66,506 research outputs found

    RNA-Seq optimization with eQTL gold standards.

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    BackgroundRNA-Sequencing (RNA-Seq) experiments have been optimized for library preparation, mapping, and gene expression estimation. These methods, however, have revealed weaknesses in the next stages of analysis of differential expression, with results sensitive to systematic sample stratification or, in more extreme cases, to outliers. Further, a method to assess normalization and adjustment measures imposed on the data is lacking.ResultsTo address these issues, we utilize previously published eQTLs as a novel gold standard at the center of a framework that integrates DNA genotypes and RNA-Seq data to optimize analysis and aid in the understanding of genetic variation and gene expression. After detecting sample contamination and sequencing outliers in RNA-Seq data, a set of previously published brain eQTLs was used to determine if sample outlier removal was appropriate. Improved replication of known eQTLs supported removal of these samples in downstream analyses. eQTL replication was further employed to assess normalization methods, covariate inclusion, and gene annotation. This method was validated in an independent RNA-Seq blood data set from the GTEx project and a tissue-appropriate set of eQTLs. eQTL replication in both data sets highlights the necessity of accounting for unknown covariates in RNA-Seq data analysis.ConclusionAs each RNA-Seq experiment is unique with its own experiment-specific limitations, we offer an easily-implementable method that uses the replication of known eQTLs to guide each step in one's data analysis pipeline. In the two data sets presented herein, we highlight not only the necessity of careful outlier detection but also the need to account for unknown covariates in RNA-Seq experiments

    Targeted mutagenesis in a human-parasitic nematode.

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    Parasitic nematodes infect over 1 billion people worldwide and cause some of the most common neglected tropical diseases. Despite their prevalence, our understanding of the biology of parasitic nematodes has been limited by the lack of tools for genetic intervention. In particular, it has not yet been possible to generate targeted gene disruptions and mutant phenotypes in any parasitic nematode. Here, we report the development of a method for introducing CRISPR-Cas9-mediated gene disruptions in the human-parasitic threadworm Strongyloides stercoralis. We disrupted the S. stercoralis twitchin gene unc-22, resulting in nematodes with severe motility defects. Ss-unc-22 mutations were resolved by homology-directed repair when a repair template was provided. Omission of a repair template resulted in deletions at the target locus. Ss-unc-22 mutations were heritable; we passed Ss-unc-22 mutants through a host and successfully recovered mutant progeny. Using a similar approach, we also disrupted the unc-22 gene of the rat-parasitic nematode Strongyloides ratti. Our results demonstrate the applicability of CRISPR-Cas9 to parasitic nematodes, and thereby enable future studies of gene function in these medically relevant but previously genetically intractable parasites

    Special features of RAD Sequencing data:implications for genotyping

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    Restriction site-associated DNA Sequencing (RAD-Seq) is an economical and efficient method for SNP discovery and genotyping. As with other sequencing-by-synthesis methods, RAD-Seq produces stochastic count data and requires sensitive analysis to develop or genotype markers accurately. We show that there are several sources of bias specific to RAD-Seq that are not explicitly addressed by current genotyping tools, namely restriction fragment bias, restriction site heterozygosity and PCR GC content bias. We explore the performance of existing analysis tools given these biases and discuss approaches to limiting or handling biases in RAD-Seq data. While these biases need to be taken seriously, we believe RAD loci affected by them can be excluded or processed with relative ease in most cases and that most RAD loci will be accurately genotyped by existing tools

    Impact of target site distribution for Type I restriction enzymes on the evolution of methicillin-resistant Staphylococcus aureus (MRSA) populations.

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    A limited number of Methicillin-resistant Staphylococcus aureus (MRSA) clones are responsible for MRSA infections worldwide, and those of different lineages carry unique Type I restriction-modification (RM) variants. We have identified the specific DNA sequence targets for the dominant MRSA lineages CC1, CC5, CC8 and ST239. We experimentally demonstrate that this RM system is sufficient to block horizontal gene transfer between clinically important MRSA, confirming the bioinformatic evidence that each lineage is evolving independently. Target sites are distributed randomly in S. aureus genomes, except in a set of large conjugative plasmids encoding resistance genes that show evidence of spreading between two successful MRSA lineages. This analysis of the identification and distribution of target sites explains evolutionary patterns in a pathogenic bacterium. We show that a lack of specific target sites enables plasmids to evade the Type I RM system thereby contributing to the evolution of increasingly resistant community and hospital MRSA

    Fv antibodies to aflatoxin B1 derived from a pre-immunized antibody phage display library system

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    The production and characterization of recombinant antibodies to aflatoxin B[SUB1] (AFB[SUB1]), a potent mycotoxin and carcinogen is described. The antibody fragments produced were then applied for use in a surface plasmon resonance-based biosensor (BIAcore), which measures biomolecular interactions in 'real-time'. Single chain Fv (scFv) antibodies were generated to aflatoxin B1 from an established phage display system, which incorporated a range of different plasmids for efficient scFv expression. The scFv's were used in the development of a competitive ELISA, and also for the development of surface plasmon resonance (SPR)-based inhibition immunoassays. They were found to be suitable for the detection of AFB[SUB1], in this format, with the assays being sensitive and reproducible

