Results 51 to 60 of about 134,396 (261)
Genotype by Environment Interaction and Yield Stability of Drought Tolerant Mung Bean [Vigna radiata (L.) Wilczek] Genotypes in Ethiopia [PDF]
A multi-environment evaluation of mung bean genotypes was conducted in six environments across Ethiopia to select promising genotypes. This study was conducted to estimate the magnitude of genotypes by environment interaction (GEI) and seed yield ...
Mekbib, Firew +3 more
core
Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova +14 more
wiley +1 more source
Despite QTL mapping being a routine procedure in plant breeding, approaches that fully exploit data from multi-trait multi-environment (MTME) trials are limited.
Crossa, J. +4 more
core +1 more source
Proportion of the variations in heartwood color traits explained by genotype, environment, and the interaction between genotype and environment (i.e., plasticity).
Yoshihiko Tsumura (408539) +13 more
core +1 more source
Beyond its role in immune evasion, this study identified that CD47 drives tumor‐intrinsic signaling in non‐small cell lung cancer (NSCLC). Transcriptomic profiling and functional studies revealed that CD47 regulates cell adhesion, migration, and metastasis through an ERK–EMT signaling axis.
Asa P.Y. Lau +8 more
wiley +1 more source
Genomic Prediction of Genotype × Environment Interaction Kernel Regression Models
In genomic selection (GS), genotype × environment interaction (G × E) can be modeled by a marker × environment interaction (M × E). The G × E may be modeled through a linear kernel or a nonlinear (Gaussian) kernel.
Jaime Cuevas +7 more
doaj +1 more source
Finding novel vulnerabilities of hypomorphic BRCA1 alleles
Synthetic lethality screens performed to identify novel vulnerabilities often model complete gene loss, thereby overlooking patient‐derived hypomorphic mutations. In this study, we have performed genome‐wide CRISPR screens on BRCA1 hypomorphic mutations, showing BRCA1I26A behaves like wild‐type, while BRCA1R1699Q mimics deficiency. Furthermore, we have
Anne Schreuder +10 more
wiley +1 more source
Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models
The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains.
Jaime Cuevas +5 more
doaj +1 more source
A novel approach to simulate gene-environment interactions in complex diseases [PDF]
Background: Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc ...
Amato, Roberto +24 more
core +1 more source
In a murine model of myocardial ischemia and reperfusion (MI/R), the CD36 azapeptide ligand MPE‐298 reduces cardiac injury and transiently lowers left ventricular long‐chain fatty acids (LCFAs) accumulation 3 h after reperfusion, accompanied by a decrease of oxidative stress and inflammation‐associated genes' expression in the heart and adipose tissue.
Jade Gauvin +12 more
wiley +1 more source

