Landscape Genetics and Phytogeography of Criollo Avocadoes Persea americana from Northeast Colombia

Avocado (Persea americana) Mill represents one of the most consumed fruits around the world. This species has been differentiated into three main races Guatemalan, Mexican and West Indian according to several molecular markers. However, the interaction between genotypic and phenotypic traits of this crop is still unknown. For this reason, a landscape genetics analysis was made in 90 criollo trees from Northeast Colombia (Antioquia) with 14 microsatellites, sequencing of 3 nuclear loci, endo-1-4-D-glucanase (Cell), Chalcone synthase (CHS) and serine-threonine-kinase (STK) and 28 morphological traits. High genetic diversity was found suggesting a hybrid origin of criollo trees. Morphological variation showed intermixed racial features. FST = 0.03, p =0.001 (measured with microsatellites) suggested low genetic differentiation. According to STRUCTURE, K = 2 for both microsatellites and concatenated nuclear sequences. Criollo trees were assigned together with the Guatemalan and Mexican races. Pearson correlation was significant between expected heterozygocities and elevation. Mantel test was low (r2 = 0.0097, p = 0.015) but significant demonstrating isolation by distance. Grafting is suitable between criollo trees and Hass variety is possible since both avocados are produced within the same altitudes.

PSXII-6 Landscape genetics used to identify gene bank beef cattle collection completeness and gaps

Gene banks (GB) primary goal is to capture genetic diversity among livestock breeds. Genetic diversity assessments by US GB have used pedigrees and genetic markers. Landscape genetics (LG), is a third approach for evaluating germplasm collections and genetic resources. We evaluated the GB’s beef collection using LG for the purpose of assessing collection gaps/completeness by using geographic information systems. The current beef cattle collection contains 3,916 animals from 11 Bos indicus (including composite, BI), and 40 Bos taurus British (BTB) and Bos taurus continental (BTC) breeds. Each GB animal was georeferenced by latitude and longitude. In addition, county level satellite imagery of the continental US was obtained and included: temperature, humidity, precipitation, and normalized difference vegetation index (NDVI). Temperature–humidity index (THI) was computed from temperature and humidity by county. In addition, USDA beef cattle statistics by county were used in mapping overlays. There was a high correspondence between in-situ cattle density and GB collection throughout the mid-west and extending to both borders. Evaluating genetic groups demonstrated that BI were derived from the Gulf Coast region, while BTB and BTC shared a distribution throughout the mid-west. The collection’s BTB were also sourced from the inter-mountain west. All environmental parameters were combined to identify similar environmental conditions where germplasm had already been collected. Through this process future geographies for sampling genetic groups were apparent. New collection areas should include the Great Basin, west Texas, New Mexico and Arizona. Further BI collections should be performed in low THI score areas and BTB and BTC collections in high THI areas is needed. Using GIS/LG adds a new perspective and resolution for future collections to ensure cattle that are adapted to a particular environment are added to the collection.

Testing concordance and conflict in spatial replication of landscape genetics inferences

The field of landscape genetics relates habitat features and genetic information to infer dispersal and genetic connectivity between populations or individuals distributed across a landscape. Such studies usually focus on a small portion of a species range, and the degree to which these geographically restricted results can be extrapolated to different areas of a species range remains poorly understood. Studies that have focused on spatial replication in landscape genetics processes either evaluate a small number of sites, are informed by a small set of genetic markers, analyze only a small subset of environmental variables, or implement models that do not fully explore parameter space. Here, we used a broadly distributed ectothermic lizard (Sceloporus occidentalis, Western Fence lizard) as a model species to evaluate the full role of topography, climate, vegetation, and roads on dispersal and genetic differentiation. We conducted landscape genetics analyses in five areas within the Sierra Nevada mountain range, using thousands of ddRAD genetic markers distributed across the genome, implemented in the landscape genetics program ResistanceGA. Across study areas, we found a great deal of consistency in the variables impacting genetic connectivity, but also noted site-specific differences in the factors in each study area. High-elevation colder areas were consistently found to be barriers to gene flow, as were areas of high ruggedness and slope. High temperature seasonality and high precipitation during the winter wet season also presented a substantial barrier to gene flow in a majority of study areas. The effect of other landscape variables on genetic differentiation was more idiosyncratic and depended on specific attributes at each site. Vegetation type was found to substantially affect gene flow only in the southernmost Sequoia site, likely due to a higher proportion of desert habitat here, thereby fragmenting habitats that have lower costs to dispersal. The effect of roads also varied between sites and may be related to differences in road usage and amount of traffic in each area. Across study areas, canyons were always substantially implicated as facilitators to dispersal and key features linking populations and maintaining genetic connectivity across landscapes. We emphasize that spatial data layers are complex and multidimensional, and a careful consideration of associations between variables is vital to form sound conclusions about the critical factors affecting dispersal and genetic connectivity across space.