Tweet
I was wondering if anyone had an empirical evidence in the comparison between the TruSeq and Nexterra protocols? We have been considering switching over to the Epicentre products exclusively but lack any definitive evidence of performance. Does anyone have an argument either way?
-
-
First, Epicentre now is owned by Illumina, so no difference there.
Second, "Nextera" is a mixture of several component methodologies:
(1) "Tagmentation" (in vitro transposase action) is used instead of sonication or other methods of mechanical fragmentation.
(2) Dual indexes (one in each adapter) are deployed rather than the single indexes of TruSeq.
(3) At least for NexteraXT, "normalization" beads are used equalize all the libraries to be included in a single pool.
(4) The lower concentration of resulting library pools is compensated for by using a heat denaturation, rather than a base denaturation prior to clustering. This may be possible because the products come off the normalization beads as ssDNA.
We have not yet run any Nextera libraries. But the process does look streamlined -- especially for handling library construction for large numbers of samples (eg 96).
--
Phillip -
Also....Nextera is now sold by Illumina, not Epicentre. Epicentre stopped selling the Nextera version 1 kits On Dec 31, 2011, and the Version 2 is now sold exclusively through Illumina.Comment
-
Thanks but I was referring to sequencing performance? For example, sample coverage, anymore or less 5' or 3' bias, coverage of exons vs introns, coding vs non-coding genes?Comment
-
you will need to contact Illumina regarding these parameters; I understand that Illumina has improved performance specs.Comment
-
shearing differences
I'm told (but have no direct experience) that the "tagmentation" step, which uses enzymatic fragmentation via an engineered transposase, has some non-randomness that could potentially result in reduced coverage in certain areas. The transposase has some sequence specificity that you'd have to look up. But the sample prep sure is easy!Comment
-
As I understand it, that's correct...minor G-bias.Comment
-
Proteomics platforms are evolving rapidly, with advances in mass spectrometry and affinity-based approaches expanding what researchers can detect and at what scale. As the field moves toward deeper proteome coverage and clinical applications, scientists face an increasingly complex landscape of tools. This article will explore how researchers are navigating these choices to find the right platform for their work.
The systematic characterization of the human proteome has... -
Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
...07-09-2026, 11:10 AM -
Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.
There is no single reason why many patients don’t respond to treatment as expected. Cancer is...07-08-2026, 05:17 AM
Comment