Journal articles 2014
Documents
Bulk genetic characterization of Ghanaian maize landraces using microsatellite markers
Oppong A, Bedoya CA, Ewool MB, Asante MD, Thompson RN, Adu-Dapaah H, Lamptey JNL, Ofori K, Offei SK and Warburton ML (2014). Bulk genetic characterization of Ghanaian maize landraces using microsatellite markers. Maydica 59:1–8. (G4007.13.04)
Abstract: Maize (Zea mays L) was first introduced into Ghana over five centuries ago and remains the most important cereal staple, grown in all agro-ecologies across the country. Yield from farmers' fields are low, which is attributed in part to farmer's preferences and/or reliance on local landraces for cultivation. Efforts are underway to improve some of these landraces for improved productivity. Seeds of maize landraces cultivated in all agro-ecologies were collected for genetic characterization using a bulked fingerprinting technique and 20 SSR markers. In all, 20 populations of 15 plants each from Ghana and 4 control populations from Latin America were characterized. The cluster analysis grouped the 20 landraces into two major groups corresponding to the vegetation/climatic conditions of the north and south of the country. Genotypes from Ashanti, which is centrally located, fell into both major clusters, which suggest its importance in maize seed distribution in Ghana and also the diverse climate/vegetation. Structure analyses grouped the genotypes into two major clusters similar to the UPGMA cluster, and populations were not fully distinct according to F statistics. The results suggest that breeders should make performance data available to seed dealers for better productivity.
Oppong A, Bedoya CA, Ewool MB, Asante MD, Thompson RN, Adu-Dapaah H, Lamptey JNL, Ofori K, Offei SK and Warburton ML (2014). Bulk genetic characterization of Ghanaian maize landraces using microsatellite markers. Maydica 59:1–8. (G4007.13.04)
Abstract: Maize (Zea mays L) was first introduced into Ghana over five centuries ago and remains the most important cereal staple, grown in all agro-ecologies across the country. Yield from farmers' fields are low, which is attributed in part to farmer's preferences and/or reliance on local landraces for cultivation. Efforts are underway to improve some of these landraces for improved productivity. Seeds of maize landraces cultivated in all agro-ecologies were collected for genetic characterization using a bulked fingerprinting technique and 20 SSR markers. In all, 20 populations of 15 plants each from Ghana and 4 control populations from Latin America were characterized. The cluster analysis grouped the 20 landraces into two major groups corresponding to the vegetation/climatic conditions of the north and south of the country. Genotypes from Ashanti, which is centrally located, fell into both major clusters, which suggest its importance in maize seed distribution in Ghana and also the diverse climate/vegetation. Structure analyses grouped the genotypes into two major clusters similar to the UPGMA cluster, and populations were not fully distinct according to F statistics. The results suggest that breeders should make performance data available to seed dealers for better productivity.
Full article
The use of SNP markers for linkage mapping in diploid and tetraploid peanuts
Bertioli DJ, Ozias-Akins P, Chu Y, Dantas KM, Santos SP, Gouvea E, Guimarães PM, Leal-Bertioli SCM, Knapp SJ and Moretzsohn MC (2014). The use of SNP markers for linkage mapping in diploid and tetraploid peanuts. G3 4(1):89–96. First published online in November 2013. (G6010.01)
Abstract: Single nucleotide polymorphic markers (SNPs) are attractive for use in genetic mapping and marker-assisted breeding because they can be scored in parallel assays at favorable costs. However, scoring SNP markers in polyploid plants like the peanut is problematic because of interfering signal generated from the DNA bases that are homeologous to those being assayed. The present study used a previously constructed 1536 GoldenGate SNP assay developed using SNPs identified between two A. duranensis accessions. In this study, the performance of this assay was tested on two RIL mapping populations, one diploid (A. duranensis × A. stenosperma) and one tetraploid [A. hypogaea cv. Runner IAC 886 × synthetic tetraploid (A. ipaënsis × A. duranensis)4×]. The scoring was performed using the software GenomeStudio version 2011.1. For the diploid, polymorphic markers provided excellent genotyping scores with default software parameters. In the tetraploid, as expected, most of the polymorphic markers provided signal intensity plots that were distorted compared to diploid patterns and that were incorrectly scored using default parameters. However, these scorings were easily corrected using the GenomeStudio software. The degree of distortion was highly variable. Of the polymorphic markers, approximately 10% showed no distortion at all behaving as expected for single-dose markers, and another 30% showed low distortion and could be considered high-quality. The genotyped markers were incorporated into diploid and tetraploid genetic maps of Arachis and, in the latter case, were located almost entirely on A genome linkage groups.
Bertioli DJ, Ozias-Akins P, Chu Y, Dantas KM, Santos SP, Gouvea E, Guimarães PM, Leal-Bertioli SCM, Knapp SJ and Moretzsohn MC (2014). The use of SNP markers for linkage mapping in diploid and tetraploid peanuts. G3 4(1):89–96. First published online in November 2013. (G6010.01)
Abstract: Single nucleotide polymorphic markers (SNPs) are attractive for use in genetic mapping and marker-assisted breeding because they can be scored in parallel assays at favorable costs. However, scoring SNP markers in polyploid plants like the peanut is problematic because of interfering signal generated from the DNA bases that are homeologous to those being assayed. The present study used a previously constructed 1536 GoldenGate SNP assay developed using SNPs identified between two A. duranensis accessions. In this study, the performance of this assay was tested on two RIL mapping populations, one diploid (A. duranensis × A. stenosperma) and one tetraploid [A. hypogaea cv. Runner IAC 886 × synthetic tetraploid (A. ipaënsis × A. duranensis)4×]. The scoring was performed using the software GenomeStudio version 2011.1. For the diploid, polymorphic markers provided excellent genotyping scores with default software parameters. In the tetraploid, as expected, most of the polymorphic markers provided signal intensity plots that were distorted compared to diploid patterns and that were incorrectly scored using default parameters. However, these scorings were easily corrected using the GenomeStudio software. The degree of distortion was highly variable. Of the polymorphic markers, approximately 10% showed no distortion at all behaving as expected for single-dose markers, and another 30% showed low distortion and could be considered high-quality. The genotyped markers were incorporated into diploid and tetraploid genetic maps of Arachis and, in the latter case, were located almost entirely on A genome linkage groups.
