Read Alignment Research Articles

Shedding light on dark genes: enhanced targeted resequencing by optimizing the combination of enrichment technology and DNA fragment length

The exome contains many obscure regions difficult to explore with current short-read sequencing methods. Repetitious genomic regions prevent the unique alignment of reads, which is essential for the identification of clinically-relevant genetic variants. Long-read technologies attempt to resolve multiple-mapping regions, but they still produce many sequencing errors. Thus, a new approach is required to enlighten the obscure regions of the genome and rescue variants that would be otherwise neglected. This work aims to improve the alignment of multiple-mapping reads through the extension of the standard DNA fragment size. As Illumina can sequence fragments up to 550 bp, we tested different DNA fragment lengths using four major commercial WES platforms and found that longer DNA fragments achieved a higher genotypability. This metric, which indicates base calling calculated by combining depth of coverage with the confidence of read alignment, increased from hundreds to thousands of genes, including several associated with clinical phenotypes. While depth of coverage has been considered crucial for the assessment of WES performance, we demonstrated that genotypability has a greater impact in revealing obscure regions, with ~1% increase in variant calling in respect to shorter DNA fragments. Results confirmed that this approach enlightened many regions previously not explored.

A DNA Read Alignment Accelerator Based on Computational RAM

Recent years have witnessed an increasing interest in the processing-in-memory (PIM) paradigm in computing due to its promise to improve the performance through the reduction of energy-hungry and long-latency memory accesses. Joined with the explosion of data to be processed, produced in genomics—particularly genome sequencing—PIM has become a potential promising candidate for accelerating genomics applications since they do not scale up well in conventional von Neumann systems. In this article, we present an in-memory accelerator architecture for DNA read alignment. This architecture outperforms corresponding software implementation by >49X and >18 000X, in terms of throughput and energy efficiency, respectively, even under conservative assumptions.

Personalized and graph genomes reveal missing signal in epigenomic data

BackgroundEpigenomic studies that use next generation sequencing experiments typically rely on the alignment of reads to a reference sequence. However, because of genetic diversity and the diploid nature of the human genome, we hypothesize that using a generic reference could lead to incorrectly mapped reads and bias downstream results.ResultsWe show that accounting for genetic variation using a modified reference genome or a de novo assembled genome can alter histone H3K4me1 and H3K27ac ChIP-seq peak calls either by creating new personal peaks or by the loss of reference peaks. Using permissive cutoffs, modified reference genomes are found to alter approximately 1% of peak calls while de novo assembled genomes alter up to 5% of peaks. We also show statistically significant differences in the amount of reads observed in regions associated with the new, altered, and unchanged peaks. We report that short insertions and deletions (indels), followed by single nucleotide variants (SNVs), have the highest probability of modifying peak calls. We show that using a graph personalized genome represents a reasonable compromise between modified reference genomes and de novo assembled genomes. We demonstrate that altered peaks have a genomic distribution typical of other peaks.ConclusionsAnalyzing epigenomic datasets with personalized and graph genomes allows the recovery of new peaks enriched for indels and SNVs. These altered peaks are more likely to differ between individuals and, as such, could be relevant in the study of various human phenotypes.

Strandedness during cDNA synthesis, the stranded parameter in htseq-count and analysis of RNA-Seq data.

RNA sequencing (RNA-Seq) is a complicated protocol, both in the laboratory in generation of data and at the computer in analysis of results. Several decisions during RNA-Seq library construction have important implications for analysis, most notably strandedness during complementary DNA library construction. Here, we clarify bioinformatic decisions related to strandedness in both alignment of DNA sequencing reads to reference genomes and subsequent determination of transcript abundance.

SUN-916 Novel Germline p.Gly42Arg MEN1 Missense Mutation in a Family Harboring Very Aggressive Pancreatic Tumor, Hyperparathyroidism and Pituitary Tumor

Background.Pancreatic neuroendocrine tumors ocurs in 30-80% of patients with MEN-1, and may be non-functioning and hormone secreting tumors. Non-functioning GEP-NETs are increasingly recognised due to advanced imaging modalities such as endoscopic ultrasound thus became the most common type in MEN1 patients. Several mutations MENIN gene were described, although patients with missense mutations are considered as low-impact mutation carriers.Case report.Index case, female, 47 years old, menarche at age of 16yo, amenorrhea until 23yo, when started continuous oral contraceptives. At age of 45 presented dizziness, paresthesia, cramps, had the diagnosis of Hyperparathyroidism related to multinodular parathyroid hyperplasia (Calcium 14mg/dL, PTH 117 pg/mL) and macroprolactinoma (prolactin 235 ng/mL; pituitary tumor 1.2 X 1.0 cm). All siblings and her mother were recruited and one brother, aged 45 years confirmed the diagnosis of hyperparathyroidism and nephrocalcinosis. Their mother, aged 77 years old, presented abdominal pain, and had the diagnosis of aggressivepancreatic tumor compressing bile duct causing intra and extra-pancreatic dilation, associated with metastatic lymph nodes. She was sunmitted to total pancreato-gastrectomy with esophagus jejunum anastomosis. Genetic screening:MEN1genetic screening for mutations was performed in all patients. In these probands, MLPA analysis was performed to detect large deletions of the MEN1gene, using SALSA MLPA probemix kit P017-D1 according to the manufacturer’s instructions (MRC-Holland, Amsterdam, The Netherlands).DNA was extracted from EDTA-Whole blood using MagNA Pure 24 (Roche). Sequencing libraries were qualified/quantified using TapeStation4200 (Agilent). Test method included coding regions ±10bp flanking intronic sequences of 3921 genes enriched using Kappa HyperPlus Library Preparation Kit (Roche) and SeqCap EZ inherited disease panel (Roche) and sequenced (2x75-bp Mid Output V2 Reagent) using NextSeq-500 (Illumina) (estimated mean coverage-100X). Read alignment, variant calling, variant filtration and annotation were performed with Varstation. SNVs and small indels (20bp) with total-read-depth,10X and variant-read-frequency more than20% found on AIP, APC, CDC73, CDKN1B, DICER1, FH, MAX, MEN1, MET, NF1, PRKAR1A, PTEN, RET, SDHA, SDHAF2, SDHB, SDHC, SDHD, TMEM127, TP53, VHL, WRN genes were analyzed.A missense mutation in exon 2, MEN1:c.124G.C:p.(GLY42Arg) was detected. Discussion and conclusion:MEN1-associated GEP-NETs seem to have a low proliferation rate and long survival has been reported, they should be of particular attention, since they are still the principal cause of death in MEN1 patients.Early screening and diagnosis are crucial for MEN-1 phenotypes.

Assessing DNA Sequence Alignment Methods for Characterizing Ancient Genomes and Methylomes

Applying high-throughput DNA sequencing technologies to the ancient DNA molecules preserved in subfossil material can provide genetic information from past individuals, populations and communities at the genomic scale. The combination of dedicated statistical techniques and specific molecular tools aimed at reducing the impact of post-mortem DNA damage can also help recover epigenetic data from ancient individuals. However, the capacity of different sequence aligners to identify ultrashort and deaminated ancient DNA templates, and their impact on the characterization of ancient methylomes, remain overlooked. In this study, we use both simulated and real ancient DNA sequence data to benchmark the performance of the read alignment tools most commonly used in ancient DNA research. We identify a read alignment strategy making use of the Bowtie2 aligner that substantially reduce computational times but shows increased sensitivity relative to previous recommendations based on the BWA aligner. This strategy significantly improves the genome coverage especially when DNA templates are shorter than 90bp, as is typically the case for ancient DNA. It also impacts on ancient DNA methylation estimates as it maximizes coverage improvement within CpG dinucleotide contexts, which hold the vast majority of DNA methylation marks in mammals. Our work contributes to improve the accuracy of DNA methylation maps and to maximize the amount of recoverable genetic information from archaeological and subfossil material. As the molecular complexity of ancient DNA libraries is generally limited, the mapping strategy recommended here is essential to both limit sequencing costs and sample destruction.

