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arXiv2012

Binary Interval Search (BITS): A Scalable Algorithm for Counting Interval Intersections

Motivation: The comparison of diverse genomic datasets is fundamental to understanding genome biology. Researchers must explore many large datasets of genome intervals (e.g., genes, sequence alignments) to place their experimental results in a broader context and to make new discoveries. Relationships between genomic datasets are typically measured by identifying intervals that intersect: that is, they overlap and thus share a common genome interval. Given the continued advances in DNA sequencing technologies, efficient methods for measuring statistically significant relationships between many sets of genomic features is crucial for future discovery. Results: We introduce the Binary Interval Search (BITS) algorithm, a novel and scalable approach to interval set intersection. We demonstrate that BITS outperforms existing methods at counting interval intersections. Moreover, we show that BITS is intrinsically suited to parallel computing architectures such as Graphics Processing Units (GPUs) by illustrating its utility for efficient Monte-Carlo simulations measuring the significance of relationships between sets of genomic intervals.

q-bio.GN↗

arXiv2013

SASeq: A Selective and Adaptive Shrinkage Approach to Detect and Quantify Active Transcripts using RNA-Seq

Identification and quantification of condition-specific transcripts using RNA-Seq is vital in transcriptomics research. While initial efforts using mathematical or statistical modeling of read counts or per-base exonic signal have been successful, they may suffer from model overfitting since not all the reference transcripts in a database are expressed under a specific biological condition. Standard shrinkage approaches, such as Lasso, shrink all the transcript abundances to zero in a non-discriminative manner. Thus it does not necessarily yield the set of condition-specific transcripts. Informed shrinkage approaches, using the observed exonic coverage signal, are thus desirable. Motivated by ubiquitous uncovered exonic regions in RNA-Seq data, termed as "naked exons", we propose a new computational approach that first filters out the reference transcripts not supported by splicing and paired-end reads, then followed by fitting a new mathematical model of per-base exonic coverage signal and the underlying transcripts structure. We introduce a tuning parameter to penalize the specific regions of the selected transcripts that were not supported by the naked exons. Our approach compares favorably with the selected competing methods in terms of both time complexity and accuracy using simulated and real-world data. Our method is implemented in SAMMate, a GUI software suite freely available from http://sammate.sourceforge.net

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arXiv2012

Differential Expression Analysis for A Mouse p53KO Microarray Dataset

Affymetrix GeneChip technology is used to detect gene expression levels in samples of cells under different conditions. In this project, we analyzed the gene expression profiling data for mouse induced pluripotent stem cell (iPSCs) (Takahashi, 2006) on Affymetrix Mouse 430 2.0 GeneChip. Three biological conditions were present: p53KO, microRNA mir34aKO, and wild type, each with three biological replicates. The first part was devoted to identifying differentially expressed genes from around 45,000 of them, and looking into their biological meanings by pathway analysis. The second part dealt with repetitive elements represented in the pool of mRNAs. We identified repetitive elements that show a significant difference between two biological conditions. Both the comparison of p53KO versus WT and mir34aKO versus WT were done. However, the emphasis was on the former. Laboratory validation with qPCR confirmed our findings. This work was done under the Overseas Research Fellowship (ORF) Scheme 2012 for Science Students by the Faculty of Science, The University of Hong Kong. Many thanks are due to the University for the fellowship, and to Professors Terry Speed and Lin He and Drs Chao-po Lin and Anne Biton of the University of California at Berkeley for their supervision and generous support.

