Department of Anatomy, University of Otago, Dunedin, New Zealand.
Helmholtz Pioneer Campus, Helmholtz Zentrum Muenchen, Neuherberg, Germany.
Elife. 2023 Dec 28;12:RP84553. doi: 10.7554/eLife.84553.
We used non-invasive real-time genomic approaches to monitor one of the last surviving populations of the critically endangered kākāpō (). We first established an environmental DNA metabarcoding protocol to identify the distribution of kākāpō and other vertebrate species in a highly localized manner using soil samples. Harnessing real-time nanopore sequencing and the high-quality kākāpō reference genome, we then extracted species-specific DNA from soil. We combined long read-based haplotype phasing with known individual genomic variation in the kākāpō population to identify the presence of individuals, and confirmed these genomically informed predictions through detailed metadata on kākāpō distributions. This study shows that individual identification is feasible through nanopore sequencing of environmental DNA, with important implications for future efforts in the application of genomics to the conservation of rare species, potentially expanding the application of real-time environmental DNA research from monitoring species distribution to inferring fitness parameters such as genomic diversity and inbreeding.
我们使用非侵入性实时基因组方法来监测极度濒危的鸮鹦鹉()最后幸存的种群之一。我们首先建立了一个环境 DNA 宏条形码协议,以便使用土壤样本以高度本地化的方式识别鸮鹦鹉和其他脊椎动物物种的分布。利用实时纳米孔测序和高质量的鸮鹦鹉参考基因组,我们从土壤中提取出物种特异性的 DNA。我们将基于长读长的单倍型定相与鸮鹦鹉种群中的已知个体基因组变异相结合,以识别个体的存在,并通过有关鸮鹦鹉分布的详细元数据来证实这些基于基因组的预测。这项研究表明,通过对环境 DNA 进行纳米孔测序可以实现个体识别,这对未来将基因组学应用于稀有物种保护的努力具有重要意义,可能会将实时环境 DNA 研究的应用从监测物种分布扩展到推断基因组多样性和近交等适应度参数。