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.