Thu, 07 Aug 2008 22:01:59 BST CiteULike: caseybrown's library [258 articles] http://www.citeulike.org/user/caseybrown CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/caseybrown/article/3080474 <i>PLoS Genet, Vol. 4, No. 8. (2008), e1000139.</i><br /><br />Whole-genome sequencing is a powerful technique for obtaining the reference sequence information of multiple organisms. Its use can be dramatically expanded to rapidly identify genomic variations, which can be linked with phenotypes to obtain biological insights. We explored these potential applications using the emerging next-generation sequencing platform Solexa Genome Analyzer, and the well-characterized model bacterium Bacillus subtilis. Combining sequencing with experimental verification, we first improved the accuracy of the published sequence of the B. subtilis reference strain 168, then obtained sequences of multiple related laboratory strains and different isolates of each strain. This provides a framework for comparing the divergence between different laboratory strains and between their individual isolates. We also demonstrated the power of Solexa sequencing by using its results to predict a defect in the citrate signal transduction pathway of a common laboratory strain, which we verified experimentally. Finally, we examined the molecular nature of spontaneously generated mutations that suppress the growth defect caused by deletion of the stringent response mediator relA. Using whole-genome sequencing, we rapidly mapped these suppressor mutations to two small homologs of relA. Interestingly, stable suppressor strains had mutations in both genes, with each mutation alone partially relieving the relA growth defect. This supports an intriguing three-locus interaction module that is not easily identifiable through traditional suppressor mapping. We conclude that whole-genome sequencing can drastically accelerate the identification of suppressor mutations and complex genetic interactions, and it can be applied as a standard tool to investigate the genetic traits of model organisms. High-Precision, Whole-Genome Sequencing of Laboratory Strains Facilitates Genetic Studies Anjana Srivatsan Yi Han Jianlan Peng Ashley Tehranchi Richard Gibbs Jue Wang Rui Chen doi:10.1371/journal.pgen.1000139 PLoS Genet, Vol. 4, No. 8. (2008), e1000139. 2008-08-04T09:00:39-00:00 2008 PLoS Genet 4 8 e1000139 Public Library of Science sequencing short_read_analysis http://www.citeulike.org/user/caseybrown/article/3082177 <i>PLoS Genet, Vol. 4, No. 8. (2008), e1000147.</i><br /><br />Quality control (QC) is a critical step in large-scale studies of genetic variation. While, on average, high-throughput single nucleotide polymorphism (SNP) genotyping assays are now very accurate, the errors that remain tend to cluster into a small percentage of “problem” SNPs, which exhibit unusually high error rates. Because most large-scale studies of genetic variation are searching for phenomena that are rare (e.g., SNPs associated with a phenotype), even this small percentage of problem SNPs can cause important practical problems. Here we describe and illustrate how patterns of linkage disequilibrium (LD) can be used to improve QC in large-scale, population-based studies. This approach has the advantage over existing filters (e.g., HWE or call rate) that it can actually reduce genotyping error rates by automatically correcting some genotyping errors. Applying this LD-based QC procedure to data from The International HapMap Project, we identify over 1,500 SNPs that likely have high error rates in the CHB and JPT samples and estimate corrected genotypes. Our method is implemented in the software package fastPHASE, available from the Stephens Lab website (http://stephenslab.uchicago.edu/software.html). Linkage Disequilibrium-Based Quality Control for Large-Scale Genetic Studies Paul Scheet Matthew Stephens doi:10.1371/journal.pgen.1000147 PLoS Genet, Vol. 4, No. 8. (2008), e1000147. 2008-08-04T19:15:44-00:00 2008 PLoS Genet 4 8 e1000147 Public Library of Science genotyping method qtl http://www.citeulike.org/user/caseybrown/article/3078073 <i>PNAS, Vol. 104, 3300.</i> Human polymorphism at microRNAs and microRNA target sites MA Saunders H Liang WH Li PNAS, Vol. 104, 3300. 2008-08-02T22:03:09-00:00 PNAS 104 3300 cisreg mirna molevol polymorphism http://www.citeulike.org/user/caseybrown/article/3078071 <i>Genes and Development, Vol. 21, No. 5., 578.</i> Dynamic regulation of miRNA expression in ordered stages of cellular development Neilson Genes and Development, Vol. 21, No. 5., 578. 2008-08-02T21:59:53-00:00 Genes and Development 21 5 578 cisreg mirna http://www.citeulike.org/user/caseybrown/article/1130487 <i>Science (22 February 2007)</i><br /><br />MicroRNAs (miRNAs) are ~22-nt RNAs that can pair to sites within mRNAs to specify posttranscriptional repression of these messages. Aberrant miRNA expression can contribute to tumorigenesis, but which of the many miRNA-target relationships are relevant to this process has been unclear. Here we report that chromosomal translocations previously associated with human tumors disrupt repression of High Mobility Group A2 (Hmga2) by let-7 miRNA. This disrupted repression promotes anchorage-independent growth, a characteristic of oncogenic transformation. Thus, losing miRNA-directed repression of an oncogene provides a mechanism for tumorigenesis, and disrupting a single miRNA-target interaction can produce an observable phenotype in mammalian cells. Disrupting the Pairing Between let-7 and Hmga2 Enhances Oncogenic Transformation. Christine Mayr Michael T Hemann David P Bartel doi:10.1126/science.1137999 Science (22 February 2007) 2007-02-28T17:09:52-00:00 2007 Science 1095-9203 cancer mirna http://www.citeulike.org/user/caseybrown/article/411468 <i>Science (24 November 2005)</i><br /><br />Thousands of mammalian mRNAs are under selective pressure to maintain 7-nucleotide sites matching microRNAs (miRNAs). We find that these conserved targets are often highly expressed at developmental stages prior to miRNA expression, and that their levels fall as the miRNA that targets them begins to accumulate. Nonconserved sites, which outnumber the conserved ten-to-one, also mediate repression. As a consequence, genes preferentially expressed at the same time and place as a miRNA have evolved to selectively avoid sites matching the miRNA. This phenomenon of selective avoidance extends to thousands of genes and enables spatial and temporal specificities of miRNAs to be revealed by finding tissues and developmental stages in which messages with corresponding sites are expressed at lower levels. The Widespread Impact of Mammalian MicroRNAs on mRNA Repression and Evolution. Kyle Kai-How Farh Andrew Grimson Calvin Jan Benjamin P Lewis Wendy K Johnston Lee P Lim Christopher B Burge David P Bartel doi:10.1126/science.1121158 Science (24 November 2005) 2005-11-29T22:03:55-00:00 2005 Science 1095-9203 cisreg mirna molevol http://www.citeulike.org/user/caseybrown/article/2746769 <i>Molecular biology and evolution (16 January 2008)</i><br /><br />A beneficial mutation which has nearly but not yet fixed in a population produces a characteristic haplotype configuration, called a partial selective sweep. Whether non-adaptive processes might generate similar haplotype configurations has not been previously explored. Here we consider five population genetic datasets taken from regions flanking high frequency transposable elements in North American strains of D. melanogaster, each of which appears to be consistent with the expectations of a partial selective sweep. We use coalescent simulations to explore whether incorporation of the species' demographic history, purifying selection against the element, or suppression of recombination caused by the element could generate putatively adaptive haplotype configurations. Where most of the datasets would be rejected as non-neutral under the standard neutral null model, only the dataset for which there is strong external evidence in support of an adaptive transposition appears to be non-neutral under the more complex null model, and in particular when demography is taken into account. High frequency, derived mutations from a recently-bottlenecked population, such as we study here, are of great interest to evolutionary genetics in the context of scans for adaptive events; we discuss the broader implications of our findings in this context. Nonadaptive explanations for signatures of partial selective sweeps in Drosophila. J Michael Macpherson Josefa González Daniela M Witten Jerel C Davis Noah A Rosenberg Aaron E Hirsh Dmitri A Petrov doi:10.1093/molbev/msn007 Molecular biology and evolution (16 January 2008) 2008-05-02T18:25:09-00:00 2008 Molecular biology and evolution 1537-1719 melanogaster molevol http://www.citeulike.org/user/caseybrown/article/1432454 <i>Cell, Vol. 129, No. 7. (29 June 2007), pp. 1401-1414.