Chromosome-Scale Assembly of Winter Oilseed Rape Brassica napus.

Rapeseed (Brassica napus), the second most important oilseed crop globally, originated from an interspecific hybridization between B. rapa and B. oleracea. After this genome collision, B. napus underwent extensive genome restructuring, via homoeologous chromosome exchanges, resulting in widespread segmental deletions and duplications. Illicit pairing among genetically similar homoeologous chromosomes during meiosis is common in recent allopolyploids like B. napus, and post-polyploidization restructuring compounds the difficulties of assembling a complex polyploid plant genome. Specifically, genomic rearrangements between highly similar chromosomes are challenging to detect due to the limitation of sequencing read length and ambiguous alignment of reads. Recent advances in long read sequencing technologies provide promising new opportunities to unravel the genome complexities of B. napus by encompassing breakpoints of genomic rearrangements with high specificity. Moreover, recent evidence revealed ongoing genomic exchanges in natural B. napus, highlighting the need for multiple reference genomes to capture structural variants between accessions. Here we report the first long-read genome assembly of a winter B. napus cultivar. We sequenced the German winter oilseed rape accession ‘Express 617’ using 54.5x of long reads. Short reads, linked reads, optical map data and high-density genetic maps were used to further correct and scaffold the assembly to form pseudochromosomes. The assembled Express 617 genome provides another valuable resource for Brassica genomics in understanding the genetic consequences of polyploidization, crop domestication, and breeding of recently-formed crop species.

Vargas: heuristic-free alignment for assessing linear and graph read aligners.

MotivationRead alignment is central to many aspects of modern genomics. Most aligners use heuristics to accelerate processing, but these heuristics can fail to find the optimal alignments of reads. Alignment accuracy is typically measured through simulated reads; however, the simulated location may not be the (only) location with the optimal alignment score.ResultsVargas implements a heuristic-free algorithm guaranteed to find the highest-scoring alignment for real sequencing reads to a linear or graph genome. With semiglobal and local alignment modes and affine gap and quality-scaled mismatch penalties, it can implement the scoring functions of commonly used aligners to calculate optimal alignments. While this is computationally intensive, Vargas uses multi-core parallelization and vectorized (SIMD) instructions to make it practical to optimally align large numbers of reads, achieving a maximum speed of 456 billion cell updates per second. We demonstrate how these ‘gold standard’ Vargas alignments can be used to improve heuristic alignment accuracy by optimizing command-line parameters in Bowtie 2, BWA-maximal exact match and vg to align more reads correctly.Availability and implementationSource code implemented in C++ and compiled binary releases are available at https://github.com/langmead-lab/vargas under the MIT license.Supplementary information Supplementary data are available at Bioinformatics online.

QUARTIC: QUick pArallel algoRithms for high-Throughput sequencIng data proCessing

Life science has entered the so-called 'big data era' where biologists, clinicians and bioinformaticians are overwhelmed with unprecedented amount of data. High-throughput sequencing has revolutionized genomics and offers new insights to decipher the genome structure. However, using these data for daily clinical practice care and diagnosis purposes is challenging as the data are bigger and bigger. Therefore, we implemented software using Message Passing Interface such that the alignment and sorting of sequencing reads can easily scale on high-performance computing architecture. Our implementation makes it possible to reduce the time to delivery to few minutes, even on large whole-genome data using several hundreds of cores.

Comparison of Read Mapping and Variant Calling Tools for the Analysis of Plant NGS Data.

High-throughput sequencing technologies have rapidly developed during the past years and have become an essential tool in plant sciences. However, the analysis of genomic data remains challenging and relies mostly on the performance of automatic pipelines. Frequently applied pipelines involve the alignment of sequence reads against a reference sequence and the identification of sequence variants. Since most benchmarking studies of bioinformatics tools for this purpose have been conducted on human datasets, there is a lack of benchmarking studies in plant sciences. In this study, we evaluated the performance of 50 different variant calling pipelines, including five read mappers and ten variant callers, on six real plant datasets of the model organism Arabidopsis thaliana. Sets of variants were evaluated based on various parameters including sensitivity and specificity. We found that all investigated tools are suitable for analysis of NGS data in plant research. When looking at different performance metrics, BWA-MEM and Novoalign were the best mappers and GATK returned the best results in the variant calling step.

