Nuclear transcriptome profiling of induced pluripotent stem cells and embryonic stem cells identify non-coding loci resistant to reprogramming

<p>Identification of functionally relevant differences between induced pluripotent stem cells (iPSC) and reference embryonic stem cells (ESC) remains a central question for therapeutic applications. Differences in gene expression between iPSC and ESC have been examined by microarray and more recently with RNA-SEQ technologies. We here report an in depth analyses of nuclear and cytoplasmic transcriptomes, using the CAGE (cap analysis of gene expression) technology, for 5 iPSC clones derived from mouse lymphocytes B and 3 ESC lines. This approach reveals nuclear transcriptomes significantly more complex in ESC than in iPSC. Hundreds of yet not annotated putative non-coding RNAs and enhancer-associated transcripts specifically transcribed in ESC have been detected and supported with epigenetic and chromatin-chromatin interactions data. We identified super-enhancers transcriptionally active specifically in ESC and associated with genes implicated in the maintenance of pluripotency. Similarly, we detected non-coding transcripts of yet unknown function being regulated by ESC specific super-enhancers. Taken together, these results demonstrate that current protocols of iPSC reprogramming do not trigger activation of numerous <i>cis</i>-regulatory regions. It thus reinforces the need for already suggested deeper monitoring of the non-coding transcriptome when characterizing iPSC clones. Such differences in regulatory transcript expression may indeed impact their potential for clinical applications.</p

List of representative genes with mutation sites located on different types of protein binding interfaces.

<p>Gene and protein identifiers are shown together with the PDB code of structural evidence of interactions (structure of homologous complex), physico-chemical distances between substituted amino scids (“Dist Phys”) and difference in binding energy (“dddG”). Several multiple substitutions of the same site are listed on the same line.</p

The effect of mutations on protein binding.

<p>(<b>A</b>) Distribution of binding energy difference upon mutation for electrostatic and van-der-Waals components. The electrostatic component of binding energy was significantly shifted toward negative values compared to the van-der-Waals component (p-value = 1.3×10⁻³) (<b>B</b>) Distributions of physico-chemical distances between amino acids that correspond to glioblastoma mutations on protein-protein interfaces and non-interface regions. Distributions that referred to amino acid substitutions on protein-protein interfaces had significantly larger distances compared to non-interface regions (p-value = 0.011).</p

Examples of mutations on protein-nucleic acid and protein-ion interactions.

<p>Residues at mutated sites on homologous proteins are shown in red (wild type) and blue (mutant) stick models. (<b>A</b>) Zinc binding motif of LMO-2, homologous protein of <i>LMX1A</i> (PDB: 2XJY chain A, sequence identity 35%). A zinc ion is shown as a dark blue sphere. Zinc binding residues are shown in yellow stick models. (<b>B</b>) DNA binding site of <i>Pax-6</i>, homolog of <i>Pax-9</i> (PDB: 6PAX chain A, sequence identity: 74%). (<b>C</b>) <i>MAPK10</i>, homolog of <i>MAPK9</i>, with Mg-ANP (ATP analog) (PDB: 1JNK chain A, sequence identity: 85%). Mg ions are shown as green spheres and ANP is shown using a white sphere representation.</p

Mapping the human interactome and glioblastoma mutations on binding interfaces.

<p>In step 1 we mapped 695 missense mutations from 598 human genes to protein sequences. Subsequently, query protein sequences were aligned to homologous, experimentally determined structural complexes (step 2), allowing us to infer query-specific interactions with other proteins, nucleic acids and ions (step 3). For protein-protein interactions, we mapped interaction partners to their corresponding human proteins (step 4a), allowing us to find 160 protein interactions between 150 genes with mutations affecting their interaction interfaces. In step 4b, we compared the structures of the unperturbed wild-type protein and the mutated protein by performing energy minimization calculations and determining binding energy differences.</p