</i><br /><br />MicroRNAs (miRNAs) are small noncoding regulatory RNAs that reduce stability and/or translation of fully or partially sequence-complementary target mRNAs. In order to identify miRNAs and to assess their expression patterns, we sequenced over 250 small RNA libraries from 26 different organ systems and cell types of human and rodents that were enriched in neuronal as well as normal and malignant hematopoietic cells and tissues. We present expression profiles derived from clone count data and provide computational tools for their analysis. Unexpectedly, a relatively small set of miRNAs, many of which are ubiquitously expressed, account for most of the differences in miRNA profiles between cell lineages and tissues. This broad survey also provides detailed and accurate information about mature sequences, precursors, genome locations, maturation processes, inferred transcriptional units, and conservation patterns. We also propose a subclassification scheme for miRNAs for assisting future experimental and computational functional analyses. A Mammalian microRNA Expression Atlas Based on Small RNA Library Sequencing. P Landgraf M Rusu R Sheridan A Sewer N Iovino A Aravin S Pfeffer A Rice AO Kamphorst M Landthaler C Lin ND Socci L Hermida V Fulci S Chiaretti R Foà J Schliwka U Fuchs A Novosel RU Müller B Schermer U Bissels J Inman Q Phan M Chien DB Weir R Choksi G De Vita D Frezzetti HI Trompeter V Hornung G Teng G Hartmann M Palkovits R Di Lauro P Wernet G Macino CE Rogler JW Nagle J Ju FN Papavasiliou T Benzing P Lichter W Tam MJ Brownstein A Bosio A Borkhardt JJ Russo C Sander M Zavolan T Tuschl doi:10.1016/j.cell.2007.04.040 Cell, Vol. 129, No. 7. (29 June 2007), pp. 1401-1414. 2007-07-04T08:21:49-00:00 2007 Cell 0092-8674 129 7 1401 1414 mirna sequencing http://www.citeulike.org/user/caseybrown/article/2369506 <i>Trends in Genetics, Vol. In Press, Corrected Proof</i><br /><br />New DNA sequencing technologies can sequence up to one billion bases in a single day at low cost, putting large-scale sequencing within the reach of many scientists. Many researchers are forging ahead with projects to sequence a range of species using the new technologies. However, these new technologies produce read lengths as short as 35-40 nucleotides, posing challenges for genome assembly and annotation. Here we review the challenges and describe some of the bioinformatics systems that are being proposed to solve them. We specifically address issues arising from using these technologies in assembly projects, both de novo and for resequencing purposes, as well as efforts to improve genome annotation in the fragmented assemblies produced by short read lengths. Bioinformatics challenges of new sequencing technology Mihai Pop Steven Salzberg doi:10.1016/j.tig.2007.12.006 Trends in Genetics, Vol. In Press, Corrected Proof 2008-02-13T12:33:43-00:00 Trends in Genetics In Press, Corrected Proof sequencing short_read_analysis http://www.citeulike.org/user/caseybrown/article/2842939 <i>BMC Bioinformatics, Vol. 9, No. 1. (2008)</i><br /><br />BACKGROUND:Next-generation DNA sequencing technologies such as Illumina's Solexa platform and Roche's 454 approach provide new avenues for investigating genome-scale questions. However, they also present novel analytical challenges that must be met for their effective application to biological questions.RESULTS:Here we report the availability of tileQC, a tile-based quality control system for Solexa data written in the R language. TileQC provides a means of recognizing bias and error in Solexa output by graphically representing data generated by flow cell tiles. The data represented in the images is then made available in the R environment for further analysis and automation of error detection.CONCLUSIONS:TileQC offers a highly adaptable and powerful tool for the quality control of Solexa-based DNA sequence data. TileQC: a system for tile-based quality control of Solexa data Peter Dolan Dee Denver doi:10.1186/1471-2105-9-250 BMC Bioinformatics, Vol. 9, No. 1. (2008) 2008-05-29T00:13:46-00:00 2008 BMC Bioinformatics 9 1 method sequencing short_read_analysis http://www.citeulike.org/user/caseybrown/article/86487 <i>Nature, Vol. aop, No. current. (30 January 2005)</i> Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs Lee Lim Nelson Lau Philip Garrett-Engele Andrew Grimson Janell Schelter John Castle David Bartel Peter Linsley Jason Johnson doi:10.1038/nature03315 Nature, Vol. aop, No. current. (30 January 2005) 2005-01-31T21:29:42-00:00 2005 Nature 0028-0836 aop current Nature Publishing Group expression_array mirna http://www.citeulike.org/user/caseybrown/article/3064278 <i>Nature (30 July 2008)</i><br /><br />MicroRNAs are endogenous 23-nucleotide RNAs that can pair to sites in the messenger RNAs of protein-coding genes to downregulate the expression from these messages. MicroRNAs are known to influence the evolution and stability of many mRNAs, but their global impact on protein output had not been examined. Here we use quantitative mass spectrometry to measure the response of thousands of proteins after introducing microRNAs into cultured cells and after deleting mir-223 in mouse neutrophils. The identities of the responsive proteins indicate that targeting is primarily through seed-matched sites located within favourable predicted contexts in 3' untranslated regions. Hundreds of genes were directly repressed, albeit each to a modest degree, by individual microRNAs. Although some targets were repressed without detectable changes in mRNA levels, those translationally repressed by more than a third also displayed detectable mRNA destabilization, and, for the more highly repressed targets, mRNA destabilization usually comprised the major component of repression. The impact of microRNAs on the proteome indicated that for most interactions microRNAs act as rheostats to make fine-scale adjustments to protein output. The impact of microRNAs on protein output Daehyun Baek Judit Villén Chanseok Shin Fernando Camargo Steven Gygi David Bartel Nature (30 July 2008) 2008-07-30T22:22:19-00:00 2008 Nature expression_array mass_spec mirna mouse http://www.citeulike.org/user/caseybrown/article/3064275 <i>Nature (30 July 2008)</i><br /><br />Animal microRNAs (miRNAs) regulate gene expression by inhibiting translation and/or by inducing degradation of target messenger RNAs. It is unknown how much translational control is exerted by miRNAs on a genome-wide scale. We used a new proteomic approach to measure changes in synthesis of several thousand proteins in response to miRNA transfection or endogenous miRNA knockdown. In parallel, we quantified mRNA levels using microarrays. Here we show that a single miRNA can repress the production of hundreds of proteins, but that this repression is typically relatively mild. A number of known features of the miRNA-binding site such as the seed sequence also govern repression of human protein synthesis, and we report additional target sequence characteristics. We demonstrate that, in addition to downregulating mRNA levels, miRNAs also directly repress translation of hundreds of genes. Finally, our data suggest that a miRNA can, by direct or indirect effects, tune protein synthesis from thousands of genes. Widespread changes in protein synthesis induced by microRNAs Matthias Selbach Bjorn Schwanhausser Nadine Thierfelder Zhuo Fang Raya Khanin Nikolaus Rajewsky Nature (30 July 2008) 2008-07-30T22:18:35-00:00 2008 Nature expression_array mass_spec mirna http://www.citeulike.org/user/caseybrown/article/3057756 <i>Nucl. Acids Res. (26 July 2008), gkn425.</i><br /><br />Novel sequencing technologies permit the rapid production of large sequence data sets. These technologies are likely to revolutionize genetics and biomedical research, but a thorough characterization of the ultra-short read output is necessary. We generated and analyzed two Illumina 1G ultra-short read data sets, i.e. 2.8 million 27mer reads from a Beta vulgaris genomic clone and 12.3 million 36mers from the Helicobacter acinonychis genome. We found that error rates range from 0.3% at the beginning of reads to 3.8% at the end of reads. Wrong base calls are frequently preceded by base G. Base substitution error frequencies vary by 10- to 11-fold, with A > C transversion being among the most frequent and C > G transversions among the least frequent substitution errors. Insertions and deletions of single bases occur at very low rates. When simulating re-sequencing we found a 20-fold sequencing coverage to be sufficient to compensate errors by correct reads. The read coverage of the sequenced regions is biased; the highest read density was found in intervals with elevated GC content. High Solexa quality scores are over-optimistic and low scores underestimate the data quality. Our results show different types of biases and ways to detect them. Such biases have implications on the use and interpretation of Solexa data, for de novo sequencing, re-sequencing, the identification of single nucleotide polymorphisms and DNA methylation sites, as well as for transcriptome analysis. 