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.

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.

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 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.

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.

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.

Selecting informative traits for multivariate quantitative trait locus mapping helps to gain optimal power.

A major consideration in multitrait analysis is which traits should be jointly analyzed. As a common strategy, multitrait analysis is performed either on pairs of traits or on all of traits. To fully exploit the power of multitrait analysis, we propose variable selection to choose a subset of informative traits for multitrait quantitative trait locus (QTL) mapping. The proposed method is very useful for achieving optimal statistical power for QTL identification and for disclosing the most relevant traits. It is also a practical strategy to effectively take advantage of multitrait analysis when the number of traits under consideration is too large, making the usual multivariate analysis of all traits challenging. We study the impact of selection bias and the usage of permutation tests in the context of variable selection and develop a powerful implementation procedure of variable selection for genome scanning. We demonstrate the proposed method and selection procedure in a backcross population, using both simulated and real data. The extension to other experimental mapping populations is straightforward.

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.

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.

Dynamic clustering of gene expression.

It is well accepted that genes are simultaneously involved in multiple biological processes and that genes are coordinated over the duration of such events. Unfortunately, clustering methodologies that group genes for the purpose of novel gene discovery fail to acknowledge the dynamic nature of biological processes and provide static clusters, even when the expression of genes is assessed across time or developmental stages. By taking advantage of techniques and theories from time frequency analysis, periodic gene expression profiles are dynamically clustered based on the assumption that different spectral frequencies characterize different biological processes. A two-step cluster validation approach is proposed to statistically estimate both the optimal number of clusters and to distinguish significant clusters from noise. The resulting clusters reveal coordinated coexpressed genes. This novel dynamic clustering approach has broad applicability to a vast range of sequential data scenarios where the order of the series is of interest.

Statistical design and analysis of RNA sequencing data.

Next-generation sequencing technologies are quickly becoming the preferred approach for characterizing and quantifying entire genomes. Even though data produced from these technologies are proving to be the most informative of any thus far, very little attention has been paid to fundamental design aspects of data collection and analysis, namely sampling, randomization, replication, and blocking. We discuss these concepts in an RNA sequencing framework. Using simulations we demonstrate the benefits of collecting replicated RNA sequencing data according to well known statistical designs that partition the sources of biological and technical variation. Examples of these designs and their corresponding models are presented with the goal of testing differential expression.

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.

The KM-Algorithm Identifies Regulated Genes in Time Series Expression Data.

We present a statistical method to rank observed genes in gene expression time series experiments according to their degree of regulation in a biological process. The ranking may be used to focus on specific genes or to select meaningful subsets of genes from which gene regulatory networks can be built. Our approach is based on a state space model that incorporates hidden regulators of gene expression. Kalman (K) smoothing and maximum (M) likelihood estimation techniques are used to derive optimal estimates of the model parameters upon which a proposed regulation criterion is based. The statistical power of the proposed algorithm is investigated, and a real data set is analyzed for the purpose of identifying regulated genes in time dependent gene expression data. This statistical approach supports the concept that meaningful biological conclusions can be drawn from gene expression time series experiments by focusing on strong regulation rather than large expression values.

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.

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.

Presynaptic calcium channel localization and calcium-dependent synaptic vesicle exocytosis regulated by the Fuseless protein.

A systematic forward genetic Drosophila screen for electroretinogram mutants lacking synaptic transients identified the fuseless (fusl) gene, which encodes a predicted eight-pass transmembrane protein in the presynaptic membrane. Null fusl mutants display >75% reduction in evoked synaptic transmission but, conversely, an approximately threefold increase in the frequency and amplitude of spontaneous synaptic vesicle fusion events. These neurotransmission defects are rescued by a wild-type fusl transgene targeted only to the presynaptic cell, demonstrating a strictly presynaptic requirement for Fusl function. Defects in FM dye turnover at the synapse show a severely impaired exo-endo synaptic vesicle cycling pool. Consistently, ultrastructural analyses reveal accumulated vesicles arrested in clustered and docked pools at presynaptic active zones. In the absence of Fusl, calcium-dependent neurotransmitter release is dramatically compromised and there is little enhancement of synaptic efficacy with elevated external Ca(2+) concentrations. These defects are causally linked with severe loss of the Cacophony voltage-gated Ca(2+) channels, which fail to localize normally at presynaptic active zone domains in the absence of Fusl. These data indicate that Fusl regulates assembly of the presynaptic active zone Ca(2+) channel domains required for efficient coupling of the Ca(2+) influx and synaptic vesicle exocytosis during neurotransmission.

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.

Naive application of permutation testing leads to inflated type I error rates.

Failure to account for family structure within populations or in complex mating designs via uninformed applications of permutation testing will lead to inflated type I error rates. Careful consideration of the design factors is essential since some situations allow several valid permutation strategies, and the choice that maximizes statistical power will not always be intuitive.