Coexpression patterns of gene expression across many microarray data sets may reveal networks of genes involved in linked processes. To identify factors involved in cellulose biosynthesis, we used a regression method to analyze 408 publicly available Affymetrix Arabidopsis microarrays. Expression of genes previously implicated in cellulose synthesis, as well as several uncharacterized genes, was highly coregulated with expression of cellulose synthase (CESA) genes. Four candidate genes, which were coexpressed with CESA genes implicated in secondary cell wall synthesis, were investigated by mutant analysis. Two mutants exhibited irregular xylem phenotypes similar to those observed in mutants with defects in secondary cellulose synthesis and were designated irx8 and irx13 . Thus, the general approach developed here is useful for identification of elements of multicomponent processes.

Established guidelines for causal inference in epidemiological studies may be inappropriate for genetic associations. A consensus process was used to develop guidance criteria for assessing cumulative epidemiologic evidence in genetic associations. A proposed semi-quantitative index assigns three levels for the amount of evidence, extent of replication, and protection from bias, and also generates a composite assessment of ‘strong’, ‘moderate’ or ‘weak’ epidemiological credibility. In addition, we discuss how additional input and guidance can be derived from biological data. Future empirical research and consensus development are needed to develop an integrated model for combining epidemiological and biological evidence in the rapidly evolving field of investigation of genetic factors.

Annual plants grow vegetatively at early developmental stages and then transition to the reproductive stage, followed by senescence in the same year. In contrast, after successive years of vegetative growth at early ages, woody perennial shoot meristems begin repeated transitions between vegetative and reproductive growth at sexual maturity. However, it is unknown how these repeated transitions occur without a developmental conflict between vegetative and reproductive growth. We report that functionally diverged paralogs FLOWERING LOCUS T1 ( FT1 ) and FLOWERING LOCUS T2 ( FT2 ), products of whole-genome duplication and homologs of Arabidopsis thaliana gene FLOWERING LOCUS T ( FT ), coordinate the repeated cycles of vegetative and reproductive growth in woody perennial poplar ( Populus spp.). Our manipulative physiological and genetic experiments coupled with field studies, expression profiling, and network analysis reveal that reproductive onset is determined by FT1 in response to winter temperatures, whereas vegetative growth and inhibition of bud set are promoted by FT2 in response to warm temperatures and long days in the growing season. The basis for functional differentiation between FT1 and FT2 appears to be expression pattern shifts, changes in proteins, and divergence in gene regulatory networks. Thus, temporal separation of reproductive onset and vegetative growth into different seasons via FT1 and FT2 provides seasonality and demonstrates the evolution of a complex perennial adaptive trait after genome duplication.

Molecular studies of squamous cell carcinoma of the head and neck (HNSCC) have demonstrated multiple genetic abnormalities such as activation of various oncogenes (Ras, Myc, epidermal growth factor receptor, and cyclin D1), tumor suppressor gene inactivation (TP53 and p16), and loss of heterozygosity at numerous chromosomal locations. Despite these observations, accurate and reliable biomarkers that predict patients at highest risk for local recurrence have yet to be defined. In an effort to identify gene expression signatures that may serve as biomarkers, we studied 41 squamous cell carcinoma tumors (25 primary and 16 locally recurrent) from various anatomical sites and 13 normal oral mucosal biopsy samples from healthy volunteers with microarray analysis using Affymetrix U133A GeneChip arrays. Differentially expressed genes were identified by calculating generalized t tests (P < 0.001) and applying a series of filtering criteria to yield a highly discriminant list of 2890 genes. Hierarchical clustering and image generation using standard software were used to visualize gene expression signatures. Several gene expression signatures were readily identifiable in the HNSCC tumors, including signatures associated with proliferation, extracellular matrix production, cytokine/chemokine expression, and immune response. Of particular interest was the association of a gene expression signature enriched for genes involved in tumor invasion and metastasis with patients experiencing locally recurrent disease. Notably, these tumors also demonstrated a marked absence of an immune response signature suggesting that modulation of tumor-specific immune responses may play a role in local treatment failure. These data provide evidence for a new gene expression-based biomarker of local treatment failure in HNSCC.

DYX2 on 6p22 is the most replicated reading disability (RD) locus. By saturating a previously identified peak of association with single nucleotide polymorphism markers, we identified a large polymorphic deletion that encodes tandem repeats of putative brain-related transcription factor binding sites in intron 2 of DCDC2 . Alleles of this compound repeat are in significant disequilibrium with multiple reading traits. RT-PCR data show that DCDC2 localizes to the regions of the brain where fluent reading occurs, and RNA interference studies show that down-regulation alters neuronal migration. The statistical and functional studies are complementary and are consistent with the latest clinical imaging data for RD. Thus, we propose that DCDC2 is a candidate gene for RD.