Biology subjects

Gain, C.

Publications and source records attributed to Gain, C..

3 recordsLinked to original sources

bioRxiv2020

A Spectral Theory for Wright's Inbreeding Coefficients and Related Quantities

Wrights inbreeding coefficient, FST, is a fundamental measure in population genetics. Assuming a predefined population subdivision, this statistic is classically used to evaluate population structure at a given genomic locus. With large numbers of loci, unsupervised approaches such as principal component analysis (PCA) have, however, become prominent in recent analyses of population structure. In this study, we describe the relationships between Wrights inbreeding coefficients and PCA for a model of K discrete populations. Our theory provides an equivalent definition of FST based on the decomposition of the genotype matrix into between and within-population matrices. The average value of Wrights FST over all loci included in the genotype matrix can be obtained from the PCA of the between-population matrix. Assuming that a separation condition is fulfilled and for reasonably large data sets, this value of FST approximates the proportion of genetic variation explained by the first (K - 1) principal components accurately. The new definition of FST is useful for computing inbreeding coefficients from surrogate genotypes, for example, obtained after correction of experimental artifacts or after removing adaptive genetic variation associated with environmental variables. The relationships between inbreeding coefficients and the spectrum of the genotype matrix not only allow interpretations of PCA results in terms of population genetic concepts but extend those concepts to population genetic analyses accounting for temporal, geographical and environmental contexts. Authors summaryPrincipal component analysis (PCA) is the most-frequently used approach to describe population genetic structure from large population genomic data sets. In this study, we show that PCA not only estimates ancestries of sampled individuals, but also computes the average value of Wrights inbreeding coefficient over the loci included in the genotype matrix. Our result shows that inbreeding coefficients and PCA eigenvalues provide equivalent descriptions of population structure. As a consequence, PCA extends the definition of this coefficient beyond the framework of allelic frequencies. We give examples on how FST can be computed from ancient DNA samples for which genotypes are corrected for coverage, and in an ecological genomic example where a proportion of genetic variation is explained by environmental variables.

evolutionary biology↗

bioRxiv2020

LEA 3: Factor models in population genetics and ecological genomics with R

A major objective of evolutionary biology is to understand the processes by which organisms have adapted to various environments, and to predict the response of organisms to new or future conditions. The availability of large genomic and environmental data sets provides an opportunity to address those questions, and the R package LEA has been introduced to facilitate population and ecological genomic analyses in this context. By using latent factor models, the program computes ancestry coefficients from population genetic data, and performs genotype-environment association analyses with correction for unobserved confounding variables. In this study, we present new functionalities of LEA, which include imputation of missing genotypes, fast algorithms for latent factor mixed models using multivariate predictors for genotype-environment association studies, population differentiation tests for admixed or continuous populations, and estimation of genetic offset based on climate models. The new functionalities are implemented in version 3.0 and higher releases of the package. Using simulated and real data sets, our study provides evaluations and examples of applications, outlining important practical considerations when analyzing ecological genomic data in R.

evolutionary biology↗

bioRxiv2019

Proteasomal Inhibition Triggers Viral Oncoprotein Degradation via Autophagy-Lysosomal Pathway

Epstein-Barr virus (EBV) nuclear oncoprotein EBNA3C is essential for B-cell transformation and development of several B-cell lymphomas particularly those are generated in an immuno-compromised background. EBNA3C recruits ubiquitin-proteasome machinery for deregulating multiple cellular oncoproteins and tumor suppressor proteins. Although EBNA3C is found to be ubiquitinated at its N-terminal region and interacts with 20S proteasome, the viral protein is surprisingly stable in growing B-lymphocytes. EBNA3C can also circumvent autophagy-lysosomal mediated protein degradation and subsequent antigen presentation for T-cell recognition. Recently, we have shown that EBNA3C enhances autophagy, which serve as a prerequisite for B-cell survival particularly under growth deprivation conditions. We now demonstrate that proteasomal inhibition by MG132 induces EBNA3C degradation both in EBV transformed B-lymphocytes and ectopic-expression systems. Interestingly, MG132 treatment promotes degradation of two EBNA3 family oncoproteins - EBNA3A and EBNA3C, but not the viral tumor suppressor protein EBNA3B. EBNA3C degradation induced by proteasomal inhibition is partially blocked when autophagy-lysosomal pathway is inhibited. In response to proteasomal inhibition, EBNA3C is predominantly K63-linked polyubiquitinated, colocalized with the autophagy-lsyosomal fraction in the cytoplasm and participated within p62-LC3B complex, which facilitates autophagy-mediated degradation. We further show that the degradation signal is present at the first 50 residues of the N-terminal region of EBNA3C. Proteasomal inhibition reduces the colony formation ability of this important viral oncoprotein, increases transcriptional activation of both latent and lytic gene expression and induces viral reactivation from EBV transformed B-lymphocytes. Altogether, this study offers rationale to use proteasome inhibitors as potential therapeutic strategy against multiple EBV associated B-cell lymphomas, where EBNA3C is expressed.\n\nAuthor SummaryEpstein-Barr virus (EBV) establishes latent infection in B-lymphocytes and is associated with a number of human malignancies, both of epithelial and lymphoid origin. EBV encoded EBNA3 family of nuclear latent antigens comprising of EBNA3A, EBNA3B, and EBNA3C are unique to immunoblastic lymphomas. While EBNA3A and EBNA3C are involved in blocking many important tumor suppressive mechanisms, EBNA3B exhibits tumor suppressive functions. Although EBNA3 proteins, in particular EBNA3C, interact with and employ different protein degradation machineries to induce B-cell lymphomagenesis, these viral proteins are extremely stable in growing B-lymphocytes. To this end, we now demonstrate that proteasomal inhibition leads to specifically degradation of oncogenic EBNA3A and EBNA3C proteins, whereas EBNA3B remains unaffected. Upon proteasomal inhibition, EBNA3C degradation occurs via autophagy-lysosomal pathway, through labeling with K63-linked polyubiquitination and participating in p62-LC3B complex involved in ubiquitin-mediated autophagy substrate selection and degradation through autolysosomal process. We also demonstrate that the N-terminal domain is responsible for autophgy-lysosomal mediated degradation, while the C-terminal domain plays a crucial role in cytoplasmic localization. Fascinatingly, while proteasomal inhibition reduces EBNA3Cs oncogenic property, it induces both latent and lytic gene expressions and promotes viral reactivation from EBV transformed B-lymphocytes. This is the first report which demonstrates a viral oncoprotein degrades through autophagy-lysosomal pathway upon proteasomal inhibition. In sum, the results promise development of novel strategies specifically targeting proteolytic pathway for the treatment of EBV associated B-cell lymphomas, particularly those are generated in immunocompromised individuals.

cancer biology↗