Inflammation Impacts Androgen Receptor Signaling in Basal Prostate Stem Cells Through Interleukin 1 Receptor Antagonist

The majority of patients with benign prostate hyperplasia (BPH) exhibit chronic prostate inflammation and the extent of inflammation correlates with the severity of symptoms. How inflammation contributes to prostate enlargement and/or BPH symptoms and the underlying mechanisms are not clearly understood. We established a unique mouse model Prostate Ovalbumin Expressing Transgenic 3 (POET3) that mimics chronic non-bacterial prostatitis in men to study the role of inflammation in prostate hyperplasia. After the injection of ovalbumin peptide-specific T cells, POET3 prostates exhibited an influx of inflammatory cells and an increase in pro-inflammatory cytokines that led to epithelial and stromal hyperplasia. We have previously demonstrated with the POET3 model that inflammation expands the basal prostate stem cell (bPSC) population and promotes bPSC differentiation in organoid cultures. In this study, we investigated the mechanisms underlying the impact of inflammation on bPSC. We found that AR activity was enhanced in inflamed bPSC and was essential for bPSC differentiation in organoid cultures. Most importantly, we identified, for the first time, interleukin 1 receptor antagonist (IL-1RA) as a key regulator of AR in basal stem cells. IL-1RA was one of the top genes upregulated by inflammation and inhibition of IL-1RA abrogated the enhanced AR nuclear accumulation and activity in organoids derived from inflamed bPSC. The mirroring effects of IL-1RA recombinant protein and IL-1α neutralizing antibody suggest that IL-1RA may function by antagonizing IL-1α inhibition of AR expression. Furthermore, we established a lineage tracing model to follow bPSC during inflammation and under castrate conditions. We found that inflammation induced bPSC proliferation and differentiation into luminal cells even under castrate conditions, indicating that AR activation driven by inflammation in bPSC is sufficient for their proliferation and differentiation under androgen-deprived conditions. However, proliferation of the differentiated bPSC in the luminal layer significantly diminished with castration, suggesting inflammation may not maintain AR activity in stromal cells, as stromal cells deprived of androgen after castration could no longer provide paracrine growth factors essential for luminal proliferation. Taken together, we have discovered novel mechanisms through which inflammation modulates AR signaling in bPSC and induces bPSC luminal differentiation that contributes to prostate hyperplasia.

Ghost QTL and hotspots in experimental crosses: novel approach for modeling polygenic effects

Ghost quantitative trait loci (QTL) are the false discoveries in QTL mapping, that arise due to the "accumulation" of the polygenic effects, uniformly distributed over the genome. The locations on the chromosome that are strongly correlated with the total of the polygenic effects depend on a specific sample correlation structure determined by the genotypes at all loci. The problem is particularly severe when the same genotypes are used to study multiple QTL, e.g. using recombinant inbred lines or studying the expression QTL. In this case, the ghost QTL phenomenon can lead to false hotspots, where multiple QTL show apparent linkage to the same locus. We illustrate the problem using the classic backcross design and suggest that it can be solved by the application of the extended mixed effect model, where the random effects are allowed to have a nonzero mean. We provide formulas for estimating the thresholds for the corresponding t-test statistics and use them in the stepwise selection strategy, which allows for a simultaneous detection of several QTL. Extensive simulation studies illustrate that our approach eliminates ghost QTL/false hotspots, while preserving a high power of true QTL detection.

Inbreeding Depression in Genotypically Matched Diploid and Tetraploid Maize

The genetic and molecular basis of heterosis has long been studied but without a consensus about mechanism. The opposite effect, inbreeding depression, results from repeated self-pollination and leads to a reduction in vigor. A popular explanation for this reaction is the homozygosis of recessive, slightly deleterious alleles upon inbreeding. However, extensive studies in alfalfa indicated that inbreeding between diploids and autotetraploids was similar despite the fact that homozygosis of alleles would be dramatically different. The availability of tetraploid lines of maize generated directly from various inbred lines provided the opportunity to examine this issue in detail in perfectly matched diploid and tetraploid hybrids and their parallel inbreeding regimes. Identical hybrids at the diploid and tetraploid levels were inbred in triplicate for seven generations. At the conclusion of this regime, F1 hybrids and selected representative generations (S1, S3, S5, S7) were characterized phenotypically in randomized blocks during the same field conditions. Quantitative measures of the multiple generations of inbreeding provided little evidence for a distinction in the decline of vigor between the diploids and the tetraploids. The results suggest that the homozygosis of completely recessive, slightly deleterious alleles is an inadequate hypothesis to explain inbreeding depression in general.

A weighted FDR procedure under discrete and heterogeneous null distributions

Multiple testing (MT) with false discovery rate (FDR) control has been widely conducted in the "discrete paradigm" where p-values have discrete and heterogeneous null distributions. However, in this scenario existing FDR procedures often lose some power and may yield unreliable inference, and for this scenario there does not seem to be an FDR procedure that partitions hypotheses into groups, employs data-adaptive weights and is nonasymptotically conservative. We propose a weighted p-value-based FDR procedure, "weighted FDR (wFDR) procedure" for short, for MT in the discrete paradigm that efficiently adapts to both heterogeneity and discreteness of p-value distributions. We theoretically justify the nonasymptotic conservativeness of the wFDR procedure under independence, and show via simulation studies that, for MT based on p-values of binomial test or Fisher's exact test, it is more powerful than six other procedures. The wFDR procedure is applied to two examples based on discrete data, a drug safety study, and a differential methylation study, where it makes more discoveries than two existing methods.

