| Literature DB >> 28642589 |
Moses Cheloti Wambulwa1,2,3,4, Muditha Kasun Meegahakumbura1,2,3,5, Samson Kamunya6, Alice Muchugi4, Michael Möller7, Jie Liu1, Jian-Chu Xu8,9, De-Zhu Li10,11,12, Lian-Ming Gao13.
Abstract
Despite the highly economic value of tea in Africa, its genetic and geographic origins remain largely unexplored. Here we address this by collecting 439 samples across 11 countries in Africa and Asia to investigate the origin and genepool composition of African tea based on 23 nuclear microsatellites loci (nSSRs) and three cpDNA intergenic spacer regions. Our results indicated that the African tea represents a potpourri originating from multiple introductions over time. The nSSR analysis revealed that the majority (79%) of tea accessions collected in Africa belong to Indian Assam tea which have likely originated from India and/or Sri Lanka. The patterns of nSSR variation also showed that Chinese Assam tea is genetically distinct from Indian Assam tea, and has rarely been used in African tea breeding efforts since only 4% of the African tea accessions possessed this genotype. We found a total of 22 cpDNA haplotypes, which grouped into three main geographic clades that were concordant with the distribution of microsatellite genotypes. Several private cpDNA haplotypes were identified in Chinese Assam tea in Southern Yunnan province of China. Therefore Chinese Assam tea will be important for the enrichment of African tea gene pools. Our results is a useful guide in future tea breeding programmes in Africa.Entities:
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Year: 2017 PMID: 28642589 PMCID: PMC5481375 DOI: 10.1038/s41598-017-04228-0
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Bayesian assignment of probabilities for 439 tea individual from Africa and Asia. The inferred genetic groups are distinguished by different colors. The black lines delimit accessions from different countries. Each accession is indicated by a vertical bar, and the length of each colored section in each vertical bar represents the posterior probability that a given accession belongs to a particular genetic group.
Figure 2Geographic distribution of nSSR alleles. The colours correspond to the genetic clusters defined by STRUCTURE analysis at K = 3. The proportions of different groups in pie-charts are based on membership coefficients at K = 3. A shape file with genotype proportions in the different countries was generated in DIVA-GIS v7.5.0.0 (http://www.diva-gis.org/). The shape file was then used to generate the map in ArcGIS v10.2.2 (Environmental Systems Research Institute, Redlands, CA, USA) (http://www.esri.com/).
Analysis of molecular variance (AMOVA) for tea individuals from all the 11 countries.
| Source of variation | d.f. | Sum of squares | Variance components | % of variation |
|---|---|---|---|---|
| Among countries | 10 | 472.515 | 0.57144 | 6.33 |
| Among individuals | 439 | 3349.5 | 7.62984 | 84.47 |
| Total | 449 | 3822.015 | 8.2013 |
Figure 3Heat map depicting pairwise F ST estimates between countries. The map was generated by using the ‘heatmap.2’ function from the gplots package in R using pairwise F ST matrix calculated in StAMPP. Populations (countries) are across the X- and Y-axis, with each square indicating the F ST estimate between the two respective individuals. The magnitude of the genetic differentiation is indicated by the colour range. MD, Madagascar; SL, Sri Lanka; CHN, China; MW, Malawi; SA, South Africa; RW, Rwanda; TZ, Tanzania; NGR, Nigeria; CAM, Cameroon; IND, India; KEN, Kenya.
Figure 4Median joining network of haplotypes of tea based on cpDNA sequence data. The size of the circles corresponds to the frequency of each haplotype whereas the small black triangles represent mutational steps.