With limited resources, there exists a trade-off between the number of individuals sequenced and the sequence depth. Depending on the biological question, higher individual sample sizes may be more valuable than high read depth (see Fumagalli, 2013; Lou, Jacobs, Wilder, & Therkildsen, 2020). For example, when inferring the geographic source of an invasive population, many reference individuals are required (see Part 2). In some cases, such as when analysing historical museum or herbarium samples, low sequencing depth may be unavoidable (McGaughran, 2020), necessitating analytical pipelines specifically designed for low-coverage genomic data (e.g. , Korneliussen, Albrechtsen, & Nielsen, 2014). Linked-read technologies such as haplotagging allow variants to be imputed with high accuracy, which means that many individuals can be sequenced at the cost of low-depth sequencing with less of a compromise in terms of effective read depth (Meier et al., 2020; see Box 3).
An alternative WGR sequencing strategy is PoolSeq (see Hivert, Leblois, Petit, Gautier, & Vitalis, 2018). If a given analysis requires allele frequencies from separate populations (e.g ., detecting directional or balancing selection; see Figure 3), genomic DNA from many individuals of the same population can be pooled in equimolar proportion and sequenced together. The concept of PoolSeq is shown below, where read colours correspond to three different (but unlabelled) individuals sequenced together. PoolSeq may be largely outdated now that methods for individual barcoding of large numbers of individuals for sequencing have become more affordable.