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Article: Contributions of adaptation and purifying selection to SARS-CoV-2 evolution.

Neher, Richard A

2022 Volume 8, Issue 2, Page(s) veac113

Abstract: Continued evolution and adaptation of SARS-CoV-2 has led to more transmissible and immune-evasive variants with profound impacts on the course of the pandemic. Here I analyze the evolution of the virus over 2.5 years since its emergence and estimate the ... ...

Abstract	Continued evolution and adaptation of SARS-CoV-2 has led to more transmissible and immune-evasive variants with profound impacts on the course of the pandemic. Here I analyze the evolution of the virus over 2.5 years since its emergence and estimate the rates of evolution for synonymous and non-synonymous changes separately for evolution within clades-well-defined monophyletic groups with gradual evolution-and for the pandemic overall. The rate of synonymous mutation is found to be around 6 changes per year. Synonymous rates within variants vary little from variant to variant and are compatible with the overall rate of 7 changes per year (or [Formula: see text] per year and codon). In contrast, the rate at which variants accumulate amino acid changes (non-synonymous mutations) was initially around 12-16 changes per year, but in 2021 and 2022 it dropped to 6-9 changes per year. The overall rate of non-synonymous evolution, that is across variants, is estimated to be about 26 amino acid changes per year (or [Formula: see text] per year and codon). This strong acceleration of the overall rate compared to within clade evolution indicates that the evolutionary process that gave rise to the different variants is qualitatively different from that in typical transmission chains and likely dominated by adaptive evolution. I further quantify the spectrum of mutations and purifying selection in different SARS-CoV-2 proteins and show that the massive global sampling of SARS-CoV-2 is sufficient to estimate site-specific fitness costs across the entire genome. Many accessory proteins evolve under limited evolutionary constraints with little short-term purifying selection. About half of the mutations in other proteins are strongly deleterious.
Language	English
Publishing date	2022-12-10
Publishing country	England
Document type	Journal Article
ZDB-ID	2818949-8
ISSN	2057-1577
ISSN	2057-1577
DOI	10.1093/ve/veac113
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Article: Radiomic tractometry: a rich and tract-specific class of imaging biomarkers for neuroscience and medical applications.

Neher, Peter / Hirjak, Dusan / Maier-Hein, Klaus

Research square

2023

Abstract: Tract-specific microstructural analysis of the brain white matter using diffusion MRI is a driver for neuroscientific discovery with a wide range of applications. Current analysis pipelines have conceptual limitations that narrow their applicability and ... ...

Abstract	Tract-specific microstructural analysis of the brain white matter using diffusion MRI is a driver for neuroscientific discovery with a wide range of applications. Current analysis pipelines have conceptual limitations that narrow their applicability and hamper subject-level analysis and predictions. Radiomic tractometry (RadTract) improves upon that, enabling the extraction and analysis of comprehensive and highly informative microstructural feature sets where previous approaches were restricted to bare summary statistics. We demonstrate the added value in a series of neuroscientific applications, including diagnostic tasks as well as the prediction of demographic and clinical measures across various datasets. Being published as an open and easy-to-use Python package, RadTract could spark the establishment of a new generation of tract-specific imaging biomarkers, with direct benefits for a range of applications from basic neuroscience to medical research.
Language	English
Publishing date	2023-05-23
Publishing country	United States
Document type	Preprint
DOI	10.21203/rs.3.rs-2950610/v1
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Article ; Online: Visualizing and quantifying structural diversity around mobile resistance genes.

Shaw, Liam P / Neher, Richard A

Microbial genomics

2023 Volume 9, Issue 12

Abstract: Understanding the evolution of mobile genes is important for understanding the spread of antimicrobial resistance (AMR). Many clinically important AMR genes have been mobilized by mobile genetic elements (MGEs) on the kilobase scale, such as integrons ... ...

