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 PoolSeq may be largely outdated now that methods for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.