Capturing hidden regulation based on noise change of gene expression level from single cell RNA-seq in yeast

Recent progress in high throughput single cell RNA-seq (scRNA-seq) has activated the development of data-driven inferring methods of gene regulatory networks. Most network estimations assume that perturbations produce downstream effects. However, the effects of gene perturbations are sometimes compensated by a gene with redundant functionality (functional compensation). In order to avoid functional compensation, previous studies constructed double gene deletions, but its vast nature of gene combinations was not suitable for comprehensive network estimation. We hypothesized that functional compensation may emerge as a noise change without mean change (noise-only change) due to varying physical properties and strong compensation effects. Here, we show compensated interactions, which are not detected by mean change, are captured by noise-only change quantified from scRNA-seq. We investigated whether noise-only change genes caused by a single deletion of STP1 and STP2, which have strong functional compensation, are enriched in redundantly regulated genes. As a result, noise-only change genes are enriched in their redundantly regulated genes. Furthermore, novel downstream genes detected from noise change are enriched in “transport”, which is related to known downstream genes. Herein, we suggest the noise difference comparison has the potential to be applied as a new strategy for network estimation that capture even compensated interaction.

Capturing Hidden Regulation based on Noise Change of Gene Expression Level from Single Cell RNA-seq in Yeast

Recent progress in high throughput single cell RNA-seq (scRNA-seq) has activated the development of data-driven inferring methods of gene regulatory networks. Most network estimations assume that perturbations produce downstream effects. However, the effects of gene perturbations are sometimes compensated by a gene with redundant functionality (functional compensation). In order to avoid functional compensation, previous studies constructed double gene deletions, but its vast nature of gene combinations was not suitable for comprehensive network estimation. We hypothesized that functional compensation may emerge as a noise change without mean change (noise-only change) due to varying physical properties and strong compensation effects. Here, we show compensated interactions, which are not detected by mean change, are captured by noise-only change quantified from scRNA-seq. We investigated whether noise-only change genes caused by a single deletion of STP1 and STP2, which have strong functional compensation, are enriched in redundantly regulated genes. As a result, noise-only change genes are enriched in their redundantly regulated genes. Furthermore, novel downstream genes detected from noise change are enriched in “transport”, which is related to known downstream genes. Herein, we suggest the noise difference comparison has the potential to be applied as a new strategy for network estimation that capture even compensated interaction.

Capturing hidden regulation based on noise change of gene expression level from single cell RNA-seq in yeast

Recent progress in high throughput single cell RNA-seq (scRNA-seq) has activated the development of data-driven inferring methods of gene regulatory networks. Most network estimations assume that perturbations produce downstream effects. However, the effects of gene perturbations are sometimes compensated by a gene with redundant functionality (functional compensation). In order to avoid functional compensation, previous studies constructed double gene deletions, but its vast nature of gene combinations was not suitable for comprehensive network estimation. We hypothesized that functional compensation may emerge as a noise change without mean change (noise-only change) due to varying physical properties and strong compensation effects. Here, we show compensated interactions, which are not detected by mean change, are captured by noise-only change quantified from scRNA-seq. We investigated whether noise-only change genes caused by a single deletion of STP1 and STP2, which have strong functional compensation, are enriched in redundantly regulated genes. As a result, noise-only change genes are enriched in their redundantly regulated genes. Furthermore, novel downstream genes detected from noise change are enriched in 'transport', which is related to known downstream genes. Herein, we suggest the noise difference comparison has the potential to be applied as a new strategy for network estimation that capture even compensated interaction.

