scholarly journals Mutations of SARS-CoV-2 nsp14 exhibit strong association with increased genome-wide mutation load

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10181 ◽  
Author(s):  
Doğa Eskier ◽  
Aslı Suner ◽  
Yavuz Oktay ◽  
Gökhan Karakülah
Keyword(s):  
Rna Synthesis ◽  
Selective Pressure ◽  
Strong Association ◽  
Disease Spread ◽  
Replication Proteins ◽  
Mutation Load ◽  
Global Impact ◽  
Genome Wide ◽  
Genomic Variance ◽  
Viral Isolates

SARS-CoV-2 is a betacoronavirus responsible for COVID-19, a pandemic with global impact that first emerged in late 2019. Since then, the viral genome has shown considerable variance as the disease spread across the world, in part due to the zoonotic origins of the virus and the human host adaptation process. As a virus with an RNA genome that codes for its own genomic replication proteins, mutations in these proteins can significantly impact the variance rate of the genome, affecting both the survival and infection rate of the virus, and attempts at combating the disease. In this study, we analyzed the mutation densities of viral isolates carrying frequently observed mutations for four proteins in the RNA synthesis complex over time in comparison to wildtype isolates. Our observations suggest mutations in nsp14, an error-correcting exonuclease protein, have the strongest association with increased mutation load without selective pressure and across the genome, compared to nsp7, nsp8 and nsp12, which form the core polymerase complex. We propose nsp14 as a priority research target for understanding genomic variance rate in SARS-CoV-2 isolates and nsp14 mutations as potential predictors for high mutability strains.

scholarly journals Mutations of SARS-CoV-2 nsp14 exhibit strong association with increased genome-wide mutation load

2020 ◽  
Author(s):  
Doğa Eskier ◽  
Aslı Suner ◽  
Yavuz Oktay ◽  
Gökhan Karakülah
Keyword(s):  
Rna Synthesis ◽  
Selective Pressure ◽  
Strong Association ◽  
Disease Spread ◽  
Replication Proteins ◽  
Mutation Load ◽  
Global Impact ◽  
Genome Wide ◽  
Genomic Variance ◽  
Viral Isolates

AbstractSARS-CoV-2 is a betacoronavirus responsible for human cases of COVID-19, a pandemic with global impact that first emerged in late 2019. Since then, the viral genome has shown considerable variance as the disease spread across the world, in part due to the zoonotic origins of the virus and the human host adaptation process. As a virus with an RNA genome that codes for its own genomic replication proteins, mutations in these proteins can significantly impact the variance rate of the genome, affecting both the survival and infection rate of the virus, and attempts at combating the disease. In this study, we analyzed the mutation densities of viral isolates carrying frequently observed mutations for four proteins in the RNA synthesis complex over time in comparison to wildtype isolates. Our observations suggest mutations in nsp14, an error-correcting exonuclease protein, have the strongest association with increased mutation load in both regions without selective pressure and across the genome, compared to nsp7, 8, and 12, which form the core polymerase complex. We propose nsp14 as a priority research target for understanding genomic variance rate in SARS-CoV-2 isolates, and nsp14 mutations as potential predictors for high mutability strains.

scholarly journals Detecting past and ongoing natural selection among ethnically Tibetan women at high altitude in Nepal

2017 ◽  
Author(s):  
Choongwon Jeong ◽  
David B. Witonsky ◽  
Buddha Basnyat ◽  
Maniraj Neupane ◽  
Cynthia M. Beall ◽  
...  
Keyword(s):  
High Altitude ◽  
Negative Selection ◽  
Selective Sweep ◽  
Selective Pressure ◽  
Strong Association ◽  
Selective Sweeps ◽  
Genome Wide ◽  
Polygenic Adaptation ◽  
Selection For ◽  
Offspring Mortality

AbstractAdaptive evolution in humans has rarely been characterized for its whole set of components, i.e. selective pressure, adaptive phenotype, beneficial alleles and realized fitness differential. We combined approaches for detecting selective sweeps and polygenic adaptations and for mapping the genetic bases of physiological and fertility phenotypes in approximately 1000 indigenous ethnically Tibetan women from Nepal, adapted to high altitude. We performed genome-wide association analysis and tests for polygenic adaptations which showed evidence of positive selection for alleles associated with more pregnancies and live births and evidence of negative selection for those associated with higher offspring mortality. Lower hemoglobin level did not show clear evidence for polygenic adaptation, despite its strong association with an EPAS1 haplotype carrying selective sweep signals.

scholarly journals Analysis of computational codon usage models and their association with translationally slow codons

2020 ◽  
Author(s):  
Gabriel Wright ◽  
Anabel Rodriguez ◽  
Jun Li ◽  
Patricia L. Clark ◽  
Tijana Milenković ◽  
...  
Keyword(s):  
Codon Usage ◽  
Computational Models ◽  
Selective Pressure ◽  
Synonymous Codon ◽  
Ground Truth ◽  
Protein Translation ◽  
Weak Correlation ◽  
Experimental Conditions ◽  
Synonymous Codons ◽  
Genome Wide

