Moreover, understanding the origin and function of the gene expression noise will provide critical insights about how noise contribute to alterations in gene regulatory architecture (Mar,2011; Chalacon, 2012), metabolic responses (Murphy, 2010; Wang, 2011), differentiation of disease cell subtypes (Ecker, 2015), embryonic development (Piras, 2014; Sosnik, 2016), drug resistance (Charlebois, 2011), and susceptibility to disease (Dar, 2014).
Quantification of the gene expression noise is not an easy task, as a genetically regulated biochemical process, gene expression is affected by stochastic or 'intrinsic'  (local cell density, cell size, shape and rate of proliferation) and tightly regulated or 'extrinsic' (cell cycle, promoter sequence, chromosomal position and associated transcription factors) biological factors ( Jones ,2014; Murphy, 2007; Snijder, 2009; Satija, 2014; Mitchell, 2018; Swain, 2002; Sanchez, 2013), as well as technical (____) factors (Brennecke, 2013).  Due to technology limitations before to the development of single-cell RNA sequencing (scRNA-seq) based in microfluidics, the previous measurements of gene expression noise reported were made under several technical limitations that restricted the number of measurable cells and genes by experiment (Pires, 2016). Pioneering studies of gene expression noise are the result of the measurement of the gene expression in a set of cells that were in different phases of the cell cycle, have differentiated into different cell types or were exposed to external stimuli (Raser, 2006; Mitchel, 2018).  
Now, thanks to the technological developments in scRNA-seq techniques based in droplets, it is possible to isolate a large number of cells, and with the improvements in RNA isolation and amplification methods, it is doable to profile the transcriptome of individual cells using next-generation sequencing technologies (Kiselev, 2019). Altogether, these advances allow improving our understanding of the origin, global distribution, and functional consequences of gene expression noise. scRNA-seq allow to identify cell-to-cell variation between thousands of cell of the same type (Zheng, 2017), this variation often indicates a diversity of hidden functional capacities that facilitate collective behavior in tissue function and normal development, and the change of this functional diversity was suggested to be associated with disease development (Chang, Hemberg, et al. 2008, Bahar Halpern, Tanami et al. 2015, Richard, Boullu et al. 2016, Mohammed, Hernando-Herraez et al. 2017). 
cell type studies
https://www.nature.com/articles/s41586-019-0933-9
https://www.nature.com/articles/s41586-019-0969-x
In the cells associated with the immune system, leverage of cellular heterogeneity at multiple molecular and phenotypic levels have been reported (). 
Immune system (IGs, CDKN1A, DUSP2, CCLs, NKBIA, LTs, PRSS2, CAMP, CTSC, among others), particularly the innate immune system produce chemokine receptors (CCLs and CCRs) in order to coordinate the activity of individual cells through intercellular communication using cytokines. This mechanisms related to the short-range communication between cells support the classical antibody-mediated complement activation associated with the B cell receptor signaling pathway during the positive regulation of lymphocyte activation.
http://science.sciencemag.org/content/332/6030/687
% Supporting a role for epigenetic mechanisms, Mariani et al. [50] demonstrated that a computational model of stochastic chromatin opening was capable of accurately reproducing measured Il4  expression patterns.
% However, both this seminal work and follow-up studies revealed that cellular heterogeneity often manifests itself on a continuous scale, rather than through multiple discrete subpopulations. Specifically, B cell and monocyte maturation programs exhibit a spectrum of transitional states. Cellular populations use continuous levels of variability in the expression of key signaling molecules and receptors to mount diverse, effective, and plastic responses.
% The immune system needs to maintain robustness. One way of coordinating the activity of individual cells is through intercellular communication (e.g., with cytokines). This allows individual cellular responses to be communicated and then propagated or restrained.
% Even in the absence of a clear molecular mechanism, understanding the role of population heterogeneity in maintaining a healthy immune system requires measuring phenotypic variation at the single cell level.
% These data provided experimental evidence that competing for stochastic intracellular events can drive heterogeneous B cell fate decisions at the single cell level, while yielding, on average, robust population behaviors that could be shaped by altering the microenvironment in which this stochastic cellular decision making is performed.
%To understand this, we will need to decipher how molecular
variability at different levels is interconnected and drives phenotypic variation. For example, does a broad distribution of surface receptor protein levels simply echo pre-existing stochasticity in mRNA transcription? If so, has the immune system evolved to leverage the noisiness of transcription – for example, using this heterogeneity to encode analog responses via a digital event [56,67]
https://www.nature.com/articles/s41577-019-0131-x
% To mount an efficient and accurate response, immune cells must coordinate their individual activation into global tissue- level responses9 Crosstalk between immune cells would remain local if it was only mediated by cell-to-cell contacts; consequently, the global regulation of inflammation requires long- range intercellular communication,  as mediated by cytokines
% T cells produce cytokines at a constant rate while they are producing16
% Cytokine receptor abundance can be used to estimate the rate of cytokine consumption, as cytokines bind to receptors according to well-characterized biophysical models and are endocytosed at a typical rate of 1–5 molecules per hour14.
% B-cells are mostly cytokine-consuming cells (IL-4, IL-5, IL-6, IL-7, IL-9, IL-13, IL-21 and TNF), they only produces TNF
% Competition for cytokine is a key mechanism to mediate homeostasis and accurate decision making within the immune system.
% the net result of cytokine  availability is the accumulation of cells responding to  that cytokine. The relevance of cytokine competition as a self- modulating scheme is then structurally robust: cells accumulate until they reach a critical number that divides up the available cytokine pool and becomes a stable fixed point. Above this number, some cells do not receive enough cytokine and die; below this number, cells receive a ‘homeostatic kick’ to proliferate or extend their lifespan, and the population returns to its homeostatic number. Within that context, quantitative approaches become invaluable to tease apart cytokine production and consumption to understand how homeostasis becomes established.