3.4D: Types of RNA - Biology

3.4D: Types of RNA - Biology

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RNA is the nucleic acid that makes proteins from the code provided by DNA through the processes of transcription and translation.

Learning Objectives

  • Describe the structure and function of RNA

Key Points

  • The nitrogen bases in RNA include adenine (A), guanine (G), cytosine (C), and uracil (U).
  • Messenger RNA (mRNA) carries the code from the DNA to the ribosomes, while transfer RNA (tRNA) converts that code into a usable form.
  • Ribosomes are the sites where tRNA and rRNA assemble proteins.
  • RNA differs from DNA in that it is single stranded, has uracil instead of thymine, carries the code for making proteins instead of directing all of the cell ‘s functions, and has ribose as its five-carbon sugar instead of deoxyribose.

Key Terms

  • codon: a sequence of three adjacent nucleotides, which encode for a specific amino acid during protein synthesis or translation
  • transcription: the synthesis of RNA under the direction of DNA

RNA Structure and Function

The two main types of nucleic acids are deoxyribonucleic acid (DNA) and ribonucleic acid (RNA). DNA is the genetic material found in all living organisms and is found in the nucleus of eukaryotes and in the chloroplasts and mitochondria. In prokaryotes, the DNA is not enclosed in a membranous envelope.

The other type of nucleic acid, RNA, is mostly involved in protein synthesis. Just like in DNA, RNA is made of monomers called nucleotides. Each nucleotide is made up of three components: a nitrogenous base, a pentose (five-carbon) sugar called ribose, and a phosphate group. Each nitrogenous base in a nucleotide is attached to a sugar molecule, which is attached to one or more phosphate groups.

In RNA, the nitrogenous bases vary slightly from those of DNA. Adenine (A), guanine (G), and cytosine (C) are present, but instead of thymine (T), a pyrimidine called uracil (U) pairs with adenine. RNA is a single stranded molecule, compared to the double helix of DNA.

The DNA molecules never leave the nucleus but instead use an intermediary to communicate with the rest of the cell. This intermediary is the messenger RNA (mRNA). When proteins need to be made, the mRNA enters the nucleus and attaches itself to one of the DNA strands. Being complementary, the sequence of nitrogen bases of the RNA is opposite that of the DNA. This is called transcription. For example, if the DNA strand reads TCCAAGTC, then the mRNA strand would read AGGUUCAG. The mRNA then carries the code out of the nucleus to organelles called ribosomes for the assembly of proteins.

Once the mRNA has reached the ribosomes, they do not read the instructions directly. Instead, another type of RNA called transfer RNA (tRNA) needs to translate the information from the mRNA into a usable form. The tRNA attaches to the mRNA, but with the opposite base pairings. It then reads the sequence in sets of three bases called codons. Each possible three letter arrangement of A,C,U,G (e.g., AAA, AAU, GGC, etc) is a specific instruction, and the correspondence of these instructions and the amino acids is known as the “genetic code.” Though exceptions to or variations on the code exist, the standard genetic code holds true in most organisms.

The ribosome acts like a giant clamp, holding all of the players in position, and facilitating both the pairing of bases between the messenger and transfer RNAs, and the chemical bonding between the amino acids. The ribosome has special subunits known as ribosomal RNAs (rRNA) because they function in the ribosome. These subunits do not carry instructions for making a specific proteins (i.e., they are not messenger RNAs) but instead are an integral part of the ribosome machinery that is used to make proteins from mRNAs. The making of proteins by reading instructions in mRNA is generally known as ” translation.”

History of RNA biology

Numerous key discoveries in biology have emerged from studies of RNA (ribonucleic acid), including seminal work in the fields of biochemistry, genetics, microbiology, molecular biology, molecular evolution and structural biology. As of 2010, 30 scientists have been awarded Nobel Prizes for experimental work that includes studies of RNA. Specific discoveries of high biological significance are discussed in this article.

