Data from: Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions, local adaptation and geographic structure

Recent advances in sequencing allow population-genomic data to be generated for virtually any species. However, approaches to analyse such data lag behind the ability to generate it, particularly in nonmodel species. Linkage disequilibrium (LD, the nonrandom association of alleles from different loci) is a highly sensitive indicator of many evolutionary phenomena including chromosomal inversions, local adaptation and geographical structure. Here, we present linkage disequilibrium network analysis (LDna), which accesses information on LD shared between multiple loci genomewide. In LD networks, vertices represent loci, and connections between vertices represent the LD between them. We analysed such networks in two test cases: a new restriction-site-associated DNA sequence (RAD-seq) data set for Anopheles baimaii, a Southeast Asian malaria vector; and a well-characterized single nucleotide polymorphism (SNP) data set from 21 three-spined stickleback individuals. In each case, we readily identified five distinct LD network clusters (single-outlier clusters, SOCs), each comprising many loci connected by high LD. In A. baimaii, further population-genetic analyses supported the inference that each SOC corresponds to a large inversion, consistent with previous cytological studies. For sticklebacks, we inferred that each SOC was associated with a distinct evolutionary phenomenon: two chromosomal inversions, local adaptation, population-demographic history and geographic structure. LDna is thus a useful exploratory tool, able to give a global overview of LD associated with diverse evolutionary phenomena and identify loci potentially involved. LDna does not require a linkage map or reference genome, so it is applicable to any population-genomic data set, making it especially valuable for nonmodel species.

近年来，测序技术的进步使得几乎所有物种均可获取群体基因组数据。然而，此类数据的分析方法却滞后于数据生成能力，针对非模式物种的情况尤为突出。连锁不平衡（Linkage disequilibrium, LD）——即不同位点等位基因的非随机关联——是诸多进化现象的高灵敏指示指标，涵盖染色体倒位、局部适应与地理结构等。本文介绍连锁不平衡网络分析（linkage disequilibrium network analysis, LDna）方法，可获取全基因组范围内多位点间共享的连锁不平衡信息。在LD网络中，顶点代表位点，顶点间的连接则代表二者之间的连锁不平衡。我们通过两个测试案例对该网络展开分析：其一为全新的孟加拉按蚊（Anopheles baimaii）限制性位点相关DNA测序（restriction-site-associated DNA sequence, RAD-seq）数据集，该物种是东南亚的疟疾传播媒介；其二为来自21尾三棘刺鱼个体的已被充分表征的单核苷酸多态性（single nucleotide polymorphism, SNP）数据集。在两个案例中，我们均快速识别出5个独立的单异常簇（single-outlier clusters, SOCs），每个簇均包含大量以高LD相互连接的位点。在孟加拉按蚊的分析中，进一步的群体遗传学分析证实，每个SOC均对应一处大型染色体倒位，这与此前的细胞学研究结果一致。对于三棘刺鱼，我们推断每个SOC分别对应不同的进化现象：两处染色体倒位、局部适应、种群人口统计学历史以及地理结构。综上，LDna是一款实用的探索性工具，可全局概览与各类进化现象相关的连锁不平衡，并识别潜在参与其中的位点。由于LDna无需依赖连锁图谱或参考基因组，因此可应用于任意群体基因组数据集，尤其对非模式物种而言具有重要价值。