GenGIS: A geospatial information system for genomic data

Abstract

The increasing availability of genetic sequence data associated with explicit geographic and ecological information is offering new opportunities to study the processes that shape biodiversity. The generation and testing of hypotheses using these data sets requires effective tools for mathematical and visual analysis that can integrate digital maps, ecological data, and large genetic, genomic, or metagenomic data sets. GenGIS is a free and open-source software package that supports the integration of digital map data with genetic sequences and environmental information from multiple sample sites. Essential bioinformatic and statistical tools are integrated into the software, allowing the user a wide range of analysis options for their sequence data. Data visualizations are combined with the cartographic display to yield a clear view of the relationship between geography and genomic diversity, with a particular focus on the hierarchical clustering of sites based on their similarity or phylogenetic proximity. Here we outline the features of GenGIS and demonstrate its application to georeferenced microbial metagenomic, HIV-1, and human mitochondrial DNA data sets.

Figure 1.

Clustering of Global Ocean Sampling (GOS) sites based on their shared phylogenetic diversity. Pie charts associated with each GOS site show the breakdown of 16S sequences by best-matching bacterial class, with rare groups collected together in the “other” category. Pie chart sizes are proportional to the total number of 16S sequences considered at each site. The clustering of sites obtained by weighted UniFrac is shown in the tree, with habitat type indicated by shape and color (cyan cross indicates embayment; circles, oceanic, [with orange, Atlantic Ocean; with yellow, Caribbean Sea]; purple triangle, estuary with low salinity; green triangle, estuary with typical oceanic salinity; pink square, freshwater lake). White branches in the tree indicate internal edges whose children cover multiple habitat types.

Figure 2.

Clustering of African nations based on phylogenetic diversity of HIV subtypes. The UPGMA clustering of countries based on their UniFrac scores is shown using a three-dimensional tree; the four subclusters discussed in the text and the countries they cover are indicated by coloring different subtrees orange, cyan, purple, and green. Location identifiers are mapped to the geographic center of each country, which is also identified with the standard two-letter country code.

Figure 3.

Map of Island Southeast Asia and Taiwan with hypothesized migration patterns of mtDNA haplogroup E1 encoded as geographic polylines. A triangle indicates the point of origin for each polyline on the island of Borneo. Most droplines connecting the geographic axis line to sample sites are omitted for clarity, but sites are colored according to their location relative to the proposed origin of haplogroup E1 and consequent migration route (Soares et al. 2008): Sulawesi (east) in orange, south Sundaland (south/southwest) in purple, south Wallacea (south/southeast) in green, and the northern points in pink. The optimal tree layout with 78 crossings is shown, with colored branches indicating leaves or groups of leaves that were exclusive to a single region once dereplication had been carried out (see Supplemental Methods). One southern subclade of E1 that contains both southeastern and southwestern sequences is highlighted, showing droplines that connect to its corresponding geographic locations.