For related information, see the articles on History of Molecular Biology and History of Genetics. For background information, see the articles on RNA and nucleic acid.

Types of RNA (Ribonucleic Acid) | Biochemistry

There are many types of RNAs, but three types of it are described here: 1. Ribosomal RNA (rRNA) 2. Messenger RNA (mRNA) 3. Transfer RNA (tRNA).

Type # 1. The Ribosomal RNA (rRNA):

The non-genetic RNAs are synthesized on the DNA template and are present in the nucleolus and cytoplasm. Therefore, the base sequences of rRNA and part of DNA where they are synthesized are complementary. In prokaryotes rRNA is formed on a part of DNA called ribosomal DNA, while in eukaryotes these are formed in nucleolus containing the nuclear DNA.

The rRNAs are found in ribosomes and accounts for 40-60% of dry weight. In general, it represents about 80% of total RNA of the cell. The ribosome consists of proteins and RNA. The ribosomes are of different types such as 8OS (found in eukaryotes) and 55S (found in mitochondria of vertebrates).

The 70S ribosomes of prokaryotes are made up of two subunits, 5OS and 30S. The SOS subunit contains 23S and 5S rRNA, whereas the 30S subunit consists of 16S rRNA.

The 8OS ribosome consists of 60S and 40S subunit. The rRNA types in both the subunits of plants differ from that of animals (Table 5.6).

The rRNA is a single stranded molecule which is twisted at certain points to form helical regions. In the helical region most of the base pairs are complementary and linked by hydrogen bonds. The uncoiled single stranded regions lack the complementary bases. Therefore, in rRNA the ratio of purine: pyrimidine is not equal. The rRNA exists in a living cell for about two generations.

Type # 2. The Messenger RNA (mRNA):

The mRNA is transcribed on the DNA template and, therefore, carries the genetic informa­tion of DNA. For the first time, Francis Jacob and Jacques Monod (1961) proposed the name mRNA for bearing the transcripts of DNA for protein synthesis on ribosomes.

The total population of mRNA in a cell varies from 5 to 10% of the total cellular RNA because the species of mRNA are short lived as these are broken into ribonucleotides by the enzyme ribonuclease. In E.coli some of the mRNAs remain alive only for about two minutes. Therefore, the cell does not contain high amount of mRNA at a time. In contrast, the mRNAs of eukaryotes are metabolically stable.

The size of mRNA varies. The smallest protein contains about 50 amino acids (50 × 3=150 nucleotides needed for monocistronic mRNA mol­ecules). Typically protein has 300-600 amino acids (900- 1,800 nucleotide long mRNA). In prokaryotes the polycistronic mRNA is more common than monocistronic mRNA and con­tains 3000-8000 nucleotides. Polycistronic mRNA contains usually 10 bases long intercistronic sequences called spacers.

The sedimentation coefficient of mRNA is 8S and average molecular weight ranges from 500,000 to 1,00,000. Since they represent a gene, their length and molecular weight change because a gene contains 100 to 1,500 nucleotides. The mRNAs are transcribed by genes, hence individual mRNA represents a single gene.

Therefore, in a cell there will be as much mRNAs as genes, and every mRNA differs from each other. Taylor (1979) has reviewed the isolation of eukaryotic mRNAs. Kozak (1983) has given a comparative account of initiation of protein synthesis in prokaryotes, eukaryotes and the organelles.

Initiation of synthesis of first polypeptide chain of a polycistronic mRNA may begin hundreds of nucleotides from the 5′ end. The section of non-translated RNA before coding region is called leader. Un-translated sequences are usually formed at both 5′ and 3′ ends.

As the mRNAs always remain in single stranded form, it may disrupt the biological activity after being coiled. However, the coils lack complementary bases. Kozak (1991) has discussed the structural features in eukaryotic mRNAs that modulate the initiation of translation.

