The International Gene Trap Consortium Website: a portal to all publicly available gene trap cell lines in mouse

Gene trapping is a method of generating murine embryonic stem (ES) cell lines containing insertional mutations in known and novel genes. A number of international groups have used this approach to create sizeable public cell line repositories available to the scientific community for the generation of mutant mouse strains. The major gene trapping groups worldwide have recently joined together to centralize access to all publicly available gene trap lines by developing a user-oriented Website for the International Gene Trap Consortium (IGTC). This collaboration provides an impressive public informatics resource comprising ∼45 000 well-characterized ES cell lines which currently represent ∼40% of known mouse genes, all freely available for the creation of knockout mice on a non-collaborative basis. To standardize annotation and provide high confidence data for gene trap lines, a rigorous identification and annotation pipeline has been developed combining genomic localization and transcript alignment of gene trap sequence tags to identify trapped loci. This information is stored in a new bioinformatics database accessible through the IGTC Website interface. The IGTC Website () allows users to browse and search the database for trapped genes, BLAST sequences against gene trap sequence tags, and view trapped genes within biological pathways. In addition, IGTC data have been integrated into major genome browsers and bioinformatics sites to provide users with outside portals for viewing this data. The development of the IGTC Website marks a major advance by providing the research community with the data and tools necessary to effectively use public gene trap resources for the large-scale characterization of mammalian gene function