SRPRISM (Single Read Paired Read Indel Substitution Minimizer): an efficient aligner for assemblies with explicit guarantees.

Alignment of sequence reads generated by next-generation sequencing is an integral part of most pipelines analyzing next-generation sequencing data. A number of tools designed to quickly align a large volume of sequences are already available. However, most existing tools lack explicit guarantees about their output. They also do not support searching genome assemblies, such as the human genome assembly GRCh38, that include primary and alternate sequences and placement information for alternate sequences to primary sequences in the assembly. This paper describes SRPRISM (Single Read Paired Read Indel Substitution Minimizer), an alignment tool for aligning reads without splices. SRPRISM has features not available in most tools, such as (i) support for searching genome assemblies with alternate sequences, (ii) partial alignment of reads with a specified region of reads to be included in the alignment, (iii) choice of ranking schemes for alignments, and (iv) explicit criteria for search sensitivity. We compare the performance of SRPRISM to GEM, Kart, STAR, BWA-MEM, Bowtie2, Hobbes, and Yara using benchmark sets for paired and single reads of lengths 100 and 250bp generated using DWGSIM. SRPRISM found the best results for most benchmark sets with error rate of up to ∼2.5% and GEM performed best for higher error rates. SRPRISM was also more sensitive than other tools even when sensitivity was reduced to improve run time performance. We present SRPRISM as a flexible read mapping tool that provides explicit guarantees on results.

Efficient Construction of a Complete Index for Pan-Genomics Read Alignment.

Short-read aligners predominantly use the FM-index, which is easily able to index one or a few human genomes. However, it does not scale well to indexing collections of thousands of genomes. Driving this issue are the two chief components of the index: (1) a rank data structure over the Burrows–Wheeler Transform (BWT) of the string that will allow us to find the interval in the string's suffix array (SA), and (2) a sample of the SA that—when used with the rank data structure—allows us to access the SA. The rank data structure can be kept small even for large genomic databases, by run-length compressing the BWT, but until recently there was no means known to keep the SA sample small without greatly slowing down access to the SA. Now that (SODA 2018) has defined an SA sample that takes about the same space as the run-length compressed BWT, we have the design for efficient FM-indexes of genomic databases but are faced with the problem of building them. In 2018, we showed how to build the BWT of large genomic databases efficiently (WABI 2018), but the problem of building the sample efficiently was left open. We compare our approach to state-of-the-art methods for constructing the SA sample, and demonstrate that it is the fastest and most space-efficient method on highly repetitive genomic databases. Lastly, we apply our method for indexing partial and whole human genomes and show that it improves over the FM-index-based Bowtie method with respect to both memory and time and over the hybrid index-based CHIC method with respect to query time and memory required for indexing.

Thousands of missing variants in the UK Biobank are recoverable by genome realignment.

The UK Biobank is an unprecedented resource for human disease research. In March 2019, 49,997 exomes were made publicly available to investigators. Here we note that thousands of variant calls are unexpectedly absent from this dataset, with 641 genes showing zero variation. We show that the reason for this was an erroneous read alignment to the GRCh38 reference. The missing variants can be recovered by modifying read alignment parameters to correctly handle the expanded set of contigs available in the human genome reference. Given the size and complexity of such population scale datasets, we propose a simple heuristic that can uncover systematic errors using summary data accessible to most investigators.