The structure of prokaryotic and eukaryotic mRNA is shown in Fig 5.12 (A-C) and discussed below:

In most of the eukaryotes and animal viruses, 5′ end of mRNA contains a cap which is formed after methylation of any of four nucleotides. For example, an mRNA contains m7G (5′) ppp (5′)N where m7G is the methylguanosine and (5′)ppp(5′) represents a 5-5′ triphosphate linked to a base (N) at 5′ end. The mRNA binds to ribosome with the help of this cap. Therefore, it governs protein synthesis.

The bacterial mRNA does not contain 5′ cap. Instead they contain a specific ribosome binding site about six nucleotide long which occurs at several places in the mRNA molecules. These are located at 4 nucleotide upstream from AUC. In bacterial mRNA there may be multiple ribosome binding sites called Shine- Dalgarno sequences in the interior of an mRNA chain, each resulting in synthesis of a different protein.

(ii) The Non-coding Regions:

There are two non-coding regions first followed by the cap and the second followed by the termination codon. The non-coding region (NCI) is about 10-100 nucleotides long and rich in A and G residues, whereas the NC2 is 50-150 nucleotides long and contains an AAUAAA residues. Both the non-coding regions do not translate protein.

(iii) The Initiation Codon:

Both in prokaryotes and eukaryotes the initiation codon (AUG) is present which starts protein synthesis. Bacterial ribosomes, unlike the eukaryotic ribosomes, directly bind to start codons in the interior of mRNA to initiate protein synthesis.

(iv) The Coding Region:

It is the most important region of mRNA which is about 1,500 nucleotides long. This region translates a long chain of protein after attaching with several ribosomes. The combination of mRNA strand with several ribosomes is called polyribosome.

Therefore, the bacterial mRNAs are commonly called polycistronic mRNA i.e. they encode multiple proteins that are separately translated from the same mRNA molecule. The eukaryotic mRNAs are typically monocistronic i.e. only one species of polypeptide chain is translated per mRNA molecule.

(v) The Termination Codon:

The termination codon is required to give the signal to stop protein synthesis. In eukaryotes the termination codons are UAA, UAG or UGA that terminates the translation process i.e. the process of protein synthesis.

(vi) The Poly (A) Sequence:

The NC2 is followed by poly (A) sequence in the eukaryotic mRNA. The prokaryotic mRNAs lack poly (A). The polyadenylate or poly (A) sequences of 200- 250 nucleotides are present at 3’OH end of mRNA. Poly (A) sequences are added when mRNA is present inside the nucleus.The function of poly (A) sequence in translation is unknown.

Type # 3. The Transfer RNA (tRNA) or Soluble RNA (sRNA):

Twenty different amino acids required for protein synthesis are present in cytoplasm. Before joining an appropriate amino acid together to form protein, they are activated by attaching to the RNA. Requirement of energy for activation is met from ATP.

The RNA which is capable to transfer an amino acid from amino acid pool, possesses capacity to combine with only one amino acid in the presence of an enzyme, aminoacyl tRNA synthetase, and recognises the codon of mRNA, is called tRNA or sRNA.

For each amino acid there is different tRNA. It is likely that 20 different tRNAs are present in cytoplasm. However in several cases more than one type of tRNA for each amino acid is present. Therefore, there are more tRNAs than the amino acids. For example, about 100 types of tRNAs are found in bacterial cell.

The mRNA, contain codes of each of three nucleotides called codon which specifies a single amino acid. The tRNA molecules read the coded message on mRNA. Therefore, the tRNA molecules act as interpreter of genetic code.

The tRNA is dissolved in cytoplasm and is too small to be precipitated even at 1,00,000 g. Its molecular weight ranges from 25,000 to 30,000 D and sedimentation coefficient is 3.85. It accounts for 10-20% of the total cytoplasmic RNA. These are synthesized in the nucleus on a DNA template by only 0.025% of total DNA at the end of cleavage stage.

As the tRNA synthesis is over on DNA template, a part of ribonucleotide (5’CCA3′) is added to the 3′ end of each molecule regardless of amino acid affinity, by an enzyme tRNA phosphorylase. It is the special feature of tRNA as compared to mRNA and rRNA.

