Dataset for: How eDNA data filtration, sequence coverage, and primer selection influence assessment of fish communities in northern temperate lakes

For nearly 15 years now, environmental DNA has demonstrated its effectiveness in monitoring biodiversity. Methodological and technical improvements have significantly enhanced the field. However, the effect of factors such as sequence coverage, bioinformatic filtration and primer choice have been less explored or need to be optimized according to specific survey objectives and study site characteristics. We evaluated these factors to help optimize monitoring fish biodiversity in North American temperate lakes. We sampled water for fish community eDNA analysis in 12 lakes from southwestern Québec, Canada. The lakes were selected to encompass a wide range of surface areas and species richness. We sampled water from a total of 520 sites (25 to 50 per lake) and analyzed three mitochondrial DNA regions (12S rRNA; 16S rRNA; and cytb) using NovaSeq sequencing. Our results, based on rarefied count matrices (from a sequencing depth of 100,000 to a minimum depth of 1,000 reads per sample), showed that keeping only species in each sample if they represented at least one thousandth (species minimum read proportion threshold = 0.001) of the sample's reads was adequate to remove false positives and had a limited negative impact on true positives with low read counts. The sequencing depth was found to have a negligible impact on the accuracy of fish community assessment in a given lake. With the same sequencing depth and a complete local reference database for each primer set, a single primer set produced similar species richness medians than the combination of two or three primer sets. Overall, 12S and 16S detected more species and provided more consistent community profiles than cytb. Based on our observations, we suggest using the 12S MiFish-U primer set and applying a minimum proportion of 0.001 reads per species and site to monitor north-temperate lentic freshwater fish communities.

近十五年来，环境DNA (environmental DNA) 在生物多样性监测领域已展现出显著成效。方法学与技术层面的改进，极大推动了该领域的发展。然而，诸如测序覆盖度、生物信息学过滤流程以及引物选择等因素所产生的影响，相关研究仍较为匮乏，或需依据特定调查目标与研究位点特征进行针对性优化。本研究针对上述因素展开评估，旨在助力北美温带湖泊鱼类生物多样性监测工作的优化。我们于加拿大魁北克省西南部的12座湖泊中采集水样，用于鱼类群落环境DNA分析。所选湖泊涵盖了跨度广泛的表面积与物种丰富度梯度。共采集520个采样位点的水样（每座湖泊25至50个位点），并采用NovaSeq测序平台对三个线粒体DNA区域——12S rRNA、16S rRNA以及细胞色素b (cytb)——进行测序分析。基于抽平后的计数矩阵（测序深度范围为每样本100000条读段至最低1000条读段），我们的研究结果显示：若仅保留样本中读段占比至少为千分之一的物种（物种最小读段占比阈值=0.001），即可有效去除假阳性结果，且对低读段计数的真阳性物种仅产生有限的负面影响。研究发现，测序深度对单座湖泊内鱼类群落评估的准确性影响可忽略不计。在相同测序深度且各引物组拥有完整本地参考数据库的前提下，单一引物组所得到的物种丰富度中位数，与两组或三组引物组联合使用时的结果相近。总体而言，12S与16S rRNA区域相较于cytb，能检测到更多物种，且群落组成谱更为稳定。基于本研究的观测结果，我们建议采用12S MiFish-U引物组，并设置每物种与位点的最小读段占比为0.001，以监测北温带静水淡水鱼类群落。