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July 7, 2019  |  

Tigmint: correcting assembly errors using linked reads from large molecules.

Genome sequencing yields the sequence of many short snippets of DNA (reads) from a genome. Genome assembly attempts to reconstruct the original genome from which these reads were derived. This task is difficult due to gaps and errors in the sequencing data, repetitive sequence in the underlying genome, and heterozygosity. As a result, assembly errors are common. In the absence of a reference genome, these misassemblies may be identified by comparing the sequencing data to the assembly and looking for discrepancies between the two. Once identified, these misassemblies may be corrected, improving the quality of the assembled sequence. Although tools exist to identify and correct misassemblies using Illumina paired-end and mate-pair sequencing, no such tool yet exists that makes use of the long distance information of the large molecules provided by linked reads, such as those offered by the 10x Genomics Chromium platform. We have developed the tool Tigmint to address this gap.To demonstrate the effectiveness of Tigmint, we applied it to assemblies of a human genome using short reads assembled with ABySS 2.0 and other assemblers. Tigmint reduced the number of misassemblies identified by QUAST in the ABySS assembly by 216 (27%). While scaffolding with ARCS alone more than doubled the scaffold NGA50 of the assembly from 3 to 8 Mbp, the combination of Tigmint and ARCS improved the scaffold NGA50 of the assembly over five-fold to 16.4 Mbp. This notable improvement in contiguity highlights the utility of assembly correction in refining assemblies. We demonstrate the utility of Tigmint in correcting the assemblies of multiple tools, as well as in using Chromium reads to correct and scaffold assemblies of long single-molecule sequencing.Scaffolding an assembly that has been corrected with Tigmint yields a final assembly that is both more correct and substantially more contiguous than an assembly that has not been corrected. Using single-molecule sequencing in combination with linked reads enables a genome sequence assembly that achieves both a high sequence contiguity as well as high scaffold contiguity, a feat not currently achievable with either technology alone.

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July 7, 2019  |  

A draft genome sequence for the Ixodes scapularis cell line, ISE6

Background: The tick cell line ISE6, derived from Ixodes scapularis, is commonly used for amplification and detection of arboviruses in environmental or clinical samples. Methods: To assist with sequence-based assays, we sequenced the ISE6 genome with single-molecule, long-read technology. Results: The draft assembly appears near complete based on gene content analysis, though it appears to lack some instances of repeats in this highly repetitive genome. The assembly appears to have separated the haplotypes at many loci. DNA short read pairs, used for validation only, mapped to the cell line assembly at a higher rate than they mapped to the Ixodes scapularis reference genome sequence. Conclusions: The assembly could be useful for filtering host genome sequence from sequence data obtained from cells infected with pathogens.

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July 7, 2019  |  

FusorSV: an algorithm for optimally combining data from multiple structural variation detection methods.

Comprehensive and accurate identification of structural variations (SVs) from next generation sequencing data remains a major challenge. We develop FusorSV, which uses a data mining approach to assess performance and merge callsets from an ensemble of SV-calling algorithms. It includes a fusion model built using analysis of 27 deep-coverage human genomes from the 1000 Genomes Project. We identify 843 novel SV calls that were not reported by the 1000 Genomes Project for these 27 samples. Experimental validation of a subset of these calls yields a validation rate of 86.7%. FusorSV is available at https://github.com/TheJacksonLaboratory/SVE .

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July 7, 2019  |  

The case for not masking away repetitive DNA

In the course of analyzing whole-genome data, it is common practice to mask or filter out repetitive regions of a genome, such as transposable elements and endogenous retroviruses, in order to focus only on genes and thus simplify the results. This Commentary is a plea from one member of the Mobile DNA community to all gene-centric researchers: please do not ignore the repetitive fraction of the genome. Please stop narrowing your findings by only analyzing a minority of the genome, and instead broaden your analyses to include the rich biology of repetitive and mobile DNA. In this article, I present four arguments supporting a case for retaining repetitive DNA in your genome-wide analysis.

