Neural network learning defines glioblastoma features to be of neural crest perivascular or radial glia lineages.

Glioblastoma is believed to originate from nervous system cells; however, a putative origin from vessel-associated progenitor cells has not been considered. We deeply single-cell RNA-sequenced glioblastoma progenitor cells of 18 patients and integrated 710 bulk tumors and 73,495 glioma single cells of 100 patients to determine the relation of glioblastoma cells to normal brain cell types. A novel neural network-based projection of the developmental trajectory of normal brain cells uncovered two principal cell-lineage features of glioblastoma, neural crest perivascular and radial glia, carrying defining methylation patterns and survival differences.

Computational Methods to Identify Cell-Fate Determinants, Identity Transcription Factors, and Niche-Induced Signaling Pathways for Stem Cell Research.

The large-scale development of high-throughput sequencing technologies has not only allowed the generation of reliable omics data related to various regulatory layers but also the development of novel computational models in the field of stem cell research. These computational approaches have enabled the disentangling of a complex interplay between these interrelated layers of regulation by interpreting large quantities of biomedical data in a systematic way. In the context of stem cell research, network modeling of complex gene-gene interactions has been successfully used for understanding the mechanisms underlying stem cell differentiation and cellular conversion.

TransSynW: A single-cell RNA-sequencing based web application to guide cell conversion experiments.

Generation of desired cell types by cell conversion remains a challenge. In particular, derivation of novel cell subtypes identified by single-cell technologies will open up new strategies for cell therapies. The recent increase in the generation of single-cell RNA-sequencing (scRNA-seq) data and the concomitant increase in the interest expressed by researchers in generating a wide range of functional cells prompted us to develop a computational tool for tackling this challenge.

G-quadruplex formation enhances splicing efficiency of PAX9 intron 1.

G-quadruplexes are secondary structures present in DNA and RNA molecules, which are formed by stacking of G-quartets (i.e., interaction of four guanines (G-tracts) bounded by Hoogsteen hydrogen bonding).

Novel ALPL genetic alteration associated with an odontohypophosphatasia phenotype.

Hypophosphatasia (HPP) is an inherited disorder of mineral metabolism caused by mutations in ALPL, encoding tissue non-specific alkaline phosphatase (TNAP). Here, we report the molecular findings from monozygotic twins, clinically diagnosed with tooth-specific odontohypophosphatasia (odonto-HPP). Sequencing of ALPL identified two genetic alterations in the probands, including a heterozygous missense mutation c.

The role of modularity in the evolution of primate postcanine dental formula: integrating jaw space with patterns of dentition.

The assembly of a phenotype into modules or developmental fields, which are semiautonomous units in development and function, seems to be one of the strategies to increase the capacity to produce phenotypic variation. In mammals the upper dentition is formed on two distinct developmental units, wherein incisors are formed on the primary palate, which is derived from the embryonic frontonasal process, and the other teeth (canine, premolar, and molar) are formed on the alveolar bone, which is derived from the maxillary process (termed herein as PALATE2). The aim of the present work was to analyze the variations in size and number of premolar and molar teeth in primate dentition and to correlate these morphometrical parameters with the relative size of these tooth classes with respect to PALATE2.