Genomic Prediction in a Multiploid Crop: Genotype by Environment Interaction and Allele Dosage Effects on Predictive Ability in Banana
Improving the efficiency of selection in conventional crossbreeding is a major priority in banana (Musa spp.) breeding. Routine application of classical marker assisted selection (MAS) is lagging in banana due to limitations in MAS tools. Genomic selection (GS) based on genomic prediction models can address some limitations of classical MAS, but the use of GS in banana has not been reported to date. This study evaluated the predictive ability of six genomic prediction models for 15 traits in a multi-ploidy training population. The high predictive values of fruit filling and fruit bunch traits show the potential of genomic prediction to increase selection efficiency in banana breeding.
Read more: https://dl.sciencesocieties.org/publications/tpg/articles/0/0/170090
Microsatellites markers associated with resistance to flower bud thrips in a cowpea F2 population derived from genotypes TVU-123 and WC36
Breeding for resistance to flower bud thrips (Megalurothrips sjostedti) in cowpea has been hindered by the quantitative nature of resistance. To identify simple sequence repeat (SSR) markers associated with resistance to flower bud thrips that could be used for marker-assisted breeding, a F2 population was generated from a cross between genotypes TVU-123 (resistant) and WC36 (susceptible). The population was evaluated for thrips damage scores, thrips counts, and pods number per plant under artificial infestation. Mainly additive gene effects were observed. A more detailed study using more markers on these loci should provide better understanding of this complex trait.
Read more: https://doi.org/10.5897/AJB2018.16480
Assessment of Genetic Variation and Population Structure of Diverse Rice Genotypes Adapted to Lowland and Upland Ecologies in Africa Using SNPs
Using interspecific crosses involving Oryza glaberrima Steud. as donor and O. sativa L. as recurrent parents, rice breeders at the Africa Rice Center developed several ‘New Rice for Africa (NERICA)’ improved varieties. This study investigated the genetic variation, relatedness, and population structure of 330 widely used rice genotypes in Africa using DArTseq-based single nucleotide polymorphisms (SNPs). This is the first study using high density markers that characterized NERICA and ARICA varieties in comparison with indica and japonica varieties widely used in Africa, which could aid rice breeders on parent selection for developing new improved rice germplasm.
Read more: https://doi.org/10.3389/fpls.2018.00446