Cholesterol Sulfotransferase SULT2B1b Modulates Sensitivity to Death Receptor Ligand TNFα in Castration-Resistant Prostate Cancer

Cholesterol sulfotransferase, SULT2B1b, has been demonstrated to modulate both androgen receptor activity and cell growth properties. However, the mechanism(s) by which SULT2B1b alters these properties within prostate cancer cells has not been described. Furthermore, specific advantages of SULT2B1b expression in prostate cancer cells are not understood. In these studies, single-cell mRNA sequencing was conducted to compare the transcriptomes of SULT2B1b knockdown (KD) versus Control KD LNCaP cells. Over 2,000 differentially expressed genes were identified along with alterations in numerous canonical pathways, including the death receptor signaling pathway. The studies herein demonstrate that SULT2B1b KD increases TNFα expression in prostate cancer cells and results in NF-κB activation in a TNF-dependent manner. More importantly, SULT2B1b KD significantly enhances TNF-mediated apoptosis in both TNF-sensitive LNCaP cells and TNF-resistant C4-2 cells. Overexpression of SULT2B1b in LNCaP cells also decreases sensitivity to TNF-mediated cell death, suggesting that SULT2B1b modulates pathways dictating the TNF sensitivity capacity of prostate cancer cells. Probing human prostate cancer patient datasets further supports this work by providing evidence that SULT2B1b expression is inversely correlated with TNF-related genes, including TNF, CD40LG, FADD, and NFKB1. Together, these data provide evidence that SULT2B1b expression in prostate cancer cells enhances resistance to TNF and may provide a growth advantage. In addition, targeting SULT2B1b may induce an enhanced therapeutic response to TNF treatment in advanced prostate cancer. IMPLICATIONS: These data suggest that SULT2B1b expression enhances resistance to TNF and may promote prostate cancer.

Multiple testing with discrete data: Proportion of true null hypotheses and two adaptive FDR procedures

We consider multiple testing with false discovery rate (FDR) control when p values have discrete and heterogeneous null distributions. We propose a new estimator of the proportion of true null hypotheses and demonstrate that it is less upwardly biased than Storey's estimator and two other estimators. The new estimator induces two adaptive procedures, that is, an adaptive Benjamini-Hochberg (BH) procedure and an adaptive Benjamini-Hochberg-Heyse (BHH) procedure. We prove that the adaptive BH (aBH) procedure is conservative nonasymptotically. Through simulation studies, we show that these procedures are usually more powerful than their nonadaptive counterparts and that the adaptive BHH procedure is usually more powerful than the aBH procedure and a procedure based on randomized p-value. The adaptive procedures are applied to a study of HIV vaccine efficacy, where they identify more differentially polymorphic positions than the BH procedure at the same FDR level.

Novel Resampling Improves Statistical Power for Multiple-Trait QTL Mapping

Multiple-trait analysis typically employs models that associate a quantitative trait locus (QTL) with all of the traits. As a result, statistical power for QTL detection may not be optimal if the QTL contributes to the phenotypic variation in only a small proportion of the traits. Excluding QTL effects that contribute little to the test statistic can improve statistical power. In this article, we show that an optimal power can be achieved when the number of QTL effects is best estimated, and that a stringent criterion for QTL effect selection may improve power when the number of QTL effects is small but can reduce power otherwise. We investigate strategies for excluding trivial QTL effects, and propose a method that improves statistical power when the number of QTL effects is relatively small, and fairly maintains the power when the number of QTL effects is large. The proposed method first uses resampling techniques to determine the number of nontrivial QTL effects, and then selects QTL effects by the backward elimination procedure for significance test. We also propose a method for testing QTL-trait associations that are desired for biological interpretation in applications. We validate our methods using simulations and Arabidopsis thaliana transcript data.

Environmental Regulation of Heterosis in the Allopolyploid Arabidopsis suecica

Allopolyploids are organisms possessing more than two complete sets of chromosomes from two or more species and are frequently more vigorous than their progenitors. To address the question why allopolyploids display hybrid vigor, we compared the natural allopolyploid Arabidopsis suecica to its progenitor species Arabidopsis thaliana and Arabidopsis arenosa. We measured chlorophyll content, CO2 assimilation, and carbohydrate production under varying light conditions and found that the allopolyploid assimilates more CO2 per unit chlorophyll than either of the two progenitor species in high intensity light. The increased carbon assimilation corresponds with greater starch accumulation, but only in strong light, suggesting that the strength of hybrid vigor is dependent on environmental conditions. In weaker light A. suecica tends to produce as much primary metabolites as the better progenitor. We found that gene expression of LIMIT DEXTRINASE1, a debranching enzyme that cleaves branch points within starch molecules, is at the same level in the allopolyploid as in the maternal progenitor A. thaliana and significantly more expressed than in the paternal progenitor A. arenosa. However, expression differences of β-amylases and GLUCAN-WATER DIKINASE1 were not statistically significantly elevated in the allopolyploid over progenitor expression levels. In contrast to allopolyploids, autopolyploid A. thaliana showed the same photosynthetic rate as diploids, indicating that polyploidization alone is likely not the reason for enhanced vigor in the allopolyploid. Taken together, our data suggest that the magnitude of heterosis in A. suecica is environmentally regulated, arises from more efficient photosynthesis, and, under specific conditions, leads to greater starch accumulation than in its progenitor species.

MAGI: Methylation analysis using genome information

By incorporating annotation information into the analysis of next-generation sequencing DNA methylation data, we provide an improvement in performance over current testing procedures. Methylation analysis using genome information (MAGI) is applicable for both unreplicated and replicated data, and provides an effective analysis for studies with low sequencing depth. When compared with current tests, the annotation-informed tests provide an increase in statistical power and offer a significance-based interpretation of differential methylation.

Next-generation transcriptome sequencing of the premenopausal breast epithelium using specimens from a normal human breast tissue bank

Introduction

Our efforts to prevent and treat breast cancer are significantly impeded by a lack of knowledge of the biology and developmental genetics of the normal mammary gland. In order to provide the specimens that will facilitate such an understanding, The Susan G. Komen for the Cure Tissue Bank at the IU Simon Cancer Center (KTB) was established. The KTB is, to our knowledge, the only biorepository in the world prospectively established to collect normal, healthy breast tissue from volunteer donors. As a first initiative toward a molecular understanding of the biology and developmental genetics of the normal mammary gland, the effect of the menstrual cycle and hormonal contraceptives on DNA expression in the normal breast epithelium was examined.

Methods

Using normal breast tissue from 20 premenopausal donors to KTB, the changes in the mRNA of the normal breast epithelium as a function of phase of the menstrual cycle and hormonal contraception were assayed using next-generation whole transcriptome sequencing (RNA-Seq).

Results

In total, 255 genes representing 1.4% of all genes were deemed to have statistically significant differential expression between the two phases of the menstrual cycle. The overwhelming majority (221; 87%) of the genes have higher expression during the luteal phase. These data provide important insights into the processes occurring during each phase of the menstrual cycle. There was only a single gene significantly differentially expressed when comparing the epithelium of women using hormonal contraception to those in the luteal phase.

