Every person’s DNA contains millions of genetic variants. Most of these differences do not directly change the structure of a protein or cause a disease. Instead, many of them influence something more subtle: when, where and how strongly a gene is activated.

Understanding these regulatory effects is one of the central challenges of modern genomics.

A landmark study published in Science by the Genotype-Tissue Expression Consortium, commonly known as GTEx, created one of the most extensive maps of how genetic variation affects gene activity across the human body.

The researchers analysed more than 15,000 RNA-sequencing samples from 49 tissues collected from 838 donors. By combining these transcriptomic measurements with whole-genome sequencing, they investigated how genetic differences influence gene expression and RNA processing in tissues including the brain, heart, liver, lungs, skin, skeletal muscle, adipose tissue and blood.

The result was a large public atlas connecting three fundamental elements of human biology:

Our genetic variants, the activity of our genes and the tissues in which that activity occurs.

This study forms part of the broader GTEx research programme to which researchers from the Institut de Recerca Sant Pau contributed. This scientific field is closely connected with the work now being developed at BASE4 Biosciences, where genomic, transcriptomic and clinical information are combined to obtain a more contextual view of human biology.

Having a gene does not mean that it is always active

Almost every cell in the human body contains essentially the same DNA.

However, a liver cell behaves very differently from a neuron, a muscle cell or an immune cell. This happens because each cell activates a different combination of genes according to its function.

This process is known as gene expression.

Gene expression determines which instructions contained in DNA are being used by a particular cell or tissue. When a gene is active, its information is generally copied into RNA. By measuring RNA, researchers can therefore observe which biological programmes are active at a given moment.

The complete collection of RNA molecules found in a sample is known as the transcriptome.

The genome is relatively stable. The transcriptome, however, is dynamic. It varies between tissues and can also change according to age, biological sex, health status, environmental exposure and other biological factors.

In simple terms:

The genome tells us which instructions are available.

The transcriptome shows which instructions are being used.

The tissue tells us where that biological activity is taking place.

The GTEx study brought these three dimensions together on an unprecedented scale.

Why do genetic variants matter?

Human genomes are extremely similar, but they are not identical.

At millions of positions in the DNA sequence, one person may carry a different genetic variant from another. Some variants have little or no measurable effect. Others can change the way genes operate.

A genetic variant may, for example:

Increase or reduce the activity of a gene.

Change the way RNA is processed.

Affect one tissue more strongly than another.

Influence several genes or biological mechanisms.

Contribute to a person’s susceptibility to a complex disease.

Many variants associated with disease are not located inside the protein-coding part of a gene. Instead, they are found in regulatory regions of the genome.

These regions act more like biological control systems. They help determine when a gene should be activated, in which cells and at what intensity.

This creates an important challenge.

A genetic association study may identify a region of the genome connected with diabetes, cardiovascular disease or another complex trait. But identifying the region does not automatically explain which gene is affected, in which tissue or through which biological mechanism.

The GTEx project was created to help bridge this gap.

What did the researchers analyse?

The study used the final version of the GTEx dataset, known as GTEx v8.

After quality control, the researchers examined 15,201 RNA-sequencing samples from 49 tissues or cell sources, all of which had sufficient data for genetic and transcriptomic analysis. The samples came from 838 post-mortem donors whose genomes had also been sequenced.

For every tissue, the researchers compared genetic variation with two important aspects of RNA biology.

The first was gene-expression level: how active a particular gene was.

The second was RNA splicing: the process through which cells can assemble RNA in different ways, allowing one gene to produce different molecular products.

The objective was not simply to create a list of active genes. It was to identify genetic variants that could help explain why gene expression and RNA processing differ between individuals and across tissues.

Genetic variation affects almost every gene

One of the study’s main conclusions was that detectable genetic regulatory effects could be found for almost all genes when enough tissues and samples were considered.

This does not mean that every gene is strongly affected by genetics or that genetic variation determines everything happening inside a cell.

It means that inherited differences between individuals can influence the activity or processing of a very large proportion of the human genome.

These effects are often described using the term expression quantitative trait locus, or eQTL.

An eQTL is a genetic variant associated with the expression level of a gene. People carrying different versions of that variant may show different levels of activity for the associated gene.

The study also analysed variants connected with differences in RNA splicing. These are known as splicing quantitative trait loci, or sQTLs.

Together, these regulatory associations provide a map of how differences in DNA can produce differences in biological activity.

The effect of a genetic variant depends on the tissue

One of the most important messages from GTEx is that genetic effects cannot always be understood without considering the tissue.