10.1093/nar/gkn425 Substantial biases in ultra-short read data sets from high-throughput DNA sequencing Juliane Dohm Claudio Lottaz Tatiana Borodina Heinz Himmelbauer doi:10.1093/nar/gkn425 Nucl. Acids Res. (26 July 2008), gkn425. 2008-07-29T20:45:04-00:00 2008 Nucl. Acids Res. gkn425 method sequencing http://www.citeulike.org/user/caseybrown/article/3056726 <i>Nat Genet, Vol. 40, No. 8. (2008), pp. 977-986.</i> Dynamic transcriptome of Schizosaccharomyces pombe shown by RNA-DNA hybrid mapping Natalie Dutrow David Nix Derick Holt Brett Milash Brian Dalley Erick Westbroek Timothy Parnell Bradley Cairns doi:10.1038/ng.196 Nat Genet, Vol. 40, No. 8. (2008), pp. 977-986. 2008-07-29T13:08:44-00:00 2008 Nat Genet 40 8 977 986 Nature Publishing Group expression_array method yeast http://www.citeulike.org/user/caseybrown/article/2970487 <i>PLoS Genet, Vol. 4, No. 7. (4 July 2008), e1000113.</i><br /><br />The loss of functional redundancy is the key process in the evolution of duplicated genes. Here we systematically assess the extent of functional redundancy among a large set of duplicated genes in Saccharomyces cerevisiae. We quantify growth rate in rich medium for a large number of S. cerevisiae strains that carry single and double deletions of duplicated and singleton genes. We demonstrate that duplicated genes can maintain substantial redundancy for extensive periods of time following duplication (∼100 million years). We find high levels of redundancy among genes duplicated both via the whole genome duplication and via smaller scale duplications. Further, we see no evidence that two duplicated genes together contribute to fitness in rich medium substantially beyond that of their ancestral progenitor gene. We argue that duplicate genes do not often evolve to behave like singleton genes even after very long periods of time. Pervasive and Persistent Redundancy among Duplicated Genes in Yeast Jedediah Dean Jerel Davis Ronald Davis Dmitri Petrov doi:10.1371/journal.pgen.1000113 PLoS Genet, Vol. 4, No. 7. (4 July 2008), e1000113. 2008-07-07T16:01:56-00:00 2008 PLoS Genet 4 7 e1000113 Public Library of Science gene_duplication yeast http://www.citeulike.org/user/caseybrown/article/3043867 <i>Mammalian Genome, Vol. 17, No. 6. (1 June 2006), pp. 643-656.</i><br /><br />Abstract  Applying quantitative trait analysis methods to genome-wide microarray-derived mRNA expression phenotypes in segregating populations is a valuable tool in the attempt to link high-level traits to their molecular causes. The massive multiple-testing issues involved in analyzing these data make the correct level of confidence to place in mRNA abundance quantitative trait loci (QTL) a difficult problem. We use a unique resource to directly test mRNA abundance QTL replicability in mice: paired recombinant inbred (RI) and F2 data sets derived from C57BL/6J (B6) and DBA/2J (D2) inbred strains and phenotyped using the same Affymetrix arrays. We have one forebrain and one striatum data set pair. We describe QTL replication at varying stringencies in these data. For instance, 78% of mRNA expression QTL (eQTL) with genome-wide adjusted p ≤ 0.0001 in RI data replicate at a genome-wide adjusted p < 0.05 or better. Replicated QTL are disproportionately putatively cis-acting, and approximately 75% have higher apparent expression levels associated with B6 genotypes, which may be partly due to probe set generation using B6 sequence. Finally, we note that while trans-acting QTL do not replicate well between data sets in general, at least one cluster of trans-acting QTL on distal Chr 1 is notably preserved between data sets. How replicable are mRNA expression QTL? Jeremy Peirce Hongqiang Li Jintao Wang Kenneth Manly Robert Hitzemann John Belknap Glenn Rosen Shirlean Goodwin Thomas Sutter Robert Williams Lu Lu doi:10.1007/s00335-005-0187-8 Mammalian Genome, Vol. 17, No. 6. (1 June 2006), pp. 643-656. 2008-07-25T22:17:19-00:00 2006 Mammalian Genome 17 6 643 656 eqtl qtl_replication http://www.citeulike.org/user/caseybrown/article/1576927 <i>PLoS ONE, Vol. 2 (2007)</i><br /><br />Many investigations have reported the successful mapping of quantitative trait loci (QTLs) for gene expression phenotypes (eQTLs). Local eQTLs, where expression phenotypes map to the genes themselves, are of especially great interest, because they are direct candidates for previously mapped physiological QTLs. Here we show that many mapped local eQTLs in genetical genomics experiments do not reflect actual expression differences caused by sequence polymorphisms in cis-acting factors changing mRNA levels. Instead they indicate hybridization differences caused by sequence polymorphisms in the mRNA region that is targeted by the microarray probes. Many such polymorphisms can be detected by a sensitive and novel statistical approach that takes the individual probe signals into account. Applying this approach to recent mouse and human eQTL data, we demonstrate that indeed many local eQTLs are falsely reported as "cis-acting" or "cis" and can be successfully detected and eliminated with this approach. Sequence polymorphisms cause many false cis eQTLs. R Alberts P Terpstra Y Li R Breitling JP Nap RC Jansen doi:10.1371/journal.pone.0000622 PLoS ONE, Vol. 2 (2007) 2007-08-20T14:01:16-00:00 2007 PLoS ONE 1932-6203 2 eqtl polymorphism http://www.citeulike.org/user/caseybrown/article/2135581 <i>The Plant Journal, Vol. 53, No. 1. (January 2008), pp. 90-101.</i> Gene expression quantitative trait locus analysis of 16000 barley genes reveals a complex pattern of genome-wide transcriptional regulation Potokina Elena Druka Arnis Luo Zewei Wise Roger Waugh Robbie Kearsey Mike doi:10.1111/j.1365-313X.2007.03315.x The Plant Journal, Vol. 53, No. 1. (January 2008), pp. 90-101. 2007-12-17T09:26:28-00:00 2008 The Plant Journal 0960-7412 53 1 90 101 Blackwell Publishing barley eqtl http://www.citeulike.org/user/caseybrown/article/3043838 <i>Genetic Epidemiology, Vol. 31, No. S1. (2007), pp. S132-S138.</i><br /><br />Here, we summarize the contributions to group 16 of Genetic Analysis Workshop 15, held in Florida, U.S.A. The theme of this group was preprocessing of expression quantitative trait loci (eQTL) studies using the Affymetrix platform. The objective of the Genetic Analysis Workshop 15 problem 1 dataset was to use transcript levels that are measured using DNA microarrays as quantitative traits and localize the genes or other features of the DNA that control gene expression by quantitative trait loci linkage analyses. All contributors of this group used the microarray expression profiles (problem 1) data. Various approaches and questions were examined to investigate the effects of preprocessing methods and/or gene filtering on the interpretation of data, specifically on heritability estimates of gene expression and on linkage results. In addition, some contributors focused on the statistical issues involved in large-scale genetic analyses of quantitative traits that account for or build composite phenotypes from a large number of correlated traits. Since the true eQTLs are not known in the problem 1 data, results from the 11 studies cannot be fully evaluated for the methods employed. However, several common trends were found. All reports concluded that preprocessing statistical analyses may have an important impact on eQTL analyses and on the identification of cis-/trans-regulators and/or major biological pathways. Genet. Epidemiol. 31(Suppl. 1):S132-S138, 2007. © 2007 Wiley-Liss, Inc. Summary of contributions to GAW15 Group 16: Processing/normalization of expression traits Aurélie Labbe Jeanette Mcclintick Maria Martinez On doi:10.1002/gepi.20290 Genetic Epidemiology, Vol. 31, No. S1. (2007), pp. S132-S138. 