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arXiv2016

Reverse Engineering Gene Interaction Networks Using the Phi-Mixing Coefficient

Constructing gene interaction networks (GINs) from high-throughput gene expression data is an important and challenging problem in systems biology. Existing algorithms produce networks that either have undirected and unweighted edges, or else are constrained to contain no cycles, both of which are biologically unrealistic. In the present paper we propose a new algorithm, based on a concept from probability theory known as the phi-mixing coefficient, that produces networks whose edges are weighted and directed, and are permitted to contain cycles. Because there is no "ground truth" for genome-wide networks on a human scale, we analyzed the outcomes of several experiments on lung cancer, and matched the predictions from the inferred networks with experimental results. Specifically, we inferred three networks (NSCLC, Neuro-endocrine NSCLC plus SCLC, and normal) from the gene expression measurements of 157 lung cancer and 59 normal cell lines, compared with the outcomes of siRNA screening of 19,000+ genes on 11 NSCLC cell lines, and analyzed data from a ChIP-Seq experiment to determine putative downstream targets of the lineage specific oncogenic transcription factor ASCL1. The inferred networks displayed a scale-free or power law behavior between the degree of a node and the number of nodes with that degree. There was a strong correlation between the degree of a gene in the inferred NSCLC network and its essentiality for the survival of the cells. The inferred downstream neighborhood genes of ASCL1 in the SCLC network were significantly enriched by ChIP-Seq determined putative target genes, while no such enrichment was found in the inferred NSCLC network.

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arXiv2013

Annotation Enrichment Analysis: An Alternative Method for Evaluating the Functional Properties of Gene Sets

Gene annotation databases (compendiums maintained by the scientific community that describe the biological functions performed by individual genes) are commonly used to evaluate the functional properties of experimentally derived gene sets. Overlap statistics, such as Fisher's Exact Test (FET), are often employed to assess these associations, but don't account for non-uniformity in the number of genes annotated to individual functions or the number of functions associated with individual genes. We find FET is strongly biased toward over-estimating overlap significance if a gene set has an unusually high number of annotations. To correct for these biases, we develop Annotation Enrichment Analysis (AEA), which properly accounts for the non-uniformity of annotations. We show that AEA is able to identify biologically meaningful functional enrichments that are obscured by numerous false-positive enrichment scores in FET, and we therefore suggest it be used to more accurately assess the biological properties of gene sets.

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arXiv2012

Integrated analysis of variants and pathways in genome-wide association studies using polygenic models of disease

Many common diseases are highly polygenic, modulated by a large number genetic factors with small effects on susceptibility to disease. These small effects are difficult to map reliably in genetic association studies. To address this problem, researchers have developed methods that aggregate information over sets of related genes, such as biological pathways, to identify gene sets that are enriched for genetic variants associated with disease. However, these methods fail to answer a key question: which genes and genetic variants are associated with disease risk? We develop a method based on sparse multiple regression that simultaneously identifies enriched pathways, and prioritizes the variants within these pathways, to locate additional variants associated with disease susceptibility. A central feature of our approach is an estimate of the strength of enrichment, which yields a coherent way to prioritize variants in enriched pathways. We illustrate the benefits of our approach in a genome-wide association study of Crohn's disease with ~440,000 genetic variants genotyped for ~4700 study subjects. We obtain strong support for enrichment of IL-12, IL-23 and other cytokine signaling pathways. Furthermore, prioritizing variants in these enriched pathways yields support for additional disease-association variants, all of which have been independently reported in other case-control studies for Crohn's disease.

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arXiv2012

An Open Framework for Extensible Multi-Stage Bioinformatics Software

In research labs, there is often a need to customise software at every step in a given bioinformatics workflow, but traditionally it has been difficult to obtain both a high degree of customisability and good performance. Performance-sensitive tools are often highly monolithic, which can make research difficult. We present a novel set of software development principles and a bioinformatics framework, Friedrich, which is currently in early development. Friedrich applications support both early stage experimentation and late stage batch processing, since they simultaneously allow for good performance and a high degree of flexibility and customisability. These benefits are obtained in large part by basing Friedrich on the multiparadigm programming language Scala. We present a case study in the form of a basic genome assembler and its extension with new functionality. Our architecture has the potential to greatly increase the overall productivity of software developers and researchers in bioinformatics.

cs.SE↗

arXiv2012

Lineage-specific transposons drove massive gene expression recruitments during the evolution of pregnancy in mammals

