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Molecular evaluation of orphan Afghan common wheat (Triticum aestivum L.) landraces collected by Dr. Kihara using single nucleotide polymorphic markers.

Manickavelu A, Jighly A, Ban T - BMC Plant Biol. (2014)

Bottom Line: Here we used SNP analysis to demonstrate the importance of Afghan wheat landraces and found tremendous genetic diversity and province-specific characteristics unique to this geographic region.This result closely resembles existing agro-climatic zones within Afghanistan, as well as the wheat varieties commonly cultivated within these regions.Molecular variance analysis showed a higher proportion of intra-province variation among landraces compared with variation among all landraces as a whole.

View Article: PubMed Central - PubMed

ABSTRACT

Background: Landraces are an important source of genetic diversity in common wheat, but archival collections of Afghan wheat landraces remain poorly characterised. The recent development of array based marker systems, particularly single nucleotide polymorphism (SNP) markers, provide an excellent tool for examining the genetic diversity of local populations. Here we used SNP analysis to demonstrate the importance of Afghan wheat landraces and found tremendous genetic diversity and province-specific characteristics unique to this geographic region.

Results: A total of 446 Afghan wheat landraces were analysed using genotype by sequencing (GBS) arrays containing ~10 K unique markers. Pair-wise genetic distance analyses revealed significant genetic distances between landraces, particularly among those collected from distanced provinces. From these analyses, we were able to divide the landraces into 14 major classes, with the greatest degree of diversity evident among landraces isolated from Badakhshan province. Population-based analyses revealed an additional 15 sub-populations within our germplasm, and significant correlations were evident in both the provincial and botanical varieties. Genetic distance analysis was used to identify differences among provinces, with the strongest correlations seen between landraces from Herat and Ghor province, followed closely by those between Badakhshan and Takhar provinces. This result closely resembles existing agro-climatic zones within Afghanistan, as well as the wheat varieties commonly cultivated within these regions. Molecular variance analysis showed a higher proportion of intra-province variation among landraces compared with variation among all landraces as a whole.

Conclusion: The SNP analyses presented here highlight the importance and genetic diversity of Afghan wheat landraces. Furthermore, these data strongly refute a previous analysis that suggested low genetic diverse within this germplasm. Ongoing analyses include phenotypic characterisation of these landraces to identify functional traits associated with individual genotypes. Taken together, these analyses can be used to help improve wheat cultivation in Afghanistan, while providing insights into the evolution and selective pressures underlying these distinct landraces.

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Population structures of 385 Afghan wheat landraces collected from nine provinces (K = 2 to 10); only provinces with ≥10 landraces were used in this analysis.
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Fig7: Population structures of 385 Afghan wheat landraces collected from nine provinces (K = 2 to 10); only provinces with ≥10 landraces were used in this analysis.

Mentions: Next, landrace population structures were re-estimated using only 385 landraces collected from Badakhshan, Ghor, Herat, Takhar, Kabul, Badghis, Kandahar, Bamyan, and Samangan provinces, resulting in 10 distinct sub-populations. The strongest divisions were seen among landraces isolated from Badakhshan and Takhar provinces, as these two regions grouped independently of the remaining regions when divided into two groups (K = 2; Figure 7). Increasing the number of clusters resulted in division of the Badakhshan samples into seven sub-populations, of which five were unique to this province.Figure 7


Molecular evaluation of orphan Afghan common wheat (Triticum aestivum L.) landraces collected by Dr. Kihara using single nucleotide polymorphic markers.

Manickavelu A, Jighly A, Ban T - BMC Plant Biol. (2014)

Population structures of 385 Afghan wheat landraces collected from nine provinces (K = 2 to 10); only provinces with ≥10 landraces were used in this analysis.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4255927&req=5

Fig7: Population structures of 385 Afghan wheat landraces collected from nine provinces (K = 2 to 10); only provinces with ≥10 landraces were used in this analysis.
Mentions: Next, landrace population structures were re-estimated using only 385 landraces collected from Badakhshan, Ghor, Herat, Takhar, Kabul, Badghis, Kandahar, Bamyan, and Samangan provinces, resulting in 10 distinct sub-populations. The strongest divisions were seen among landraces isolated from Badakhshan and Takhar provinces, as these two regions grouped independently of the remaining regions when divided into two groups (K = 2; Figure 7). Increasing the number of clusters resulted in division of the Badakhshan samples into seven sub-populations, of which five were unique to this province.Figure 7

Bottom Line: Here we used SNP analysis to demonstrate the importance of Afghan wheat landraces and found tremendous genetic diversity and province-specific characteristics unique to this geographic region.This result closely resembles existing agro-climatic zones within Afghanistan, as well as the wheat varieties commonly cultivated within these regions.Molecular variance analysis showed a higher proportion of intra-province variation among landraces compared with variation among all landraces as a whole.

View Article: PubMed Central - PubMed

ABSTRACT

Background: Landraces are an important source of genetic diversity in common wheat, but archival collections of Afghan wheat landraces remain poorly characterised. The recent development of array based marker systems, particularly single nucleotide polymorphism (SNP) markers, provide an excellent tool for examining the genetic diversity of local populations. Here we used SNP analysis to demonstrate the importance of Afghan wheat landraces and found tremendous genetic diversity and province-specific characteristics unique to this geographic region.

Results: A total of 446 Afghan wheat landraces were analysed using genotype by sequencing (GBS) arrays containing ~10 K unique markers. Pair-wise genetic distance analyses revealed significant genetic distances between landraces, particularly among those collected from distanced provinces. From these analyses, we were able to divide the landraces into 14 major classes, with the greatest degree of diversity evident among landraces isolated from Badakhshan province. Population-based analyses revealed an additional 15 sub-populations within our germplasm, and significant correlations were evident in both the provincial and botanical varieties. Genetic distance analysis was used to identify differences among provinces, with the strongest correlations seen between landraces from Herat and Ghor province, followed closely by those between Badakhshan and Takhar provinces. This result closely resembles existing agro-climatic zones within Afghanistan, as well as the wheat varieties commonly cultivated within these regions. Molecular variance analysis showed a higher proportion of intra-province variation among landraces compared with variation among all landraces as a whole.

Conclusion: The SNP analyses presented here highlight the importance and genetic diversity of Afghan wheat landraces. Furthermore, these data strongly refute a previous analysis that suggested low genetic diverse within this germplasm. Ongoing analyses include phenotypic characterisation of these landraces to identify functional traits associated with individual genotypes. Taken together, these analyses can be used to help improve wheat cultivation in Afghanistan, while providing insights into the evolution and selective pressures underlying these distinct landraces.

Show MeSH