Diversity and Population Structure
In this study, we focused on worldwide populations of head lice to
understand their genetic diversity and distribution, which may help shed
light on major events of their human host dispersal throughout the
recent past. We investigated the worldwide population structure of human
head lice using whole genome nuclear SNPs. Results of multiple
clustering analyses agreed with an overall population structure that
showed five genetically distinct nuclear clusters. In all our analyses
that evaluated population structure, sub-Saharan African individuals
separate out from the rest of the individuals when considering only two
populations (Africa and the remainder of the world) up to as many as
five genetic populations (Figure 4). This African cluster is also the
most genetically diverse possessing a greater number of polymorphic
sites compared to other non-African countries. Through comparison to an
outgroup (the chimpanzee louse) we were able to confirm that this
sub-Saharan African population is sister and basal to the rest of the
non-African individuals (Figure 7).These results are consistent with
Yong et al., 2003 who also found a clear geographic separation between
African and non-African lice using partial nuclear genes 18S rRNA and
EF1-alpha. Human genetics and history present a similar pattern, with a
great deal of genetic diversity being found in sub-Saharan African
populations (Campbell & Tishkoff, 2008). Some of these characteristics
include highest nucleotide diversity, highest observed heterozygosity,
and high percentage variation separating them out from all other
populations. In human population genetics, all of these are
characteristics of Africa being the source population to all modern-day
humans (J. Z. Li et al., 2008; Xing et al., 2010).
Upon closer investigation of the five nuclear genetic clusters that we
uncovered in human head lice, we detected some global patterns arising
that are similar to its host. In Asia + Oceania, lice split among two
genetic clusters consisting of Southeast Asia and South Asian
individuals (Figure 4). This geographical split between South and
Southeast Asia is consistent with the southern expansion route proposed
for human dispersals into Asia (Macaulay et al., 2005; Reyes-Centeno et
al., 2014; Tassi et al., 2015). Southeast Asia further divided into four
geographically structured sub-clusters comprised of a Thailand + Laos +
Cambodia genetic cluster, and China, Papua New Guinea, and Philippines
each forming separate genetic clusters (Figure S7), reflecting the fine
scale population structure of humans in that area (Henn et al., 2010).
In contrast, the South Asian genetic cluster includes lice from
locations that are geographically separated from it (i.e., Mongolia,
Hungary, and Egypt). The genetic affinity of the samples from Hungary
and Egypt could be the result of sampling from recent immigrants or
travelers (in both cases, the samples were obtained from a single
individual). However, our TREEMIX analysis showed gene flow between
Hungary and Egypt with a relatively high migration weight which was
highly significant (p<10-308). This gene
flow event may explain the similarity between Hungary and Egypt. While
the genetic affinity among these groups may be reflective of louse
demographic history, further research is needed to better understand
these relationships. Furthermore, due to the limited number of sampling
in Hungary and Egypt, these samples may not necessarily reflect the
genetic structure found across these countries and any interpretations
taken from a sample derived from a single host should be done with
caution.
The samples from Europe and the Americas showed little differentiation,
grouping together in the PCA, DPAC and fastSTRUCTURE analyses. Nuclear
diversity, heterozygosity, and FST values were similarly
low between the Europe, North America, and South American samples, which
is unexpected given the host population structure and dispersal history.
In humans, African populations have the highest genetic diversity,
followed by Europeans and Asians, with the lowest genetic diversity in
indigenous American populations (Rosenberg et al., 2002). However, one
key difference in host and parasite diversity patterns is the sampling
strategies. In this study, lice were not collected from isolated ethnic
groups or from aboriginal Americans like in human genetic diversity
studies. Therefore, genetic similarity between European and American
louse populations could be due to more recent gene flow (e.g., during
European colonization of the Americas). Alternatively, the low genetic
diversity and similarity of European and American (North and South
America) lice could be due to selective pressures from insecticide use.
The high use of pyrethroid insecticides to control louse infestations in
Europe and the Americas (Diamantis et al., 2009) may have reduced the
genetic variation among these populations but further investigation is
needed, and is currently underway, to test this alternative explanation.
In addition, it could also be the case that our lice were sampled from
European descendants in cities outside of Europe (i.e in the Americas) .
At K=5 clusters, a subset of the continental North American samples,
primarily from Central America, separate out from the Europe + Americas
cluster. The populations in this cluster also had moderate levels of
observed heterozygosity (0.05-0.08), greater than in European and other
American populations. It could be that these Central American louse
populations may have experienced less insecticide exposure or the
genetic variation may reflect earlier louse demographic history that
could not be observed in the other American louse populations. For
example, our TREEMIX analysis using allele frequency distributions shows
a potential ancestral gene flow event between Philippines and the
countries in this Central American cluster (Figure 8), suggesting
inter-continental mixing at some point in time.
The geographically structured genetic clusters we uncovered here are
concordant with previous findings examining microsatellite markers from
eight localities around the world (Ascunce et al., 2013). Our current
dataset adds information about African populations and how the genetic
diversity of human head lice is distributed across the world by
ancestral demographic events. Based on our analyses of population
substructure, it is evident that the 5 major nuclear clusters that we
uncovered are further subdivided into major regions within continents
suggesting even more genetically structured louse populations (Figure
S5-S9).