Detecting circular RNA from high-throughput sequence data with de Bruijn graph

BackgroundCircular RNA is a type of non-coding RNA, which has a circular structure. Many circular RNAs are stable and contain exons, but are not translated into proteins. Circular RNA has important functions in gene regulation and plays an important role in some human diseases. Several biological methods, such as RNase R treatment, have been developed to identify circular RNA. Multiple bioinformatics tools have also been developed for circular RNA detection with high-throughput sequence data.ResultsIn this paper, we present circDBG, a new method for circular RNA detection with de Bruijn graph. We conduct various experiments to evaluate the performance of CircDBG based on both simulated and real data. Our results show that CircDBG finds more reliable circRNA with low bias, has more efficiency in running time, and performs better in balancing accuracy and sensitivity than existing methods. As a byproduct, we also introduce a new method to classify circular RNAs based on reads alignment. Finally, we report a potential chimeric circular RNA that is found by CircDBG based on real sequence data. CircDBG can be downloaded from https://github.com/lxwgcool/CircDBG.ConclusionsWe develop a new method called CircDBG for circular RNA detection, which is based on de Bruijn graph. We conduct extensive experiments and demonstrate CircDBG outperforms existing tools, especially in saving running time, reducing bias and improving capability of balancing accuracy and sensitivity. We also introduce a new method to classify circular RNAs and report a potential case of chimeric circular RNA.

Benchmarking hybrid assemblies of Giardia and prediction of widespread intra-isolate structural variation

BackgroundCurrently available short read genome assemblies of the tetraploid protozoan parasite Giardia intestinalis are highly fragmented, highlighting the need for improved genome assemblies at a reasonable cost. Long nanopore reads are well suited to resolve repetitive genomic regions resulting in better quality assemblies of eukaryotic genomes. Subsequent addition of highly accurate short reads to long-read assemblies further improves assembly quality. Using this hybrid approach, we assembled genomes for three Giardia isolates, two with published assemblies and one novel, to evaluate the improvement in genome quality gained from long reads. We then used the long reads to predict structural variants to examine this previously unexplored source of genetic variation in Giardia.MethodsWith MinION reads for each isolate, we assembled genomes using several assemblers specializing in long reads. Assembly metrics, gene finding, and whole genome alignments to the reference genomes enabled direct comparison to evaluate the performance of the nanopore reads. Further improvements from adding Illumina reads to the long-read assemblies were evaluated using gene finding. Structural variants were predicted from alignments of the long reads to the best hybrid genome for each isolate and enrichment of key genes was analyzed using random genome sampling and calculation of percentiles to find thresholds of significance.ResultsOur hybrid assembly method generated reference quality genomes for each isolate. Consistent with previous findings based on SNPs, examination of heterozygosity using the structural variants found that Giardia BGS was considerably more heterozygous than the other isolates that are from Assemblage A. Further, each isolate was shown to contain structural variant regions enriched for variant-specific surface proteins, a key class of virulence factor in Giardia.ConclusionsThe ability to generate reference quality genomes from a single MinION run and a multiplexed MiSeq run enables future large-scale comparative genomic studies within the genus Giardia. Further, prediction of structural variants from long reads allows for more in-depth analyses of major sources of genetic variation within and between Giardia isolates that could have effects on both pathogenicity and host range.

Amplimap: a versatile tool to process and analyze targeted NGS data.

SUMMARY amplimap is a command-line tool to automate the processing and analysis of data from targeted next-generation sequencing experiments with PCR-based amplicons or capture-based enrichment systems. From raw sequencing reads, amplimap generates output such as read alignments, annotated variant calls, target coverage statistics and variant allele counts and frequencies for each target base pair. In addition to its focus on user-friendliness and reproducibility, amplimap supports advanced features such as consensus base calling for read families based on unique molecular identifiers and filtering false positive variant calls caused by amplification of off-target loci. AVAILABILITY AND IMPLEMENTATION amplimap is available as a free Python package under the open-source Apache 2.0 License. Documentation, source code and installation instructions are available at https://github.com/koelling/amplimap.

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

BackgroundAdvances 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.ResultsHere, 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.ConclusionsThe 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.

