A shift to metapopulation genetic management for persistence of a species threatened by fragmentation: the case of an endangered Australian freshwater fish

In a world where habitats are degrading and the climate is warming and becoming unpredictable, biodiversity conservation efforts and funding remain grossly inadequate. As part of a multi-faceted approach to halting extinctions, shifting from preserving small, remnant populations to a practice of genetically connecting populations that recreate larger and more diverse populations is expected to be beneficial. This harnesses key evolutionary processes to promote species’ abilities to adapt to changing environments and to increase the likelihood of population persistence. We use the endangered Macquarie perch (Macquaria australasica) as a case study to develop a genetic strategy for metapopulation management aimed at promoting population growth and persistence. The Macquarie perch’s range has been highly fragmented, and its remaining habitat is at risk of catastrophic degradation due to climate change. We integrate results of new and existing genetic analyses to illustrate how genetically depauperate populations can benefit from admixture, and how the outcomes of management interventions can be quantified through genetic monitoring. We develop the pipeline JeDi (https://github.com/drobledoruiz/JeDi) for estimating unbiased individual heterozygosity, population nucleotide diversity,y and pairwise population divergence, using reduced-representation genome sequencing data and an assembled reference genome. We use this pipeline to estimate baseline data for monitoring of Macquarie perch populations and show that combining two genetic sources of migrants during population restoration resulted in doubling of nucleotide diversity compared to either source. Genetic diversity estimates using our pipeline are comparable across studies, datasets and species, and suitable for evaluating the rate of global biodiversity change.

Methods
To obtain data for variant and invariant sites for all individuals, we used raw sequencing data provided by DArT. Pre-processing of raw reads included trimming Illumina adaptors with fastp (Chen et al. 2018), and demultiplexing with process_radtags of STACKS package (Catchen et al. 2013). We mapped the processed reads to the chromosome-length Macquarie perch genome using BWA-MEM (Li and Durbin 2009) with parameter -R set to '@RG\tID:sample_name\tSM:sample_name'. Mapped reads per individual were sorted, filtered (min MAPQ ≥ 20) and transformed to BAM with samtools (Li et al. 2009). Genotyping and downstream filtering was performed with the pipeline JeDi, resulting in a dataset of 706 individuals scored for 8,236,685 total sites, including 51,900 variant sites (including 46,973 biallelic and 4,927 tri- or tetra-allelic).

This dataset includes 1) a tab-separated file with the first column being individual IDs, and the second column their population, 2) mapped reads in a BAM file per individual named “ID.bam”, archived as .tar.gz, which were used as input for the pipeline JeDi.

在栖息地持续退化、气候变暖且愈发不可预测的当今世界，生物多样性保护工作与资金投入仍严重不足。作为遏制物种灭绝的多维度策略之一，从保护小型残存种群转向通过遗传连接种群以重建更大、更多样化种群的实践，有望带来显著效益。该策略依托关键进化过程，提升物种适应多变环境的能力，并增加种群存续的可能性。我们以濒危的麦夸里鲈（Macquaria australasica）为研究案例，开发用于集合种群管理的遗传策略，旨在促进种群增长与存续。麦夸里鲈的分布范围已高度破碎化，其残存栖息地正面临气候变化引发的灾难性退化风险。我们整合全新与已发表的遗传分析结果，阐明遗传多样性匮乏的种群如何从遗传混合中获益，以及如何通过遗传监测量化管理干预的效果。我们开发了JeDi分析流程（https://github.com/drobledoruiz/JeDi），依托简化基因组测序（reduced-representation genome sequencing）数据与组装完成的参考基因组，估算无偏的个体杂合度、种群核苷酸多样性以及种群间的成对分化程度。我们利用该流程估算麦夸里鲈种群监测的基线数据，并证实：在种群修复过程中结合两种遗传来源的迁移个体，可使核苷酸多样性较单一来源提升一倍。基于本流程得到的遗传多样性估算值可在不同研究、数据集与物种间保持可比性，适用于评估全球生物多样性变化速率。

## 材料与方法
为获取所有个体的变异位点与不变位点数据，我们使用了DArT提供的原始读段测序数据。原始读段的预处理步骤包括：使用fastp去除Illumina接头序列（Chen等，2018），并通过STACKS软件包的process_radtags工具完成样本解复用（Catchen等，2013）。我们使用BWA-MEM工具（Li与Durbin，2009）将处理后的读段比对至染色体级别的麦夸里鲈参考基因组，参数-R设为'@RG ID:sample_name SM:sample_name'。使用samtools（Li等，2009）将每个个体的比对读段进行排序、过滤（最小比对质量值MAPQ≥20）并转换为BAM格式。基因型分型与后续过滤通过JeDi流程完成，最终得到包含706个个体的数据集，共检测8236685个位点，其中51900个为变异位点（包括46973个双等位基因位点与4927个三等位/四等位基因位点）。

本数据集包含：1）制表符分隔的文本文件，第一列为个体ID，第二列为其所属种群；2）每个个体的比对读段存储为BAM文件，命名为“ID.bam”，并归档为.tar.gz格式，该文件可作为JeDi流程的输入数据。