2008-07-25T22:01:34-00:00 2007 Genetic Epidemiology 31 S1 S132 S138 eqtl expression_array method http://www.citeulike.org/user/caseybrown/article/3043837 <i>BMC Proceedings, Vol. 1, No. Suppl 1. (2007)</i><br /><br />We applied a simple and efficient two-step method to analyze a family-based association study of gene expression quantitative trait loci (eQTL) in a mixed model framework. This two-step method produces very similar results to the full mixed model method, with our method being significantly faster than the full model. Using the Genetic Analysis Workshop 15 (GAW15) Problem 1 data, we demonstrated the value of data filtering for reducing the number of tests and controlling the number of false positives. Specifically, we showed that removing non-expressed genes by filtering on expression variability effectively reduced the number of tests by nearly 50%. Furthermore, we demonstrated that filtering on genotype counts substantially reduced spurious detection. Finally, we restricted our analysis to the markers and transcripts that were closely located. We found five times more signals in close proximity (cis-) to transcripts than in our genome-wide analysis. Our results suggest that careful pre-filtering and partitioning of data are crucial for controlling false positives and allowing detection of genuine effects in genetic analysis of gene expression. Rapid and robust association mapping of expression quantitative trait loci Alex Lam Michael Schouten Yurii Aulchenko Chris Haley Dirk de Koning BMC Proceedings, Vol. 1, No. Suppl 1. (2007) 2008-07-25T22:00:21-00:00 2007 BMC Proceedings 1 Suppl 1 eqtl http://www.citeulike.org/user/caseybrown/article/3043834 <i>BMC Proceedings, Vol. 1, No. Suppl 1. (2007)</i><br /><br />We propose a method to perform linkage genome scans for many correlated traits in the Genetic Analysis Workshop 15 (GAW15) data. The proposed method has two steps: first, we use a clustering method to find the tight clusters of the traits and use the first principal component (PC) of the traits in each cluster to represent the cluster; second, we perform a linkage scan for each cluster by using the representative trait of the cluster. The results of applying the method to the GAW15 Problem 1 data indicate that most of the traits in the same cluster have the same regulators, and the representative trait measure, the first PC, can explain a large part of the total variation of all the traits in each cluster. Furthermore, considering one cluster of traits at a time may yield more linkage signals than considering traits individually. A method dealing with a large number of correlated traits in a linkage genome scan Tao Feng Shuanglin Zhang Qiuying Sha BMC Proceedings, Vol. 1, No. Suppl 1. (2007) 2008-07-25T21:54:28-00:00 2007 BMC Proceedings 1 Suppl 1 eqtl multivariate http://www.citeulike.org/user/caseybrown/article/3043833 <i>BMC Proceedings, Vol. 1, No. Suppl 1. (2007)</i><br /><br />The goal of this paper is to investigate the effect of using principal components as a data reduction method for expression data in linkage analysis. We used 45 probes normalized using the Affymetrix Global Scaling that had evidence of high heritability to estimate the first 10 principal components (PC). A genome-wide linkage scan was performed on the 45 expression values and the 10 PCs using 2272 single-nucleotide polymorphisms. Our conclusions were: 1) PC analyses under-performed the single-probe analysis for known signals; 2) the PC that best reproduced the single-probe analysis was primarily composed of that probe; 3) no new signals were detected in the PC analysis; 4) no new pleiotropic effects were detected in the PC analysis. Linkage analysis using principal components of gene expression data Elizabeth Atkinson Brooke Fridley Ellen Goode Shannon Mcdonnell Wen Mares Kari Rabe Zhifu Sun Susan Slager Mariza de Andrade BMC Proceedings, Vol. 1, No. Suppl 1. (2007) 2008-07-25T21:53:21-00:00 2007 BMC Proceedings 1 Suppl 1 eqtl multivariate http://www.citeulike.org/user/caseybrown/article/3043832 <i>BMC Proceedings, Vol. 1, No. Suppl 1. (2007)</i><br /><br />Performing linkage and association analyses on a large set of correlated data presents an interesting set of problems. In the current setting, we have 3554 expression levels from lymphoblastoid cell lines in 194 individuals from 14 three-generation Utah CEPH (Centre d'Etude du Polymorphisme Humain) pedigrees. We formed multivariate expression phenotypes from six sets of genes. These consisted of a set of genes identified by the data providers as showing common linkage to a region of chromosome 14, as well as five other sets suggested by ontological evidence. Using principal-component analyses, we generated seven quantitative phenotypes for expression levels from these six sets of genes. We performed quantitative genome linkage screens on these traits using the expression traits from the third generation of each pedigree. As expected, the strongest linkage signal was achieved when the trait under analysis was the composite of the expressions of genes previously showing linkage to chromosome 14. In particular, this trait produced a LOD score of 5.2 on chromosome 14. The trait also produced LOD scores over 3.5 on chromosomes 1, 7, 9, and 11; this suggests that these genes may be controlled by additional genetic factors on the genome. Subsequent association analyses on the first two generations of these pedigrees identified two polymorphisms on chromosome 11 as significant after correcting for multiple tests. These results suggest that principal-component analyses are useful for the analysis of pleiotropic loci. Furthermore, we have identified two single-nucleotide polymorphisms that may influence the expression of multiple genes linked to chromosome 14. Linkage and association analyses of principal components in expression data Anthony Hinrichs Robert Culverhouse Carol Jin Brian Suarez BMC Proceedings, Vol. 1, No. Suppl 1. (2007) 2008-07-25T21:50:39-00:00 2007 BMC Proceedings 1 Suppl 1 eqtl multivariate http://www.citeulike.org/user/caseybrown/article/3043829 <i>BMC Proceedings, Vol. 1, No. Suppl 1. (2007)</i><br /><br />We evaluate the impact of three pre-processing methods for Affymetrix microarray data on expression quantitative trait locus (eQTL) mapping, using 14 CEPH Utah families (GAW Problem 1 data). Different sets of expression traits were chosen according to different selection criteria: expression level, variance, and heritability. For each gene, three expression phenotypes were obtained by different pre-processing methods. Each quantitative phenotype was then submitted to a whole-genome scan, using multipoint variance component LODs. Pre-processing methods were compared with respect to their linkage outcomes (number of linkage signals with LODs greater than 3, consistencies in the location of the trait-specific linkage signals, and type of cis/trans-regulating loci). Overall, we found little agreement between linkage results from the different pre-processing methods: most of the linkage signals were specific to one pre-processing method. However, agreement rates varied according to the criteria used to select the traits. For instance, these rates were higher in the set of the most heritable traits. On the other hand, the pre-processing method had little impact on the relative proportion of detected cis and trans-regulating loci. Interestingly, although the number of detected cis-regulating loci was relatively small, pre-processing methods agreed much better in this set of linkage signals than in the trans-regulating loci. Several potential factors explaining the discordance observed between the methods are discussed. Impact of gene expression data pre-processing on expression quantitative trait locus mapping Aurelie Labbe Marie Roth Pierre Carmichael Maria Martinez BMC Proceedings, Vol. 1, No. Suppl 1. (2007) 2008-07-25T21:44:43-00:00 2007 BMC Proceedings 1 Suppl 1 eqtl expression_array http://www.citeulike.org/user/caseybrown/article/2967620 <i>Trends in Genetics, Vol. In Press, Corrected Proof</i><br /><br />Expression quantitative trait loci (eQTL) mapping studies have become a widely used tool for identifying genetic variants that affect gene regulation. In these studies, expression levels are viewed as quantitative traits, and gene expression phenotypes are mapped to particular genomic loci by combining studies of variation in gene expression patterns with genome-wide genotyping. Results from recent eQTL mapping studies have revealed substantial heritable variation in gene expression within and between populations. In many cases, genetic factors that influence gene expression levels can be mapped to proximal (putatively cis) eQTLs and, less often, to distal (putatively trans) eQTLs. Beyond providing great insight into the biology of gene regulation, a combination of eQTL studies with results from traditional linkage or association studies of human disease may help predict a specific regulatory role for polymorphic sites previously associated with disease. Revealing the architecture of gene regulation: the promise of eQTL studies Yoav Gilad Scott Rifkin Jonathan Pritchard doi:10.1016/j.tig.2008.06.001 Trends in Genetics, Vol. In Press, Corrected Proof 2008-07-06T17:45:41-00:00 Trends in Genetics In Press, Corrected Proof eqtl review http://www.citeulike.org/user/caseybrown/article/1157459 <i>BMC Genomics, Vol. 8 (12 March 2007), 69.