EBP-Colombia and the bioeconomy: Genomics in the service of biodiversity conservation and sustainable development.

The 2016 Peace Agreement has increased access to Colombia's unique ecosystems, which remain understudied and increasingly under threat. The Colombian government has recently announced its National Bioeconomic Strategy (NBS), founded on the sustainable characterization, management, and conservation of the nation's biodiversity as a means to achieve sustainability and peace. Molecular tools will accelerate such endeavors, but capacity remains limited in Colombia. The Earth Biogenome Project's (EBP) objective is to characterize the genomes of all eukaryotic life on Earth through networks of partner institutions focused on sequencing either specific taxa or eukaryotic communities at regional or national scales. Colombia's immense biodiversity and emerging network of stakeholders have inspired the creation of the national partnership "EBP-Colombia." Here, we discuss how this Colombian-driven collaboration between government, academia, and the private sector is integrating research with sustainable, environmentally focused strategies to develop Colombia's postconflict bioeconomy and conserve biological and cultural diversity. EBP-Colombia will accelerate the uptake of technology and promote partnership and exchange of knowledge among Colombian stakeholders and the EBP's global network of experts; assist with conservation strategies to preserve Colombia's vast biological wealth; and promote innovative approaches among public and private institutions in sectors such as agriculture, tourism, recycling, and medicine. EBP-Colombia can thus support Colombia's NBS with the objective of sustainable and inclusive development to address the many social, environmental, and economic challenges, including conflict, inequality, poverty, and low agricultural productivity, and so, offer an alternative model for economic development that similarly placed countries can adopt.

Unsupervised genome-wide recognition of local relationship patterns.

BACKGROUND: Phenomena such as incomplete lineage sorting, horizontal gene transfer, gene duplication and subsequent sub- and neo-functionalisation can result in distinct local phylogenetic relationships that are discordant with species phylogeny. In order to assess the possible biological roles for these subdivisions, they must first be identified and characterised, preferably on a large scale and in an automated fashion. RESULTS: We developed Saguaro, a combination of a Hidden Markov Model (HMM) and a Self Organising Map (SOM), to characterise local phylogenetic relationships among aligned sequences using cacti, matrices of pair-wise distance measures. While the HMM determines the genomic boundaries from aligned sequences, the SOM hypothesises new cacti in an unsupervised and iterative fashion based on the regions that were modelled least well by existing cacti. After testing the software on simulated data, we demonstrate the utility of Saguaro by testing two different data sets: (i) 181 Dengue virus strains, and (ii) 5 primate genomes. Saguaro identifies regions under lineage-specific constraint for the first set, and genomic segments that we attribute to incomplete lineage sorting in the second dataset. Intriguingly for the primate data, Saguaro also classified an additional ~3% of the genome as most incompatible with the expected species phylogeny. A substantial fraction of these regions was found to overlap genes associated with both the innate and adaptive immune systems. CONCLUSIONS: Saguaro detects distinct cacti describing local phylogenetic relationships without requiring any a priori hypotheses. We have successfully demonstrated Saguaro's utility with two contrasting data sets, one containing many members with short sequences (Dengue viral strains: n = 181, genome size = 10,700 nt), and the other with few members but complex genomes (related primate species: n = 5, genome size = 3 Gb), suggesting that the software is applicable to a wide variety of experimental populations. Saguaro is written in C++, runs on the Linux operating system, and can be downloaded from http://saguarogw.sourceforge.net/.