Hybrid de novo tandem repeat detection using short and long reads

TALC: Transcript-level Aware Long-read Correction

MOTIVATION

Long-read sequencing technologies are invaluable for determining complex RNA transcript architectures but are error-prone. Numerous 'hybrid correction' algorithms have been developed for genomic data that correct long reads by exploiting the accuracy and depth of short reads sequenced from the same sample. These algorithms are not suited for correcting more complex transcriptome sequencing data.

RESULTS

We have created a novel reference-free algorithm called Transcript-level Aware Long-Read Correction (TALC) which models changes in RNA expression and isoform representation in a weighted De Bruijn graph to correct long reads from transcriptome studies. We show that transcript-level aware correction by TALC improves the accuracy of the whole spectrum of downstream RNA-seq applications and is thus necessary for transcriptome analyses that use long read technology.

AVAILABILITY AND IMPLEMENTATION

TALC is implemented in C++ and available at https://github.com/lbroseus/TALC.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

RepAHR: an improved approach for de novo repeat identification by assembly of the high-frequency reads

Background

Repetitive sequences account for a large proportion of eukaryotes genomes. Identification of repetitive sequences plays a significant role in many applications, such as structural variation detection and genome assembly. Many existing de novo repeat identification pipelines or tools make use of assembly of the high-frequency k-mers to obtain repeats. However, a certain degree of sequence coverage is required for assemblers to get the desired assemblies. On the other hand, assemblers cut the reads into shorter k-mers for assembly, which may destroy the structure of the repetitive regions. For the above reasons, it is difficult to obtain complete and accurate repetitive regions in the genome by using existing tools.

Results

In this study, we present a new method called RepAHR for de novo repeat identification by assembly of the high-frequency reads. Firstly, RepAHR scans next-generation sequencing (NGS) reads to find the high-frequency k-mers. Secondly, RepAHR filters the high-frequency reads from whole NGS reads according to certain rules based on the high-frequency k-mer. Finally, the high-frequency reads are assembled to generate repeats by using SPAdes, which is considered as an outstanding genome assembler with NGS sequences.

Conlusions

We test RepAHR on five data sets, and the experimental results show that RepAHR outperforms RepARK and REPdenovo for detecting repeats in terms of N50, reference alignment ratio, coverage ratio of reference, mask ratio of Repbase and some other metrics.

A New Census of Protein Tandem Repeats and Their Relationship with Intrinsic Disorder

Protein tandem repeats (TRs) are often associated with immunity-related functions and diseases. Since that last census of protein TRs in 1999, the number of curated proteins increased more than seven-fold and new TR prediction methods were published. TRs appear to be enriched with intrinsic disorder and vice versa. The significance and the biological reasons for this association are unknown. Here, we characterize protein TRs across all kingdoms of life and their overlap with intrinsic disorder in unprecedented detail. Using state-of-the-art prediction methods, we estimate that 50.9% of proteins contain at least one TR, often located at the sequence flanks. Positive linear correlation between the proportion of TRs and the protein length was observed universally, with Eukaryotes in general having more TRs, but when the difference in length is taken into account the difference is quite small. TRs were enriched with disorder-promoting amino acids and were inside intrinsically disordered regions. Many such TRs were homorepeats. Our results support that TRs mostly originate by duplication and are involved in essential functions such as transcription processes, structural organization, electron transport and iron-binding. In viruses, TRs are found in proteins essential for virulence.

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

BACKGROUND

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.

RESULTS

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.

CONCLUSIONS

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.

Satellite DNA evolution: old ideas, new approaches

A substantial portion of the genomes of most multicellular eukaryotes consists of large arrays of tandemly repeated sequence, collectively called satellite DNA. The processes generating and maintaining different satellite DNA abundances across lineages are important to understand as satellites have been linked to chromosome mis-segregation, disease phenotypes, and reproductive isolation between species. While much theory has been developed to describe satellite evolution, empirical tests of these models have fallen short because of the challenges in assessing satellite repeat regions of the genome. Advances in computational tools and sequencing technologies now enable identification and quantification of satellite sequences genome-wide. Here, we describe some of these tools and how their applications are furthering our knowledge of satellite evolution and function.

The SeqAn C++ template library for efficient sequence analysis: A resource for programmers

BACKGROUND

The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome (Venter et al., 2001) would not have been possible without advanced assembly algorithms and the development of practical BWT based read mappers have been instrumental for NGS analysis. However, owing to the high speed of technological progress and the urgent need for bioinformatics tools, there was a widening gap between state-of-the-art algorithmic techniques and the actual algorithmic components of tools that are in widespread use. We previously addressed this by introducing the SeqAn library of efficient data types and algorithms in 2008 (Döring et al., 2008).

RESULTS

The SeqAn library has matured considerably since its first publication 9 years ago. In this article we review its status as an established resource for programmers in the field of sequence analysis and its contributions to many analysis tools.

CONCLUSIONS

We anticipate that SeqAn will continue to be a valuable resource, especially since it started to actively support various hardware acceleration techniques in a systematic manner.

TAREAN: a computational tool for identification and characterization of satellite DNA from unassembled short reads

Satellite DNA is one of the major classes of repetitive DNA, characterized by tandemly arranged repeat copies that form contiguous arrays up to megabases in length. This type of genomic organization makes satellite DNA difficult to assemble, which hampers characterization of satellite sequences by computational analysis of genomic contigs. Here, we present tandem repeat analyzer (TAREAN), a novel computational pipeline that circumvents this problem by detecting satellite repeats directly from unassembled short reads. The pipeline first employs graph-based sequence clustering to identify groups of reads that represent repetitive elements. Putative satellite repeats are subsequently detected by the presence of circular structures in their cluster graphs. Consensus sequences of repeat monomers are then reconstructed from the most frequent k-mers obtained by decomposing read sequences from corresponding clusters. The pipeline performance was successfully validated by analyzing low-pass genome sequencing data from five plant species where satellite DNA was previously experimentally characterized. Moreover, novel satellite repeats were predicted for the genome of Vicia faba and three of these repeats were verified by detecting their sequences on metaphase chromosomes using fluorescence in situ hybridization.

TAREAN: a computational tool for identification and characterization of satellite DNA from unassembled short reads

Satellite DNA is one of the major classes of repetitive DNA, characterized by tandemly arranged repeat copies that form contiguous arrays up to megabases in length. This type of genomic organization makes satellite DNA difficult to assemble, which hampers characterization of satellite sequences by computational analysis of genomic contigs. Here, we present tandem repeat analyzer (TAREAN), a novel computational pipeline that circumvents this problem by detecting satellite repeats directly from unassembled short reads. The pipeline first employs graph-based sequence clustering to identify groups of reads that represent repetitive elements. Putative satellite repeats are subsequently detected by the presence of circular structures in their cluster graphs. Consensus sequences of repeat monomers are then reconstructed from the most frequent k-mers obtained by decomposing read sequences from corresponding clusters. The pipeline performance was successfully validated by analyzing low-pass genome sequencing data from five plant species where satellite DNA was previously experimentally characterized. Moreover, novel satellite repeats were predicted for the genome of Vicia faba and three of these repeats were verified by detecting their sequences on metaphase chromosomes using fluorescence in situ hybridization.