Low-coverage whole genome sequencing followed by imputation has been proposed as a cost-effective genotyping approach for disease and population genetics studies. However, its competitiveness against SNP arrays is undermined as current imputation methods are computationally expensive and unable to leverage large reference panels. Here, we describe a method, GLIMPSE, for phasing and imputation of low-coverage sequencing datasets from modern reference panels. We demonstrate its remarkable performance across different coverages and human populations. It achieves imputation of a full genome for less than $1, outperforming existing methods by orders of magnitude, with an increased accuracy of more than 20% at rare variants. We also show that 1x coverage enables effective association studies and is better suited than dense SNP arrays to access the impact of rare variations. Overall, this study demonstrates the promising potential of low-coverage imputation and suggests a paradigm shift in the design of future genomic studies.

The UK Biobank performed whole-genome sequencing (WGS) and whole-exome sequencing (WES) across hundreds of thousands of individuals, allowing researchers to study the effects of both common and rare variants. Haplotype phasing distinguishes the two inherited copies of each chromosome into haplotypes and unlocks novel analyses at the haplotype level. In this work, we describe a new phasing method, SHAPEIT5, that accurately and rapidly phases large sequencing datasets and illustrates its key features on the UK Biobank WGS and WES data. First, we show that it phases rare variants with high accuracy. For instance, variants found in 1 sample out of 100,000 in the WES data are phased with accuracy above 95%. Second, we show that it can phase singletons, although with moderate accuracy, thereby making their inclusion in downstream analyses possible. Third, we show that the use of UK Biobank as a reference panel increases the accuracy of genotype imputation, an increase that is more pronounced when phased with SHAPEIT5 compared to other methods. Finally, we screen the phased WES data for loss-of-function (LoF) compound heterozygous (CH) events and identify 549 genes in which both gene copies are found knocked out. This list of genes complements current knowledge of gene essentiality in the human genome. We provide SHAPEIT5 in an open-source format, providing researchers with the means to leverage haplotype information in genetic studies.

10Low-coverage whole genome sequencing followed by imputation has been proposed as a 11 cost-effective genotyping approach for disease and population genetics studies. However, its 12 competitiveness against SNP arrays is undermined as current imputation methods are 13 computationally expensive and unable to leverage large reference panels. 14 Here, we describe a method, GLIMPSE, for phasing and imputation of low-coverage 15 sequencing datasets from modern reference panels. We demonstrate its remarkable 16 performance across different coverages and human populations. It achieves imputation of a 17 full genome for less than $1, outperforming existing methods by orders of magnitude, with an 18 increased accuracy of more than 20% at rare variants. We also show that 1x coverage enables 19 effective association studies and is better suited than dense SNP arrays to access the impact 20 of rare variations. Overall, this study demonstrates the promising potential of low-coverage 21 imputation and suggests a paradigm shift in the design of future genomic studies. 22 23