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Posts Tagged ‘non-coding’


 

Author and Curator: Ritu Saxena, Ph.D.

A recent post by Dr. Margaret Baker entitled “Junk DNA codes for valuable miRNAs: non-coding DNA controls Diabetes” talks about how the ENCODE project is revealing new insights into the functions of non-coding region of the human genome previously labeled as “junk DNA”. MicroRNA or miRNA, which as stated by Dr. Baker, “are among the non-gene encoding sequences in the genome and have been shown to play a major post-transcriptional role in expression of multiple genes.”

The post has touched upon several aspects of miRNA including origin, function, and mechanism of action. This commentary is an extension of Dr. Baker’s post, expanding upon the mechanism of action of miRNAs along with their role in potential disease therapy.

microRNA: Revisiting the past

MicroRNA were not discovered long back, infact, it was in 1998 when the presence of the non-coding RNAs that could be involved in switching ‘on’ and ‘off’ of certain genes. In the last decade, 2006 Nobel Prize for medicine or physiology was awarded to scientists Andrew Fire and Craig Mello for their discovery of this new role of RNA molecules.

A breakthrough research was published in the September 2010 issue of Nature journal, stating that mammalian microRNAs predominantly act by decreasing the levels of target mRNA. Mammalian microRNAs predominantly act to decrease target mRNA levels. miRNAs were initially thought to repress protein output without changes in the corresponding mRNA levels. Guo et al challenged the previous notion of ‘translational repression’ and concluded on the basis of their experimental results that ‘mRNA-destabilization’ scenario for the major part is responsible for the repression in protein expression via miRNAs. Authors utilized the method of ‘ribosome profiling’ to measure the overall effects of miRNA on protein production and then compared these to simultaneously measured effects on mRNA levels. Ribosome profiling prepares maps that exact positions of ribosomes on transcripts after nucleases chew upon the exposed part of transcripts that are not covered by ribosomes. MiR-1 and miR-155 were introduced into the HeLa-cell line. Both of these miRNAs are not  normally expressed in HeLa cells. Another miRNA used was mir-223 which is expressed in significant amounts in neutrophils. The reason for choosing the set of these miRNAs was that they had already been shown to repress protein levels via proteomics research. It was deciphered that miRNA-mediated repression was similar regardless of target expression level and further stated that “for both ectopic and endogenous miRNA regulatory interactions, lowered mRNA levels account for lowered mRNA levels accounted for most for most (>/=84%) of the decreased protein production.” These results show that changes in mRNA levels closely reflect the impact of miRNAs on gene expression and indicate that destabilization of target mRNAs is the predominant reason for reduced protein output.

Authors concluded that the discovery “will apply broadly to the vast majority of miRNA targeting interactions. If indeed general, this conclusion will be welcome news to biologists wanting to measure the ultimate impact of miRNAs on their direct regulatory targets.”

Since then and even before the paper was published, several other miRNAs and their roles have been discovered. Information on miRNAs has been consolidated in a database that can be accessed online at http://www.mirbase.org/

microRNA: From bench to bedside

Scientific community had speculated the role of non-coding RNAs in disease treatment right after their discovery. One such study demonstrating the utilization of microRNA for Cancer treatment was published in the September 2010 issue of the journal Nature Medicine. miR-380-5p represses p53 to control cellular survival and is associated with poor outcome inMYCN-amplified neuroblastoma

The p53 gene is known as a tumor suppressor gene and its inactivation has been associated in some cancers such as neuroblastoma. The study reported that microRNA-380 (miR-380) was able to repress the expression of p53 gene in cancer patients causing uninhibited cell survival and proliferation. The research group was able to decrease the tumor size in vivo in a mouse model of the neuroblastoma by delivering miR-380 antagonist. The researchers also observed that the inhibition of endogenous miR-380 in embryonic stem or neuroblastoma cells resulted in induction of p53, and extensive apoptotic cell death.

Thus, the success of miR antagonist for decreasing tumor size speaks of the effectiveness of miR as a potential therapeutic target for cancer treatment.

In conclusion, as stated by Dr. Baker in her post, “the miRNA data for tissues and specific cell types involved in disease pathology form a new approach to either detecting or possibly correcting gene (coding or non-coding) dysregulation. miRNA mimics and anti-miRNA agents are being developed as new therapeutic modalities.”