A major challenge in biology is explaining how novel characters originate, however, the molecular mechanisms that underlie the emergence of evolutionary innovations are unclear. Here we show that while gene expression in the uterus evolves at a slow and relatively constant rate, it has been punctuated by periods of rapid change associated with the recruitment of thousands of genes into uterine expression during the evolution of pregnancy in mammals. We found that numerous genes and signaling pathways essential for the establishment of pregnancy and maternal-fetal communication evolved uterine expression in mammals. Remarkably the majority of genes recruited into endometrial expression have cis-regulatory elements derived from lineage-specific transposons, suggesting that that bursts of transposition facilitate adaptation and speciation through genomic and regulatory reorganization.

q-bio.PE↗

arXiv2013

Transposable element sequence evolution is influenced by gene context

Background: Transposable elements (TEs) in eukaryote genomes are quantitatively the main components affecting genome size, structure and expression. The dynamics of their insertion and deletion depend on diverse factors varying in strength and nature along the genome. We address here how TE sequence evolution is affected by neighboring genes and the chromatin status (euchromatin or heterochromatin) at their insertion site. Results: We estimated ages of TE sequences in Arabidopsis thaliana, and found that they depend on the distance to the nearest genes: TEs located close to genes are older than those that are more distant. Consequently, TE sequences in heterochromatic regions, which are gene-poor regions, are surprisingly younger and longer than that elsewhere. Conclusions: We provide evidence for biased TE age distribution close or near to genes. Interestingly, TE sequences in euchromatin and those in heterochromatin evolve at different rates, and as a result, could explain that TE sequences in heterochromatin tend to be younger and longer. Then, we revisit models of TE sequence dynamics and point out differences for TE-rich genomes, such as maize and wheat, compared to TE-poor genomes such as fly and A. thaliana.

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arXiv2012

An explanation of unexpected Hoxd expressions in mutant mice

The Hox gene collinearity enigma has often been approached using models based on biomolecular mechanisms. The biophysical model, is an alternative approach, speculating that collinearity is caused by physical forces pulling the Hox clusters from a territory where they are inactive to a distinct spatial domain where they are activated in a step by step manner. Hox gene translocations have recently been observed in support of the biophysical model. Furthermore, genetic engineering experiments, performed in embryonic mice, gave rise to some unexpected mutant expressions that biomolecular models could not predict. In several cases when anterior Hoxd genes are deleted, the expression of the genes whose expression is probed in the mutants are impossible to anticipate. On the contrary, the biophysical model offers convincing explanation. All these experimental results support the idea of physical forces being responsible for Hox gene collinearity. In order to test the validity of the various models further, certain experiment involving gene deletions are proposed. The biophysical and biomolecular models predict different results for these experiments, hence the expected outcome will confirm or question the validity of these models.

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arXiv2012

Polygenic Modeling with Bayesian Sparse Linear Mixed Models

Both linear mixed models (LMMs) and sparse regression models are widely used in genetics applications, including, recently, polygenic modeling in genome-wide association studies. These two approaches make very different assumptions, so are expected to perform well in different situations. However, in practice, for a given data set one typically does not know which assumptions will be more accurate. Motivated by this, we consider a hybrid of the two, which we refer to as a "Bayesian sparse linear mixed model" (BSLMM) that includes both these models as special cases. We address several key computational and statistical issues that arise when applying BSLMM, including appropriate prior specification for the hyper-parameters, and a novel Markov chain Monte Carlo algorithm for posterior inference. We apply BSLMM and compare it with other methods for two polygenic modeling applications: estimating the proportion of variance in phenotypes explained (PVE) by available genotypes, and phenotype (or breeding value) prediction. For PVE estimation, we demonstrate that BSLMM combines the advantages of both standard LMMs and sparse regression modeling. For phenotype prediction it considerably outperforms either of the other two methods, as well as several other large-scale regression methods previously suggested for this problem. Software implementing our method is freely available from http://stephenslab.uchicago.edu/software.html

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arXiv2012

Power-laws and the Conservation of Information in discrete token systems: Part 2 The role of defect

