Conifers have dominated forests for more than 200 million years and are of huge ecological and economic importance. Here we present the draft assembly of the 20-gigabase genome of Norway spruce (Picea abies), the first available for any gymnosperm. The number of well-supported genes (28,354) is similar to the .100 times smaller genome of Arabidopsis thaliana, and there is no evidence of a recent whole-genome duplication in the gymnosperm lineage. Instead, the large genome size seems to result from the slow and steady accumulation of a diverse set of long-terminal repeat transposable elements, possibly owing to the lack of an efficient elimination mechanism. Comparative sequencing of Pinus sylvestris, Abies sibirica, Juniperus communis, Taxus baccata and Gnetum gnemon reveals that the transposable element diversity is shared among extant conifers. Expression of 24-nucleotide small RNAs, previously implicated in transposable element silencing, is tissue-specific and much lower than in other plants. We further identify numerous long (.10,000 base pairs) introns, gene-like fragments, uncharacterized long non-coding RNAs and short RNAs. This opens up new genomic avenues for conifer forestry and breeding.

BackgroundThe process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished genome sequences remains challenging. Many genome assembly tools are available, but they differ greatly in terms of their performance (speed, scalability, hardware requirements, acceptance of newer read technologies) and in their final output (composition of assembled sequence). More importantly, it remains largely unclear how to best assess the quality of assembled genome sequences. The Assemblathon competitions are intended to assess current state-of-the-art methods in genome assembly.ResultsIn Assemblathon 2, we provided a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and snake). This resulted in a total of 43 submitted assemblies from 21 participating teams. We evaluated these assemblies using a combination of optical map data, Fosmid sequences, and several statistical methods. From over 100 different metrics, we chose ten key measures by which to assess the overall quality of the assemblies.ConclusionsMany current genome assemblers produced useful assemblies, containing a significant representation of their genes and overall genome structure. However, the high degree of variability between the entries suggests that there is still much room for improvement in the field of genome assembly and that approaches which work well in assembling the genome of one species may not necessarily work well for another.

BackgroundNext Generation Sequencing technologies are able to provide high genome coverages at a relatively low cost. However, due to limited reads' length (from 30 bp up to 200 bp), specific bioinformatics problems have become even more difficult to solve. De novo assembly with short reads, for example, is more complicated at least for two reasons: first, the overall amount of "noisy" data to cope with increased and, second, as the reads' length decreases the number of unsolvable repeats grows. Our work's aim is to go at the root of the problem by providing a pre-processing tool capable to produce (in-silico) longer and highly accurate sequences from a collection of Next Generation Sequencing reads.ResultsIn this paper a seed-and-extend local assembler is presented. The kernel algorithm is a loop that, starting from a read used as seed, keeps extending it using heuristics whose main goal is to produce a collection of error-free and longer sequences. In particular, GapFiller carefully detects reliable overlaps and operates clustering similar reads in order to reconstruct the missing part between the two ends of the same insert. Our tool's output has been validated on 24 experiments using both simulated and real paired reads datasets. The output sequences are declared correct when the seed-mate is found. In the experiments performed, GapFiller was able to extend high percentages of the processed seeds and find their mates, with a false positives rate that turned out to be nearly negligible.ConclusionsGapFiller, starting from a sufficiently high short reads coverage, is able to produce high coverages of accurate longer sequences (from 300 bp up to 3500 bp). The procedure to perform safe extensions, together with the mate-found check, turned out to be a powerful criterion to guarantee contigs' correctness. GapFiller has further potential, as it could be applied in a number of different scenarios, including the post-processing validation of insertions/deletions detection pipelines, pre-processing routines on datasets for de novo assembly pipelines, or in any hierarchical approach designed to assemble, analyse or validate pools of sequences.

Here we describe the SweGen data set, a comprehensive map of genetic variation in the Swedish population. These data represent a basic resource for clinical genetics laboratories as well as for sequencing-based association studies by providing information on genetic variant frequencies in a cohort that is well matched to national patient cohorts. To select samples for this study, we first examined the genetic structure of the Swedish population using high-density SNP-array data from a nation-wide cohort of over 10 000 Swedish-born individuals included in the Swedish Twin Registry. A total of 1000 individuals, reflecting a cross-section of the population and capturing the main genetic structure, were selected for whole-genome sequencing. Analysis pipelines were developed for automated alignment, variant calling and quality control of the sequencing data. This resulted in a genome-wide collection of aggregated variant frequencies in the Swedish population that we have made available to the scientific community through the website https://swefreq.nbis.se. A total of 29.2 million single-nucleotide variants and 3.8 million indels were detected in the 1000 samples, with 9.9 million of these variants not present in current databases. Each sample contributed with an average of 7199 individual-specific variants. In addition, an average of 8645 larger structural variants (SVs) were detected per individual, and we demonstrate that the population frequencies of these SVs can be used for efficient filtering analyses. Finally, our results show that the genetic diversity within Sweden is substantial compared with the diversity among continental European populations, underscoring the relevance of establishing a local reference data set.

