Gordon Wiegleb
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View article: Gene expression divergence during Drosophila head development on single nuclei resolution
Gene expression divergence during Drosophila head development on single nuclei resolution Open
In this work, I optimized single-nuclei and single-cell RNA sequencing protocols for working with small amounts of input tissue. Using one of these protocols, I generated 14 single-nuclei RNA expression datasets. These data cover up to fiv…
View article: Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material
Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material Open
Background Recent technological advances opened the opportunity to simultaneously study gene expression for thousands of individual cells on a genome-wide scale. The experimental accessibility of such single-cell RNA sequencing (scRNAseq) …
View article: Additional file 8 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material
Additional file 8 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material Open
Additional file 8: Table S8. List of top 3000 variable genes for scRNAseq and snRNAseq data, respectively.
View article: Additional file 5 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material
Additional file 5 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material Open
Additional file 5: Table S5. GO analysis of cell clusters identified in scRNAseq.
View article: Additional file 7 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material
Additional file 7 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material Open
Additional file 7: Table S7. GO analysis of cell clusters identified in snRNAseq.
View article: Additional file 10 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material
Additional file 10 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material Open
Additional file 10: Table S10. Comparison of differentially expressed genes for each comparable cluster between scRNAseq and snRNAseq data.
View article: Additional file 4 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material
Additional file 4 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material Open
Additional file 4: Table S4. List of marker genes for each cluster in scRNAseq analysis.
View article: Additional file 3 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material
Additional file 3 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material Open
Additional file 3: Table S3. Results of automatic cluster annotation and assignment to combined clusters.
View article: Additional file 9 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material
Additional file 9 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material Open
Additional file 9: Table S9. Top 3000 variable genes and GO enrichment results for scRNAseq, snRNAseq and shared.
View article: Additional file 2 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material
Additional file 2 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material Open
Additional file 2: Table S2. Score Matrix used to annotate cell types and list of references for individual marker genes used for cluster/cell type annotation.
View article: Additional file 6 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material
Additional file 6 of Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material Open
Additional file 6: Table S6. List of marker genes for each cluster in snRNAseq analysis.
View article: Multiple loci linked to inversions are associated with eye size variation in species of the<i>Drosophila virilis</i>phylad
Multiple loci linked to inversions are associated with eye size variation in species of the<i>Drosophila virilis</i>phylad Open
The size and shape of organs is tightly controlled to achieve optimal function. Natural morphological variations often represent functional adaptations to an ever-changing environment. For instance, variation in head morphology is pervasiv…
View article: Dynamic genome wide expression profiling of Drosophila head development reveals a novel role of Hunchback in retinal glia cell development and blood-brain barrier integrity
Dynamic genome wide expression profiling of Drosophila head development reveals a novel role of Hunchback in retinal glia cell development and blood-brain barrier integrity Open
Drosophila melanogaster head development represents a valuable process to study the developmental control of various organs, such as the antennae, the dorsal ocelli and the compound eyes from a common precursor, the eye-antennal imaginal d…
View article: Expression profiling reveals novel role of Hunchback in retinal glia cell development and blood-brain barrier integrity
Expression profiling reveals novel role of Hunchback in retinal glia cell development and blood-brain barrier integrity Open
The development of different cell types must be tightly coordinated in different organs. The developing head of Drosophila melanogaster represents an excellent model to study the molecular mechanisms underlying this coordination because th…