Conclusions

We have taken advantage of a unique research resource, the KTB, to complete the first-ever next-generation transcriptome sequencing of the epithelial compartment of 20 normal human breast specimens. This work has produced a comprehensive catalog of the differences in the expression of protein-coding genes as a function of the phase of the menstrual cycle. These data constitute the beginning of a reference data set of the normal mammary gland, which can be consulted for comparison with data developed from malignant specimens, or to mine the effects of the hormonal flux that occurs during the menstrual cycle.

Molecular response to the pathogen Phytophthora sojae among ten soybean near isogenic lines revealed by comparative transcriptomics

BACKGROUND

Phytophthora root and stem rot (PRR) of soybean, caused by Phytophthora sojae, is controlled by Rps genes. However, little is known regarding the Rps-induced molecular responses to P. sojae and how they actually overlap. We thus sequenced, analyzed, and compared the transcriptomes of 10 near isogenic lines (NILs), each with a unique Rps gene/allele, and the susceptible parent Williams, pre- and post-inoculation with the pathogen.

RESULTS

A total of 4,330 differentially expressed genes (DEGs) were identified in Williams versus 2,014 to 5,499 DEGs in individual NILs upon inoculation with the pathogen. Comparisons of the DEGs between the NILs and Williams identified incompatible interaction genes (IIGs) and compatible interaction genes (CIGs). Hierarchical cluster and heatmap analyses consistently grouped the NILs into three clusters: Cluster I (Rps1-a), Cluster II (Rps1-b, 1-c and 1-k) and Cluster III (Rps3-a, 3-b, 3-c, 4, 5, and 6), suggesting an overlap in Rps-induced defense signaling among certain NILs. Gene ontology (GO) analysis revealed associations between members of the WRKY family and incompatible reactions and between a number of phytohormone signaling pathways and incompatible/compatible interactions. These associations appear to be distinguished according to the NIL clusters.

CONCLUSIONS

This study characterized genes and multiple branches of putative regulatory networks associated with resistance to P. sojae in ten soybean NILs, and depicted functional "fingerprints" of individual Rps-mediated resistance responses through comparative transcriptomic analysis. Of particular interest are dramatic variations of detected DEGs, putatively involved in ethylene (ET)-, jasmonic acid (JA)-, (reactive oxygen species) ROS-, and (MAP-kinase) MAPK- signaling, among these soybean NILs, implicating their important roles of these signaling in differentiating molecular defense responses. We hypothesize that different timing and robustness in defense signaling to the same pathogen may be largely responsible for such variations.

Cytokinins secreted by Agrobacterium promote transformation by repressing a plant myb transcription factor

Agrobacterium-mediated transformation is the most widely used technique for generating transgenic plants. However, many crops remain recalcitrant. We found that an Arabidopsis myb family transcription factor (MTF1) inhibited plant transformation susceptibility. Mutating MTF1 increased attachment of several Agrobacterium strains to roots and increased both stable and transient transformation in both susceptible and transformation-resistant Arabidopsis ecotypes. Cytokinins from Agrobacterium tumefaciens decreased the expression of MTF1 through activation of the cytokinin response regulator ARR3. Mutating AHK3 and AHK4, genes that encode cytokinin-responsive kinases, increased the expression of MTF1 and impaired plant transformation. Mutant mtf1 plants also had increased expression of AT14A, which encodes a putative transmembrane receptor for cell adhesion molecules. Plants overexpressing AT14A exhibited increased susceptibility to transformation, whereas at14a mutant plants exhibited decreased attachment of bacteria to roots and decreased transformation, suggesting that AT14A may serve as an anchor point for Agrobacteria. Thus, by promoting bacterial attachment and transformation of resistant plants and increasing such processes in susceptible plants, treating roots with cytokinins may help engineer crops with improved features or yield.

Robust adjustment of sequence tag abundance

MOTIVATION

The majority of next-generation sequencing technologies effectively sample small amounts of DNA or RNA that are amplified (i.e. copied) before sequencing. The amplification process is not perfect, leading to extreme bias in sequenced read counts. We present a novel procedure to account for amplification bias and demonstrate its effectiveness in mitigating gene length dependence when estimating true gene expression.

RESULTS

We tested the proposed method on simulated and real data. Simulations indicated that our method captures true gene expression more effectively than classic censoring-based approaches and leads to power gains in differential expression testing, particularly for shorter genes with high transcription rates. We applied our method to an unreplicated Arabidopsis RNA-seq dataset resulting in disparate gene ontologies arising from gene set enrichment analyses.

AVAILABILITY AND IMPLEMENTATION

R code to perform the RASTA procedures is freely available on the web at www.stat.purdue.edu/∼doerge/.

Non-trisomic homeobox gene expression during craniofacial development in the Ts65Dn mouse model of Down syndrome

Trisomy 21 in humans causes cognitive impairment, craniofacial dysmorphology, and heart defects collectively referred to as Down syndrome. Yet, the pathophysiology of these phenotypes is not well understood. Craniofacial alterations may lead to complications in breathing, eating, and communication. Ts65Dn mice exhibit craniofacial alterations that model Down syndrome including a small mandible. We show that Ts65Dn embryos at 13.5 days gestation (E13.5) have a smaller mandibular precursor but a normal sized tongue as compared to euploid embryos, suggesting a relative instead of actual macroglossia originates during development. Neurological tissues were also altered in E13.5 trisomic embryos. Our array analysis found 155 differentially expressed non-trisomic genes in the trisomic E13.5 mandible, including 20 genes containing a homeobox DNA binding domain. Additionally, Sox9, important in skeletal formation and cell proliferation, was upregulated in Ts65Dn mandible precursors. Our results suggest trisomy causes altered expression of non-trisomic genes in development leading to structural changes associated with DS. Identification of genetic pathways disrupted by trisomy is an important step in proposing rational therapies at relevant time points to ameliorate craniofacial abnormalities in DS and other congenital disorders.

The fate of duplicated genes in a polyploid plant genome

Polyploidy is generally not tolerated in animals, but is widespread in plant genomes and may result in extensive genetic redundancy. The fate of duplicated genes is poorly understood, both functionally and evolutionarily. Soybean (Glycine max L.) has undergone two separate polyploidy events (13 and 59 million years ago) that have resulted in 75% of its genes being present in multiple copies. It therefore constitutes a good model to study the impact of whole-genome duplication on gene expression. Using RNA-seq, we tested the functional fate of a set of approximately 18 000 duplicated genes. Across seven tissues tested, approximately 50% of paralogs were differentially expressed and thus had undergone expression sub-functionalization. Based on gene ontology and expression data, our analysis also revealed that only a small proportion of the duplicated genes have been neo-functionalized or non-functionalized. In addition, duplicated genes were often found in collinear blocks, and several blocks of duplicated genes were co-regulated, suggesting some type of epigenetic or positional regulation. We also found that transcription factors and ribosomal protein genes were differentially expressed in many tissues, suggesting that the main consequence of polyploidy in soybean may be at the regulatory level.

