How many high-quality variants were called in coding exons?

Of 123,629 high-quality indels called in coding exons, 117,242 (95%) have a length < 6 bases, with shorter deletions being the most common (Fig. 1e).

How many PTVs are found in ExAC?

Among the 7,404,909 high-quality variants in ExAC, the authors found 179,774 high-confidence PTVs (as defined in Supplementary Information section 6), 121,309 of which are singletons.

How many possible CpG transitions were observed?

the authors observe 63.1% of possibleCpG transitions (C to T variants, in which the adjacent base is G), while only observing 3% of possible transversions and 9.2% of other possible transitions (Supplementary Table 9).

What is the way to predict the number of synonymous variants?

The model performs well in predicting the number of synonymous variants, which should be under minimal selection, per gene (r = 0.98; Extended Data Fig. 3b).The authors quantified deviation from expectation with a Z score11, which for synonymous variants is centred at zero, but is significantly shifted towards higher values (greater constraint) for both missense and PTV (Wilcoxon P < 10−50 for both; Fig. 3a).

How many variants had sufficient evidence for pathogenicity?

Nine variants had sufficient data to support disease association, typically with eithermild or incompletely penetrant disease effects; the remainder either had insufficient evidence for pathogenicity, no claim of pathogenicity, or were benign traits (Supplementary Information section 5.3).

What is the main reason for the large sample size of ExAC?

most ExAC individuals were ascertained for biomedically important disease; although the authors have attempted to exclude severe paediatric diseases, the inclusion of both cases and controls for several polygenic disorders means that ExAC certainly contains disease-associated variants37.

What is the significance of the ExAC data?

The very large sample size of ExAC also provides opportunities for a high-resolution analysis of the sensitivity of human genes to functional variation.

How many exomes were assembled from a wide range of consortia?

The authors assembled approximately 1 petabyte of raw sequencing data (FASTQ files) from 91,796 individual exomes drawn from a wide range of primarily disease-focused consortia (Supplementary Table 2).

What is the value of the missense Z score?

Z scores show no correlation with the number of tissues in which a gene is expressed, but the most missense- and PTV-constrained genes tend to be expressed in more tissues.

What are the main reasons why the data are difficult to access?

In theory, these data represent a powerful source of information about the global patterns of human genetic variation, but in practice, are difficult to access for practical, logistical, and ethical reasons; in addition, their utility is complicated by the heterogeneity in the experimental methodologies and variant calling pipelines used to generate them.

(PDF) Analysis of protein-coding genetic variation in 60,706 humans (2015) | Monkol Lek

Q: What have the authors contributed in "Analysis of protein-coding genetic variation in 60,706 humans" ?

Monkol Lek et al. this paper presented an aggregation consortium of the authors of this paper.

Q: What have the authors stated for future works in "Analysis of protein-coding genetic variation in 60,706 humans" ?

Finally, and most critically, detailed phenotype data are unavailable for the vast majority of ExAC samples ; future initiatives that assemble sequence and clinical data from very large-scale cohorts will be required to fully translate human genetic findings into biological and clinical understanding. Although the ExAC data set exceeds the scale of previously available frequency reference data sets, much remains to be gained by further increases in sample size.

Q: What is the reason for the inclusion of whole genomes in the ExAC data set?

ExAC was made possible by the willingness of multiple large disease-focused consortia to share their raw data, and by the availability of the software and computational resources required to create a harmonized variant call set on the scale of tens of thousands of samples.

Q: How did ExAC reduce the number of candidate variants?

Filtering on ExAC reduced the number of candidate protein-altering variants by sevenfold compared to the ESP data set, and was most powerful when the highest allele frequency in any one population (‘popmax’) was used rather than the average−5 0 5 10Z scorea0 0.2 0.4 0.6 0.8 1OlfactoryRecessiveAllDominantEssentialMild HIModerate HISevere HIFraction of genes with pLI ≥ 0.9bSynonymous Missense Protein–truncatingLow Medium High Low Medium High Low Medium High 0510152025303540

Q: How many PTVs are found in ExAC?

Among the 7,404,909 high-quality variants in ExAC, the authors found 179,774 high-confidence PTVs (as defined in Supplementary Information section 6), 121,309 of which are singletons.

