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.

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 ß-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.

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.

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.

Analysis of gene expression in resynthesized Brassica napus Allopolyploids using arabidopsis 70mer oligo microarrays.

BACKGROUND: Studies in resynthesized Brassica napus allopolyploids indicate that homoeologous chromosome exchanges in advanced generations (S(5ratio6)) alter gene expression through the loss and doubling of homoeologous genes within the rearrangements. Rearrangements may also indirectly affect global gene expression if homoeologous copies of gene regulators within rearrangements have differential affects on the transcription of genes in networks. METHODOLOGY/PRINCIPAL FINDINGS: We utilized Arabidopsis 70mer oligonucleotide microarrays for exploring gene expression in three resynthesized B. napus lineages at the S(0ratio1) and S(5ratio6) generations as well as their diploid progenitors B. rapa and B. oleracea. Differential gene expression between the progenitors and additive (midparent) expression in the allopolyploids were tested. The S(5ratio6) lines differed in the number of genetic rearrangements, allowing us to test if the number of genes displaying nonadditive expression was related to the number of rearrangements. Estimates using per-gene and common variance ANOVA models indicated that 6-15% of 26,107 genes were differentially expressed between the progenitors. Individual allopolyploids showed nonadditive expression for 1.6-32% of all genes. Less than 0.3% of genes displayed nonadditive expression in all S(0ratio1) lines and 0.1-0.2% were nonadditive among all S(5ratio6) lines. Differentially expressed genes in the polyploids were over-represented by genes differential between the progenitors. The total number of differentially expressed genes was correlated with the number of genetic changes in S(5ratio6) lines under the common variance model; however, there was no relationship using a per-gene variance model, and many genes showed nonadditive expression in S(0ratio1) lines. CONCLUSIONS/SIGNIFICANCE: Few genes reproducibly demonstrated nonadditive expression among lineages, suggesting few changes resulted from a general response to polyploidization. Furthermore, our microarray analysis did not provide strong evidence that homoeologous rearrangements were a determinant of genome-wide nonadditive gene expression. In light of the inherent limitations of the Arabidopsis microarray to measure gene expression in polyploid Brassicas, further studies are warranted.

Estimating the proportion of true null hypotheses for multiple comparisons.

Whole genome microarray investigations (e.g. differential expression, differential methylation, ChIP-Chip) provide opportunities to test millions of features in a genome. Traditional multiple comparison procedures such as familywise error rate (FWER) controlling procedures are too conservative. Although false discovery rate (FDR) procedures have been suggested as having greater power, the control itself is not exact and depends on the proportion of true null hypotheses. Because this proportion is unknown, it has to be accurately (small bias, small variance) estimated, preferably using a simple calculation that can be made accessible to the general scientific community. We propose an easy-to-implement method and make the R code available, for estimating the proportion of true null hypotheses. This estimate has relatively small bias and small variance as demonstrated by (simulated and real data) comparing it with four existing procedures. Although presented here in the context of microarrays, this estimate is applicable for many multiple comparison situations.

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.

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.

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.

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.

Sensitivity of 70-mer oligonucleotides and cDNAs for microarray analysis of gene expression in Arabidopsis and its related species.

Synthetic oligonucleotides (oligos) represent an attractive alternative to cDNA amplicons for spotted microarray analysis in a number of model organisms, including Arabidopsis, C. elegans, Drosophila, human, mouse and yeast. However, little is known about the relative effectiveness of 60-70-mer oligos and cDNAs for detecting gene expression changes. Using 192 pairs of Arabidopsis thaliana cDNAs and corresponding 70-mer oligos, we performed three sets of dye-swap experiments and used analysis of variance (anova) to compare sources of variation and sensitivities for detecting gene expression changes in A. thaliana, A. arenosa and Brassica oleracea. Our major findings were: (1) variation among different RNA preparations from the same tissue was small, but large variation among dye-labellings and slides indicates the need to replicate these factors; (2) sources of variation were similar for experiments with all three species, suggesting these feature types are effective for analysing gene expression in related species; (3) oligo and cDNA features had similar sensitivities for detecting expression changes and they identified a common subset of significant genes, but results from quantitative RT-PCR did not support the use of one over the other. These findings indicate that spotted oligos are at least as effective as cDNAs for microarray analyses of gene expression. We are using oligos designed from approximately 26,000 annotated genes of A. thaliana to study gene expression changes in Arabidopsis and Brassica polyploids.

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.

Transfer of T-DNA and Vir proteins to plant cells by Agrobacterium tumefaciens induces expression of host genes involved in mediating transformation and suppresses host defense gene expression.