</i> Genetical genomics: use all data Miguel Perez-Enciso Jose Quevedo Antonio Bahamonde doi:10.1186/1471-2164-8-69 BMC Genomics, Vol. 8 (12 March 2007), 69. 2007-03-13T04:01:18-00:00 2007 BMC Genomics 1471-2164 8 69 eqtl http://www.citeulike.org/user/caseybrown/article/1182081 <i>PLoS Genet, Vol. 3, No. 2. (23 February 2007)</i><br /><br />Functional genomics relies on two essential parameters: the sensitivity of phenotypic measures and the power to detect genomic perturbations that cause phenotypic variations. In model organisms, two types of perturbations are widely used. Artificial mutations can be introduced in virtually any gene and allow the systematic analysis of gene function via mutants fitness. Alternatively, natural genetic variations can be associated to particular phenotypes via genetic mapping. However, the access to genome manipulation and breeding provided by model organisms is sometimes counterbalanced by phenotyping limitations. Here we investigated the natural genetic diversity of Saccharomyces cerevisiae cellular morphology using a very sensitive high-throughput imaging platform. We quantified 501 morphological parameters in over 50,000 yeast cells from a cross between two wild-type divergent backgrounds. Extensive morphological differences were found between these backgrounds. The genetic architecture of the traits was complex, with evidence of both epistasis and transgressive segregation. We mapped quantitative trait loci (QTL) for 67 traits and discovered 364 correlations between traits segregation and inheritance of gene expression levels. We validated one QTL by the replacement of a single base in the genome. This study illustrates the natural diversity and complexity of cellular traits among natural yeast strains and provides an ideal framework for a genetical genomics dissection of multiple traits. Our results did not overlap with results previously obtained from systematic deletion strains, showing that both approaches are necessary for the functional exploration of genomes. Genetic complexity and quantitative trait loci mapping of yeast morphological traits. S Nogami Y Ohya G Yvert doi:10.1371/journal.pgen.0030031 PLoS Genet, Vol. 3, No. 2. (23 February 2007) 2007-03-23T19:25:03-00:00 2007 PLoS Genet 1553-7404 3 2 eqtl qtl yeast http://www.citeulike.org/user/caseybrown/article/446169 <i>Nature, Vol. 430, No. 7001. (12 August 2004), pp. 743-747.</i><br /><br />Natural variation in gene expression is extensive in humans and other organisms, and variation in the baseline expression level of many genes has a heritable component. To localize the genetic determinants of these quantitative traits (expression phenotypes) in humans, we used microarrays to measure gene expression levels and performed genome-wide linkage analysis for expression levels of 3,554 genes in 14 large families. For approximately 1,000 expression phenotypes, there was significant evidence of linkage to specific chromosomal regions. Both cis- and trans-acting loci regulate variation in the expression levels of genes, although most act in trans. Many gene expression phenotypes are influenced by several genetic determinants. Furthermore, we found hotspots of transcriptional regulation where significant evidence of linkage for several expression phenotypes (up to 31) coincides, and expression levels of many genes that share the same regulatory region are significantly correlated. The combination of microarray techniques for phenotyping and linkage analysis for quantitative traits allows the genetic mapping of determinants that contribute to variation in human gene expression. Genetic analysis of genome-wide variation in human gene expression. M Morley CM Molony TM Weber JL Devlin KG Ewens RS Spielman VG Cheung doi:10.1038/nature02797 Nature, Vol. 430, No. 7001. (12 August 2004), pp. 743-747. 2005-12-21T12:19:34-00:00 2004 Nature 1476-4687 430 7001 743 747 eqtl http://www.citeulike.org/user/caseybrown/article/3043599 <i>BMC Genomics, Vol. 7, No. 1. (2006)</i><br /><br />BACKGROUND:Correlations between polymorphic markers and observed phenotypes provide the basis for mapping traits in quantitative genetics. When the phenotype is gene expression, then loci involved in regulatory control can theoretically be implicated. Recent efforts to construct gene regulatory networks from genotype and gene expression data have shown that biologically relevant networks can be achieved from an integrative approach. In this paper, we consider the problem of identifying individual pairs of genes in a direct or indirect, causal, trans-acting relationship.RESULTS:Inspired by epistatic models of multi-locus quantitative trait (QTL) mapping, we propose a unified model of expression and genotype to identify quantitative trait genes (QTG) by extending the conventional linear model to include both genotype and expression of regulator genes and their interactions. The model provides mapping of specific genes in contrast to standard linkage approaches that implicate large QTL intervals typically containing tens of genes. In simulations, we found that the method can often detect weak trans-acting regulators amid the background noise of thousands of traits and is robust to transcription models containing multiple regulator genes. We reanalyze several pleiotropic loci derived from a large set of yeast matings and identify a likely alternative regulator not previously published. However, we also found that many regulators can not be so easily mapped due to the presence of cis-acting QTLs on the regulators, which induce close linkage among small neighborhoods of genes. QTG mapped regulator-target pairs linked to ARN1 were combined to form a regulatory module, which we observed to be highly enriched in iron homeostasis related genes and contained several causally directed links that had not been identified in other automatic reconstructions of that regulatory module. Finally, we also confirm the surprising, previously published results that regulators controlling gene expression are not enriched for transcription factors, but we do show that our more precise mapping model reveals functional enrichment for several other biological processes related to the regulation of the cell.CONCLUSION:By incorporating interacting expression and genotype, our QTG mapping method can identify specific regulator genes in contrast to standard QTL interval mapping. We have shown that the method can recover biologically significant regulator-target pairs and the approach leads to a general framework for inducing a regulatory module network topology of directed and undirected edges that can be used to identify leads in pathway analysis. Causal inference of regulator-target pairs by gene mapping of expression phenotypes David Kulp Manjunatha Jagalur doi:10.1186/1471-2164-7-125 BMC Genomics, Vol. 7, No. 1. (2006) 2008-07-25T20:02:40-00:00 2006 BMC Genomics 7 1 eqtl http://www.citeulike.org/user/caseybrown/article/2824834 <i>BMC Genomics, Vol. 9, No. 1. (2008)</i><br /><br />BACKGROUND:Many studies have shown that the abundance level of gene expression is heritable. Analogous to the traditional genetic study, most researchers treat the expression of one gene as a quantitative trait and map it to expression quantitative trait loci (eQTL). This is 1D-trait mapping. 1D-trait mapping ignores the trait-trait interaction completely, which is a major shortcoming. RESULTS:To overcome this limitation, we study the expression of a pair of genes and treat the variation in their co-expression pattern as a two dimensional quantitative trait. We develop a method to find gene pairs, whose co-expression patterns, including both signs and strengths, are mediated by genetic variations and map these 2D-traits to the corresponding genetic loci. We report several applications by combining 1D-trait mapping with 2D-trait mapping, including the contribution of genetic variations to the perturbations in the regulatory mechanisms of yeast metabolic pathways.CONCLUSIONS:Our approach of 2D-trait mapping provides a novel and effective way to connect genetic variations with higher order biological modules via gene expression profiles. Trait-trait dynamic interaction: 2D-trait eQTL mapping for genetic variation study Wei Sun Shinsheng Yuan Ker Li doi:10.1186/1471-2164-9-242 BMC Genomics, Vol. 9, No. 1. (2008) 2008-05-23T09:50:07-00:00 2008 BMC Genomics 9 1 eqtl multivariate yeast http://www.citeulike.org/user/caseybrown/article/2515087 <i>Am J Hum Genet, Vol. 81, No. 3. (September 2007), pp. 427-437.