Reconstructing the history of founder events using genome-wide patterns of allele sharing across individuals.

Founder events play a critical role in shaping genetic diversity, fitness and disease risk in a population. Yet our understanding of the prevalence and distribution of founder events in humans and other species remains incomplete, as most existing methods require large sample sizes or phased genomes. Thus, we developed ASCEND that measures the correlation in allele sharing between pairs of individuals across the genome to infer the age and strength of founder events. We show that ASCEND can reliably estimate the parameters of founder events under a range of demographic scenarios. We then apply ASCEND to two species with contrasting evolutionary histories: ~460 worldwide human populations and ~40 modern dog breeds. In humans, we find that over half of the analyzed populations have evidence for recent founder events, associated with geographic isolation, modes of sustenance, or cultural practices such as endogamy. Notably, island populations have lower population sizes than continental groups and most hunter-gatherer, nomadic and indigenous groups have evidence of recent founder events. Many present-day groups--including Native Americans, Oceanians and South Asians--have experienced more extreme founder events than Ashkenazi Jews who have high rates of recessive diseases due their known history of founder events. Using ancient genomes, we show that the strength of founder events differs markedly across geographic regions and time--with three major founder events related to the peopling of Americas and a trend in decreasing strength of founder events in Europe following the Neolithic transition and steppe migrations. In dogs, we estimate extreme founder events in most breeds that occurred in the last 25 generations, concordant with the establishment of many dog breeds during the Victorian times. Our analysis highlights a widespread history of founder events in humans and dogs and elucidates some of the demographic and cultural practices related to these events.

Ecological and genomic vulnerability to climate change across native populations of Robusta coffee (Coffea canephora).

The assessment of population vulnerability under climate change is crucial for planning conservation as well as for ensuring food security. Coffea canephora is, in its native habitat, an understorey tree that is mainly distributed in the lowland rainforests of tropical Africa. Also known as Robusta, its commercial value constitutes a significant revenue for many human populations in tropical countries. Comparing ecological and genomic vulnerabilities within the species' native range can provide valuable insights about habitat loss and the species' adaptive potential, allowing to identify genotypes that may act as a resource for varietal improvement. By applying species distribution models, we assessed ecological vulnerability as the decrease in climatic suitability under future climatic conditions from 492 occurrences. We then quantified genomic vulnerability (or risk of maladaptation) as the allelic composition change required to keep pace with predicted climate change. Genomic vulnerability was estimated from genomic environmental correlations throughout the native range. Suitable habitat was predicted to diminish to half its size by 2050, with populations near coastlines and around the Congo River being the most vulnerable. Whole-genome sequencing revealed 165 candidate SNPs associated with climatic adaptation in C. canephora, which were located in genes involved in plant response to biotic and abiotic stressors. Genomic vulnerability was higher for populations in West Africa and in the region at the border between DRC and Uganda. Despite an overall low correlation between genomic and ecological vulnerability at broad scale, these two components of vulnerability overlap spatially in ways that may become damaging. Genomic vulnerability was estimated to be 23% higher in populations where habitat will be lost in 2050 compared to regions where habitat will remain suitable. These results highlight how ecological and genomic vulnerabilities are relevant when planning on how to cope with climate change regarding an economically important species.

Adaptive potential of Coffea canephora from Uganda in response to climate change.

Understanding vulnerabilities of plant populations to climate change could help preserve their biodiversity and reveal new elite parents for future breeding programmes. To this end, landscape genomics is a useful approach for assessing putative adaptations to future climatic conditions, especially in long-lived species such as trees. We conducted a population genomics study of 207 Coffea canephora trees from seven forests along different climate gradients in Uganda. For this, we sequenced 323 candidate genes involved in key metabolic and defence pathways in coffee. Seventy-one single nucleotide polymorphisms (SNPs) were found to be significantly associated with bioclimatic variables, and were thereby considered as putatively adaptive loci. These SNPs were linked to key candidate genes, including transcription factors, like DREB-like and MYB family genes controlling plant responses to abiotic stresses, as well as other genes of organoleptic interest, such as the DXMT gene involved in caffeine biosynthesis and a putative pest repellent. These climate-associated genetic markers were used to compute genetic offsets, predicting population responses to future climatic conditions based on local climate change forecasts. Using these measures of maladaptation to future conditions, substantial levels of genetic differentiation between present and future diversity were estimated for all populations and scenarios considered. The populations from the forests Zoka and Budongo, in the northernmost zone of Uganda, appeared to have the lowest genetic offsets under all predicted climate change patterns, while populations from Kalangala and Mabira, in the Lake Victoria region, exhibited the highest genetic offsets. The potential of these findings in terms of ex situ conservation strategies are discussed.