Differential expression--the next generation and beyond

RNA-sequencing (RNA-seq) technologies have not only pushed the boundaries of science, but also pushed the computational and analytic capacities of many laboratories. With respect to mapping and quantifying transcriptomes, RNA-seq has certainly established itself as the approach of choice. However, as the complexities of experiments continue to grow, there is still no standard practice that allows for design, processing, normalization, efficient dimension reduction and/or statistical analysis. With this in mind, we provide a brief review of some of the key challenges that are general to all RNA-seq experiments, namely experimental design, statistical analysis and dimensionality reduction.

The nonsense-mediated decay pathway maintains synapse architecture and synaptic vesicle cycle efficacy

A systematic Drosophila forward genetic screen for photoreceptor synaptic transmission mutants identified no-on-and-no-off transient C (nonC) based on loss of retinal synaptic responses to light stimulation. The cloned gene encodes phosphatidylinositol-3-kinase-like kinase (PIKK) Smg1, a regulatory kinase of the nonsense-mediated decay (NMD) pathway. The Smg proteins act in an mRNA quality control surveillance mechanism to selectively degrade transcripts containing premature stop codons, thereby preventing the translation of truncated proteins with dominant-negative or deleterious gain-of-function activities. At the neuromuscular junction (NMJ) synapse, an extended allelic series of Smg1 mutants show impaired structural architecture, with decreased terminal arbor size, branching and synaptic bouton number. Functionally, loss of Smg1 results in a ~50% reduction in basal neurotransmission strength, as well as progressive transmission fatigue and greatly impaired synaptic vesicle recycling during high-frequency stimulation. Mutation of other NMD pathways genes (Upf2 and Smg6) similarly impairs neurotransmission and synaptic vesicle cycling. These findings suggest that the NMD pathway acts to regulate proper mRNA translation to safeguard synapse morphology and maintain the efficacy of synaptic function.

Meta-analysis combines affymetrix microarray results across laboratories

With microarray technology becoming more prevalent in recent years, it is now common for several laboratories to employ the same microarray technology to identify differentially expressed genes that are related to the same phenomenon in the same species. Although experimental specifics may be similar, each laboratory will typically produce a slightly different list of statistically significant genes, which calls into question the validity of each gene list (i.e. which list is best). A statistically-based meta-analytic approach to microarray analysis systematically combines results from the different laboratories to provide a single estimate of the degree of differential expression for each gene. This approach provides a more precise view of genes that are of significant interest, while simultaneously allowing for differences between laboratories. The widely-used Affymetrix oligonucleotide array and its software are of particular interest because the results are naturally suited to a meta-analysis. A simulation model based on the Affymetrix platform is developed to examine the adaptive nature of the meta-analytic approach and to illustrate the utility of such an approach in combining microarray results across laboratories.

Differential sensitivity of the Arabidopsis thaliana transcriptome and enhancers to the effects of genome doubling

Two fundamental types of polyploids are known: allopolyploids, in which different parental chromosome sets were combined by ancestral hybridization and duplication; and autopolyploids, which derive from multiplication of the same chromosome set. In autopolyploids, changes to the nuclear environment are not as profound as in allopolyploids, and therefore the effects of genome doubling on gene regulation remain unclear. To investigate the consequences of autopolyploidization per se, we performed a microarray analysis in three equivalent lineages of matched diploids and autotetraploids of Arabidopsis thaliana. Additionally, we compared the expression levels of GFP transgenes driven by endogenous enhancer elements (enhancer traps) in diploids and autotetraploid of 16 transgenic lines. We expected that true ploidy-dependent changes should occur in independently derived autopolyploid lineages. By this criterion, our microarray analysis detected few changes associated with polyploidization, while the enhancer-trap analysis revealed altered GFP expression at multiple plant life stages for 25% of the lines tested. Genes on individual traps were coordinately regulated while endogenous gene expression was not affected except for one line. The unique sensitivity of enhancer traps to ploidy, in contrast to the observed stability of genes, could derive from lower complexity of regulatory pathways acting on traps versus endogenous genes.

Gene expression analysis at the intersection of ploidy and hybridity in maize

Heterosis and polyploidy are two important aspects of plant evolution. To examine these issues, we conducted a global gene expression study of a maize ploidy series as well as a set of tetraploid inbred and hybrid lines. This gene expression analysis complements an earlier phenotypic study of these same materials. We find that ploidy change affects a large fraction of the genome, albeit at low levels; gene expression changes rarely exceed 2-fold and are typically not statistically significant. The most common gene expression profile we detected is greater than linear increase from monoploid to diploid, and reductions from diploid to triploid and from triploid to tetraploid, a trend that mirrors plant stature. When examining heterosis in tetraploid maize lines, we found a large fraction of the genome impacted but the majority of changes were not statistically significant at 2-fold or less. Non-additive expression was common in the hybrids, and the extent of non-additivity increased both in number and magnitude from duplex to quadruplex hybrids. Overall, we find that gene expression trends mirror observations from the phenotypic studies; however, obvious mechanistic connections remain unknown.

Epigenomic consequences of immortalized plant cell suspension culture

Plant cells grown in culture exhibit genetic and epigenetic instability. Using a combination of chromatin immunoprecipitation and DNA methylation profiling on tiling microarrays, we have mapped the location and abundance of histone and DNA modifications in a continuously proliferating, dedifferentiated cell suspension culture of Arabidopsis. We have found that euchromatin becomes hypermethylated in culture and that a small percentage of the hypermethylated genes become associated with heterochromatic marks. In contrast, the heterochromatin undergoes dramatic and very precise DNA hypomethylation with transcriptional activation of specific transposable elements (TEs) in culture. High throughput sequencing of small interfering RNA (siRNA) revealed that TEs activated in culture have increased levels of 21-nucleotide (nt) siRNA, sometimes at the expense of the 24-nt siRNA class. In contrast, TEs that remain silent, which match the predominant 24-nt siRNA class, do not change significantly in their siRNA profiles. These results implicate RNA interference and chromatin modification in epigenetic restructuring of the genome following the activation of TEs in immortalized cell culture.