</i><br /><br />Cisplatin, a platinating agent commonly used to treat several cancers, is associated with nephrotoxicity, neurotoxicity, and ototoxicity, which has hindered its utility. To gain a better understanding of the genetic variants associated with cisplatin-induced toxicity, we present a stepwise approach integrating genotypes, gene expression, and sensitivity of HapMap cell lines to cisplatin. Cell lines derived from 30 trios of European descent (CEU) and 30 trios of African descent (YRI) were used to develop a preclinical model to identify genetic variants and gene expression that contribute to cisplatin-induced cytotoxicity in two different populations. Cytotoxicity was determined as cell-growth inhibition at increasing concentrations of cisplatin for 48 h. Gene expression in 176 HapMap cell lines (87 CEU and 89 YRI) was determined using the Affymetrix GeneChip Human Exon 1.0 ST Array. We identified six, two, and nine representative SNPs that contribute to cisplatin-induced cytotoxicity through their effects on 8, 2, and 16 gene expressions in the combined, Centre d'Etude du Polymorphisme Humain (CEPH), and Yoruban populations, respectively. These genetic variants contribute to 27%, 29%, and 45% of the overall variation in cell sensitivity to cisplatin in the combined, CEPH, and Yoruban populations, respectively. Our whole-genome approach can be used to elucidate the expression of quantitative trait loci contributing to a wide range of cellular phenotypes. Identification of genetic variants contributing to cisplatin-induced cytotoxicity by use of a genomewide approach. RS Huang S Duan SJ Shukla EO Kistner TA Clark TX Chen AC Schweitzer JE Blume ME Dolan doi:10.1086/519850 Am J Hum Genet, Vol. 81, No. 3. (September 2007), pp. 427-437. 2008-03-11T14:14:00-00:00 2007 Am J Hum Genet 0002-9297 81 3 427 437 eqtl pharmacogenetics http://www.citeulike.org/user/caseybrown/article/2795023 <i>PLoS genetics, Vol. 4, No. 5. (May 2008)</i><br /><br />There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts - cis effects, and elsewhere in the genome - trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8x10(-57)), CCL4L1 (p = 3.9x10(-21)), IL18 (p = 6.8x10(-13)), LPA (p = 4.4x10(-10)), GGT1 (p = 1.5x10(-7)), SHBG (p = 3.1x10(-7)), CRP (p = 6.4x10(-6)) and IL1RN (p = 7.3x10(-6)) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8x10(-40)), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways. A genome-wide association study identifies protein quantitative trait loci (pQTLs). D Melzer JR Perry D Hernandez AM Corsi K Stevens I Rafferty F Lauretani A Murray JR Gibbs G Paolisso S Rafiq J Simon-Sanchez H Lango S Scholz MN Weedon S Arepalli N Rice N Washecka A Hurst A Britton W Henley J van de Leemput R Li AB Newman G Tranah T Harris V Panicker C Dayan A Bennett MI McCarthy A Ruokonen MR Jarvelin J Guralnik S Bandinelli TM Frayling A Singleton L Ferrucci doi:10.1371/journal.pgen.1000072 PLoS genetics, Vol. 4, No. 5. (May 2008) 2008-05-13T13:37:36-00:00 2008 PLoS genetics 1553-7404 4 5 eqtl metabolism http://www.citeulike.org/user/caseybrown/article/3043368 <i>Genetics, Vol. 157, No. 4. (1 April 2001), pp. 1789-1803.</i><br /><br />An approach to increase the efficiency of mapping quantitative trait loci (QTL) was proposed earlier by the authors on the basis of bivariate analysis of correlated traits. The power of QTL detection using the log-likelihood ratio (LOD scores) grows proportionally to the broad sense heritability. We found that this relationship holds also for correlated traits, so that an increased bivariate heritability implicates a higher LOD score, higher detection power, and better mapping resolution. However, the increased number of parameters to be estimated complicates the application of this approach when a large number of traits are considered simultaneously. Here we present a multivariate generalization of our previous two-trait QTL analysis. The proposed multivariate analogue of QTL contribution to the broad-sense heritability based on interval-specific calculation of eigenvalues and eigenvectors of the residual covariance matrix allows prediction of the expected QTL detection power and mapping resolution for any subset of the initial multivariate trait complex. Permutation technique allows chromosome-wise testing of significance for the whole trait complex and the significance of the contribution of individual traits owing to: (a) their correlation with other traits, (b) dependence on the chromosome in question, and (c) both a and b. An example of application of the proposed method on a real data set of 11 traits from an experiment performed on an F2/F3 mapping population of tetraploid wheat (Triticum durum x T. dicoccoides) is provided. Enhanced Efficiency of Quantitative Trait Loci Mapping Analysis Based on Multivariate Complexes of Quantitative Traits Abraham Korol Yefim Ronin Alexander Itskovich Junhua Peng Eviatar Nevo Genetics, Vol. 157, No. 4. (1 April 2001), pp. 1789-1803. 2008-07-25T18:02:54-00:00 2001 Genetics 157 4 1789 1803 multivariate qtl http://www.citeulike.org/user/caseybrown/article/3043349 <i>J. Anim Sci., Vol. 83, No. 11. (1 November 2005), pp. 2471-2481.</i><br /><br />The merits of complementary multivariate techniques to identify QTL associated with multiple traits were evaluated. Records from 806 F2 pigs pertaining to a Berkshire x Duroc three-generation population were available. Six multitrait groups on SSC 2, 6, 13, and 18 with information on 30 markers were studied. Multivariate techniques studied included multivariate models and principal components analysis of each multitrait group. All models included, in addition to systematic effects, additive, dominance, and imprinting coefficients corresponding to a one-QTL model and a random family effect. Multivariate analysis identified QTL associated with genomewise significant variation in four of the multitrait groups. The majority of the multivariate analysis provided greater precision of parameter estimates and higher statistical significance in some cases than univariate approaches, because of the greater parameterization of the multivariate models and moderate information content of the data. Principal component analysis results were consistent with univariate and multivariate analyses and recovered the levels of statistical significance observed in univariate analyses on the original data. In addition, principal component analysis was able to provide a location associated with LM area not detected by other analyses. The relative advantage of multivariate over the univariate approaches varied with the level of genetic covariance between traits because of the modeled QTL effect and information contained in the data; however, multivariate approaches have the unique capability to identify pleiotropic effects or multiple linked QTL. Evaluation of approaches to detect quantitative trait loci for growth, carcass, and meat quality on swine chromosomes 2, 6, 13, and 18. II. Multivariate and principal component analyses TM Stearns JE Beever BR Southey M Ellis FK Mckeith SL Rodriguez-Zas J. Anim Sci., Vol. 83, No. 11. (1 November 2005), pp. 2471-2481. 2008-07-25T17:52:41-00:00 2005 J. Anim Sci. 83 11 2471 2481 multivariate qtl http://www.citeulike.org/user/caseybrown/article/2985765 <i>Nature (09 July 2008)</i> High-resolution mapping of meiotic crossovers and non-crossovers in yeast Eugenio Mancera Richard Bourgon Alessandro Brozzi Wolfgang Huber Lars Steinmetz doi:10.1038/nature07135 Nature (09 July 2008) 2008-07-10T18:32:00-00:00 2008 Nature 0028-0836 Nature Publishing Group genetics yeast http://www.citeulike.org/user/caseybrown/article/1579788 <i>Genetics (29 July 2007), genetics.107.071407.</i><br /><br />In 2001, Sen and Churchill reported a general framework for quantitative trait loci (QTL) mapping in inbred line crosses. The framework is a powerful one, as many QTL mapping methods can be represented as special cases and many important considerations are accommodated. These considerations include accounting for covariates, nonstandard crosses,missing genotypes, genotyping errors, multiple interacting QTL, and nonnormal as well as multivariate phenotypes. The dimension of a multivariate phenotype easily handled within the framework is bounded by the number of subjects, as a full rank covariance matrix describing correlations across the phenotypes is required. We address this limitation and extend the Sen-Churchill framework to accommodate expression quantitative trait loci (eQTL) mapping studies, where high-dimensional gene expression phenotypes are obtained via microarrays. Doing so allows for the precise comparison of existing eQTL mapping approaches and facilitates the development of an eQTL interval mapping approach that shares information across transcripts and improves localization of eQTL. Evaluations are based on simulation studies and a study of diabetes in mouse. 