Genome breakthrough shows how much our genes shape who we are

A sweeping analysis of whole-genome sequences (WGS) has sharpened the picture of how much our genes shape everyday traits.

By examining nearly all DNA differences across hundreds of thousands of people, researchers found that modern sequencing now explains about 88 percent of the genetic influence long estimated from family studies.

Researchers from the University of Queensland worked with Illumina and the UK Biobank. The findings help resolve a long-standing question at the center of the nature versus nurture.

How DNA shapes complex traits

The study was led by Dr. Loïc Yengo, who uses large population datasets to map how DNA differences shape complex traits.

The team analyzed 347,630 adults of European ancestry and calculated how much variation in each trait is explained by genetic variants measured across the entire genome. 

This was possible because experts with the UK Biobank recently completed genomic sequencing for 490,640 participants.

The dataset expands access to rare and non-coding differences in DNA, making it a powerful resource.

Sequencing shows why genes matter

Heritability is the share of differences in a trait due to genetics within a population at a specific time. In this analysis, the average genetic share across 34 traits was about 0.28, and height stood out at about 0.71.

“WGS captures approximately 88 percent of the pedigree-based narrow-sense heritability,” said Dr. Yengo.

Across traits, common DNA changes carried much of the signal, while rare differences contributed a smaller but meaningful slice.

“We identified 15 traits with no significant difference between WGS-based and pedigree-based heritability estimates,” said Dr. Yengo.

The result shows that, for many traits, modern sequencing now accounts for most of the genetic influence that earlier family designs implied.

This update fits with other large-scale evidence on traits such as height. A 2022 height study mapped more than 12,000 common-variant signals and showed that very large samples can recover almost all of the common variant share.

Heritability that’s not accounted for

Researchers still want to understand why a small share of heritability remains unaccounted for even in very large sequencing studies.

Some of that gap may come from ultra-rare variants, which appear so infrequently that even large datasets struggle to measure their influence with confidence.

There are also open questions about structural variants, including large insertions and deletions, which short-read sequencing technologies do not always capture well. 

Scientists expect that combining long-read sequencing, improved reference genomes, and larger ancestry-diverse samples will help clarify how much these harder-to-measure differences contribute.

Traits linked to rare variants

The analysis separated uncommon DNA differences from more widespread ones to see how each group matters.

Rare variants – DNA changes found in fewer than one percent of people – together explained about one-fifth of the genetic share across traits.

Common variants carried the rest, yet the rare slice is important because it can point to genes and pathways with larger effects.

For blood lipids, researchers have already tied more than one-quarter of the rare variant heritability to specific genomic regions, an unusually high share for complex traits.

Fixing bias in heritability estimates

Family-based designs can be pulled off course by shared environments and by assortative mating, the tendency for people with similar traits to partner, which can inflate resemblance between relatives. 

Sequencing unrelated individuals and modeling ancestry carefully reduces those issues and delivers estimates that better reflect DNA’s additive contribution.

The study also tested methods that are sensitive to fine geographic structure. That extra step mattered most for behavioral measures, where people live and move can correlate with both genes and environment.

Genes that sequencing still misses

Most participants in the main analysis were of European ancestry, which narrows the scope of what we can conclude for the world.

The authors call for larger, multi-ancestry cohorts so that risk estimates and discovery improve for everyone.

A small fraction of heritability remains unaccounted for. Ultra-uncommon DNA changes and long structural variants – large insertions, deletions, or rearrangements of DNA – could explain part of the remainder. Better reference genomes may close more of the gap.

Future research directions

Risk-prediction tools known as polygenic scores, the combined measures of many variants used to estimate disease risk, are expected to improve as rare variants are added. 

The researchers estimate that folding rare variants into such scores could lift predictive power by up to 20 percent for some conditions.

Early identification is the practical promise. If risk can be estimated more accurately, clinicians can match people to prevention steps that matter long before symptoms appear.

The study is published in the journal Nature.

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