Molecular Biology & EvolutionPopova et al. studied the evolution of M. tuberculosum under drug pressure using a unified phylogeny-based approach to reveal both drug-dependent evolution and epistatic interactions between sites.
Jason H. Moore, Ph.D.Epistatic hotspots organize antibody fitness landscape and boost evolvability https://pubmed.ncbi.nlm.nih.gov/39773024/ #epistasis
Epistatic hotspots organize antibody fitness landscape and boost evolvability - PubMed
The course of evolution is strongly shaped by interaction between mutations. Such epistasis can yield rugged sequence-function maps and constrain the availability of adaptive paths. While theoretical intuition is often built on global statistics of large, homogeneous model landscapes, mutagenesis me …
Giuseppe MichieliStructural and molecular #basis of the #epistasis effect in enhanced affinity between #SARS-CoV-2 #KP3 and #ACE2 http://biorxiv.org/cgi/content/short/2024.09.03.610799v1?rss=1
KP.3, featuring F456L and Q493E, exhibits a markedly enhanced ACE2 binding affinity compared to #KP2 and #JN1 #variant due to synergistic effects between these mutations.
A combinatorially complete epistatic fitness landscape in an enzyme active site https://www.pnas.org/doi/10.1073/pnas.2400439121 #epistasis
Our TBT 2005 paper on "Traversing the conceptual divide between biological & statistical epistasis: systems biology & a more modern synthesis" https://onlinelibrary.wiley.com/doi/10.1002/bies.20236 #epistasis #genetics #complexity #TBT
#Epistasis mediates the evolution of #receptor binding mode in recent #human #H3N2 #hemagglutinin, Nat Commun.: https://www.nature.com/articles/s41467-024-49487-4
Combinatorial #mutagenesis reveals that G186D and D190N, along with other natural mutations in recent H3N2 strains, alter compatibility with a common egg-adaptive mutation in seasonal influenza vaccines. Our findings elucidate role of epistasis in shaping recent evolution of human hemagglutinin & substantiate high evolvability of its receptor-binding mode.
Epistasis mediates the evolution of the receptor binding mode in recent human H3N2 hemagglutinin - Nature Communications
The receptor binding mode of recent human H3N2 hemagglutinin has evolved due to mutations G186D and D190N, which epistatically interact and co-emerged in clades 3C.2a1b.1a and 3C.2a1b.2a2.
BridGE: a pathway-based analysis tool for detecting genetic interactions from GWAS https://www.nature.com/articles/s41596-024-00954-8 #epistasis #genetics #gwas #bioinformatics
BridGE: a pathway-based analysis tool for detecting genetic interactions from GWAS - Nature Protocols
Genetic interactions have been found to influence phenotypes in a variety of systems, yet their specific contribution to complex diseases remains unclear. This protocol describes Bridging Gene sets with Epistasis (BridGE), a computational approach for discovering interactions between biological pathways from genome-wide association studies data.
Next-Gen GWAS: full 2D epistatic interaction maps retrieve part of missing heritability and improve phenotypic prediction https://genomebiology.biomedcentral.com/articles/10.1186/s13059-024-03202-0 #gwas #epistasis #genetics #bioinformatics
Next-Gen GWAS: full 2D epistatic interaction maps retrieve part of missing heritability and improve phenotypic prediction - Genome Biology
The problem of missing heritability requires the consideration of genetic interactions among different loci, called epistasis. Current GWAS statistical models require years to assess the entire combinatorial epistatic space for a single phenotype. We propose Next-Gen GWAS (NGG) that evaluates over 60 billion single nucleotide polymorphism combinatorial first-order interactions within hours. We apply NGG to Arabidopsis thaliana providing two-dimensional epistatic maps at gene resolution. We demonstrate on several phenotypes that a large proportion of the missing heritability can be retrieved, that it indeed lies in epistatic interactions, and that it can be used to improve phenotype prediction.
CellBioNewsA new #mathematical language for #biological #networks.
#gene_expression #regulators #microbiome #epistasis
https://phys.org/news/2023-12-mathematical-language-biological-networks.html
A new mathematical language for biological networks
A team of researchers around Berlin mathematics professor Michael Joswig is presenting a novel concept for the mathematical modeling of genetic interactions in biological systems. Collaborating with biologists from ETH Zurich and Carnegy Science (U.S.), the team has successfully identified master regulators within the context of an entire genetic network.
Factorizing polygenic epistasis improves prediction and uncovers biological pathways in complex traits - AJHG https://linkinghub.elsevier.com/retrieve/pii/S0002-9297(23)00355-5 #epistasis #gwas