DAG lipase activity is necessary for TRP channel regulation in Drosophila photoreceptors

In Drosophila, a phospholipase C-mediated signaling cascade links photoexcitation of rhodopsin to the opening of the TRP/TRPL channels. A lipid product of the cascade, diacylglycerol (DAG) and its metabolite(s), polyunsaturated fatty acids (PUFAs), have both been proposed as potential excitatory messengers. A crucial enzyme in the understanding of this process is likely to be DAG lipase (DAGL). However, DAGLs that might fulfill this role have not been previously identified in any organism. In this work, the Drosophila DAGL gene, inaE, has been identified from mutants that are defective in photoreceptor responses to light. The inaE-encoded protein isoforms show high sequence similarity to known mammalian DAG lipases, exhibit DAG lipase activity in vitro, and are highly expressed in photoreceptors. Analyses of norpA inaE double mutants and severe inaE mutants show that normal DAGL activity is required for the generation of physiologically meaningful photoreceptor responses.

Extending the modified bayesian information criterion (mBIC) to dense markers and multiple interval mapping

SUMMARY

The modified version of Bayesian Information Criterion (mBIC) is a relatively simple model selection procedure that can be used when locating multiple interacting quantitative trait loci (QTL). Our earlier work demonstrated the statistical properties of mBIC for situations where the average genetic map interval is at least 5 cM. In this work mBIC is adapted to genome searches based on a dense map and, more importantly, to the situation where consecutive QTL and interactions are located by multiple interval mapping. Easy to use formulas for the extended mBIC are given. A simulation study, as well as the analysis of real data, confirm the good properties of the extended mBIC.

Identification of novel high-frequency DNA methylation changes in breast cancer

Recent data have revealed that epigenetic alterations, including DNA methylation and chromatin structure changes, are among the earliest molecular abnormalities to occur during tumorigenesis. The inherent thermodynamic stability of cytosine methylation and the apparent high specificity of the alterations for disease may accelerate the development of powerful molecular diagnostics for cancer. We report a genome-wide analysis of DNA methylation alterations in breast cancer. The approach efficiently identified a large collection of novel differentially DNA methylated loci (∼200), a subset of which was independently validated across a panel of over 230 clinical samples. The differential cytosine methylation events were independent of patient age, tumor stage, estrogen receptor status or family history of breast cancer. The power of the global approach for discovery is underscored by the identification of a single differentially methylated locus, associated with the GHSR gene, capable of distinguishing infiltrating ductal breast carcinoma from normal and benign breast tissues with a sensitivity and specificity of 90% and 96%, respectively. Notably, the frequency of these molecular abnormalities in breast tumors substantially exceeds the frequency of any other single genetic or epigenetic change reported to date. The discovery of over 50 novel DNA methylation-based biomarkers of breast cancer may provide new routes for development of DNA methylation-based diagnostics and prognostics, as well as reveal epigenetically regulated mechanism involved in breast tumorigenesis.

Analysis of gene expression profiles in response to Sclerotinia sclerotiorum in Brassica napus

Sclerotinia sclerotiorum is a necrotrophic plant pathogen which causes serious disease in agronomically important crop species. The molecular basis of plant defense to this pathogen is poorly understood. We investigated gene expression changes associated with S. sclerotiorum infection in a partially resistant and a susceptible genotype of oilseed Brassica napus using a whole genome microarray from Arabidopsis. A total of 686 and 1,547 genes were found to be differentially expressed after infection in the resistant and susceptible genotypes, respectively. The number of differentially expressed genes increased over infection time with the majority being up-regulated in both genotypes. The putative functions of the differentially expressed genes included pathogenesis-related (PR) proteins, proteins involved in the oxidative burst, protein kinase, molecule transporters, cell maintenance and development, abiotic stress, as well as proteins with unknown functions. The gene regulation patterns indicated that a large part of the defense response exhibited as a temporal and quantitative difference between the two genotypes. Genes associated with jasmonic acid (JA) and ethylene signal transduction pathways were induced, but no salicylic acid (SA) responsive genes were identified. Candidate defense genes were identified by integration of the early response genes in the partially resistant line with previously mapped quantitative trait loci (QTL). Expression levels of these genes were verified by Northern blot analyses. These results indicate that genes encoding various proteins involved in diverse roles, particularly WRKY transcription factors and plant cell wall related proteins may play an important role in the defense response to S. sclerotiorum disease.

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.

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 (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.

A two-step multiple comparison procedure for a large number of tests and multiple treatments

For situations where the number of tested hypotheses is increasingly large, the power to detect statistically significant multiple treatment effects decreases. As is the case with microarray technology, often researchers are interested in identifying differentially expressed genes for more than two types of cells or treatments. A two-step procedure is proposed for the purpose of increasing power to detect significant effects (i.e., to identify differentially expressed genes). Specifically, in the first step, the null hypothesis of equality across the mean expression levels for all treatments is tested for each gene. In the second step, only pairwise comparisons corresponding to the genes for which the treatment means are statistically different in the first step are tested. We propose an approach to estimate the overall FDR for both fixed rejection regions and fixed FDR significance levels. Also proposed is a procedure to find the FDR significance levels used in the first step and the second step such that the overall FDR can be controlled below a pre-specified FDR significance level. When compared via simulation the two-step approach has increased power over a one-step procedure, and controls the FDR at a desire significance level.

Comprehensive DNA methylation profiling in a human cancer genome identifies novel epigenetic targets

Using a unique microarray platform for cytosine methylation profiling, the DNA methylation landscape of the human genome was monitored at more than 21,000 sites, including 79% of the annotated transcriptional start sites (TSS). Analysis of an oligodendroglioma derived cell line LN-18 revealed more than 4000 methylated TSS. The gene-centric analysis indicated a complex pattern of DNA methylation exists along each autosome, with a trend of increasing density approaching the telomeres. Remarkably, 2% of CpG islands (CGI) were densely methylated, and 17% had significant levels of 5 mC, whether or not they corresponded to a TSS. Substantial independent verification, obtained from 95 loci, suggested that this approach is capable of large scale detection of cytosine methylation with an accuracy approaching 90%. In addition, we detected large genomic domains that are also susceptible to DNA methylation reinforced inactivation, such as the HOX cluster on chromosome 7 (CH7). Extrapolation from the data suggests that more than 2000 genomic loci may be susceptible to methylation and associated inactivation, and most have yet to be identified. Finally, we report six new targets of epigenetic inactivation (IRX3, WNT10A, WNT6, RARalpha, BMP7 and ZGPAT). These targets displayed cell line and tumor specific differential methylation when compared with normal brain samples, suggesting they may have utility as biomarkers. Uniquely, hypermethylation of the CGI within an IRX3 exon was correlated with over-expression of IRX3 in tumor tissues and cell lines relative to normal brain samples.