AbstractImproved computational modeling of protein translation rates, including better prediction of where translational slowdowns along an mRNA sequence may occur, is critical for understanding co-translational folding. Because codons within a synonymous codon group are translated at different rates, many computational translation models rely on analyzing synonymous codons. Some models rely on genome-wide codon usage bias (CUB), believing that globally rare and common codons are the most informative of slow and fast translation, respectively. Others use the CUB observed only in highly expressed genes, which should be under selective pressure to be translated efficiently (and whose CUB may therefore be more indicative of translation rates). No prior work has analyzed these models for their ability to predict translational slowdowns. Here, we evaluate five models for their association with slowly translated positions as denoted by two independent ribosome footprint (RFP) count experiments from S. cerevisiae, because RFP data is often considered as a “ground truth” for translation rates across mRNA sequences. We show that all five considered models strongly associate with the RFP data and therefore have potential for estimating translational slowdowns. However, we also show that there is a weak correlation between RFP counts for the same genes originating from independent experiments, even when their experimental conditions are similar. This raises concerns about the efficacy of using current RFP experimental data for estimating translation rates and highlights a potential advantage of using computational models to understand translation rates instead.

Strong association between the 12q24 locus and sweet taste preference in the Japanese population revealed by genome-wide meta-analysis

2020 ◽  
Vol 65 (11) ◽  
pp. 939-947 ◽  
Author(s):  
Kaoru Kawafune ◽  
Tsuyoshi Hachiya ◽  
Shun Nogawa ◽  
Shoko Takahashi ◽  
Huijuan Jia ◽  
...  
Keyword(s):  
Japanese Population ◽  
Meta Analysis ◽  
Strong Association ◽  
Taste Preference ◽  
Sweet Taste ◽  
Genome Wide

Genome-Wide Association Study of Inattention and Hyperactivity–Impulsivity Measured as Quantitative Traits

2013 ◽  
Vol 16 (2) ◽  
pp. 560-574 ◽  
Author(s):  
Jane L. Ebejer ◽  
David L. Duffy ◽  
Julius van der Werf ◽  
Margaret J. Wright ◽  
Grant Montgomery ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Association Studies ◽  
Full Range ◽  
Strong Association ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Community Based ◽  
Normal Behaviour ◽  
Genome Wide ◽  
Inattention And Hyperactivity

Genome-wide association studies (GWAS) of attention-deficit/hyperactivity disorder (ADHD) offer the benefit of a hypothesis-free approach to measuring the quantitative effect of genetic variants on affection status. Generally the findings of GWAS relying on ADHD status have been non-significant, but the one study using quantitative measures of symptoms found SLC9A9 and SLC6A1 were associated with inattention and hyperactivity–impulsivity. Accordingly, we performed a GWAS using quantitative measures of each ADHD subtype measured with the Strengths and Weaknesses of ADHD and Normal Behaviour (SWAN) scale in two community-based samples. This scale captures the full range of attention and kinetic behavior; from high levels of attention and appropriate activity to the inattention and hyperactivity–impulsivity associated with ADHD within two community-based samples. Our discovery sample comprised 1,851 participants (mean age = 22.8 years [4.8]; 50.6% female), while our replication sample comprised 155 participants (mean age = 26.3 years [3.1]; 68.4% females). Age, sex, age × sex, and age2 were included as covariates and the results from each sample were combined using meta-analysis, then analyzed with a gene-based test to estimate the combined effect of markers within genes. We compare our results with markers that have previously been found to have a strong association with ADHD symptoms. Neither the GWAS nor subsequent meta-analyses yielded genome-wide significant results; the strongest effect was observed at rs2110267 (4.62 × 10−7) for symptoms of hyperactivity–impulsivity. The strongest effect in the gene-based test was for GPR139 on symptoms of inattention (6.40 × 10−5). Replication of this study with larger samples will add to our understanding of the genetic etiology of ADHD.

scholarly journals A gene-based recessive diplotype exome scan discovers FGF6, a novel hepcidin-regulating iron-metabolism gene

Blood ◽  
2019 ◽  
Vol 133 (17) ◽  
pp. 1888-1898 ◽  
Author(s):  
Shicheng Guo ◽  
Shuai Jiang ◽  
Narendranath Epperla ◽  
Yanyun Ma ◽  
Mehdi Maadooliat ◽  
...  
Keyword(s):  
Growth Factor ◽  
Fibroblast Growth Factor ◽  
Iron Metabolism ◽  
Iron Homeostasis ◽  
Genome Wide Association Study ◽  
Strong Association ◽  
Genome Wide Association ◽  
Fibroblast Growth ◽  
Genome Wide ◽  
Association Data

Abstract Standard analyses applied to genome-wide association data are well designed to detect additive effects of moderate strength. However, the power for standard genome-wide association study (GWAS) analyses to identify effects from recessive diplotypes is not typically high. We proposed and conducted a gene-based compound heterozygosity test to reveal additional genes underlying complex diseases. With this approach applied to iron overload, a strong association signal was identified between the fibroblast growth factor–encoding gene, FGF6, and hemochromatosis in the central Wisconsin population. Functional validation showed that fibroblast growth factor 6 protein (FGF-6) regulates iron homeostasis and induces transcriptional regulation of hepcidin. Moreover, specific identified FGF6 variants differentially impact iron metabolism. In addition, FGF6 downregulation correlated with iron-metabolism dysfunction in systemic sclerosis and cancer cells. Using the recessive diplotype approach revealed a novel susceptibility hemochromatosis gene and has extended our understanding of the mechanisms involved in iron metabolism.

Sign in / Sign up

Export Citation Format

Share Document