BackgroundThe use of short reads from High Throughput Sequencing (HTS) techniques is now commonplace in de novo assembly. Yet, obtaining contiguous assemblies from short reads is challenging, thus making scaffolding an important step in the assembly pipeline. Different algorithms have been proposed but many of them use the number of read pairs supporting a linking of two contigs as an indicator of reliability. This reasoning is intuitive, but fails to account for variation in link count due to contig features.We have also noted that published scaffolders are only evaluated on small datasets using output from only one assembler. Two issues arise from this. Firstly, some of the available tools are not well suited for complex genomes. Secondly, these evaluations provide little support for inferring a software’s general performance.ResultsWe propose a new algorithm, implemented in a tool called BESST, which can scaffold genomes of all sizes and complexities and was used to scaffold the genome of P. abies (20 Gbp). We performed a comprehensive comparison of BESST against the most popular stand-alone scaffolders on a large variety of datasets. Our results confirm that some of the popular scaffolders are not practical to run on complex datasets. Furthermore, no single stand-alone scaffolder outperforms the others on all datasets. However, BESST fares favorably to the other tested scaffolders on GAGE datasets and, moreover, outperforms the other methods when library insert size distribution is wide.ConclusionWe conclude from our results that information sources other than the quantity of links, as is commonly used, can provide useful information about genome structure when scaffolding.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2105-15-281) contains supplementary material, which is available to authorized users.

In just the last decade, a multitude of bio-technologies and software pipelines have emerged to revolutionize genomics. To further their central goal, they aim to accelerate and improve the quality of de novo whole-genome assembly starting from short DNA sequences/reads. However, the performance of each of these tools is contingent on the length and quality of the sequencing data, the structure and complexity of the genome sequence, and the resolution and quality of long-range information. Furthermore, in the absence of any metric that captures the most fundamental “features” of a high-quality assembly, there is no obvious recipe for users to select the most desirable assembler/assembly. This situation has prompted the scientific community to rely on crowd-sourcing through international competitions, such as Assemblathons or GAGE, with the intention of identifying the best assembler(s) and their features. Somewhat circuitously, the only available approach to gauge de novo assemblies and assemblers relies solely on the availability of a high-quality fully assembled reference genome sequence. Still worse, reference-guided evaluations are often both difficult to analyze, leading to conclusions that are difficult to interpret. In this paper, we circumvent many of these issues by relying upon a tool, dubbed , which is capable of evaluating de novo assemblies from the read-layouts even when no reference exists. We extend the FRCurve approach to cases where lay-out information may have been obscured, as is true in many deBruijn-graph-based algorithms. As a by-product, FRCurve now expands its applicability to a much wider class of assemblers – thus, identifying higher-quality members of this group, their inter-relations as well as sensitivity to carefully selected features, with or without the support of a reference sequence or layout for the reads. The paper concludes by reevaluating several recently conducted assembly competitions and the datasets that have resulted from them.

The high‐throughput capacities of the Illumina sequencing platforms and the possibility to label samples individually have encouraged wide use of sample multiplexing. However, this practice results in read misassignment (usually <1%) across samples sequenced on the same lane. Alarmingly high rates of read misassignment of up to 10% were reported for lllumina sequencing machines with exclusion amplification chemistry. This may make use of these platforms prohibitive, particularly in studies that rely on low‐quantity and low‐quality samples, such as historical and archaeological specimens. Here, we use barcodes, short sequences that are ligated to both ends of the DNA insert, to directly quantify the rate of index hopping in 100‐year old museum‐preserved gorilla (Gorilla beringei) samples. Correcting for multiple sources of noise, we identify on average 0.470% of reads containing a hopped index. We show that sample‐specific quantity of misassigned reads depends on the number of reads that any given sample contributes to the total sequencing pool, so that samples with few sequenced reads receive the greatest proportion of misassigned reads. This particularly affects ancient DNA samples, as these frequently differ in their DNA quantity and endogenous content. Through simulations we show that even low rates of index hopping, as reported here, can lead to biases in ancient DNA studies when multiplexing samples with vastly different quantities of endogenous material.

In pulmonary sarcoidosis, CD4+ T-cells expressing T-cell receptor Vα2.3 accumulate in the lungs of HLA-DRB1*03 + patients. To investigate T-cell receptor-HLA-DRB1*03 interactions underlying recognition of hitherto unknown antigens, we performed detailed analyses of T-cell receptor expression on bronchoalveolar lavage fluid CD4 + T-cells from sarcoidosis patients. Pulmonary sarcoidosis patients (n=43) underwent bronchoscopy with bronchoalveolar lavage. T-cell receptor α and β chains of CD4 + T-cells were analysed by flow cytometry, DNA-sequenced, and threedimensional molecular models of T-cell receptor-HLA-DRB1*03 complexes generated.Simultaneous expression of Vα2.3 with the Vβ22 chain was identified in the lungs of all HLA-DRB1*03 + patients. Accumulated Vα2.3/Vβ22-expressing T-cells were highly clonal, with identical or near-identical Vα2.3 chain sequences and inter-patient similarities in Vβ22 chain amino acid distribution. Molecular modelling revealed specific T-cell receptor-HLA-DRB1*03-peptide interactions, with a previously identified, sarcoidosis-associated vimentin peptide, (Vim)429-443 DSLPLVDTHSKRTLL, matching both the HLA peptide-binding cleft and distinct T-cell receptor features perfectly.We demonstrate, for the first time, the accumulation of large clonal populations of specific Vα2.3/Vβ22 T-cell receptor-expressing CD4 + T-cells in the lungs of HLA-DRB1*03 + sarcoidosis patients. Several distinct contact points between Vα2.3/Vβ22 receptors and HLA-DRB1*03 molecules suggest presentation of prototypic vimentin-derived peptides. @ERSpublications Clonal CD4 + lung T-cells associating with HLA-DRB1*03 molecules indicate specific antigens in pulmonary sarcoidosis