Abstract：
Despite their critical roles in genetic sex determination, sex chromosomes remain unknown in many non-model organisms, especially those having recently evolved sex-linked regions (SLRs). These evolutionarily young and labile sex chromosomes are important for understanding early sex chromosome evolution but are difficult to identify due to the lack of Y/W degeneration and SLRs limited to small genomic regions. Here, we present SLRfinder, a method to identify candidate SLRs using linkage disequilibrium (LD) clustering, heterozygosity and genetic divergence. SLRfinder does not rely on specific sequencing methods or a specific type of reference genome (e.g., from the homomorphic sex). In addition, the input of SLRfinder does not require phenotypic sexes, which may be unknown from population sampling, but sex information can be incorporated and is necessary to validate candidate SLRs. We tested SLRfinder using various published datasets and compared it to the local principal component analysis (PCA) method and the depth-based method Sex Assignment Through Coverage (SATC). As expected, the local PCA method could not be used to identify unknown SLRs. SATC works better on conserved sex chromosomes, whereas SLRfinder outperforms SATC in analysing labile sex chromosomes, especially when SLRs harbour inversions. Power analyses showed that SLRfinder worked better when sampling more populations that share the same SLR. If analysing one population, a relatively larger sample size (around 50) is needed for sufficient statistical power to detect significant SLR candidates, although true SLRs are likely always top-ranked. SLRfinder provides a novel and complementary approach for identifying SLRs and uncovering additional sex chromosome diversity in nature.
摘要：
尽管它们在遗传性别决定中起着关键作用，性染色体在许多非模型生物中仍然未知，尤其是那些最近进化的性别相关区域（SLR）。这些进化上年轻且不稳定的性染色体对于理解早期性染色体进化很重要，但由于缺乏Y/W变性和限于小基因组区域的SLR而难以鉴定。这里,我们介绍SLRfinder，一种使用连锁不平衡(LD)聚类识别候选SLR的方法，杂合性和遗传差异。SLRfinder不依赖于特定的测序方法或特定类型的参考基因组(例如，来自同态性)。此外,SLRfinder的输入不需要表型性别，从人口抽样中可能未知，但性别信息可以纳入，并且是验证候选SLR所必需的。我们使用各种已发布的数据集测试了SLRfinder，并将其与局部主成分分析（PCA）方法和基于深度的方法进行了比较。不出所料,局部PCA方法不能用于识别未知的SLR。SATC在保守性染色体上效果更好，而SLRfinder在分析不稳定的性染色体方面优于SATC，尤其是当SLR港口倒置时。功率分析表明，当采样更多共享相同SLR的人群时，SLRfinder效果更好。如果分析一个人口，需要相对较大的样本量(大约50个)来获得足够的统计能力来检测显著的SLR候选，虽然真正的SLR可能总是排名第一。SLRfinder提供了一种新颖的互补方法，用于鉴定SLR并揭示自然界中其他性染色体多样性。
