Hi Users,
Can anyone suggest what is the application of Hi-C?
How it is useful?
In what kind of research work will it be useful?
Thanks
Hi Users,
Can anyone suggest what is the application of Hi-C?
How it is useful?
In what kind of research work will it be useful?
Thanks
Do some research on pubmed :http://www.ncbi.nlm.nih.gov/pubmed/25448293
Hi-C is a chromosome conformation capture technology whose aim is to give an idea on how chromosomes fold and associated with each other. For example, knowing the conformation of a chromosome allows you to understand the relation of genes and enhancers. Looking into the literature you will see a large array of applications. Hi-C has been instrumental in the characterisation of the so called Topologically associating domains (TADs) that are stable building blocks (apparently they are folding units) present in all eukaryotic studied so far.
I personally think that Hi-C together with many other conformation capture methods, are disruptive technologies that are quickly changing our understanding of genetics by allowing us to move from the 1D analysis to 3D interpretations.
First, I would recommend to go through "xC" (chromosomal conformation capture) technologies: http://www.ncbi.nlm.nih.gov/pubmed/19588093. Actually in early times people were doing FISH analysis and counting the number of cells that have two marked regions in close proximity to see if given chromosomal regions are in contact.
HiC basically gives you a map of contacts between all pairs of genomic loci. Todays resolution allows you to split the genome into 0.5-1Mb regions and to get an estimate of contact frequency between a pair of regions on the same/different chromosomes.
HiC is most useful in fundamental research and can help to link epigenetics with physical chromatin interactions and positioning in the nucleus. It can also be used to see how the DNA is folded during various cell cycle stages, etc. This approach could also be used to probe if spatial positioning matters when dealing with "fragile" (frequently mutated) DNA regions, therefore it is important in cancer research.
"Today's resolution allows you to split the genome into 0.5-1Mb regions and to get an estimate of contact frequency between a pair of regions on the same/different chromosomes."
This statement is true for mammals, but much higher resolution (and deeper insight) can be obtained from Hi-C in Drosophila and yeast. See http://www.sciencedirect.com/science/article/pii/S0092867412000165 & http://www.nature.com/nature/journal/v465/n7296/full/nature08973.html?free=2
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Disruptive???
I checked if I was using the term right and I think I am. In Wikipedia disruptive innovation is associated to markets and how a new technology disrupts and existing market. They way I see it, chromosome capture technologies are also disruptive with respect to current research by forcing the need to incorporate new findings into established research and opening a new field of investigation.
It is quite a complex technology and while HiC contact maps look awesome. However, when summarized appropriately, they are highly correlated with chromatin features, replication timing, etc. As for me right now HiC data is no that breakthrough when viewed together with a high number of ChIP, H3K.., etc tracks. I mean, it is not that certain that the effort required to perform a solid HiC experiment worth a set of well-performed ChIP-seq for the majority of epigenetic studies.
I disagree. Without conformation capture technologies you can hardly get an idea of how chromosomes fold and how such structure affects gene regulation. Chromatin states do correlate with features observed on Hi-C but can hardly inform you about the 3D structure.
Sure, one can get lots of important information, e.g. does a given enhancer element really interacts with loci of interest. But I was talking about practical point, if it is a disruptive innovation, than it should add some essential data to become a routine analysis tool in cancer progression studies, etc. Of course this looks like a sort of correlation debate vs causality. I'm really excited to see some examples with a direct application of HiC in studying genetic disorders.