Today, a press release announced a today announced a strategic alliance including a commercialization agreement and equity investment. Illumina will market, sell, distribute, and service BASE™ Technology products developed by Oxford Nanopore for DNA sequencing into the research and diagnostic markets on a worldwide basis.
Given Illuminas position in the market, this is a big leap forward for the commerzialization of nanopore sequencing.
In the new issue of Biotechniques, a paper by Maricic and Pääbo (login may be required) describes how a change to the standard 454 sequencing protocol can dramatically increase the size of the library of DNA that goes into the actual sequencing reaction.
The trick used is to replace the last step in the library preparation where single stranded DNA is released from streptavidin beads. The original 454 protocol employes NaOH denaturation for this step, but the researchers found that this procedure results in a loss of over 99% of the DNA. However, When they replaced the NaOH denaturation with a heat denaturation by incubation recovery increased to 98%.
These authors are coming from the ancient DNA community and have an obvious motivation for optimizing the DNA retrieval from scarce ancient biological material. However, these findings are equally important to other applications aimed at sequencing small volumes of biological material such as tumors and within-host sub-populations of pathogens.
Last update: November 25, 2009
We have elaborated on David Dooling’s original overview of some of the important metrics of the most prevalent High-Throughput Sequencing platforms.
| |
Roche |
Illumina |
ABI |
| Technology: |
454 |
Solexa |
SOLiD |
| Platform: |
Junior |
GS 20 |
FLX |
Ti |
GA |
GA II |
GA IIx |
1 |
2 |
3 |
| Reads: |
100 k |
500 k |
500 k |
1 M |
28 M |
100 M |
150 M |
40 M |
115 M |
320 M |
| Fragment |
| Read length: |
400 |
100 |
200 |
400 |
35 |
50 |
100 |
25 |
35 |
50 |
| Run time: |
12 hr |
6 hr |
7 hr |
9 hr |
3 d |
3 d |
4 d |
6 d |
5 d |
8 d |
| Images: |
? |
11 GB |
13 GB |
27 GB |
500 GB |
1.1 TB |
1.7 TB |
1.8 TB |
2.5 TB |
1.9 TB |
| PA Disk: |
? |
3 GB |
3 GB |
15 GB |
175 GB |
300 GB |
350 GB |
300 GB |
750 GB |
1200 GB |
| PA CPU: |
? |
10 hr |
140 hr |
220 hr |
100 hr |
70 hr |
100 hr |
NA |
NA |
NA |
| SRA: |
? |
500 MB |
1 GB |
4 GB |
30 GB |
50 GB |
75 GB |
100 GB |
140 GB |
600 GB |
| Fragment yield |
| Gigabases / run |
0.035 |
0.05 |
0.1 |
0.5 |
1 |
5 |
15 |
1 |
4 |
16 |
| Megabases / hour |
2.92 |
8.3 |
14.3 |
55.6 |
13.9 |
69.4 |
156.3 |
6.9 |
33.3 |
83.3 |
| Gigabases / week |
0.5 |
1.4 |
2.4 |
9.3 |
2.3 |
11.7 |
26.3 |
1.2 |
5.6 |
14 |
| Paired-end |
| Read length: |
|
|
200 |
400 |
2×35 |
2×50 |
2×100 |
2×25 |
2×35 |
2×50 |
| Insert: |
|
|
3.5 kb |
3.5 kb |
200 b |
200 b |
200 b |
3 kb |
3 kb |
3 kb |
| Run time: |
|
|
7 hr |
9 hr |
6 d |
10 d |
10 d |
12 d |
10 d |
16 d |
| Images: |
|
|
13 GB |
30 GB |
1 TB |
2.2 TB |
3.4 TB |
3.6 TB |
5 TB |
3.8 TB |
| PA Disk: |
|
|
3 GB |
15 GB |
350 GB |
500 GB |
600 GB |
600 GB |
1.5 TB |
2.4 TB |
| PA CPU: |
|
|
140 hr |
220 |
160 hr |
120 hr |
170 hr |
NA |
NA |
NA |
| SRA: |
|
|
1 GB |
4 GB |
60 GB |
100 GB |
150 GB |
200 GB |
280 GB |
1200 GB |
| Paired-end yield |
| Gigabases / run |
|
|
0.1 |
0.5 |
2 |
9 |
30 |
2 |
8 |
32 |
| Megabases / hour |
|
|
14.3 |
55.6 |
13.9 |
37.5 |
125 |
13.9 |
66.7 |
166.7 |
| Gigabases / week |
|
|
2.4 |
9.3 |
2.3 |
6.3 |
21 |
2.3 |
11.2 |
28 |
This overview is a work in progress and will be updated as new and relevant technologies emerge.
You can find the original table here. As the original compilation, this work is openly available through an Attribution-Share Alike 3.0 Creative Commons license.
It can be quite overwhelming to keep oneself updated with the newest technological innovations in the field of High-Throughput Sequencing. Which machines can do what - for example do you know which machines that can handle paired end data? Or has the highest yield per hour?
That is why we have elaborated on David Dooling’s excellent overview of some of the important metrics of the most prevalent High-Throughput Sequencing platforms.
You can find the published overview here:
Overview of High-Throughput Sequencing platforms
The original table is here
We have been fortunate to gain a new and very skilled employee in Singapore, Mr Henry Wang, which means that we now have a native Chinese speaker in CLC bio. In this video Henry uses his mother tongue to explains how to assemble data from two different NGS platforms, Illumina Genome Analyzer and 454, in one run. The data set contains both paired-ends and single reads.
