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A massively parallel pipeline to clone DNA variants and examine molecular phenotypes of human disease mutations.

Wei X, Das J, Fragoza R, Liang J, Bastos de Oliveira FM, Lee HR, Wang X, Mort M, Stenson PD, Cooper DN, Lipkin SM, Smolka MB, Yu H - PLoS Genet. (2014)

Bottom Line: We describe a massively-parallel site-directed mutagenesis approach, "Clone-seq", leveraging next-generation sequencing to rapidly and cost-effectively generate a large number of mutant alleles.We use this pipeline to show that disease mutations on protein-protein interaction interfaces are significantly more likely than those away from interfaces to disrupt corresponding interactions.The general scheme of our experimental pipeline can be readily expanded to other types of interactome-mapping methods to comprehensively evaluate the functional relevance of all DNA variants, including those in non-coding regions.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicine, Weill Cornell College of Medicine, New York, New York, United States of America; Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, United States of America.

ABSTRACT
Understanding the functional relevance of DNA variants is essential for all exome and genome sequencing projects. However, current mutagenesis cloning protocols require Sanger sequencing, and thus are prohibitively costly and labor-intensive. We describe a massively-parallel site-directed mutagenesis approach, "Clone-seq", leveraging next-generation sequencing to rapidly and cost-effectively generate a large number of mutant alleles. Using Clone-seq, we further develop a comparative interactome-scanning pipeline integrating high-throughput GFP, yeast two-hybrid (Y2H), and mass spectrometry assays to systematically evaluate the functional impact of mutations on protein stability and interactions. We use this pipeline to show that disease mutations on protein-protein interaction interfaces are significantly more likely than those away from interfaces to disrupt corresponding interactions. We also find that mutation pairs with similar molecular phenotypes in terms of both protein stability and interactions are significantly more likely to cause the same disease than those with different molecular phenotypes, validating the in vivo biological relevance of our high-throughput GFP and Y2H assays, and indicating that both assays can be used to determine candidate disease mutations in the future. The general scheme of our experimental pipeline can be readily expanded to other types of interactome-mapping methods to comprehensively evaluate the functional relevance of all DNA variants, including those in non-coding regions.

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Relationships between molecular phenotypes and disease phenotypes.(a) Fraction of mutation pairs on the same gene that cause the same disease: for the same and different effects on protein stability. (b) Fraction of mutation pairs on the same gene that cause the same disease: for the same and different interaction disruption profiles. Error bars indicate +SE. (c) Crystal structure (PDB id: 1U7F) depicting the Y353S and R361C mutations (on Smad4) at interface residues for the Smad4-Smad3 interaction. (d) Y2H analysis of the effects of Smad Y353S, R361, and N13S mutations on its interactions with Smad3, Lmo4, Rassf5, and Smad9. Western blotting with anti-GFP antibody confirming the protein expression levels of wild-type Smad4 and its 3 mutant alleles – Y353S, R361C and N13S. γ-tubulin was used as a loading control.
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pgen-1004819-g005: Relationships between molecular phenotypes and disease phenotypes.(a) Fraction of mutation pairs on the same gene that cause the same disease: for the same and different effects on protein stability. (b) Fraction of mutation pairs on the same gene that cause the same disease: for the same and different interaction disruption profiles. Error bars indicate +SE. (c) Crystal structure (PDB id: 1U7F) depicting the Y353S and R361C mutations (on Smad4) at interface residues for the Smad4-Smad3 interaction. (d) Y2H analysis of the effects of Smad Y353S, R361, and N13S mutations on its interactions with Smad3, Lmo4, Rassf5, and Smad9. Western blotting with anti-GFP antibody confirming the protein expression levels of wild-type Smad4 and its 3 mutant alleles – Y353S, R361C and N13S. γ-tubulin was used as a loading control.

Mentions: We then analyzed whether the molecular phenotypes measured by our high-throughput GFP and Y2H assays are correlated with corresponding disease phenotypes. We first examined how mutation pairs on the same gene affect protein stability and its relationship to their corresponding diseases. We find that pairs of mutations that are either both stable or both unstable cause the same disease in 68% and 70% of cases, respectively. However, pairs comprising one stable and one unstable mutation cause the same disease in only 30% of cases (P = 6×10−9 and 8×10−10, respectively, Fig. 5a). For example, we find that the mutations R727C and L844F on the spindle checkpoint kinase Bub1b both cause the protein to become unstable and lose all its interactors. These mutations are both associated with the same disease, mosaic variegated aneuploidy, an autosomal recessive disorder that causes predominantly trisomies and monosomies of different chromosomes [22], [23]. Since our GFP assay shows that these two mutations cause loss of protein product, our results are consistent with Matusuura et al.'s finding that a more than 50% decrease in Bub1b activity leads to abnormal mitotic spindle checkpoint function and mosaic variegated aneuploidy [24].


