Discussion
Microsatellites are a useful tool to rapidly acquire genetic information
that informs conservation, breeding, and management decisions. They are
especially informative for identifying population genetic structure
among subpopulations and have the capacity to infer sibship
relationships among individuals within a subpopulation
(Koch, McCabe, Love,
& Cox-Foster, 2021; Van Eeckhoven et al., 2022). While the front-end
of microsatellite development can be expensive, using established
microsatellites is a cost-effective method for population genetics
studies relative to reduced representation genome sequencing on a
per-specimen basis in the market today
(Guichoux et al., 2011).
Microsatellite analyses have uncovered cryptic genetic diversity among
different bee species (Koch,
Rodriguez, Pitts, & Strange, 2018), and have been useful markers for
correlating biological phenomena such as population declines and
genotype-by-environment associations
(Cameron et al.,
2011; Koch, Vandame, et al., 2018; Pitts-Singer, Cane, & Trostle,
2014). Furthermore, microsatellite marker development is on the rise
across agriculturally important solitary bee species
(Neumann &
Seidelmann, 2006; Strange et al., 2017; Van Eeckhoven et al., 2022). In
this study, we expand microsatellite marker availability and utility in
the solitary bee genus Osmia , with special focus on O.
lignaria .
Our identification and filtering strategy using the O. lignariagenome assembly uncovered a high volume of candidate microsatellite loci
that can be tested using additional molecular techniques. We present
those candidate loci in Supplementary Tables 1 - 3. In our study, we
failed to find many perfect microsatellites that resulted in a product
size greater than 241 nts under our filtering strategy. However, we were
able to identify sizes exceeding 241 nts when we further examined
imperfect microsatellite loci. An imperfect microsatellite is the result
of a mutation at a microsatellite locus that often creates an imperfect
motif (Behura & Severson,
2015). Imperfect microsatellites are suspected to be more stable than
perfect microsatellites as they are less likely to incur slippage
mutations (Sturzeneker,
Haddad, Bevilacqua, Simpson, & Pena, 1998). Interestingly, in our
study of O. lignaria , we found significantly more genotyping
error in the perfect microsatellites relative to the imperfect
microsatellites. Based on this result, we suggest that further
microsatellite development studies should examine genotype error in the
context of microsatellite type when identifying loci for population
genetic studies. Markers that succumb to high genotyping error will
likely result in deviations from HWE and should be removed from
population genetic analyses
(Hoffman & Amos,
2005; Morin et al., 2009).
Our characterization and assessment of novel O. lignariamicrosatellites underscores the importance of including genotype error
rates in population genetic studies. Genotyping error can significantly
impact estimates of genetic diversity, population structure, and sibship
relationships (Hoffman &
Amos, 2005). In turn, these errors impact the interpretation of genetic
data and can lead to poor management decisions for livestock and
wildlife if not controlled. Genotyping error in a microsatellite
analysis is the product of diverse phenomena including poor quality of
template DNA, allelic dropout, and misprinting
(Hoffman & Amos, 2005).
Even in cases where well established microsatellite markers are used for
population genetics studies (Hoffman & Amos, 2005), poor DNA template
quality has caused 50% of the genotyping error
(Morin et al., 2009). This
phenomenon underscores the importance of performing pilot studies and
strategic re-amplification of samples when conducting genetic analyses
(Hoffman & Amos, 2005).
The goal of this study was to present novel microsatellite markers forO. lignaria and characterize their utility. Application of the
microsatellite markers on two Intermountain North America populations ofO. lignaria in Idaho found no differences in population genetic
diversity across populations and low, but significant, population
structure. Furthermore, we found no significant difference betweenHO and Nei’s HE in both
populations, and thereby, provide no evidence to suggest inbreeding is
occurring within either population. This inference is further supported
by low FI S values and permutation
tests. We estimated that ~60% of the alleles (1 -
[Uniq. alleles/No. Alleles]) identified in the study are shared
between both populations. Combined, these results suggest that it is
likely that contemporary dispersal (i.e., gene flow) is taking
place across populations. This is not surprising as the populations
studied are ~30 km apart and native residents of the
Bear River Mountains (Fig. 1). Furthermore, sibship analysis provides
evidence for full sibling families within each population. Thus, the
novel microsatellites have the capacity to identify genetic
lineages/families within a population, which is important information
for biological research such as the characterization of nest founding
behaviors and offspring survival
(Tepedino & Torchio,
1994).
