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Presse Medicale (Paris, France : 1983) Jun 2017Developmental genetics of congenital heart diseases has evolved from analysis of serial slices in embryos towards molecular genetics of cardiac morphogenesis with a... (Review)
Review
Developmental genetics of congenital heart diseases has evolved from analysis of serial slices in embryos towards molecular genetics of cardiac morphogenesis with a dynamic view of cardiac development. Genetics of congenital heart diseases has also changed from formal genetic analysis of familial recurrences or population-based analysis to screening for mutations in candidates genes identified in animal models. Close cooperation between molecular embryologists, pathologists involved in heart development and pediatric cardiologists is crucial for further increase of knowledge in the field of cardiac morphogenesis and genetics of cardiac defects. The genetic model for congenital heart disease has to be revised to favor a polygenic origin rather than a monogenic one. The main mechanism is altered genic dosage that can account for heart diseases in chromosomal anomalies as well as in point mutations in syndromic and isolated congenital heart diseases. The use of big data grouping information from cardiac development, interactions between genes and proteins, epigenetic factors such as chromatin remodeling or DNA methylation is the current source for improving our knowledge in the field and to give clues for future therapies.
Topics: Animals; Chromosome Disorders; DNA Mutational Analysis; Disease Models, Animal; Epigenesis, Genetic; Genetic Association Studies; Heart; Heart Defects, Congenital; Humans; Molecular Biology; Multifactorial Inheritance; Point Mutation
PubMed: 28583745
DOI: 10.1016/j.lpm.2017.05.014 -
Methods in Molecular Biology (Clifton,... 2024Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 system has been developed as a robust genome engineering tool in a variety of organisms...
Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 system has been developed as a robust genome engineering tool in a variety of organisms attributed to its high efficiency and versatility. In this chapter, we described the detailed procedures of CRISPR-Cas9-based genetic manipulation in Pseudomonas aeruginosa, including precise gene deletion and insertion via Cas9-mediated DNA double-strand break and homologous recombination repair. In addition, we provided a detailed protocol for cytidine base editor, a highly efficient gene inactivation and point mutation tool in Pseudomonas aeruginosa.
Topics: Gene Editing; CRISPR-Cas Systems; Pseudomonas aeruginosa; Point Mutation; Recombinational DNA Repair
PubMed: 37819511
DOI: 10.1007/978-1-0716-3473-8_1 -
Frontiers in Cellular and Infection... 2022Mutations may produce highly transmissible and damaging HIV variants, which increase the genetic diversity, and pose a challenge to develop vaccines. Therefore, it is of...
Mutations may produce highly transmissible and damaging HIV variants, which increase the genetic diversity, and pose a challenge to develop vaccines. Therefore, it is of great significance to understand how mutations drive the virulence of HIV. Based on the 11897 reliable genomes of HIV-1 retrieved from HIV sequence Database, we analyze the 12 types of point mutation (A>C, A>G, A>T, C>A, C>G, C>T, G>A, G>C, G>T, T>A, T>C, T>G) from multiple statistical perspectives for the first time. The global/geographical location/subtype/k-mer analysis results report that A>G, G>A, C>T and T>C account for nearly 64% among all SNPs, which suggest that APOBEC-editing and ADAR-editing may play an important role in HIV-1 infectivity. Time analysis shows that most genomes with abnormal mutation numbers comes from African countries. Finally, we use natural vector method to check the k-mer distribution changing patterns in the genome, and find that there is an important substitution pattern between nucleotides A and G, and 2-mer CG may have a significant impact on viral infectivity. This paper provides an insight into the single mutation of HIV-1 by using the latest data in the HIV sequence Database.
Topics: HIV-1; Point Mutation; Mutation; Mutation, Missense; Databases, Nucleic Acid
PubMed: 36457853
DOI: 10.3389/fcimb.2022.1033481 -
Protein Science : a Publication of the... Jan 2021Predicting the effect of missense variations on protein stability and dynamics is important for understanding their role in diseases, and the link between protein...