A massively parallel pipeline to clone DNA variants and examine molecular phenotypes of human disease mutations.

Wei X, Das J, Fragoza R, Liang J, Bastos de Oliveira FM, Lee HR, Wang X, Mort M, Stenson PD, Cooper DN, Lipkin SM, Smolka MB, Yu H - PLoS Genet. (2014)

Relationships between molecular phenotypes and disease phenotypes.(a) Fraction of mutation pairs on the same gene that cause the same disease: for the same and different effects on protein stability. (b) Fraction of mutation pairs on the same gene that cause the same disease: for the same and different interaction disruption profiles. Error bars indicate +SE. (c) Crystal structure (PDB id: 1U7F) depicting the Y353S and R361C mutations (on Smad4) at interface residues for the Smad4-Smad3 interaction. (d) Y2H analysis of the effects of Smad Y353S, R361, and N13S mutations on its interactions with Smad3, Lmo4, Rassf5, and Smad9. Western blotting with anti-GFP antibody confirming the protein expression levels of wild-type Smad4 and its 3 mutant alleles – Y353S, R361C and N13S. γ-tubulin was used as a loading control.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4263371&req=5

pgen-1004819-g005: Relationships between molecular phenotypes and disease phenotypes.(a) Fraction of mutation pairs on the same gene that cause the same disease: for the same and different effects on protein stability. (b) Fraction of mutation pairs on the same gene that cause the same disease: for the same and different interaction disruption profiles. Error bars indicate +SE. (c) Crystal structure (PDB id: 1U7F) depicting the Y353S and R361C mutations (on Smad4) at interface residues for the Smad4-Smad3 interaction. (d) Y2H analysis of the effects of Smad Y353S, R361, and N13S mutations on its interactions with Smad3, Lmo4, Rassf5, and Smad9. Western blotting with anti-GFP antibody confirming the protein expression levels of wild-type Smad4 and its 3 mutant alleles – Y353S, R361C and N13S. γ-tubulin was used as a loading control.
Mentions: We then analyzed whether the molecular phenotypes measured by our high-throughput GFP and Y2H assays are correlated with corresponding disease phenotypes. We first examined how mutation pairs on the same gene affect protein stability and its relationship to their corresponding diseases. We find that pairs of mutations that are either both stable or both unstable cause the same disease in 68% and 70% of cases, respectively. However, pairs comprising one stable and one unstable mutation cause the same disease in only 30% of cases (P = 6×10−9 and 8×10−10, respectively, Fig. 5a). For example, we find that the mutations R727C and L844F on the spindle checkpoint kinase Bub1b both cause the protein to become unstable and lose all its interactors. These mutations are both associated with the same disease, mosaic variegated aneuploidy, an autosomal recessive disorder that causes predominantly trisomies and monosomies of different chromosomes [22], [23]. Since our GFP assay shows that these two mutations cause loss of protein product, our results are consistent with Matusuura et al.'s finding that a more than 50% decrease in Bub1b activity leads to abnormal mitotic spindle checkpoint function and mosaic variegated aneuploidy [24].

Bottom Line: We describe a massively-parallel site-directed mutagenesis approach, "Clone-seq", leveraging next-generation sequencing to rapidly and cost-effectively generate a large number of mutant alleles.We use this pipeline to show that disease mutations on protein-protein interaction interfaces are significantly more likely than those away from interfaces to disrupt corresponding interactions.The general scheme of our experimental pipeline can be readily expanded to other types of interactome-mapping methods to comprehensively evaluate the functional relevance of all DNA variants, including those in non-coding regions.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicine, Weill Cornell College of Medicine, New York, New York, United States of America; Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, United States of America.

ABSTRACT
Understanding the functional relevance of DNA variants is essential for all exome and genome sequencing projects. However, current mutagenesis cloning protocols require Sanger sequencing, and thus are prohibitively costly and labor-intensive. We describe a massively-parallel site-directed mutagenesis approach, "Clone-seq", leveraging next-generation sequencing to rapidly and cost-effectively generate a large number of mutant alleles. Using Clone-seq, we further develop a comparative interactome-scanning pipeline integrating high-throughput GFP, yeast two-hybrid (Y2H), and mass spectrometry assays to systematically evaluate the functional impact of mutations on protein stability and interactions. We use this pipeline to show that disease mutations on protein-protein interaction interfaces are significantly more likely than those away from interfaces to disrupt corresponding interactions. We also find that mutation pairs with similar molecular phenotypes in terms of both protein stability and interactions are significantly more likely to cause the same disease than those with different molecular phenotypes, validating the in vivo biological relevance of our high-throughput GFP and Y2H assays, and indicating that both assays can be used to determine candidate disease mutations in the future. The general scheme of our experimental pipeline can be readily expanded to other types of interactome-mapping methods to comprehensively evaluate the functional relevance of all DNA variants, including those in non-coding regions.

Show MeSH