TRiCoLOR: tandem repeat profiling using whole-genome long-read sequencing data

Toward understanding the role of genomic repeat elements in neurodegenerative diseases

Neurodegenerative diseases cause great medical and economic burdens for both patients and society; however, the complex molecular mechanisms thereof are not yet well understood. With the development of high-coverage sequencing technology, researchers have started to notice that genomic repeat regions, previously neglected in search of disease culprits, are active contributors to multiple neurodegenerative diseases. In this review, we describe the association between repeat element variants and multiple degenerative diseases through genome-wide association studies and targeted sequencing. We discuss the identification of disease-relevant repeat element variants, further powered by the advancement of long-read sequencing technologies and their related tools, and summarize recent findings in the molecular mechanisms of repeat element variants in brain degeneration, such as those causing transcriptional silencing or RNA-mediated gain of toxic function. Furthermore, we describe how in silico predictions using innovative computational models, such as deep learning language models, could enhance and accelerate our understanding of the functional impact of repeat element variants. Finally, we discuss future directions to advance current findings for a better understanding of neurodegenerative diseases and the clinical applications of genomic repeat elements.

LongTR: genome-wide profiling of genetic variation at tandem repeats from long reads

Tandem repeats are frequent across the human genome, and variation in repeat length has been linked to a variety of traits. Recent improvements in long read sequencing technologies have the potential to greatly improve tandem repeat analysis, especially for long or complex repeats. Here, we introduce LongTR, which accurately genotypes tandem repeats from high-fidelity long reads available from both PacBio and Oxford Nanopore Technologies. LongTR is freely available at https://github.com/gymrek-lab/longtr and https://zenodo.org/doi/10.5281/zenodo.11403979 .

Sequencing and characterizing short tandem repeats in the human genome

Short tandem repeats (STRs) are highly polymorphic sequences throughout the human genome that are composed of repeated copies of a 1-6-bp motif. Over 1 million variable STR loci are known, some of which regulate gene expression and influence complex traits, such as height. Moreover, variants in at least 60 STR loci cause genetic disorders, including Huntington disease and fragile X syndrome. Accurately identifying and genotyping STR variants is challenging, in particular mapping short reads to repetitive regions and inferring expanded repeat lengths. Recent advances in sequencing technology and computational tools for STR genotyping from sequencing data promise to help overcome this challenge and solve genetically unresolved cases and the 'missing heritability' of polygenic traits. Here, we compare STR genotyping methods, analytical tools and their applications to understand the effect of STR variation on health and disease. We identify emergent opportunities to refine genotyping and quality-control approaches as well as to integrate STRs into variant-calling workflows and large cohort analyses.

Enhanced Detection and Genotyping of Disease-Associated Tandem Repeats Using HMMSTR and Targeted Long-Read Sequencing

Tandem repeat sequences comprise approximately 8% of the human genome and are linked to more than 50 neurodegenerative disorders. Accurate characterization of disease-associated repeat loci remains resource intensive and often lacks high resolution genotype calls. We introduce a multiplexed, targeted nanopore sequencing panel and HMMSTR, a sequence-based tandem repeat copy number caller. HMMSTR outperforms current signal- and sequence-based callers relative to two assemblies and we show it performs with high accuracy in heterozygous regions and at low read coverage. The flexible panel allows us to capture disease associated regions at an average coverage of >150x. Using these tools, we successfully characterize known or suspected repeat expansions in patient derived samples. In these samples we also identify unexpected expanded alleles at tandem repeat loci not previously associated with the underlying diagnosis. This genotyping approach for tandem repeat expansions is scalable, simple, flexible, and accurate, offering significant potential for diagnostic applications and investigation of expansion co-occurrence in neurodegenerative disorders.

