Jesse D. Munkvold

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.cnl-2B.1, that was significant in all environments tested and explained from 5 to 31% of the trait variation in a given environment. Three other QTL QPhs.cnl-2D.1, QPhs.cnl-3D.1, and QPhs.cnl-6D.1 were detected in six, four, and ten environments, respectively. The potentially related traits of heading date (HD), plant height (HT), seed dormancy (DOR), and rate of germination (ROG) were also recorded in a limited number of environments. HD was found to be significantly negatively correlated with PHS score in most environments, likely due to a major HD QTL, QHd.cnl-2B.1, found to be tightly linked to the PHS QTL QPhs.cnl-2B.1. Using greenhouse grown material no overlap was found between seed dormancy and the four most consistent PHS QTL, suggesting that greenhouse environments are not representative of field environments. This study provides valuable information for marker-assisted breeding for PHS resistance, future haplotyping studies, and research into seed dormancy.

Comparison of digital image analysis using elliptic Fourier descriptors and major dimensions to phenotype seed shape in hexaploid wheat (Triticum aestivum L.)

Digital image analysis (DIA) is widely used for describing plant organ shape. However, the various types of shape descriptors that can be generated using DIA may identify different loci in genetic analyses. The purpose of this study was to evaluate two different DIA approaches to quantifying wheat seed shape for exploring trait correlations and quantitative trait loci (QTL) mapping. Phenotypic data were produced using the software programs ImageJ (National Institutes of Health, USA, http://rsbweb.nih.gov/ij/) and SHAPE (Hiroyoshi Iwata, http://lbm.ab.a.u-tokyo.ac.jp/≃iwata/shape/). ImageJ generates measures of length, width, perimeter, and area that can be used to describe dimensions of objects, whereas SHAPE generates elliptic Fourier descriptors (EFDs) to capture shape variation such as roughness, asymmetric skewing, or other two-dimensional aspects not encompassed by axes or distinctions in overall object area. There were significant differences in the results of the QTL analysis depending on the DIA software used. The use of EFDs to characterize horizontal measures of seed shape in wheat identified more QTL with higher LOD scores than length to width ratio. Additionally, the entire three dimensional shape of the seed described using two images in different orientations was shown to identify seed shape QTL that co-located with flour yield (FLYLD) and would go undetected based solely on a two dimensional image of the seed. Both methods identified QTL for length, width, thickness, and vertical perimeter that were co-localized with QTL for FLYLD.

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.cnl-2B.1, located on wheat chromosome 2B. A comparative genetic study with the related grass species rice (Oryza sativa L.) and Brachypodium distachyon at the homologous region to the QPhs.cnl-2B.1 interval was used to identify the candidate genes for marker development and subsequent fine mapping. Expressed sequence tags and a comparative mapping were used to design 278 primer pairs, of which 22 produced polymorphic amplicons that mapped to the group 2 chromosomes. Fourteen mapped to chromosome 2B, and ten were located in the QTL interval. A comparative analysis revealed good macrocollinearity between the PHS interval and 3 million base pair (mb) region on rice chromosomes 7 and 3, and a 2.7-mb region on Brachypodium Bd1. The comparative intervals in rice were found to contain three previously identified rice seed dormancy QTL. Further analyses of the interval in rice identified genes that are known to play a role in seed dormancy, including a homologue for the putative Arabidopsis ABA receptor ABAR/GUN5. Additional candidate genes involved in calcium signaling were identified and were placed in a functional protein association network that includes additional proteins critical for ABA signaling and germination. This study provides promising candidate genes for seed dormancy in both wheat and rice as well as excellent molecular markers for further comparative and fine mapping.

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. Comparative gene co-expression networks have been used to uncover biological mechanisms that differentiate tissues or other biological factors. In this study, we have extended consensus and differential Weighted Gene Co-Expression Network Analysis to compare the influence of different growing environments on gene co-expression in the mature wheat (Triticum aestivum) embryo. This network approach was combined with mapping of individual gene expression QTL to examine the genetic control of environmentally static and variable gene expression. The approach is useful for gene expression experiments containing multiple environments and allowed for the identification of specific gene co-expression modules responsive to environmental factors. This procedure identified conserved coregulation of gene expression between environments related to basic developmental and cellular functions, including protein localization and catabolism, vesicle composition/trafficking, Golgi transport, and polysaccharide metabolism among others. Environmentally unique modules were found to contain genes with predicted functions in responding to abiotic and biotic environmental variables. These findings represent the first report using consensus and differential Weighted Gene Co-expression Network Analysis to characterize the influence of environment on coordinated transcriptional regulation.

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. By using the coding sequence from Solanum lycopersicum, S. galapagense, S. pimpinellifolium, S. corneliomuelleri, and S. tuberosum and the genomic sequence from S. lycopersicum ‘Heinz’, an heirloom line, S. lycopersicum ‘Yellow Pear’, and two of cultivated tomato’s closest relatives, S. galapagense and S. pimpinellifolium, we have aimed to resolve the phylogenies of these closely related species as well as identify phylogenetic discordance in the reference cultivated tomato. Results. Divergence date estimates suggest that the divergence of S. lycopersicum, S. galapagense, and S. pimpinellifolium happened less than 0.5 MYA. Phylogenies based on 8,857 coding sequences support grouping of S. lycopersicum and S. galapagense, although two secondary trees are also highly represented. A total of 25 genes in our analysis had sites with evidence of positive selection along the S. lycopersicum lineage. Whole genome phylogenies showed that while incongruence is prevalent in genomic comparisons between these genotypes, likely as a result of introgression and incomplete lineage sorting, a primary phylogenetic history was strongly supported. Conclusions. Based on analysis of these genotypes, S. galapagense appears to be closely related to S. lycopersicum, suggesting they had a common ancestor prior to the arrival of an S. galapagense ancestor to the Galápagos Islands, but after divergence of the sequenced S. pimpinellifolium. Genes showing selection along the S. lycopersicum lineage may be important in domestication or selection occurring post-domestication. Further analysis of intraspecific data in these species will help to establish the evolutionary history of cultivated tomato. The use of an heirloom line is helpful in deducing true phylogenetic information of S. lycopersicum and identifying regions of introgression from wild species.