    Characterisation of the 3' region of the PSG11 gene : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Genetics at Massey University, Palmerston North, New Zealand

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    Appendix : Content removed due to copyright restrictions. 1. Bichimica et Biophysica Acta l2l9 (1994) 195-t97 Sequence of a novel pregnancy-specific B,-glycoprotein C-terminal domain Terence W. Joe, Patricia A. McLenachan. Brian C. Mansfield 2. GENOMICS 22, 356-363 (1994) Characterization of the PSG11 Gene P. A. McLenachan,* K. J Rutherfurd* K. T. Beggs S.E. Sims,* B. C. Mansfield 3. Evolutionary Analysis of the Multi-gene Pregnancy-specific B1-glycoprotein Family: Separation of Historical and Non-historical Signals. Patricia A. McLenachan*, Peter J. Lockhart, H. Rick Faber*, Mansfield [accepted manuscript]The pregnancy-specific beta-1 glycoproteins (PSG) are a family of abundant proteins essential to pregnancy that are encoded by 11 genes located on chromosome 19q 13.1-13.3. The genes can be divided into three subgroups based on the organisation of their 3' coding regions. In 1989, our group isolated cosmid hC3.11, which contained most of the PSG11 gene, but which did not include the 3' coding region. This thesis reports subsequent work to characterise two further cosmids which span the PSG11 locus and which do include the 3' coding region. These cosmids were mapped and partially sequenced Three exons encoding potential alternative C-terminal domains were identified: Cw, Cr and Cs. The Cs domain lies 4.6kb from the end of the B2 domain. This is the first report of genomic sequence for this particular domain and for a functional PSG subgroup 3 gene. Downstream from this exon are sequences homologous to the C-termini of subgroup 1 PSG genes This finding suggests that subgroup 1,2 and 3 genes are related via insertion/deletion events. Data from seven PSG genes from all three subgroups and from four different regions were used to construct evolutionary trees. Variability patterns in the data were examined and these showed that the mechanism of sequence evolution for the N-terminal domain, the A1 domain, and to a certain extent, the B2 domain was not neutral Sequences from these regions were shown to be unsuitable for determining historical relationships between PSG genes. In contrast, the data from the C-terminal region showed a better fit with the assumptions of sequence evolution (e.g. all changes are independent and identically distributed) required by currently implemented analysis methods. Evolutionary tree reconstruction using this region gave a phylogeny that was consistent with one based on the genomic organisation of the genes

    Single cell transcriptome analysis using next generation sequencing.

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    The heterogeneity of tissues, especially in cancer research, is a central issue in transcriptome analysis. In recent years, research has primarily focused on the development of methods for single cell analysis. Single cell analysis aims at gaining (novel) insights into biological processes of healthy and diseased cells. Some of the challenges in transcriptome analysis concern low abundance of sample starting material, necessary sample amplification steps and subsequent analysis. In this study, two fundamentally different approaches to amplification were compared using next-generation sequencing analysis: I. exponential amplification using polymerase-chain-reaction (PCR) and II. linear amplification. For both approaches, protocols for single cell extraction, cell lysis, cDNA synthesis, cDNA amplification and preparation of next-generation sequencing libraries were developed. We could successfully show that transcriptome analysis of low numbers of cells is feasible with both exponential and linear amplification. Using exponential amplification, the highest amplification rates up to 106 were possible. The reproducibility of results is a strength of the linear amplification method. The analysis of next generation sequencing data in single cell samples showed detectable expression in at least 16.000 genes. The variance between samples results in a need to work with a greater amount of biological replicates. In summary it can be said that single cell transcriptome analysis with next generation sequencing is possible but improvements leading to a higher yield of transcriptome reads is required. In the near future by comparing single cancer cells with healthy ones for example, a basis for improved prognosis and diagnosis can be realised

    The Reverse Transcription Signature of N-\u3csub\u3e1\u3c/sub\u3e-Methyladenosine in RNA-Seq is Sequence Dependent

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    The combination of Reverse Transcription (RT) and high-throughput sequencing has emerged as a powerful combination to detect modified nucleotides in RNA via analysis of either abortive RT-products or of the incorporation of mismatched dNTPs into cDNA. Here we simultaneously analyze both parameters in detail with respect to the occurrence of N-1-methyladenosine (m1A) in the template RNA. This naturally occurring modification is associated with structural effects, but it is also known as a mediator of antibiotic resistance in ribosomal RNA. In structural probing experiments with dimethylsulfate, m1A is routinely detected by RT-arrest. A specifically developed RNA-Seq protocol was tailored to the simultaneous analysis of RT-arrest and misincorporation patterns. By application to a variety of native and synthetic RNA preparations, we found a characteristic signature of m1A, which, in addition to an arrest rate, features misincorporation as a significant component. Detailed analysis suggests that the signature depends on RNA structure and on the nature of the nucleotide 3’ of m1A in the template RNA, meaning it is sequence dependent. The RT-signature ofm1Awas used for inspection and confirmation of suspected modification sites and resulted in the identification of hitherto unknown m1A residues in trypanosomal tRNA
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