified from all LD blocks for six types of traits. Results of this study indicated that these SNP markers could differentiate phenotypically distinct breeds like Surti,Pandharpuri and Jaffarabadi but not others. So, there is a need to develop SNP chip based on SNP markers identified by sequence information of local breeds.Author SummaryIndian buffaloes, through 13 recognised breeds, contribute about 49% in total milk production and play a vital role in enhancing the economic condition of Indian farmers. High density genotyping these breeds will allow us to study differences at the molecular level. Evolutionary relationship and phenotypes relations with genotype could be tested with high density genotyping. Breed structure analysis helps to take effective breeding policy decision. In the present study, we have used the high-throughput microarray based genotyping technology for SNP markers. These markers were used for breed differentiation using various genetic parameters. Population structure reflected the proportion of breed admixture among studied breeds. We have also tried to dig the markers associated with traits based LD calculation. However, these SNPs couldn’t explain obvious variation up to the expected level, hence, there is need to develop an indigenous SNP chip based on Indian buffalo populations.

scholarly journals High-throughput genotype-based population structure analysis of selected buffalo breeds

2021 ◽  
Vol 5 (2) ◽  
Author(s):  
Prakash B Thakor ◽  
Ankit T Hinsu ◽  
Dhruv R Bhatia ◽  
Tejas M Shah ◽  
Nilesh Nayee ◽  
...  
Keyword(s):  
Population Structure ◽  
Genetic Structure ◽  
Structure Analysis ◽  
Principal Component ◽  
Snp Markers ◽  
Sequence Information ◽  
Population Structure Analysis ◽  
Geographical Regions ◽  
Indian River ◽  
Single Cluster

Abstract India is considered as the home tract of some of the best buffalo breeds. However, the genetic structure of the Indian river buffalo is poorly understood. Hence, there is a need to characterize the populations and understand the genetic structure of various buffalo breeds for selection and to design breeding strategies. In this study, we have analyzed genetic variability and population structure of seven buffalo breeds from their respective geographical regions using Axiom Buffalo Genotyping Array. Diversity, as measured by expected heterozygosity, ranged from 0.364 in Surti to 0.384 in Murrah breed, and pair-wise FST values revealed the lowest genetic distance between Murrah and Nili-Ravi (0.0022), while the highest between Surti and Pandharpuri (0.030). Principal component analysis and structure analysis unveiled the differentiation of Surti, Pandharpuri, and Jaffarabadi in first two principal components and at K = 4, respectively, while remaining breeds were grouped together as a separate single cluster and admixed. Murrah and Mehsana showed early linkage disequilibrium (LD) decay, while Surti breed showed late decay. In LD blocks to quantitative trait locis (QTLs) concordance analysis, 4.65% of concordance was observed with 873 LD blocks overlapped with 2,330 QTLs. Overall, total 4,090 markers were identified from all LD blocks for six types of traits. Results of this study indicated that these single-nucleotide polymorphism (SNP) markers could differentiate phenotypically distinct breeds like Surti, Pandharpuri, and Jaffarabadi but not others. So, there is a need to develop SNP chip based on SNP markers identified by sequence information of local breeds.

scholarly journals Chinese Fir Breeding in the High-Throughput Sequencing Era: Insights from SNPs

Forests ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 681 ◽  
Author(s):  
Huiquan Zheng ◽  
Dehuo Hu ◽  
Ruping Wei ◽  
Shu Yan ◽  
Runhui Wang
Keyword(s):  
Population Structure ◽  
Genetic Structure ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Breeding Population ◽  
Population Diversity ◽  
Chinese Fir ◽  
High Density ◽  
Population Structure Analysis ◽  
Snp Panel

