Extensive disruption of protein interactions by genetic variants across the allele frequency spectrum in human populations

Fragoza, Robert; Das, Jishnu; Wierbowski, Shayne D.; Liang, Jin; Tran, Tina N.; Liang, Siqi; Beltrán, Juan Felipe; Rivera-Erick, Christen A.; Ye, Kaixiong; Wang, Ting-Yi; Li, Yao; Mort, Matthew; Stenson, Peter D.; Cooper, David Neil; Wei, Xiaomu; Keinan, Alon; Schimenti, John C.; Clark, Andrew G.; Yu, Haiyuan

doi:10.1038/s41467-019-11959-3

Cited by 57 publications

(76 citation statements)

References 76 publications

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“…Sequence conservation could partially explain the correlation between GTS score and gene essentiality, as essential genes tend to be more conserved due to their functional importance and at the same time accumulate less deleterious rare mutations in recent human history. Similar to noted trends of both essential and disease-associated genes [67,68], human genes with GTS scores in the lowest decile, regardless of their essentiality, exhibit increased numbers of protein interactions than those from higher GTS deciles ( Fig 4D).…”

Section: Plos Computational Biologysupporting

confidence: 64%

Mutation severity spectrum of rare alleles in the human genome is predictive of disease type

et al. 2020

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The human genome harbors a variety of genetic variations. Single-nucleotide changes that alter amino acids in protein-coding regions are one of the major causes of human phenotypic variation and diseases. These single-amino acid variations (SAVs) are routinely found in whole genome and exome sequencing. Evaluating the functional impact of such genomic alterations is crucial for diagnosis of genetic disorders. We developed DeepSAV, a deeplearning convolutional neural network to differentiate disease-causing and benign SAVs based on a variety of protein sequence, structural and functional properties. Our method outperforms most stand-alone programs, and the version incorporating population and gene-level information (DeepSAV+PG) has similar predictive power as some of the best available. We transformed DeepSAV scores of rare SAVs in the human population into a quantity termed "mutation severity measure" for each human protein-coding gene. It reflects a gene's tolerance to deleterious missense mutations and serves as a useful tool to study gene-disease associations. Genes implicated in cancer, autism, and viral interaction are found by this measure as intolerant to mutations, while genes associated with a number of other diseases are scored as tolerant. Among known disease-associated genes, those that are mutation-intolerant are likely to function in development and signal transduction pathways, while those that are mutation-tolerant tend to encode metabolic and mitochondrial proteins.

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Section: Plos Computational Biologysupporting

confidence: 64%

Mutation severity spectrum of rare alleles in the human genome is predictive of disease type

et al. 2020

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“…Instead, AvgAI scores tend to select for gene essentiality, with an increase in essential genes and a decrease in non-essential genes at the lowest AvgAI decile ( Figure 4C). Similar to noted trends of both essential and disease-associated genes [58,59], human genes with AvgAI scores in the lowest decile, regardless of their essentiality, exhibit increased numbers of protein interactions than those from higher AvgAI deciles ( Figure 4D).…”

Section: Mutation Severity Measures Based On Deepsav Identify Potensupporting

confidence: 61%

Mutation severity spectrum of rare alleles in the human genome is predictive of disease type

Pei

Kinch

Grishin

2019

Preprint

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The human genome harbors a variety of genetic variations. Single-nucleotide changes that alter amino acids in protein-coding regions are one of the major causes of human phenotypic variation and diseases. These single-amino acid variations (SAVs) are routinely found in whole genome and exome sequencing. Evaluating the functional impact of such genomic alterations is crucial for diagnosis of genetic disorders. We developed DeepSAV, a deep-learning convolutional neural network to differentiate disease-causing and benign SAVs based on a variety of protein sequence, structural and functional properties. Our method outperforms most stand-alone programs and has similar predictive power as some of the best available. We transformed DeepSAV scores of rare SAVs observed in the general population into a mutation severity measure of protein-coding genes. This measure reflects a gene's tolerance to deleterious missense mutations and serves as a useful tool to study gene-disease associations. Genes implicated in cancer, autism, and viral interaction are found by this measure as intolerant to mutations, while genes associated with a number of other diseases are scored as tolerant. Among known diseaseassociated genes, those that are mutation-intolerant are likely to function in development and signal transduction pathways, while those that are mutation-tolerant tend to encode metabolic and mitochondrial proteins.

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“…Vector construction and Western blot were performed as previous described 22 . Briefly, the WT and mutant RABL2A open reading frames were inserted into pDEST-DUAL vector by Gateway LR reactions and then the vectors were transfected into HEK293T cells.…”

Section: Methodsmentioning

confidence: 99%

Variants inRABL2Acausing male infertility and ciliopathy

Ding

Fragoza

Singh

et al. 2020

Preprint

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Purpose: Approximately 7% of men suffer from infertility worldwide and sperm abnormalities are the major cause. Though genetic defects are thought to underlie a substantial fraction of all male infertility cases, the actual molecular bases are usually undetermined. Because the consequences of most genetic variants in populations are unknown, this complicates genetic diagnosis even after genome sequencing of patients. Some patients with ciliopathies, including primary ciliary dyskinesia (PCD) and Bardet-Biedl syndrome (BBS), also suffer from infertility because sperm flagella, which share several characteristics with cilia, are also affected in these patients. Methods: To identify infertility-causing genetic variants in human populations, we used in silico predictions to identify potentially deleterious SNP (single nucleotide polymorphism) alleles of RABL2A, a gene essential for normal cilia and flagella function. Candidate variants were assayed for protein stability in vitro, and the destabilizing variants were modeled in mice using CRISPR/Cas9-mediated genome editing. The resulting mice were characterized phenotypically for reproductive and developmental defects. Results: Two of the SNP alleles, Rabl2L119F (rs80006029) and Rabl2V158F (rs200121688), destabilized the protein. Mice bearing these alleles exhibited PCD- and BBS-associated disorders including male infertility, early growth retardation, excessive weight gain in adulthood, heterotaxia, pre-axial polydactyly, neural tube defects (NTD) and hydrocephalus. Conclusion: Our study identified and validated pathogenicity of two variants causing ciliopathies and male infertility in human populations, and identified phenotypes not previously described for null alleles of Rabl2.

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Extensive disruption of protein interactions by genetic variants across the allele frequency spectrum in human populations

Cited by 57 publications

References 76 publications

Mutation severity spectrum of rare alleles in the human genome is predictive of disease type

Mutation severity spectrum of rare alleles in the human genome is predictive of disease type

Mutation severity spectrum of rare alleles in the human genome is predictive of disease type

Variants inRABL2Acausing male infertility and ciliopathy

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