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July 7, 2019  |  

Darwin: A genomics co-processor provides up to 15,000 X acceleration on long read assembly

of life in fundamental ways. Genomics data, however, is far outpacing Moore’s Law. Third-generation sequencing tech- nologies produce 100× longer reads than second generation technologies and reveal a much broader mutation spectrum of disease and evolution. However, these technologies incur prohibitively high computational costs. Over 1,300 CPU hours are required for reference-guided assembly of the human genome (using [47]), and over 15,600 CPU hours are required for de novo assembly [57]. This paper describes “Darwin” — a co-processor for genomic sequence alignment that, without sacrificing sensitivity, provides up to 15,000× speedup over the state-of-the-art software for reference-guided assembly of third-generation reads. Darwin achieves this speedup through hardware/algorithm co-design, trading more easily accelerated alignment for less memory-intensive filtering, and by optimizing the memory system for filtering. Darwin combines a hardware-accelerated version of D-SOFT, a novel filtering algorithm, with a hardware-accelerated version of GACT, a novel alignment algorithm. GACT generates near-optimal alignments of arbitrarily long genomic sequences using constant memory for the compute-intensive step. Dar- win is adaptable, with tunable speed and sensitivity to match emerging sequencing technologies and to meet the requirements of genomic applications beyond read assembly.

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July 7, 2019  |  

ARKS: chromosome-scale scaffolding of human genome drafts with linked read kmers.

The long-range sequencing information captured by linked reads, such as those available from 10× Genomics (10xG), helps resolve genome sequence repeats, and yields accurate and contiguous draft genome assemblies. We introduce ARKS, an alignment-free linked read genome scaffolding methodology that uses linked reads to organize genome assemblies further into contiguous drafts. Our approach departs from other read alignment-dependent linked read scaffolders, including our own (ARCS), and uses a kmer-based mapping approach. The kmer mapping strategy has several advantages over read alignment methods, including better usability and faster processing, as it precludes the need for input sequence formatting and draft sequence assembly indexing. The reliance on kmers instead of read alignments for pairing sequences relaxes the workflow requirements, and drastically reduces the run time.Here, we show how linked reads, when used in conjunction with Hi-C data for scaffolding, improve a draft human genome assembly of PacBio long-read data five-fold (baseline vs. ARKS NG50?=?4.6 vs. 23.1 Mbp, respectively). We also demonstrate how the method provides further improvements of a megabase-scale Supernova human genome assembly (NG50?=?14.74 Mbp vs. 25.94 Mbp before and after ARKS), which itself exclusively uses linked read data for assembly, with an execution speed six to nine times faster than competitive linked read scaffolders (~?10.5 h compared to 75.7 h, on average). Following ARKS scaffolding of a human genome 10xG Supernova assembly (of cell line NA12878), fewer than 9 scaffolds cover each chromosome, except the largest (chromosome 1, n?=?13).ARKS uses a kmer mapping strategy instead of linked read alignments to record and associate the barcode information needed to order and orient draft assembly sequences. The simplified workflow, when compared to that of our initial implementation, ARCS, markedly improves run time performances on experimental human genome datasets. Furthermore, the novel distance estimator in ARKS utilizes barcoding information from linked reads to estimate gap sizes. It accomplishes this by modeling the relationship between known distances of a region within contigs and calculating associated Jaccard indices. ARKS has the potential to provide correct, chromosome-scale genome assemblies, promptly. We expect ARKS to have broad utility in helping refine draft genomes.

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July 7, 2019  |  

The challenge of analyzing the sugarcane genome.

Reference genome sequences have become key platforms for genetics and breeding of the major crop species. Sugarcane is probably the largest crop produced in the world (in weight of crop harvested) but lacks a reference genome sequence. Sugarcane has one of the most complex genomes in crop plants due to the extreme level of polyploidy. The genome of modern sugarcane hybrids includes sub-genomes from two progenitors Saccharum officinarum and S. spontaneum with some chromosomes resulting from recombination between these sub-genomes. Advancing DNA sequencing technologies and strategies for genome assembly are making the sugarcane genome more tractable. Advances in long read sequencing have allowed the generation of a more complete set of sugarcane gene transcripts. This is supporting transcript profiling in genetic research. The progenitor genomes are being sequenced. A monoploid coverage of the hybrid genome has been obtained by sequencing BAC clones that cover the gene space of the closely related sorghum genome. The complete polyploid genome is now being sequenced and assembled. The emerging genome will allow comparison of related genomes and increase understanding of the functioning of this polyploidy system. Sugarcane breeding for traditional sugar and new energy and biomaterial uses will be enhanced by the availability of these genomic resources.

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July 7, 2019  |  

GtTR: Bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing.

