Reconstructing haplotypes from sequencing data is one of the major challenges in genetics. Haplotypes play a crucial role in many analyses, including genome-wide association studies and population genetics. Haplotype reconstruction becomes more difficult for higher numbers of homologous chromosomes, as it is often the case for polyploid plants. This complexity is compounded further by higher heterozygosity, which denotes the frequent presence of variants between haplotypes. We have designed Ranbow, a new tool for haplotype reconstruction of polyploid genome from short read sequencing data. Ranbow integrates all types of small variants in bi- and multi-allelic sites to reconstruct haplotypes. To evaluate Ranbow and currently available competing methods on real data, we have created and released a real gold standard dataset from sweet potato sequencing data. Our evaluations on real and simulated data clearly show Ranbow's superior performance in terms of accuracy, haplotype length, memory usage, and running time. Specifically, Ranbow is one order of magnitude faster than the next best method. The efficiency and accuracy of Ranbow makes whole genome haplotype reconstruction of complex genome with higher ploidy feasible.

MOTIVATION: The reliable detection of genomic variation in resequencing data is still a major challenge, especially for variants larger than a few base pairs. Sequencing reads crossing boundaries of structural variation carry the potential for their identification, but are difficult to map. RESULTS: Here we present a method for 'split' read mapping, where prefix and suffix match of a read may be interrupted by a longer gap in the read-to-reference alignment. We use this method to accurately detect medium-sized insertions and long deletions with precise breakpoints in genomic resequencing data. Compared with alternative split mapping methods, SplazerS significantly improves sensitivity for detecting large indel events, especially in variant-rich regions. Our method is robust in the presence of sequencing errors as well as alignment errors due to genomic mutations/divergence, and can be used on reads of variable lengths. Our analysis shows that SplazerS is a versatile tool applicable to unanchored or single-end as well as anchored paired-end reads. In addition, application of SplazerS to targeted resequencing data led to the interesting discovery of a complete, possibly functional gene retrocopy variant. AVAILABILITY: SplazerS is available from http://www.seqan.de/projects/ splazers. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: We developed Breakpointer, a fast algorithm to locate breakpoints of structural variants (SVs) from single-end reads produced by next-generation sequencing. By taking advantage of local non-uniform read distribution and misalignments created by SVs, Breakpointer scans the alignment of single-end reads to identify regions containing potential breakpoints. The detection of such breakpoints can indicate insertions longer than the read length and SVs located in repetitve regions which might be missd by other methods. Thus, Breakpointer complements existing methods to locate SVs from single-end reads. AVAILABILITY: https://github.com/ruping/Breakpointer CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary material is available at Bioinformatics online.

MOTIVATION: A major challenge in regulatory genomics is the identification of associations between functional categories of genes (e.g. tissues, metabolic pathways) and their regulating transcription factors (TFs). While, for a limited number of categories, the regulating TFs are already known, still for many functional categories the responsible factors remain to be elucidated. RESULTS: We put forward a novel method (PASTAA) for detecting transcriptions factors associated with functional categories, which utilizes the prediction of binding affinities of a TF to promoters. This binding strength information is compared to the likelihood of membership of the corresponding genes in the functional category under study. Coherence between the two ranked datasets is seen as an indicator of association between a TF and the category. PASTAA is applied primarily to the determination of TFs driving tissue-specific expression. We show that PASTAA is capable of recovering many TFs acting tissue specifically and, in addition, provides novel associations so far not detected by alternative methods. The application of PASTAA to detect TFs involved in the regulation of tissue-specific gene expression revealed a remarkable number of experimentally supported associations. The validated success for various datasets implies that PASTAA can directly be applied for the detection of TFs associated with newly derived gene sets. AVAILABILITY: The PASTAA source code as well as a corresponding web interface is freely available at http://trap.molgen.mpg.de.

MOTIVATION: Alternative splicing is currently seen to explain the vast disparity between the number of predicted genes in the human genome and the highly diverse proteome. The mapping of expressed sequences tag (EST) consensus sequences derived from the GeneNest database onto the genome provides an efficient way of predicting exon-intron boundaries, gene structure and alternative splicing events. However, the alternative splicing events are obscured by a large number of putatively artificial exon boundaries arising due to genomic contamination or alignment errors. The current work describes a methodology to associate quality values to the predicted exon-intron boundaries. High quality exon-intron boundaries are used to predict constitutive and alternative splicing ranked by confidence values, aiming to facilitate large-scale analysis of alternative splicing and splicing in general. RESULTS: Applying the current methodology, constitutive splicing is observed in 33,270 EST clusters, out of which 45% are alternatively spliced. The classification derived from the computed confidence values for 17 of these splice events frequently correlate (15/17) with RT-PCR experiments performed for 40 different tissue samples. As an application of the confidence measure, an evaluation of distribution of alternative splicing revealed that majority of variants correspond to the coding regions of the genes. However, still a significant fraction maps to non-coding regions, thereby indicating a functional relevance of alternative splicing in untranslated regions. AVAILABILITY: The predicted alternative splice variants are visualized in the SpliceNest database at http://splicenest.molgen.mpg.de