The tRNA molecules contain about 70-93% nucleotides arranged in a single strand at 5 → 3′ ends. This sstRNA forms dou­ble strands at certain regions with a single stranded loop. The 3′ end terminates with – CCA sequence and the 5′ end with G or C.

In addition to bases A, G, C and U present in tRNA, certain unusual bases are also found. These unusual bases are absent in other RNAs. The unusual bases are formed by specific chemical modification such as addition of methyl (-CH3) group to form 3-methyl cytosine or 1-methylguanosine, deamination of adenosine to inosine, reduction of uracil to dihydrouracil or rearrangement of uracil into pseudo uracil.

The other unusual bases are methyl guanine (Gme), dimethyl guanine (Gme2), methyl cytosine (Cme), ribothymine (T), pseudouridine (Ѱ), dihydrouridine (DHU, H2U, U2), inosine (I) and methylinosine (Ime).

Most of the bases pair according to Watson and Crick’s model but unusual bases do not because of bringing about changes due to substitution or alterations in those positions that take part in hydrogen bonding. The unusual bases protect the tRNA molecules from break down by RNAase. Consequently several non-base paired loops are formed in tRNA.

Clover Leaf Model of tRNA:

For the first time R. Holley (1968) prepared the clover leaf model for yeast tRNA alanine (tRNA ala ) which includes several known functions of tRNA. This model has been well accepted.

A typical clover leaf model is shown in Fig. 5.13 which reveals the following features:

(i) The single polynucleotide chain of all the tRNA molecule is folded upon itself to form five arms e.g. acceptor arm, DHU arm, anticodon arm, variable arm and T|/C arm. An arm consists of a stem and a loop. Except the acceptor arm, the other arms consist of their respective stem and loop.

(ii) The acceptor stem consists of 7 base pairs and 4 unpaired bases, the unpaired bases contain a three -CCA bases and a forth variable purine (A or G) at 3′ end or polynucleotide chain. The last residue, adenylic acid (A) acts as amino acid attachment site. The 5′ end of tRNA contains either (G) or (C).

(iii) The DHU (dihydrouridine) loop constitutes 7-12 unpaired bases, and acts as the site for recognition of amino acid activating enzyme aminoacyl tRNA synthetase. It consists of a total of 15-18 nucleotides (3-4 base pairs and 7-11 unpaired bases) in the loop. It has two variable regions a and P on both sides of guanine residues. These two regions contain 1-3 nucleotides, often pyrimidines.

(iv) All the tRNA molecules contain different nucleotide triplet codons on anticodon loop. It is also called anticodon or codon recognition site. It is complementary to the corresponding triplet codon of the mRNA molecule.

The anticodon stem consists of 5 base pairs, and the anticodon loop contains 7 unpaired nucleotides. The middle three nucleotides act as anticodon which identify three complementary bases of mRNA molecule. There is a hyper modified purine (HPu) on 3′ side chain of anticodon.

(v) The tRNA also possesses a TѰC arm that consists of a stem of 5 base pairs and a loop of 7 unpaired bases including pseudouridine. The TΨC loop consists of a TΨC sequence at 5′ → 3′ direction. The TΨC arm has a ribosome recognition site and binds the tRNA molecules to the ribosome.

(vi) In some tRNAs with long chain, a variable arm of extra arm is present between the anticodon arm and TΨ arm. The variable arm may or may not contain a stem. The electron photomicrograph reveals a tertiary structure of tRNA where the different limbs are separately formed by the acceptor, TΨC and DHU arms and anticodon arm are visible (Fig. 5.14). These limbs formed by hydrogen bonds are found between bases and ribose-phosphate backbone, and between the residues of backbone.

The tRNA that initates protein synthesis is called initiator tRNA. The initator tRNA of eukaryotes differs from the prokaryotes. The tRNA specifies methionine as the starting amino acid in eukaryotic protein synthesis and N-formyl methionine in prokaryotes. Therefore, the two tRNAs specific to these two amino acids are methionyl tRNA (tRNA/-met). These two tRNAs differ from each other.