The same genetic variant may have:

A strong effect in the liver.

A weaker effect in adipose tissue.

No detectable effect in blood.

A different effect in a particular brain region.

Some regulatory mechanisms are shared across several tissues, while others are highly tissue-specific.

This makes biological sense. Different tissues perform different functions and contain different types of cells. A variant affecting a gene involved in liver metabolism may therefore have a very different impact from one influencing neuronal activity or immune function.

The study showed that tissue specificity is not a secondary detail. It is a fundamental part of how genetic regulation operates in the human body.

This has important consequences for biomedical research.

Blood is one of the most accessible biological samples and contains a large amount of valuable information. However, a signal measured in blood does not necessarily behave in the same way in the brain, heart, liver or skeletal muscle.

To interpret blood-derived molecular information properly, researchers need models capable of relating accessible signals to the tissues and biological pathways they may represent.

Cell types help explain differences between tissues

A tissue is not composed of a single type of cell.

The liver, skin, brain and adipose tissue each contain several cellular populations. The proportions of those cells can vary between people, biological conditions and samples.

The GTEx researchers found that cell-type composition is a key factor in understanding genetic regulation across tissues.

Two samples from the same tissue may show different gene-expression patterns partly because they contain different proportions of particular cell types.

This also helps explain why certain genetic effects appear to be shared across apparently different tissues. In some cases, the common effect may arise because those tissues contain a similar cell population in which the variant is active.

Therefore, interpreting a molecular signal requires more than identifying the tissue. Researchers must also consider the cells contributing to that signal.

This insight has become increasingly important as biomedical science moves towards single-cell and spatial technologies, which can distinguish biological activity with greater precision.

From genetic associations to biological mechanisms

Genome-wide association studies, or GWAS, have identified thousands of genetic regions connected with human traits and diseases.

These studies can reveal that a region of DNA is statistically associated with a condition, but they do not always identify the responsible gene or biological process.

The GTEx atlas helps interpret these findings.

By connecting disease-associated variants with changes in gene expression or RNA splicing, researchers can investigate:

Which gene may be affected by the variant.

In which tissue the effect is most relevant.

Whether the variant changes gene activity or RNA processing.

Which biological mechanism may connect the variant to the disease.

The study showed that genetic regulatory data can help explain a meaningful proportion of associations identified through GWAS. It also demonstrated that individual genes may be controlled by several independent genetic variants and that one regulatory variant can sometimes influence multiple biological traits.

This complexity is important.

Complex diseases are rarely explained by a single mutation or a single molecular pathway. They usually emerge from the interaction of many genetic, molecular, clinical and environmental factors.

GTEx provides a reference for studying part of that chain:

Genetic variation → gene regulation → tissue-specific biology → human traits and disease risk.

Why this matters for precision medicine

Traditional medicine often relies on population averages.

These averages are useful, but they cannot fully explain why two people with similar clinical characteristics may have different disease risks, biological responses or treatment outcomes.

The GTEx study demonstrates that genetic variation can influence the activity of genes throughout the human body—and that these effects depend heavily on tissue and cellular context.

This means that two people may carry different regulatory variants that influence:

How strongly a biological pathway is activated.

How an organ responds to stress or disease.

How a medicine is metabolised.

How immune or metabolic processes are regulated.

How genetic risk is translated into functional biology.

The study does not provide individual diagnoses or treatment recommendations. It is a foundational research resource.

However, it helps establish the scientific framework required for more personalised medicine: one in which genetic information is interpreted not in isolation, but according to its functional and tissue-specific consequences.

The scientific contribution from Sant Pau

The GTEx project was a large international effort involving hundreds of scientists and institutions.

Researchers from the Institut de Recerca Sant Pau participated in the wider body of GTEx research published in Science, alongside teams from the Centre for Genomic Regulation, the University of Barcelona and international research centres. The Sant Pau contribution was led by Dr José Manuel Soria, Head of the Genomics of Complex Diseases Unit at the Institut de Recerca Sant Pau and Scientific Director of BASE4 Biosciences.

Dr Soria and Ángel Martínez-Pérez, currently co-founder of BASE4 Biosciences, were named contributors to related GTEx research examining how gene expression differs across human tissues and biological contexts.

For scientific accuracy, the atlas described in this article was published under the authorship of the GTEx Consortium, with François Aguet, Kristin Ardlie and Tuuli Lappalainen listed among its corresponding scientific leaders. It should therefore be presented as an international consortium study rather than as research led exclusively by Sant Pau.

The relevance of the Sant Pau team lies in its participation in this wider programme of research and in helping advance the study of genetic regulation, complex diseases and tissue-specific biology.

