NucBreak: location of structural errors in a genome assembly by using paired-end Illumina reads

BACKGROUND

Advances in whole genome sequencing strategies have provided the opportunity for genomic and comparative genomic analysis of a vast variety of organisms. The analysis results are highly dependent on the quality of the genome assemblies used. Assessment of the assembly accuracy may significantly increase the reliability of the analysis results and is therefore of great importance.

RESULTS

Here, we present a new tool called NucBreak aimed at localizing structural errors in assemblies, including insertions, deletions, duplications, inversions, and different inter- and intra-chromosomal rearrangements. The approach taken by existing alternative tools is based on analysing reads that do not map properly to the assembly, for instance discordantly mapped reads, soft-clipped reads and singletons. NucBreak uses an entirely different and unique method to localise the errors. It is based on analysing the alignments of reads that are properly mapped to an assembly and exploit information about the alternative read alignments. It does not annotate detected errors. We have compared NucBreak with other existing assembly accuracy assessment tools, namely Pilon, REAPR, and FRCbam as well as with several structural variant detection tools, including BreakDancer, Lumpy, and Wham, by using both simulated and real datasets.

CONCLUSIONS

The benchmarking results have shown that NucBreak in general predicts assembly errors of different types and sizes with relatively high sensitivity and with lower false discovery rate than the other tools. Such a balance between sensitivity and false discovery rate makes NucBreak a good alternative to the existing assembly accuracy assessment tools and SV detection tools. NucBreak is freely available at https://github.com/uio-bmi/NucBreak under the MPL license.

NucDiff: in-depth characterization and annotation of differences between two sets of DNA sequences

Background

Comparing sets of sequences is a situation frequently encountered in bioinformatics, examples being comparing an assembly to a reference genome, or two genomes to each other. The purpose of the comparison is usually to find where the two sets differ, e.g. to find where a subsequence is repeated or deleted, or where insertions have been introduced. Such comparisons can be done using whole-genome alignments. Several tools for making such alignments exist, but none of them 1) provides detailed information about the types and locations of all differences between the two sets of sequences, 2) enables visualisation of alignment results at different levels of detail, and 3) carefully takes genomic repeats into consideration.

Results

We here present NucDiff, a tool aimed at locating and categorizing differences between two sets of closely related DNA sequences. NucDiff is able to deal with very fragmented genomes, repeated sequences, and various local differences and structural rearrangements. NucDiff determines differences by a rigorous analysis of alignment results obtained by the NUCmer, delta-filter and show-snps programs in the MUMmer sequence alignment package. All differences found are categorized according to a carefully defined classification scheme covering all possible differences between two sequences. Information about the differences is made available as GFF3 files, thus enabling visualisation using genome browsers as well as usage of the results as a component in an analysis pipeline. NucDiff was tested with varying parameters for the alignment step and compared with existing alternatives, called QUAST and dnadiff.

Conclusions

We have developed a whole genome alignment difference classification scheme together with the program NucDiff for finding such differences. The proposed classification scheme is comprehensive and can be used by other tools. NucDiff performs comparably to QUAST and dnadiff but gives much more detailed results that can easily be visualized. NucDiff is freely available on https://github.com/uio-cels/NucDiff under the MPL license.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1748-z) contains supplementary material, which is available to authorized users.

GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome

Background

Recent large-scale undertakings such as ENCODE and Roadmap Epigenomics have generated experimental data mapped to the human reference genome (as genomic tracks) representing a variety of functional elements across a large number of cell types. Despite the high potential value of these publicly available data for a broad variety of investigations, little attention has been given to the analytical methodology necessary for their widespread utilisation.

Findings

We here present a first principled treatment of the analysis of collections of genomic tracks. We have developed novel computational and statistical methodology to permit comparative and confirmatory analyses across multiple and disparate data sources. We delineate a set of generic questions that are useful across a broad range of investigations and discuss the implications of choosing different statistical measures and null models. Examples include contrasting analyses across different tissues or diseases. The methodology has been implemented in a comprehensive open-source software system, the GSuite HyperBrowser. To make the functionality accessible to biologists, and to facilitate reproducible analysis, we have also developed a web-based interface providing an expertly guided and customizable way of utilizing the methodology. With this system, many novel biological questions can flexibly be posed and rapidly answered.

Conclusions

Through a combination of streamlined data acquisition, interoperable representation of dataset collections, and customizable statistical analysis with guided setup and interpretation, the GSuite HyperBrowser represents a first comprehensive solution for integrative analysis of track collections across the genome and epigenome. The software is available at: https://hyperbrowser.uio.no.