RNA biology provides the key to cell identity and health

A hairpin loop from a pre-mRNA. Highlighted are the nucleobases (green) and the ribose-phosphate backbone (blue). Note that this is a single strand of RNA that folds back upon itself. Credit: Vossman/ Wikipedia

Two papers in Genome Research by the FANTOM Consortium have provided new insights into the core regulatory networks governing cell types in different vertebrate species, and the role of RNA as regulators of cell function and identity.

The FANTOM Consortium was established at RIKEN two decades ago to go beyond genomics and examine RNA—known as the transcriptome. Understanding the transcriptome is crucial for further advances in biology because although the cells in our bodies share the same genomic DNA, their diversity is attributed to their RNA make up, with more than 400 types defined and many more thought to exist. Thus, understanding how RNA is expressed is a key for grasping how each cell type establishes its distinctive function, morphology, and behavior by activating specific transcriptional programs. Both studies published today were based on the CAGE technology that was developed at RIKEN to profile the transcriptome using next-generation sequencers.

The first study (Alam et al.) compares transcriptome data from matching primary cell types in human, mouse, rat, dog, and chicken. While the group found that the transcriptome measured by CAGE for the same cell type differed markedly between species, they identified a core regulatory network defining each cell type that is common between species. In general, the genes encoding products involved in RNA biology in the cell nucleus were found to be activated consistently in the same cell type regardless of the species. According to Michiel de Hoon, the corresponding author of the paper, "We identified genes acting within the nucleus whose usage was conserved for 100's of millions of years of evolution. On the other hand, genes that primarily act in communication between cells had diverged and were being used differently in different species, implying that the distinctive phenotype of each species is to a great extent due to the specific way that cells in an organism communicate with each other."

The second study (Ramilowski J., Yip CW., et al.), part of FANTOM 6—the latest edition of the project—looked at human long non-coding RNAs, which outnumber protein-coding genes in mammals but whose function is still poorly understood. The researchers selectively targeted nearly 300 long non-coding RNAs for suppression in human fibroblast cells using an automated robotics system, and combined live cell imaging with CAGE to observe how cells respond at both the cellular and the molecular level. Jay Shin, one of the corresponding authors of this study, emphasized that "it was critical to automate our efforts as much as possible to reduce biases in our experimental design, and to quickly identify and correct any that remained." Based on the analysis, over 25 percent of long non-coding RNAs were found to affect cell growth and morphology, as well as cell migration, which is important in cancer. Surprisingly, targeting different isoforms (variants) of the same long non-coding RNA led to profoundly different cellular and molecular phenotypes, giving rise to the enticing conjecture that each long non-coding RNA isoform produced by a cell might have its own specific regulatory function.

According to Jordan Ramilowski, one of the first authors of the study, "Deep CAGE profiling of the molecular state of the cells after suppression of each long non-coding RNA allowed us to perform a functional analysis of long non-coding RNAs at an unprecedented level, and provides a valuable resource for a detailed investigating and understanding of the RNA biology and its potential application to enhancing human health."

Piero Carninci commented that "although this is still a pilot project, the results show involvement of lncRNAs in a broad variety of cellular processes and functions, which makes the case for extension of these studies to a broader number of cells and lncRNAs. We are excited to see that these RNAs, often considered 'junk' when discovered some 15 years ago, are often proven to be functional. We also believe that that the nomenclature should shift from 'non-coding' to terminology that better reflects their role, such as 'regulatory RNAs' or 'structural RNAs'."

Yulong Song et al. Sense–antisense miRNA pairs constitute an elaborate reciprocal regulatory circuit, Genome Research (2020). DOI: 10.1101/gr.257121.119

RNA scientists identify many genes involved in neuron development

Neurons result from a highly complex and unique series of cell divisions. For example, in fruit flies, the process starts with stem cells that divide into mother cells (progenitor cells), that then divide into precursor cells that eventually become neurons.