Knowledge on population diversity and structure is of fundamental importance for conifer breeding programs. In this study, we concentrated on the development and application of high-density single nucleotide polymorphism (SNP) markers through a high-throughput sequencing technique termed as specific-locus amplified fragment sequencing (SLAF-seq) for the economically important conifer tree species, Chinese fir (Cunninghamia lanceolata). Based on the SLAF-seq, we successfully established a high-density SNP panel consisting of 108,753 genomic SNPs from Chinese fir. This SNP panel facilitated us in gaining insight into the genetic base of the Chinese fir advance breeding population with 221 genotypes for its genetic variation, relationship and diversity, and population structure status. Overall, the present population appears to have considerable genetic variability. Most (94.15%) of the variability was attributed to the genetic differentiation of genotypes, very limited (5.85%) variation occurred on the population (sub-origin set) level. Correspondingly, low FST (0.0285–0.0990) values were seen for the sub-origin sets. When viewing the genetic structure of the population regardless of its sub-origin set feature, the present SNP data opened a new population picture where the advanced Chinese fir breeding population could be divided into four genetic sets, as evidenced by phylogenetic tree and population structure analysis results, albeit some difference in membership of the corresponding set (cluster vs. group). It also suggested that all the genetic sets were admixed clades revealing a complex relationship of the genotypes of this population. With a step wise pruning procedure, we captured a core collection (core 0.650) harboring 143 genotypes that maintains all the allele, diversity, and specific genetic structure of the whole population. This generalist core is valuable for the Chinese fir advanced breeding program and further genetic/genomic studies.

scholarly journals Genetic Diversity, Population Structure Analysis Using Ultra-High Throughput Diversity array Technology (DArTseq) in Different Origin Sesame (Sesamum indicum L)

2020 ◽  
Author(s):  
TEWODROS TESFAYE NEGASH ◽  
KASSAHUN TESFAYE ◽  
GEMECHU KENENI WAKEYO ◽  
CATHRINE ZIYOMO
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Structure Analysis ◽  
High Throughput ◽  
Research Work ◽  
Snp Markers ◽  
Diversity Array Technology ◽  
Population Structure Analysis ◽  
Array Technology ◽  
Sesame Genotypes

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.

scholarly journals Genetic diversity and population structure analysis of bambara groundnut (Vigna subterrenea L) landraces using DArT SNP markers

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253600
Author(s):  
Charles U. Uba ◽  
Happiness O. Oselebe ◽  
Abush A. Tesfaye ◽  
Wosene G. Abtew
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
West Africa ◽  
East Africa ◽  
Unknown Origin ◽  
Snp Markers ◽  
Bambara Groundnut ◽  
Conservation Strategy ◽  
Population Structure Analysis ◽  
Geographical Regions

Understanding the genetic structure and diversity of crops facilitates progress in plant breeding. A collection of 270 bambara groundnut (Vigna subterrenea L) landraces sourced from different geographical regions (Nigeria/Cameroon, West, Central, Southern and East Africa) and unknown origin (sourced from United Kingdom) was used to assess genetic diversity, relationship and population structure using DArT SNP markers. The major allele frequency ranged from 0.57 for unknown origin to 0.91 for West Africa region. The total gene diversity (0.482) and Shannon diversity index (0.787) was higher in West African accessions. The genetic distance between pairs of regions varied from 0.002 to 0.028 with higher similarity between Nigeria/Cameroon-West Africa accessions and East-Southern Africa accessions. The analysis of molecular variance (AMOVA) revealed 89% of genetic variation within population, 8% among regions and 3% among population. The genetic relatedness among the collections was evaluated using neighbor joining tree analysis, which grouped all the geographic regions into three major clusters. Three major subgroups of bambara groundnut were identified using the ADMIXTURE model program and confirmed by discriminant analysis of principal components (DAPC). These subgroups were West Africa, Nigeria/Cameroon and unknown origin that gave rise to sub-population one, and Central Africa was sub-population two, while Southern and East Africa were sub-population three. In general, the results of all the different analytical methods used in this study confirmed the existence of high level of diversity among the germplasm used in this study that might be utilized for future genetic improvement of bambara groundnut. The finding also provides new insight on the population structure of African bambara groundnut germplasm which will help in conservation strategy and management of the crop.

scholarly journals Genetic Diversity and Population Structure of Ethiopian Sheep Populations Revealed by High-Density SNP Markers

