3. Spatial and temporal localization

We follow with a description of possible experimental data sets for populating transcriptome model in W. RNA-seq data sets would be the preferred source for fine structure of word contents, but microarray expression data could also be used for overall population of W.

#### 3.1. Spatial localization by RNA imaging

The only method that provides insight into both the level and localization in single cells is in situ hybridization (ISH), which has increased considerably in importance in RNA research. ISH along with multiplex RNA profiling (MERFISH) can be used to measure the degree of associations among transcripts. Numerous RNA species have been identified, counted, and localized in single cells using MERFISH, a single-molecule imaging approach that uses combinatorial labeling and sequential imaging with an encoding scheme capable of detection and/or correction of errors. This multiplexed measurement of individual RNAs can be used to measure the gene expression profile and noise, along with covariation in expression among different genes, and spatial distribution of RNAs within single cells.

#### 3.1.1. Localization of small RNAs

For miRNAs, ISH is exceptionally challenging because of miRNA features such as small size, sequence similarity among various miRNA family members, and low tissue-specific or development-specific expression levels. Standard ISH protocols can be modified to improve miRNA detection [45]. Locked nucleic acid (LNA/DNA) probes have great utility in miRNA detection because of short hybridization time, high efficiency, discriminatory power, and high melting temperature of the miRNA/probe complex [46]. Minimal length of LNA/DNA probes was found to be 12 nt with probes usually containing 30% LNA nucleotides [46]. A mixture of 2<sup>0</sup> - OMe RNA and LNA modifications in a 2:1 ratio resulted in improved specificity and stability of the probe/RNA duplex in comparison to LNA/DNA probes [47]. Experiment specificity was found to be further improved by lengthening the probe length to 19 nt [48].

#### 3.1.2. Localization by MERFISH

Chen et al. [33] used array-synthesized oligopools as templates to make encoding probes in the MERFISH protocol. An oligopaint approach developed by Beliveau et al. [49] can generate a large number of oligonucleotide probes to label chromosome DNA. Inspired by this approach, Chen et al. [33] designed a two-step labeling scheme to encode and read out cellular RNAs. They labeled a target set of cellular RNAs with a set of encoding probes, each probe comprising a RNA targeting sequence and two flanking readout sequences. Four readout sequences were assigned to each target RNA species based on error-correction optimized code words. They identified these readout sequences with complementary FISH probes via rounds of hybridization and imaging; each round using a different readout probe. To increase the signal-to-background ratio, each cellular RNA is labeled with 192 encoding probes.

#### 3.2. RNA diffusion

global shift in expression occurs between conditions, such that control-based normalization may be necessary for technical variation, and a global mean read for global differences in RNA

We follow with a description of possible experimental data sets for populating transcriptome model in W. RNA-seq data sets would be the preferred source for fine structure of word contents, but microarray expression data could also be used for overall population of W.

The only method that provides insight into both the level and localization in single cells is in situ hybridization (ISH), which has increased considerably in importance in RNA research. ISH along with multiplex RNA profiling (MERFISH) can be used to measure the degree of associations among transcripts. Numerous RNA species have been identified, counted, and localized in single cells using MERFISH, a single-molecule imaging approach that uses combinatorial labeling and sequential imaging with an encoding scheme capable of detection and/or correction of errors. This multiplexed measurement of individual RNAs can be used to measure the gene expression profile and noise, along with covariation in expression among differ-

For miRNAs, ISH is exceptionally challenging because of miRNA features such as small size, sequence similarity among various miRNA family members, and low tissue-specific or development-specific expression levels. Standard ISH protocols can be modified to improve miRNA detection [45]. Locked nucleic acid (LNA/DNA) probes have great utility in miRNA detection because of short hybridization time, high efficiency, discriminatory power, and high melting temperature of the miRNA/probe complex [46]. Minimal length of LNA/DNA probes was found to be 12 nt with probes usually containing 30% LNA nucleotides [46]. A mixture of 2<sup>0</sup>

OMe RNA and LNA modifications in a 2:1 ratio resulted in improved specificity and stability of the probe/RNA duplex in comparison to LNA/DNA probes [47]. Experiment specificity was

Chen et al. [33] used array-synthesized oligopools as templates to make encoding probes in the MERFISH protocol. An oligopaint approach developed by Beliveau et al. [49] can generate a large number of oligonucleotide probes to label chromosome DNA. Inspired by this approach, Chen et al. [33] designed a two-step labeling scheme to encode and read out cellular RNAs. They labeled a target set of cellular RNAs with a set of encoding probes, each probe comprising a RNA targeting sequence and two flanking readout sequences. Four readout sequences were assigned to each target RNA species based on error-correction optimized code words.

found to be further improved by lengthening the probe length to 19 nt [48].


levels.

3. Spatial and temporal localization

92 Applications of RNA-Seq and Omics Strategies - From Microorganisms to Human Health

3.1. Spatial localization by RNA imaging

3.1.1. Localization of small RNAs

3.1.2. Localization by MERFISH

ent genes, and spatial distribution of RNAs within single cells.

Brownian effects are ubiquitous in numerous examples of soft condensed matter physics [20] in which the system can be modeled as a set of interacting degrees of freedom in contact with a heat reservoir. Brownian motion plays an important role when one infers macroscopic behaviors from mesoscopic levels of description, frequently a desire in the study of complex systems. Dynamics at the mesoscopic level is governed by a set of Langevin processes or equivalently by the corresponding N-particle Fokker–Planck equation. This scheme applies nonequilibrium thermodynamics to derive the kinetic equations describing the evolution of an N-particle probability distribution function [20]. One then considers a system of N Brownian particles diluted in a solvent, which acts as a thermal reservoir. Particle velocities are then modeled as internal thermodynamic variables and permit an analysis in the phase space of the Brownian particles. A local equilibrium hypothesis constrains the phase space level and from it one derives the thermodynamic entropy balance equation. Entropy production accounts for irreversible processes taking place in the phase space, then quantifying fluxes and forces can be done in a similar manner as in the thermodynamics of irreversible processes [20]. A general thermodynamic treatment of systems of N interacting Brownian motion particles as described by Fokker-Planck equations is detailed by Savel'ev et al. [16].
