Biology subjects

Yencho, C.

Publications and source records attributed to Yencho, C..

5 recordsLinked to original sources

bioRxiv2023

Early root architectural traits and their relationship with yield in Ipomoea batatas L.

Root system architecture in storage root crops are an important component of plant growth and yield performance that has received little attention by researchers because of the inherent difficulties posed by in-situ root observation. Sweetpotato (Ipomoea batatas L.) is an important climate-resilient storage root crop of worldwide importance for both tropical and temperate regions, and identifying genotypes with advantageous root phenotypes and improved root architecture to facilitate breeding for improved storage root yield and quality characteristics in both high and low input scenarios would be beneficial. We evaluated 38 diverse sweetpotato genotypes for early root architectural traits and correlated a subset of these with storage root yield. Early root architectural traits were scanned and digitized using the RhizoVision Explorer software system. Significant genotypic variation was detected for all early root traits including root mass, total root length, root volume, root area and root length by diameter classes. Based on the values of total root length, we separated the 38 genotypes into three root sizes (small, medium, and large). Principal component analysis identified four clusters, primarily defined by shoot mass, root volume, root area, root mass, total root length and root length by diameter class. Average total and marketable yield and number of storage roots, was assessed on a subset of eight genotypes in the field. Several early root traits were positively correlated with total yield, marketable yield, and number of storage roots. These results suggest that root traits, particularly total root length and root mass could improve yield potential and should be incorporated into sweetpotato ideotypes. To help increase sweetpotato performance in challenging environments, breeding efforts may benefit through the incorporation of early root phenotyping using the idea of integrated root phenotypes.

plant biology↗

bioRxiv2020

The recombination landscape and multiple QTL mapping in a Solanum tuberosum cv. 'Atlantic'-derived F1 population

There are many challenges involved with the genetic analyses of autopolyploid species, such as the tetraploid potato, Solanum tuberosum (2n = 4x = 48). The development of new analytical methods has made it valuable to re-analyze an F1 population (n = 156) derived from a cross involving Atlantic, a widely grown chipping variety in the USA. A fully integrated genetic map with 4,285 single nucleotide polymorphisms, spanning 1,630 cM, was constructed with MAPpoly software. We observed that bivalent configurations were the most abundant ones (51.0[~]72.4% depending on parent and linkage group), though multivalent configurations were also observed (2.2[~]39.2%). Seven traits were evaluated over four years (2006-8 and 2014) and quantitative trait loci (QTL) mapping was carried out using QTLpoly software. Based on a multiple-QTL model approach, we detected 21 QTL for 15 out of 27 trait-year combination phenotypes. A hotspot on linkage group 5 was identified as QTL for maturity, plant yield, specific gravity and internal heat necrosis resistance over different years were co-located. Additional QTL for specific gravity and dry matter were detected with maturity-corrected phenotypes. Among the genes around QTL peaks, we found those on chromosome 5 that have been previously implicated in maturity (StCDF1) and tuber formation (POTH1). These analyses have the potential to provide insights into the biology and breeding of tetraploid potato and other autopolyploid species.

genetics↗

bioRxiv2019

Development of diagnostic SNP markers for quality assurance and control in sweetpotato breeding programs

Quality assurance and control (QA/QC) is an essential element of a breeding programs optimization efforts towards increased genetic gains. Due to auto-hexaploid genome complexity, a low-cost marker platform for routine QA/QC in sweetpotato breeding programs is still unavailable. We used 662 parents of the International Potato Center (CIP)s global breeding program spanning Peru, Uganda, Mozambique and Ghana, to develop a low-density highly informative single nucleotide polymorphism (SNP) marker set to be deployed for routine QA/QC. Segregation of the selected 30 SNPs (two SNPs per base chromosome) in a recombined breeding population was evaluated using 282 progeny from some of the parents above. The progeny were replicated from in-vitro, screenhouse and field, and the selected SNP-set was confirmed to identify relatively similar mislabeling error rates as a high density SNP-set of 10,159 markers. Six additional trait-specific markers were added to the selected SNP set from previous quantitative trait loci mapping. The 36-SNP set will be deployed for QA/QC in breeding pipelines and in fingerprinting of advanced clones or released varieties to monitor genetic gains in famers fields. The study also enabled evaluation of CIPs global breeding population structure and the effect of some of the most devastating biotic stresses like sweetpotato virus disease on genetic variation management. These results will inform future deployment of genomic selection in sweetpotato.\n\nKey MessageA 36-SNP diagnostic marker set has been developed for quality assurance and control to support global sweetpotato breeding optimization efforts. Breeding population structure is shaped by sweetpotato virus disease prevalence.

genetics↗

bioRxiv2019

When a phenotype is not the genotype: Implications of phenotype misclassification and pedigree errors in genomics-assisted breeding of sweetpotato

Experimental error, especially through genotype misclassification and pedigree errors, negatively affects breeding decisions by creating noise that compounds the genetic signals for selection. Unlike genotype-by-environment interactions, for which different methods have been proposed to address, the effect of noise due to pedigree errors and misclassification has not received much attention in most crops. We used two case studies in sweetpotato, based on data from the International Potato Centers breeding program to estimate the level of phenotype misclassification and pedigree error and to demonstrate the consequences of such errors when combining phenotypes with the respective genotypes. In the first case study, 27.7% phenotype misclassification was observed when moving genotypes from a diversity panel through in-vitro, screenhouse and field trialing. Additionally, 22.7% pedigree error was observed from misclassification between and within families. The second case study involving multi-environment testing of a full-sib population and quantitative trait loci (QTL) mapping showed reduced genetic correlations among pairs of environments in mega-environments with higher phenotype misclassification errors when compared to the mega-environments with lower phenotype misclassification errors. Additionally, no QTL could be identified in the low genetic correlation mega-environments. Simulation analysis indicated that phenotype misclassification was more detrimental to QTL detection when compared to missingness in data. The current information is important to inform current and future breeding activities involving genomic-assisted breeding decisions in sweetpotato, and to facilitate putting in place improved workflows that minimize phenotype misclassification and pedigree errors.

genetics↗

bioRxiv2017

Assembly Of Whole-Chromosome Pseudomolecules For Polyploid Plant Genomes Using Outcrossed Mapping Populations

The assembly of whole-chromosome pseudomolecules for plant genomes remains challenging due to polyploidy and high repeat content. We developed an approach for constructing complete pseudomolecules for polyploid species using genotyping-by-sequencing data from outcrossing mapping populations coupled with high coverage whole genome sequence data of a reference genome. Our approach combines de novo assembly with linkage mapping to arrange scaffolds into pseudomolecules. We show that the method is able to reconstruct simulated chromosomes for both diploid and tetraploid genomes. Comparisons to three existing genetic mapping tools show that our method outperforms the other methods in accuracy on both grouping and ordering, and is robust to the presence of substantial amounts of missing data and genotyping errors. We applied our method to three real datasets including a diploid Ipomoea trifida and two tetraploid potato mapping populations. The linkage maps show significant concordance with the reference chromosomes. We resolved seven assembly errors for the published Ipomoea trifida genome assembly as well as anchored an unplaced scaffold in the published potato genome.

bioinformatics↗