Chris Duran, PhD

Plant biotechnology journal (2012). Pages: 1-7.

Kaitao Lai, Chris Duran, Paul J Berkman, Michał T Lorenc, Jiri Stiller, Sahana Manoli, Matthew J Hayden, Kerrie L Forrest, Delphine Fleury, Ute Baumann, Manuel Zander, Annaliese S Mason, Jacqueline Batley, David Edwards et al.

Single nucleotide polymorphisms (SNPs) are the most abundant type of molecular genetic marker and can be used for producing high-resolution genetic maps, marker-trait association studies and marker-assisted breeding. Large polyploid genomes such as wheat present a challenge for SNP discovery because of the potential presence of multiple homoeologs for each gene. AutoSNPdb has been successfully applied to identify SNPs from Sanger sequence data for several species, including barley, rice and Brassica, but the volume of data required to accurately call SNPs in the complex genome of wheat has prevented its application to this important crop. DNA sequencing technology has been revolutionized by the introduction of next-generation sequencing, and it is now possible to generate several million sequence reads in a timely and cost-effective manner. We have produced wheat transcriptome sequence data using 454 sequencing technology and applied this for SNP discovery using a modified autoSNPdb method, which integrates SNP and gene annotation information with a graphical viewer. A total of 4 694 141 sequence reads from three bread wheat varieties were assembled to identify a total of 38 928 candidate SNPs. Each SNP is within an assembly complete with annotation, enabling the selection of polymorphism within genes of interest.

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Bioinformatics (2012). Volume: 28, Issue: 12. Pages: 1647-1649.

M. Kearse, R. Moir, A. Wilson, S. Stones-Havas, M. Cheung, S. Sturrock, S. Buxton, A. Cooper, S. Markowitz, C. Duran, T. Thierer, B. Ashton, P. Meintjes, A. Drummond et al.

Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com

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Briefings in functional genomics (2012). Volume: 11, Issue: 1. Pages: 12-24.

Hong C Lee, Kaitao Lai, Michal Tadeusz Lorenc, Michael Imelfort, Chris Duran, David Edwards et al.

Genome sequencing has been revolutionized by next-generation technologies, which can rapidly produce vast quantities of data at relatively low cost. With data production now no longer being limited, there is a huge challenge to analyse the data flood and interpret biological meaning. Bioinformatics scientists have risen to the challenge and a large number of software tools and databases have been produced and these continue to evolve with this rapidly advancing field. Here, we outline some of the tools and databases commonly used for the analysis of next-generation sequence data with comment on their utility.

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Genetics, Genomics and Breeding of Oilseed Brassicas (2011). Pages: 194-205.

Michal Lorenc, Zoran Boskovic, Jiri Stiller, Chris Duran, David Edwards et al.

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Genetics, Genomics and Breeding of Vegetable Brassicas (2011). Pages: 406-418.

Chris Duran, Zoran Boskovic, Jacqueline Batley, David Edwards et al.

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Bioinformatics:Tools and Applications (2009). Pages: 165-189.

Chris Duran, David Edwards, Jacqueline Batley et al.

The bulk of variation at the nucleotide level is often not visible at the phenotypic level. However, this variation can be exploited using molecular genetic marker systems. Molecular genetic markers represent one of the most powerful tools for genome analysis and permit the association of heritable traits with underlying genomic variation. Molecular marker technology has developed rapidly over the last decade, with the development of high-throughput genotyping methods and the availability of large amounts of sequence data for automated marker discovery. Two forms of sequence based marker, Simple Sequence Repeats (SSRs), also known as microsatellites, and Single Nucleotide Polymorphisms (SNPs) are the principal markers currently applied in modern genetic analysis. This are supplemented with anonymous marker systems such as Amplified Fragment Length Polymorphisms (AFLPs; Vos et al. 1995), and Diversity Array Technology (DArT; Jaccoud et al. 2001). The reducing cost of DNA sequencing has led to the availability of large sequence data sets that enable the mining of sequence based markers, such as SSRs and SNPs, which may then be applied to diversity analysis, genetic trait mapping, association studies, and marker assisted selection.

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Methods in molecular biology (Clifton, N.J.) (2009). Pages: 41-55.

Chris Duran, David Edwards, Jacqueline Batley et al.

Genetic linkage maps represent the order of known molecular genetic markers along a given chromosome for a given species. This provides an insight into the organisation of a plant genome. In comparative genomics, synteny is the preserved order of genes on chromosomes of related species which results from descent from a common ancestor. Comparative mapping is a valuable technique to identify similarities and differences between species and enables the transfer of information from one map to another and assists in the reconstruction of ancestral genomes. This chapter demonstrates the application of online resources to identify candidate genes underlying a QTL, conduct genome comparisons, identify syntenic regions and view comparative genetic maps in grass and Brassica species.