Reference:

Pharmaceutical Intelligence post, Author, Dr. Margaret Baker: Junk DNA codes for valuable miRNAs: non-coding DNA controls Diabetes

https://pharmaceuticalintelligence.com/2012/09/24/junk-dna-codes-for-valuable-mirnas/

 

Research articles: Mammalian microRNAs predominantly act to decrease target mRNA levels

miR-380-5p represses p53 to control cellular survival and is associated with poor outcome inMYCN-amplified neuroblastoma

Expert reviews- miRNA and Cancer treatment

 

News briefs: http://ygoy.com/2010/10/02/new-treatment-for-junk-dna-induced-cancers-discovered/

http://www.evolutionnews.org/2010/10/micrornas–once_dismissed_as_j038861.html

 

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ENCODE data reveals important information from Genome Wide Association Studies relevant to understanding complex genetic diseases

Author: Ritu Saxena, Ph.D.

Introduction

“The depth, quality, and diversity of the ENCODE data are unprecedented” is what was stated by John Stamatoyannopoulos, professor of genomic sciences at the University of Washington and one of the many principle investigators of ENCODE project. ENCODE (Encyclopedia of DNA elements), indeed, was an ambitious project launched as a pilot in 2003 and then expanded in 2007 for the whole genome analysis and identification of all the functional elements of the human genome. The findings were striking as they challenged the definition of “gene” and ‘the central dogma of genetics (Gene-mRNA-protein). Infact, the non-coding part that constitutes about 80% of the genome or the so-called “junk DNA” was found to contain elements crucial for gene regulation. The elements, in large part, include RNA transcripts that are not transcribed into proteins but might have a regulatory role. For detailed reading, refer to the findings published in the issue of Nature, The ENCODE Project Consortium Nature 489, 57–74 (2012) An integrated encyclopedia of DNA elements in the human genome

Key features of the data, as explained in the National Human Genome Research Institute website (National Human Genome Research Institute News feature), include comprehensive mapping of:

  • Protein-coding genes — Proteins are molecules made of amino acids linked together in a specific sequence; the amino acid sequence is encoded by the sequence of DNA subunits called nucleotides that make up genes.
  • Non-coding genes — Stretches of DNA that are read by the cell as if they were genes but do not encode proteins. These appear to help regulate the activity of the genome.
  • Chromatin structure features — Complex physical structures made from a combination of DNA and binding proteins that make up the contents of the nucleus and affects genome function.
  • Histone modifications — Histones are the proteins that make up the chromatin structures that help shape and control the genome. In addition, histone proteins can be physically modified by adding chemical groups, such as a methyl molecule, that further regulates genomic activity.
  • DNA methylation — Just like histones, methyl groups can be added to DNA itself in a process called DNA methylation. Chemically attaching methyl groups to DNA physically changes the ability of enzymes to reach the DNA and thus alters the gene expression pattern in cells. Methylation helps cells “remember what they are doing” or alter levels of gene expression, and it is a crucial part of normal development and cellular differentiation in higher organisms.
  • Transcription factor binding sites — Transcription factors are proteins that bind to specific DNA sequences, controlling the flow (or transcription) of genetic information from DNA to mRNA. Mapping the binding sites can help researchers understand how genomic activity is controlled.

How could ENCODE be helpful in the study of complex human diseases?

Complex diseases and Genome wide association studies (GWAS)

Coronary artery disease, type 2 diabetes and many forms of cancer are complex human diseases that have a significant genetic component. Unlike mendelian disorders that have defined loci, the genetic component of complex disorders lies in the form of genetic variations in the genome making an individual susceptible to these complex diseases.

Researchers have performed Genome-wide association studies (GWAS) of the human genome, leading to the identification of thousands of DNA variants that could be linked with complex traits and diseases. However, identifying the variants, referred to as SNPs (Single Nucleotide Polymorphisms), that actually contribute to the disease, and understanding how they exert influence on a disease has been more of a mystery.

How would ENCODE solve the puzzle?