Metabolome and Transcriptome Analyses Reveal Tissue-Specific Variations in Gene Expression and Metabolites of Olive

Metabolome and transcriptional correlation analyses can be used to reveal the relationship between metabolites and gene expression in different tissues. Here, targeted metabolome and Illumina RNA-Seq analyses were used for the identification of co-regulated metabolites and genes from three different tissue of Olea europaea (fruits, new leaves, and old leaves). In total, 57.49 Gb of clean data from nine samples was obtained. The clean data of each sample reached 5.25 Gb, and the Q30 base percentage exceeded 88.44%. Through sequence alignments of clean reads from each sample with the olive reference genome, 3049 newly annotated genes were identified, of which 2350 were functionally annotated. Differentially expressed genes (DEGs) and metabolite correlation analysis showed that most of the up-regulated genes in fruits were enriched in fatty acid (FA) biosynthesis metabolic pathways; the up-regulated genes in leaves were mainly related to plant hormones, biotic (abiotic) stress tolerance, signal transduction, and secondary metabolite biosynthesis pathways. The current global gene expression and metabolite content profiling exercise provides a comprehensive view of the combination of transcriptome and metabolome data, which provides valuable information for identifying DEGs in olives.

Sarek: A portable workflow for whole-genome sequencing analysis of germline and somatic variants.

Whole-genome sequencing (WGS) is a fundamental technology for research to advance precision medicine, but the limited availability of portable and user-friendly workflows for WGS analyses poses a major challenge for many research groups and hampers scientific progress. Here we present Sarek, an open-source workflow to detect germline variants and somatic mutations based on sequencing data from WGS, whole-exome sequencing (WES), or gene panels. Sarek features (i) easy installation, (ii) robust portability across different computer environments, (iii) comprehensive documentation, (iv) transparent and easy-to-read code, and (v) extensive quality metrics reporting. Sarek is implemented in the Nextflow workflow language and supports both Docker and Singularity containers as well as Conda environments, making it ideal for easy deployment on any POSIX-compatible computers and cloud compute environments. Sarek follows the GATK best-practice recommendations for read alignment and pre-processing, and includes a wide range of software for the identification and annotation of germline and somatic single-nucleotide variants, insertion and deletion variants, structural variants, tumour sample purity, and variations in ploidy and copy number. Sarek offers easy, efficient, and reproducible WGS analyses, and can readily be used both as a production workflow at sequencing facilities and as a powerful stand-alone tool for individual research groups. The Sarek source code, documentation and installation instructions are freely available at https://github.com/nf-core/sarek and at https://nf-co.re/sarek/.

Lep-Anchor: automated construction of linkage map anchored haploid genomes.

Linkage mapping provides a practical way to anchor de novo genome assemblies into chromosomes and to detect chimeric or otherwise erroneous contigs. Such anchoring improves with higher number of markers and individuals, as long as the mapping software can handle all the information. Recent software Lep-MAP3 can robustly construct linkage maps for millions of genotyped markers and on thousands of individuals, providing optimal maps for genome anchoring. For such large datasets, automated and robust genome anchoring tool is especially valuable and can significantly reduce intensive computational and manual work involved. Here, we present a software Lep-Anchor (LA) to anchor genome assemblies automatically using dense linkage maps. As the main novelty, it takes into account the uncertainty of the linkage map positions caused by low recombination regions, cross type or poor mapping data quality. Furthermore, it can automatically detect and cut chimeric contigs, and use contig-contig, single read or alternative genome assembly alignments as additional information on contig order and orientations and to collapse haplotype contigs. We demonstrate the performance of LA using real data and show that it outperforms ALLMAPS on anchoring completeness and speed. Accuracy-wise LA and ALLMAPS are about equal, but at the expense of lower completeness of ALLMAPS. The software Chromonomer was faster than the other two methods but has major limitations and is lower in accuracy. We also show that with additional information, such as contig-contig and read alignments, the anchoring completeness can be improved by up to 70% without significant loss in accuracy. Based on simulated data, we conclude that the anchoring accuracy can be improved by utilizing information about map position uncertainty. Accuracy is the rate of contigs in correct orientation and completeness is the number contigs with inferred orientation. Lep-Anchor is available with the source code under GNU general public license from http://sourceforge.net/projects/lep-anchor. All the scripts and code used to produce the reported results are included with Lep-Anchor.