2017 ◽  
Vol 8 ◽  
Author(s):  
Zewdu Edea ◽  
Tadelle Dessie ◽  
Hailu Dadi ◽  
Kyoung-Tag Do ◽  
Kwan-Suk Kim
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Snp Markers ◽  
High Density

scholarly journals Estimation of the Genetic Diversity and Population Structure of Thailand’s Rice Landraces Using SNP Markers

Agronomy ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 995
Author(s):  
Wanchana Aesomnuk ◽  
Siriphat Ruengphayak ◽  
Vinitchan Ruanjaichon ◽  
Tanee Sreewongchai ◽  
Chanate Malumpong ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Genetic Differentiation ◽  
Isolation By Distance ◽  
Mantel Test ◽  
Snp Markers ◽  
High Yield ◽  
Rice Varieties ◽  
Rice Landraces ◽  
Geographical Regions

Rice is a staple food for more than half of the world’s population. Modern rice varieties have been developed for high yield and quality; however, there has been a substantial loss of diversity. A greater number of genetically dynamic landraces could offer valuable and useful genetic resources for rice improvement. In this study, the genetic diversity and population structure of 365 accessions of lowland and upland landraces from four populations from different geographical regions of Thailand were investigated using 75 SNP markers. Clustering analyses using maximum likelihood, Principal Coordinate Analysis (PCoA), and Discriminant Analysis of Principal Components (DAPC) clustered these landraces into two main groups, corresponding to indica and japonica groups. The indica group was further clustered into two subgroups according to the DAPC and STRUCTURE analyses (K = 3). The analysis of molecular variance (AMOVA) analysis results revealed that 91% of the variation was distributed among individuals, suggesting a high degree of genetic differentiation among rice accessions within the populations. Pairwise FST showed the greatest genetic differentiation between the northeastern and southern populations and the smallest genetic differentiation between the northern and northeastern populations. Isolation-by-distance analysis based on a Mantel test indicated a significant relationship between the genetic distance and geographic distance among the Thai rice landraces. The results from this study provide insight into the genetic diversity of Thai rice germplasm, which will enhance the germplasm characterization, conservation, and utilization in rice genetics and breeding.

scholarly journals Genetic diversity and population structure of Luffa acutangula accessions in a Thailand collection using SNP markers

2020 ◽  
Author(s):  
Grimar Abdiel Perez ◽  
Pumipat Tongyoo ◽  
Julapark Chunwongse ◽  
Hans de Jong ◽  
Paweena Chuenwarin
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Phylogenetic Tree ◽  
Structure Analysis ◽  
Fruit Shape ◽  
Snp Markers ◽  
Distinguishing Characteristic ◽  
Breeding Programs ◽  
Unrooted Phylogenetic Tree ◽  
Luffa Acutangula

AbstractThis study explored a germplasm consisting of 112 Luffa acutangula (ridge gourd) accessions mainly from Thailand, and some accessions from Vietnam, China, Philippines, Indonesia, USA, Bangladesh and Laos for an analysis of the population structure and underlying genetic diversity using 2,834 SNPs. STRUCTURE analysis (ΔK at K=6) allowed us to group the accessions into six subpopulations that corresponded well with the unrooted phylogenetic tree and principal coordinate analyses. The phylogenetic tree showed the diversity of L. acutangula in Thailand, and accessions from other countries apart from Thailand were grouped together in the same branches. In STRUCTURE, subpopulation 2 contained only accessions from Thailand while other subpopulations contained a combination of accessions from Thailand and from other countries. When plotted, the STRUCTURE bars to the area of collection, it revealed the geneflow from the surrounding places nearby as indicated by the admixed genetic in the STRUCTURE bars. AMOVA based on STRUCTURE clustering showed the variation between populations (12.83%) and confirmed the absence of population structure in subpopulations (−10.59%). There was a distinguishing characteristic fruit shape and length in each subpopulation. The ample genetic diversity found in the L. acutangula germplasm can be utilized in ridge gourd breeding programs to help meet the demands and needs of both consumers and farmers.

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