Agrobacterium tumefaciens is a plant pathogen that incites crown gall tumors by transferring to and expressing a portion of a resident plasmid in plant cells. Currently, little is known about the host response to Agrobacterium infection. Using suppressive subtractive hybridization and DNA macroarrays, we identified numerous plant genes that are differentially expressed during early stages of Agrobacterium-mediated transformation. Expression profiling indicates that Agrobacterium infection induces plant genes necessary for the transformation process while simultaneously repressing host defense response genes, thus indicating successful utilization of existing host cellular machinery for genetic transformation purposes. A comparison of plant responses to different strains of Agrobacterium indicates that transfer of both T-DNA and Vir proteins modulates the expression of host genes during the transformation process.

Understanding mechanisms of novel gene expression in polyploids.

Polyploidy has long been recognized as a prominent force shaping the evolution of eukaryotes, especially flowering plants. New phenotypes often arise with polyploid formation and can contribute to the success of polyploids in nature or their selection for use in agriculture. Although the causes of novel variation in polyploids are not well understood, they could involve changes in gene expression through increased variation in dosage-regulated gene expression, altered regulatory interactions, and rapid genetic and epigenetic changes. New research approaches are being used to study these mechanisms and the results should provide a more complete understanding of polyploidy.

Genetic control of susceptibility to experimental Lyme arthritis is polygenic and exhibits consistent linkage to multiple loci on chromosome 5 in four independent mouse crosses.

C3H/He mice infected with Borrelia burgdorferi develop severe arthritis and are high antibody responders, while infected C57BL/6 and BALB/c mice develop mild arthritis and less robust humoral responses. Genetic analysis using composite interval mapping (CIM) on reciprocal backcross populations derived from C3H/HeN and C57BL/6N or C3H/HeJ and BALB/cAnN mice identified 12 new quantitative trait loci (QTL) linked to 10 murine Lyme disease phenotypes. These QTL reside on chromosomes 1, 2, 4, 6, 7, 9, 10, 12, 14, 15, 16, and 17. A reanalysis of an F(2) intercross between C57BL/6N and C3H/HeN mice using CIM identified two new QTL on chromosomes 4 and 15 and confirmed the location of seven previously identified loci. Two or more experimental crosses independently verified six QTL controlling phenotypes after B. burgdorferi infection. Additionally, Bb2 on chromosome 5 was reproduced in four experimental populations and was linked to the candidate locus Cora1. Evidence of four distinct QTL residing within the 30-cM region of chromosome 5 encompassing the previously mapped Bb2 and Bb3 loci was shown by CIM. Interestingly, some alleles contributing to susceptibility to Lyme arthritis were derived from C57BL/6N and BALB/cAnN mice, showing that disease-resistant strains harbor susceptibility alleles.

Model selection for quantitative trait locus analysis in polyploids.

Over the years, substantial gains have been made in locating regions of agricultural genomes associated with characteristics, diseases, and agroeconomic traits. These gains have relied heavily on the ability to statistically estimate the association between DNA markers and regions of a genome (quantitative trait loci or QTL) related to a particular trait. The majority of these advances have focused on diploid species, even though many important agricultural crops are, in fact, polyploid. The purpose of our work is to initiate an algorithmic approach for model selection and QTL detection in polyploid species. This approach involves the construction of all possible chromosomal configurations (models) that may result in a gamete, model reduction based on estimation of marker dosage from progeny data, and lastly model selection. While simplified for initial explanation, our approach has demonstrated itself to be extendible to many breeding schemes and less restricted settings.

Interacting quantitative trait loci control phenotypic variation in murine estradiol-regulated responses.

The steroid hormone estradiol (E2) elicits a spectrum of systemic and uterotropic responses in vivo. For example, E2 treatment of ovariectomized adult and sexually immature rodents leads to uterine leukocytic infiltration, cell proliferation, and organ growth. E2-regulated growth is also associated with a variety of normal and pathological phenotypes. Historically, the uterine growth response has been used as the key model to understand the molecular and biochemical mechanisms underlying E2-dependent growth. In this study, genome exclusion mapping identified two quantitative trait loci (QTL) in the mouse, Est2 and Est3 on chromosomes 5 and 11, respectively, that control the phenotypic variation in uterine wet weight. Both QTL are linked to a variety of E2-regulated genes, suggesting that they may represent loci within conserved gene complexes that play fundamental roles in mediating the effects of E2. Interaction and multiple trait analyses using the uterine leukocyte response and wet weight suggest that Est4, a QTL on chromosome 10, may encode an interacting factor that influences the quantitative variation in both responses. Our results show that E2-dependent responses can be genetically controlled and that a genetic basis may underlie the variation observed in many E2-dependent phenotypes.