Identification of QTLs controlling gene expression networks defined a priori

Background

Gene 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.

Results

We 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.

Conclusion

This 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.

High-density haplotyping with microarray-based expression and single feature polymorphism markers in Arabidopsis

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.

Genomewide nonadditive gene regulation in Arabidopsis allotetraploids

Polyploidy has occurred throughout the evolutionary history of all eukaryotes and is extremely common in plants. Reunification of the evolutionarily divergent genomes in allopolyploids creates regulatory incompatibilities that must be reconciled. Here we report genomewide gene expression analysis of Arabidopsis synthetic allotetraploids, using spotted 70-mer oligo-gene microarrays. We detected >15% transcriptome divergence between the progenitors, and 2105 and 1818 genes were highly expressed in Arabidopsis thaliana and A. arenosa, respectively. Approximately 5.2% (1362) and 5.6% (1469) genes displayed expression divergence from the midparent value (MPV) in two independently derived synthetic allotetraploids, suggesting nonadditive gene regulation following interspecific hybridization. Remarkably, the majority of nonadditively expressed genes in the allotetraploids also display expression changes between the parents, indicating that transcriptome divergence is reconciled during allopolyploid formation. Moreover, >65% of the nonadditively expressed genes in the allotetraploids are repressed, and >94% of the repressed genes in the allotetraploids match the genes that are expressed at higher levels in A. thaliana than in A. arenosa, consistent with the silencing of A. thaliana rRNA genes subjected to nucleolar dominance and with overall suppression of the A. thaliana phenotype in the synthetic allotetraploids and natural A. suecica. The nonadditive gene regulation is involved in various biological pathways, and the changes in gene expression are developmentally regulated. In contrast to the small effects of genome doubling on gene regulation in autotetraploids, the combination of two divergent genomes in allotetraploids by interspecific hybridization induces genomewide nonadditive gene regulation, providing a molecular basis for de novo variation and allopolyploid evolution.

eae36, a locus on mouse chromosome 4, controls susceptibility to experimental allergic encephalomyelitis in older mice and mice immunized in the winter

Genetic factors are believed to contribute to multiple sclerosis (MS) susceptibility; however, strong evidence implicating intrinsic and environmental factors in the etiopathogenesis of MS also exists. Susceptibility to experimental allergic encephalomyelitis (EAE), the principal animal model of MS, is also influenced by nongenetic factors, including age and season at immunization. This suggests that age- and season-by-gene interactions exist and that different susceptibility loci may influence disease as a function of the two parameters. In this study, linkage analysis based on genome exclusion mapping was carried out using age and season at immunization restricted cohorts of (B10.S x SJL/J) F2 intercross mice in an effort to identify such linkages. Significant linkage of EAE to eae4 and eae5 was detected with 6- to 12-week-old and summer cohorts. In contrast, significant linkage of EAE to eae4 and eae5 was not detected with the >12-week-old and winter/spring populations. Rather, significant linkage to D4Mit203 at 128.50 Mb on chromosome 4 was detected with animals that were >12 weeks old at the time of immunization or were immunized in the winter. This previously unidentified locus has been designated eae36. These results support the existence of age- and season-by-gene-specific interactions in the genetic control of susceptibility to autoimmune inflammatory disease of the central nervous system and suggest that late-onset MS may be immunogenetically distinct.

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 approximately 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.

Biased estimators of quantitative trait locus heritability and location in interval mapping

In many empirical studies, it has been observed that genome scans yield biased estimates of heritability, as well as genetic effects. It is widely accepted that quantitative trait locus (QTL) mapping is a model selection procedure, and that the overestimation of genetic effects is the result of using the same data for model selection as estimation of parameters. There are two key steps in QTL modeling, each of which biases the estimation of genetic effects. First, test procedures are employed to select the regions of the genome for which there is significant evidence for the presence of QTL. Second, and most important for this demonstration, estimates of the genetic effects are reported only at the locations for which the evidence is maximal. We demonstrate that even when we know there is just one QTL present (ignoring the testing bias), and we use interval mapping to estimate its location and effect, the estimator of the effect will be biased. As evidence, we present results of simulations investigating the relative importance of the two sources of bias and the dependence of bias of heritability estimators on the true QTL heritability, sample size, and the length of the investigated part of the genome. Moreover, we present results of simulations demonstrating the skewness of the distribution of estimators of QTL locations and the resulting bias in estimation of location. We use computer simulations to investigate the dependence of this bias on the true QTL location, heritability, and the sample size.

Epigenomic mapping in Arabidopsis using tiling microarrays

In addition to genetic information, chromosomes transmit epigenetic information from cell to cell during division, and sometimes from generation to generation. While genetic information is encoded directly in the DNA sequence, epigenetic information is not, although it is usually associated with specific chromosomal regions. Epigenetic modifications in plants include cytosine methylation as well as modification of histones and other chromosomal proteins. Small interfering RNA play major roles in targeting these modifications to specific regions. Genomic tiling microarrays are powerful tools for analysing epigenetic information, and we review their application in building epigenomic maps in the model plant, Arabidopsis.

Adding confidence to gene expression clustering

It has been well established that gene expression data contain large amounts of random variation that affects both the analysis and the results of microarray experiments. Typically, microarray data are either tested for differential expression between conditions or grouped on the basis of profiles that are assessed temporally or across genetic or environmental conditions. While testing differential expression relies on levels of certainty to evaluate the relative worth of various analyses, cluster analysis is exploratory in nature and has not had the benefit of any judgment of statistical inference. By using a novel dissimilarity function to ascertain gene expression clusters and conditional randomization of the data space to illuminate distinctions between statistically significant clusters of gene expression patterns, we aim to provide a level of confidence to inferred clusters of gene expression data. We apply both permutation and convex hull approaches for randomization of the data space and show that both methods can provide an effective assessment of gene expression profiles whose coregulation is statistically different from that expected by random chance alone.