Annually resolved North Atlantic marine climate over the last millennium

Owing to the lack of absolutely dated oceanographic information before the modern instrumental period, there is currently significant debate as to the role played by North Atlantic Ocean dynamics in previous climate transitions (for example, Medieval Climate Anomaly-Little Ice Age, MCA-LIA). Here we present analyses of a millennial-length, annually resolved and absolutely dated marine δ¹⁸O archive. We interpret our record of oxygen isotope ratios from the shells of the long-lived marine bivalve Arctica islandica (δ¹⁸O-shell), from the North Icelandic shelf, in relation to seawater density variability and demonstrate that solar and volcanic forcing coupled with ocean circulation dynamics are key drivers of climate variability over the last millennium. During the pre-industrial period (AD 1000–1800) variability in the sub-polar North Atlantic leads changes in Northern Hemisphere surface air temperatures at multi-decadal timescales, indicating that North Atlantic Ocean dynamics played an active role in modulating the response of the atmosphere to solar and volcanic forcing.

A lack of annually resolved climate records from the marine archive limits our understanding of oceanic processes. Here, the authors present a millennial-length, annually-resolved and absolutely-dated marine δ¹⁸O record from the shells of marine bivalves and offer insight into North Atlantic climate dynamics.

Improved metagenome assemblies and taxonomic binning using long-read circular consensus sequence data

DNA assembly is a core methodological step in metagenomic pipelines used to study the structure and function within microbial communities. Here we investigate the utility of Pacific Biosciences long and high accuracy circular consensus sequencing (CCS) reads for metagenomic projects. We compared the application and performance of both PacBio CCS and Illumina HiSeq data with assembly and taxonomic binning algorithms using metagenomic samples representing a complex microbial community. Eight SMRT cells produced approximately 94 Mb of CCS reads from a biogas reactor microbiome sample that averaged 1319 nt in length and 99.7% accuracy. CCS data assembly generated a comparative number of large contigs greater than 1 kb, to those assembled from a ~190x larger HiSeq dataset (~18 Gb) produced from the same sample (i.e approximately 62% of total contigs). Hybrid assemblies using PacBio CCS and HiSeq contigs produced improvements in assembly statistics, including an increase in the average contig length and number of large contigs. The incorporation of CCS data produced significant enhancements in taxonomic binning and genome reconstruction of two dominant phylotypes, which assembled and binned poorly using HiSeq data alone. Collectively these results illustrate the value of PacBio CCS reads in certain metagenomics applications.

The khmer software package: enabling efficient nucleotide sequence analysis

The khmer package is a freely available software library for working efficiently with fixed length DNA words, or k-mers. khmer provides implementations of a probabilistic k-mer counting data structure, a compressible De Bruijn graph representation, De Bruijn graph partitioning, and digital normalization. khmer is implemented in C++ and Python, and is freely available under the BSD license at  https://github.com/dib-lab/khmer/.

The stringlike genes of the limpet Patella vulgata

As a first step in analyzing the function of a cdc25 homolog during the embryonic development of Patella vulgata (Pv), genomic clones encoding these stringlike proteins (Stl) were isolated and characterized. These clones belong to four groups which are derived from different regions of the Pv genome. As the sequences of Stl genes from two of these groups are almost identical, we suggest that these genes represent copies of the same gene. The Stl3 gene, which has been analyzed in detail, consists of four exons separated by three introns. Its sequence encodes a 250-amino-acid protein with a calculated weight of 28 kDa. The Stl protein contains regions conserved in all other cdc25 proteins. Stl messengers are not stored maternally in Pv oocytes and Stl transcription only starts after the first embryonic cleavages.

Isolation and composition of the constitutive agglutinins from haploid Saccharomyces cerevisiae cells

Sex-specific agglutinins from the cell surface of haploid cells of Saccharomyces cerevisiae (X2180, mta and mt alpha) were purified and analysed. The constitutive agglutinin from mta cells was extractable with 3 mM dithiothreitol. It was shown to be a glycoprotein (3% mannose) with an apparent Mr of 43,000 based on gel filtration, but in SDS-PAGE it behaved as a much smaller molecule (Mr between 18,000 and 26,000). About one in three amino acids was a hydroxyamino acid. Its biological activity was resistant to boiling for 1 h, but sensitive to pronase. Intact mt alpha cells retained their agglutinability in the presence of dithiothreitol but limited trypsinizing released a biologically active agglutinin fragment. It had an apparent Mr of 320,000 (gel filtration). When analysed by SDS-PAGE, a single diffuse band with an apparent Mr of 225,000 was observed. The protein was 94% (w/w) mannose with a trace of N-acetyl glucosamine. Its biological activity was almost completely lost after boiling for 1 h. Both agglutinins behaved as monovalent molecules and specifically inhibited the biological activity of both noninduced and pheromone-induced cells. Pheromone treatment of mta cells resulted in an apparent 32-fold increase in agglutinin activity at the cell surface, whereas pheromone treatment of mt alpha cells only doubled the apparent agglutinin activity.