Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing 100093, China.
Key Laboratory of Pollinating Insect Biology, Ministry of Agriculture and Rural Affairs, Beijing 100093, China.
Genes (Basel). 2022 Jan 21;13(2):182. doi: 10.3390/genes13020182.
Whole-genome sequencing has become routine for population genetic studies. Sequencing of individuals provides maximal data but is rather expensive and fewer samples can be studied. In contrast, sequencing a pool of samples (pool-seq) can provide sufficient data, while presenting less of an economic challenge. Few studies have compared the two approaches to infer population genetic structure and diversity in real datasets. Here, we apply individual sequencing (ind-seq) and pool-seq to the study of Western honey bees ().
We collected honey bee workers that belonged to 14 populations, including 13 subspecies, totaling 1347 colonies, who were individually (139 individuals) and pool-sequenced (14 pools). We compared allele frequencies, genetic diversity estimates, and population structure as inferred by the two approaches.
Pool-seq and ind-seq revealed near identical population structure and genetic diversities, albeit at different costs. While pool-seq provides genome-wide polymorphism data at considerably lower costs, ind-seq can provide additional information, including the identification of population substructures, hybridization, or individual outliers.
If costs are not the limiting factor, we recommend using ind-seq, as population genetic structure can be inferred similarly well, with the advantage gained from individual genetic information. Not least, it also significantly reduces the effort required for the collection of numerous samples and their further processing in the laboratory.
全基因组测序已成为群体遗传学研究的常规手段。对个体进行测序可提供最大的数据量,但费用较高,且可研究的样本较少。相比之下,对样本池进行测序(pool-seq)可以提供足够的数据,同时经济压力较小。在真实数据集的群体遗传结构和多样性推断方面,很少有研究比较这两种方法。在此,我们将个体测序(ind-seq)和 pool-seq 应用于西方蜜蜂()的研究。
我们收集了属于 14 个种群的蜜蜂工蜂,包括 13 个亚种,共 1347 个蜂群,对 139 个个体和 14 个样本池进行了个体(ind-seq)和池测序(pool-seq)。我们比较了两种方法推断的等位基因频率、遗传多样性估计值和群体结构。
pool-seq 和 ind-seq 揭示了近乎相同的群体结构和遗传多样性,尽管成本不同。虽然 pool-seq 以较低的成本提供全基因组多态性数据,但 ind-seq 可以提供额外的信息,包括群体亚结构、杂交或个体异常值的识别。
如果成本不是限制因素,我们建议使用 ind-seq,因为可以通过个体遗传信息获得类似的群体遗传结构推断优势,同时还可以显著减少收集大量样本及其在实验室进一步处理所需的工作量。