In 2001, the “International Human Genome Sequencing Consortium” announced the first draft of the human genome reference sequence. The Human Genome Project, as it was called, had taken more than eleven years of work and involved more than 1000 scientists from 40 countries. This reference, however, did not represent a single individual but instead is a composite of humans that could not accurately capture the complexity of human genetic variation.
Building on this, scientists have carried out many sequencing projects over the last 20 years to identify and catalog genetic differences between an individual and the reference genome. Those differences usually focused on small single base changes and missed larger genetic alterations. Current technologies now are beginning to detect and characterize larger differences – called structural variants – such as insertions of several hundred letters. Structural variants are more likely than smaller genetic differences to interfere with gene function.
An international research team has now published an article in Science announcing a new, considerably more comprehensive reference dataset obtained using a combination of advanced sequencing and mapping technologies. The new reference dataset reflects 64 assembled human genomes, representing 25 different human populations from across the globe. Importantly, each of the genomes was assembled without guidance from the first human genome and as a result better captures genetic differences from different human populations. The study was led by scientists from the European Molecular Biology Laboratory Heidelberg (EMBL), the Heinrich Heine University Düsseldorf (HHU), The Jackson Laboratory for Genomic Medicine in Farmington, Conn. (JAX), and the University of Washington in Seattle (UW).
“With these new reference data, genetic differences can be studied with unprecedented accuracy against the background of global genetic variation, which facilitates the biomedical evaluation of genetic variants carried by an individual," emphasizes the co-first author of the study, Dr. Peter Ebert from the Institute of Medical Biometry and Bioinformatics at HHU. The distribution of genetic variants can differ substantially between population groups as a result of spontaneous and continuously occurring changes in the genetic material. If such a mutation is passed on over many generations, it can become a genetic variant specific to that population.
The new reference data provide an important basis for including the full spectrum of genetic variants in so-called genome-wide association studies. The aim is to estimate the individual risk of developing certain diseases such as cancer and to understand the underlying molecular mechanisms. This, in turn, can be used as a basis for more targeted therapies and preventative medicine.
This work might enable further applications in precision medicine. Drug efficacy, for example, can vary between individuals based on their genomes. The new reference data now represent the full range of different genetic variant types and incorporates human genomes of great diversity. Therefore, this new resource might contribute to developing novel approaches in personalized medicine, where the selection of therapies is tailored to a patient’s individual genetic background.
"Just a few years ago, I would not have imagined that resolving genomes to this completeness would become possible so fast. This was enabled by exciting advances both of biotechnological and computational methods." says Dr. Peter Ebert, co-first author and computational biologist at Heinrich Heine University Düsseldorf, Germany. "Great to see this technology applied to a diversity panel of human genomes. These genome sequences will be an important resource for fundamental research and clinical genomics going forward."
Senior author Prof. Dr. Tobias Marschall, who led the research at HHU, added that "it was especially exciting to see that these new genome sequences enable a much more detailed analysis of data from standard sequencing technologies, which are routinely applied to millions of genomes by researchers and clinicians across the globe." He believes that "future studies to find associations between genetic variants and disease susceptibility will clearly benefit from this new approach."
This study builds on a new method published by these researchers last year in Nature Biotechnology to accurately reconstruct the two components of a person's genome – one inherited from a person’s father, one from a person’s mother. When assembling a person’s genome, this method eliminates the potential biases that could result from comparisons with an imperfect reference genome.
Dr. Ebert highlights the interdisciplinary cooperation at HHU: “We performed our extensive computations on the High Performance Computing Cluster Hilbert. The HPC team of the Düsseldorf ZIM thus had an important role for the success of our research project."
Peter Ebert*, Peter A. Audano*, Qihui Zhu*, Bernardo Rodriguez-Martin*, David Porubsky, Marc Jan Bonder, Arvis Sulovari, Jana Ebler, Weichen Zhou, Rebecca Serra Mari, Feyza Yilmaz, Xuefang Zhao, PingHsun Hsieh, Joyce Lee, Sushant Kumar, Jiadong Lin, Tobias Rausch, Yu Chen, Jingwen Ren, Martin Santamarina, Wolfram Höps, Hufsah Ashraf, Nelson T. Chuang, Xiaofei Yang, Katherine M. Munson, Alexandra P. Lewis, Susan Fairley, Luke J. Tallon, Wayne E. Clarke, Anna O. Basile, Marta Byrska-Bishop, André Corvelo, Uday S. Evani, Tsung-Yu Lu, Mark J.P. Chaisson, Junjie Chen, Chong Li, Harrison Brand, Aaron M. Wenger, Maryam Ghareghani, William T. Harvey, Benjamin Raeder, Patrick Hasenfeld, Allison A. Regier, Haley J. Abel, Ira M. Hall, Paul Flicek, Oliver Stegle, Mark B. Gerstein, Jose M.C. Tubio, Zepeng Mu, Yang I. Li, Xinghua Shi, Alex R. Hastie, Kai Ye, Zechen Chong, Ashley D. Sanders, Michael C. Zody, Michael E. Talkowski, Ryan E. Mills, Scott E. Devine, Charles Lee#, Jan O. Korbel#, Tobias Marschall#, Evan E. Eichler#, Haplotype-resolved diverse human genomes and integrated analysis of structural variation, Science 2021
*Co-first authors #Co-senior and co-corresponding authors