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What’s the choke point of scanning an entire genome? Is it purely computational? Imaging? Biological unknowns?

by exdsq 5y ago

jkingsman 5y ago
For IVF embryos, it's the small amount of genetic material which makes accurate sequencing difficult. For standard human whole genome sequencing (WGS), the fastest times are down to five hours[1] (although that is exceptional), for which the imaging was massively parallelized and it seems that the choke point was computational for that particular case (sequencing like this basically multiples the DNA, shreds all the copies, images each shred in a reasonably-parallel manner, and then uses longest-common-subsequence to put all the shreds back together digitally). Average WGS times for something a person can buy for a couple hundred dollars take a few weeks, and will usually be bottlenecked by logistics (mailing things, getting it to the lab, etc.) and then the imaging (a flow cell runs the fragments over an imaging device; parallelization is accomplished by running multiple flow cells at once). I might be slightly off on my terminology here but the idea is broadly correct, I think: Differing grades of sequencing are determined by the average depth of fragments for each base-pair -- e.g. 1x sequencing implies an average coverage of one fragment per base-pair, which could lead to mis-aligned or improperly joined samples. 30x-50x sequencing is pretty common for consumer grade WGS these days, which gives a higher number of fragments that allows you to weed out bad reads or incorrect joins of the sequence, though errors can still occur. This is usually sufficient for diploid (having two values for each base pair, one maternal and one paternal) humans, since it's important to determine if the basepair is heterozygous (different bases from each parent) or homozygous (same base from each parent). However, if you're doing cancer sequencing, a tumor may contain many many more different genes, so a massively deeper sequencing depth is required to ensure you have reasonable statistical certainty on what variations occur within the different genomes. Higher depth == more material == longer time to sequence since you have more material to image. Note that services like 23andMe are NOT doing whole genome sequencing; they are using specialized flow cells that only examine certain specific sites on the genome called single nucleotide polymorphisms[2], which are traits or indicators that are turned on or off by a single nucleotide, hence it being much cheaper and faster to run. [1]: https://med.stanford.edu/news/all-news/2022/01/dna-sequencing-technique.html#:~:text=A%20research%20effort%20led%20by,5%20hours%20and%202%20minutes https://med.stanford.edu/news/all-news/2022/01/dna-sequencin.... [2]: https://en.wikipedia.org/wiki/Single-nucleotide_polymorphism https://en.wikipedia.org/wiki/Single-nucleotide_polymorphism
- exdsq 5y ago
  Thanks for your response! So is it true to say every genome could be sequenced, assuming time and money isn’t an issue?
  - timy2shoes 5y ago
    Starting material is a huge problem. You need at least 50ng of DNA for an Illumina sequencing run, usually more if you want to sequence ultra deep, which you will need for whole genome sequencing. For PCR you need at least 0.1ng (usually higher) of DNA. But a single cell has about 80 pg of DNA. So you need to amplify the DNA several orders of magnitude before you can apply standard PCR. Several approaches can solve this problem, DOP-PCR, MDA, MALBAC. But each results in biased amplification, with differing biases with each method. Source: I worked on the computational modeling of this problem in grad school, https://academic.oup.com/bioinformatics/article/30/22/3159/2391301 https://academic.oup.com/bioinformatics/article/30/22/3159/2...
    - tux1968 5y ago
      The most interesting idea from the article, that was new to me, was using larger samples available from each parent, to augment and guide the analysis of the small amount of material available from the embryo. Obvious idea after you hear it, but very clever nonetheless.
  - dekhn 5y ago
    if you're asking whether we could sequence 7 billion people, yes, it would be absolutely possible. Obtaining samples would be harder than the sequencing. If you really took this seriously there would be only 3 sequencing sites in the world and they would be located close to the largest datacenters. Each sequence is about 100G data (the raw data file that's shipped around) so if you really wanted to keep all of that it's 700 exabytes, but since you're sequencing everybody, you can instead create a tree structure of deltas from references with additional nodes representing major haplotypes and other structure. This would be more like ~1M-1G/person, so 7 petabytes to 7 exabytes, well within the storage limits of a modern datacenter cluster. To go along with that storage, you'd also need ~1M fast CPUs and ~250K fast GPUs, plenty of RAM, and a really good privacy and security story. All of that could be formatted for large-scale analytics and the problem treated much like machine learning/data science problems in ads and other similar areas. If you're really serious, this is just a bulk buy for one of the data center providers and they would be happy to make a fixed profit margin contract to do this for you. I helped set up all the infrastructure to enable google to do this ~10 years ago (I got a patent on compressing DNA for storage) and now they're at the point of hosting this sort of service (terra bio). I could do everything I described above for $25B but there is absolutely no medical reason to do anything of this scale.
arrosenberg 5y ago
It's very doable, but we only know what a small amount of the genome is actually doing. Whole Exome testing hits the majority of the points people are interested in and is way less computationally expensive, since it's a fraction of the genome.
- exdsq 5y ago
  Okay interesting - so reading the genome is basically solved nowadays and it's understanding what it's actually doing where we're working atm?

