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Jacqueline Batley

Publications and source records attributed to Jacqueline Batley.

6 recordsLinked to original sources

SNPServer: a real-time SNP discovery tool.

SNPServer is a real-time flexible tool for the discovery of SNPs (single nucleotide polymorphisms) within DNA sequence data. The program uses BLAST, to identify related sequences, and CAP3, to cluster and align these sequences. The alignments are parsed to the SNP discovery software autoSNP, a program that detects SNPs and insertion/deletion polymorphisms (indels). Alternatively, lists of related sequences or pre-assembled sequences may be entered for SNP discovery. SNPServer and autoSNP use redundancy to differentiate between candidate SNPs and sequence errors. For each candidate SNP, two measures of confidence are calculated, the redundancy of the polymorphism at a SNP locus and the co-segregation of the candidate SNP with other SNPs in the alignment. SNPServer is available at http://hornbill.cspp.latrobe.edu.au/snpdiscovery.html.

Internet↗

Brassica ASTRA: an integrated database for Brassica genomic research.

Brassica ASTRA is a public database for genomic information on Brassica species. The database incorporates expressed sequences with Swiss-Prot and GenBank comparative sequence annotation as well as secondary Gene Ontology (GO) annotation derived from the comparison with Arabidopsis TAIR GO annotations. Simple sequence repeat molecular markers are identified within resident sequences and mapped onto the closely related Arabidopsis genome sequence. Bacterial artificial chromosome (BAC) end sequences derived from the Multinational Brassica Genome Project are also mapped onto the Arabidopsis genome sequence enabling users to identify candidate Brassica BACs corresponding to syntenic regions of Arabidopsis. This information is maintained in a MySQL database with a web interface providing the primary means of interrogation. The database is accessible at http://hornbill.cspp.latrobe.edu.au.

Brassica↗

Simple sequence repeat marker loci discovery using SSR primer.

SUMMARY: Simple sequence repeats (SSRs) have become important molecular markers for a broad range of applications, such as genome mapping and characterization, phenotype mapping, marker assisted selection of crop plants and a range of molecular ecology and diversity studies. With the increase in the availability of DNA sequence information, an automated process to identify and design PCR primers for amplification of SSR loci would be a useful tool in plant breeding programs. We report an application that integrates SPUTNIK, an SSR repeat finder, with Primer3, a PCR primer design program, into one pipeline tool, SSR Primer. On submission of multiple FASTA formatted sequences, the script screens each sequence for SSRs using SPUTNIK. The results are parsed to Primer3 for locus-specific primer design. The script makes use of a Web-based interface, enabling remote use. AVAILABILITY: This program has been written in PERL and is freely available for non-commercial users by request from the authors. The Web-based version may be accessed at http://hornbill.cspp.latrobe.edu.au/

Algorithms↗

Redundancy based detection of sequence polymorphisms in expressed sequence tag data using autoSNP.

UNLABELLED: AutoSNP is a program to detect single nucleotide polymorphisms (SNPs) and insertion/deletion polymorphisms (indels) in expressed sequence tag (EST) data. The program uses d2cluster and cap3 to cluster and align EST sequences, and uses redundancy to differentiate between candidate SNPs and sequence errors. Candidate polymorphisms are identified as occurring in multiple reads within an alignment. For each candidate SNP, two measures of confidence are calculated, the redundancy of the polymorphism at a SNP locus and the co segregation of the candidate SNP with other SNPs in the alignment. AVAILABILITY: The program was written in PERL and is freely available to non-commercial users by request from the authors.

Cluster Analysis↗

Mining for single nucleotide polymorphisms and insertions/deletions in maize expressed sequence tag data.

We have developed a computer based method to identify candidate single nucleotide polymorphisms (SNPs) and small insertions/deletions from expressed sequence tag data. Using a redundancy-based approach, valid SNPs are distinguished from erroneous sequence by their representation multiple times in an alignment of sequence reads. A second measure of validity was also calculated based on the cosegregation of the SNP pattern between multiple SNP loci in an alignment. The utility of this method was demonstrated by applying it to 102,551 maize (Zea mays) expressed sequence tag sequences. A total of 14,832 candidate polymorphisms were identified with an SNP redundancy score of two or greater. Segregation of these SNPs with haplotype indicates that candidate SNPs with high redundancy and cosegregation confidence scores are likely to represent true SNPs. This was confirmed by validation of 264 candidate SNPs from 27 loci, with a range of redundancy and cosegregation scores, in four inbred maize lines. The SNP transition/transversion ratio and insertion/deletion size frequencies correspond to those observed by direct sequencing methods of SNP discovery and suggest that the majority of predicted SNPs and insertion/deletions identified using this approach represent true genetic variation in maize.

Base Sequence↗