Transcriptional responses of Arabidopsis thaliana to chewing and sucking insect herbivores.

We tested the hypothesis that Arabidopsis can recognize and respond differentially to insect species at the transcriptional level using a genome wide microarray. Transcriptional reprogramming was characterized using co-expression analysis in damaged and undamaged leaves at two times in response to mechanical wounding and four insect species. In all, 2778 (10.6%) of annotated genes on the array were differentially expressed in at least one treatment. Responses differed mainly between aphid and caterpillar and sampling times. Responses to aphids and caterpillars shared only 10% of up-regulated and 8% of down-regulated genes. Responses to two caterpillars shared 21 and 12% of up- and down-regulated genes, whereas responses to the two aphids shared only 7 and 4% of up-regulated and down-regulated genes. Overlap in genes expressed between 6 and 24 h was 3-15%, and depended on the insect species. Responses in attacked and unattacked leaves differed at 6 h but converged by 24 h. Genes responding to the insects are also responsive to many stressors and included primary metabolism. Aphids down-regulated amino acid catabolism; caterpillars stimulated production of amino acids involved in glucosinolate synthesis. Co-expression analysis revealed 17 response networks. Transcription factors were a major portion of differentially expressed genes throughout and responsive genes shared most of the known or postulated binding sites. However, cis-element composition of genes down regulated by the aphid M. persicae was unique, as were those of genes down-regulated by caterpillars. As many as 20 cis-elements were over-represented in one or more treatments, including some from well-characterized classes and others as yet uncharacterized. We suggest that transcriptional changes elicited by wounding and insects are heavily influenced by transcription factors and involve both enrichment of a common set of cis-elements and a unique enrichment of a few cis-elements in responding genes.

Network analysis reveals the relationship among wood properties, gene expression levels and genotypes of natural Populus trichocarpa accessions.

High-throughput approaches have been widely applied to elucidate the genetic underpinnings of industrially important wood properties. Wood traits are polygenic in nature, but gene hierarchies can be assessed to identify the most important gene variants controlling specific traits within complex networks defining the overall wood phenotype. We tested a large set of genetic, genomic, and phenotypic information in an integrative approach to predict wood properties in Populus trichocarpa. Nine-yr-old natural P. trichocarpa trees including accessions with high contrasts in six traits related to wood chemistry and ultrastructure were profiled for gene expression on 49k Nimblegen (Roche NimbleGen Inc., Madison, WI, USA) array elements and for 28,831 polymorphic single nucleotide polymorphisms (SNPs). Pre-selected transcripts and SNPs with high statistical dependence on phenotypic traits were used in Bayesian network learning procedures with a stepwise K2 algorithm to infer phenotype-centric networks. Transcripts were pre-selected at a much lower logarithm of Bayes factor (logBF) threshold than SNPs and were not accommodated in the networks. Using persistent variables, we constructed cross-validated networks for variability in wood attributes, which contained four to six variables with 94-100% predictive accuracy. Accommodated gene variants revealed the hierarchy in the genetic architecture that underpins substantial phenotypic variability, and represent new tools to support the maximization of response to selection.

Genome-wide association mapping for wood characteristics in Populus identifies an array of candidate single nucleotide polymorphisms.

Establishing links between phenotypes and molecular variants is of central importance to accelerate genetic improvement of economically important plant species. Our work represents the first genome-wide association study to the inherently complex and currently poorly understood genetic architecture of industrially relevant wood traits. Here, we employed an Illumina Infinium 34K single nucleotide polymorphism (SNP) genotyping array that generated 29,233 high-quality SNPs in c. 3500 broad-based candidate genes within a population of 334 unrelated Populus trichocarpa individuals to establish genome-wide associations. The analysis revealed 141 significant SNPs (α ≤ 0.05) associated with 16 wood chemistry/ultrastructure traits, individually explaining 3-7% of the phenotypic variance. A large set of associations (41% of all hits) occurred in candidate genes preselected for their suggested a priori involvement with secondary growth. For example, an allelic variant in the FRA8 ortholog explained 21% of the total genetic variance in fiber length, when the trait's heritability estimate was considered. The remaining associations identified SNPs in genes not previously implicated in wood or secondary wall formation. Our findings provide unique insights into wood trait architecture and support efforts for population improvement based on desirable allelic variants.

Genome-wide and expression analysis of protein phosphatase 2C in rice and Arabidopsis.

BACKGROUND: The protein phosphatase 2Cs (PP2Cs) from various organisms have been implicated to act as negative modulators of protein kinase pathways involved in diverse environmental stress responses and developmental processes. A genome-wide overview of the PP2C gene family in plants is not yet available. RESULTS: A comprehensive computational analysis identified 80 and 78 PP2C genes in Arabidopsis thaliana (AtPP2Cs) and Oryza sativa (OsPP2Cs), respectively, which denotes the PP2C gene family as one of the largest families identified in plants. Phylogenic analysis divided PP2Cs in Arabidopsis and rice into 13 and 11 subfamilies, respectively, which are supported by the analyses of gene structures and protein motifs. Comparative analysis between the PP2C genes in Arabidopsis and rice identified common and lineage-specific subfamilies and potential 'gene birth-and-death' events. Gene duplication analysis reveals that whole genome and chromosomal segment duplications mainly contributed to the expansion of both OsPP2Cs and AtPP2Cs, but tandem or local duplication occurred less frequently in Arabidopsis than rice. Some protein motifs are widespread among the PP2C proteins, whereas some other motifs are specific to only one or two subfamilies. Expression pattern analysis suggests that 1) most PP2C genes play functional roles in multiple tissues in both species, 2) the induced expression of most genes in subfamily A by diverse stimuli indicates their primary role in stress tolerance, especially ABA response, and 3) the expression pattern of subfamily D members suggests that they may constitute positive regulators in ABA-mediated signaling pathways. The analyses of putative upstream regulatory elements by two approaches further support the functions of subfamily A in ABA signaling, and provide insights into the shared and different transcriptional regulation machineries in dicots and monocots. CONCLUSION: This comparative genome-wide overview of the PP2C family in Arabidopsis and rice provides insights into the functions and regulatory mechanisms, as well as the evolution and divergence of the PP2C genes in dicots and monocots. Bioinformatics analyses suggest that plant PP2C proteins from different subfamilies participate in distinct signaling pathways. Our results have established a solid foundation for future studies on the functional divergence in different PP2C subfamilies.

Ancient signals: comparative genomics of plant MAPK and MAPKK gene families.

MAPK signal transduction modules play crucial roles in regulating many biological processes in plants, and their components are encoded by highly conserved genes. The recent availability of genome sequences for rice and poplar now makes it possible to examine how well the previously described Arabidopsis MAPK and MAPKK gene family structures represent the broader evolutionary situation in plants, and analysis of gene expression data for MPK and MKK genes in all three species allows further refinement of those families, based on functionality. The Arabidopsis MAPK nomenclature appears sufficiently robust to allow it to be usefully extended to other well-characterized plant systems.