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Biology subjects

Gress, T.

Publications and source records attributed to Gress, T..

2 recordsLinked to original sources

Museomic approaches to genotype historic Cinchona barks

Over the last few centuries, millions of plant specimens have been collected and stored within herbaria and biocultural collections. They therefore represent a considerable resource for a broad range of scientific uses. However, collections degrade over time, and it is therefore increasingly difficult to characterise their genetic signatures. Here, we genotyped highly degraded Cinchona barks and leaves from herbaria using two separate high-throughput sequencing methods (HtS) and compared their performance. We subsequently genotyped specimens using genome skimming, the most commonly performed high-throughput sequencing (HtS) technique. We additionally used a recently developed capture bait set (Angiosperm353) for a target enrichment approach. Specifically, phylogenomic analyses of modern leaf and historical barks of Cinchona were performed, including 23 historical barks and six fresh leaf specimens. We found that samples degraded over time, which directly reduced the quantity and quality of the data produced by both methodologies (in terms of reads mapped to the references). However, we found that both approaches generated enough data to infer phylogenetic relationships, even between highly degraded specimens that are over 230 years old. However, the target capture kit produced data for target nuclear loci and also chloroplast data, which allowed for phylogenies to be inferred from both genomes, whereas it was only possible to use chloroplast data using genome skimming. We therefore find the Angiosperms353 target capture kit a powerful alternative to genome skimming, which can be used to obtain more information from herbarium specimens, and ultimately additional cultural benefits.

genomics↗

A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer

Pancreatic cancer (PC) is a complex disease in which both non-genetic and genetic factors interplay. To-date, 40 GWAS hits have been associated with PC risk in individuals of European descent, explaining 4.1% of the phenotypic variance. Here, we complemented a classical new PC GWAS (1D) with spatial autocorrelation analysis (2D) and Hi-C maps (3D) to gain additional insight into the inherited basis of PC. In-silico functional analysis of public genomic information allowed prioritization of potentially relevant candidate variants. We replicated 17/40 previous PC-GWAS hits and identified novel variants with potential biological functions. The spatial autocorrelation approach prioritized low MAF variants not detected by GWAS. These were further expanded via 3D interactions to 54 target regions with high functional relevance. This multi-step strategy, combined with an in-depth in-silico functional analysis, offers a comprehensive approach to advance the study of PC genetic susceptibility and could be applied to other diseases.

genetics↗