Department of Physics of Complex Systems, ELTE Eötvös Loránd University, Pázmány P. s. 1A, Budapest, 1117, Hungary.
Department of Computational Sciences, Wigner Research Centre for Physics of the HAS, Konkoly-Thege Miklós út 29-33., Budapest, 1121, Hungary.
Sci Rep. 2019 Aug 12;9(1):11624. doi: 10.1038/s41598-019-48093-5.
Community level genetic information can be essential to direct health measures and study demographic tendencies but is subject to considerable ethical and legal challenges. These concerns become less pronounced when analyzing urban sewage samples, which are ab ovo anonymous by their pooled nature. We were able to detect traces of the human mitochondrial DNA (mtDNA) in urban sewage samples and to estimate the distribution of human mtDNA haplogroups. An expectation maximization approach was used to determine mtDNA haplogroup mixture proportions for samples collected at each different geographic location. Our results show reasonable agreement with both previous studies of ancient evolution or migration and current US census data; and are also readily reproducible and highly robust. Our approach presents a promising alternative for sample collection in studies focusing on the ethnic and genetic composition of populations or diseases associated with different mtDNA haplogroups and genotypes.
社区层面的遗传信息对于指导健康措施和研究人口趋势至关重要,但也存在相当多的伦理和法律挑战。当分析城市污水样本时,这些问题的重要性就降低了,因为这些样本的本质就是匿名的。我们能够在城市污水样本中检测到人类线粒体 DNA(mtDNA)的痕迹,并估计人类 mtDNA 单倍群的分布。我们使用期望最大化方法来确定在每个不同地理位置采集的样本中的 mtDNA 单倍群混合比例。我们的结果与之前关于古代进化或迁徙的研究以及当前的美国人口普查数据有很好的一致性;并且还具有良好的可重复性和高度稳健性。我们的方法为研究与不同 mtDNA 单倍群和基因型相关的人口或疾病的种族和遗传构成的样本收集提供了一种很有前景的替代方法。