A cancer cell-line titration series for evaluating somatic classification.

BackgroundAccurate detection of somatic single nucleotide variants and small insertions and deletions from DNA sequencing experiments of tumour-normal pairs is a challenging task. Tumour samples are often contaminated with normal cells confounding the available evidence for the somatic variants. Furthermore, tumours are heterogeneous so sub-clonal variants are observed at reduced allele frequencies. We present here a cell-line titration series dataset that can be used to evaluate somatic variant calling pipelines with the goal of reliably calling true somatic mutations at low allele frequencies.ResultsCell-line DNA was mixed with matched normal DNA at 8 different ratios to generate samples with known tumour cellularities, and exome sequenced on Illumina HiSeq to depths of >300×. The data was processed with several different variant calling pipelines and verification experiments were performed to assay >1500 somatic variant candidates using Ion Torrent PGM as an orthogonal technology. By examining the variants called at varying cellularities and depths of coverage, we show that the best performing pipelines are able to maintain a high level of precision at any cellularity. In addition, we estimate the number of true somatic variants undetected as cellularity and coverage decrease.ConclusionsOur cell-line titration series dataset, along with the associated verification results, was effective for this evaluation and will serve as a valuable dataset for future somatic calling algorithm development. The data is available for further analysis at the European Genome-phenome Archive under accession number EGAS00001001016. Data access requires registration through the International Cancer Genome Consortium's Data Access Compliance Office (ICGC DACO)

Identification of genes expressed by immune cells of the colon that are regulated by colorectal cancer-associated variants.

A locus on human chromosome 11q23 tagged by marker rs3802842 was associated with colorectal cancer (CRC) in a genome-wide association study; this finding has been replicated in case-control studies worldwide. In order to identify biologic factors at this locus that are related to the etiopathology of CRC, we used microarray-based target selection methods, coupled to next-generation sequencing, to study 103 kb at the 11q23 locus. We genotyped 369 putative variants from 1,030 patients with CRC (cases) and 1,061 individuals without CRC (controls) from the Ontario Familial Colorectal Cancer Registry. Two previously uncharacterized genes, COLCA1 and COLCA2, were found to be co-regulated genes that are transcribed from opposite strands. Expression levels of COLCA1 and COLCA2 transcripts correlate with rs3802842 genotypes. In colon tissues, COLCA1 co-localizes with crystalloid granules of eosinophils and granular organelles of mast cells, neutrophils, macrophages, dendritic cells and differentiated myeloid-derived cell lines. COLCA2 is present in the cytoplasm of normal epithelial, immune and other cell lineages, as well as tumor cells. Tissue microarray analysis demonstrates the association of rs3802842 with lymphocyte density in the lamina propria (p = 0.014) and levels of COLCA1 in the lamina propria (p = 0.00016) and COLCA2 (tumor cells, p = 0.0041 and lamina propria, p = 6 × 10(-5)). In conclusion, genetic, expression and immunohistochemical data implicate COLCA1 and COLCA2 in the pathogenesis of colon cancer. Histologic analyses indicate the involvement of immune pathways

A Cognitive Model of an Epistemic Community: Mapping the Dynamics of Shallow Lake Ecosystems

We used fuzzy cognitive mapping (FCM) to develop a generic shallow lake ecosystem model by augmenting the individual cognitive maps drawn by 8 scientists working in the area of shallow lake ecology. We calculated graph theoretical indices of the individual cognitive maps and the collective cognitive map produced by augmentation. The graph theoretical indices revealed internal cycles showing non-linear dynamics in the shallow lake ecosystem. The ecological processes were organized democratically without a top-down hierarchical structure. The steady state condition of the generic model was a characteristic turbid shallow lake ecosystem since there were no dynamic environmental changes that could cause shifts between a turbid and a clearwater state, and the generic model indicated that only a dynamic disturbance regime could maintain the clearwater state. The model developed herein captured the empirical behavior of shallow lakes, and contained the basic model of the Alternative Stable States Theory. In addition, our model expanded the basic model by quantifying the relative effects of connections and by extending it. In our expanded model we ran 4 simulations: harvesting submerged plants, nutrient reduction, fish removal without nutrient reduction, and biomanipulation. Only biomanipulation, which included fish removal and nutrient reduction, had the potential to shift the turbid state into clearwater state. The structure and relationships in the generic model as well as the outcomes of the management simulations were supported by actual field studies in shallow lake ecosystems. Thus, fuzzy cognitive mapping methodology enabled us to understand the complex structure of shallow lake ecosystems as a whole and obtain a valid generic model based on tacit knowledge of experts in the field.Comment: 24 pages, 5 Figure

Evaluation of serum CEA, CYFRA21-1 and CA125 for the early detection of colorectal cancer using longitudinal preclinical samples

Blood-borne biomarkers for early detection of colorectal cancer (CRC) could markedly increase screening uptake. The aim of this study was to evaluate serum carcinoembryonic antigen (CEA), CYFRA21-1 and CA125 for the early detection of CRC in an asymptomatic cohort