Abstract Figure

The role of tandem repeat expansions in brain disorders

The human genome contains numerous genetic polymorphisms contributing to different health and disease outcomes. Tandem repeat (TR) loci are highly polymorphic yet under-investigated in large genomic studies, which has prompted research efforts to identify novel variations and gain a deeper understanding of their role in human biology and disease outcomes. We summarize the current understanding of TRs and their implications for human health and disease, including an overview of the challenges encountered when conducting TR analyses and potential solutions to overcome these challenges. By shedding light on these issues, this article aims to contribute to a better understanding of the impact of TRs on the development of new disease treatments.

Expanding horizons of tandem repeats in biology and medicine: Why 'genomic dark matter' matters

Approximately half of the human genome includes repetitive sequences, and these DNA sequences (as well as their transcribed repetitive RNA and translated amino-acid repeat sequences) are known as the repeatome. Within this repeatome there are a couple of million tandem repeats, dispersed throughout the genome. These tandem repeats have been estimated to constitute ∼8% of the entire human genome. These tandem repeats can be located throughout exons, introns and intergenic regions, thus potentially affecting the structure and function of tandemly repetitive DNA, RNA and protein sequences. Over more than three decades, more than 60 monogenic human disorders have been found to be caused by tandem-repeat mutations. These monogenic tandem-repeat disorders include Huntington's disease, a variety of ataxias, amyotrophic lateral sclerosis and frontotemporal dementia, as well as many other neurodegenerative diseases. Furthermore, tandem-repeat disorders can include fragile X syndrome, related fragile X disorders, as well as other neurological and psychiatric disorders. However, these monogenic tandem-repeat disorders, which were discovered via their dominant or recessive modes of inheritance, may represent the 'tip of the iceberg' with respect to tandem-repeat contributions to human disorders. A previous proposal that tandem repeats may contribute to the 'missing heritability' of various common polygenic human disorders has recently been supported by a variety of new evidence. This includes genome-wide studies that associate tandem-repeat mutations with autism, schizophrenia, Parkinson's disease and various types of cancers. In this article, I will discuss how tandem-repeat mutations and polymorphisms could contribute to a wide range of common disorders, along with some of the many major challenges of tandem-repeat biology and medicine. Finally, I will discuss the potential of tandem repeats to be therapeutically targeted, so as to prevent and treat an expanding range of human disorders.

Evolutionary Study of Protein Short Tandem Repeats in Protein Families

Tandem repeats in proteins are patterns of residues repeated directly adjacent to each other. The evolution of these repeats can be assessed by using groups of homologous sequences, which can help pointing to events of unit duplication or deletion. High pressure in a protein family for variation of a given type of repeat might point to their function. Here, we propose the analysis of protein families to calculate protein short tandem repeats (pSTRs) in each protein sequence and assess their variability within the family in terms of number of units. To facilitate this analysis, we developed the pSTR tool, a method to analyze the evolution of protein short tandem repeats in a given protein family by pairwise comparisons between evolutionarily related protein sequences. We evaluated pSTR unit number variation in protein families of 12 complete metazoan proteomes. We hypothesize that families with more dynamic ensembles of repeats could reflect particular roles of these repeats in processes that require more adaptability.

NanoSTR: A method for detection of target short tandem repeats based on nanopore sequencing data

Short tandem repeats (STRs) are widely present in the human genome. Studies have confirmed that STRs are associated with more than 30 diseases, and they have also been used in forensic identification and paternity testing. However, there are few methods for STR detection based on nanopore sequencing due to the challenges posed by the sequencing principles and the data characteristics of nanopore sequencing. We developed NanoSTR for detection of target STR loci based on the length-number-rank (LNR) information of reads. NanoSTR can be used for STR detection and genotyping based on long-read data from nanopore sequencing with improved accuracy and efficiency compared with other existing methods, such as Tandem-Genotypes and TRiCoLOR. NanoSTR showed 100% concordance with the expected genotypes using error-free simulated data, and also achieved >85% concordance using the standard samples (containing autosomal and Y-chromosomal loci) with MinION sequencing platform, respectively. NanoSTR showed high performance for detection of target STR markers. Although NanoSTR needs further optimization and development, it is useful as an analytical method for the detection of STR loci by nanopore sequencing. This method adds to the toolbox for nanopore-based STR analysis and expands the applications of nanopore sequencing in scientific research and clinical scenarios. The main code and the data are available at https://github.com/langjidong/NanoSTR.