The puzzle lies in interpreting how the SNPs found in the genome affect a person’s susceptibility to a particular trait or disease and what is the mechanism behind it. As identified in the GWAS, most variants that are associated with the phenotype of the trait or disease lie in the non-coding region of the genome. Infact, in more than 400 studies compiled in the GWAS catalog only a small minority of the trait/disease-associated SNPs occur in protein-coding regions; the large majority (89%) are in noncoding regions. These variants fall in the gene deserts that lie far from protein-coding region, similar to those where cis-regulatory modules (CRMs) are found. CRMs such as promoters and enhancers are a group of binding sites for transcription factors, and the presence of transcription factors bound to these sites is a good indicator of the potential regulatory regions.

The integrative analysis of ENCODE data has give important insights to the results of GWAS studies. Investigators have employed ENCODE data as an initial guide to discover regulatory regions in which genetic variation is affecting a complex trait. Additionally, ENCODE study when examined the SNPs from GWAS that were associated with the phenotype of the trait, found that these regions are enriched in DNase-sensitive regions i.e, lie in the function-associated DNA region of the genome as it could be bound by transcription factors affecting the regulation of gene expression. Thus, the project demonstrates that non-coding regions must be considered when interpreting GWAS results, and it provides a strong motivation for reinterpreting previous GWAS findings.

Using ENCODE Data to Interpret GWAS Results

ENCODE and predisposition to CANCER:

C-Myc, a proto-oncogene, codes for a transcripton factor, when expressed constitutively leads to uninhibited cell proliferation resulting in cancer. It has been observed that common variants within a ~1 Mb region upstream of c-Myc gene have been associated with cancers of the colon, prostate, and breast. Several SNPs have been reported in this region, that although affect the phenotype, lie in the distal cis-region of the MYC gene. Alignment of the ENCODE data in this region with the significant variants from the GWAS also reveals that key variants are found in the transcription factor occupied DNA segments mapped by this consortium. One variant rs698327, lies within a DNase hypersensitive site that is bound by several transcription factors, enhancer-associated protein p300, and contains histone modifications relative to enhancers (high H3K4me1, low H3K4me3). ENCODE data indicates that non-coding regions in the human chromosome 8q24 loci are associated with cancer and as observed in the case of c-myc gene, similar studies on cancer-related genes could help explain predisposition to cancer.

ENCODE and fetal hemoglobin expression:

Another example of the use of ENCODE data is that of gene regulation of fetal hemoglobin. Several regions were predicted via ENCODE that were involved in the regulation of fetal hemoglobin. It was found that these predicted regions are close to the SNPs in the BLC11A gene that is associated with persistent expression of fetal hemoglobin.

Future perspective

As evident from the above examples, the ENCODE data shows that genetic variants do affect regulated expression of a target gene. Recently, several research groups in the UK performed a large-scale GWAS study to determine the genetic predisposition to fracture risk. The collaborative effort, published in a recent issue of the PLoS journal, was made to identify genetic variants associated with cortical bone thickness (CBT) and bone mineral density (BMD) with data from more than 10,000 subjects. http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1002745 The study generated a wealth of data including the result – identification of SNPs in the WNT16 and its adjacent gene, FAM3C were found to be relevant to CBT and BMD. ENCODE data, in this case, could be helpful in interpreting more detailed information including determining additional SNPs, the regulatory information of the genes involved and much more. Thus, it could be concluded that ENCODE data could be immensely useful in interpreting associations between disease and DNA sequences that can vary from person to person.

Sources:

Research articles

An integrated encyclopedia of DNA elements in the human genome

A User’s Guide to the Encyclopedia of DNA Elements (ENCODE)

What does our genome encode?

Genome-wide Epigenetic Data Facilitate Understanding of Disease Susceptibility Association Studies

Genomics: ENCODE explained

ENCODE Project Writes Eulogy For Junk DNA

WNT16 Influences Bone Mineral Density, Cortical Bone Thickness, Bone Strength, and Osteoporotic Fracture Risk

 News articles

ENCODE project: In massive genome analysis new data suggests ‘gene’ redefinition

National Human Genome Research Institute News feature

Related posts

Expanding the Genetic Alphabet and linking the genome to the metabolome

Junk DNA codes for valuable miRNAs: non-coding DNA controls Diabetes

ENCODE Findings as Consortium

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