Uncovering the hidden origin behind the missing heritability

Descripción del proyecto

Descifrar el código de la evolución compleja

A pesar de compartir gran parte de su composición genética, los individuos de una misma especie suelen mostrar diferencias sorprendentes en sus rasgos. Aunque la genómica moderna ha descubierto miles de variantes genéticas relacionadas con esta diversidad fenotípica, una parte sustancial de esta variación sigue sin poder explicarse. El equipo del proyecto UnMiss, financiado por el CEI, pretende descubrir las fuentes ocultas de esta «heredabilidad perdida». Utilizando la levadura como organismo modelo, los investigadores pretenden construir un atlas masivo de variantes y rasgos genéticos a partir de más de mil cepas naturales. También combinarán la secuenciación del genoma, la expresión génica y los análisis unicelulares y explorarán cómo los cambios genéticos poco frecuentes, los factores ambientales y las variaciones aleatorias interactúan para dar forma a rasgos complejos. Los hallazgos del proyecto podrían transformar la forma en que los científicos predicen los resultados genéticos.

Objetivo

"Understanding the genetic causes of phenotypic diversity in natural populations is a major challenge. While advances have been made in identifying the genetic basis of complex traits, our knowledge remains incomplete. Whole-genome sequencing has enabled genome-wide association studies (GWAS) to link genetic variants to traits, including human diseases. However, even with thousands of causal variants identified, they often account for only a small fraction of phenotypic variation. Uncovering the sources of this ""missing heritability"" is essential for predicting complex traits from genome sequences. The sources of missing heritability are largely unknown but may include: (i) incomplete variant catalogs focusing on single nucleotide variants (SNVs) while neglecting structural variants (SVs), (ii) limited power to detect rare variants in GWAS, (iii) difficulties in accounting for environmental effects and stochastic phenotypic variation, and (iv) complex gene-by-gene and gene-by-environment interactions. The UnMiss project aims to address these gaps using yeast as a model organism, allowing for systematic exploration of missing heritability. By developing a genetic variant atlas and a phenotype panel from 1,011 natural yeast isolates, we will examine how different variants contribute to trait heritability. Comparative GWAS analyses of these isolates and a panel of 1,000 hybrids will help clarify the role of low-frequency and rare variants. Gene expression data across conditions and single-cell analyses will further explore the genetic basis of environmental and stochastic trait variation. By deeply phenotyping the same population, we ensure that all traits are analyzed in the same individuals, allowing for the integration of data across different trait types. This comprehensive approach sets the foundation for large-scale network integration and mediation analyses, aiming to uncover hidden patterns that can facilitate the prediction of complex traits."