Introduction
The discovery and interpretation of genotypes sequenced from neutrally
evolving genetic markers are critical to breeding decisions of managed
and wild species in agriculture and biodiversity conservation,
respectively. Globally, the genetic diversity of some 7,500 livestock
breeds is decreasing, putting significant pressure on economic markets
and food availability
(Boettcher et al., 2010).
Supporting genetically diverse populations of agriculturally significant
species allows for breeds to remain resilient in the face of climate
change, changes in market needs, management practices, husbandry
practices, parasites, and pathogens
(Boettcher et al., 2010).
Likewise, the conservation of genetic diversity is critical for the
conservation of declining wildlife to buffer against comparable
environmental stressors such as parasites, pathogens, and climate change
(DeWoody, Harder,
Mathur, & Willoughby, 2021; Teixeira & Huber, 2021). To this end,
identifying and employing genetic markers such as microsatellites in
guiding the management of livestock and wildlife is important to
agricultural and non-agricultural ecosystems
(Abdelmanova
et al., 2021; Beacham et al., 2008; Ginja et al., 2013; Guichoux et al.,
2011; Pham et al., 2013; Strange, Delaney, Tarpy, & James, 2017),
especially when combined with additional biological and ecological data
(Addis, Lowe, Hossack,
& Allendorf, 2015; Koch, Vandame, Mérida-Rivas, Sagot, & Strange,
2018).
Bees (Hymenoptera: Anthophila) are a unique group of animals as they
serve as couriers of pollen across flowering plants more often than any
other taxa, thereby supporting plant reproduction. Globally, there are
more than 20,000 described bee species
(Ascher & Pickering,
2020). The most intensively managed bee species is the European honey
bee, Apis mellifera L. (Hymenoptera: Apidae) due to its
reputation as a productive honey-maker and crop pollinator. Within the
last century, the critical role of managed honey bees in supporting
industrial scale crop production has been demonstrated worldwide, well
outside their endemic range of Europe and North Africa. The
identification and interpretation of genetic markers have been critical
in the development of effective honey bee breeding and management
strategies
(Bourgeois,
Sylvester, Danka, & Rinderer, 2008; Delaney, Meixner, Schiff, &
Sheppard, 2009; Jensen et al., 2006; Paál et al., 2021; Parejo,
Henriques, Pinto, Soland-Reckeweg, & Neuditschko, 2018). More
recently, environmental pressures such as increased use of pesticides,
increased susceptibility to and transmission of disease, changes in diet
quality, and land-use change, have become major stressors that imperil
the commercial supply of honey bees
(Shanahan, 2022). The
recent losses of managed honey bee colonies in some parts of the world
have emphasized the need to develop breeding and management programs for
additional bee species that can be used for pollination of commercial
crops (National Research
Council, 2007).
The blue orchard bee, Osmia lignaria Say (Hymenoptera:
Megachilidae) is a solitary, cavity-nesting mason bee native to North
America (Bosch &
Kemp, 2001; Branstetter, Müller, Griswold, Orr, & Zhu, 2021). Starting
in the 1970s, pioneering work by Philip Torchio and his colleagues
demonstrated the usefulness of O. lignaria to support the
pollination of certain agricultural crops (Fig. 1)
(J. Bosch & Kemp, 2001).
It is an effective pollinator of fruit trees, especially almonds,
apples, cherries, nectarines, and plums
(Bosch
& Kemp, 1999; Bosch, Kemp, & Peterson, 2000; Bosch, Kemp, & Trostle,
2006; Boyle & Pitts-Singer, 2019; Sheffield, 2014; Torchio, 1976),
among other rosaceous and berry crops
(Bosch & Kemp, 2001). The
capacity of these bees to forage for pollen and nectar under cool and
wet spring weather conditions, their tendency to move between trees and
tree rows, and their collection of pollen as loose, dry granules on the
underside of the abdomen lends to their efficiency as pollinators,
especially in orchard crops
(Bosch & Kemp, 2001). For
example, when O. lignaria are deployed alone or as co-pollinators
with honey bees into almond and cherry orchards, an increase in fruit
set and yield have been observed
(Pitts-Singer, Artz,
Peterson, Boyle, & Wardell, 2018). Thus, the inclusion of O.
lignari a into integrated crop pollination management strategies
provides pollination insurance and supports sustainable yields of
important pollinator-dependent crops
(Isaacs et al., 2017).
The commercialization of native and introduced solitary bee species to
deliver pollination services has occurred across the globe (Osterman et
al., 2021), and includes several megachild species, like O.
lignaria , that readily build nests in provided artificial tunnels.Osmia lignaria is a member of the bicornis clade within
the subgenus Osmia (Osmia ), a group that includes a number
of managed pollinator species, and it is composed of two named
subspecies: O. lignaria lignaria Say and O. lignaria
propinqua Cresson
(Branstetter et al., 2021).
The two subspecies are geographically separated into eastern and western
ranges approximately by the 100th Meridian
(Bosch & Kemp, 2001;
Rust, 1974). In the eastern portion of its native range, O. l.lignaria is distributed from Georgia north to Nova Scotia, and
west to Texas and Michigan. In the western portion of its distribution,O. l. propinqua is distributed from southern California north to
British Columbia and east to South Dakota and Texas
(Bosch & Kemp, 2001).
However, the validity of the subspecies is uncertain and morphological
and genetic data is needed to test the subspecies hypothesis.
Microsatellites are useful and affordable genetic markers that have the
capacity to capture multilocus genotype information for estimating
genetic diversity and structure
(Guichoux et al., 2011). In
this study, we use a recently developed genome assembly of O.
lignaria to identify novel microsatellite markers that can support
population genetic analysis of O. lignaria . Next, we used the
markers to estimate sib-ship relationships among two Intermountain North
America O. l. propinqua (hereafter stated as O. lignaria )
populations and determined basic population genetic diversity metrics.
Furthermore, we estimated population structure with an analysis of
molecular variance to test for differences in genetic variance in theO. lignaria populations. Finally, we test the novel
microsatellite loci on other Osmia species within theapicata , bicornis, emarginata , and ribiflorisclades. Our overall goal is to demonstrate the utility of these new
microsatellite markers in O. lignaria as well as their potential
use in other agriculturally important Osmia species.