Abstract	Understanding the evolution of mobile genes is important for understanding the spread of antimicrobial resistance (AMR). Many clinically important AMR genes have been mobilized by mobile genetic elements (MGEs) on the kilobase scale, such as integrons and transposons, which can integrate into both chromosomes and plasmids and lead to rapid spread of the gene through bacterial populations. Looking at the flanking regions of these mobile genes in diverse genomes can highlight common structures and reveal patterns of MGE spread. However, historically this has been a largely descriptive process, relying on gene annotation and expert knowledge. Here we describe a general method to visualize and quantify the structural diversity around genes using pangraph to find blocks of homologous sequence. We apply this method to a set of 12 clinically important beta-lactamase genes and provide interactive visualizations of their flanking regions at https://liampshaw.github.io/flanking-regions. We show that nucleotide-level variation in the mobile gene itself generally correlates with increased structural diversity in its flanking regions, demonstrating a relationship between rates of mutational evolution and rates of structural evolution, and find a bias for greater structural diversity upstream. Our framework is a starting point to investigate general rules that apply to the horizontal spread of new genes through bacterial populations.
MeSH term(s)	Plasmids/genetics ; Bacteria/genetics ; beta-Lactamases/genetics ; Integrons
Chemical Substances	beta-Lactamases (EC 3.5.2.6)
Language	English
Publishing date	2023-12-19
Publishing country	England
Document type	Journal Article
ZDB-ID	2835258-0
ISSN	2057-5858 ; 2057-5858
ISSN (online)	2057-5858
ISSN	2057-5858
DOI	10.1099/mgen.0.001168
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Article: Fitness effects of mutations to SARS-CoV-2 proteins.

Bloom, Jesse D / Neher, Richard A

bioRxiv : the preprint server for biology

2023

Abstract: Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is ...

Abstract	Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino-acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness/). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.
Language	English
Publishing date	2023-06-06
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.01.30.526314
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Article: Fitness effects of mutations to SARS-CoV-2 proteins.

Bloom, Jesse D / Neher, Richard A

Virus evolution

2023 Volume 9, Issue 2, Page(s) vead055

Abstract	Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here, we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness/). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.
Language	English
Publishing date	2023-09-18
Publishing country	England
Document type	Journal Article
ZDB-ID	2818949-8
ISSN	2057-1577
ISSN	2057-1577
DOI	10.1093/ve/vead055
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Article ; Online: Contributions of adaptation and purifying selection to SARS-CoV-2 evolution

Neher, Richard A

bioRxiv

Abstract: Continued evolution and adaptation of SARS-CoV-2 has lead to more transmissible and immune-evasive variants with profound impact on the course of the pandemic. Here I analyze the evolution of the virus over 2.5 years since its emergence and estimate ... ...

Abstract	Continued evolution and adaptation of SARS-CoV-2 has lead to more transmissible and immune-evasive variants with profound impact on the course of the pandemic. Here I analyze the evolution of the virus over 2.5 years since its emergence and estimate rates of evolution for synonymous and non-synonymous changes separately for evolution within clades -- well defined mono-phyletic groups with gradual evolution -- and for the pandemic overall. The rate of synonymous mutations is found to be around 6 changes per year. Synonymous rates within variants vary little from variant to variant and are compatible with the overall rate. In contrast, the rate at which variants accumulate amino acid changes (non-synonymous mutation) was initially around 12-16 changes per year, but in 2021 and 2022 dropped to 6-9 changes per year. The overall rate of non-synonymous evolution, that is across variants, is estimated to be about 25 amino acid changes per year. This 2-fold higher rate indicates that the evolutionary process that gave rise to the different variants is qualitatively different from that in typical transmission chains and likely dominated by adaptive evolution. I further quantify the spectrum of mutations and purifying selection in different SARS-CoV-2 proteins. Many accessory proteins evolve under limited evolutionary constraint with little short term purifying selection. About half of the mutations in other proteins are strongly deleterious and rarely observed, not even at low frequency.
Keywords	covid19
Language	English
Publishing date	2022-08-22
Publisher	Cold Spring Harbor Laboratory
Document type	Article ; Online
DOI	10.1101/2022.08.22.504731
Database	COVID19

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Article ; Online: Fitness effects of mutations to SARS-CoV-2 proteins

Bloom, Jesse D / Neher, Richard A

bioRxiv

Abstract	Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino-acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.
Keywords	covid19
Language	English
Publishing date	2023-01-31
Publisher	Cold Spring Harbor Laboratory
Document type	Article ; Online
DOI	10.1101/2023.01.30.526314
Database	COVID19

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Article ; Online: PanGraph

Noll, Nicholas / Molari, Marco / Shaw, Liam P / Neher, Richard A

Microbial genomics

2023 Volume 9, Issue 6

Abstract: The genomic diversity of microbes is commonly parameterized as SNPs relative to a reference genome of a well-characterized, but arbitrary, isolate. However, any reference genome contains only a fraction of the ... ...