Tandem repeats comprise significant proportion of the human genome including coding and regulatory regions. They are highly prone to repeat number variation and nucleotide mutation due to their repetitive and unstable nature, making them a major source of genomic variation between individuals. Despite recent advances in high throughput sequencing, analysis of tandem repeats in the context of complex diseases is still hindered by technical limitations. We report a novel targeted sequencing approach, which allows simultaneous analysis of hundreds of repeats. We developed a Bayesian algorithm, namely – GtTR – which combines information from a reference long-read dataset with a short read counting approach to genotype tandem repeats at population scale. PCR sizing analysis was used for validation.We used a PacBio long-read sequenced sample to generate a reference tandem repeat genotype dataset with on average 13% absolute deviation from PCR sizing results. Using this reference dataset GtTR generated estimates of VNTR copy number with accuracy within 95% high posterior density (HPD) intervals of 68 and 83% for capture sequence data and 200X WGS data respectively, improving to 87 and 94% with use of a PCR reference. We show that the genotype resolution increases as a function of depth, such that the median 95% HPD interval lies within 25, 14, 12 and 8% of the its midpoint copy number value for 30X, 200X WGS, 395X and 800X capture sequence data respectively. We validated nine targets by PCR sizing analysis and genotype estimates from sequencing results correlated well with PCR results.The novel genotyping approach described here presents a new cost-effective method to explore previously unrecognized class of repeat variation in GWAS studies of complex diseases at the population level. Further improvements in accuracy can be obtained by improving accuracy of the reference dataset.

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July 7, 2019  |  

HECIL: A Hybrid Error Correction Algorithm for Long Reads with Iterative Learning.

Second-generation DNA sequencing techniques generate short reads that can result in fragmented genome assemblies. Third-generation sequencing platforms mitigate this limitation by producing longer reads that span across complex and repetitive regions. However, the usefulness of such long reads is limited because of high sequencing error rates. To exploit the full potential of these longer reads, it is imperative to correct the underlying errors. We propose HECIL-Hybrid Error Correction with Iterative Learning-a hybrid error correction framework that determines a correction policy for erroneous long reads, based on optimal combinations of decision weights obtained from short read alignments. We demonstrate that HECIL outperforms state-of-the-art error correction algorithms for an overwhelming majority of evaluation metrics on diverse, real-world data sets including E. coli, S. cerevisiae, and the malaria vector mosquito A. funestus. Additionally, we provide an optional avenue of improving the performance of HECIL’s core algorithm by introducing an iterative learning paradigm that enhances the correction policy at each iteration by incorporating knowledge gathered from previous iterations via data-driven confidence metrics assigned to prior corrections.

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July 7, 2019  |  

An improved approach for reconstructing consensus repeats from short sequence reads

Repeat elements are important components of most eukaryotic genomes. Most existing tools for repeat analysis rely either on high quality reference genomes or existing repeat libraries. Thus, it is still challenging to do repeat analysis for species with highly repetitive or complex genomes which often do not have good reference genomes or annotated repeat libraries. Recently we developed a computational method called REPdenovo that constructs consensus repeat sequences directly from short sequence reads, which outperforms an existing tool called RepARK. One major issue with REPdenovo is that it doesn’t perform well for repeats with relatively high divergence rates or low copy numbers. In this paper, we present an improved approach for constructing consensus repeats directly from short reads. Comparing with the original REPdenovo, the improved approach uses more repeat-related k-mers and improves repeat assembly quality using a consensus-based k-mer processing method.

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July 7, 2019  |  

Loss of RXFP2 and INSL3 genes in Afrotheria shows that testicular descent is the ancestral condition in placental mammals.

Descent of testes from a position near the kidneys into the lower abdomen or into the scrotum is an important developmental process that occurs in all placental mammals, with the exception of five afrotherian lineages. Since soft-tissue structures like testes are not preserved in the fossil record and since key parts of the placental mammal phylogeny remain controversial, it has been debated whether testicular descent is the ancestral or derived condition in placental mammals. To resolve this debate, we used genomic data of 71 mammalian species and analyzed the evolution of two key genes (relaxin/insulin-like family peptide receptor 2 [RXFP2] and insulin-like 3 [INSL3]) that induce the development of the gubernaculum, the ligament that is crucial for testicular descent. We show that both RXFP2 and INSL3 are lost or nonfunctional exclusively in four afrotherians (tenrec, cape elephant shrew, cape golden mole, and manatee) that completely lack testicular descent. The presence of remnants of once functional orthologs of both genes in these afrotherian species shows that these gene losses happened after the split from the placental mammal ancestor. These “molecular vestiges” provide strong evidence that testicular descent is the ancestral condition, irrespective of persisting phylogenetic discrepancies. Furthermore, the absence of shared gene-inactivating mutations and our estimates that the loss of RXFP2 happened at different time points strongly suggest that testicular descent was lost independently in Afrotheria. Our results provide a molecular mechanism that explains the loss of testicular descent in afrotherians and, more generally, highlight how molecular vestiges can provide insights into the evolution of soft-tissue characters.

