Statistical sampling of missing environmental variables improves biophysical genomic prediction in wheat.

The integration of genomic prediction with crop growth models enabled the estimation of missing environmental variables which improved the prediction accuracy of grain yield. Since the invention of whole-genome prediction (WGP) more than two decades ago, breeding programmes have established extensive reference populations that are cultivated under diverse environmental conditions. The introduction of the CGM-WGP model, which integrates crop growth models (CGM) with WGP, has expanded the applications of WGP to the prediction of unphenotyped traits in untested environments, including future climates.

Integrating biophysical crop growth models and whole genome prediction for their mutual benefit: a case study in wheat phenology.

Running crop growth models (CGM) coupled with whole genome prediction (WGP) as a CGM-WGP model introduces environmental information to WGP and genomic relatedness information to the genotype-specific parameters modelled through CGMs. Previous studies have primarily used CGM-WGP to infer prediction accuracy without exploring its potential to enhance CGM and WGP. Here, we implemented a heading and maturity date wheat phenology model within a CGM-WGP framework and compared it with CGM and WGP.

Using genomic prediction with crop growth models enables the prediction of associated traits in wheat.

Crop growth models (CGM) can predict the performance of a cultivar in untested environments by sampling genotype-specific parameters. As they cannot predict the performance of new cultivars, it has been proposed to integrate CGMs with whole genome prediction (WGP) to combine the benefits of both models. Here, we used a CGM-WGP model to predict the performance of new wheat (Triticum aestivum) genotypes.

A giant NLR gene confers broad-spectrum resistance to Phytophthora sojae in soybean.

Phytophthora root and stem rot caused by P. sojae is a destructive soybean soil-borne disease found worldwide. Discovery of genes conferring broad-spectrum resistance to the pathogen is a need to prevent the outbreak of the disease.

Comparative genomics and phylogenetic discordance of cultivated tomato and close wild relatives.

Background. Studies of ancestry are difficult in the tomato because it crosses with many wild relatives and species in the tomato clade that have diverged very recently. As a result, the phylogeny in relation to its closest relatives remains uncertain.

Fine mapping of a preharvest sprouting QTL interval on chromosome 2B in white wheat.

Fine mapping by recombinant backcross populations revealed that a preharvest sprouting QTL on 2B contained two QTLs linked in coupling with different effects on the phenotype. Wheat preharvest sprouting (PHS) occurs when grain germinates on the plant before harvest, resulting in reduced grain quality. Previous mapping of quantitative trait locus (QTL) revealed a major PHS QTL, QPhs.

A measure to evaluate classroom teaching practices in nursing.

Aim: The Oregon Consortium for Nursing Education (OCNE) Classroom Teaching Fidelity Scale was created to measure the implementation of the OCNE curriculum and its related pedagogy.

Background: OCNE is a partnership of eight community colleges and the five-campus state-supported university. OCNE developed a shared competency-based curriculum and pedagogical practices.

Systems genetics of environmental response in the mature wheat embryo.

Quantitative phenotypic traits are influenced by genetic and environmental variables as well as the interaction between the two. Underlying genetic × environment interaction is the influence that the surrounding environment exerts on gene expression. Perturbation of gene expression by environmental factors manifests itself in alterations to gene co-expression networks and ultimately in phenotypic plasticity.

Factors affecting the academic progression of associate degree graduates.

The Oregon Consortium for Nursing Education (OCNE) is a coalition of community colleges and the campuses of the Oregon Health & Sciences University (OHSU), created to share a competency-based curriculum by which associate degree graduates from an OCNE campus are eligible to complete requirements for the bachelor's degree after 1 year of additional full-time study. Since 2006, three graduating classes from consortium community college programs have graduated 760 students eligible for direct transfer to OHSU; however, only 228 (30%) have actually transferred. This study aimed to explore the factors that influenced the 208 graduates in the class of 2010 not to transfer.

Comparative genetic analysis of a wheat seed dormancy QTL with rice and Brachypodium identifies candidate genes for ABA perception and calcium signaling.

Wheat preharvest sprouting (PHS) occurs when seed germinates on the plant before harvest resulting in reduced grain quality. In wheat, PHS susceptibility is correlated with low levels of seed dormancy. A previous mapping of quantitative trait loci (QTL) revealed a major PHS/seed dormancy QTL, QPhs.

Mapping quantitative trait loci for preharvest sprouting resistance in white wheat.

The premature germination of seeds before harvest, known as preharvest sprouting (PHS), is a serious problem in all wheat growing regions of the world. In order to determine genetic control of PHS resistance in white wheat from the relatively uncharacterized North American germplasm, a doubled haploid population consisting of 209 lines from a cross between the PHS resistant variety Cayuga and the PHS susceptible variety Caledonia was used for QTL mapping. A total of 16 environments were used to detect 15 different PHS QTL including a major QTL, QPhs.

A chromosome bin map of 16,000 expressed sequence tag loci and distribution of genes among the three genomes of polyploid wheat.

Because of the huge size of the common wheat (Triticum aestivum L., 2n = 6x = 42, AABBDD) genome of 17,300 Mb, sequencing and mapping of the expressed portion is a logical first step for gene discovery. Here we report mapping of 7104 expressed sequence tag (EST) unigenes by Southern hybridization into a chromosome bin map using a set of wheat aneuploids and deletion stocks.

Group 3 chromosome bin maps of wheat and their relationship to rice chromosome 1.

The focus of this study was to analyze the content, distribution, and comparative genome relationships of 996 chromosome bin-mapped expressed sequence tags (ESTs) accounting for 2266 restriction fragments (loci) on the homoeologous group 3 chromosomes of hexaploid wheat (Triticum aestivum L.). Of these loci, 634, 884, and 748 were mapped on chromosomes 3A, 3B, and 3D, respectively.

Comparative DNA sequence analysis of wheat and rice genomes.

The use of DNA sequence-based comparative genomics for evolutionary studies and for transferring information from model species to crop species has revolutionized molecular genetics and crop improvement strategies. This study compared 4485 expressed sequence tags (ESTs) that were physically mapped in wheat chromosome bins, to the public rice genome sequence data from 2251 ordered BAC/PAC clones using BLAST. A rice genome view of homologous wheat genome locations based on comparative sequence analysis revealed numerous chromosomal rearrangements that will significantly complicate the use of rice as a model for cross-species transfer of information in nonconserved regions.

Identification of chromosome arms influencing expression of the HMW glutenins in wheat.

The high-molecular-weight (HMW) glutenin genes, located on the group 1L chromosome arms, are a major determinant for baking quality in wheat ( Triticum aestivum L.). In addition, the HMW glutenin genes provide a valuable model system for studying the evolution and regulation of orthologous and paralogous genes in polyploid species.