In a matching paper (arXiv:1207.5027), I proved that Conservation of Size and Information in a discrete token based system is overwhelmingly likely to lead to a power-law component size distribution with respect to the size of its unique alphabet. This was substantiated to a very high level of significance using some 55 million lines of source code of mixed provenance. The principle was also applied to show that average gene length should be constant in an animal kingdom where the same constraints appear to hold, the implication being that Conservation of Information plays a similar role in discrete token-based systems as the Conservation of Energy does in physical systems. In this part 2, the role of defect will be explored and a functional behaviour for defect derived to be consistent with the power-law behaviour substantiated above. This will be supported by further experimental data and the implications explored.

cs.IT↗

arXiv2012

Genome-wide analysis points to roles for extracellular matrix remodeling, the visual cycle, and neuronal development in myopia

Myopia, or nearsightedness, is the most common eye disorder, resulting primarily from excess elongation of the eye. The etiology of myopia, although known to be complex, is poorly understood. Here we report the largest ever genome-wide association study (43,360 participants) on myopia in Europeans. We performed a survival analysis on age of myopia onset and identified 19 significant associations (p < 5e-8), two of which are replications of earlier associations with refractive error. These 19 associations in total explain 2.7% of the variance in myopia age of onset, and point towards a number of different mechanisms behind the development of myopia. One association is in the gene PRSS56, which has previously been linked to abnormally small eyes; one is in a gene that forms part of the extracellular matrix (LAMA2); two are in or near genes involved in the regeneration of 11-cis-retinal (RGR and RDH5); two are near genes known to be involved in the growth and guidance of retinal ganglion cells (ZIC2, SFRP1); and five are in or near genes involved in neuronal signaling or development. These novel findings point towards multiple genetic factors involved in the development of myopia and suggest that complex interactions between extracellular matrix remodeling, neuronal development, and visual signals from the retina may underlie the development of myopia in humans.

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arXiv2012

A genetic variant near olfactory receptor genes influences cilantro preference

The leaves of the Coriandrum sativum plant, known as cilantro or coriander, are widely used in many cuisines around the world. However, far from being a benign culinary herb, cilantro can be polarizing---many people love it while others claim that it tastes or smells foul, often like soap or dirt. This soapy or pungent aroma is largely attributed to several aldehydes present in cilantro. Cilantro preference is suspected to have a genetic component, yet to date nothing is known about specific mechanisms. Here we present the results of a genome-wide association study among 14,604 participants of European ancestry who reported whether cilantro tasted soapy, with replication in a distinct set of 11,851 participants who declared whether they liked cilantro. We find a single nucleotide polymorphism (SNP) significantly associated with soapy-taste detection that is confirmed in the cilantro preference group. This SNP, rs72921001, (p=6.4e-9, odds ratio 0.81 per A allele) lies within a cluster of olfactory receptor genes on chromosome 11. Among these olfactory receptor genes is OR6A2, which has a high binding specificity for several of the aldehydes that give cilantro its characteristic odor. We also estimate the heritability of cilantro soapy-taste detection in our cohort, showing that the heritability tagged by common SNPs is low, about 0.087. These results confirm that there is a genetic component to cilantro taste perception and suggest that cilantro dislike may stem from genetic variants in olfactory receptors. We propose that OR6A2 may be the olfactory receptor that contributes to the detection of a soapy smell from cilantro in European populations.

q-bio.GN↗

arXiv2012

Balancing noise and plasticity in eukaryotic gene expression

Coupling the control of expression stochasticity (noise) to the ability of expression change (plasticity) can alter gene function and influence adaptation. A number of factors, such as transcription re-initiation, strong chromatin regulation or genome neighboring organization, underlie this coupling. However, these factors do not necessarily combine in equivalent ways and strengths in all genes. Can we identify then alternative architectures that modulate in distinct ways the linkage of noise and plasticity? Here we first show that strong chromatin regulation, commonly viewed as a source of coupling, can lead to plasticity without noise. The nature of this regulation is relevant too, with plastic but noiseless genes being subjected to general activators whereas plastic and noisy genes experience more specific repression. Contrarily, in genes exhibiting poor transcriptional control, it is translational efficiency what separates noise from plasticity, a pattern related to transcript length. This additionally implies that genome neighboring organization -as modifier- appears only effective in highly plastic genes. In this class, we confirm bidirectional promoters (bipromoters) as a configuration capable to reduce coupling by abating noise but also reveal an important trade-off, since bipromoters also decrease plasticity. This presents ultimately a paradox between intergenic distances and modulation, with short intergenic distances both associated and disassociated to noise at different plasticity levels. Balancing the coupling among different types of expression variability appears as a potential shaping force of genome regulation and organization. This is reflected in the use of different control strategies at genes with different sets of functional constraints.