10.1534/genetics.107.071407 A Statistical Framework for Expression Quantitative Trait Loci (eQTL) Mapping Meng Chen Christina Kendziorski doi:10.1534/genetics.107.071407 Genetics (29 July 2007), genetics.107.071407. 2007-08-21T11:22:15-00:00 2007 Genetics genetics.107.071407 eqtl http://www.citeulike.org/user/caseybrown/article/3014359 <i>(3 March 2008)</i><br /><br />Imputation-based association methods provide a powerful framework for testing un- typed variants for association with phenotype, and for combining results from multiple studies that use different genotyping platforms. Here we consider several issues that arise when applying these methods in practice, including i) factors affecting imputation accuracy, including choice of reference panel; ii) the effects of imputation accuracy on power to detect associations; iii) the importance, or otherwise, of taking into account uncertainty of imputed genotypes; and iv) the relative merits of different approaches to testing imputed genotypes for association with phenotype. We find that small changes in imputation accuracy tend to produce small changes in power to detect associations, but that the method used to test imputed genotypes can have a larger affect. In par- ticular we find, and explain reasons for, the advantages of a Bayesian approach over the conventional likelihood ratio statistic. Within the Bayesian framework we find that good approximations to a full analysis can be achieved by simply replacing unknown genotypes with a point estimate, their posterior mean. This approximation consid- erably reduces computational expense, and the methods we present are practical on a genome-wide scale with very modest computational resources (e.g. a single desktop computer). The accuracy of this approximation also has helpful implications for com- bining information across studies in situations where only single SNP summary data can be easily shared. Methods discussed here are implemented in the software package BIMBAM, available from http://stephenslab.uchicago.edu/software.html Practical Issues in Imputation-Based Association Mapping Yongtao Guan Matthew Stephens (3 March 2008) 2008-07-17T13:40:44-00:00 2008 qtl http://www.citeulike.org/user/caseybrown/article/3014266 <i>RECOMB (2008)</i><br /><br />The recent availability of large scale data sets profiling sin- gle nucleotide polymorphisms (SNPs) and gene expression across differ- ent human populations, has directed much attention towards discovering patterns of genetic variation and their association with gene regulation. The influence of environmental, developmental and other factors on gene expression can obscure such associations. We present a model that ex- plicitly accounts for non-genetic factors so as to improve significantly the power of an expression Quantitative Trait Loci (eQTL) study. Our method also exploits the inherent block structure of haplotype data to further enhance its sensitivity. On data from the HapMap pro ject, we find more than three times as many significant associations than a stan- dard eQTL method. Accounting for Non-Genetic Factors Improves the Power of eQTL Studies Oliver Stegle Anitha Kanna Richard Durbin John Winn RECOMB (2008) 2008-07-17T12:33:27-00:00 2008 RECOMB eqtl http://www.citeulike.org/user/caseybrown/article/1030375 <i>Nat Biotech, Vol. 25, No. 1. (February 2007), pp. 117-124.</i> Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation Peng Lu Christine Vogel Rong Wang Xin Yao Edward Marcotte doi:10.1038/nbt1270 Nat Biotech, Vol. 25, No. 1. (February 2007), pp. 117-124. 2007-01-08T20:50:52-00:00 2007 Nat Biotech 25 1 117 124 ecoli transcription translation http://www.citeulike.org/user/caseybrown/article/1150091 <i>Mol. Cell. Biol., Vol. 19, No. 3. (1 March 1999), pp. 1720-1730.</i><br /><br />We have determined the relationship between mRNA and protein expression levels for selected genes expressed in the yeast Saccharomyces cerevisiae growing at mid-log phase. The proteins contained in total yeast cell lysate were separated by high-resolution two-dimensional (2D) gel electrophoresis. Over 150 protein spots were excised and identified by capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS). Protein spots were quantified by metabolic labeling and scintillation counting. Corresponding mRNA levels were calculated from serial analysis of gene expression (SAGE) frequency tables (V. E. Velculescu, L. Zhang, W. Zhou, J. Vogelstein, M. A. Basrai, D. E. Bassett, Jr., P. Hieter, B. Vogelstein, and K. W. Kinzler, Cell 88:243-251, 1997). We found that the correlation between mRNA and protein levels was insufficient to predict protein expression levels from quantitative mRNA data. Indeed, for some genes, while the mRNA levels were of the same value the protein levels varied by more than 20-fold. Conversely, invariant steady-state levels of certain proteins were observed with respective mRNA transcript levels that varied by as much as 30-fold. Another interesting observation is that codon bias is not a predictor of either protein or mRNA levels. Our results clearly delineate the technical boundaries of current approaches for quantitative analysis of protein expression and reveal that simple deduction from mRNA transcript analysis is insufficient. Correlation between Protein and mRNA Abundance in Yeast Steven Gygi Yvan Rochon Robert Franza Ruedi Aebersold Mol. Cell. Biol., Vol. 19, No. 3. (1 March 1999), pp. 1720-1730. 2007-03-08T23:46:52-00:00 1999 Mol. Cell. Biol. 19 3 1720 1730 transcription translation yeast http://www.citeulike.org/user/caseybrown/article/1994824 <i>Genome Res. (21 November 2007), gr.6984908.</i><br /><br />Massively parallel sequencing holds great promise for expression profiling, as it combines the high throughput of SAGE with the accuracy of EST sequencing. Nevertheless, until now only very limited information had been available on the suitability of the current technology to meet the requirements. Here, we evaluate the potential of 454 sequencing technology for expression profiling using Drosophila melanogaster. We show that short (< [~]80 bp) and long (> [~]300400 bp) cDNA fragments are under-represented in 454 sequence reads. Nevertheless, sequencing of 3' cDNA fragments generated by nebulization could be used to overcome the length bias of the 454 sequencing technology. Gene expression measurements generated by restriction analysis and nebulization for fragments within the 80- to 300-bp range showed correlations similar to those reported for replicated microarray experiments (0.830.91); 97% of the cDNA fragments could be unambiguously mapped to the genomic DNA, demonstrating the advantage of longer sequence reads. Our analyses suggest that the 454 technology has a large potential for expression profiling, and the high mapping accuracy indicates that it should be possible to compare expression profiles across species. 10.1101/gr.6984908 Gene expression profiling by massively parallel sequencing Tatiana Torres Muralidhar Metta Birgit Ottenwalder Christian Schlotterer doi:10.1101/gr.6984908 Genome Res. (21 November 2007), gr.6984908. 2007-11-27T16:15:35-00:00 2007 Genome Res. gr.6984908 454 rna_seq sequencing transcription http://www.citeulike.org/user/caseybrown/article/2972799 <i>Trends in Genetics, Vol. 24, No. 7. (July 2008), pp. 319-323.</i><br /><br />We compared the transcription regulatory interactions inferred from three high-throughput methods. Because these methods use different principles, they have few interactions in common, suggesting they capture distinct facets of the transcription regulatory program. We show that these methods uncover disparate biological phenomena: long-range interactions between telomeres and transcription factors, downstream effects of interference with ribosome biogenesis and a protein-aggregation response. Through a detailed analysis of the latter, we predict components of the system responding to protein-aggregation stress. Comparison of transcription regulatory interactions inferred from high-throughput methods: what do they reveal? S Balaji Lakshminarayan Iyer Madan Babu L Aravind doi:10.1016/j.tig.2008.04.006 Trends in Genetics, Vol. 24, No. 7. (July 2008), pp. 319-323. 