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Burbano, H. A.

Publications and source records attributed to Burbano, H. A..

4 recordsLinked to original sources

Mining ancient microbiomes using selective enrichment of damaged DNA molecules

BackgroundThe identification of bona fide microbial taxa in microbiomes derived from ancient and historical samples is complicated by the unavoidable mixture between DNA from ante- and post-mortem microbial colonizers. One possibility to distinguish between these sources of microbial DNA is querying for the presence of age-associated degradation patterns typical of ancient DNA (aDNA). The presence of uracils, resulting from cytosine deamination, has been detected ubiquitously in aDNA retrieved from diverse sources, and used as an authentication criterion. Here, we employ a library preparation method that separates molecules that carry uracils from those that do not for a set of samples that includes Neandertal remains, herbarium specimens and archaeological plant remains. ResultsWe show that sequencing DNA libraries enriched in molecules carrying uracils effectively amplifies age associated degradation patterns in microbial mixtures of ancient and historical origin. This facilitates the discovery of authentic ancient microbial taxa in cases where degradation patterns are difficult to detect due to large sequence divergence in microbial mixtures. Additionally, the relative enrichment of taxa in the uracil enriched fraction can help to identify bona fide ancient microbial taxa that could be missed using a more targeted approach. ConclusionsOur experiments show, that in addition to its use in enriching authentic endogenous DNA of organisms of interest, the selective enrichment of damaged DNA molecules can be a valuable tool in the discovery of ancient microbial taxa.

genomics

A map of climate change-driven natural selection in Arabidopsis thaliana

Through the lens of evolution, climate change is an agent of directional selection that forces populations to change and adapt, or face extinction. Current assessments of the risks associated with climate change1,2, however, do not typically take into account that natural selection can dramatically impact the genetic makeup of populations3. We made use of extensive genome information in Arabidopsis thaliana and measured how rainfall-manipulation affected the fitness of 517 natural lines grown in Spain and Germany. This allowed us to directly infer selection at the genetic level4. Natural selection was particularly strong in the hot-dry Spanish location, killing 63% of lines and significantly changing the frequency of [~]5% of all genome-wide variants. A significant proportion of this selection over variants could be predicted from climate (mis)match between experimental sites and the geographic areas of where variants are found (R2=29-52%). Field-validated predictions across the species range indicated that Mediterranean and Western Siberia populations -- at the edges of the species environmental limits -- currently experience the strongest climate-driven selection, and Central Europeans the weakest. With rapidly increasing droughts and rising temperatures in Europe5, we forecast a wave of directional selection moving North, putting many native A thaliana populations at evolutionary risk.

evolutionary biology

A rainfall-manipulation experiment with 517 Arabidopsis thaliana accessions

The gold standard for studying natural selection and adaptation in the wild is to quantify lifetime fitness of individuals from natural populations that have been grown together in a common garden, or that have been reciprocally transplanted. By combining fitness values with species traits and genome sequences, one can infer selection coefficients at the genetic level. Here we present a rainfall-manipulation experiment with 517 whole-genome sequenced natural accessions of the plant Arabidopsis thaliana spanning the global distribution of the species. The experiments were conducted in two field stations in contrasting climates, in the Mediterranean and in Central Europe, where we built rainout shelters and simulated high and low rainfall. Using custom image analysis we quantified fitness- and phenology-related traits for 23,154 pots, which contained about 14,500 plants growing independently, and over 310,000 plants growing in small populations (max. 30 plants). This large field experiment dataset, which associates fitness and ecologically-relevant traits with genomes, will provide an important resource to test eco-evolutionary genetic theories and to understand the potential evolutionary impacts of future climates on an important plant model species.

evolutionary biology

nQuire: A Statistical Framework For Ploidy Estimation Using Next Generation Sequencing

SummarynQuire is a statistical framework that distinguishes between diploids, triploids and tetraploids using next generation sequencing. The command-line tool models the distribution of base frequencies at variable sites using a Gaussian Mixture Model, and uses maximum likelihood to select the most plausible ploidy model.\n\nAvailability and ImplementationThe model is implemented as a stand-alone Linux command line tool in the C programming language and is available at github under the MIT licence. Please also refer to github.com/clwgg/nQuire for usage instructions. Contact: clemens.weiss@tuebingen.mpg.de or hernan.burbano@tuebingen.mpg.de

bioinformatics