Contralesional functional network reorganization of the insular cortex in diffuse low-grade glioma patients

Diffuse low-grade gliomas (DLGGs) growing on the insular lobe induce contralesional hemispheric insular lobe compensation of damaged functioning by increasing cortical volumes. However, it remains unclear how functional networks are altered in patients with insular lobe DLGGs during functional compensation. Thirty-five patients with insular DLGGs were classified into the left (insL, n = 16) and right groups (insR, n = 19), and 33 healthy subjects were included in the control group. Resting state functional magnetic resonance imaging was used to generate functional connectivity (FC), and network topological properties were evaluated using graph theoretical analysis based on FC matrices. Network-based statistics were applied to compare differences in the FC matrices. A false discovery rate was applied to correct the topological properties. There was no difference in the FC of edges between the control and insL groups; however, the nodal shortest path length of the right insular lobe was significantly increased in the insL group compared to the control group. Additionally, FC was increased in the functional edges originating from the left insular lobe in the insR group compared to the control group. Moreover, there were no differences in topological properties between the insR and control groups. The contralesional insular lobe is crucial for network alterations. The detailed patterns of network alterations were different depending on the affected hemisphere. The observed network alterations might be associated with functional network reorganization and functional compensation.

FUNCTIONAL CONNECTIVITY IN MILD GNITIVE IMPAIRMENT PATIENTS WITH PIB+ AND – BIOMARKERS

Background: According to the recent NIA-AA, a probable predictor of Alzheimer’s disease convertor in mild cognitive impairment (MCI) is the Aβ protein deposit in PET PIB exam. However, there is a lack of studies investigating functional connectivity in PIB +/- MCI patients. Objectives: to investigate differences in functional connectivity during resting state in MCI patients with PET PIB+ and - biomarkers. Methods: PET PIB+ (N=12 and PIB- (N=12) MCI patients underwent fMRI during resting state using 3 ROIS related to memory (posterior cingulate and bilateral hippocampus). Results: there were significant connectivity differences (p <0.05) between PIB+ and PIB- patients above 80% for right temporal region connectivity regarding left and right temporal region. Conclusions The results suggest that PET PIB+ MCI patients show significant difference in functional connectivity on the right temporal region in relation to left and right hippocampus ROI during the resting state possibly related to functional compensation.

Functional compensation precedes recovery of tissue mass following acute liver injury

The liver plays a central role in metabolism, protein synthesis and detoxification. It possesses unique regenerative capacity upon injury. While many factors regulating cellular proliferation during liver repair have been identified, the mechanisms by which the injured liver maintains vital functions prior to tissue recovery are unknown. Here, we identify a new phase of functional compensation following acute liver injury that occurs prior to cellular proliferation. By coupling single-cell RNA-seq with in situ transcriptional analyses in two independent murine liver injury models, we discover adaptive reprogramming to ensure expression of both injury response and core liver function genes dependent on macrophage-derived WNT/β-catenin signaling. Interestingly, transcriptional compensation is most prominent in non-proliferating cells, clearly delineating two temporally distinct phases of liver recovery. Overall, our work describes a mechanism by which the liver maintains essential physiological functions prior to cellular reconstitution and characterizes macrophage-derived WNT signals required for this compensation.

Myeloid transformation by MLL-ENL depends strictly on C/EBP

Chromosomal rearrangements of the mixed-lineage leukemia gene MLL1 are the hallmark of infant acute leukemia. The granulocyte-macrophage progenitor state forms the epigenetic basis for myelomonocytic leukemia stemness and transformation by MLL-type oncoproteins. Previously, it was shown that the establishment of murine myelomonocytic MLL-ENL transformation, but not its maintenance, depends on the transcription factor C/EBPα, suggesting an epigenetic hit-and-run mechanism of MLL-driven oncogenesis. Here, we demonstrate that compound deletion of Cebpa/Cebpb almost entirely abrogated the growth and survival of MLL-ENL–transformed cells. Rare, slow-growing, and apoptosis-prone MLL-ENL–transformed escapees were recovered from compound Cebpa/Cebpb deletions. The escapees were uniformly characterized by high expression of the resident Cebpe gene, suggesting inferior functional compensation of C/EBPα/C/EBPβ deficiency by C/EBPε. Complementation was augmented by ectopic C/EBPβ expression and downstream activation of IGF1 that enhanced growth. Cebpe gene inactivation was accomplished only in the presence of complementing C/EBPβ, but not in its absence, confirming the Cebpe dependency of the Cebpa/Cebpb double knockouts. Our data show that MLL-transformed myeloid cells are dependent on C/EBPs during the initiation and maintenance of transformation.