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Plant & cell physiology (2012). Volume: 53, Issue: 2. Pages: e2.

Kaitao Lai, Paul J Berkman, Michal Tadeusz Lorenc, Chris Duran, Lars Smits, Sahana Manoli, Jiri Stiller, David Edwards et al.

Bread wheat (Triticum aestivum) is one of the most important crop plants, globally providing staple food for a large proportion of the human population. However, improvement of this crop has been limited due to its large and complex genome. Advances in genomics are supporting wheat crop improvement. We provide a variety of web-based systems hosting wheat genome and genomic data to support wheat research and crop improvement. WheatGenome.info is an integrated database resource which includes multiple web-based applications. These include a GBrowse2-based wheat genome viewer with BLAST search portal, TAGdb for searching wheat second-generation genome sequence data, wheat autoSNPdb, links to wheat genetic maps using CMap and CMap3D, and a wheat genome Wiki to allow interaction between diverse wheat genome sequencing activities. This system includes links to a variety of wheat genome resources hosted at other research organizations. This integrated database aims to accelerate wheat genome research and is freely accessible via the web interface at http://www.wheatgenome.info/.

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Nature genetics (2011). Volume: 43, Issue: 10. Pages: 1035-9.

Xiaowu Wang, Hanzhong Wang, Jun Wang, Rifei Sun, Jian Wu, Shengyi Liu, Yinqi Bai, Jeong-Hwan Mun, Ian Bancroft, Feng Cheng, Sanwen Huang, Xixiang Li, Wei Hua, Junyi Wang, Xiyin Wang, Michael Freeling, J Chris Pires, Andrew H Paterson, Boulos Chalhoub, Bo Wang, Alice Hayward, Andrew G Sharpe, Beom-Seok Park, Bernd Weisshaar, Binghang Liu, Bo Li, Bo Liu, Chaobo Tong, Chi Song, Christopher Duran, Chunfang Peng, Chunyu Geng, Chushin Koh, Chuyu Lin, David Edwards, Desheng Mu, Di Shen, Eleni Soumpourou, Fei Li, Fiona Fraser, Gavin Conant, Gilles Lassalle, Graham J King, Guusje Bonnema, Haibao Tang, Haiping Wang, Harry Belcram, Heling Zhou, Hideki Hirakawa, Hiroshi Abe, Hui Guo, Hui Wang, Huizhe Jin, Isobel A P Parkin, Jacqueline Batley, Jeong-Sun Kim, Jérémy Just, Jianwen Li, Jiaohui Xu, Jie Deng, Jin A Kim, Jingping Li, Jingyin Yu, Jinling Meng, Jinpeng Wang, Jiumeng Min, Julie Poulain, Katsunori Hatakeyama, Kui Wu, Li Wang, Lu Fang, Martin Trick, Matthew G Links, Meixia Zhao, Mina Jin, Nirala Ramchiary, Nizar Drou, Paul J Berkman, Qingle Cai, Quanfei Huang, Ruiqiang Li, Satoshi Tabata, Shifeng Cheng, Shu Zhang, Shujiang Zhang, Shunmou Huang, Shusei Sato, Silong Sun, Soo-Jin Kwon, Su-Ryun Choi, Tae-Ho Lee, Wei Fan, Xiang Zhao, Xu Tan, Xun Xu, Yan Wang, Yang Qiu, Ye Yin, Yingrui Li, Yongchen Du, Yongcui Liao, Yongpyo Lim, Yoshihiro Narusaka, Yupeng Wang, Zhenyi Wang, Zhenyu Li, Zhiwen Wang, Zhiyong Xiong, Zhonghua Zhang et al.

We report the annotation and analysis of the draft genome sequence of Brassica rapa accession Chiifu-401-42, a Chinese cabbage. We modeled 41,174 protein coding genes in the B. rapa genome, which has undergone genome triplication. We used Arabidopsis thaliana as an outgroup for investigating the consequences of genome triplication, such as structural and functional evolution. The extent of gene loss (fractionation) among triplicated genome segments varies, with one of the three copies consistently retaining a disproportionately large fraction of the genes expected to have been present in its ancestor. Variation in the number of members of gene families present in the genome may contribute to the remarkable morphological plasticity of Brassica species. The B. rapa genome sequence provides an important resource for studying the evolution of polyploid genomes and underpins the genetic improvement of Brassica oil and vegetable crops.

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Plant biotechnology journal (2011). Volume: 9, Issue: 7. Pages: 768-75.