Our assessment on the utility of the novel microsatellites in otherOsmia species supports future population genetic studies of the
genus. To date, microsatellite markers have been developed for O.
bicornis (Neumann &
Seidelmann, 2006; Van Eeckhoven et al., 2022), which is in the same
clade (bicornis clade) as O. lignaria . The subgenusOsmia , especially the clade bicornis , possess a diversity
of Osmia species that are important pollinators of crops
including O. cornuta , O. cornifrons , and O. taurus(Branstetter et al.,
2021; Osterman et al., 2021). We found that the novel microsatellite
loci amplified in up to 18 of the 22 in one specimen of O.
cornuta (mean marker amplification = 9.9 ± 2.0 [n = 9])
(Supplementary Table 7). Osmia cornuta is native to north Africa
and Europe and was introduced to the U.S. from Spain to pollinate crops
in 1984 (Torchio & Asensio,
1985). While O. cornuta has not been established in the
U.S. due to biological limitations
(Torchio, Asensio, &
Thorp, 1987; Torchio & Asensio, 1985), female O. cornuta have
been found to visit between 9,500 and 23,600 almond flowers implicating
high pollination efficiency
(Bosch, 1994). Given the
significance of O. cornuta to agriculture particularly in Europe,
the novel microsatellite markers will have the capacity to characterize
population genetic structure and diversity of managed populations to
guide future management and breeding strategies. Finally, the invasion
of the intentionally introduced O. cornifrons and accidentally
introduced O. taurus to North America may benefit from population
genetic study (LeCroy,
Savoy-Burke, Carr, Delaney, & Roulston, 2020). Specifically, we expect
that the novel microsatellites to answer questions concerning the
colonization timing of these non-native bees, underlying genetic
diversity and structure, and potentially their rate of expansion
throughout North America.
The use of microsatellites to characterize population genetic diversity
in bee pollinators has a long history. Based on Google Scholar
(https://scholar.google.com/),
the first peer-reviewed paper that characterizes microsatellites in bees
(Hymenoptera: Anthophila) was on A. mellifera and Bombus
terrestris by Estoup et al.
(1993). Over
the last 29 years, microsatellites continued to be developed for honey
bees (Apis spp.)
(Estoup, Garnery,
Solignac, & Cornuet, 1995; Solignac et al., 2003), bumble bees
(Bombus spp.)
(Estoup, Scholl,
Pouvreau, & Solignac, 1995; Reber Funk, Schmid-Hempel, &
Schmid-Hempel, 2006; Stolle et al., 2009), mason bees (Osmiaspp.) (Neumann &
Seidelmann, 2006; Van Eeckhoven et al., 2022), stingless bees
(Melipona spp.)
(Peters, Queller, Imperatriz
Fonseca, & Strassmann, 1998), orchid bees (Euglossa spp.)
(López-Uribe,
Santiago, Bogdanowicz, & Danforth, 2013; Paxton, Zobel, Steiner, &
Zillikens, 2009), and alfalfa leafcutting bees (Megachilerotundata F.; Megachilidae)
(Strange et al., 2017),
among others. The development of microsatellite markers in bee
pollinators has been critical in supporting research studies of bee
evolution and ecology and in making informed decisions on their
management in agricultural and wildlife conservation settings. For
example, microsatellites have proven instrumental in informing honey bee
breeding decisions
(Bourgeois et
al., 2008; Delaney et al., 2009; Jensen et al., 2006), estimating
bumble bee decline
(Cameron et al., 2011;
Lozier & Cameron, 2009), and determining the impacts of habitat
fragmentation on gene flow in orchid bees
(Soro, Quezada-Euan,
Theodorou, Moritz, & Paxton, 2016; Suni & Brosi, 2011).
Osmia lignaria has been heavily adopted by producers to pollinate
a diversity of orchard and berry crops that span across a broad
geographic range with diverse climates
(Bosch &
Kemp, 1999; Boyle & Pitts-Singer, 2019; Sheffield, 2014; Torchio,
1976). Furthermore, populations endemic to the continental U.S. lends
to both genetic and physiological regional differences
(Branstetter et al.,
2021; Pitts-Singer et al., 2014). Commercial suppliers in the western
U.S. are sourcing O. lignaria from different parts of their
native range including Washington, Utah, Idaho, and California, but may
sell such bees directly to customers or to other distributors across the
U.S. As new O. lignaria producers enter the market in response to
the growing demands for integrated crop pollination
(Isaacs et al., 2017), the
sustainability of O. lignaria sourcing, management, and breeding
would benefit from knowledge on underlying population genetic diversity
and structure. For example, illegal trap nesting of O. lignariaand other solitary bees on public lands is commonplace throughout the
Intermountain West. In fact, the Cub River field site is associated with
a history of illegal trap nesting for Osmia species
(Tepedino & Nielson,
2017). If left unchecked, trap-nesting could decimate endemic O.
lignaria populations, ultimately reducing the genetic diversity
available to commercial enterprises. Application of population genetic
diversity data with microsatellites could uncover resilient or imperiled
populations and ultimately guide sustainable trap-nesting pursuits. In
conclusion, we anticipate the novel markers developed in our study to
support critical investigations of O. lignaria evolution,
ecology, conservation, and livestock development.