Hybridizations between Musa species and subspecies, enabled by their transport via human migration, were proposed to have played an important role in banana domestication. We exploited sequencing data of 226 Musaceae accessions, including wild and cultivated accessions, to characterize the inter(sub)specific hybridization pattern that gave rise to cultivated bananas. We identified 11 genetic pools that contributed to cultivars, including two contributors of unknown origin. Informative alleles for each of these genetic pools were pinpointed and used to obtain genome ancestry mosaics of accessions. Diploid and triploid cultivars had genome mosaics involving three up to possibly seven contributors. The simplest mosaics were found for some diploid cultivars from New Guinea, combining three contributors, i.e., banksii and zebrina representing Musa acuminata subspecies and, more unexpectedly, the New Guinean species Musa schizocarpa. Breakpoints of M. schizocarpa introgressions were found to be conserved between New Guinea cultivars and the other analyzed diploid and triploid cultivars. This suggests that plants bearing these M. schizocarpa introgressions were transported from New Guinea and gave rise to currently cultivated bananas. Many cultivars showed contrasted mosaics with predominant ancestry from their geographical origin across Southeast Asia to New Guinea. This revealed that further diversification occurred in different Southeast Asian regions through hybridization with other Musa (sub)species, including two unknown ancestors that we propose to be M. acuminata ssp. halabanensis and a yet to be characterized M. acuminata subspecies. These results highlighted a dynamic crop formation process that was initiated in New Guinea, with subsequent diversification throughout Southeast Asia.
Deciphering microbiota functions is crucial to predict ecosystem sustainability in response to global change. High-throughput sequencing at the individual or community level has revolutionized our understanding of microbial ecology, leading to the big data era and improving our ability to link microbial diversity with microbial functions. Recent advances in bioinformatics have been key for developing functional prediction tools based on DNA metabarcoding data and using taxonomic gene information. This cheaper approach in every aspect serves as an alternative to shotgun sequencing. Although these tools are increasingly used by ecologists, an objective evaluation of their modularity, portability, and robustness is lacking. Here, we reviewed 100 scientific papers on functional inference and ecological trait assignment to rank the advantages, specificities, and drawbacks of these tools, using a scientific benchmarking. To date, inference tools have been mainly devoted to bacterial functions, and ecological trait assignment tools, to fungal functions. A major limitation is the lack of reference genomes—compared with the human microbiota—especially for complex ecosystems such as soils. Finally, we explore applied research prospects. These tools are promising and already provide relevant information on ecosystem functioning, but standardized indicators and corresponding repositories are still lacking that would enable them to be used for operational diagnosis.
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