Abstract	The genomic diversity of microbes is commonly parameterized as SNPs relative to a reference genome of a well-characterized, but arbitrary, isolate. However, any reference genome contains only a fraction of the microbial
MeSH term(s)	Genomics ; Genome, Bacterial
Language	English
Publishing date	2023-06-06
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2835258-0
ISSN	2057-5858 ; 2057-5858
ISSN (online)	2057-5858
ISSN	2057-5858
DOI	10.1099/mgen.0.001034
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Article ; Online: Evolution of the SARS-CoV-2 Mutational Spectrum.

Bloom, Jesse D / Beichman, Annabel C / Neher, Richard A / Harris, Kelley

Molecular biology and evolution

2023 Volume 40, Issue 4

Abstract: SARS-CoV-2 evolves rapidly in part because of its high mutation rate. Here, we examine whether this mutational process itself has changed during viral evolution. To do this, we quantify the relative rates of different types of single-nucleotide mutations ...

Abstract	SARS-CoV-2 evolves rapidly in part because of its high mutation rate. Here, we examine whether this mutational process itself has changed during viral evolution. To do this, we quantify the relative rates of different types of single-nucleotide mutations at 4-fold degenerate sites in the viral genome across millions of human SARS-CoV-2 sequences. We find clear shifts in the relative rates of several types of mutations during SARS-CoV-2 evolution. The most striking trend is a roughly 2-fold decrease in the relative rate of G→T mutations in Omicron versus early clades, as was recently noted by Ruis et al. (2022. Mutational spectra distinguish SARS-CoV-2 replication niches. bioRxiv, doi:10.1101/2022.09.27.509649). There is also a decrease in the relative rate of C→T mutations in Delta, and other subtle changes in the mutation spectrum along the phylogeny. We speculate that these changes in the mutation spectrum could arise from viral mutations that affect genome replication, packaging, and antagonization of host innate-immune factors, although environmental factors could also play a role. Interestingly, the mutation spectrum of Omicron is more similar than that of earlier SARS-CoV-2 clades to the spectrum that shaped the long-term evolution of sarbecoviruses. Overall, our work shows that the mutation process is itself a dynamic variable during SARS-CoV-2 evolution and suggests that human SARS-CoV-2 may be trending toward a mutation spectrum more similar to that of other animal sarbecoviruses.
MeSH term(s)	Animals ; Humans ; SARS-CoV-2 ; COVID-19 ; Mutation ; Mutation Rate ; Severe acute respiratory syndrome-related coronavirus ; Genome, Viral
Language	English
Publishing date	2023-04-11
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	998579-7
ISSN	1537-1719 ; 0737-4038
ISSN (online)	1537-1719
ISSN	0737-4038
DOI	10.1093/molbev/msad085
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Article ; Online: TreeKnit: Inferring ancestral reassortment graphs of influenza viruses.

Barrat-Charlaix, Pierre / Vaughan, Timothy G / Neher, Richard A

PLoS computational biology

2022 Volume 18, Issue 8, Page(s) e1010394

Abstract: When two influenza viruses co-infect the same cell, they can exchange genome segments in a process known as reassortment. Reassortment is an important source of genetic diversity and is known to have been involved in the emergence of most pandemic ... ...

Abstract	When two influenza viruses co-infect the same cell, they can exchange genome segments in a process known as reassortment. Reassortment is an important source of genetic diversity and is known to have been involved in the emergence of most pandemic influenza strains. However, because of the difficulty in identifying reassortment events from viral sequence data, little is known about their role in the evolution of the seasonal influenza viruses. Here we introduce TreeKnit, a method that infers ancestral reassortment graphs (ARG) from two segment trees. It is based on topological differences between trees, and proceeds in a greedy fashion by finding regions that are compatible in the two trees. Using simulated genealogies with reassortments, we show that TreeKnit performs well in a wide range of settings and that it is as accurate as a more principled bayesian method, while being orders of magnitude faster. Finally, we show that it is possible to use the inferred ARG to better resolve segment trees and to construct more informative visualizations of reassortments.
MeSH term(s)	Bayes Theorem ; Genome, Viral/genetics ; Humans ; Influenza, Human ; Orthomyxoviridae/genetics ; Phylogeny ; Reassortant Viruses/genetics
Language	English
Publishing date	2022-08-19
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1010394
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