Predicting the effect of missense variations on protein stability and dynamics is important for understanding their role in diseases, and the link between protein structure and function. Approaches to estimate these changes have been proposed, but most only consider single-point missense variants and a static state of the protein, with those that incorporate dynamics are computationally expensive. Here we present DynaMut2, a web server that combines Normal Mode Analysis (NMA) methods to capture protein motion and our graph-based signatures to represent the wildtype environment to investigate the effects of single and multiple point mutations on protein stability and dynamics. DynaMut2 was able to accurately predict the effects of missense mutations on protein stability, achieving Pearson's correlation of up to 0.72 (RMSE: 1.02 kcal/mol) on a single point and 0.64 (RMSE: 1.80 kcal/mol) on multiple-point missense mutations across 10-fold cross-validation and independent blind tests. For single-point mutations, DynaMut2 achieved comparable performance with other methods when predicting variations in Gibbs Free Energy (ΔΔG) and in melting temperature (ΔT ). We anticipate our tool to be a valuable suite for the study of protein flexibility analysis and the study of the role of variants in disease. DynaMut2 is freely available as a web server and API at http://biosig.unimelb.edu.au/dynamut2.
Topics: Internet; Mutation, Missense; Point Mutation; Protein Stability; Proteins; Software
PubMed: 32881105
DOI: 10.1002/pro.3942 -
Stem Cell Research May 2021When studying patient specific induced pluripotent stem cells (iPS cells) as a disease model, the ideal control is an isogenic line that has corrected the point...
When studying patient specific induced pluripotent stem cells (iPS cells) as a disease model, the ideal control is an isogenic line that has corrected the point mutation, instead of iPS cells from siblings or other healthy subjects. However, repairing a point mutation in iPS cells even with the newly developed CRISPR-Cas9 technique remains difficult and time-consuming. Here we report a strategy that makes the Cas9 "knock-in" methodology both hassle-free and error-free. Instead of selecting a Cas9 recognition site close to the point mutation, we chose a site located in the nearest intron. We constructed a donor template with the fragment containing the corrected point mutation as one of the homologous recombination arms flanking a PGK-Puro cassette. After selection with puromycin, positive clones were identified and further transfected with a CRE vector to remove the PGK-Puro cassette. Using this methodology, we successfully repaired the point mutation G2019S of the LRRK2 gene in a Parkinson Disease (PD) patient iPS line and the point mutation R329H of the AARS1 gene in a Charcot-Marie-Tooth disease (CMT) patient iPS line. These isogenic iPS lines are ideal as a control in future studies.
Topics: CRISPR-Cas Systems; Clone Cells; Clustered Regularly Interspaced Short Palindromic Repeats; Homologous Recombination; Humans; Induced Pluripotent Stem Cells; Mutation; Point Mutation
PubMed: 33857832
DOI: 10.1016/j.scr.2021.102332 -
PLoS Computational Biology Feb 2019Mutation signatures in cancer genomes reflect endogenous and exogenous mutational processes, offering insights into tumour etiology, features for prognostic and biologic...
Mutation signatures in cancer genomes reflect endogenous and exogenous mutational processes, offering insights into tumour etiology, features for prognostic and biologic stratification and vulnerabilities to be exploited therapeutically. We present a novel machine learning formalism for improved signature inference, based on multi-modal correlated topic models (MMCTM) which can at once infer signatures from both single nucleotide and structural variation counts derived from cancer genome sequencing data. We exemplify the utility of our approach on two hormone driven, DNA repair deficient cancers: breast and ovary (n = 755 samples total). We show how introducing correlated structure both within and between modes of mutation can increase accuracy of signature discovery, particularly in the context of sparse data. Our study emphasizes the importance of integrating multiple mutation modes for signature discovery and patient stratification, and provides a statistical modeling framework to incorporate additional features of interest for future studies.
Topics: Computational Biology; Genetic Variation; Genome; Humans; Machine Learning; Models, Statistical; Mutation; Neoplasms; Point Mutation; Prognosis; Sequence Analysis, DNA; Transcriptome
PubMed: 30794536
DOI: 10.1371/journal.pcbi.1006799 -
Journal of Comparative Pathology Nov 2018Mutation of the isocitrate dehydrogenase 1 (IDH1) gene at codon 132 has been identified in approximately 70% of low-grade (II and III) human gliomas and secondary...
