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Spatial structure and climatic adaptation in African maize revealed by surveying SNP diversity in relation to global breeding and landrace panels.

Westengen OT, Berg PR, Kent MP, Brysting AK - PLoS ONE (2012)

Bottom Line: Environmental association analysis was used to detect SNPs associated with three climatic variables based on the full 43,963 SNP dataset.Controlling for population history in a linear model, we identify 79 SNPs associated with maximum temperature during the growing season.The associations located in genes of known importance for abiotic stress tolerance are interesting candidates for local adaptations.

View Article: PubMed Central - PubMed

Affiliation: Centre for Development and the Environment, SUM, University of Oslo, Oslo, Norway. ola.westengen@sum.uio.no

ABSTRACT

Background: Climate change threatens maize productivity in sub-Saharan Africa. To ensure food security, access to locally adapted genetic resources and varieties is an important adaptation measure. Most of the maize grown in Africa is a genetic mix of varieties introduced at different historic times following the birth of the trans-Atlantic economy, and knowledge about geographic structure and local adaptations is limited.

Methodology: A panel of 48 accessions of maize representing various introduction routes and sources of historic and recent germplasm introductions in Africa was genotyped with the MaizeSNP50 array. Spatial genetic structure and genetic relationships in the African panel were analysed separately and in the context of a panel of 265 inbred lines representing global breeding material (based on 26,900 SNPs) and a panel of 1127 landraces from the Americas (270 SNPs). Environmental association analysis was used to detect SNPs associated with three climatic variables based on the full 43,963 SNP dataset.

Conclusions: The genetic structure is consistent between subsets of the data and the markers are well suited for resolving relationships and admixture among the accessions. The African accessions are structured in three clusters reflecting historical and current patterns of gene flow from the New World and within Africa. The Sahelian cluster reflects original introductions of Meso-American landraces via Europe and a modern introduction of temperate breeding material. The Western cluster reflects introduction of Coastal Brazilian landraces, as well as a Northeast-West spread of maize through Arabic trade routes across the continent. The Eastern cluster most strongly reflects gene flow from modern introduced tropical varieties. Controlling for population history in a linear model, we identify 79 SNPs associated with maximum temperature during the growing season. The associations located in genes of known importance for abiotic stress tolerance are interesting candidates for local adaptations.

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Structure plot of the assignment probabilities in the African panel.Each accession is represented by a bar and the highest Q group membership defines cluster assignment. Asterisks mark the three modern varieties included (from left to right: Staha; TMV1, Longe 5). The plot is based on 26,900 SNPs and the highest probability run for K = 3.
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pone-0047832-g001: Structure plot of the assignment probabilities in the African panel.Each accession is represented by a bar and the highest Q group membership defines cluster assignment. Asterisks mark the three modern varieties included (from left to right: Staha; TMV1, Longe 5). The plot is based on 26,900 SNPs and the highest probability run for K = 3.

Mentions: STRUCTURE analysis of the African panel alone (26,900 SNPs) indicates that the best estimate of K is 3; the likelihood increases up to K = 3 with a decrease in likelihood and an increase in variation and decrease in delta K between runs thereafter (Fig. S1.1, S1.2). A STRUCTURE plot for the 48 accessions is presented in Fig. 1. We name the clusters according to main geographic origin: a Western cluster, including the West African populations plus two Zambian populations; a Sahelian cluster found in Sudan and Chad, including the Spanish population; and an Eastern cluster including all the Tanzanian populations. The names of the clusters and their location on the map (Fig. 2) are based on the average latitude and longitude values of accessions within clusters, excluding the two Zambian accessions from the Western cluster and the Spanish accession from the Sahelian cluster. The K = 3 pattern is consistent between subsets of the data. Comparison of number of assigned accessions (with K = 3) in the 10% and 1% datasets with the full 26,900 African panel dataset is summarized in Table 1 and the full overview of the membership assignments is found in Table S4. Correlations of membership ratios between cluster 1 (Eastern) from the different analyses are strong and significant (Fig. S2a–c). The NJ analysis of the African panel is largely in agreement with the STRUCTURE results, with the accessions belonging to the Western cluster clustering separately from all other accessions and with some intermixture between the accessions belonging to the Sahelian and Eastern clusters (Fig. S3).


