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On page 1 showing 1 ~ 2 papers out of 2 papers

Stochasticity constrained by deterministic effects of diet and age drive rumen microbiome assembly dynamics.

  • Ori Furman‎ et al.
  • Nature communications‎
  • 2020‎

How complex communities assemble through the animal's life, and how predictable the process is remains unexplored. Here, we investigate the forces that drive the assembly of rumen microbiomes throughout a cow's life, with emphasis on the balance between stochastic and deterministic processes. We analyse the development of the rumen microbiome from birth to adulthood using 16S-rRNA amplicon sequencing data and find that the animals shared a group of core successional species that invaded early on and persisted until adulthood. Along with deterministic factors, such as age and diet, early arriving species exerted strong priority effects, whereby dynamics of late successional taxa were strongly dependent on microbiome composition at early life stages. Priority effects also manifest as dramatic changes in microbiome development dynamics between animals delivered by C-section vs. natural birth, with the former undergoing much more rapid species invasion and accelerated microbiome development. Overall, our findings show that together with strong deterministic constrains imposed by diet and age, stochastic colonization in early life has long-lasting impacts on the development of animal microbiomes.


Accurate estimation of cell composition in bulk expression through robust integration of single-cell information.

  • Brandon Jew‎ et al.
  • Nature communications‎
  • 2020‎

We present Bisque, a tool for estimating cell type proportions in bulk expression. Bisque implements a regression-based approach that utilizes single-cell RNA-seq (scRNA-seq) or single-nucleus RNA-seq (snRNA-seq) data to generate a reference expression profile and learn gene-specific bulk expression transformations to robustly decompose RNA-seq data. These transformations significantly improve decomposition performance compared to existing methods when there is significant technical variation in the generation of the reference profile and observed bulk expression. Importantly, compared to existing methods, our approach is extremely efficient, making it suitable for the analysis of large genomic datasets that are becoming ubiquitous. When applied to subcutaneous adipose and dorsolateral prefrontal cortex expression datasets with both bulk RNA-seq and snRNA-seq data, Bisque replicates previously reported associations between cell type proportions and measured phenotypes across abundant and rare cell types. We further propose an additional mode of operation that merely requires a set of known marker genes.


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