Collaboration with UNICAMP - New paper: Ecological Genomics of Ischnosiphon puberulus in a waterlogging gradient of Amazonian riparian forests

In this study led by Prof. Clarisse Palma-Silva et al., from UNICAMP, we investigated the stress response pathways of the tropical ground-herb species Ischnosiphon puberulus, a monocot from the Marantaceae family, within Amazonian riparian forests, focusing on varying flooding regimes. The research was carried out in the Cupari River basin in the Brazilian Amazon, where samples were collected from two distinct types of forests: the predictably flooded Igapó forests and the less frequently flooded Terra firme forests. The study aimed to understand how environmental differences, particularly those related to flooding, drive differential gene expression and contribute to population genetic differentiation.

One of the significant accomplishments of this research is the assembly of the I. puberulus genome, marking the first complete genome assembly in the family Marantaceae. The genome assembly achieved high-quality chromosome-level resolution with many chromosomes being complete from telomere to telomere. This was accomplished using third-generation sequencing technologies, including PacBio HiFi sequencing and Hi-C for scaffolding. This advanced genome assembly facilitated a detailed transcriptomic analysis, which identified 4,326 differentially expressed transcripts between populations from Igapó and Terra firme environments. The enriched gene ontology terms highlighted associations with various environmental stress responses, such as water transport, root development, and oxidative stress. Notably, the study found that contrasting flooding conditions lead to significant genetic differentiation between populations, driven more by environmental isolation than by geographical distance. This research provides novel insights into the molecular basis of plant adaptation to environmental stress in highly biodiverse Neotropical ecosystems, revealing how I. puberulus copes with varying degrees of waterlogging and contributing to our understanding of adaptive divergence in Amazonian plants.

All the genomics and transcriptomics datasets underlying our findings are publicly available under the umbrella bioproject: PRJNA1099595.