Author and Reporter: Anamika Sarkar, Ph.D
Early in the month of September, Nature, published 30 research papers on the results found from the ambitious and one time felt risky project, named, ENCODE (Encyclopedia of DNA Elements). The results of ENCODE revealed that 80% of human genome is not “junk”, as thought before, rather act as regulatory domains for further signaling events.
When human genome was first sequenced, more than a decade ago, scientists were surprised with the low ratio of coding regions transcribing genes to the number of bases in human DNA. Out of 3 billion bases in human DNA scientists found only 21,000 genes. This unexpected finding led to few basic questions:
- Why do humans have so many base pairs?
- How highly regulated complex behaviors of biochemical, cellular and physiological processes can be translated to regulation at genetic levels?
ENCODE project results unveil our limited knowledge about human genome until now. Their results open up new ways of thinking human DNA and its functional domains. It also brings in huge challenges for both experimental developments and data driven computational approaches for better understanding and applications of these new findings.
To gain insight from large scale data and identifying key players from a large pool of data, Bioinformatics approaches will probably be the only way to move forward. This also means importance of developing new algorithms which will include the capability of including regulatory functions linking with gene regulation. Presently, most algorithms are targeted toward identifying genes and their connections in a linear fashion. However, regulatory domains and their functional activities might be non linear, something which will be revealed with many more experimental results in coming years.
The functional characteristics of human genome will also lead to better understanding of genetic differences between normal states and disease states. Moreover, with proper identification of functional characteristics of a particular gene regulation, drugs can be targeted with much more precision in future. However, to make success of such a complicated problem, it will require visionary design and execution of experiment and computational biology teams working together.
It is well recognized already that Bioinformatics approaches can hugely help in identifying key players in regulation of genes. However many times it is not easy to translate information at the genetic levels directly to cellular or physiological levels. Some of the main reasons are – a) the complex cross talks between proteins which lead to intracellular signaling events and b) highly non linear information sharing among receptors and ligands for extra cellular signaling processes. To achieve efficient understanding of the functional characteristics of non-coding regions of DNA in context with regulation of genes, an effort should be given to map the functional network of gene regulation to signaling pathways of protein networks. This will require development of experimental as well as computational approaches to capture genetic as well as proteomics analysis together. Furthermore, for better understanding of cellular and physiological decisions, mapping between regulations of genes and intracellular signaling pathways should be extended for dynamic analysis with time.
The extraordinary findings from ENCODE project pose many challenges in front for getting answers to many unknowns for next decade or so but also give solutions to some basic questions which have haunted scientific world for almost a decade.
Sources:
News and Views- ENCODE explained: http://www.nature.com/nature/journal/v489/n7414/full/489052a.html
News and Analysis – ENCODE Project writes Eulogy for Junk DNA : http://www.sciencemag.org/content/337/6099/1159.summary?sid=835cf304-a61f-45d5-8d77-ad44b454e448
ENCODE Project (Nature Article): http://www.nature.com/nature/journal/v489/n7414/full/nature11247.html
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Anamika,
Thank you for your post.
I will read and comment during the day.
Please connect to Your Groups on LinkedIn twitter and facebook
This is fabulous. I am quite certain that these processes are not linear, but it is simpler for us to view them that way. The Watson-Crick model has a linear arrangement of base pairs. But now there is serious reason to expand the alphabet, and there are synthetic nucleotides/nucleoside that van pair with a hydrophobic (not hydrogen bonding) attachment. We also don’t understand the d-orbital in key analytes allowing for multiple intermediates from several valence states. The handling of nonparametric algorithms has come far. Proteomis is the first step toward reaching the metabolic phase.
I like that comment.
Thank you Dr. Larry for your validation of my thought. I am trained to see our human body as the best machine with least redundant activities. Thus, non linearity is absolutely required to make the processes efficient. However, starting with linear processes has always led scientists to know more about the system, and then adding non linearity slowly allows scientists to know furthermore about the system. Else, it can become out of control very fast. I agree with you I do think there will be need for expanding the alphabets.Moreover, I think one should be careful to identify the degree of importance in regulatory functional activities as the set of alphabets increase.
Anamika,
This is a daring critical thinking evaluation of the the three sources with your own expression as of what the state of affairs are, may be in the future and WHAT is mostly needed to achieve progress. Thus, your post exemplify the excellence of your own thought process and a great ability to articulate it to the reader. Both as necessary and sufficient in most case to be positioned for planning the next breakthrough.
I would consider to suggest to you for your consideration to change the title of the post along the lines of:
The Unknown yet about Junk DNA: Mapping the functional network of gene regulation to signaling pathways of protein networks.
If you change the title, please reconnect to all your Groups.
Thank you for a great evaluation of the state of Affairs related to ENCODE.
Thanks Aviva for your comment. I think my article is a cautious warning to the future.