Q: How many possible CpG transitions were observed?

the authors observe 63.1% of possibleCpG transitions (C to T variants, in which the adjacent base is G), while only observing 3% of possible transversions and 9.2% of other possible transitions (Supplementary Table 9).

Q: What is the way to predict the number of synonymous variants?

The model performs well in predicting the number of synonymous variants, which should be under minimal selection, per gene (r = 0.98; Extended Data Fig. 3b).The authors quantified deviation from expectation with a Z score11, which for synonymous variants is centred at zero, but is significantly shifted towards higher values (greater constraint) for both missense and PTV (Wilcoxon P < 10−50 for both; Fig. 3a).

Q: How many variants had sufficient evidence for pathogenicity?

Nine variants had sufficient data to support disease association, typically with eithermild or incompletely penetrant disease effects; the remainder either had insufficient evidence for pathogenicity, no claim of pathogenicity, or were benign traits (Supplementary Information section 5.3).

Q: What is the main reason for the large sample size of ExAC?

most ExAC individuals were ascertained for biomedically important disease; although the authors have attempted to exclude severe paediatric diseases, the inclusion of both cases and controls for several polygenic disorders means that ExAC certainly contains disease-associated variants37.

Most frequently asked questions

1. What have the authors contributed in "Analysis of protein-coding genetic variation in 60,706 humans" ?

Monkol Lek et al. this paper presented an aggregation consortium of the authors of this paper.

2. What have the authors stated for future works in "Analysis of protein-coding genetic variation in 60,706 humans" ?

Finally, and most critically, detailed phenotype data are unavailable for the vast majority of ExAC samples ; future initiatives that assemble sequence and clinical data from very large-scale cohorts will be required to fully translate human genetic findings into biological and clinical understanding.. Although the ExAC data set exceeds the scale of previously available frequency reference data sets, much remains to be gained by further increases in sample size.

3. What is the reason for the inclusion of whole genomes in the ExAC data set?

ExAC was made possible by the willingness of multiple large disease-focused consortia to share their raw data, and by the availability of the software and computational resources required to create a harmonized variant call set on the scale of tens of thousands of samples.

4. How did ExAC reduce the number of candidate variants?

Filtering on ExAC reduced the number of candidate protein-altering variants by sevenfold compared to the ESP data set, and was most powerful when the highest allele frequency in any one population (‘popmax’) was used rather than the average−5 0 5 10Z scorea0 0.2 0.4 0.6 0.8 1OlfactoryRecessiveAllDominantEssentialMild HIModerate HISevere HIFraction of genes with pLI ≥ 0.9bSynonymous Missense Protein–truncatingLow Medium High Low Medium High Low Medium High 0510152025303540

Analysis of protein-coding genetic variation in 60,706 humans

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Most frequently asked questions

1. What have the authors contributed in "Analysis of protein-coding genetic variation in 60,706 humans" ?

2. What have the authors stated for future works in "Analysis of protein-coding genetic variation in 60,706 humans" ?

3. What is the reason for the inclusion of whole genomes in the ExAC data set?

4. How did ExAC reduce the number of candidate variants?

5. How many high-quality variants were called in coding exons?

6. How many PTVs are found in ExAC?

7. How many possible CpG transitions were observed?

8. What is the way to predict the number of synonymous variants?

9. How many variants had sufficient evidence for pathogenicity?

10. What is the main reason for the large sample size of ExAC?

11. What is the significance of the ExAC data?

12. How many exomes were assembled from a wide range of consortia?

13. What is the value of the missense Z score?

14. What are the main reasons why the data are difficult to access?

Figures

Citations

ClinVar: improving access to variant interpretations and supporting evidence.

CADD: predicting the deleteriousness of variants throughout the human genome.

GENCODE reference annotation for the human and mouse genomes.

Biological Structure and Function Emerge from Scaling Unsupervised Learning to 250 Million Protein Sequences

VarSome: the human genomic variant search engine

References

Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.

A global reference for human genetic variation.

A framework for variation discovery and genotyping using next-generation DNA sequencing data

Lethality and centrality in protein networks

The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans

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