PATTERNS · Detecting Polygenic Adaptation Targeting Gene Expression Regulation In Humans Using eQTL Networks.
„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“
- Период
- 2020-04-01 → 2022-03-31
- Финансиране от ЕС
- 184 708 €
- Участници
- 1
- Схема
- MSCA-IF
Линиите свързват координатора с партньорите.
Накратко на български
Полигенната адаптация при хората изследва как множество малки генетични промени влияят върху сложни функции, като например имунния отговор или метаболизма на захарите. Разбирането на тези механизми помага да се установи какви биологични функции се развиват чрез регулирането на генната експресия в различните тъкани.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Резултати накратко
Detecting Polygenic Adaptation Targeting Gene Expression Regulation In Humans Using eQTL Networks.
In humans, a lot of phenotypes involved in local adaptation such as immune response to specific pathogens or metabolism of nutrients such as sugar, fats and protein are called "polygenic". This means that they are determined by several genes or genomic regions. Polygenic adaptation has been proposed to be a major adaptive mechanism for complex phenotypes. In this model, the frequency of several slightly advantageous mutations at independent genomic loci increase simultaneously in frequency in the population. Most of these advantageous mutations are believed to be located within non-coding, regulatory regions of the genome. However, detecting polygenic adaptation signatures, in particular outside of coding, genic regions, has proved to be challenging. Most approaches to detect polygenic adaptation consist in combining signatures of positive selection across functionally homogeneous sets of genes or variants. Conversely, few studies have looked at regulatory variants, and none have accounted for the tissue-specificity of gene expression. Here, we proposed to combine network biology and population genetics approaches in order to detect polygenic adaptation acting on complex phenotypes through gene expression regulation, and to identify and characterise biological functions evolving under polygenic adaptation, taking into account the tissue-specificity of their expression. This project aimed to answer the following questions: Q1. How can we efficiently detect polygenic selection targeting regulatory variants ? Q2. Which phenotypes and biological functions have been targeted by polygenic adaptation in humans? These questions have led to two main results: 1. The development of a statistical approach to detect polygenic selection signals. Its power has been assessed carefully using simulation and its sensitivity to confounding scenarios has been assessed. 2. The identification of groups of genetic variants regulating the expression of groups of functionally-related genes, that can be used as a basis to detect polygenic adaptation targeting gene expression levels. This project aimed at increasing our general understanding of processes that shaped present-day genetic diversity in human populations, and in particular the impact of polygenic selection on genome-wide diversity. The application of the developed approach will provide a quantitative assessment of the proportion of gene expression variation that can be attributed to groups of genetic variants under polygenic adaptation. In addition, the analysis of polygenic selection in several dataset providing samples of different tissues from hundreds of individuals should provide insights into how evolutionary processes affect phenotypes expressed in various tissues in humans. Finally, by crossing these results with GWAS databases, we should improve our understanding of the role of polygenic adaptation in the evolution of the risks to develop complex diseases, which could help anthropologists and biologists to better understand how complex phenotypes evolve and how side-effects of selection can sometimes lead to an increase in disease risks.
Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз
Цел на проекта
Polygenic adaptation, in which small changes in allele frequencies co-occur at multiple variants, has been proposed to be a major adaptive mechanism for complex phenotypes. Most approaches to detect polygenic adaptation consist in combining signatures of positive selection across functionally homogenous sets of genes or variants. However, few studies have looked at regulatory variants and none have accounted for the tissue-specificity of gene expression.Here, we propose to combine network biology and population genetics methods in order to detect polygenic adaptation acting on complex phenotypes through gene expression regulation. First, we will identify communities of regulatory variants that coregulate groups of genes, by representing both cis- and trans-expression quantitative trait loci as bipartite graphs. We will then search for communities enriched for signatures of weak positive selection to identify regulatory variants under polygenic adaptation. After evaluating the power of our approach using simulations, we will apply it to data from several tissues from the GTEx project. This will allow us to identify and characterise biological functions evolving under polygenic adaptation, taking into account the tissue-specificity of their expression. We thus hope to better understand the extent to which polygenic adaptation shaped the human genetic diversity and susceptibility to complex diseases.The PATTERNS project will be led by the experienced researcher (ER), who has worked on network biology during her postdoc in the USA. She will collaborate with the supervisor who is an expert in theoretical population genetics, and receive training in teaching, grant writing and management and communication. This will help the ER in her path to independence by strengthening her unique profile at the intersection of system biology and population genetics. The host institution will in turn benefit from her experience and network in the USA.
Оригинален текст от CORDIS (на английски).
Участници
- CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS · ParisКоординаторФранция
Връзки
Данни: CORDIS, © Европейски съюз