The third international hackathon for applying insights into large-scale genomic composition to use cases in a wide range of organisms

In October 2021, 59 scientists from 14 countries and 13 U.S. states collaborated virtually in the Third Annual Baylor College of Medicine & DNANexus Structural Variation hackathon. The goal of the hackathon was to advance research on structural variants (SVs) by prototyping and iterating on open-source software. This led to nine hackathon projects focused on diverse genomics research interests, including various SV discovery and genotyping methods, SV sequence reconstruction, and clinically relevant structural variation, including SARS-CoV-2 variants. Repositories for the projects that participated in the hackathon are available at https://github.com/collaborativebioinformatics.

DeepRepeat: direct quantification of short tandem repeats on signal data from nanopore sequencing

Despite recent improvements in basecalling accuracy, nanopore sequencing still has higher error rates on short-tandem repeats (STRs). Instead of using basecalled reads, we developed DeepRepeat which converts ionic current signals into red-green-blue channels, thus transforming the repeat detection problem into an image recognition problem. DeepRepeat identifies and accurately quantifies telomeric repeats in the CHM13 cell line and achieves higher accuracy in quantifying repeats in long STRs than competing methods. We also evaluate DeepRepeat on genome-wide or candidate region datasets from seven different sources. In summary, DeepRepeat enables accurate quantification of long STRs and complements existing methods relying on basecalled reads.

Evaluation of Germline Structural Variant Calling Methods for Nanopore Sequencing Data

Structural variants (SVs) are genomic rearrangements that involve at least 50 nucleotides and are known to have a serious impact on human health. While prior short-read sequencing technologies have often proved inadequate for a comprehensive assessment of structural variation, more recent long reads from Oxford Nanopore Technologies have already been proven invaluable for the discovery of large SVs and hold the potential to facilitate the resolution of the full SV spectrum. With many long-read sequencing studies to follow, it is crucial to assess factors affecting current SV calling pipelines for nanopore sequencing data. In this brief research report, we evaluate and compare the performances of five long-read SV callers across four long-read aligners using both real and synthetic nanopore datasets. In particular, we focus on the effects of read alignment, sequencing coverage, and variant allele depth on the detection and genotyping of SVs of different types and size ranges and provide insights into precision and recall of SV callsets generated by integrating the various long-read aligners and SV callers. The computational pipeline we propose is publicly available at https://github.com/davidebolo1993/EViNCe and can be adjusted to further evaluate future nanopore sequencing datasets.

Nanopore sequencing technology, bioinformatics and applications

Rapid advances in nanopore technologies for sequencing single long DNA and RNA molecules have led to substantial improvements in accuracy, read length and throughput. These breakthroughs have required extensive development of experimental and bioinformatics methods to fully exploit nanopore long reads for investigations of genomes, transcriptomes, epigenomes and epitranscriptomes. Nanopore sequencing is being applied in genome assembly, full-length transcript detection and base modification detection and in more specialized areas, such as rapid clinical diagnoses and outbreak surveillance. Many opportunities remain for improving data quality and analytical approaches through the development of new nanopores, base-calling methods and experimental protocols tailored to particular applications.

An Introductory Overview of Open-Source and Commercial Software Options for the Analysis of Forensic Sequencing Data

The top challenges of adopting new methods to forensic DNA analysis in routine laboratories are often the capital investment and the expertise required to implement and validate such methods locally. In the case of next-generation sequencing, in the last decade, several specifically forensic commercial options became available, offering reliable and validated solutions. Despite this, the readily available expertise to analyze, interpret and understand such data is still perceived to be lagging behind. This review gives an introductory overview for the forensic scientists who are at the beginning of their journey with implementing next-generation sequencing locally and because most in the field do not have a bioinformatics background may find it difficult to navigate the new terms and analysis options available. The currently available open-source and commercial software for forensic sequencing data analysis are summarized here to provide an accessible starting point for those fairly new to the forensic application of massively parallel sequencing.

