Entre el 24 y 28 de septiembre acoge la escuela de verano sobre bioinformática “STATegra Summer School on NGS and Data Integration”. Este encuentro profesional, promovido y organizado por la Unidad de Bioinformática Traslacional de Navarrabiomed, ofrece el 28 de septiembre dos sesiones abiertas a profesionales interesados entre las 13:30 y las 15:30 horas. El aforo es limitado y las personas interesadas deberán inscribirse previamente enviando nombre, dos apellidos y centro a la dirección de email email@example.com
- “Enhancer interactomes resolve the cis-regulatory architecture and control of gene expression in T cells” . Ricardo N. Ramirez, Postdoctoral fellow, Harvard Medical School, USA.
The specification of gene expression programs is facilitated in part through the control and activation of enhancer elements, which combinatorially regulate distal genes that can be several Kb to Mb away. We followed two paths to ascertain how the enhancer interactome determine the transcriptome of FoxP3+ Treg cells. First, we took advantage of the atlas of accessible chromatin across the entire mouse immune system generated with ATAC-seq by the ImmGen consortium, asking when enhancer elements that serve as FoxP3 docking sites become accessible. In agreement with previous reports that Foxp3 exploits a pre-existent enhancer landscape, many sites bound by FoxP3 in Treg cells were already accessible at the earliest stages of T differentiation. However, ~25% of FoxP3 binding sites were only accessible late in differentiation, or even specifically in Treg cells. Significant enrichment of the NFkb motif and H3K4Me1 chromatin demarcates these dynamic from constitutively open FoxP3-bound elements, providing a mechanistic explanation for the role of this combination of factors in specifying Treg differentiation. Second, to chart the interaction between enhancer elements and how they differ between Tconv and Treg cells, we applied H3K27Ac HiChIP to determine short and long-range interactions genome-wide, also refining this map with FoxP3 and Cohesin ChIP-seq. The results reveal cis-regulatory loop configurations of distal enhancers and target genes that mediate cell-specific gene expression between T cell states. Many loops are organized as “cliques” that connect enhancer elements, where some of the links within a clique may be differently active in Tconv or Treg cells, others more monomorphic. In some instances, activation of some Treg-specific genes coincide with a complete opening of loop interactions in the locus. Integration of transcription factor binding data with the Treg enhancer interactome reveals an interesting interplay between Cohesin and FoxP3 occupancy at loop anchors, suggesting a novel role for FoxP3 in the control of gene expression programs through chromatin looping.
- “From Precision Biology & Machine Learning To Clinical Translation & Next Generation Smart Agents” Jesper Tegnér, Professor in Bioscience and Computer Science, KAUST University, Saudi Arabia.
The ever-increasing amount and quality of Biological and Medical data is transforming research, innovation, and education. We need not only to extract, to fuse (i.e. integrate) available and locally generated project specific new data, but crucially to make sense of it – either for a given specific question or in search for a fresh hypothesis. This is indeed both exciting and daunting. For example, from solving the human genome to precision medicine, we have witnessed a significant amount of heat, hype, and hope in particular w.r.t. putative clinical translations. Computational techniques, from bioinformatics pipelines to machine learning and large-scale modeling and simulation are essential for moving beyond stamp collection, leveling towards predictive and data-driven biology and medicine. Yet, we need to assess carefully between what is hope, hype and realistic expectations and tools. I will discuss opportunities and challenges in this emerging interlaced landscape of computing and living systems. In particular. I’l address prospects for (a) understanding of complex biological circuits, (b) enabling clinical translation, and (c) designing smart algorithms and machines.