Search bioRxivSearch

Biology subjects

Huang, E.

Publications and source records attributed to Huang, E..

3 recordsLinked to original sources

Single-cell in situ transcriptomic map of astrocyte cortical layer diversity

During organogenesis, patterns and gradients of gene expression underlie organization and diversified cell specification to generate complex tissue architecture. While the cerebral cortex is organized into six excitatory neuronal layers, it is unclear whether glial cells are diversified to mimic neuronal laminae or show distinct layering. To determine the molecular architecture of the mammalian cortex, we developed a high content pipeline that can quantify single-cell gene expression in situ. The Large-area Spatial Transcriptomic (LaST) map confirmed expected cortical neuron layer organization and also revealed a novel neuronal identity signature. Screening 46 candidate genes for astrocyte diversity across the cortex, we identified grey matter superficial, mid and deep astrocyte identities in gradient layer patterns that were distinct from neurons. Astrocyte layers formed in early postnatal cortex and mostly persisted in adult mouse and human cortex. Mutations that shifted neuronal post-mitotic identity or organization were sufficient to alter glial layering, indicating an instructive role for neuronal cues. In normal mouse cortex, astrocyte layer patterns showed area diversity between functionally distinct cortical regions. These findings indicate that excitatory neurons and astrocytes cells are organized into distinct lineage-associated laminae, which give rise to higher order neuroglial complexity of cortical architecture.

neuroscience

Optical and physical mapping with local finishing enables megabase-scale resolution of agronomically important regions in the wheat genome

BackgroundNumerous scaffold-level sequences for wheat are now being released and, in this context, we report on a strategy for improving the overall assembly to a level comparable to that of the human genome.\n\nResultsUsing chromosome 7A of wheat as a model, sequence-finished megabase scale sections of this chromosome were established by combining a new independent assembly based on a BAC-based physical map, BAC pool paired end sequencing, chromosome arm specific mate-pair sequencing and Bionano optical mapping with the IWGSC RefSeq v1.0 sequence and its underlying raw data. The combined assembly results in 18 super-scaffolds across the chromosome. The value of finished genome regions is demonstrated for two approximately 2.5 Mb regions associated with yield and the grain quality phenotype of fructan carbohydrate grain levels. In addition, the 50 Mb centromere region analysis incorporates cytological data highlighting the importance of non-sequence data in the assembly of this complex genome region.\n\nConclusionsSufficient genome sequence information is shown to be now available for the wheat community to produce sequence-finished releases of each chromosome of the reference genome. The high-level completion identified that an array of seven fructosyl transferase genes underpins grain quality and yield attributes are affected by five f-box-only-protein-ubiquitin ligase domain and four root-specific lipid transfer domain genes. The completed sequence also includes the centromere.

genomics

Identification of Pathways Associated with Chemosensitivity through Network Embedding

Basal gene expression levels have been shown to be predictive of cellular response to cytotoxic treatments. However, such analyses do not fully reveal complex genotype-phenotype relationships, which are partly encoded in highly interconnected molecular networks. Biological pathways provide a complementary way of understanding drug response variation among individuals. In this study, we integrate chemosensitivity data from a recent pharmacogenomics study with basal gene expression data from the CCLE project and prior knowledge of molecular networks to identify specific pathways mediating chemical response. We first develop a computational method called PACER, which ranks pathways for enrichment in a given set of genes using a novel network embedding method. It examines known relationships among genes as encoded in a molecular network along with gene memberships of all pathways to determine a vector representation of each gene and pathway in the same low-dimensional vector space. The relevance of a pathway to the given gene set is then captured by the similarity between the pathway vector and gene vectors. To apply this approach to chemosensitivity data, we identify genes with basal expression levels in a panel of cell lines that are correlated with cytotoxic response to a compound, and then rank pathways for relevance to these response-correlated genes using PACER. Extensive evaluation of this approach on benchmarks constructed from databases of compound target genes, compound chemical structure, as well as large collections of drug response signatures demonstrates its advantages in identifying compound-pathway associations, compared to existing statistical methods of pathway enrichment analysis. The associations identified by PACER can serve as testable hypotheses about chemosensitivity pathways and help further study the mechanism of action of specific cytotoxic drugs. More broadly, PACER represents a novel technique of identifying enriched properties of any gene set of interest while also taking into account networks of known gene-gene relationships and interactions.

pharmacology and toxicology