Paul J Berkman, Adam Skarshewski, Michał T Lorenc, Kaitao Lai, Chris Duran, Edmund Y S Ling, Jiri Stiller, Lars Smits, Michael Imelfort, Sahana Manoli, Megan McKenzie, Marie Kubaláková, Hana Šimková, Jacqueline Batley, Delphine Fleury, Jaroslav Doležel, David Edwards et al.

The genome of bread wheat (Triticum aestivum) is predicted to be greater than 16 Gbp in size and consist predominantly of repetitive elements, making the sequencing and assembly of this genome a major challenge. We have reduced genome sequence complexity by isolating chromosome arm 7DS and applied second-generation technology and appropriate algorithmic analysis to sequence and assemble low copy and genic regions of this chromosome arm. The assembly represents approximately 40% of the chromosome arm and all known 7DS genes. Comparison of the 7DS assembly with the sequenced genomes of rice (Oryza sativa) and Brachypodium distachyon identified large regions of conservation. The syntenic relationship between wheat, B. distachyon and O. sativa, along with available genetic mapping data, has been used to produce an annotated draft 7DS syntenic build, which is publicly available at http://www.wheatgenome.info. Our results suggest that the sequencing of isolated chromosome arms can provide valuable information of the gene content of wheat and is a step towards whole-genome sequencing and variation discovery in this important crop.

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Genome / National Research Council Canada = Génome / Conseil national de recherches Canada (2010). Volume: 53, Issue: 11. Pages: 1017-23.

Chris Duran, Dominic Eales, Daniel Marshall, Michael Imelfort, Jiri Stiller, Paul J Berkman, Terry Clark, Megan McKenzie, Nikki Appleby, Jacqueline Batley, Kaye Basford, David Edwards et al.

Association mapping currently relies on the identification of genetic markers. Several technologies have been adopted for genetic marker analysis, with single nucleotide polymorphisms (SNPs) being the most popular where a reasonable quantity of genome sequence data are available. We describe several tools we have developed for the discovery, annotation, and visualization of molecular markers for association mapping. These include autoSNPdb for SNP discovery from assembled sequence data; TAGdb for the identification of gene specific paired read Illumina GAII data; CMap3D for the comparison of mapped genetic and physical markers; and BAC and Gene Annotator for the online annotation of genes and genomic sequences.

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Plant methods (2010). Pages: 19.

Daniel J Marshall, Alice Hayward, Dominic Eales, Michael Imelfort, Jiri Stiller, Paul J Berkman, Terry Clark, Megan McKenzie, Kaitao Lai, Chris Duran, Jacqueline Batley, David Edwards et al.

The introduction of second generation sequencing technology has enabled the cost effective sequencing of genomes and the identification of large numbers of genes and gene promoters. However, the assembly of DNA sequences to create a representation of the complete genome sequence remains costly, especially for the larger and more complex plant genomes.

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16th Australian Research Assembly on Brassicas (2009). Pages: 1-5.

Chris Duran, Jiri Stiller, Mike Imelfort, Dominic Eales, Chang Pyo Hong, Daniel Marshall, Megan Vardy, Harsh Raman, Jacqueline Batley, David Edwards et al.

Brassica genomes are relatively large and complex due to historic duplication events, the amplification of families of transposable elements, and polyploidisation. The development of second generation DNA sequencing methods is rapidly changing plant genome research and we are applying this technology for the analysis of the Brassica genomes. We have generated genome sequence data for several Brassica species and developed tools for the analysis of this data. These tools can be applied for gene and molecular marker discovery to support Brassica crop improvement.

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Plant biotechnology journal (2009). Volume: 7, Issue: 4. Pages: 312-7.

Michael Imelfort, Chris Duran, Jacqueline Batley, David Edwards et al.

The ongoing revolution in DNA sequencing technology now enables the reading of thousands of millions of nucleotide bases in a single instrument run. However, this data quantity is often compromised by poor confidence in the read quality. The identification of genetic polymorphisms from this data is therefore problematic and, combined with the vast quantity of data, poses a major bioinformatics challenge. However, once these difficulties have been addressed, next-generation sequencing will offer a means to identify and characterize the wealth of genetic polymorphisms underlying the vast phenotypic variation in biological systems. We describe the recent advances in next-generation sequencing technology, together with preliminary approaches that can be applied for single nucleotide polymorphism discovery in plant species.

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Mammalian genome : official journal of the International Mammalian Genome Society (2007). Volume: 18, Issue: 3. Pages: 157-63.

John M Hancock, Niels C Adams, Vassilis Aidinis, Andrew Blake, Molly Bogue, Steve D M Brown, Elissa J Chesler, Duncan Davidson, Christopher Duran, Janan T Eppig, Valérie Gailus-Durner, Hilary Gates, Georgios V Gkoutos, Simon Greenaway, Martin Hrabé de Angelis, George Kollias, Sophie Leblanc, Kirsty Lee, Christoph Lengger, Holger Maier, Ann-Marie Mallon, Hiroshi Masuya, David G Melvin, Werner Müller, Helen Parkinson, Glenn Proctor, Eli Reuveni, Paul Schofield, Aadya Shukla, Cynthia Smith, Tetsuro Toyoda, Laurent Vasseur, Shigeharu Wakana, Alison Walling, Jacqui White, Joe Wood, Michalis Zouberakis et al.

