ngs_backbone: a pipeline for read cleaning, mapping and SNP calling using Next Generation Sequence

BackgroundThe possibilities offered by next generation sequencing (NGS) platforms are revolutionizing biotechnological laboratories. Moreover, the combination of NGS sequencing and affordable high-throughput genotyping technologies is facilitating the rapid discovery and use of SNPs in non-model species. However, this abundance of sequences and polymorphisms creates new software needs. To fulfill these needs, we have developed a powerful, yet easy-to-use application.ResultsThe ngs_backbone software is a parallel pipeline capable of analyzing Sanger, 454, Illumina and SOLiD (Sequencing by Oligonucleotide Ligation and Detection) sequence reads. Its main supported analyses are: read cleaning, transcriptome assembly and annotation, read mapping and single nucleotide polymorphism (SNP) calling and selection. In order to build a truly useful tool, the software development was paired with a laboratory experiment. All public tomato Sanger EST reads plus 14.2 million Illumina reads were employed to test the tool and predict polymorphism in tomato. The cleaned reads were mapped to the SGN tomato transcriptome obtaining a coverage of 4.2 for Sanger and 8.5 for Illumina. 23,360 single nucleotide variations (SNVs) were predicted. A total of 76 SNVs were experimentally validated, and 85% were found to be real.Conclusionsngs_backbone is a new software package capable of analyzing sequences produced by NGS technologies and predicting SNVs with great accuracy. In our tomato example, we created a highly polymorphic collection of SNVs that will be a useful resource for tomato researchers and breeders. The software developed along with its documentation is freely available under the AGPL license and can be downloaded from http://bioinf.comav.upv.es/ngs_backbone/ or http://github.com/JoseBlanca/franklin.

[1]  Paul Flicek,et al.  Sense from sequence reads: methods for alignment and assembly , 2009, Nature Methods.

[2]  M. Metzker.  Sequencing technologies — the next generation , 2010, Nature Reviews Genetics.

[3]  W. Williams,et al.  Evolution of Crop Plants. , 1977 .

[4]  Naomi S. Altman,et al.  Comparison of next generation sequencing technologies for transcriptome characterization , 2009, BMC Genomics.

[5]  S. Tanksley,et al.  RFLP analysis of phylogenetic relationships and genetic variation in the genus Lycopersicon , 1990, Theoretical and Applied Genetics.

[6]  Richard Durbin,et al.  Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .

[7]  Manolis Kellis,et al.  The Tasmanian Devil Transcriptome Reveals Schwann Cell Origins of a Clonally Transmissible Cancer , 2009, Science.

[8]  W. Babik,et al.  Heart transcriptome of the bank vole (Myodes glareolus): towards understanding the evolutionary variation in metabolic rate , 2010, BMC Genomics.

[9]  E. Kabelka,et al.  Discovery of single nucleotide polymorphisms in Lycopersicon esculentum by computer aided analysis of expressed sequence tags , 2004 .

[10]  C. N. Gundry,et al.  Amplicon melting analysis with labeled primers: a closed-tube method for differentiating homozygotes and heterozygotes. , 2003, Clinical chemistry.

[11]  Johan A. Grahnen,et al.  Transcriptome sequencing in an ecologically important tree species: assembly, annotation, and marker discovery , 2010, BMC Genomics.

[12]  Daniel J. Blankenberg,et al.  A framework for collaborative analysis of ENCODE data: making large-scale analyses biologist-friendly. , 2007, Genome research.

[13]  C. E. Williams,et al.  Phenetic relationships and levels of variability detected by restriction fragment length polymorphism and random amplified polymorphic DNA analysis of cultivated and wild accessions of Lycopersicon esculentum. , 1993, Genome.

[14]  J. Maloof,et al.  Sequence diversity in three tomato species: SNPs, markers, and molecular evolution , 2009, BMC Plant Biology.

[15]  T. Wetter,et al.  Using the miraEST assembler for reliable and automated mRNA transcript assembly and SNP detection in sequenced ESTs. , 2004, Genome research.

[16]  C. M. Rick.  Tomato: Lycopersicon esculentum (Solanaceae) , 1995 .

[17]  Cole Trapnell,et al.  Ultrafast and memory-efficient alignment of short DNA sequences to the human genome , 2009, Genome Biology.

[18]  Hui-Hsien Chou,et al.  DNA sequence quality trimming and vector removal , 2001, Bioinform..

[19]  M. DePristo,et al.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. , 2010, Genome research.

[20]  Gonçalo R. Abecasis,et al.  The Sequence Alignment/Map format and SAMtools , 2009, Bioinform..

[21]  D. Shibata,et al.  Expressed sequence tags from the laboratory-grown miniature tomato (Lycopersicon esculentum) cultivar Micro-Tom and mining for single nucleotide polymorphisms and insertions/deletions in tomato cultivars. , 2005, Gene.

[22]  Jia Liu,et al.  Diversity in conserved genes in tomato , 2007, BMC Genomics.

[23]  A. Baldo,et al.  Tomato SNP Discovery by EST Mining and Resequencing , 2005, Molecular Breeding.

[24]  Alexie Papanicolaou,et al.  Next generation transcriptomes for next generation genomes using est2assembly , 2009, BMC Bioinformatics.

[25]  C. Chilcott,et al.  Oligonucleotide array discovery of polymorphisms in cultivated tomato (Solanum lycopersicum L.) reveals patterns of SNP variation associated with breeding , 2009, BMC Genomics.