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July 7, 2019  |  

Meeting report: mobile genetic elements and genome plasticity 2018

The Mobile Genetic Elements and Genome Plasticity conference was hosted by Keystone Symposia in Santa Fe, NM USA, February 11–15, 2018. The organizers were Marlene Belfort, Evan Eichler, Henry Levin and Lynn Maquat. The goal of this conference was to bring together scientists from around the world to discuss the function of transposable elements and their impact on host species. Central themes of the meeting included recent innovations in genome analysis and the role of mobile DNA in disease and evolution. The conference included 200 scientists who participated in poster presentations, short talks selected from abstracts, and invited talks. A total of 58 talks were organized into eight sessions and two workshops. The topics varied from mechanisms of mobilization, to the structure of genomes and their defense strategies to protect against transposable elements.

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July 7, 2019  |  

Fast-SG: an alignment-free algorithm for hybrid assembly.

Long-read sequencing technologies are the ultimate solution for genome repeats, allowing near reference-level reconstructions of large genomes. However, long-read de novo assembly pipelines are computationally intense and require a considerable amount of coverage, thereby hindering their broad application to the assembly of large genomes. Alternatively, hybrid assembly methods that combine short- and long-read sequencing technologies can reduce the time and cost required to produce de novo assemblies of large genomes.Here, we propose a new method, called Fast-SG, that uses a new ultrafast alignment-free algorithm specifically designed for constructing a scaffolding graph using light-weight data structures. Fast-SG can construct the graph from either short or long reads. This allows the reuse of efficient algorithms designed for short-read data and permits the definition of novel modular hybrid assembly pipelines. Using comprehensive standard datasets and benchmarks, we show how Fast-SG outperforms the state-of-the-art short-read aligners when building the scaffoldinggraph and can be used to extract linking information from either raw or error-corrected long reads. We also show how a hybrid assembly approach using Fast-SG with shallow long-read coverage (5X) and moderate computational resources can produce long-range and accurate reconstructions of the genomes of Arabidopsis thaliana (Ler-0) and human (NA12878).Fast-SG opens a door to achieve accurate hybrid long-range reconstructions of large genomes with low effort, high portability, and low cost.

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July 7, 2019  |  

Regulation of neuronal differentiation, function, and plasticity by alternative splicing.

Posttranscriptional mechanisms provide powerful means to expand the coding power of genomes. In nervous systems, alternative splicing has emerged as a fundamental mechanism not only for the diversification of protein isoforms but also for the spatiotemporal control of transcripts. Thus, alternative splicing programs play instructive roles in the development of neuronal cell type-specific properties, neuronal growth, self-recognition, synapse specification, and neuronal network function. Here we discuss the most recent genome-wide efforts on mapping RNA codes and RNA-binding proteins for neuronal alternative splicing regulation. We illustrate how alternative splicing shapes key steps of neuronal development, neuronal maturation, and synaptic properties. Finally, we highlight efforts to dissect the spatiotemporal dynamics of alternative splicing and their potential contribution to neuronal plasticity and the mature nervous system. Expected final online publication date for the Annual Review of Cell and Developmental Biology Volume 34 is October 6, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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July 7, 2019  |  

Nanoarrays on passivated aluminum surface for site-specific immobilization of biomolecules

The rapid development of biosensing platforms for highly sensitive and specific detection raises the desire of precise localization of biomolecules onto various material surfaces. Aluminum has been strategically employed in the biosensor system due to its compatibility with CMOS technology and its optical and electrical properties such as prominent propagation of surface plasmons. Herein, we present an adaptable method for preparation of carbon nanoarrays on aluminum surface passivated with poly(vinylphosphonic acid) (PVPA). The carbon nanoarrays were defined by means of electron beam induced deposition (EBID) and they were employed to realize site-specific immobilization of target biomolecules. To demonstrate the concept, selective streptavidin/neutravidin immobilization on the carbon nanoarrays was achieved through protein physisorption with a significantly high contrast of the carbon domains over the surrounding PVPA-modified aluminum surface. By adjusting the fabrication parameters, local protein densities could be varied on similarly sized nanodomains in a parallel process. Moreover, localization of single 40 nm biotinylated beads was achieved by loading them on the neutravidin-decorated nanoarrays. As a further demonstration, DNA polymerase with a streptavidin tag was bound to the biotin-beads that were immobilized on the nanoarrays and in situ rolling circle amplification (RCA) was subsequently performed. The observation of organized DNA arrays synthesized by RCA verified the nanoscale localization of the enzyme with retained biological activity. Hence, the presented approach could provide a flexible and universal avenue to precise localizing various biomolecules on aluminum surface for potential biosensor and bioelectronic applications.

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