Invited by Professor Yiping Hou in our department, Anders Albrechtsen, associate professor of the Department of Bioinformatics at the University of Copenhagen, gave a talk titled “Low-pass whole genome sequencing of over 140,000 pregnant Chinese women reveals population genetic history and new phenotypic associations” at 14:30 pm on November 20, 2019.
First, he introduced the background of the non-invasive prenatal test. When non-invasive prenatal diagnosis technology is used to detect Down syndrome, Trisomy 21, etc., it will generate a large amount of DNA data with low sequencing depth. Compared with general high-quality sequencing data, this type of data is more difficult to analyze due to its extremely low genome coverage, high genotype uncertainty, and the presence of other non-human DNA (such as bacterial, fungal, and viral DNA). Then he described the statistical methods used in the project to analyze these data, such as principal component analysis, genome-wide association studies, and processing and calculation of low-depth sequence data. After conducting a series of analyses, it was found that the differences between the North and the South of the Han nationality in China are clear, but the differences between the east and the west are not obvious. At the same time, several more significant genes were found to be related to lipid metabolism, BMI, height and genes related to the production of twins, etc. In addition, the professor made interpretations about the genes that were found to be significantly different in the dataset.
After the lecture, the teachers and students discussed with professor about the methods of genotype imputation and calculation, detection and analysis of copy number variations, and interpretation of the results of non-invasive prenatal diagnosis. The audiences learned about population genetic analysis and data analysis of non-invasive prenatal diagnosis from the lecture. At the same time, the analysis results and assumptions and interpretation methods also provided very useful inspiration for our future research.
A brief introduction about the speaker:
Associate professor Anders Albrechtsen received a doctorate degree in bio-informatics from the University of Copenhagen in 2009. He had been working as a postdoctoral researcher at the University of California, Berkeley in 2009-2012. Currently, the research group mainly uses statistical and computational methods to analyze the genomic data, including quantitative analysis and detection of population structure, detection of natural selection at the genomic level, simulation of identity-by-descent, genome-wide association studies, ultra-low-depth next generation sequencing data and ancient DNA data analysis. The group has established a lot of widely used software, such as ANGSD, NGSadmix, fast NGSadmix, etc. He has published more than 100 articles, including 16 articles in Nature and Science, with a h-index of 51, Google academic citations greater than 10,000. He is also a reviewer for the internationally renowned magazines such as American Journal of Human Genetics, Nature Genetics, Genome Research, Genetics.