Sheep Updates 2008 - part 3

This session covers fiveteen papers from different authors: CONTROLLING FLY STRIKE 1. Breeding for Blowfly Resistance - Indicatoe Traits, LJE Karlsson, JC Greeff, L Slocombe, Department of Agriculture & Food, Western Australia 2.A practical method to select for breech strike resistance in non-pedigreed Merino flocks, LJE Karlsson, JC Greeff, L Slocombe, K. Jones, N. Underwood, Department of Agriculture & Food, Western Australia 3. Twice a year shearing - no mulesing, Fred Wilkinson, Producer, Brookton WA BEEF 4. Commercial testing of a new tool for prediction of fatness in beef cattle, WD HoffmanA, WA McKiernanA, VH OddyB, MJ McPheeA, Cooperative Research Centre for Beef Genetic Technologies, A N.S.W. Deptartment of Primary Industries, B University of New England 5. A new tool for the prediction of fatness in beef cattle, W.A. McKiernanA, V.H. OddyB and M.J. McPheeC; Cooperative Research Centre for Beef Genetic Technologies, A N.S.W. Dept of Primary Industries, B University of New England, C N.S.W. Dept of Primary Industries Beef Industry Centre of Excellence. 6. Effect of gene markers for tenderness on eating quality of beef, B.L. McIntyre, CRC for Beef Genetic Technologies, Department of Agriculture and Food WA 7. Accelerating beef industry innovation through Beef Profit Partnerships, Parnell PF1,2, Clark RA1,3, Timms J1,3, Griffith G1,2, Alford A1,2, Mulholland C1 and Hyland P1,4,1Co-operative Research Centre for Beef Genetic Technologies; 2NSW Department of Primary Industries; 3 Qld Department of Primary Industries and Fisheries; 4The University of Queensland. SUSTAINABILITY 8. The WA Sheep Industry - is it ethically and environmentally sustainable? Danielle England, Department of Agriculture and Food Western Australia 9. Overview of ruminant agriculture and greenhouse emissions, Fiona Jones, Department of Agriculture and Food Western Australia 10. Grazing for Nitrogen Efficiency, John Lucey, Martin Staines and Richard Morris, Department of Agriculture and Food Western Australia 11. Investigating potential adaptations to climate change for low rainfall farming system, Megan Abrahams, Caroline Peek, Dennis Van Gool, Daniel Gardiner, Kari-Lee Falconer, Department of Agriculture and Food Western Australia SHEEP 12. Benchmarking ewe productivity through on-farm genetic comparisons, Sandra Prosser, Mario D’Antuono and Johan Greeff; Department of Agriculture and Food Western Australia 13. Increasing profitability by pregnancy scanning ewes, John Young1, Andrew Thompson2 and Chris Oldham2; 1Farming Systems Analysis Service, Kojonup, WA, 2Department of Agriculture and Food Western Australia 14. Targeted treatment of worm-affected sheep - more efficient, more sustainable, Brown Besier, Department of Agriculture and Food Western Australia 15. Improving Weaner Sheep Survival, Angus Campbell and Ralph Behrendt, Cooperative Research Centre for Sheep Industry Innovatio

A polygenic burden of rare disruptive mutations in schizophrenia.

Schizophrenia is a common disease with a complex aetiology, probably involving multiple and heterogeneous genetic factors. Here, by analysing the exome sequences of 2,536 schizophrenia cases and 2,543 controls, we demonstrate a polygenic burden primarily arising from rare (less than 1 in 10,000), disruptive mutations distributed across many genes. Particularly enriched gene sets include the voltage-gated calcium ion channel and the signalling complex formed by the activity-regulated cytoskeleton-associated scaffold protein (ARC) of the postsynaptic density, sets previously implicated by genome-wide association and copy-number variation studies. Similar to reports in autism, targets of the fragile X mental retardation protein (FMRP, product of FMR1) are enriched for case mutations. No individual gene-based test achieves significance after correction for multiple testing and we do not detect any alleles of moderately low frequency (approximately 0.5 to 1 per cent) and moderately large effect. Taken together, these data suggest that population-based exome sequencing can discover risk alleles and complements established gene-mapping paradigms in neuropsychiatric disease

Beyond factor analysis: Multidimensionality and the Parkinson’s Disease Sleep Scale-Revised

Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinson’s disease (PD). The Parkinson’s Disease Sleep Scale (PDSS) and its variants (the Parkinson’s disease Sleep Scale-Revised; PDSS-R, and the Parkinson’s Disease Sleep Scale-2; PDSS-2) quantify a range of symptoms impacting sleep in only 15 items. However, data from these scales may be problematic as included items have considerable conceptual breadth, and there may be overlap in the constructs assessed. Multidimensional measurement models, accounting for the tendency for items to measure multiple constructs, may be useful more accurately to model variance than traditional confirmatory factor analysis. In the present study, we tested the hypothesis that a multidimensional model (a bifactor model) is more appropriate than traditional factor analysis for data generated by these types of scales, using data collected using the PDSS-R as an exemplar. 166 participants diagnosed with idiopathic PD participated in this study. Using PDSS-R data, we compared three models: a unidimensional model; a 3-factor model consisting of sub-factors measuring insomnia, motor symptoms and obstructive sleep apnoea (OSA) and REM sleep behaviour disorder (RBD) symptoms; and, a confirmatory bifactor model with both a general factor and the same three sub-factors. Only the confirmatory bifactor model achieved satisfactory model fit, suggesting that PDSS-R data are multidimensional. There were differential associations between factor scores and patient characteristics, suggesting that some PDSS-R items, but not others, are influenced by mood and personality in addition to sleep symptoms. Multidimensional measurement models may also be a helpful tool in the PDSS and the PDSS-2 scales and may improve the sensitivity of these instruments