A decade ago, during the invent of human genome sequence and micro array technology and Bioinformatic algorithms, we (scientific world) missed the point that gene is the smallest machinery of cellular and physiological processes. It took another half a decade to identify the importance of new experimental techniques at protein or physiological levels.
Computational models need both inputs and validations to be able to successfully predict either dynamic processes or specific targets. Thus, I wanted to make a cautious point of view to bring attention to the state of art findings from ENCODE which can be used in much more efficient manner with collaborative efforts of different fields together and help us to identify better drug targets and better healthy life.
I see your point that the title might not be reflection of my point of view of the article. Hence, I am changing it to reflect more the content in the article.
Great I am posting it on my Groups with the new Title.
[…] Reveals from ENCODE project will invite high synergistic collaborations to discover specific target… […]
PUT IT IN CONTEXT OF CANCER CELL MOVEMENT
The contraction of skeletal muscle is triggered by nerve impulses, which stimulate the release of Ca2+ from the sarcoplasmic reticuluma specialized network of internal membranes, similar to the endoplasmic reticulum, that stores high concentrations of Ca2+ ions. The release of Ca2+ from the sarcoplasmic reticulum increases the concentration of Ca2+ in the cytosol from approximately 10-7 to 10-5 M. The increased Ca2+ concentration signals muscle contraction via the action of two accessory proteins bound to the actin filaments: tropomyosin and troponin (Figure 11.25). Tropomyosin is a fibrous protein that binds lengthwise along the groove of actin filaments. In striated muscle, each tropomyosin molecule is bound to troponin, which is a complex of three polypeptides: troponin C (Ca2+-binding), troponin I (inhibitory), and troponin T (tropomyosin-binding). When the concentration of Ca2+ is low, the complex of the troponins with tropomyosin blocks the interaction of actin and myosin, so the muscle does not contract. At high concentrations, Ca2+ binding to troponin C shifts the position of the complex, relieving this inhibition and allowing contraction to proceed.
Figure 11.25
Association of tropomyosin and troponins with actin filaments. (A) Tropomyosin binds lengthwise along actin filaments and, in striated muscle, is associated with a complex of three troponins: troponin I (TnI), troponin C (TnC), and troponin T (TnT). In (more ) Contractile Assemblies of Actin and Myosin in Nonmuscle Cells
Contractile assemblies of actin and myosin, resembling small-scale versions of muscle fibers, are present also in nonmuscle cells. As in muscle, the actin filaments in these contractile assemblies are interdigitated with bipolar filaments of myosin II, consisting of 15 to 20 myosin II molecules, which produce contraction by sliding the actin filaments relative to one another (Figure 11.26). The actin filaments in contractile bundles in nonmuscle cells are also associated with tropomyosin, which facilitates their interaction with myosin II, probably by competing with filamin for binding sites on actin.
Figure 11.26
Contractile assemblies in nonmuscle cells. Bipolar filaments of myosin II produce contraction by sliding actin filaments in opposite directions. Two examples of contractile assemblies in nonmuscle cells, stress fibers and adhesion belts, were discussed earlier with respect to attachment of the actin cytoskeleton to regions of cell-substrate and cell-cell contacts (see Figures 11.13 and 11.14). The contraction of stress fibers produces tension across the cell, allowing the cell to pull on a substrate (e.g., the extracellular matrix) to which it is anchored. The contraction of adhesion belts alters the shape of epithelial cell sheets: a process that is particularly important during embryonic development, when sheets of epithelial cells fold into structures such as tubes.
The most dramatic example of actin-myosin contraction in nonmuscle cells, however, is provided by cytokinesisthe division of a cell into two following mitosis (Figure 11.27). Toward the end of mitosis in animal cells, a contractile ring consisting of actin filaments and myosin II assembles just underneath the plasma membrane. Its contraction pulls the plasma membrane progressively inward, constricting the center of the cell and pinching it in two. Interestingly, the thickness of the contractile ring remains constant as it contracts, implying that actin filaments disassemble as contraction proceeds. The ring then disperses completely following cell division.
Figure 11.27
Cytokinesis. Following completion of mitosis (nuclear division), a contractile ring consisting of actin filaments and myosin II divides the cell in two.
http://www.ncbi.nlm.nih.gov/books/NBK9961/
This is good. I don’t recall seeing it in the original comment. I am very aware of the actin myosin troponin connection in heart and in skeletal muscle, and I did know about the nonmuscle work. I won’t deal with it now, and I have been working with Aviral now online for 2 hours.
I have had a considerable background from way back in atomic orbital theory, physical chemistry, organic chemistry, and the equilibrium necessary for cations and anions. Despite the calcium role in contraction, I would not discount hypomagnesemia in having a disease role because of the intracellular-extracellular connection. The description you pasted reminds me also of a lecture given a few years ago by the Nobel Laureate that year on the mechanism of cell division.
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Many thanks,Annette