Understanding the functions encoded in the mouse genome will be central to an understanding of the genetic basis of human disease. To achieve this it will be essential to be able to characterize the phenotypic consequences of variation and alterations in individual genes. Data on the phenotypes of mouse strains are currently held in a number of different forms (detailed descriptions of mouse lines, first-line phenotyping data on novel mutations, data on the normal features of inbred lines) at many sites worldwide. For the most efficient use of these data sets, we have initiated a process to develop standards for the description of phenotypes (using ontologies) and file formats for the description of phenotyping protocols and phenotype data sets. This process is ongoing and needs to be supported by the wider mouse genetics and phenotyping communities to succeed. We invite interested parties to contact us as we develop this process further.

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Bioinformatics (2010). Volume: 26, Issue: 2. Pages: 273-274.

Chris Duran, Z Boskovic, M Imelfort, J Batley, N A Hamilton, D Edwards et al.

Genetic linkage mapping enables the study of genome organization and the association of heritable traits with regions of sequenced genomes. Comparative genetic mapping is particularly powerful as it allows translation of information between related genomes and gives an insight into genome evolution. A common tool for the storage, comparison and visualization of genetic maps is CMap. However, current visualization in CMap is limited to the comparison of adjacent aligned maps. To overcome this limitation, we have developed CMap3D, a tool to compare multiple genetic maps in three-dimensional space. CMap3D is based on a client/server model ensuring operability with current CMap data repositories. This tool can be applied to any species where genetic map information is available and enables rapid, direct comparison between multiple aligned maps.

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Current Bioinformatics (2009). Pages: 16-27.

Chris Duran, Nikki Appleby, David Edwards, Jacqueline Batley et al.

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Nucl. Acids Res. (2009). Volume: 37, Issue: suppl_1. Pages: D951-953.

Chris Duran, Nikki Appleby, Terry Clark, David Wood, Michael Imelfort, Jacqueline Batley, David Edwards et al.

Single nucleotide polymorphisms (SNPs) may be considered the ultimate genetic marker as they represent the finest resolution of a DNA sequence (a single nucleotide), are generally abundant in populations and have a low mutation rate. Analysis of assembled EST sequence data provides a cost-effective means to identify large numbers of SNPs associated with functional genes. We have developed an integrated SNP discovery pipeline, which identifies SNPs from assembled EST sequences. The results are maintained in a custom relational database along with EST source and annotation information. The current database hosts data for the important crops rice, barley and Brassica. Users may rapidly identify polymorphic sequences of interest through BLAST sequence comparison, keyword searches of annotations derived from UniRef90 and GenBank comparisons, GO annotations or in genes corresponding to syntenic regions of reference genomes. In addition, SNPs between specific varieties may be identified for targeted mapping and association studies. SNPs are viewed using a user-friendly graphical interface. The database is freely accessible at http://autosnpdb.qfab.org.au/.

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Plant Biotechnol J (2009). Volume: 7, Issue: 4. Pages: 326-333.

Chris Duran, Nikki Appleby, Megan Vardy, Michael Imelfort, David Edwards, Jacqueline Batley et al.

Molecular markers are used to provide the link between genotype and phenotype, for the production of molecular genetic maps and to assess genetic diversity within and between related species. Single nucleotide polymorphisms (SNPs) are the most abundant molecular genetic marker. SNPs can be identified in silico, but care must be taken to ensure that the identified SNPs reflect true genetic variation and are not a result of errors associated with DNA sequencing. The SNP detection method autoSNP has been developed to identify SNPs from sequence data for any species. Confidence in the predicted SNPs is based on sequence redundancy, and haplotype co-segregation scores are calculated for a further independent measure of confidence. We have extended the autoSNP method to produce autoSNPdb, which integrates SNP and gene annotation information with a graphical viewer. We have applied this software to public barley expressed sequences, and the resulting database is available over the Internet. SNPs can be viewed and searched by sequence, functional annotation or predicted synteny with a reference genome, in this case rice. The correlation between SNPs and barley cultivar, expressed tissue type and development stage has been collated for ease of exploration. An average of one SNP per 240 bp was identified, with SNPs more prevalent in the 5' regions and simple sequence repeat (SSR) flanking sequences. Overall, autoSNPdb can provide a wealth of genetic polymorphism information for any species for which sequence data are available.

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