Changes in gene expression within the nucleus accumbens and striatum following sexual experience

Sexual experience, like repeated drug use, produces long-term changes including sensitization in the nucleus accumbens and dorsal striatum. To better understand the molecular mechanisms underlying the neuroadaptations following sexual experience, we employed a DNA microarray approach to identify genes differentially expressed between sexually experienced and sexually naive female hamsters within the nucleus accumbens and dorsal striatum. For 6 weeks, a stimulus male was placed in the home cage of one-half of the hormonally primed, ovariectomized female hamsters. On the seventh week, the two experimental groups were subdivided, with one half paired with a stimulus male. In comparison with sexually naive animals, sexually experienced hamsters receiving a stimulus male on week 7 exhibited an increase in a large number of genes. Conversely, sexually experienced female hamsters not receiving a stimulus male on week 7 exhibited a reduction in the expression of many genes. For directional changes and the categories of genes regulated by the experimental conditions, data were consistent across the nucleus accumbens and dorsal striatum. However, the specific genes exhibiting changes in expression were disparate. These experiments, among the first to profile genes regulated by female sexual behavior, will provide insight into the mechanisms by which both motivated behaviors and drugs of abuse induce long-term changes in the mesolimbic and nigrostriatal dopamine pathways.

Modifying the Schwarz Bayesian information criterion to locate multiple interacting quantitative trait loci

The problem of locating multiple interacting quantitative trait loci (QTL) can be addressed as a multiple regression problem, with marker genotypes being the regressor variables. An important and difficult part in fitting such a regression model is the estimation of the QTL number and respective interactions. Among the many model selection criteria that can be used to estimate the number of regressor variables, none are used to estimate the number of interactions. Our simulations demonstrate that epistatic terms appearing in a model without the related main effects cause the standard model selection criteria to have a strong tendency to overestimate the number of interactions, and so the QTL number. With this as our motivation we investigate the behavior of the Schwarz Bayesian information criterion (BIC) by explaining the phenomenon of the overestimation and proposing a novel modification of BIC that allows the detection of main effects and pairwise interactions in a backcross population. Results of an extensive simulation study demonstrate that our modified version of BIC performs very well in practice. Our methodology can be extended to general populations and higher-order interactions.

Combining Affymetrix microarray results

BACKGROUND

As the use of microarray technology becomes more prevalent it is not unusual to find several laboratories employing the same microarray technology to identify genes related to the same condition in the same species. Although the experimental specifics are similar, typically a different list of statistically significant genes result from each data analysis.

RESULTS

We propose a statistically-based meta-analytic approach to microarray analysis for the purpose of systematically combining results from the different laboratories. This approach provides a more precise view of genes that are significantly related to the condition of interest while simultaneously allowing for differences between laboratories. Of particular interest is the widely used Affymetrix oligonucleotide array, the results of which are naturally suited to a meta-analysis. A simulation model based on the Affymetrix platform is developed to examine the adaptive nature of the meta-analytic approach and to illustrate the usefulness of such an approach in combining microarray results across laboratories. The approach is then applied to real data involving a mouse model for multiple sclerosis.

CONCLUSION

The quantitative estimates from the meta-analysis model tend to be closer to the "true" degree of differential expression than any single lab. Meta-analytic methods can systematically combine Affymetrix results from different laboratories to gain a clearer understanding of genes' relationships to specific conditions of interest.

A model selection-based interval-mapping method for autopolyploids

While extensive progress has been made in quantitative trait locus (QTL) mapping for diploid species, similar progress in QTL mapping for polyploids has been limited due to the complex genetic architecture of polyploids. To date, QTL mapping in polyploids has focused mainly on tetraploids with dominant and/or codominant markers. Here, we extend this view to include any even ploidy level under a dominant marker system. Our approach first selects the most likely chromosomal marker configurations using a Bayesian selection criterion and then fits an interval-mapping model to each candidate. Profiles of the likelihood-ratio test statistic and the maximum-likelihood estimates (MLEs) of parameters including QTL effects are obtained via the EM algorithm. Putative QTL are then detected using a resampling-based significance threshold, and the corresponding parental configuration is identified to be the underlying parental configuration from which the data are observed. Although presented via pseudo-doubled backcross experiments, this approach can be readily extended to other breeding systems. Our method is applied to single-dose restriction fragment autotetraploid alfalfa data, and the performance is investigated through simulation studies.

Genomic changes in synthetic Arabidopsis polyploids

Polyploids are common and arise frequently by genome duplication (autopolyploids) or interspecific hybridization (allopolyploids). Neoallopolyploids display sterility, lethality, phenotypic instability, gene silencing and epigenetic changes. Little is known about the molecular basis of these phenomena, and how much genomic remodeling happens upon allopolyploidization. Extensive genomic remodeling has been documented in wheat, but little remodeling occurs in cotton. Newly synthesized Arabidopsis allopolyploids, which display phenotypic instability and low fertility, displayed several, possibly related mechanisms that can remodel genomes. We detected transcriptional activity of several transposons although their transposition was limited. One represents a new family of conditionally active En-Spm-like transposons of Arabidopsis thaliana, which underwent remodeling of CG methylation upon allopolyploidization. A random amplified fragment length polymorphism survey suggested remodeling at few, specific loci. Meiotic analyses revealed the appearance of chromosomal fragments in a substantial fraction of anther meiocytes. In several individuals produced by hybrids between the synthetic and a natural allopolyploid pollen viability inversely correlated with meiotic instability. Activity of selected DNA transposons and the possibly related chromosomal breaks could cause changes by inducing translocations and rearrangements.

Genomic changes in synthetic Arabidopsis polyploids

Polyploids are common and arise frequently by genome duplication (autopolyploids) or interspecific hybridization (allopolyploids). Neoallopolyploids display sterility, lethality, phenotypic instability, gene silencing and epigenetic changes. Little is known about the molecular basis of these phenomena, and how much genomic remodeling happens upon allopolyploidization. Extensive genomic remodeling has been documented in wheat, but little remodeling occurs in cotton. Newly synthesized Arabidopsis allopolyploids, which display phenotypic instability and low fertility, displayed several, possibly related mechanisms that can remodel genomes. We detected transcriptional activity of several transposons although their transposition was limited. One represents a new family of conditionally active En-Spm-like transposons of Arabidopsis thaliana, which underwent remodeling of CG methylation upon allopolyploidization. A random amplified fragment length polymorphism survey suggested remodeling at few, specific loci. Meiotic analyses revealed the appearance of chromosomal fragments in a substantial fraction of anther meiocytes. In several individuals produced by hybrids between the synthetic and a natural allopolyploid pollen viability inversely correlated with meiotic instability. Activity of selected DNA transposons and the possibly related chromosomal breaks could cause changes by inducing translocations and rearrangements.

