Genomic prediction in biparental tropical maize populations in water-stressed and well-watered environments using low-density and GBS SNPs.

One of the most important applications of genomic selection in maize breeding is to predict and identify the best untested lines from biparental populations, when the training and validation sets are derived from the same cross. Nineteen tropical maize biparental populations evaluated in multienvironment trials were used in this study to assess prediction accuracy of different quantitative traits using low-density (~200 markers) and genotyping-by-sequencing (GBS) single-nucleotide polymorphisms (SNPs), respectively. An extension of the Genomic Best Linear Unbiased Predictor that incorporates genotype × environment (GE) interaction was used to predict genotypic values; cross-validation methods were applied to quantify prediction accuracy. Our results showed that: (1) low-density SNPs (~200 markers) were largely sufficient to get good prediction in biparental maize populations for simple traits with moderate-to-high heritability, but GBS outperformed low-density SNPs for complex traits and simple traits evaluated under stress conditions with low-to-moderate heritability; (2) heritability and genetic architecture of target traits affected prediction performance, prediction accuracy of complex traits (grain yield) were consistently lower than those of simple traits (anthesis date and plant height) and prediction accuracy under stress conditions was consistently lower and more variable than under well-watered conditions for all the target traits because of their poor heritability under stress conditions; and (3) the prediction accuracy of GE models was found to be superior to that of non-GE models for complex traits and marginal for simple traits.

Genetic structure and relationships within and between cultivated and wild sorghum (Sorghum bicolor (L.) Moench) in Kenya as revealed by microsatellite markers.

Understanding the extent and partitioning of diversity within and among crop landraces and their wild/weedy relatives constitutes the first step in conserving and unlocking their genetic potential. This study aimed to characterize the genetic structure and relationships within and between cultivated and wild sorghum at country scale in Kenya, and to elucidate some of the underlying evolutionary mechanisms. We analyzed at total of 439 individuals comprising 329 cultivated and 110 wild sorghums using 24 microsatellite markers. We observed a total of 295 alleles across all loci and individuals, with 257 different alleles being detected in the cultivated sorghum gene pool and 238 alleles in the wild sorghum gene pool. We found that the wild sorghum gene pool harbored significantly more genetic diversity than its domesticated counterpart, a reflection that domestication of sorghum was accompanied by a genetic bottleneck. Overall, our study found close genetic proximity between cultivated sorghum and its wild progenitor, with the extent of crop-wild divergence varying among cultivation regions. The observed genetic proximity may have arisen primarily due to historical and/or contemporary gene flow between the two congeners, with differences in farmers' practices explaining inter-regional gene flow differences. This suggests that deployment of transgenic sorghum in Kenya may lead to escape of transgenes into wild-weedy sorghum relatives. In both cultivated and wild sorghum, genetic diversity was found to be structured more along geographical level than agro-climatic level. This indicated that gene flow and genetic drift contributed to shaping the contemporary genetic structure in the two congeners. Spatial autocorrelation analysis revealed a strong spatial genetic structure in both cultivated and wild sorghums at the country scale, which could be explained by medium- to long-distance seed movement.

Analysis of genetic diversity and structure in Ethiopian populations of Phytolacca dodecandra using RAPD.

The genetic diversity and structure in 17 wild populations (249 individuals) of Phytolacca dodecandra (endod) sampled along altitudinal gradients of 1600-3000 meters above sea level (m.a.s.l.) in Ethiopia was studied using random amplified polymorphic DNA (RAPD). A total of 70 polymorphic loci (P) scored from 12 RAPD primers were used to calculate different diversity indices within and between populations, habitats, geographical regions, climatic zones and altitude groups. The number of polymorphic loci and overall Shannon information measure (H) in the populations varied from 30 to 55 and from 0.228 to 0.418, respectively. In general, differences in population variability were found significantly correlated to effective population size. Both P and H were significantly higher in an undisturbed than in a disturbed habitat, and in the lowland and central-highland than in the highland altitude group. However, for both parameters the differences were not statistically significant between regions and climatic zones. Genetic distance between populations varied from 0.301 to 0.628. Cluster analysis performed using the genetic distance matrix revealed a clear separation of the highland populations (2501-3000 m.a.s.l.) from those of the lowland/central-highlands (1600-2500 m.a.s.l.) irrespective of their geographical regions and climatic zones. Analysis of molecular variance (AMOVA) indicated that differences in habitat, geographical regions and climatic zones explained 4.6%, 2.5% and 4.6%, respectively. But none of these differences were significant. Altitude explained 17.2% of the total variance and was highly significant. The data, therefore, clearly indicated the association of genetic structure in endod with altitude. The proportion of RAPD variation found among populations (21.2-35.0%) was somewhat intermediate between values reported for selfing and outcrossing species. The fixation index (FST) values (0.350 to 0.384) indicated very high genetic differentiation among populations.