BACKGROUND: Accurate detection of polymorphisms with a next generation sequencer data is an important element of current genetic analysis. However, there is still no detection pipeline that is completely reliable. RESULT: We demonstrate two new detection methods of polymorphisms focusing on the Polymorphic Edge (PED). In the matching between two homologous sequences, the first mismatched base to appear is the SNP, or the edge of the structural variation. The first method is based on k-mers from short reads and detects polymorphic edges with k-mers for which there is no match between target and control, making it possible to detect SNPs by direct comparison of short-reads in two datasets (target and control) without a reference genome sequence. The second method is based on bidirectional alignment to detect polymorphic edges, not only SNPs but also insertions, deletions, inversions and translocations. Using these two methods, we succeed in making a high-quality comparison map between rice cultivars showing good match to the theoretical value of introgression, and in detecting specific large deletions across cultivars. CONCLUSIONS: Using Polymorphic Edge Detection (PED), the k-mer method is able to detect SNPs by direct comparison of short-reads in two datasets without genomic alignment step, and the bidirectional alignment method is able to detect SNPs and structural variations from even single-end short-reads. The PED is an efficient tool to obtain accurate data for both SNPs and structural variations. AVAILABILITY: The PED software is available at: https://github.com/akiomiyao/ped .

BACKGROUND: Transposition event detection of transposable element (TE) in the genome using short reads from the next-generation sequence (NGS) was difficult, because the nucleotide sequence of TE itself is repetitive, making it difficult to identify locations of its insertions by alignment programs for NGS. We have developed a program with a new algorithm to detect the transpositions from NGS data. RESULTS: In the process of tool development, we used next-generation sequence (NGS) data of derivative lines (ttm2 and ttm5) of japonica rice cv. Nipponbare, regenerated through cell culture. The new program, called a transposon insertion finder (TIF), was applied to detect the de novo transpositions of Tos17 in the regenerated lines. TIF searched 300 million reads of a line within 20 min, identifying 4 and 12 de novo transposition in ttm2 and ttm5 lines, respectively. All of the transpositions were confirmed by PCR/electrophoresis and sequencing. Using the program, we also detected new transposon insertions of P-element from NGS data of Drosophila melanogaster. CONCLUSION: TIF operates to find the transposition of any elements provided that target site duplications (TSDs) are generated by their transpositions.

An animal genome database has been developed on a Unix workstation and maintained by a relational database management system. This database has focused on the comparative gene mapping between species to assist the mapping of the genes related to phenotypic traits in livestock. The linkage maps, cytogenetic maps, polymerase chain reaction primers of pig, cattle, mouse and human, and their references have been included in the database, and the correspondence among species have been stipulated in the database. In order to search the database effectively, the World Wide Web server (http://ws4.niai.affrc.go.jp/) and the electronic mail server system (e-mail: jgbase-mail@ niai.affrc.go.jp) have been developed on different Unix workstations. These servers are connected to the Internet.