Towards population-scale long-read sequencing

Long-read sequencing technologies have now reached a level of accuracy and yield that allows their application to variant detection at a scale of tens to thousands of samples. Concomitant with the development of new computational tools, the first population-scale studies involving long-read sequencing have emerged over the past 2 years and, given the continuous advancement of the field, many more are likely to follow. In this Review, we survey recent developments in population-scale long-read sequencing, highlight potential challenges of a scaled-up approach and provide guidance regarding experimental design. We provide an overview of current long-read sequencing platforms, variant calling methodologies and approaches for de novo assemblies and reference-based mapping approaches. Furthermore, we summarize strategies for variant validation, genotyping and predicting functional impact and emphasize challenges remaining in achieving long-read sequencing at a population scale.

CaBagE: A Cas9-based Background Elimination strategy for targeted, long-read DNA sequencing

A substantial fraction of the human genome is difficult to interrogate with short-read DNA sequencing technologies due to paralogy, complex haplotype structures, or tandem repeats. Long-read sequencing technologies, such as Oxford Nanopore's MinION, enable direct measurement of complex loci without introducing many of the biases inherent to short-read methods, though they suffer from relatively lower throughput. This limitation has motivated recent efforts to develop amplification-free strategies to target and enrich loci of interest for subsequent sequencing with long reads. Here, we present CaBagE, a method for target enrichment that is efficient and useful for sequencing large, structurally complex targets. The CaBagE method leverages the stable binding of Cas9 to its DNA target to protect desired fragments from digestion with exonuclease. Enriched DNA fragments are then sequenced with Oxford Nanopore's MinION long-read sequencing technology. Enrichment with CaBagE resulted in a median of 116X coverage (range 39-416) of target loci when tested on five genomic targets ranging from 4-20kb in length using healthy donor DNA. Four cancer gene targets were enriched in a single reaction and multiplexed on a single MinION flow cell. We further demonstrate the utility of CaBagE in two ALS patients with C9orf72 short tandem repeat expansions to produce genotype estimates commensurate with genotypes derived from repeat-primed PCR for each individual. With CaBagE there is a physical enrichment of on-target DNA in a given sample prior to sequencing. This feature allows adaptability across sequencing platforms and potential use as an enrichment strategy for applications beyond sequencing. CaBagE is a rapid enrichment method that can illuminate regions of the 'hidden genome' underlying human disease.

TRiCoLOR: tandem repeat profiling using whole-genome long-read sequencing data

BACKGROUND

Tandem repeat sequences are widespread in the human genome, and their expansions cause multiple repeat-mediated disorders. Genome-wide discovery approaches are needed to fully elucidate their roles in health and disease, but resolving tandem repeat variation accurately remains a challenging task. While traditional mapping-based approaches using short-read data have severe limitations in the size and type of tandem repeats they can resolve, recent third-generation sequencing technologies exhibit substantially higher sequencing error rates, which complicates repeat resolution.

RESULTS

We developed TRiCoLOR, a freely available tool for tandem repeat profiling using error-prone long reads from third-generation sequencing technologies. The method can identify repetitive regions in sequencing data without a prior knowledge of their motifs or locations and resolve repeat multiplicity and period size in a haplotype-specific manner. The tool includes methods to interactively visualize the identified repeats and to trace their Mendelian consistency in pedigrees.

CONCLUSIONS

TRiCoLOR demonstrates excellent performance and improved sensitivity and specificity compared with alternative tools on synthetic data. For real human whole-genome sequencing data, TRiCoLOR achieves high validation rates, suggesting its suitability to identify tandem repeat variation in personal genomes.