Mutation of the isocitrate dehydrogenase 1 (IDH1) gene at codon 132 has been identified in approximately 70% of low-grade (II and III) human gliomas and secondary glioblastomas, with the IDH1 R132H point mutation representing 92.7% of these mutations. In people, the presence of an IDH1 gene mutation is associated with a better prognosis (both progression-free survival time and overall survival time) and a better response to therapy, including chemotherapy and radiation therapy. Furthermore, IDH1 mutations are included in diagnostic panels to improve diagnosis and molecular classification. Canine gliomas resemble their human counterpart both morphologically and immunohistochemically, therefore they are likely to share similar genetic abnormalities. The IDH1 gene is also comparable between man and dogs. If the IDH1 R132H point mutation is demonstrated in canine gliomas, the prognostic significance of this mutation in people may be transferable to the dog. The objective of this study was to investigate canine gliomas for the IDH1 R132H point mutation using immunohistochemistry. Thirty-one formalin-fixed and paraffin wax-embedded canine gliomas were examined for both IDH1 R132H expression and pan-IDH1 (IDH1 wild-type and point mutated IDH1). Glial tumour specimens were recorded to be either positive or negative for expression. Pan-IDH1 expression was identified in all 31 tumours (100%), while the IDH1 R132H point mutation was identified in none of the tumours (0%). Therefore, the IDH1 R132H point mutation was not identified in this population of canine gliomas and may not be a suitable biomarker or treatment target in canine gliomas. Further investigation is required to determine if other point mutations occur in the IDH1 gene of canine gliomas.
Topics: Animals; Brain Neoplasms; Dog Diseases; Dogs; Glioma; Isocitrate Dehydrogenase; Point Mutation
PubMed: 30502793
DOI: 10.1016/j.jcpa.2018.09.005 -
Nature Biomedical Engineering Jan 2020
Topics: Adenine; Animals; Mice; Point Mutation; Tyrosinemias
PubMed: 31937937
DOI: 10.1038/s41551-019-0489-x -
Gastrointestinal Endoscopy Mar 2021
Topics: Adenocarcinoma; Biomarkers; High-Throughput Nucleotide Sequencing; Humans; Pancreatic Neoplasms; Point Mutation
PubMed: 33583519
DOI: 10.1016/j.gie.2020.07.024 -
Scientific Reports Jun 2023Protein-protein interactions (PPIs) play a critical role in all biological processes. Menin is tumor suppressor protein, mutated in multiple endocrine neoplasia type 1...
Protein-protein interactions (PPIs) play a critical role in all biological processes. Menin is tumor suppressor protein, mutated in multiple endocrine neoplasia type 1 syndrome and has been shown to interact with multiple transcription factors including (RPA2) subunit of replication protein A (RPA). RPA2, heterotrimeric protein required for DNA repair, recombination and replication. However, it's still remains unclear the specific amino acid residues that have been involved in Menin-RPA2 interaction. Thus, accurately predicting the specific amino acid involved in interaction and effects of MEN1 mutations on biological systems is of great interests. The experimental approaches for identifying amino acids in menin-RPA2 interactions are expensive, time-consuming, and challenging. This study leverages computational tools, free energy decomposition and configurational entropy scheme to annotate the menin-RPA2 interaction and effect on menin point mutation, thereby proposing a viable model of menin-RPA2 interaction. The menin-RPA2 interaction pattern was calculated on the basis of different 3D structures of menin and RPA2 complexes, constructed using homology modeling and docking strategy, generating three best-fit models: Model 8 (- 74.89 kJ/mol), Model 28 (- 92.04 kJ/mol) and Model 9 (- 100.4 kJ/mol). The molecular dynamic (MD) was performed for 200 ns and binding free energies and energy decomposition analysis were calculated using Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) in GROMACS. From binding free energy change, model 8 of Menin-RPA2 exhibited most negative binding energy of - 205.624 kJ/mol, followed by model 28 of Menin-RPA2 with - 177.382 kJ/mol. After S606F point mutation in Menin, increase of BFE (ΔG) by - 34.09 kJ/mol in Model 8 of mutant Menin-RPA2 occurs. Interestingly, we found a significant reduction of BFE (ΔG) and configurational entropy by - 97.54 kJ/mol and - 2618 kJ/mol in mutant model 28 as compared the o wild type. Collectively, this is the first study to highlight the configurational entropy of protein-protein interactions thereby strengthening the prediction of two significant important interaction sites in menin for the binding of RPA2. These predicted sites could be vulnerable for structural alternation in terms of binding free energy and configurational entropy after missense mutation in menin.
Topics: Humans; Point Mutation; Mutation; Transcription Factors; Binding Sites; Multiple Endocrine Neoplasia Type 1; Amino Acids; Replication Protein A
PubMed: 37291166
DOI: 10.1038/s41598-023-35599-2