A team of the University of Michigan (U-M), spearheaded by Nigel Michki, a graduate student, and Assistant Professor Dawen Cai in the departments of Biophysics (LS&A) and Cell and Developmental Biology at the Medical School, identified many genes that are important in fruit flies' neuron development, and that had never been described before in that context.

Since many genes are conserved across species such as between fruit flies (Drosophila), mice, and humans, what is learnt in flies can also serve as a model to better understand other species, including humans. "Now that we know which genes are involved in this form of neurogenesis in flies, we can look for them in other species and test for them. We work on a multitude of organisms at U-M and we've the potential to interrogate across organisms," explains Michki. "In my opinion, the work we did is one of the many pieces that will inform other work that will inform disease," adds Michki. "This is why we do foundational research like this one."

Flies are also commonly used in many different types of research that might benefit from having a more comprehensive list of the fly genes with their associated roles in neuron cell development.

The discovery

Neurons are made from stem cells that massively multiply before becoming neurons. In the human brain, the process is extremely complex, involving billions of cells. In the fly brain, the process is much simpler, with around 200 stem cells for the entire brain. The smaller scale allows for a fine analysis of the neuronal cell division process from start to finish.

In flies, when the stem cell divides, it yields another stem cell and a progenitor cell. When this last one divides, it makes a so-called precursor cell that divides only once and gives rise to two neurons. Genes control this production process by telling the cells either to divide -- and which particular type of cell to produce -- or to stop dividing.

To this day, only a few of the genes that control this neuron development process have been identified and in this publication in Cell Reports, the scientists have characterized many more genes involved. Along the timeline of the neuron development process, the U-M team could precisely record which genes were involved and for how long.

In particular, at the progenitors' stage, the scientists identified three genes that are important at this stage for defining what 'kind' of neuron each progenitor will make these particular genes had never been described before in this context. They also validated previously known marker genes that are known to regulate the cell reproduction process.

When they applied their analysis technique to the other phases of the neuron development process, they also recorded the expression of additional genes. However, it is still unknown why these genes go up in expression at different steps of the neuron development process and what role they actually play in these different steps. "Now that many candidate genes are identified, we are investigating the roles they play in the neuron maturation and fate determination process," says Cai. "We are also excited to explore other developmental timepoints to illustrate the dynamic changes of the molecular landscape in the fly brain."

"This work provides rich information on how to program stem cell progeny into distinct neuron types as well as how to trans-differentiate non-neuronal cell types into neurons. These findings will have significant impact on the understanding of the normal brain development as well as on neuron regeneration medicine," adds Cheng-Yu Lee, a Professor from the U-M Life Sciences Institute who collaborated with the Cai Lab.

The techniques

This study is mostly based on high-throughput single-cell RNA-sequencing techniques. The scientists took single cells from fruit flies' brains and sequenced the RNA, generating hundreds of gigabytes of data in only one day. From the RNA sequences, they could determine the developmental stage of each neuron. "We now have a very good understanding of how this process goes at the RNA level," says Michki.

The team also used traditional microscope observations to localize where these different RNAs are being expressed in the brain. "Combining in silico analysis and in situ exploration not only validates the quality of our sequencing results, but also restores the spatial and temporal relationship of the candidate genes, which is lost in the single cell dissociation process," says Cai.

At the beginning of their study, the scientists analyzed the large data set with open-source software. Later, they developed a portal (MiCV) that eases the use of existing computer services and allows to test for repeatability. This portal can be utilized for cell and gene data analysis from a variety of organs and does not require computer programming experience. "Tools like MiCV can be very powerful for researchers who are doing this type of research for the first time and who want to quickly generate new hypotheses from their data," says Michki. "It saves a lot of time for data analysis, as well as expenses on consultant fees. The ultimate goal is to allow scientists to focus more on their research rather than on sometimes daunting data analysis tools." The MiCV tool is currently being commercialized.

