Biology subjects

Burgarella, C.

Publications and source records attributed to Burgarella, C..

4 recordsLinked to original sources

bioRxiv2018

Adaptive introgression: an untapped evolutionary mechanism for crop adaptation

Global environmental changes strongly impact wild and domesticated species biology and their associated ecosystem services. For crops, global warming has led to significant changes in terms of phenology and/or yield. To respond to the agricultural challenges of this century, there is a strong need for harnessing the genetic variability of crops and adapting them to new conditions. Gene flow, from either the same species or a different species, may be an immediate primary source to widen genetic diversity and adaptions to various environments. When the incorporation of a foreign variant leads to an increase of the fitness of the recipient pool, it is referred to as \"adaptive introgression\". Crop species are excellent case studies of this phenomenon since their genetic variability has been considerably reduced over space and time but most of them continue exchanging genetic material with their wild relatives. In this paper, we review studies of adaptive introgression, presenting methodological approaches and challenges to detecting it. We pay particular attention to the potential of this evolutionary mechanism for the adaptation of crops. Furthermore, we discuss the importance of farmers knowledge and practices in shaping wild-to-crop gene flow. Finally, we argue that screening the wild introgression already existing in the cultivated gene pool may be an effective strategy for uncovering wild diversity relevant for crop adaptation to current environmental changes and for informing new breeding directions.

evolutionary biology↗

bioRxiv2018

Discontinuities in quinoa biodiversity in the dry Andes: an 18-century perspective based on allelic genotyping

History and environment shape crop biodiversity, particularly in areas with vulnerable human communities and ecosystems. Tracing crop biodiversity over time helps understand how rural societies cope with anthropogenic or climatic changes. Exceptionally well preserved ancient DNA of quinoa (Chenopodium quinoa Willd.) from the cold and arid Andes of Argentina has allowed us to track changes and continuities in quinoa diversity over 18 centuries, by coupling genotyping of 157 ancient and modern seeds by 24 SSR markers with cluster and coalescence analyses. Cluster analyses revealed clear population patterns separating modern and ancient quinoas. Coalescence-based analyses revealed that genetic drift within a single population cannot explain genetic differentiation among ancient and modern quinoas. The hypothesis of a genetic bottleneck related to the Spanish Conquest also does not seem to apply at a local scale. Instead, the most likely scenario is the replacement of preexisting quinoa gene pools with new ones of lower genetic diversity. This process occurred at least twice in the last 18 centuries: first, between the 6th and 12th centuries--a time of agricultural intensification well before the Inka and Spanish conquests--and then between the 13th century and today--a period marked by farming marginalization in the late 19th century likely due to a severe multidecadal drought. While these processes of local gene pool replacement do not imply losses of genetic diversity at the metapopulation scale, they support the view that gene pool replacement linked to social and environmental changes can result from opposite agricultural trajectories.

ecology↗

bioRxiv2018

Pervasive hybridizations in the history of wheat relatives

Bread wheat and durum wheat derive from an intricate evolutionary history of three genomes, namely A, B and D, present in both extent diploid and polyploid species. Despite its importance for wheat research, no consensus on the phylogeny of the wheat clade has emerged so far, possibly because of hybridizations and gene flows that make phylogeny reconstruction challenging. Recently, it has been proposed that the D genome originated from an ancient hybridization event between the A and B genomes1. However, the study only relied on four diploid wheat relatives when 13 species are accessible. Using transcriptome data from all diploid species and a new methodological approach, we provide the first comprehensive phylogenomic analysis of this group. Our analysis reveals that most species belong to the D-genome lineage and descend from the previously detected hybridization event, but with a more complex scenario and with a different parent than previously thought. If we confirmed that one parent was the A genome, we found that the second was not the B genome but the ancestor of Aegilops mutica (T genome), an overlooked wild species. We also unravel evidence of other massive gene flow events that could explain long-standing controversies in the classification of wheat relatives. We anticipate that these results will strongly affect future wheat research by providing a robust evolutionary framework and refocusing interest on understudied species. The new method we proposed should also be pivotal for further methodological developments to reconstruct species relationship with multiple hybridizations.

evolutionary biology↗

bioRxiv2017

Demographic inference through approximate-Bayesian-computation skyline plots

The skyline plot is a graphical representation of historical effective population sizes as a function of time. Past population sizes for these plots are estimated from genetic data, without a priori assumptions on the mathematical function defining the shape of the demographic trajectory. Because of this flexibility in shape, skyline plots can, in principle, provide realistic descriptions of the complex demographic scenarios that occur in natural populations. Currently, demographic estimates needed for skyline plots are estimated using coalescent samplers or a composite likelihood approach. Here, we provide a way to estimate historical effective population sizes using an Approximate Bayesian Computation (ABC) framework. We assess its performance using simulated and actual microsatellite datasets. Our method correctly retrieves the signal of contracting, constant and expanding populations, although the graphical shape of the plot is not always an accurate representation of the true demographic trajectory, particularly for recent changes in size and contracting populations. Because of the flexibility of ABC, similar approaches can be extended to other types of data, to multiple populations, or to other parameters that can change through time, such as the migration rate.

evolutionary biology↗