My scientists discovered 17 new genetic loci that affect face shape
Science and Technology Daily News (Reporter Lu Chengkuan) Recently, the reporter learned from the Beijing Institute of Genomics, Chinese Academy of Sciences that researchers at the Institute have developed a method that can integrate and analyze multiple genome-wide association studies, C-GWAS, and used this method to analyze human genome-wide association studies. 78 facial morphological phenotypes, 17 new genetic loci that affect face shape were discovered.
Related research results were published in Nature Communications.
Genome-wide association study (GWAS) is an effective method to study complex phenotypic genetic factors in humans.
At present, scientists have discovered a large number of genetic loci using GWAS.
"However, due to the inability to analyze multiple phenotypes at the same time, the standard GWAS process cannot efficiently detect genetic loci with pleiotropic effects." Liu Fan, the corresponding author of the paper and a researcher at the Beijing Institute of Genomics, Chinese Academy of Sciences, said, "For this reason, we developed A method capable of integrated analysis of multiple genome-wide association studies called C-GWAS."
Human facial morphology represents a complex set of multidimensional, heritable, and interconnected phenotypes.
The researchers applied C-GWAS to analyze 78 facial morphological phenotypes.
The results show that the detection rate of genetic loci of C-GWAS is three times that of traditional methods, and 17 new genetic loci that affect face shape have been discovered.
Through further validation analysis and functional genomics analysis, the researchers showed that the results of C-GWAS have higher genetic pleiotropy than those obtained by traditional methods.
"This has significantly improved the genetic interpretation of face shape, and the excavated genes have more clear biological developmental functions, indicating that C-GWAS has great advantages in analyzing multi-dimensional and complex phenotypic genetic structures." Liu Fan emphasized.
"From the existing results, C-GWAS is an efficient algorithm that can integrate and analyze multi-phenotype GWAS summary data. It is highly sensitive to genetic pleiotropy and has strong stability in complex scenarios." Fan Liu said that C-GWAS successfully discovered a batch of new genetic loci and functional genes in the analysis of human facial morphotypes, which has deepened people's understanding of the genetic structure of faces. In the future, C-GWAS will be used to analyze more The genetic structure of high-dimensional complex phenotypes provides technical support for the delineation of shared genetic factor networks among human phenotype groups.