The genetic architecture of transcript-level variation is largely unknown. The genetic determinants of transcript-level variation were characterized in a recombinant inbred line (RIL) population (n ¼ 211) of Arabidopsis thaliana using whole-genome microarray analysis and expression quantitative trait loci (eQTL) mapping of transcript levels as expression traits (e-traits). Genetic control of transcription was highly complex: one-third of the quantitatively controlled transcripts/e-traits were regulated by cis-eQTL, and many trans-eQTL mapped to hotspots that regulated hundreds to thousands of e-traits. Several thousand eQTL of large phenotypic effect were detected, but almost all (93%) of the 36,871 eQTL were associated with small phenotypic effects (R 2 , 0.3). Many transcripts/e-traits were controlled by multiple eQTL with opposite allelic effects and exhibited higher heritability in the RILs than their parents, suggesting nonadditive genetic variation. To our knowledge, this is the first large-scale global eQTL study in a relatively large plant mapping population. It reveals that the genetic control of transcript level is highly variable and multifaceted and that this complexity may be a general characteristic of eukaryotes.

Quantitative disease resistance (QDR) has been observed within many crop plants but is not as well understood as qualitative (monogenic) disease resistance and has not been used as extensively in breeding. Mapping quantitative trait loci (QTLs) is a powerful tool for genetic dissection of QDR. DNA markers tightly linked to quantitative resistance loci (QRLs) controlling QDR can be used for marker-assisted selection (MAS) to incorporate these valuable traits. QDR confers a reduction, rather than lack, of disease and has diverse biological and molecular bases as revealed by cloning of QRLs and identification of the candidate gene(s) underlying QRLs. Increasing our biological knowledge of QDR and QRLs will enhance understanding of how QDR differs from qualitative resistance and provide the necessary information to better deploy these resources in breeding. Application of MAS for QRLs in breeding for QDR to diverse pathogens is illustrated by examples from wheat, barley, common bean, tomato, and pepper. Strategies for optimum deployment of QRLs require research to understand effects of QDR on pathogen populations over time.

Expression microarrays hybridized with RNA can simultaneously provide both phenotypic (gene expression) and genotypic (marker) data. We developed two types of genetic markers from Affymetrix GeneChip expression data to generate detailed haplotypes for 148 recombinant inbred lines (RILs) derived from Arabidopsis thaliana accessions Bayreuth and Shahdara. Gene expression markers (GEMs) are based on differences in transcript levels that exhibit bimodal distributions in segregating progeny, while single feature polymorphism (SFP) markers rely on differences in hybridization to individual oligonucleotide probes. Unlike SFPs, GEMs can be derived from any type of DNA-based expression microarray. Our method identifies SFPs independent of a gene’s expression level. Alleles for each GEM and SFP marker were ascertained with GeneChip data from parental accessions as well as RILs; a novel algorithm for allele determination using RIL distributions capitalized on the high level of genetic replication per locus. GEMs and SFP markers provided robust markers in 187 and 968 genes, respectively, which allowed estimation of gene order consistent with that predicted from the Col-0 genomic sequence. Using microarrays on a population to simultaneously measure gene expression variation and obtain genotypic data for a linkage map will facilitate expression QTL analyses without the need for separate genotyping. We have demonstrated that gene expression measurements from microarrays can be leveraged to identify polymorphisms across the genome and can be efficiently developed into genetic markers that are verifiable in a large segregating RIL population. Both marker types also offer opportunities for massively parallel mapping in unsequenced and less studied species.

Differential gene expression controls variation in numerous plant traits, such as flowering time and plant/ pest interactions, but little is known about the genomic distribution of the determinants of transcript levels and their associated variation. Affymetrix ATH1 GeneChip microarrays representing 22,810 genes were used to survey the transcriptome of seven Arabidopsis thaliana accessions in the presence and absence of exogenously applied salicylic acid (SA). These accessions encompassed 80% of the moderate-to highfrequency nucleotide polymorphisms in Arabidopsis. A factorial design, consisting of three biological replicates per accession for the two treatments at three time points (4, 28, and 52 hr post-treatment), and a total of 126 microarrays were used. Between any pair of Arabidopsis accessions, we detected on average 2234 genes (ranging from 1428 to 3334) that were significantly differentially expressed under the conditions of this experiment, using a split-plot analysis of variance. Upward of 6433 genes were differentially expressed between at least one pair of accessions. These results suggest that analysis of additional genetic, developmental, and environmental conditions may show that a significant fraction of the Arabidopsis genome is differentially expressed. Examination of sequence diversity demonstrated a significant positive association with diversity in gene expression. N ATURAL phenotypic variation is often quantitatively distributed and occurs in both simple and complex traits. DNA sequence polymorphisms can be a primary genetic cause of phenotypic variation in populations. Some recent studies have assessed genomewide DNA sequence variation within and between different species (Gibbs et al.

The shoots of cultivated tomato ( Lycopersicon esculentum cv. T5) wilt if their roots are exposed to chilling temperatures of around 5 ∞ ∞ ∞ ∞ C. Under the same treatment, a chillingtolerant congener ( Lycopersicon hirsutum LA 1778) maintains shoot turgor. To determine the physiological basis of this differential response, the effect of chilling on both excised roots and roots of intact plants in pressure chambers were investigated. In excised roots and intact plants, root hydraulic conductance declined with temperature to nearly twice the extent expected from the temperature dependence of the viscosity of water, but the response was similar in both species. The species differed markedly, however, in stomatal behaviour: in L. hirsutum , stomatal conductance declined as root temperatures were lowered, whereas the stomata of L. esculentum remained open until the roots reached 5 ∞ ∞ ∞ ∞ C, and the plants became flaccid and suffered damage. Grafted plants with the shoots of one genotype and roots of another indicated that the differential stomatal behaviour during root chilling has distinct shoot and root components.