RNA synthetic biology

RNA molecules play important and diverse regulatory roles in the cell by virtue of their interaction with other nucleic acids, proteins and small molecules. Inspired by this natural versatility, researchers have engineered RNA molecules with new biological functions. In the last two years efforts in synthetic biology have produced novel, synthetic RNA components capable of regulating gene expression in vivo largely in bacteria and yeast, setting the stage for scalable and programmable cellular behavior. Immediate challenges for this emerging field include determining how computational and directed-evolution techniques can be implemented to increase the complexity of engineered RNA systems, as well as determining how such systems can be broadly extended to mammalian systems. Further challenges include designing RNA molecules to be sensors of intracellular and environmental stimuli, probes to explore the behavior of biological networks and components of engineered cellular control systems.

Gene Regulation Network Modeling and Mechanism Analysis Based on MicroRNA-Disease Related Data

Haihong Liu , Fang Yan , in Systems Medicine , 2021

MicroRNA-Disease Related Data

MicroRNAs (miRNAs) are a family of small non-coding RNAs (

22 nt), which typically act as negative regulators of expression of target mRNA at post-transcriptional levels. They bind to the 3′untranslated regions (UTRs) of the target mRNA by base pairing, resulting in cleavage or translational inhibition of the target mRNA ( Ambros, 2004 Bartel, 2004 Meister and Tuschl, 2004 ). In some special cases, miRNAs may also function as positive regulators ( Jopling et al., 2005 Vasudevan et al., 2007 ). It is estimated that 1%–4% genes in the human genome are miRNAs and a single miRNA can regulate as many as 200 mRNAs and about one thirds of human gene can be targeted by miRNAs ( Esquela-Kerscher and Slack, 2006 Bandyopadhyay et al., 2010 ). Increasing evidences indicates that miRNAs play critical roles in many key biological processes, including the cell growth, tissue differentiation, cell proliferation and apoptosis, signal transduction, viral infection and so on. Therefore, dysregulation of miRNA may be the cause of various diseases ( Esquela-Kerscher and Slack, 2006 ).

Recent years, many researchers have demonstrated that a great number of miRNA-disease associations and revealed that the mechanisms of miRNAs concerned in diseases are very complicated. Mutation of miRNAs result in the dysfunction of downstream target genes, which can lead to the occur of cancer ( Xiao et al., 2012 ). Therefore, a comprehensive modeling and mechanism analysis of these miRNA-disease associations will provide us a clear understanding to dissect the pathways of the miRNA and disease associations, although our knowledge on miRNA-disease associations are far from perfects. However, studying for disease-miRNA associations by using the experimental method is not only costly, time-consuming and energy consumption ( Jiang et al., 2010 ). On the other hand, a large amount of biological data on miRNAs has been produced. Therefore, it is necessary to establish a reasonable model and develop powerful computational methods to predict potential disease-associated miRNAs on a large scale ( Chen et al., 2012 ). For instance, two publicly available and manually curated databases have been developed by Lu et al. (2008) and Jiang et al. (2009) to supply a extensive resource of experimentally verified miRNA-disease associations, i.e. Human MicroRNA Disease Database (HMDD) and miR2Disease.

3.4D: Types of RNA - Biology

RNA will consider papers in six categories: Reports, Articles, Bioinformatics, Hypotheses, Methods, and Letters to the Editor. Authors should designate a category upon submission of a manuscript. Reports document significant new results that lend themselves to succinct presentation (i.e., combined Results and Discussion) and can contain no more than four display items. Reports are evaluated using the same criteria as Articles preliminary observations that require further experimentation to support the major conclusions will not be accepted. There are no explicit length limitations to Articles a "normal" paper will occupy 6-8 printed pages (20-30 double-spaced manuscript pages) however, length is not a criterion for evaluation. Bioinformatics describe computer-based analyses of sequence data or new computer-based tools of interest to RNA scientists. Hypotheses outline novel concepts or new ways of integrating existing data. Methods are brief accounts of methodological advances or improvements that are of potential utility to a broad range of RNA researchers. Letters to the Editor are intended as a forum for raising or clarifying issues of specific interest to the RNA community.

