Quantifying negative selection in human 3’ UTRs uncovers constrained targets of RNA-binding proteins

Findlay, Scott D.; Romo, Lindsay; Burge, Christopher B.

doi:10.1101/2022.11.30.518628

Cited by 11 publications

(7 citation statements)

References 82 publications

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“…Even though, as mentioned earlier, it has been shown that intergenic variants may be used as an alternative class of variants for the estimation of the baseline level of rare variation (Findlay et al, 2022), we had insufficient evidence that intergenic variants could be used interchangeably with synonymous variants for the purpose of model calibration without any significant effect on the results.…”

Section: Methodsmentioning

confidence: 89%

“…Overall, we believe that our proposed context-based approach is superior compared with using mutability as a proxy for the estimation of the expected level of rare variation, as mutation rates modelling proves a difficult task (Findlay et al, 2022). Even though it is possible to reduce bias of MAPS towards transversion variants by modifying the fit of the model, we argue that this approach can be seen as ad hoc and not future-proof, considering that every new release of gnomAD would require refitting the model.…”

Section: Discussionmentioning

confidence: 99%

“…MAPS scores are calculated as the scaled excess or deficit of singletons (variants with allele count of 1), where the expected number is derived based on context sequence from a singletons-by-mutability model calibrated on a relatively neutral class of variants. Even though it has been shown that intergenic variants can be used for calibration (Findlay et al, 2022), synonymous variants have traditionally been preferred for this purpose. Importantly, given then the complexity of mutability estimation, there is no straightforward way of modelling mutation rates; however, attempts have been made to incorporate additional mutability-related annotations in the singletons-by-mutability model (Findlay et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…Even though it has been shown that intergenic variants can be used for calibration (Findlay et al, 2022), synonymous variants have traditionally been preferred for this purpose. Importantly, given then the complexity of mutability estimation, there is no straightforward way of modelling mutation rates; however, attempts have been made to incorporate additional mutability-related annotations in the singletons-by-mutability model (Findlay et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Improving estimates of negative selection in human genome using CAPS

Gudkov,

Thibaut,

Giannoulatou

2024

Preprint

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Despite ongoing efforts, variant interpretation in disease sequencing studies is often hindered by the lack of well-established ways of determining the potential pathogenicity of genetic variation, especially for understudied classes of single-nucleotide variants (SNVs). Population genetics methods offer an attractive solution to this problem by enabling the assessment of the effects of SNVs through their distributions in human populations. For instance, negative selection is known to shift site-frequency spectra of genetic variation, thus affecting the ratio of singleton variants. It has been shown that the extent of negative selection can serve as a proxy for deleteriousness. An example of this approach is the Mutability-Adjusted Proportion of Singletons (MAPS) metric. Although MAPS proves a useful instrument for the assessment of selection-based deleteriousness in SNVs, it is highly sensitive to the calibration of the singletons-by-mutability model, which results in potentially biased estimates for some classes of variants. Building up on the methodology used in MAPS, we developed a novel metric of negative selection in the human genome - CAPS, or Context-Adjusted Proportion of Singletons. Compared to its predecessor, CAPS provides estimates of negative selection that are less biased and have more accurate confidence intervals. CAPS inherits some of the same features that make MAPS useful for studying SNVs, yet the key difference of our method is the complete elimination of the mutability layer in the model, which makes the metric more robust and reliable. We believe that CAPS holds promise for improving the discovery of new disease-variant associations in clinical and research settings.

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Section: Methodsmentioning

confidence: 89%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Improving estimates of negative selection in human genome using CAPS

Gudkov,

Thibaut,

Giannoulatou

2024

Preprint

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“…RNA binding protein predictions were generated using the methods detailed in Findlay et al ( 38 ) for all possible variants within motifs that are proximal to ENCODE eCLIP sites, that are also high affinity sites as predicted by RBPamp(39). These were intersected with our variants and filtered to retain only those with a reference affinity of ≥ 0.1 and with an impact of ‘loss of binding’ predicted by the RBP binding affinity model (defined as alternative allele affinity / reference allele affinity < ⅓).…”

Section: Methodsmentioning

confidence: 99%

Systematic identification of disease-causing promoter and untranslated region variants in 8,040 undiagnosed individuals with rare disease

Martin-Geary,

Blakes,

Dawes

et al. 2023

Preprint

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BackgroundBoth promoters and untranslated regions (UTRs) have critical regulatory roles, yet variants in these regions are largely excluded from clinical genetic testing due to difficulty in interpreting pathogenicity. The extent to which these regions may harbour diagnoses for individuals with rare disease is currently unknown.MethodsWe present a framework for the identification and annotation of potentially deleterious proximal promoter and UTR variants in known dominant disease genes. We use this framework to annotatede novovariants (DNVs) in 8,040 undiagnosed individuals in the Genomics England 100,000 genomes project, which were subject to strict region-based filtering, clinical review, and validation studies where possible. In addition, we performed region and variant annotation-based burden testing in 7,862 unrelated probands against matched unaffected controls.ResultsWe prioritised eleven DNVs and identified an additional variant overlapping one of the eleven. Ten of these twelve variants (82%) are in genes that are a strong match to the individual’s phenotype and six had not previously been identified. Through burden testing, we did not observe a significant enrichment of potentially deleterious promoter and/or UTR variants in individuals with rare disease collectively across any of our region or variant annotations.ConclusionsOverall, we demonstrate the value of screening promoters and UTRs to uncover additional diagnoses for previously undiagnosed individuals with rare disease and provide a framework for doing so without dramatically increasing interpretation burden.

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Genome-wide identification of dominant polyadenylation hexamers for use in variant classification

Shiferaw,

Hong,

Cooper

et al. 2023

Human Molecular Genetics

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Polyadenylation is an essential process for the stabilization and export of mRNAs to the cytoplasm and the polyadenylation signal hexamer (herein referred to as hexamer) plays a key role in this process. Yet, only 14 Mendelian disorders have been associated with hexamer variants. This is likely an under-ascertainment as hexamers are not well defined and not routinely examined in molecular analysis. To facilitate the interrogation of putatively pathogenic hexamer variants, we set out to define functionally important hexamers genome-wide as a resource for research and clinical testing interrogation. We identified predominant polyA sites (herein referred to as pPAS) and putative predominant hexamers across protein coding genes (PAS usage >50% per gene). As a measure of the validity of these sites, the population constraint of 4532 predominant hexamers were measured. The predominant hexamers had fewer observed variants compared to non-predominant hexamers and trimer controls, and CADD scores for variants in these hexamers were significantly higher than controls. Exome data for 1477 individuals were interrogated for hexamer variants and transcriptome data were generated for 76 individuals with 65 variants in predominant hexamers. 3′ RNA-seq data showed these variants resulted in alternate polyadenylation events (38%) and in elongated mRNA transcripts (12%). Our list of pPAS and predominant hexamers are available in the UCSC genome browser and on GitHub. We suggest this list of predominant hexamers can be used to interrogate exome and genome data. Variants in these predominant hexamers should be considered candidates for pathogenic variation in human disease, and to that end we suggest pathogenicity criteria for classifying hexamer variants.

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Quantifying negative selection in human 3’ UTRs uncovers constrained targets of RNA-binding proteins

Cited by 11 publications

References 82 publications

Improving estimates of negative selection in human genome using CAPS

Improving estimates of negative selection in human genome using CAPS

Systematic identification of disease-causing promoter and untranslated region variants in 8,040 undiagnosed individuals with rare disease

Genome-wide identification of dominant polyadenylation hexamers for use in variant classification

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