Crop Updates 2005 - Farming Systems

This session covers forty four papers from different authors: PLENARY 1. 2005 Outlook, David Stephens and Nicola Telcik, Department of Agriculture FERTILITY AND NUTRITION 2. The effect of higher nitrogen fertiliser prices on rotation and fertiliser strategies in cropping systems, Ross Kingwell, Department of Agriculture and University of Western Australia 3. Stubble management: The short and long term implications for crop nutrition and soil fertility, Wayne Pluske, Nutrient Management Systems and Bill Bowden, Department of Agriculture 4. Stubble management: The pros and cons of different methods, Bill Bowden, Department of Agriculture, Western Australia and Mike Collins, WANTFA 5. Effect of stubble burning and seasonality on microbial processes and nutrient recycling, Frances Hoyle, The University of Western Australia 6. Soil biology and crop production in Western Australian farming systems, D.V. Murphy, N. Milton, M. Osman, F.C. Hoyle, L.K Abbott, W.R. Cookson and S. Darmawanto, The University of Western Australia 7. Urea is as effective as CAN when no rain for 10 days, Bill Crabtree, Crabtree Agricultural Consulting 8. Fertiliser (N,P,S,K) and lime requirements for wheat production in the Merredin district, Geoff Anderson, Department of Agriculture and Darren Kidson, Summit Fertilizers 9. Trace element applications: Up-front verses foliar? Bill Bowden and Ross Brennan, Department of Agriculture 10. Fertcare®, Environmental Product Stewardship and Advisor Standards for thee Fertiliser Industry, Nick Drew, Fertilizer Industry Federation of Australia (FIFA) SOIL AND LAND MANAGEMENT 11. Species response to row spacing, density and nutrition, Bill Bowden, Craig Scanlan, Lisa Sherriff, Bob French and Reg Lunt, Department of Agriculture 12. Investigation into the influence of row orientation in lupin crops, Jeff Russell, Department of Agriculture and Angie Roe, Farm Focus Consultants 13. Deriving variable rate management zones for crops, Ian Maling, Silverfox Solutions and Matthew Adams, DLI 14. In a world of Precision Agriculture, weigh trailers are not passé, Jeff Russell, Department of Agriculture 15. Cover crop management to combat ryegrass resistance and improve yields, Jeff Russell, Department of Agriculture and Angie Roe, Farm Focus Consultants 16. ARGT home page, the place to find information on annual ryegrass toxicity on the web, Dr George Yan, BART Pty Ltd 17. Shallow leading tine (SLT) ripper significantly reduces draft force, improves soil tilth and allows even distribution of subsoil ameliorants, Mohammad Hamza, Glen Riethmuller and Wal Anderson, Department of Agriculture PASTURE ANS SUMMER CROP SYSTEMS 18. New annual pasture legumes for Mediteranean farming systems, Angelo Loi, Phil Nichols, Clinton Revell and David Ferris, Department of Agriculture 19. How sustainable are phase rotations with Lucerne? Phil Ward, CSIRO Plant Industry 20. Management practicalities of summer cropping, Andrea Hills and Sally-Anne Penny, Department of Agriculture 21. Rainfall zone determines the effect of summer crops on winter yields, Andrea Hills, Sally-Anne Penny and David Hall, Department of Agriculture 22. Summer crops and water use, Andrea Hills, Sally-Anne Penny and David Hall, Department of Agriculture, and Michael Robertson and Don Gaydon, CSIRO Brisbane 23. Risk analysis of sorgum cropping, Andrea Hills and Sally-Anne Penny, Department of Agriculture, and Dr Michael Robertson and Don Gaydon, CSIRO Brisbane FARMER DECISION SUPPORT AND ADOPTION 24. Variety release and End Point Royalties – a new system? Tress Walmsley, Department of Agriculture 25. Farming system analaysis using the STEP Tool, Caroline Peek and Megan Abrahams, Department of Agriculture 26. The Leakage Calculator: A simple tool for groundwater recharge assessment, Paul Raper, Department of Agriculture 27. The cost of Salinity Calculator – your tool to assessing the profitability of salinity management options, Richard O’Donnell and Trevor Lacey, Department of Agriculture 28. Climate decision support tools, Meredith Fairbanks and David Tennant, Department of Agriculture 29. Horses for courses – using the best tools to manage climate risk, Cameron Weeks, Mingenew-Irwin Group/Planfarm and Richard Quinlan, Planfarm Agronomy 30. Use of seasonal outlook for making N decisions in Merredin, Meredith Fairbanks and Alexandra Edward, Department of Agriculture 31. Forecasts and profits, Benefits or bulldust? Chris Carter and Doug Hamilton, Department of Agriculture 32. A tool to estimate fixed and variable header and tractor depreciation costs, Peter Tozer, Department of Agriculture 33. Partners in grain: ‘Putting new faces in new places’, Renaye Horne, Department of Agriculture 34. Results from the Grower group Alliance, Tracey Gianatti, Grower Group Alliance 35. Local Farmer Group Network – farming systems research opportunities through local groups, Paul Carmody, Local Farmer Group Network GREENHOUSE GAS AND CLIMATE CHANGE 36. Changing rainfall patterns in the grainbelt, Ian Foster, Department of Agriculture 37. Vulnerability of broadscale agriculture to the impacts of climate change, Michele John, CSIRO (formerly Department of Agriculture) and Ross George, Department of Agriculture 38. Impacts of climate change on wheat yield at Merredin, Imma Farré and Ian Foster, Department of Agriculture 39. Climate change, land use suitability and water security, Ian Kininmonth, Dennis van Gool and Neil Coles, Department of Agriculture 40. Nitrous oxide emissions from cropping systems, Bill Porter, Department of Agriculture, Louise Barton, University of Western Australia 41. The potential of greenhouse sinks to underwrite improved land management in Western Australia, Richard Harper and Peter Ritson, CRC for Greenhouse Accounting and Forest Products Commission, Tony Beck, Tony Beck Consulting Services, Chris Mitchell and Michael Hill, CRC for Greenhouse Accounting 42. Removing uncertainty from greenhouse emissions, Fiona Barker-Reid, Will Gates, Ken Wilson and Rob Baigent, Department of Primary Industries - Victoria and CRC for Greenhouse Accounting (CRCGA), and Ian Galbally, Mick Meyer and Ian Weeks, CSIRO Atmospheric Research and CRCGA 43. Greenhouse in Agriculture Program (GIA), Traci Griffin, CRC for Greenhouse Accounting 44. Grains Greenhouse Accounting framework, D. Rodriguez, M. Probust, M. Meyers, D. Chen, A. Bennett, W. Strong, R. Nussey, I. Galbally and M. Howden CONTACT DETAILS FOR PRINCIPAL AUTHOR