How this scientific foundation connects with BASE4 Biosciences

The GTEx atlas reflects several of the principles behind the technology being developed at BASE4 Biosciences.

The first is that genetic information alone is not enough.

A DNA variant may indicate increased susceptibility to a disease or biological condition, but it does not necessarily reveal whether the associated mechanism is currently active.

At BASE4, genomic information is therefore combined with transcriptomic and clinical data.

Genetics helps identify inherited predisposition. Transcriptomics provides a more dynamic view of current biological activity. Clinical and lifestyle information adds the context required to interpret those signals meaningfully.

The second shared principle is that biology is tissue-specific.

A molecular signal cannot always be interpreted in the same way across the entire body. A genetic or transcriptomic change may be relevant to one tissue while having a limited effect in another.

BASE4 uses computational models to analyse blood-derived molecular data and relate those signals to different tissues, biological pathways and health systems.

The objective is not to claim that a blood sample directly measures every organ. Instead, the platform aims to interpret accessible molecular information using tissue-aware models informed by large biological reference datasets and proprietary scientific development.

The third principle is that human biology is multidimensional.

Understanding an individual requires considering multiple layers simultaneously:

Genetic predisposition.

Current gene expression.

Tissue and pathway context.

Biological sex.

Age.

Clinical history.

Lifestyle and environmental factors.

Changes over time.

GTEx built a reference atlas showing how genetics influences gene regulation across tissues at a population level.

BASE4’s goal is to build on this type of scientific foundation and move towards an individual, longitudinal interpretation of human biology.

From static genetic risk to functional biology

A genetic test can reveal variants that a person has carried since birth.

That information can be highly valuable, but it is fundamentally static. It generally does not tell us whether the associated biological pathway is currently activated, compensated for or altered by other factors.

Transcriptomic information provides a complementary layer.

By analysing RNA, researchers can observe how biological instructions are being used at a particular point in time. Combining genetic and transcriptomic information may therefore help distinguish between:

A genetic predisposition that is present but not functionally active.

A molecular pathway currently showing altered activity.

A biological response that may be changing over time.

Signals that appear more relevant to certain tissues or health systems.

This integration is central to BASE4’s approach.

Rather than analysing isolated biomarkers, BASE4 is developing models designed to place molecular signals within a broader biological context.

The aim is to move from a static question—

“Which genetic risks does this person carry?”

—to a more functional one—

“How is this person’s biology currently behaving, and how might it be changing?”

What the study does (and does not) demonstrate

The GTEx atlas is one of the most important reference resources in human genomics, but its conclusions must be interpreted carefully.

The study demonstrates that:

Genetic regulatory effects are widespread across the human genome.

Many of these effects depend on the tissue being studied.

Cell-type composition is essential for interpreting gene-expression data.

Regulatory data can help connect genetic associations with possible biological mechanisms.

Integrating genomic and transcriptomic information provides more insight than studying either layer alone.

However, it does not demonstrate that:

Every genetic regulatory association causes disease.

Gene expression alone is sufficient to diagnose a patient.

Blood can directly reproduce the molecular state of every tissue.

A regulatory variant determines an individual’s clinical outcome.

The GTEx dataset directly validates BASE4’s models or products.

The connection with BASE4 is therefore scientific and conceptual.

GTEx established a large population-level map of how genetics influences gene activity across human tissues. BASE4 is developing technology intended to integrate similar biological dimensions at the individual level and interpret them alongside clinical context and longitudinal change.

Building a more complete view of human health

The central lesson from GTEx is that DNA is only the beginning of the biological story.

A genetic variant becomes medically meaningful through the way it affects molecular processes, cells, tissues and physiological systems.

Understanding that process requires several layers of information:

What genetic variant is present?

Which gene does it regulate?

In which tissue does the effect occur?

Which cells are involved?

Which biological pathway is affected?

How does this interact with the person’s current health and clinical context?

The GTEx project created an essential reference for answering the first part of these questions.

Its findings have helped transform human genetics from the study of static DNA sequences into the study of functional, tissue-specific regulation.

This is also the direction pursued by BASE4 Biosciences: moving beyond isolated genetic risk and building a more integrated model of how human biology operates across genes, tissues, pathways and time.

The genome provides the instructions.

The transcriptome reveals how those instructions are being used.

The tissue provides the biological context.

Together, these layers can bring us closer to a more precise and individual understanding of human health.

Scientific reference

The GTEx Consortium. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science. 2020;369(6509):1318–1330. doi:10.1126/science.aaz1776.