What’s the choke point of scanning an entire genome? Is it purely computational? Imaging? Biological unknowns?

by exdsq 5y ago

What’s the choke point of scanning an entire genome? Is it purely computational? Imaging? Biological unknowns?

For IVF embryos, it's the small amount of genetic material which makes accurate sequencing difficult. For standard human whole genome sequencing (WGS), the fastest times are down to five hours[1] (although that is exceptional), for which the imaging was massively parallelized and it seems that the choke point was computational for that particular case (sequencing like this basically multiples the DNA, shreds all the copies, images each shred in a reasonably-parallel manner, and then uses longest-common-subsequence to put all the shreds back together digitally). Average WGS times for something a person can buy for a couple hundred dollars take a few weeks, and will usually be bottlenecked by logistics (mailing things, getting it to the lab, etc.) and then the imaging (a flow cell runs the fragments over an imaging device; parallelization is accomplished by running multiple flow cells at once). I might be slightly off on my terminology here but the idea is broadly correct, I think: Differing grades of sequencing are determined by the average depth of fragments for each base-pair -- e.g. 1x sequencing implies an average coverage of one fragment per base-pair, which could lead to mis-aligned or improperly joined samples. 30x-50x sequencing is pretty common for consumer grade WGS these days, which gives a higher number of fragments that allows you to weed out bad reads or incorrect joins of the sequence, though errors can still occur. This is usually sufficient for diploid (having two values for each base pair, one maternal and one paternal) humans, since it's important to determine if the basepair is heterozygous (different bases from each parent) or homozygous (same base from each parent). However, if you're doing cancer sequencing, a tumor may contain many many more different genes, so a massively deeper sequencing depth is required to ensure you have reasonable statistical certainty on what variations occur within the different genomes. Higher depth == more material == longer time to sequence since you have more material to image. Note that services like 23andMe are NOT doing whole genome sequencing; they are using specialized flow cells that only examine certain specific sites on the genome called single nucleotide polymorphisms[2], which are traits or indicators that are turned on or off by a single nucleotide, hence it being much cheaper and faster to run. [1]: https://med.stanford.edu/news/all-news/2022/01/dna-sequencing-technique.html#:~:text=A%20research%20effort%20led%20by,5%20hours%20and%202%20minutes https://med.stanford.edu/news/all-news/2022/01/dna-sequencin.... [2]: https://en.wikipedia.org/wiki/Single-nucleotide_polymorphism https://en.wikipedia.org/wiki/Single-nucleotide_polymorphism

exdsq 5y ago
Thanks for your response! So is it true to say every genome could be sequenced, assuming time and money isn’t an issue?
- timy2shoes 5y ago
  Starting material is a huge problem. You need at least 50ng of DNA for an Illumina sequencing run, usually more if you want to sequence ultra deep, which you will need for whole genome sequencing. For PCR you need at least 0.1ng (usually higher) of DNA. But a single cell has about 80 pg of DNA. So you need to amplify the DNA several orders of magnitude before you can apply standard PCR. Several approaches can solve this problem, DOP-PCR, MDA, MALBAC. But each results in biased amplification, with differing biases with each method. Source: I worked on the computational modeling of this problem in grad school, https://academic.oup.com/bioinformatics/article/30/22/3159/2391301 https://academic.oup.com/bioinformatics/article/30/22/3159/2...
  - tux1968 5y ago
    The most interesting idea from the article, that was new to me, was using larger samples available from each parent, to augment and guide the analysis of the small amount of material available from the embryo. Obvious idea after you hear it, but very clever nonetheless.
- dekhn 5y ago
  if you're asking whether we could sequence 7 billion people, yes, it would be absolutely possible. Obtaining samples would be harder than the sequencing. If you really took this seriously there would be only 3 sequencing sites in the world and they would be located close to the largest datacenters. Each sequence is about 100G data (the raw data file that's shipped around) so if you really wanted to keep all of that it's 700 exabytes, but since you're sequencing everybody, you can instead create a tree structure of deltas from references with additional nodes representing major haplotypes and other structure. This would be more like ~1M-1G/person, so 7 petabytes to 7 exabytes, well within the storage limits of a modern datacenter cluster. To go along with that storage, you'd also need ~1M fast CPUs and ~250K fast GPUs, plenty of RAM, and a really good privacy and security story. All of that could be formatted for large-scale analytics and the problem treated much like machine learning/data science problems in ads and other similar areas. If you're really serious, this is just a bulk buy for one of the data center providers and they would be happy to make a fixed profit margin contract to do this for you. I helped set up all the infrastructure to enable google to do this ~10 years ago (I got a patent on compressing DNA for storage) and now they're at the point of hosting this sort of service (terra bio). I could do everything I described above for $25B but there is absolutely no medical reason to do anything of this scale.

arrosenberg 5y ago

It's very doable, but we only know what a small amount of the genome is actually doing. Whole Exome testing hits the majority of the points people are interested in and is way less computationally expensive, since it's a fraction of the genome.

exdsq 5y ago
Okay interesting - so reading the genome is basically solved nowadays and it's understanding what it's actually doing where we're working atm?