Joanito, I. | bioRxiv Science

bioRxiv2021

Robust clustering and interpretation ofscRNA-seq data using reference componentanalysis

MotivationThe transcriptomic diversity of the hundreds of cell types in the human body can be analysed in unprecedented detail using single cell (SC) technologies. Though clustering of cellular transcriptomes is the default technique for defining cell types and subtypes, single cell clustering can be strongly influenced by technical variation. In fact, the prevalent unsupervised clustering algorithms can cluster cells by technical, rather than biological, variation. ResultsCompared to de novo (unsupervised) clustering methods, we demonstrate using multiple benchmarks that supervised clustering, which uses reference transcriptomes as a guide, is robust to batch effects. To leverage the advantages of supervised clustering, we present RCA2, a new, scalable, and broadly applicable version of our RCA algorithm. RCA2 provides a user-friendly framework for supervised clustering and downstream analysis of large scRNA-seq data sets. RCA2 can be seamlessly incorporated into existing algorithmic pipelines. It incorporates various new reference panels for human and mouse, supports generation of custom panels and uses efficient graph-based clustering and sparse data structures to ensure scalability. We demonstrate the applicability of RCA2 on SC data from human bone marrow, healthy PBMCs and PBMCs from COVID-19 patients. Importantly, RCA2 facilitates cell-type-specific QC, which we show is essential for accurate clustering of SC data from heterogeneous tissues. In the era of cohort-scale SC analysis, supervised clustering methods such as RCA2 will facilitate unified analysis of diverse SC datasets. AvailabilityRCA2 is implemented in R and is available at github.com/prabhakarlab/RCAv2

bioinformatics↗

bioRxiv2020

Basal leakage in oscillation: coupled transcriptional and translational control using feed-forward loops

The circadian clock is a complex system that plays many important roles in most organisms. Previously, many mathematical models have been used to sharpen our understanding of the Arabidopsis clock. However, these models are mostly dependent on transcriptional regulation, and the importance of post-translational regulation is still rarely discussed from theoretical aspects. In this study, we built a series of simplified oscillators with different regulations to study the importance of post-translational regulation (specifically, 26S proteasome degradation) in the clock system. We found that a simple transcriptional-based oscillator can already generate sustained oscillation, but the oscillation can be easily destroyed in the presence of transcriptional leakage. Coupling post-translational control with transcriptional-based oscillator in a feed-forward loop will greatly improve the robustness of the oscillator in the presence of basal leakage. Using these general models, we were able to replicate the increased variability observed in the E3 ligase mutant for both plant and mammalian clocks. With this insight, we also predict a plausible regulator of several E3 ligase genes in the plants clock. Thus, our results provide insights into and the plausible importance in coupling transcription and post-translation controls in the clock system. Author summaryFor circadian clocks, several current models had successfully captured the essential dynamic behavior of the clock system mainly with transcriptional regulation. Previous studies have shown that the 26s (1, 2) proteasome degradation controls are important in maintaining the stability of circadian rhythms. However, how the loss-of-function or over-expression mutant of this targeted degradations lead to unstable oscillation is still unclear. In this work, we investigate the importance of coupled transcriptional and post-translational feedback loop in the circadian oscillator. With general models our study indicate that the unstable behavior of degradation mutants could be caused by the increase in the basal level of the clock genes. We found that coupling a non-linear degradation control into this transcriptional based oscillator using feed-forward loop improves the robustness of the oscillator. Using this finding, we further predict some plausible regulators of Arabidopsiss E3 ligase protein such as COP1 and SINAT5. Hence, our results provide insights on the importance of coupling transcription and post-translation controls in the clock system.

systems biology↗