Marilyn A. L. West

Arabidopsis LEAFY COTYLEDON1 Is Sufficient to Induce Embryo Development in Vegetative Cells

The Arabidopsis LEAFY COTYLEDON1 (LEC1) gene is required for the specification of cotyledon identity and the completion of embryo maturation. We isolated the LEC1 gene and showed that it functions at an early developmental stage to maintain embryonic cell fate. The LEC1 gene encodes a transcription factor homolog, the CCAAT box-binding factor HAP3 subunit. LEC1 RNA accumulates only during seed development in embryo cell types and in endosperm tissue. Ectopic postembryonic expression of the LEC1 gene in vegetative cells induces the expression of embryo-specific genes and initiates formation of embryo-like structures. Our results suggest that LEC1 is an important regulator of embryo development that activates the transcription of genes required for both embryo morphogenesis and cellular differentiation.

Global eQTL Mapping Reveals the Complex Genetic Architecture of Transcript-Level Variation in Arabidopsis

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 = 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 (R2 < 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.

Embryogenesis in Higher Plants: An Overview.

The sporophytic generation of higher plants is initiated with the double fertilization event that results in the formation of a single-celled zygote and a progenitor cell of the endosperm. Embryogenesis describes the subsequent period of development, during which the zygote undergoes a complex series of morphological and cellular changes resulting in the formation of a developmentally arrested mature embryo comprised of an embryonic axis with shoot and root poles and cotyledon(s), which often contains high levels of storage macromolecules such as proteins and lipids. Thus, the events that occur during embryonic development establish the organization of the plant body and prepare the embryo for both dormancy and germination. Higher plant embryogenesis has been studied intensively during the past century. Studies using light and electron microscopy have provided detailed descriptions of the morphological and anatomical changes that characterize embryonic development (Maheshwari, 1950; Wardlaw, 1955; Natesh and Rau, 1984; Raghavan, 1986). Cellular differentiation has been studied largely in relationship to the biosynthesis and accumulation of storage proteins, lipids, and starch, macromolecular reserves that ultimately serve as nutrients for postgerminative seedlings (Jenner, 1982; Slack and Browse, 1984; Casey et al., 1986; Shotwell and Larkins, 1989). The focus of attention on these reserves reflects their agricultura1 importance and the fact that the abundance of these macromolecules facilitates studies of their accumulation. By contrast, much less is known about the processes that underlie embryo morphogenesis, although increasing attention is being devoted to this area. In this review, we will provide an overview of the processes that occur during embryonic development, focusing primarily on dicotyledonous plants. Additionally, we will discuss some of the critical processes involved in embryo formation, about which relatively little is known. This review is meant to provide a conceptual summary of embryonic development rather than to cover all aspects of embryogenesis in detail or to describe events that occur in all species of plants. Readers are referred to other reviews on embryogenesis for additional coverage of the topic (Natesh and Rau, 1984; Dure, 1985; Raghavan, 1986; Crouch, 1987; Goldberg et al., 1989; Meinke, 1991a; De Jong et al., 1993; Lindsey and Topping, 1993).

Global expression analysis of nucleotide binding site-leucine rich repeat-encoding and related genes in Arabidopsis

BackgroundNucleotide binding site-leucine rich repeat (NBS-LRR)-encoding genes comprise the largest class of plant disease resistance genes. The 149 NBS-LRR-encoding genes and the 58 related genes that do not encode LRRs represent approximately 0.8% of all ORFs so far annotated in Arabidopsis ecotype Col-0. Despite their prevalence in the genome and functional importance, there was little information regarding expression of these genes.ResultsWe analyzed the expression patterns of ~170 NBS-LRR-encoding and related genes in Arabidopsis Col-0 using multiple analytical approaches: expressed sequenced tag (EST) representation, massively parallel signature sequencing (MPSS), microarray analysis, rapid amplification of cDNA ends (RACE) PCR, and gene trap lines. Most of these genes were expressed at low levels with a variety of tissue specificities. Expression was detected by at least one approach for all but 10 of these genes. The expression of some but not the majority of NBS-LRR-encoding and related genes was affected by salicylic acid (SA) treatment; the response to SA varied among different accessions. An analysis of previously published microarray data indicated that ten NBS-LRR-encoding and related genes exhibited increased expression in wild-type Landsberg erecta (Ler) after flagellin treatment. Several of these ten genes also showed altered expression after SA treatment, consistent with the regulation of R gene expression during defense responses and overlap between the basal defense response and salicylic acid signaling pathways. Enhancer trap analysis indicated that neither jasmonic acid nor benzothiadiazole (BTH), a salicylic acid analog, induced detectable expression of the five NBS-LRR-encoding genes and one TIR-NBS-encoding gene tested; however, BTH did induce detectable expression of the other TIR-NBS-encoding gene analyzed. Evidence for alternative mRNA polyadenylation sites was observed for many of the tested genes. Evidence for alternative splicing was found for at least 12 genes, 11 of which encode TIR-NBS-LRR proteins. There was no obvious correlation between expression pattern, phylogenetic relationship or genomic location of the NBS-LRR-encoding and related genes studied.ConclusionTranscripts of many NBS-LRR-encoding and related genes were defined. Most were present at low levels and exhibited tissue-specific expression patterns. Expression data are consistent with most Arabidopsis NBS-LRR-encoding and related genes functioning in plant defense responses but do not preclude other biological roles.

Genomic Survey of Gene Expression Diversity in Arabidopsis thaliana

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 high-frequency 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.