2008-07-08T15:17:34-00:00 2008 Trends in Genetics 24 7 319 323 network review transcription http://www.citeulike.org/user/caseybrown/article/2883810 <i>Genome Res. (11 June 2008), gr.079558.108.</i><br /><br />Ultra high-throughput sequencing is emerging as an attractive alternative to microarrays for genotyping, analysis of methylation patterns and identification of transcription factor binding sites. Here, we describe an application of the Illumina sequencing platform to study mRNA expression levels. Our goals were to estimate technical variance associated with Illumina sequencing in this context and to compare its ability to identify differentially expressed genes with existing array technologies. To do so, we estimated gene expression differences between liver and kidney RNA samples using multiple sequencing replicates, and compared the sequencing data to results obtained from Affymetrix arrays using the same RNA samples. We find that the Illumina sequencing data are highly replicable, with relatively little technical variation, and so, for many purposes, it may suffice to sequence each mRNA sample only once (i.e., using one lane). The information in a single lane of Illumina sequencing data appears comparable to that in a single array in enabling identification of differentially expressed genes, while allowing for additional analyses such as detection of low-expressed genes, alternative splice variants, and novel transcripts. Based on our observations, we propose an empirical protocol and a statistical framework for the analysis of gene expression using ultra high-throughput sequencing technology. 10.1101/gr.079558.108 RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays John Marioni Cristopher Mason Shrikant Mane Matthew Stephens Yoav Gilad doi:10.1101/gr.079558.108 Genome Res. (11 June 2008), gr.079558.108. 2008-06-11T20:56:53-00:00 2008 Genome Res. gr.079558.108 method rna_seq sequencing transcription http://www.citeulike.org/user/caseybrown/article/2811350 <i>Nature (18 May 2008)</i> Dynamic repertoire of a eukaryotic transcriptome surveyed at single-nucleotide resolution Brian Wilhelm Samuel Marguerat Stephen Watt Falk Schubert Valerie Wood Ian Goodhead Christopher Penkett Jane Rogers Jürg Bähler doi:10.1038/nature07002 Nature (18 May 2008) 2008-05-19T01:16:04-00:00 2008 Nature 0028-0836 Nature Publishing Group rna_seq sequencing transcription yeast http://www.citeulike.org/user/caseybrown/article/2857485 <i>Cell, Vol. 133, No. 3. (2 May 2008), pp. 523-536.</i><br /><br />Summary Deciphering the multiple layers of epigenetic regulation that control transcription is critical to understanding how plants develop and respond to their environment. Using sequencing-by-synthesis technology we directly sequenced the cytosine methylome (methylC-seq), transcriptome (mRNA-seq), and small RNA transcriptome (smRNA-seq) to generate highly integrated epigenome maps for wild-type Arabidopsis thaliana and mutants defective in DNA methyltransferase or demethylase activity. At single-base resolution we discovered extensive, previously undetected DNA methylation, identified the context and level of methylation at each site, and observed local sequence effects upon methylation state. Deep sequencing of smRNAs revealed a direct relationship between the location of smRNAs and DNA methylation, perturbation of smRNA biogenesis upon loss of CpG DNA methylation, and a tendency for smRNAs to direct strand-specific DNA methylation in regions of RNA-DNA homology. Finally, strand-specific mRNA-seq revealed altered transcript abundance of hundreds of genes, transposons, and unannotated intergenic transcripts upon modification of the DNA methylation state. Highly Integrated Single-Base Resolution Maps of the Epigenome in Arabidopsis Ryan Lister Ronan O'Malley Julian Tonti-Filippini Brian Gregory Charles Berry Harvey Millar Joseph Ecker doi:10.1016/j.cell.2008.03.029 Cell, Vol. 133, No. 3. (2 May 2008), pp. 523-536. 2008-06-02T16:18:04-00:00 2008 Cell 133 3 523 536 arabidopsis rna_seq sequencing transcription http://www.citeulike.org/user/caseybrown/article/2860398 <i>Nature methods (30 May 2008)</i><br /><br />We have mapped and quantified mouse transcriptomes by deeply sequencing them and recording how frequently each gene is represented in the sequence sample (RNA-Seq). This provides a digital measure of the presence and prevalence of transcripts from known and previously unknown genes. We report reference measurements composed of 41-52 million mapped 25-base-pair reads for poly(A)-selected RNA from adult mouse brain, liver and skeletal muscle tissues. We used RNA standards to quantify transcript prevalence and to test the linear range of transcript detection, which spanned five orders of magnitude. Although >90% of uniquely mapped reads fell within known exons, the remaining data suggest new and revised gene models, including changed or additional promoters, exons and 3' untranscribed regions, as well as new candidate microRNA precursors. RNA splice events, which are not readily measured by standard gene expression microarray or serial analysis of gene expression methods, were detected directly by mapping splice-crossing sequence reads. We observed 1.45 x 10(5) distinct splices, and alternative splices were prominent, with 3,500 different genes expressing one or more alternate internal splices. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Ali Mortazavi Brian A Williams Kenneth McCue Lorian Schaeffer Barbara Wold doi:10.1038/nmeth.1226 Nature methods (30 May 2008) 2008-06-04T06:59:21-00:00 2008 Nature methods 1548-7105 rna_seq sequencing solid transcription http://www.citeulike.org/user/caseybrown/article/2927415 <i>Nature methods (30 May 2008)</i><br /><br />We developed a massive-scale RNA sequencing protocol, short quantitative random RNA libraries or SQRL, to survey the complexity, dynamics and sequence content of transcriptomes in a near-complete fashion. This method generates directional, random-primed, linear cDNA libraries that are optimized for next-generation short-tag sequencing. We surveyed the poly(A)(+) transcriptomes of undifferentiated mouse embryonic stem cells (ESCs) and embryoid bodies (EBs) at an unprecedented depth (10 Gb), using the Applied Biosystems SOLiD technology. These libraries capture the genomic landscape of expression, state-specific expression, single-nucleotide polymorphisms (SNPs), the transcriptional activity of repeat elements, and both known and new alternative splicing events. We investigated the impact of transcriptional complexity on current models of key signaling pathways controlling ESC pluripotency and differentiation, highlighting how SQRL can be used to characterize transcriptome content and dynamics in a quantitative and reproducible manner, and suggesting that our understanding of transcriptional complexity is far from complete. Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nicole Cloonan Alistair R R Forrest Gabriel Kolle Brooke B A Gardiner Geoffrey J Faulkner Mellissa K Brown Darrin F Taylor Anita L Steptoe Shivangi Wani Graeme Bethel Alan J Robertson Andrew C Perkins Stephen J Bruce Clarence C Lee Swati S Ranade Heather E Peckham Jonathan M Manning Kevin J McKernan Sean M Grimmond doi:10.1038/nmeth.1223 Nature methods (30 May 2008) 2008-06-25T20:30:50-00:00 2008 Nature methods 1548-7105 rna_seq sequencing stem_cell transcription http://www.citeulike.org/user/caseybrown/article/2913169 <i>Genome Biology, Vol. 9 (20 June 2008), R100.</i> Gene expression response in target organ and whole blood varies as a function of target organ injury phenotype Edward Lobenhofer Todd Auman Pamela Blackshear Gary Boorman Pierre Bushel Michael Cunningham Jennifer Fostel Kevin Gerrish Alexandra Heinloth Richard Irwin David Malarkey Alex Merrick Stella Sieber Charles Tucker Sandra Ward Ralph Wilson Patrick Hurban Raymond Tennant Richard Paules doi:10.1186/gb-2008-9-6-r100 Genome Biology, Vol. 9 (20 June 2008), R100. 2008-06-21T09:41:11-00:00 2008 Genome Biology 1465-6906 9 R100 liver metabolism rat http://www.citeulike.org/user/caseybrown/article/2932009 <i>Nat Genet, Vol. 40, No. 7. (July 2008), pp. 897-903.</i> Combinatorial patterns of histone acetylations and methylations in the human genome Zhibin Wang Chongzhi Zang Jeffrey Rosenfeld Dustin Schones Artem Barski Suresh Cuddapah Kairong Cui Tae-Young Roh Weiqun Peng Michael Zhang Keji Zhao doi:10.1038/ng.154 Nat Genet, Vol. 40, No. 7. (July 2008), pp. 897-903. 2008-06-26T19:38:09-00:00 2008 Nat Genet 40 7 897 903 Nature Publishing Group chromatin histone_modification