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Genetic Disorders
Published in Jeremy R. Jass, Understanding Pathology, 2020
Whereas DNA is made of only four bases, proteins are built of 20 amino acids. The DNA code works through a series of three bases serving as a template for one amino acid. Three such adjacent bases are known as a codon. Mutations frequently involve a single base within a codon. For example, one base may be substituted by an inappropriate base, such as a C instead of a T. This tiny change may then send out the wrong message (a missense mutation). Typically, the altered codon may code for a different amino acid, which may in turn alter the structure and function of the protein. Alternatively, the mutation could order the synthesis of the protein to stop prematurely (by becoming a specific stop signal, or as a nonsense mutation), resulting in the production of a ‘truncated protein’. A nucleotide may be added or deleted resulting in a frameshift mutation (disrupting downstream coding completely and again causing protein truncation). It is also possible that the mutation could have no significant consequences (silent mutation). Given that each chromosome has many millions of bases, an error in only one (called a point mutation) will be extremely difficult to find. It is like being asked to find a single misprinted letter in a dictionary. The technology for detecting such a small error certainly exists, but the task is onerous and there are many pitfalls. Larger mutations, for example the deletion of a long run of bases, may be equally difficult to detect.
Evolution of Histone Genes
Published in S. K. Dutta, DNA Systematics, 2019
The analysis of nucleotide divergence presented above assumes that mutations are random. With respect to silent mutations this implies that there is no selection in favor or against certain codons. This is clearly not the case for any of the species, although different species show different stringencies in their codon preferences. In yeast there is a fairly strict set of codon preferences74 which differ from those of the vertebrates, making the yeast genes AT rich while the vertebrate and sea urchin genes are all GC rich (Table 5). The yeast histone genes show a similar codon selection to other abundant yeast mRNAs.74 This codon usage is very different from that seen in the Neurospora histone genes.27 The codon usage in different sea urchin species is similar for the early and late histone genes in different species (Table 6). Thus, the extensive divergence between these two gene sets in the silent changes is not due to selective pressure of differential codon usage.
Precision medicine in oncology: An overview
Published in Debmalya Barh, Precision Medicine in Cancers and Non-Communicable Diseases, 2018
Fazilet Yılmaz, Sultan Ciftci Yılmaz, Esra Gunduz, Mehmet Gunduz
One nucleotide change in the genome is called single nucleotide variation (SNV). Phenotypical alterations can be observed based on the location of the SNV. Generally, a change occurring in an exon is more dangerous than a change occurring in an intron. In the case of a silent mutation, no change can be observed, but missense, nonsense, or frameshift mutations usually cause dramatic changes in the protein structure. Typically, cancer is coupled with mutation in an oncogene and/or tumor suppressor gene (Klug et al., 2012).
Rare variant association study of veteran twin whole-genomes links severe depression with a nonsynonymous change in the neuronal gene BHLHE22
Published in The World Journal of Biological Psychiatry, 2022
Daniel Hupalo, Christopher W. Forsberg, Jack Goldberg, William S. Kremen, Michael J. Lyons, Anthony R. Soltis, Coralie Viollet, Robert J. Ursano, Murray B. Stein, Carol E. Franz, Yan V. Sun, Viola Vaccarino, Nicholas L. Smith, Clifton L. Dalgard, Matthew D. Wilkerson, Harvey B. Pollard
Samples of DNA were housed at the Department of Veteran Affairs (VA) Massachusetts Veterans Epidemiology Research and Information Centre (MAVERIC) biorepository and were sent to The American Genome Centre at Uniformed Services University. They were then sequenced on an Illumina HiSeq X System using paired-end 151 bp read lengths targeting 400 million total reads. Sequenced reads were processed by the Illumina HiSeq Analysis Software version 2.0 (2.5.55.13). Variants across all samples in the cohort were merged and normalised. Population level autosomal variant sites were then filtered using two conditions: (1) the proportion of samples with non-reference alleles having a PASS filter is at least 90%; and (2) the proportion of samples having a minimum genotype quality (greater or equal to 20) of at least 90%. Variants within the cohort VCF were annotated using ANNOVAR (Wang et al. 2010). Reference population allele frequencies were obtained from TwinsUK, 1000 Genomes Project, GnomAD, and ExAC (1000 Genomes Project Consortium et al. 2015; Moayyeri et al. 2013; Lek et al. 2016). Non-silent mutations were assessed using data from SIFT, Polyphen2, MutationAssessor, PROVEAN, and fathmm (Adzhubei et al. 2010; Choi et al. 2012; Shihab et al. 2013; Vaser et al. 2016). Twin mate identities were verified by calculating identity by state (IBS) via rvtests (Zhan et al. 2016). To compare two samples' genome-wide genotypes including non-reference and reference-matching genotypes, genome variant call format (GVCF) files were merged and analysed for concordance.
Significance of the coexistence of non-codon 315 katG, inhA, and oxyR-ahpC intergenic gene mutations among isoniazid-resistant and multidrug-resistant isolates of Mycobacterium tuberculosis: a report of novel mutations
Published in Pathogens and Global Health, 2022
Fatemeh Norouzi, Sharareh Moghim, ShimaSadat Farzaneh, Hossein Fazeli, Mahshid Salehi, Bahram Nasr Esfahani
Lempens1et al. were reported mostly moderate-level INH resistance (6.4 mg/L) for the common katG Ser315Thr mutation, and very high INH MICs (≥19.2 mg/L) for the coexistence of katG Ser315Thr and inhA c-15 t [34]. The katG Arg463Leu mutation, which was demonstrated to be a polymorphism, was not correlated with the INH resistance [35,36]. However, Purkan et al. reported the contribution of Arg463Leu mutation to INH resistance in an in silico translation analysis [37]. Also, the results of another study confirmed the correlation of Arg463Leu mutation with a high level of INH resistance and confirmed the explanation proposed by Purkan et al. [31]. However, further research is required about the coexistence of mutations at codons 315 and 463 in the katG gene (41.07%) with a low level of INH resistance as katG S315N shows a low level of resistance [31]. It seems that the mechanism of protein folding can be slower due to silent mutations and lead to changes in protein formation. Also, the coexistence of silent mutations with other mutations can increase the effects of mutated proteins [38].
Deep mutagenesis in the study of COVID-19: a technical overview for the proteomics community
Published in Expert Review of Proteomics, 2020
Following FACS selection of the human culture to enrich a cell population with high binding activity for SARS-CoV-2 protein S, RNA transcripts were isolated and Illumina sequenced. An enrichment ratio is calculated for each mutation by dividing its frequency in the sorted cell transcripts by its frequency in the naive plasmid library [51]. Illumina sequencing did not cover the full length of ACE2 and instead the cDNA was sequenced as a series of fragments that together provided full coverage of the diversified regions. One assumes during analysis that there are no additional mutations outside a sequenced fragment, a reasonable assumption when a mutation is found because the library was constructed to have only one amino acid substitution per plasmid. However, the assumption breaks down when no mutations are observed in the sequenced fragment, as one cannot know whether there was a mutation elsewhere outside the sequenced region. As a consequence, the wild type sequence is not directly observed and is instead only estimated. There are strategies using the introduction and analysis of silent mutations that can resolve this issue [52]. Overall, there was close agreement between the mutation enrichment ratios from two independent replicates of the FACS experiments, indicating that the ACE2 library was well sampled and there was high confidence in the data [15].