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

Recent genomic analyses of pathologically-defined tumor types identify “within-a-tissue” disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head & neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multi-platform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All datasets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies

The WI+RE Way

WI+RE (Writing Instruction + Research Education) is a learner-led team of undergraduate and graduate student employees at UCLA Library who apply values-driven design principles and grassroots instructional media production techniques to foster breakthroughs in research, reading, and writing for their fellow learners. The WI+RE Way (UCLA Library WI+RE, 2019c) is a collaboratively authored manifesto for learner-led design co-authored by WI+RE's learner-designers in collaboration with library staff. 

Comparison of methods for genomic localization of gene trap sequences

<p>Abstract</p> <p>Background</p> <p>Gene knockouts in a model organism such as mouse provide a valuable resource for the study of basic biology and human disease. Determining which gene has been inactivated by an untargeted gene trapping event poses a challenging annotation problem because gene trap sequence tags, which represent sequence near the vector insertion site of a trapped gene, are typically short and often contain unresolved residues. To understand better the localization of these sequences on the mouse genome, we compared stand-alone versions of the alignment programs BLAT, SSAHA, and MegaBLAST. A set of 3,369 sequence tags was aligned to build 34 of the mouse genome using default parameters for each algorithm. Known genome coordinates for the cognate set of full-length genes (1,659 sequences) were used to evaluate localization results.</p> <p>Results</p> <p>In general, all three programs performed well in terms of localizing sequences to a general region of the genome, with only relatively subtle errors identified for a small proportion of the sequence tags. However, large differences in performance were noted with regard to correctly identifying exon boundaries. BLAT correctly identified the vast majority of exon boundaries, while SSAHA and MegaBLAST missed the majority of exon boundaries. SSAHA consistently reported the fewest false positives and is the fastest algorithm. MegaBLAST was comparable to BLAT in speed, but was the most susceptible to localizing sequence tags incorrectly to pseudogenes.</p> <p>Conclusion</p> <p>The differences in performance for sequence tags and full-length reference sequences were surprisingly small. Characteristic variations in localization results for each program were noted that affect the localization of sequence at exon boundaries, in particular.</p

Comparison of methods for genomic localization of gene trap sequences.

BackgroundGene knockouts in a model organism such as mouse provide a valuable resource for the study of basic biology and human disease. Determining which gene has been inactivated by an untargeted gene trapping event poses a challenging annotation problem because gene trap sequence tags, which represent sequence near the vector insertion site of a trapped gene, are typically short and often contain unresolved residues. To understand better the localization of these sequences on the mouse genome, we compared stand-alone versions of the alignment programs BLAT, SSAHA, and MegaBLAST. A set of 3,369 sequence tags was aligned to build 34 of the mouse genome using default parameters for each algorithm. Known genome coordinates for the cognate set of full-length genes (1,659 sequences) were used to evaluate localization results.ResultsIn general, all three programs performed well in terms of localizing sequences to a general region of the genome, with only relatively subtle errors identified for a small proportion of the sequence tags. However, large differences in performance were noted with regard to correctly identifying exon boundaries. BLAT correctly identified the vast majority of exon boundaries, while SSAHA and MegaBLAST missed the majority of exon boundaries. SSAHA consistently reported the fewest false positives and is the fastest algorithm. MegaBLAST was comparable to BLAT in speed, but was the most susceptible to localizing sequence tags incorrectly to pseudogenes.ConclusionThe differences in performance for sequence tags and full-length reference sequences were surprisingly small. Characteristic variations in localization results for each program were noted that affect the localization of sequence at exon boundaries, in particular