Exome-wide benchmark of difficult-to-sequence regions using short-read next-generation DNA sequencing

Abstract

Next-generation DNA sequencing (NGS) in short-read mode has been recently used for genetic testing in various clinical settings. NGS data accuracy is crucial in clinical settings, and several reports regarding quality control of NGS data, focusing mostly on establishing NGS sequence read accuracy, have been published thus far. Variant calling is another critical source of NGS errors that remains mostly unexplored despite its established significance. In this study, we used a machine-learning-based method to establish an exome-wide benchmark of difficult-to-sequence regions using 10 genome sequence features on the basis of real-world NGS data accumulated in The Genome Aggregation Database (gnomAD) of the human reference genome sequence (GRCh38/hg38). We used the obtained metrics, designated “UNMET score,” along with other lines of structural information of the human genome to identify difficult-to-sequence genomic regions using conventional NGS. Thus, the UNMET score could provide appropriate caveats to address potential sequential errors in protein-coding exons of the human reference genome sequence GRCh38/hg38 in clinical sequencing.

Comparative evaluation of four exome enrichment solutions in 2024: Agilent, Roche, Vazyme and Nanodigmbio

“…Unfortunately, none of the kits evaluated in this study excelled in covering these problematic areas although they didn't show a dramatic shift in coverage of GC content. Now it becomes more clear that well-designed probes kits are less affected by GC-bias and the problem of regions with low mapping quality is more related with short read sequencing (13,(17)(18)(19). We recommend that researchers consider these limitations when designing experiments, and also refer to the IGV visualization of difficult-to-sequence genes from Hijikata's article, which we found particularly helpful.…”

“…It has been previously identified that approximately 1Mb of the human exome can be skipped during sequencing (17,18). Recent research has precisely localized and described these difficult-to-sequence regions in exome data, which are mainly affected by low-mappability regions, such as pseudogenes, tandem repeats, homopolymers, and other low-complexity regions (19). While WGS increases the diagnostic yield over WES (20), understanding WES's challenges could drive improvements, minimize limitations and make it a more cost-effective procedure.…”

Nanopore sequencing of 1000 Genomes Project samples to build a comprehensive catalog of human genetic variation

“…For example, 42% (47,315/113,696) of the high-confidence SVs occur fully outside of the GIAB Tier 1 regions, and visual inspection of 30 events confirmed the presence of an SV. We also identified 407 high-confidence SVs within coding regions defined as unreliable for variant identification using short-read sequencing based on analysis of gnomAD data (Hijikata et al 2024). In both cases, these SVs reside in regions that may be filtered by variant annotation pipelines.…”