Undergrad Student. The whole class did the same lab. Iβm just 1 of 22. Everyone does this every semester
I've had my genome sequenced and I've ended up down a bit of a rabbit hole on it. I've used some 3rd party software to look for specific markers. I'm pretty far down the rabbit hole hence I haven't slept at all last night. π I used 23 and me to create the raw data and promethazine to create the more in depth reports. If anyone has some tips and tricks, I'm all ears! Also interested to know of any deeper understanding you might have of how genes interoperate.
This is the best tl;dr I could make, original reduced by 86%. (I'm a bot)
> Most of the variants that affect gene expression are located within a few kilobases of the affected gene, and are dubbed cis-eQTLs.
> These variants are typically located in regions of genetic sequence that modify the regulation of only one of a person's two copies of the affected gene - for example in regulatory elements called promoters, enhancers and repressors.
> Many of the variants tested had previously been found to be associated with complex diseases and, interestingly, the consortium found that about half of these were associated with altered gene expression in some of the tissues that they tested.
> In the third and fourth papers, the consortium combined its GTEx data with other data sets to investigate how variants associated with altered gene expression can regulate two phenomena - RNA-editing processes3 and X-chromosome inactivation4.
> First, although the consortium identified almost 1 million genetic variants associated with differences in gene expression, it could be that most don't directly cause gene-expression differences.
> The ability to manipulate genetic variants using CRISPR-Cas9 genome editing and to analyse any subsequent changes in gene expression, as the authors do in a handful of cases, should also allow researchers to determine causal genetic variation.
Summary Source | FAQ | Feedback | Top keywords: gene^#1 expression^#2 variant^#3 genetic^#4 tissue^#5
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Researchers may have sequenced the βfinal unknownβ of the human genome
The new genome is a leap forward, researchers say, that was made possible by new DNA sequencing technologies developed by two private sector companies: Pacific Biosciences of Menlo Park, Calif., also known as PacBio, and Oxford Nanopore, of Oxford Science Park, U.K.. Their technologies for reading out DNA have very specific advantages over the tools that have long been considered researchersβ gold standards.
The work was possible because the Oxford Nanopore and PacBio technologies do not cut the DNA up into tiny puzzle pieces. The Oxford Nanopore technology runs a DNA molecule through a tiny hole, resulting in a very long sequence. The PacBio tech uses lasers to examine the same sequence of DNA again and again, creating a readout that can be highly accurate. Both are more expensive than the existing Illumina technology.
Seems pretty likely that if they were to find a new strain it would be here in the UK where 40% of the worldβs sequencing is done. How come the rest of the world acted like this is a UK problem and not a global one?
I think the two next big revolutions in disease discovery, understanding genes and ultimately curing disease will be machine learning (Artificial intelligence) and Population wide (big sample size) Whole Genome Sequencing (WGS) for that AI to work through.
It would become standard procedure that everyone from newborn babies (at the parents consent) up to the elderly (and everyone in between) would be WGS by their physician at the patients consent. The patient can refuse and opt out.
This WGS data would be paired and periodically updated with any known disease and ailments that were reported throughout that persons lifetime.
This WGS data (and any new diseases / ailments reported by the patient) would periodically be sent by a person's physician to a nationwide storage of other US citizens that consented and opted in. This stored data would use blockchain, encryption and the highest security features. This data would only be accessible to other physicians and AI that would be able to sort through it. It would be available to researchers (only if a patient consents), such as what occurs now with private companies that already do this.
WGS could be performed on a patient (at their consent) every decade (or two) of life to see how genes mutate and progress as a person ages.
This storage would be nationwide, large scale and be similar to how a patients medical records are stored and retrievable even if visiting another hospital.
The AI could parse through all of this WGS data (each gene) and attached diseases that is periodically updated to connect the dots on disease risk for prevention measures, disease discovery (if diagnosis eludes physicians) as well as gene targets for gene editing techniques (such as CRISPR) for disease prevention and disease cure.
Because of the large nationwide scale of this, this will lead to disease prevention, faster disease discovery, disease curing, and our understanding of how genes change from infancy to old age so that we as a society can prevent age related gene mutations and disease.
WGS are already being done at the research level but this is at an incredibly small scale (which impacts accuracy and findings). This research is prohibitively expensive and it leads to researchers basically having to re-invent the wheel (sequencing healthy and diseased patients) each time.
WGS and storage of this data is already done by private companies such as Dante Labs, Nebula Genomics, 23 and me etc.
With these FOR PROFI
... keep reading on reddit β‘
