Identification of quantitative trait nucleotides and candidate genes for tuber yield and mosaic virus tolerance in an elite population of white guinea yam (Dioscorea rotundata) using genome-wide association scan

Open Access Journal; Published online: 22 Nov 2021Background Improvement of tuber yield and tolerance to viruses are priority objectives in white Guinea yam breeding programs. However, phenotypic selection for these traits is quite challenging due to phenotypic plasticity and cumbersome screening of phenotypic-induced variations. This study assessed quantitative trait nucleotides (QTNs) and the underlying candidate genes related to tuber yield per plant (TYP) and yam mosaic virus (YMV) tolerance in a panel of 406 white Guinea yam (Dioscorea rotundata) breeding lines using a genome-wide association study (GWAS). Results Population structure analysis using 5,581 SNPs differentiated the 406 genotypes into seven distinct sub-groups based delta K. Marker-trait association (MTA) analysis using the multi-locus linear model (mrMLM) identified seventeen QTN regions significant for TYP and five for YMV with various effects. The seveteen QTNs were detected on nine chromosomes, while the five QTNs were identified on five chromosomes. We identified variants responsible for predicting higher yield and low virus severity scores in the breeding panel through the marker-effect prediction. Gene annotation for the significant SNP loci identified several essential putative genes associated with the growth and development of tuber yield and those that code for tolerance to mosaic virus. Conclusion Application of different multi-locus models of GWAS identified 22 QTNs. Our results provide valuable insight for marker validation and deployment for tuber yield and mosaic virus tolerance in white yam breeding. The information on SNP variants and genes from the present study would fast-track the application of genomics-informed selection decisions in breeding white Guinea yam for rapid introgression of the targeted traits through markers validation

Multiple-traits selection in White Guinea Yam (Dioscorea rotundata) genotypes

Open Access Journal; Published online: 07 Nov 2022Choosing superior parents with complementary trait values for hybridization and selecting variants with desired product profiles to release as a new cultivar are important breeding activities to progress genetic improvement in crops. This study assessed the genetic potential of 36 parental lines of white Guinea yam (Dioscorea rotundata) genotypes using multi-trait index-based factor analysis and ideotype design (FAI-BLUP). The experiment utilized 36 white yam genotypes laid out in a 6 × 6 triple lattice design with three replications and phenotyped for 18 agronomic and food quality traits. Findings showed significant differences among genotypes for all assessed traits. Fifteen traits had desired genetic gains, whereas stem diameter (−1.34%), and two starch property traits ((holding strength (−26.31%) and final paste viscosity (−3.33%)) had undesired selection gain. The FAI-BLUP index provided total genetic gains of 148.91% for traits desired for increase and –29.26% for those desired for decrease. Genotypes TDr08-21-2, TDr9518544, TDr9501932, TDr8902665 and Pampars were identified as top best candidate for simultaneous improvement of the measured traits in white yam breeding. The findings indicate the effectiveness of the FAI-BLUP index in identifying and selecting genotypes

Molecular and phenotypic profiling of white Guinea yam (Dioscorea rotundata) breeding lines.

Open Access JournalPhenotypic and genotypic profiling helps identify genotypes with suitable and complementary traits for genetic improvement in crops. A total of 32 traits were assessed in 36 genotypes of white Guinea yam established in a 6 × 6 triple lattice design. The objective was to evaluate an array of plant traits that define the genetic merits of breeding lines for yam improvement. Different analytical tools were used to identify and prioritize relevant traits defining the genetic merits of breeding lines in the yam improvement program. Out of the 32 traits measured, the linear combination of 14 traits that minimize within-group variance and maximize between-group variance for discriminating the genetic values of yam breeding lines were identified. When best linear unbiased prediction with genomic relationship matrix (GBLUP) was used, the accuracies of genomic breeding values were higher (r=0.87 to 0.97) for the seven traits (dry matter content, intensity of flesh oxidization of shredded tuber, pasting temperature, pasting time, tuber flesh colour, yam mosaic virus and fresh tuber yield) with high broad-sense heritability values (H2m>0.6). While, for the remaining seven traits with low (H2m<0.3) to medium (H2m=0.3 to 0.54) broad-sense heritability values, the accuracies of genomic estimated breeding values (GEBV) were low (r<0.4) to medium (r=0.4-0.8). The genotype–trait (GT) biplot display revealed superior clones with desirable genetic values for the key traits. These results are relevant for parental selection aimed at improving key agronomic traits in white Guinea yam

Genetic parameter estimation and selection in advanced breeding population of white Guinea yam

Published online: 01 Mar 2021White Guinea yam (Dioscorea rotundata Poir.) is an important tuber crop grown extensively in tropical regions of West African yam belt. Tuber yield, dry matter content, and tolerance to yam mosaic virus are key traits used for identification and selection of superior varieties for commercial deployment. In this study, we estimated genetic parameters for fresh tuber yield, tuber dry matter content, and quantitative field tolerance to yam mosaic virus in 49 clones grown in multi-environment trials (METs). We conducted genomic prediction involving 6337 single nucleotide polymorphisms (SNPs) and phenotypic field evaluation of data collected on the three traits from four sites. Additive genetic and non-genetic factors contributed significantly to phenotypic variation of studied yam traits in METs but to varying degrees. The non-genetic effects were relatively high for most of the measured traits. Narrow-sense heritability values were low (<0.30) for all studied traits. Further analysis of the performance of the clones at test sites with additive main effects and multiplicative interaction (AMMI) analysis exhibited significant genotype by environment interactions (GEI) for the three traits. The AMMI identified TDr10/00412, TDr11/00055, and TDr09/00135 clones with lowest mean trait stability index and outstanding performance for fresh tuber yield (t ha−1), tuber dry matter, and mosaic virus resistance across sites. The elite clones identified could serve as useful source of alleles for the genetic improvement of the crop and possibly considered for release to farmers

Spatial representation for navigation in animats

This article considers the problem of spatial representation for animat navigation systems. It is proposed that the global navigation task, or "wayfinding, " is best supported by multiple interacting subsystems, each of which builds its own partial representation of relevant world knowledge. Evidence from the study of animal navigation is reviewed to demonstrate that similar principles underlie the wayfinding behavior of animals, including humans. A simulated wayfinding system is described that embodies and illustrates several of the themes identified with animat navigation. This system constructs a network of partial models of the quantitative spatial relations between groups of salient landmarks. Navigation tasks are solved by propagating egocentric view information through this network, using a simple but effective heuristic to arbitrate between multiple solutions

Towards a four factor theory of anticipatory learning

This paper takes an overtly anticipatory stance to the understanding of animat learning and behavior. It analyses four major animal learning theories and attempts to identify the anticipatory and predictive elements inherent to them, and to provide a new unifying approach based on the anticipatory nature of those elements based on five simple predictive “rules”. These rules encapsulate all the principal properties of the four diverse theories (the four factors) and provide a simple framework for understanding how an individual animat may appear to operate according to different principles under varying circumstances. The paper then indicates how these anticipatory principles can be used to define a more detailed set of postulates for the Dynamic Expectancy Model of animat learning and behavior, and to construct its computer implementation SRS/E. Some of the issues discussed are illustrated with an example experimental procedure using SRS/E