Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders

Sun, Y.; Liu, F.; Fan, C.; Wang, Y.; Song, L.; Fang, Z.; Han, R.; Wang, Z.; Wang, X.; Yang, Z.; Xu, Z.; Peng, J.; Shi, C.; Zhang, H.; Dong, W.; Huang, H.; Li, Y.; Le, Y.; Sun, J.; Peng, Z.

doi:10.1101/2020.04.01.019570

bioRxiv · 10.1101/2020.04.01.019570

Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders

Sun, Y.·Liu, F.·Fan, C.·Wang, Y.·Song, L.·Fang, Z.·Han, R.·Wang, Z.·Wang, X.·Yang, Z.·Xu, Z.·Peng, J.·Shi, C.·Zhang, H.·Dong, W.·Huang, H.·Li, Y.·Le, Y.·Sun, J.·Peng, Z.

View original source ↗Export metadata ↓

Abstract

BackgroundWith the reduce of cost and incomparable advantages, WGS is likely to change the way of clinical diagnosis of rare and undiagnosed diseases. However, the sensitivity and breadth of coverage of clinical WGS as a diagnostic test for genetic disorders has not been fully evaluated, especially for CNV detection. MethodsAll the samples underwent WGS using MGISEQ-2000. The performance of NA12878, YH cell line, and the Chinese trios were measured for sensitivity, PPV, depth and breadth of coverage. We also compared the performance of WES and WGS using NA12878. The sensitivity and PPV were tested using family-based trio design in the Chinese trios. We also developed a systematic WGS pipeline for the analysis of 8 clinical cases with known disease-causing variants. ResultsIn general, the sensitivity and PPV for SNV/indel detection increased with mean depth, and reached a plateau at a ~40X mean depth using down-sampling samples of NA12878. With a mean depth of 40X, the sensitivity of homozyous and heterozygous SNPs of NA12878 was >99.25% and >99.50% respectively, and PPVs were 99.97% and 98.96%. Homozygous and heterozygous indels showed lower sensitivity and PPV. The sensitivity and PPV is still not 100% even with a mean depth of ~150X. We also observed a substantial variation in the sensitivity of CNV detection across different tools, especially in CNVs with a size of less than 1kb. In general, the breadth of coverage for disease-associated genes and CNVs increased with mean depth. The sensitivity and coverage of WGS (~40X) is better than WES (~120X). Among the Chinese trios with ~40X mean depth, the sensitivity in the offspring was >99.48% and >96.36% for SNP and indel detection, and PPVs were 99.86% and 97.93%. All the 12 previously validated variants in the 8 clinical cases were successfully detected by our WGS pipeline. ConclusionsThe current standard of a mean depth of 40X may be sufficient for SNV/indel detection and identification of most CNVs. Clinical scientists should know the range of sensitivity and PPV for different classes of variants for a particular WGS pipeline, which would be useful when interpreting and delivering clinical reports.

Source connections

Published article ↗

Explore related subjects

genomics Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Sun, Y., Liu, F., Fan, C., Wang, Y., Song, L., Fang, Z., Han, R., Wang, Z., Wang, X., Yang, Z., Xu, Z., Peng, J., Shi, C., Zhang, H., Dong, W., Huang, H., Li, Y., Le, Y., Sun, J., Peng, Z.. 2020-04-02. Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders. https://doi.org/10.1101/2020.04.01.019570

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Somatic variant detection using an individual-specific pangenome reference: a case study of a pediatric acute myeloid leukemia patient

Background: Reference bias can cause false or missed somatic variant calls, also in clinically relevant genes. Pangenomes aim to reduce this bias, but evidence of their diagnostic benefit is lacking. We tested how an individual-specific pangenome affects somatic variant calling in bulk samples and single cells. Results: We built an individual-specific pangenome from Nanopore assemblies of normal hematopoietic stem and progenitor cells of a child with acute myeloid leukemia. We aligned short-read whole-genome sequencing data of bulk and single-cell samples to hg38 and to the pangenome, and called somatic variants with standard downstream tools after anchoring pangenome alignments to hg38. Single nucleotide variants were mostly shared, while indel calls unique to the pangenome were fewer than those unique to hg38, mostly in repeats. Both approaches detected NUP98-NSD1 and FLT3 internal tandem duplication (FLT3-ITD) drivers. The pangenome-based phylogeny showed more parallel branching in comparison to hg38-based tree. The pangenome removed three false-positive PRSS1 variants and, in single cells, frameshift insertion calls next to polyG and polyC repeats. However, surjection to hg38 coordinates split a WT1 driver indel call in a low-complexity region into two separate calls. Validation showed that all somatic structural variant calls, except NUP98-NSD1 and FLT3-ITD, were germline variants or artifacts. Conclusions: The use of individual-specific pangenome led to fewer false-positive indel and driver calls, mainly in repeats and single cells, and changed the branching of the inferred phylogeny. However, surjection artifacts and false-positive somatic structural variants show that pangenome-based results need read-level inspection and validation before clinical use.

genomics↗

bioRxiv2026

Molecule-resolved inference reveals the spatial organization of transcriptional programs

Transcriptional programs encode cellular identity and physiological activity, linking gene regulation to cellular phenotypes. Although spatial transcriptomics measures individual RNA molecules across intact tissues, most analyses aggregate them into cells or pixels, obscuring molecular level functional dynamics. We introduce FICTURE2, a statistical model that infers the transcriptional program from which each individual molecule is generated, using gene identity and spatial context alone without segmentation or binning. FICTURE2 learns programs with distinct spatial distributions, ranging from millimeter-scale continuous transition to micron-scale subcellular localization, the coexisting patterns of which then reveal both cellular identity and physiological activity with unified interpretations. FICTURE2 supports both unsupervised and reference-guided inference and is orders of magnitude more efficient than alternative approaches, enabling systematic analysis of large-scale spatial datasets as we demonstrate in data across diverse tissue types profiled by various spatial technologies.

genomics↗

bioRxiv2026

Shared genomic signatures of Arctic adaptation among distantly related plant lineages

Extreme environments impose strong selection pressures that can drive convergent adaptation among distantly related species. Arctic plants survive low temperatures, 24-hour light in summer and darkness in winter, short growing seasons, limited precipitation, nutrient-poor soils, and extreme seasonal variation. To test if these conditions are associated with shared genomic signatures, we generated a chromosome-level genome assembly for Oxyria digyna and compared it with existing reference genomes for three distantly related Arctic species (Cochlearia groenlandica, Draba nivalis, Dryas octopetala) and for 16 non-Arctic species from the same families. We identified 214 orthogroups with signatures of positive selection in all Arctic species, 1.6 times the number shared among the non-Arctic species. Although no gene ontology (GO) categories remained significantly enriched after multiple-testing correction, descriptive annotations included genes involved in general functions including protein folding, glycolysis, transcription, and oxidative-stress responses. Orthogroups showing copy number variation were associated with biotic interactions, sexual reproduction, and nutrient acquisition, suggesting that species may respond to biotic and nutrient stresses by shifts in gene copy number. Arctic and alpine genomes contained lower proportions of some repetitive elements, including terminal inverted repeats, and smaller regions of centromeric repeats than non-Arctic genomes. Overall, we see shared genes under positive selection, similar functions of genes with high copy number variation, and lower counts of some repetitive elements in the Arctic plant genomes. Our findings reveal a shared genomic signature of Arctic adaptation across deeply diverged plant lineages, suggesting that evolution in extreme environments repeatedly targets similar genomic features.

genomics↗