Methods for genome-wide analysis of gene expression changes in polyploids

Polyploidy is an evolutionary innovation, providing extra sets of genetic material for phenotypic variation and adaptation. It is predicted that changes of gene expression by genetic and epigenetic mechanisms are responsible for novel variation in nascent and established polyploids (Liu and Wendel, 2002; Osborn et al., 2003; Pikaard, 2001). Studying gene expression changes in allopolyploids is more complicated than in autopolyploids, because allopolyploids contain more than two sets of genomes originating from divergent, but related, species. Here we describe two methods that are applicable to the genome-wide analysis of gene expression differences resulting from genome duplication in autopolyploids or interactions between homoeologous genomes in allopolyploids. First, we describe an amplified fragment length polymorphism (AFLP)--complementary DNA (cDNA) display method that allows the discrimination of homoeologous loci based on restriction polymorphisms between the progenitors. Second, we describe microarray analyses that can be used to compare gene expression differences between the allopolyploids and respective progenitors using appropriate experimental design and statistical analysis. We demonstrate the utility of these two complementary methods and discuss the pros and cons of using the methods to analyze gene expression changes in autopolyploids and allopolyploids. Furthermore, we describe these methods in general terms to be of wider applicability for comparative gene expression in a variety of evolutionary, genetic, biological, and physiological contexts.

The Collaborative Cross, a community resource for the genetic analysis of complex traits

The goal of the Complex Trait Consortium is to promote the development of resources that can be used to understand, treat and ultimately prevent pervasive human diseases. Existing and proposed mouse resources that are optimized to study the actions of isolated genetic loci on a fixed background are less effective for studying intact polygenic networks and interactions among genes, environments, pathogens and other factors. The Collaborative Cross will provide a common reference panel specifically designed for the integrative analysis of complex systems and will change the way we approach human health and disease.

Reversible histone acetylation and deacetylation mediate genome-wide, promoter-dependent and locus-specific changes in gene expression during plant development

Histone acetylation and deacetylation activate or repress transcription, yet the physiological relevance of reversible changes in chromatin structure and gene expression is poorly understood. We have shown that disrupting the expression of AtHD1 that encodes a putative Arabidopsis thaliana histone deacetylase induces a variety of developmental abnormalities. However, causal effects of the AtHD1 disruption on chromatin structure and gene expression are unknown. Using Arabidopsis spotted oligo-gene microarray analysis, here we report that >7% of the transcriptome was up- or downregulated in A. thaliana plants containing a T-DNA insertion in AtHD1 (athd1-t1), indicating that AtHD1 provides positive and negative control of transcriptional regulation. Remarkably, genes involved in ionic homeostasis and protein synthesis were ectopically expressed, whereas genes in ionic homeostasis, protein transport, and plant hormonal regulation were repressed in athd1-t1 leaves or flowers, suggesting a role of AtHD1 in developmental and environmental regulation of gene expression. Moreover, defective AtHD1 induced site-specific and reversible acetylation changes in H3-Lys9, H4-Lys12, and H4 tetra-lysines (residues 5, 8, 12, and 16) in homozygous recessive and heterozygous plants. Transcriptional activation was locus specific and often associated with specific acetylation sites in the vicinity of promoters, whereas gene repression did not correlate with changes in histone acetylation or correlated directly with H3-Lys9 methylation but not with DNA methylation. The data suggest that histone acetylation and deacetylation are promoter dependent, locus specific, and genetically reversible, which provides a general mechanism for reversible gene regulation responsive to developmental and environmental changes.

The development of an Arabidopsis model system for genome-wide analysis of polyploidy effects

Arabidopsis is a model system not only for studying numerous aspects of plant biology, but also for understanding mechanisms of the rapid evolutionary process associated with genome duplication and polyploidization. Although in animals interspecific hybrids are often sterile and aneuploids are related to disease syndromes, both Arabidopsis autopolyploids and allopolyploids occur in nature and can be readily formed in the laboratory, providing an attractive system for comparing changes in gene expression and genome structure among relatively 'young' and 'established' or 'ancient' polyploids. Powerful reverse and forward genetics in Arabidopsis offer an exceptional means by which regulatory mechanisms of gene and genome duplication may be revealed. Moreover, the Arabidopsis genome is completely sequenced; both coding and non-coding sequences are available. We have developed spotted oligo-gene and chromosome microarrays using the complete Arabidopsis genome sequence. The oligo-gene microarray consists of ~26 000 70-mer oligonucleotides that are designed from all annotated genes in Arabidopsis, and the chromosome microarray contains 1 kb genomic tiling fragments amplified from a chromosomal region or the complete sequence of chromosome 4. We have demonstrated the utility of microarrays for genome-wide analysis of changes in gene expression, genome organization and chromatin structure in Arabidopsis polyploids and related species.

Role of transposable elements in heterochromatin and epigenetic control

Heterochromatin has been defined as deeply staining chromosomal material that remains condensed in interphase, whereas euchromatin undergoes de-condensation. Heterochromatin is found near centromeres and telomeres, but interstitial sites of heterochromatin (knobs) are common in plant genomes and were first described in maize. These regions are repetitive and late-replicating. In Drosophila, heterochromatin influences gene expression, a heterochromatin phenomenon called position effect variegation. Similarities between position effect variegation in Drosophila and gene silencing in maize mediated by "controlling elements" (that is, transposable elements) led in part to the proposal that heterochromatin is composed of transposable elements, and that such elements scattered throughout the genome might regulate development. Using microarray analysis, we show that heterochromatin in Arabidopsis is determined by transposable elements and related tandem repeats, under the control of the chromatin remodelling ATPase DDM1 (Decrease in DNA Methylation 1). Small interfering RNAs (siRNAs) correspond to these sequences, suggesting a role in guiding DDM1. We also show that transposable elements can regulate genes epigenetically, but only when inserted within or very close to them. This probably accounts for the regulation by DDM1 and the DNA methyltransferase MET1 of the euchromatic, imprinted gene FWA, as its promoter is provided by transposable-element-derived tandem repeats that are associated with siRNAs.