In addition to the categories above, RNA publishes Reviews, Perspectives, Mini-Reviews, and Commentaries. Normally, these are by invitation, but presubmission inquiries to the Reviews Editor are welcome.

Submission of a paper implies that it has not been published previously and is not under consideration for publication elsewhere. Closely related papers that are in press elsewhere or that have been or will be submitted elsewhere must be included with the submitted manuscript. It is understood that researchers who submit papers to this journal are prepared to make available to qualified academic researchers materials needed to duplicate their research results (DNA, cell lines, antibodies, microbial strains, mouse lines, etc.). Authors should submit nucleic acid and protein sequences, NMR and X-ray crystallographic data to the appropriate database. Upon acceptance copyright must be assigned to the RNA Society.

The RNA Age: A Primer

Ruth Williams
May 11, 2017

Since nucleic acid research burst onto the scientific scene in the 1950s, DNA has been the star of the show. RNA&mdashwith the exception of forms such as ribosomal RNAs (rRNAs) and transfer RNAs (tRNAs)&mdashhas largely been considered the mere messenger between the all-important DNA and its protein products. Indeed, it was given that very name!

&ldquo[DNA] was thought of as the top of the information flow,&rdquo says biochemist Julia Salzman of Stanford University. &ldquoBut that view is starting to become more and more questioned in the community.&rdquo

In the last couple of decades, new areas of RNA research have been springing up left and right&mdasheach one offering surprising insights into this intriguing molecule. Along with booms in the fields of long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and RNA interference (RNAi), researchers have discovered and explored CRISPR RNAs, enhancer RNAs, and, most recently&mdashSalzman&rsquos specialty&mdashcircular RNAs.

3.4D: Types of RNA - Biology

This brain cell database contains a survey of biological features derived from single cell data, from both human and mouse. It is part of a multi-year project to create a census of cells in the mammalian brain.

The database contains electrophysiological, morphological, and transcriptomic data measured from individual cells, as well as models simulating cell activity. Thus far, data generation has focused on select areas of cerebral cortex, and thalamic neurons.

Browse electrophysiological response data and reconstructed neuronal morphologies using the Cell Feature Search tool. Single cell gene expression data is described on the RNA-Seq Data page.

Use the Allen Software Development Kit (SDK) to programmatically access and analyze raw data, and to run models.

Data can be downloaded by selecting individual experiments in the Cell Feature Search tool, by accessing transcriptomic RNA-Seq files, or through the Allen SDK or API.

Single Cells from Human Brain

Cells are acquired from donated ex vivo brain tissue dissected from temporal or frontal lobes, based on anatomical annotations described in The Allen Human Brain Reference Atlas. For electrophysiological and morphological analyses in the cortex, cells are selected based on soma shape and laminar location.

For transcriptomic analysis, individual layers of cortex are dissected, and neuronal nuclei are isolated. Laminar sampling is guided by the relative number of neurons present in each layer.

Single Cells from Mouse Brain

Cells are acquired from selected brain areas in the adult mouse. Cells are identified for isolation using transgenic mouse lines harboring fluorescent reporters, with drivers that allow enrichment for cell classes based on marker genes. For electrophysiological and morphological analyses, excitatory cells with layer-enriched distribution and inhibitory cells expressing canonical markers were isolated. Brain areas selected for analysis include subregions from visual cortex, motor cortex and anterior lateral motor cortex (ALM), in the secondary motor area (MOs). Subregions from visual cortex (secondary visual areas) are also included.

For transcriptomic analysis, regional and laminar dissections were performed on specimens from pan-neuronal, pan-excitatory, and pan-inhibitory transgenic lines, to sample comprehensively. Data from the lateral geniculate nucleus (LGd) is also included.


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