Systematic dissection of biases in whole-exome and whole-genome sequencing reveals major determinants of coding sequence coverage

Yury A Barbitoff,Anna A Kostareva,Dmitrii E Polev,Irina V Shcherbakova,Artem M Kiselev,Andrey S Glotov,Alexander V Predeus,Elena A Serebryakova,Oleg S Glotov

doi:10.1038/s41598-020-59026-y

Abstract

Advantages and diagnostic effectiveness of the two most widely used resequencing approaches, whole exome (WES) and whole genome (WGS) sequencing, are often debated. WES dominated large-scale resequencing projects because of lower cost and easier data storage and processing. Rapid development of 3rd generation sequencing methods and novel exome sequencing kits predicate the need for a robust statistical framework allowing informative and easy performance comparison of the emerging methods. In our study we developed a set of statistical tools to systematically assess coverage of coding regions provided by several modern WES platforms, as well as PCR-free WGS. We identified a substantial problem in most previously published comparisons which did not account for mappability limitations of short reads. Using regression analysis and simple machine learning, as well as several novel metrics of coverage evenness, we analyzed the contribution from the major determinants of CDS coverage. Contrary to a common view, most of the observed bias in modern WES stems from mappability limitations of short reads and exome probe design rather than sequence composition. We also identified the ~ 500 kb region of human exome that could not be effectively characterized using short read technology and should receive special attention during variant analysis. Using our novel metrics of sequencing coverage, we identified main determinants of WES and WGS performance. Overall, our study points out avenues for improvement of enrichment-based methods and development of novel approaches that would maximize variant discovery at optimal cost.

Highlights

Advantages and diagnostic effectiveness of the two most widely used resequencing approaches, whole exome (WES) and whole genome (WGS) sequencing, are often debated
It is important to note that most modern variant calling tools ignore reads with mapping quality (MQ) less than 10 and reads marked as PCR or optical duplicates; such reads were removed when calculating coverage
Most sources agree that whole-genome sequencing (WGS) is 2 to 3 times more expensive, but the number changes a lot between different centers

Summary

Introduction

Advantages and diagnostic effectiveness of the two most widely used resequencing approaches, whole exome (WES) and whole genome (WGS) sequencing, are often debated. The issue of WES/WGS comparison has been addressed by several studies that sought out optimal sequencing method to achieve maximum coverage of the protein-coding regions of the genome (listed in Supplementary Table S1). One of these included Agilent and Nimblegen (Roche) WES capture technologies, that were compared with the conventional WGS approach in terms of resulting coverage per sequencing read and the efficiency of clinically significant SNV detection[15]. In several more recent studies, it was repeatedly stated that WGS provides more even and unbiased coverage of coding regions and generates more accurate variant calls[13,16,17]

Methods

Results

Conclusion