A deep population reference panel of tandem repeat variation

Evolutionary feedback from the environment shapes mechanisms that generate genome variation

Darwin recognized that 'a grand and almost untrodden field of inquiry will be opened, on the causes and laws of variation.' However, because the Modern Synthesis assumes that the intrinsic probability of any individual mutation is unrelated to that mutation's potential adaptive value, attention has been focused on selection rather than on the intrinsic generation of variation. Yet many examples illustrate that the term 'random' mutation, as widely understood, is inaccurate. The probabilities of distinct classes of variation are neither evenly distributed across a genome nor invariant over time, nor unrelated to their potential adaptive value. Because selection acts upon variation, multiple biochemical mechanisms can and have evolved that increase the relative probability of adaptive mutations. In effect, the generation of heritable variation is in a feedback loop with selection, such that those mechanisms that tend to generate variants that survive recurring challenges in the environment would be captured by this survival and thus inherited and accumulated within lineages of genomes. Moreover, because genome variation is affected by a wide range of biochemical processes, genome variation can be regulated. Biochemical mechanisms that sense stress, from lack of nutrients to DNA damage, can increase the probability of specific classes of variation. A deeper understanding of evolution involves attention to the evolution of, and environmental influences upon, the intrinsic variation generated in gametes, in other words upon the biochemical mechanisms that generate variation across generations. These concepts have profound implications for the types of questions that can and should be asked, as omics databases become more comprehensive, detection methods more sensitive, and computation and experimental analyses even more high throughput and thus capable of revealing the intrinsic generation of variation in individual gametes. These concepts also have profound implications for evolutionary theory, which, upon reflection it will be argued, predicts that selection would increase the probability of generating adaptive mutations, in other words, predicts that the ability to evolve itself evolves.

Adaptive Long-Read Sequencing Reveals GGC Repeat Expansion in ZFHX3 Associated with Spinocerebellar Ataxia Type 4

BACKGROUND

Spinocerebellar ataxia type 4 (SCA4) is an autosomal dominant ataxia with invariable sensory neuropathy originally described in a family with Swedish ancestry residing in Utah more than 25 years ago. Despite tight linkage to the 16q22 region, the molecular diagnosis has since remained elusive.

OBJECTIVES

Inspired by pathogenic structural variation implicated in other 16q-ataxias with linkage to the same locus, we revisited the index SCA4 cases from the Utah family using novel technologies to investigate structural variation within the candidate region.

METHODS

We adopted a targeted long-read sequencing approach with adaptive sampling on the Oxford Nanopore Technologies (ONT) platform that enables the detection of segregating structural variants within a genomic region without a priori assumptions about any variant features.

RESULTS

Using this approach, we found a heterozygous (GGC)n repeat expansion in the last coding exon of the zinc finger homeobox 3 (ZFHX3) gene that segregates with disease, ranging between 48 and 57 GGC repeats in affected probands. This finding was replicated in a separate family with SCA4. Furthermore, the estimation of this GGC repeat size in short-read whole genome sequencing (WGS) data of 21,836 individuals recruited to the 100,000 Genomes Project in the UK and our in-house dataset of 11,258 exomes did not reveal any pathogenic repeats, indicating that the variant is ultrarare.

CONCLUSIONS

These findings support the utility of adaptive long-read sequencing as a powerful tool to decipher causative structural variation in unsolved cases of inherited neurological disease. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Detection and discovery of repeat expansions in ataxia enabled by next-generation sequencing: present and future

Hereditary cerebellar ataxias are a heterogenous group of progressive neurological disorders that are disproportionately caused by repeat expansions (REs) of short tandem repeats (STRs). Genetic diagnosis for RE disorders such as ataxias are difficult as the current gold standard for diagnosis is repeat-primed PCR assays or Southern blots, neither of which are scalable nor readily available for all STR loci. In the last five years, significant advances have been made in our ability to detect STRs and REs in short-read sequencing data, especially whole-genome sequencing. Given the increasing reliance of genomics in diagnosis of rare diseases, the use of established RE detection pipelines for RE disorders is now a highly feasible and practical first-step alternative to molecular testing methods. In addition, many new pathogenic REs have been discovered in recent years by utilising WGS data. Collectively, genomes are an important resource/platform for further advancements in both the discovery and diagnosis of REs that cause ataxia and will lead to much needed improvement in diagnostic rates for patients with hereditary ataxia.

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.

WebSTR: A Population-wide Database of Short Tandem Repeat Variation in Humans

Short tandem repeats (STRs) are consecutive repetitions of one to six nucleotide motifs. They are hypervariable due to the high prevalence of repeat unit insertions or deletions primarily caused by polymerase slippage during replication. Genetic variation at STRs has been shown to influence a range of traits in humans, including gene expression, cancer risk, and autism. Until recently STRs have been poorly studied since they pose significant challenges to bioinformatics analyses. Moreover, genome-wide analysis of STR variation in population-scale cohorts requires large amounts of data and computational resources. However, the recent advent of genome-wide analysis tools has resulted in multiple large genome-wide datasets of STR variation spanning nearly two million genomic loci in thousands of individuals from diverse populations. Here we present WebSTR, a database of genetic variation and other characteristics of genome-wide STRs across human populations. WebSTR is based on reference panels of more than 1.7 million human STRs created with state of the art repeat annotation methods and can easily be extended to include additional cohorts or species. It currently contains data based on STR genotypes for individuals from the 1000 Genomes Project, H3Africa, the Genotype-Tissue Expression (GTEx) Project and colorectal cancer patients from the TCGA dataset. WebSTR is implemented as a relational database with programmatic access available through an API and a web portal for browsing data. The web portal is publicly available at https://webstr.ucsd.edu.

Insights from a genome-wide truth set of tandem repeat variation

Tools for genotyping tandem repeats (TRs) from short read sequencing data have improved significantly over the past decade. Extensive comparisons of these tools to gold standard diagnostic methods like RP-PCR have confirmed their accuracy for tens to hundreds of well-studied loci. However, a scarcity of high-quality orthogonal truth data limited our ability to measure tool accuracy for the millions of other loci throughout the genome. To address this, we developed a TR truth set based on the Synthetic Diploid Benchmark (SynDip). By identifying the subset of insertions and deletions that represent TR expansions or contractions with motifs between 2 and 50 base pairs, we obtained accurate genotypes for 139,795 pure and 6,845 interrupted repeats in a single diploid sample. Our approach did not require running existing genotyping tools on short read or long read sequencing data and provided an alternative, more accurate view of tandem repeat variation. We applied this truth set to compare the strengths and weaknesses of widely-used tools for genotyping TRs, evaluated the completeness of existing genome-wide TR catalogs, and explored the properties of tandem repeat variation throughout the genome. We found that, without filtering, ExpansionHunter had higher accuracy than GangSTR and HipSTR over a wide range of motifs and allele sizes. Also, when errors in allele size occurred, ExpansionHunter tended to overestimate expansion sizes, while GangSTR tended to underestimate them. Additionally, we saw that widely-used TR catalogs miss between 16% and 41% of variant loci in the truth set. These results suggest that genome-wide analyses would benefit from genotyping a larger set of loci as well as further tool development that builds on the strengths of current algorithms. To that end, we developed a new catalog of 2.8 million loci that captures 95% of variant loci in the truth set, and created a modified version of ExpansionHunter that runs 2 to 3x faster than the original while producing the same output.