Identification of QTLs controlling gene expression networks defined a priori

BackgroundGene expression microarrays allow the quantification of transcript accumulation for many or all genes in a genome. This technology has been utilized for a range of investigations, from assessments of gene regulation in response to genetic or environmental fluctuation to global expression QTL (eQTL) analyses of natural variation. Current analysis techniques facilitate the statistical querying of individual genes to evaluate the significance of a change in response, also known as differential expression. Since genes are also known to respond as groups due to their membership in networks, effective approaches are needed to investigate transcriptome variation as related to gene network responses.ResultsWe describe a statistical approach that is capable of assessing higher-order a priori defined gene network response, as measured by microarrays. This analysis detected significant network variation between two Arabidopsis thaliana accessions, Bay-0 and Shahdara. By extending this approach, we were able to identify eQTLs controlling network responses for 18 out of 20 a priori-defined gene networks in a recombinant inbred line population derived from accessions Bay-0 and Shahdara.ConclusionThis approach has the potential to be expanded to facilitate direct tests of the relationship between phenotypic trait and transcript genetic architecture. The use of a priori definitions for network eQTL identification has enormous potential for providing direction toward future eQTL analyses.

Natural Variation among Arabidopsis thaliana Accessions for Transcriptome Response to Exogenous Salicylic Acid

Little is known about how gene expression variation within a given species controls phenotypic variation under different treatments or environments. Here, we surveyed the transcriptome response of seven diverse Arabidopsis thaliana accessions in response to two treatments: the presence and absence of exogenously applied salicylic acid (SA), an important signaling molecule in plant defense. A factorial experiment was conducted with three biological replicates per accession with and without applications of SA and sampled at three time points posttreatment. Transcript level data from Affymetrix ATH1 microarrays were analyzed on both per-gene and gene-network levels to detect expression level polymorphisms associated with SA response. Significant variation in transcript levels for response to SA was detected among the accessions, with relatively few genes responding similarly across all accessions and time points. Twenty-five of 54 defined gene networks identified from other microarray studies (pathogen-challenged Columbia [Col-0]) showed a significant response to SA in one or more accessions. A comparison of gene-network relationships in our data to the pathogen-challenged Col-0 data demonstrated a higher-order conservation of linkages between defense response gene networks. Cvi-1 and Mt-0 appeared to have globally different SA responsiveness in comparison to the other five accessions. Expression level polymorphisms for SA response were abundant at both individual gene and gene-network levels in the seven accessions, suggesting that natural variation for SA response is prevalent in Arabidopsis.

A comparison of microarray and MPSS technology platforms for expression analysis of Arabidopsis.

BackgroundSeveral high-throughput technologies can measure in parallel the abundance of many mRNA transcripts within a sample. These include the widely-used microarray as well as the more recently developed methods based on sequence tag abundances such as the Massively Parallel Signature Sequencing (MPSS) technology. A comparison of microarray and MPSS technologies can help to establish the metrics for data comparisons across these technology platforms and determine some of the factors affecting the measurement of mRNA abundances using different platforms.ResultsWe compared transcript abundance (gene expression) measurement data obtained using Affymetrix and Agilent microarrays with MPSS data. All three technologies were used to analyze the same set of mRNA samples; these samples were extracted from various wild type Arabidopsis thaliana tissues and floral mutants. We calculated correlations and used clustering methodology to compare the normalized expression data and expression ratios across samples and technologies. Abundance expression measurements were more similar between different samples measured by the same technology than between the same sample measured by different technologies. However, when expression ratios were employed, samples measured by different technologies were found to cluster together more frequently than with abundance expression levels.Furthermore, the two microarray technologies were more consistent with each other than with MPSS. We also investigated probe-position effects on Affymetrix data and tag-position effects in MPSS. We found a similar impact on Affymetrix and MPSS measurements, which suggests that these effects were more likely a characteristic of the RNA sample rather than technology-specific biases.ConclusionComparisons of transcript expression ratios showed greater consistency across platforms than measurements of transcript abundance. In addition, for measurements based on abundances, technology differences can mask the impact of biological differences between samples and tissues.

Old Methods for New Ideas: Genetic Dissection of the Determinants of Gene Expression Levels

There is increasing interest in understanding the molecular basis of complex traits. Initially, the genetic dissection of quantitative traits involved measurements of gross phenotypes. Subsequently, specific physiological and developmental components of individual traits have been dissected. Most recently, the underlying mechanisms of inheritance have been studied through various approaches that are supported by modern technological and methodological advances, namely quantitative trait locus/loci (QTL) analysis (Mackay, 2001; Mauricio, 2001; Doerge, 2002) and mutant analysis (Rossant and Spence, 1998; Hughes et al., 2000) in genetics; genome sequencing (Jang et al., 1999; The Arabidopsis Genome Initiative, 2000; Mouse Genome Sequencing Consortium, 2002) and gene expression analysis (Duggan et al., 1999; Lipshutz et al., 1999) in genomics; and protein structure analysis (Service, 1999) and protein assay (Kodadek, 2001; MacBeath, 2002)

GENETIC MAPPING OF GENE EXPRESSION LEVELS: EXPRESSION LEVEL POLYMORPHISM ANALYSIS FOR DISSECTING REGULATORY NETWORKS OF PLANT DISEASE RESISTANCE

The genetic basis of inherited traits has been studied through different approaches in many areas of science. Examples include quantitative trait locus (QTL) analysis and mutant analysis in genetics, genome sequencing and gene expression analysis in genomics. Each of these approaches is used for the investigation of complex traits, such as disease resistance, but also provides knowledge on components of complex biological systems. We introduce a novel functional genomics approach that integrates two areas, genetics and genomics, by applying QTL analysis to quantitative differences in the mRNA abundance of trait-related genes. This approach allows comprehensive dissection of regulatory networks for complex traits at a systems biology level. We also address statistical issues, and suggest guidelines for future experiments in this new framework. (