Most of these are going to be Whole-genome sequencing of some model organism:
en.wikipedia.org/wiki/Whole_genome_sequencing#History lists them all. Basically th big "firsts" all happened in the 1990s and early 2000s.
DNA microarray by Ciro Santilli 37 Updated 2025-07-16
Can be seen as a cheap form of DNA sequencing that only test for a few hits. Some major applications:
Metagenomics by Ciro Santilli 37 Updated 2025-07-16
Experiments that involve sequencing bulk DNA found in a sample to determine what species are present, as opposed to sequencing just a single specific specimen. Examples of samples that are often used:
One related application which most people would not consider metagenomics, is that of finding circulating tumor DNA in blood to detect tumors.
RNA-Seq by Ciro Santilli 37 Updated 2025-07-16
Sequencing the DNA tells us what the organism can do. Sequencing the RNA tells us what the organism is actually doing at a given point in time. The problem is not killing the cell while doing that. Is it possible to just take a chunk of the cell to sequence without killing it maybe?
Illumina by Ciro Santilli 37 Updated 2025-07-16
The by far dominating DNA sequencing company of the late 2000's and 2010's due to having the smallest cost per base pair.
Illumina actually bought their 2010's dominating technology from a Cambridge company called Solexa.
To understand how Illumina's technology works basically, watch this video: Video 1. "Illumina Sequencing by Synthesis by Illumina (2016)".
Video 1.
Illumina Sequencing by Synthesis by Illumina (2016)
Source.
The key innovation of this method is the Bridge amplification step, which produces a large amount of identical DNA strands.
Bridge amplification by Ciro Santilli 37 Updated 2025-07-16
This is one of the the key innovations of the Illumina (originally Solexa) sequencing.
This step is genius because sequencing is basically a signal-to-noise problem, as you are trying to observe individual tiny nucleotides mixed with billions of other tiny nucleotides.
With bridge amplification, we group some of the nucleotides together, and multiply the signal millions of times for that part of the DNA.
Oxford Nanopore MinION by Ciro Santilli 37 Updated 2025-07-16
One of the sequencers made by Oxford Nanopore Technologies.
The device has had several updates since however, notably of the pore proteins which are present in the critical flow cell consumable.
Official documentation: nanoporetech.com/products/minion (archive)
Figure 5.
Oxford nanopore MinION flow cell package.
Source.
Figure 6.
Oxford nanopore MinION flow cell front.
Source.
Figure 7.
Oxford nanopore MinION flow cell back.
Source.
Figure 8.
Oxford nanopore MinION flow cell pipette loading.
Source.
Figure 9.
Oxford Nanopore MinION connected to a Mac via USB.
Source.
Video 1.
Oxford Nanopore MinION software channels pannel on Mac.
Source.
PuntSeq is a side project led by a few University of Cambridge PhDs that aims to determine which bacteria are present in the River Cam.
In July 2019, the PuntSeq team got together with the awesome Cambridge Biomakespace, an awesome biology makerspace open to all, to create a two day science outreach activity showing their procedures.
The data collected in this experiment, together with other collection sessions done by the organizers actually led to a publication on eLife: elifesciences.org/articles/61504 "Freshwater monitoring by nanopore sequencing" by Lara Urban et al. (2021), so it is awesome to see that were are actual being part of "real science".
Ciro knows nothing about biology, but since he is very curious about it, he jumped at this opportunity, and decided to document things as well as his limited knowledge would allow.
All participants chipped in some money to help cover the experiment's costs. Ciro suspects that this activity was done partially to help crowdfund the experiment, but it was a worthy investment!
The impressions you get from the experiment as a software engineer will be:
  • OMG, this is so labour intensive, why haven't they automated this
  • OMG, this is frightening, all the 8 hours of work I've just done are present in that tiny plastic tube
  • Amazing! Look at that apparatus! And the bio people are like: I've used this a million times, it's cheap and every lab has one, just work faster and don't break you piece of junk!
For those that know biology and just want to do the thing, see: Section "Protocols used".
The PuntSeq team uses an Oxford Nanopore MinION DNA sequencer made by Oxford Nanopore Technologies to sequence the 16S region of bacterial DNA, which is about 1500 nucleotides long.
This kind of "decode everything from the sample to see what species are present approach" is called "metagenomics".
This is how the MinION looks like: Figure 1. "Oxford Nanopore MinION top".
The 16S region codes for one of the RNA pieces that makes the bacterial ribosome.
Before sequencing the DNA, we will do a PCR with primers that fit just before and just after the 16S DNA, in well conserved regions expected to be present in all bacteria.
The PCR replicates only the DNA region between our two selected primers a gazillion times so that only those regions will actually get picked up by the sequencing step in practice.
Eukaryotes also have an analogous ribosome part, the 18S region, but the PCR primers are selected for targets around the 16S region which are only present in prokaryotes.
This way, we amplify only the 16S region of bacteria, excluding other parts of bacterial genome, and excluding eukaryotes entirely.
Despite coding such a fundamental piece of RNA, there is still surprisingly variability in the 16S region across different bacteria, and it is those differences will allow us to identify which bacteria are present in the river.
The variability exists because certain base pairs are not fundamental for the function of the 16S region. This variability happens mostly on RNA loops as opposed to stems, i.e. parts of the RNA that don't base pair with other RNA in the RNA secondary structure as shown at: Code 1. "RNA stem-loop structure".
                A-U
               /   \
A-U-C-G-A-U-C-G     C
| | | | | | | |     |
U-A-G-C-U-A-G-C     G
               \   /
                U-A
|             ||    |
+-------------++----+
    stem        loop
Code 1.
RNA stem-loop structure
.
This is how the 16S RNA secondary structure looks like in its full glory: Figure 5. "16S RNA secondary structure".
Since loops don't base pair, they are less crucial in the determination of the secondary structure of the RNA.
The variability is such that it is possible to identify individual species apart if full sequences are known with certainty.
With the experimental limitations of experiment however, we would only be able to obtain family or genus level breakdowns.

Pinned article: Introduction to the OurBigBook Project

Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
We have two killer features:
  1. topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculus
    Articles of different users are sorted by upvote within each article page. This feature is a bit like:
    • a Wikipedia where each user can have their own version of each article
    • a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
    This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
    Figure 1.
    Screenshot of the "Derivative" topic page
    . View it live at: ourbigbook.com/go/topic/derivative
  2. local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:
    This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
    Figure 2.
    You can publish local OurBigBook lightweight markup files to either https://OurBigBook.com or as a static website
    .
    Figure 3.
    Visual Studio Code extension installation
    .
    Figure 4.
    Visual Studio Code extension tree navigation
    .
    Figure 5.
    Web editor
    . You can also edit articles on the Web editor without installing anything locally.
    Video 3.
    Edit locally and publish demo
    . Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension.
    Video 4.
    OurBigBook Visual Studio Code extension editing and navigation demo
    . Source.
  3. https://raw.githubusercontent.com/ourbigbook/ourbigbook-media/master/feature/x/hilbert-space-arrow.png
  4. Infinitely deep tables of contents:
    Figure 6.
    Dynamic article tree with infinitely deep table of contents
    .
    Descendant pages can also show up as toplevel e.g.: ourbigbook.com/cirosantilli/chordate-subclade
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact