We found that only 4 SNPs

were significantly associated with different fiber quality properties, and none with ELO. The remaining polymorphic sites cannot independently exert significant effects on fiber quality properties. In haplotype–FQ associations, Galunisertib clinical trial Exp2 was treated as an indivisible biological entity in the form of different allele or haplotypes. The most favorable UHML and STR properties were observed for haplotype Hap_6. In future MAS and molecular design breeding programs, we should identify and propagate plants carrying haplotype Hap_6 in the Exp2 region, with the aim of transferring positive alleles to breeding germplasm. And during genotyping of MAS, some attention should be paid to the 4 SNP loci. The authors thank the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper. This work was

supported by the National Natural Science Foundation of China (30971821), Specialized Research Fund for the Doctoral Program of Higher Education (Ministry of Education; 20090204120017), the Shaanxi Natural Science Fund project (2010JQ3005), the National Transgenic Plants Project of China (2011ZX08005-002), and China Agriculture Research System (CARS-18-45). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. “
“Cassava (Manihot Selleckchem ONO-4538 esculenta Crantz) is one of the most important food crops worldwide. It is a storage root crop grown by most smallholder farmers partly because of its flexibility in harvesting time and ability to perform well in drought-prone and marginal areas under poor management, where other crops fail [1]. Despite these advantages, cassava presents substantial differential genotypic responses under varying environmental conditions, a phenomenon termed genotype × environment Cytidine deaminase interaction (GEI) [1]. GEI is a routine occurrence in plant breeding programmes

[2]. GEI and yield-stability analyses have accordingly become increasingly important for measuring cultivar stability and suitability for cultivation across seasons and ecological zones [3]. An understanding of GEI can be helpful in identifying ideal test conditions and in formulating recommendations for areas of optional genotype adaptation. Multi-environment trials have been found to be essential in plant breeding for studying cultivar stability and predicting yield performance of cultivars across environments [4]. The phenotypic expression of an individual is determined by both genotype and environment effects [5]. These two effects are not always additive, because of GEI. A GEI results from changes in the magnitude of differences between genotypes in different environments or from changes in the relative ranking of the genotypes [6]. It presents limitations in the selection of superior genotypes, and thereby reduces the utility of analyses of means and of inferences that would otherwise be valid [7].