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Alvarez-Buylla, E.

Publications and source records attributed to Alvarez-Buylla, E..

2 recordsLinked to original sources

Genome-Wide Association Studies meta-analysis uncovers NOJO and SGS3 novel genes involved in Arabidopsis thaliana primary root development and plasticity

Postembryonic primary root growth relies on meristems that harbour multipotent stem cells that produce new cells that will duplicate and provide all the different root cell types. Arabidopsis thaliana primary root growth has become a model for evo-devo studies due to its simplicity and facility to record cell proliferation and differentiation. To identify new genetic components relevant to primary root growth, we used a Genome-Wide Association Studies (GWAS) meta-analysis approach using data published in the last decade. In this work, we performed intra and inter-studies analyses to discover new genetic components that could participate in primary root growth. We used 639 accessions from nine different studies and performed different GWAS tests ranging from single studies and pairwise analysis with high correlation associations, analyzing the same number of accessions in different studies to using the daily data of the root growth kinetic of the same research. We found that primary root growth changes were associated with 41 genomic loci, of which six (14.6%) have been previously described as inhibitors or promoters of primary root growth. The knockdown of genes associated with two of these loci: a gene that participates in Trans-acting siRNAs (tasiRNAs) processing Suppressor of Gene Silencing (SGS3) and a gene with a Sterile Alpha Motif (SAM) confirmed their participation as repressors of primary root growth. As none has been shown to participate in this developmental process before, our GWAS analysis identified new genes that participate in primary root growth. Overall, our findings provide novel insights into the genomic basis of root development and further demonstrate the usefulness of GWAS meta-analyses in non-human species.

molecular biology↗

A quantitative network modeling approach to evaluate the role of cytokine combinations on CD4+ T cell differentiation, partial polarization, and plasticity

Diverse cellular polarization states with different phenotypes and functions are derived from the differentiation of activated CD4+ T naive lymphocytes in the presence of particular cytokines. In addition, conversion of polarized cells to phenotypes different from that originally induced has been documented, highlighting the capacity of the immune response for adaptation to changing circumstances. In a recent study, we proposed a minimal Boolean regulatory network of CD4+ T differentiation that incorporates transcription factors, signaling pathways, and autocrine and exogenous cytokines. The qualitative model effectively reproduced the main polarized phenotypes of CD4+ T cells and several of the plasticity events reported in the literature. Yet, the amount and the expression of cytokines relative to expression of other factors influence CD4+ T cell transitions. In this paper, we have extended the Boolean network to a continuous model that allows us to assess the effect of quantitative differences in the concentrations and combinations of exogenous and endogenous cytokines, as well as diverse levels of transcription factors expression, in order to assess the role of intracellular and extracellular components in CD4+ T differentiation and plasticity. Interestingly, the model predicts either abrupt or gradual differentiation patterns between observed phenotypes depending on critical concentrations of single or multiple environmental cytokines. Plastic changes induced by environmental cytokines were observed in conditions of partial phenotype polarization in the Th1/Th2 transition. On the other hand, the Th17/iTreg transition was highly dependent on cytokine concentrations in the environment. Thus, modeling shows how the concentration of exogenous factors, the degree of initial polarization, and cell heterogeneity, may determine the differentiation and plasticity capacity of CD4+ T cells. The model and results presented here are useful to further understand system-level mechanisms underlying observed patterns of CD4+ T differentiation and plasticity.

systems biology↗