q-bio.GN↗

arXiv2012

Horizontal gene transfer drives extreme physiological change in Haloarchaea

The haloarchaea are aerobic, heterotrophic, photophosphorylating prokaryotes, whose supposed closest relatives and ancestors, the methanogens, are CO2-reducing, anaerobic chemolithotrophs. Using two available haloarchaeal genomes we firstly confirmed the methanogenic ancestry of the group and then investigated those individual genes in the haloarchaea that differ in their phylogenetic signal to this relationship. We found that almost half the genes, about which we can make strong statements, have bacterial ancestry and are likely a result of multiple horizontal transfer events. Futhermore their functions specifically relate to the phenotypic changes required for a chemolithotroph to become a heterotroph. If this phylogenetic relationship is correct, it implies the development of the haloarchaeal phenotype was among the most extreme changes in cellular physiology fuelled by horizontal gene transfer.

q-bio.GN↗

arXiv2012

Analysis of central Hox protein types across bilaterian clades: On the origin of central Hox proteins from an Antennapedia/Hox7-like ancestor

Hox proteins are one of the best studied sets of transcription factors in developmental biology. They are major determinants for establishing morphological differences along the anterior-posterior axis of animals and are generally regarded as highly conserved in function. This view is based on experiments comparing a few (anterior) Hox proteins, however, the extent to which central or abdominal Hox proteins share sequence features or functions remains largely unexplored. To shed light on the origin and functional divergence of the central Hox proteins, we combine a powerful bioinformatics tool (CLANS) with a large-scale phylogeny of species. CLANS is used to differentiate between the various types of central Hox protein sequences, while the phylogeny provides an evolutionary context to the analysis. The combination of both enables us to infer the relative timepoint at which a given central Hox protein type arose. We identify seven distinct central Hox protein sequence types, only one of which is common to all protostome and deuterostome clades (Antp/Hox7). Together, these results lead us to suggest reevaluating the usefulness of the increasingly depicted synteny-based classification scheme that assumes a one-to-one orthology between protostome and deuterostome central Hox proteins. Instead, we propose that the use of sequence-based classification schemes able to resolve the central and posterior Hox proteins provides a more promising and biologically meaningful alternative to resolving these groups. This analysis, which provides a unique overview of the Hox protein sequence types present across protostomes and deuterostomes as well as a relative dating for the emergence of the central Hox protein types, provides a crucial clue to illuminate how and when the distinct developmental blueprints for organisms evolved within the evolutionarily immensely successful bilaterian lineage.

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arXiv2012

Virtual screening and lead optimisation to identify novel inhibitors for HDAC-8

Histone deacetylase (HDAC) and Histone acetyl-transferase (HAT) are enzymes that influence transcription by selectively deacetylating or acetylating the (epsilon)-amino groups of lysine located near the amino termini of core histone proteins. Over expression of HDACs noted in many forms of cancers including leukemia and breast cancer. HDAC inhibitors have been shown to be potent inducers of growth arrest, differentiation, and/or apoptotic cell death. There is a growing interest in the development of histone deacetylase inhibitors as anti cancer agents. Three known ligands of HDAC-8 were taken and docked. The best scores were analyzed and structures similar to these ligands were downloaded using carol and corina databases and docked. Also large databases of small molecules were computationally screened using molecular docking for hits that can conformationally and chemically fit to the active site. Molecules which got high scores for both GoldScore and ChemScore were selected and compared with the previous results. Those with best results were then taken for calculating H-bond interactions and close contacts. Bioactivity prediction of the best ranked ligands was done. Their physicochemical properties were also analyzed. Four new molecules were identified and suggested for further testing in the wet lab.

q-bio.BM↗