Final answer:
A purely polygenic gene would lead to a large number of GWAS hits due to the involvement of multiple genes, and common SNPs would collectively influence the trait although each might have a small individual effect. This results in a wide spectrum of phenotypes for polygenic traits.
Step-by-step explanation:
Understanding Polygenic Traits in Genome-Wide Association Studies (GWAS)
When considering how a purely polygenic gene would manifest in scientific studies, specific patterns are expected. In terms of GWAS hits, a high number of hits would be anticipated because polygenic traits are influenced by multiple genes, which means more SNPs would be associated with the trait in question. As for the role of common SNPs, they tend to have small effect sizes but can collectively have a significant impact on polygenic traits due to their prevalent occurrence in the gene pool.
Polygenic traits, such as height, weight, or skin color, involve multiple genes and may be influenced by environmental factors, leading to a broad spectrum of phenotypes within the population. This distribution typically forms a bell-shaped curve with extremes at either end, representing different combinations of dominant and recessive alleles.
GWAS is particularly effective for studying complex traits like polygenic diseases as they scan the genome for SNPs associated with the trait. The identification of these SNPs can provide insight into susceptibility, molecular pathways, and potential therapeutic targets.