2,049 research outputs found

    On the Inversion-Indel Distance

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    Willing E, Zaccaria S, Dias Vieira Braga M, Stoye J. On the Inversion-Indel Distance. BMC Bioinformatics. 2013;14(Suppl 15: Proc. of RECOMB-CG 2013): S3.Background The inversion distance, that is the distance between two unichromosomal genomes with the same content allowing only inversions of DNA segments, can be computed thanks to a pioneering approach of Hannenhalli and Pevzner in 1995. In 2000, El-Mabrouk extended the inversion model to allow the comparison of unichromosomal genomes with unequal contents, thus insertions and deletions of DNA segments besides inversions. However, an exact algorithm was presented only for the case in which we have insertions alone and no deletion (or vice versa), while a heuristic was provided for the symmetric case, that allows both insertions and deletions and is called the inversion-indel distance. In 2005, Yancopoulos, Attie and Friedberg started a new branch of research by introducing the generic double cut and join (DCJ) operation, that can represent several genome rearrangements (including inversions). Among others, the DCJ model gave rise to two important results. First, it has been shown that the inversion distance can be computed in a simpler way with the help of the DCJ operation. Second, the DCJ operation originated the DCJ-indel distance, that allows the comparison of genomes with unequal contents, considering DCJ, insertions and deletions, and can be computed in linear time. Results In the present work we put these two results together to solve an open problem, showing that, when the graph that represents the relation between the two compared genomes has no bad components, the inversion-indel distance is equal to the DCJ-indel distance. We also give a lower and an upper bound for the inversion-indel distance in the presence of bad components

    The Drosophila genome nexus: a population genomic resource of 623 Drosophila melanogaster genomes, including 197 from a single ancestral range population.

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    Hundreds of wild-derived Drosophila melanogaster genomes have been published, but rigorous comparisons across data sets are precluded by differences in alignment methodology. The most common approach to reference-based genome assembly is a single round of alignment followed by quality filtering and variant detection. We evaluated variations and extensions of this approach and settled on an assembly strategy that utilizes two alignment programs and incorporates both substitutions and short indels to construct an updated reference for a second round of mapping prior to final variant detection. Utilizing this approach, we reassembled published D. melanogaster population genomic data sets and added unpublished genomes from several sub-Saharan populations. Most notably, we present aligned data from phase 3 of the Drosophila Population Genomics Project (DPGP3), which provides 197 genomes from a single ancestral range population of D. melanogaster (from Zambia). The large sample size, high genetic diversity, and potentially simpler demographic history of the DPGP3 sample will make this a highly valuable resource for fundamental population genetic research. The complete set of assemblies described here, termed the Drosophila Genome Nexus, presently comprises 623 consistently aligned genomes and is publicly available in multiple formats with supporting documentation and bioinformatic tools. This resource will greatly facilitate population genomic analysis in this model species by reducing the methodological differences between data sets

    Progressive Mauve: Multiple alignment of genomes with gene flux and rearrangement

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    Multiple genome alignment remains a challenging problem. Effects of recombination including rearrangement, segmental duplication, gain, and loss can create a mosaic pattern of homology even among closely related organisms. We describe a method to align two or more genomes that have undergone large-scale recombination, particularly genomes that have undergone substantial amounts of gene gain and loss (gene flux). The method utilizes a novel alignment objective score, referred to as a sum-of-pairs breakpoint score. We also apply a probabilistic alignment filtering method to remove erroneous alignments of unrelated sequences, which are commonly observed in other genome alignment methods. We describe new metrics for quantifying genome alignment accuracy which measure the quality of rearrangement breakpoint predictions and indel predictions. The progressive genome alignment algorithm demonstrates markedly improved accuracy over previous approaches in situations where genomes have undergone realistic amounts of genome rearrangement, gene gain, loss, and duplication. We apply the progressive genome alignment algorithm to a set of 23 completely sequenced genomes from the genera Escherichia, Shigella, and Salmonella. The 23 enterobacteria have an estimated 2.46Mbp of genomic content conserved among all taxa and total unique content of 15.2Mbp. We document substantial population-level variability among these organisms driven by homologous recombination, gene gain, and gene loss. Free, open-source software implementing the described genome alignment approach is available from http://gel.ahabs.wisc.edu/mauve .Comment: Revision dated June 19, 200

    Multi-platform discovery of haplotype-resolved structural variation in human genomes

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    Targeted genome modifications in soybean with CRISPR/Cas9

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    Background: The ability to selectively alter genomic DNA sequences in vivo is a powerful tool for basic and applied research. The CRISPR/Cas9 system precisely mutates DNA sequences in a number of organisms. Here, the CRISPR/Cas9 system is shown to be effective in soybean by knocking-out a green fluorescent protein (GFP) transgene and modifying nine endogenous loci. Results: Targeted DNA mutations were detected in 95% of 88 hairy-root transgenic events analyzed. Bi-allelic mutations were detected in events transformed with eight of the nine targeting vectors. Small deletions were the most common type of mutation produced, although SNPs and short insertions were also observed. Homoeologous genes were successfully targeted singly and together, demonstrating that CRISPR/Cas9 can both selectively, and generally, target members of gene families. Somatic embryo cultures were also modified to enable the production of plants with heritable mutations, with the frequency of DNA modifications increasing with culture time. A novel cloning strategy and vector system based on In-Fusion (R) cloning was developed to simplify the production of CRISPR/Cas9 targeting vectors, which should be applicable for targeting any gene in any organism. Conclusions: The CRISPR/Cas9 is a simple, efficient, and highly specific genome editing tool in soybean. Although some vectors are more efficient than others, it is possible to edit duplicated genes relatively easily. The vectors and methods developed here will be useful for the application of CRISPR/Cas9 to soybean and other plant species

    Genome maps across 26 human populations reveal population-specific patterns of structural variation.

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    Large structural variants (SVs) in the human genome are difficult to detect and study by conventional sequencing technologies. With long-range genome analysis platforms, such as optical mapping, one can identify large SVs (>2 kb) across the genome in one experiment. Analyzing optical genome maps of 154 individuals from the 26 populations sequenced in the 1000 Genomes Project, we find that phylogenetic population patterns of large SVs are similar to those of single nucleotide variations in 86% of the human genome, while ~2% of the genome has high structural complexity. We are able to characterize SVs in many intractable regions of the genome, including segmental duplications and subtelomeric, pericentromeric, and acrocentric areas. In addition, we discover ~60 Mb of non-redundant genome content missing in the reference genome sequence assembly. Our results highlight the need for a comprehensive set of alternate haplotypes from different populations to represent SV patterns in the genome
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