Multiomics uses multiple approaches to understand a single problem
layering various -omics on top of each other for a multidimensional view of human biology.
With this holistic approach, novel insights are uncovered.
Research is revolutionized.
Some of the biggest drivers I see that are encouraging
the adoption of multiomics assays
include the understanding that cell processes
are very tightly connected, even though they may be very different.
For example, the transcriptome, the proteome, the epigenome,
they're all connected and they communicate with each other.
When studying genetic diseases,
multiomics gives biological context to disease-causing genetic variants,
enabling the discovery of novel pathways and biomarkers.
I think the thing that is cool about Multiomics
in pushing research forward
is the fact that it gives you multiple views into the same problem.
So you are just looking at the same problem from different angles
or different layers for that matter, and it's like in reality,
the world happens in a multiomics setup,
it’s not just the transcriptome or proteome.
There were several discoveries we've made using a multiomics method.
One of those would be the mapping
of quantitative trait loci for African-Americans.
This had actually never been done specifically for African Americans.
and we were able to find genetic variants that regulate their genome,
but could not be found in other populations.
In cellular biology, multiomics provides a deeper analysis
at the single-cell level, giving a more complete picture
that can reveal profound insights about which cell types
are present, their functions, and interactions between them.
I think single cell -omics approaches are ideally suited to the study
of complex organs such as the kidney or the brain or others,
where there are not only a large number of distinct cell types,
but they vary in proportion by orders of magnitude.
There are many critically important cell types that only constitute
one or two percent of the whole and whose
transcriptomic signatures are lost and undetectable in bulk approaches.
Whereas in single cell transcriptomic approaches,
we detect them with ease.
Multiomics is helping cancer researchers identify new drug targets,
improve current therapies, discover novel biomarkers,
and diagnose and cure cancer earlier.
Multiomics can be incredibly useful in the context of clinical trials.
When you're developing a new therapy, it can be really important to identify the mechanism of action,
as well as the mechanism of resistance to that therapy in human patients.
Using a multiomic approach gives you the greatest resolution and the greatest granularity.
Being able to parse out these complex mechanisms
and really understand how that therapy can be made better in future trials.
Enhanced discovery power.
Deeper understanding.
A more holistic view.
Multiomics is revolutionizing research, revealing novel insights and making new discoveries possible.
If we as biologists can capture and intercept as many of those facets of cell biology as possible,
we can develop a more comprehensive understanding of cell biology by utilizing multiomics.
We most definitely have found things we would have missed had we not used a multiomics approach.
I think multiomics has been absolutely critical for many of the insights that we've been developing in collaboration with our partners.
One hundred percent I'm very excited about the things you could find by combining the -omics data sets.
The field is moving so quickly that if you try to wait for a time when it seems like it's mature,
it will already have moved on to the next great thing. So I really encourage everybody to just dive right in.
More to see.
More to understand.
More with multiomics.