Spatial structure and climatic adaptation in African maize revealed by surveying SNP diversity in relation to global breeding and landrace panels.

Westengen OT, Berg PR, Kent MP, Brysting AK - PLoS ONE (2012)

Structure plot of the assignment probabilities in the African panel.Each accession is represented by a bar and the highest Q group membership defines cluster assignment. Asterisks mark the three modern varieties included (from left to right: Staha; TMV1, Longe 5). The plot is based on 26,900 SNPs and the highest probability run for K = 3.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3472975&req=5

pone-0047832-g001: Structure plot of the assignment probabilities in the African panel.Each accession is represented by a bar and the highest Q group membership defines cluster assignment. Asterisks mark the three modern varieties included (from left to right: Staha; TMV1, Longe 5). The plot is based on 26,900 SNPs and the highest probability run for K = 3.
Mentions: STRUCTURE analysis of the African panel alone (26,900 SNPs) indicates that the best estimate of K is 3; the likelihood increases up to K = 3 with a decrease in likelihood and an increase in variation and decrease in delta K between runs thereafter (Fig. S1.1, S1.2). A STRUCTURE plot for the 48 accessions is presented in Fig. 1. We name the clusters according to main geographic origin: a Western cluster, including the West African populations plus two Zambian populations; a Sahelian cluster found in Sudan and Chad, including the Spanish population; and an Eastern cluster including all the Tanzanian populations. The names of the clusters and their location on the map (Fig. 2) are based on the average latitude and longitude values of accessions within clusters, excluding the two Zambian accessions from the Western cluster and the Spanish accession from the Sahelian cluster. The K = 3 pattern is consistent between subsets of the data. Comparison of number of assigned accessions (with K = 3) in the 10% and 1% datasets with the full 26,900 African panel dataset is summarized in Table 1 and the full overview of the membership assignments is found in Table S4. Correlations of membership ratios between cluster 1 (Eastern) from the different analyses are strong and significant (Fig. S2a–c). The NJ analysis of the African panel is largely in agreement with the STRUCTURE results, with the accessions belonging to the Western cluster clustering separately from all other accessions and with some intermixture between the accessions belonging to the Sahelian and Eastern clusters (Fig. S3).

Bottom Line: Environmental association analysis was used to detect SNPs associated with three climatic variables based on the full 43,963 SNP dataset.Controlling for population history in a linear model, we identify 79 SNPs associated with maximum temperature during the growing season.The associations located in genes of known importance for abiotic stress tolerance are interesting candidates for local adaptations.

View Article: PubMed Central - PubMed

Affiliation: Centre for Development and the Environment, SUM, University of Oslo, Oslo, Norway. ola.westengen@sum.uio.no

ABSTRACT

Background: Climate change threatens maize productivity in sub-Saharan Africa. To ensure food security, access to locally adapted genetic resources and varieties is an important adaptation measure. Most of the maize grown in Africa is a genetic mix of varieties introduced at different historic times following the birth of the trans-Atlantic economy, and knowledge about geographic structure and local adaptations is limited.

Methodology: A panel of 48 accessions of maize representing various introduction routes and sources of historic and recent germplasm introductions in Africa was genotyped with the MaizeSNP50 array. Spatial genetic structure and genetic relationships in the African panel were analysed separately and in the context of a panel of 265 inbred lines representing global breeding material (based on 26,900 SNPs) and a panel of 1127 landraces from the Americas (270 SNPs). Environmental association analysis was used to detect SNPs associated with three climatic variables based on the full 43,963 SNP dataset.

Conclusions: The genetic structure is consistent between subsets of the data and the markers are well suited for resolving relationships and admixture among the accessions. The African accessions are structured in three clusters reflecting historical and current patterns of gene flow from the New World and within Africa. The Sahelian cluster reflects original introductions of Meso-American landraces via Europe and a modern introduction of temperate breeding material. The Western cluster reflects introduction of Coastal Brazilian landraces, as well as a Northeast-West spread of maize through Arabic trade routes across the continent. The Eastern cluster most strongly reflects gene flow from modern introduced tropical varieties. Controlling for population history in a linear model, we identify 79 SNPs associated with maximum temperature during the growing season. The associations located in genes of known importance for abiotic stress tolerance are interesting candidates for local adaptations.

Show MeSH