Genetic diversity of native and cultivated Ugandan Robusta coffee (Coffea canephora Pierre ex A. Froehner): Climate influences, breeding potential and diversity conservation.

Wild genetic resources and their ability to adapt to environmental change are critically important in light of the projected climate change, while constituting the foundation of agricultural sustainability. To address the expected negative effects of climate change on Robusta coffee trees (Coffea canephora), collecting missions were conducted to explore its current native distribution in Uganda over a broad climatic range. Wild material from seven forests could thus be collected. We used 19 microsatellite (SSR) markers to assess genetic diversity and structure of this material as well as material from two ex-situ collections and a feral population. The Ugandan C. canephora diversity was then positioned relative to the species' global diversity structure. Twenty-two climatic variables were used to explore variations in climatic zones across the sampled forests. Overall, Uganda's native C. canephora diversity differs from other known genetic groups of this species. In northwestern (NW) Uganda, four distinct genetic clusters were distinguished being from Zoka, Budongo, Itwara and Kibale forests A large southern-central (SC) cluster included Malabigambo, Mabira, and Kalangala forest accessions, as well as feral and cultivated accessions, suggesting similarity in genetic origin and strong gene flow between wild and cultivated compartments. We also confirmed the introduction of Congolese varieties into the SC region where most Robusta coffee production takes place. Identified populations occurred in divergent environmental conditions and 12 environmental variables significantly explained 16.3% of the total allelic variation across populations. The substantial genetic variation within and between Ugandan populations with different climatic envelopes might contain adaptive diversity to cope with climate change. The accessions that we collected have substantially enriched the diversity hosted in the Ugandan collections and thus contribute to ex situ conservation of this vital genetic resource. However, there is an urgent need to develop strategies to enhance complementary in-situ conservation of Coffea canephora in native forests in northwestern Uganda.

McSwan: A joint site frequency spectrum method to detect and date selective sweeps across multiple population genomes.

Inferring the mode and tempo of natural selection helps further our understanding of adaptation to past environmental changes. Here, we introduce McSwan, a method to detect and date past and recent natural selection events in the case of a hard sweep. The method is based on the comparison of site frequency spectra obtained under various demographic models that include selection. McSwan demonstrated high power (high sensitivity and specificity) in capturing hard selective sweep events without requiring haplotype phasing. It performed slightly better than SweeD when the recent effective population size was low and the genomic region was small. We then applied our method to a European (CEU) and an African (LWK) human re-sequencing data set. Most hard sweeps were detected in the CEU population (96%). Moreover, hard sweeps in the African population were estimated to have occurred further back in time (mode: 43,625 years BP) compared to those of Europeans (mode: 24,850 years BP). Most of the estimated ages of hard sweeps in Europeans were associated with the Last Glacial Maximum and were enriched in immunity-associated genes.

Development and evaluation of a genome-wide Coffee 8.5K SNP array and its application for high-density genetic mapping and for investigating the origin of Coffea arabica L.

Coffee species such as Coffea canephora P. (Robusta) and C. arabica L. (Arabica) are important cash crops in tropical regions around the world. C. arabica is an allotetraploid (2n = 4x = 44) originating from a hybridization event of the two diploid species C. canephora and C. eugenioides (2n = 2x = 22). Interestingly, these progenitor species harbour a greater level of genetic variability and are an important source of genes to broaden the narrow Arabica genetic base. Here, we describe the development, evaluation and use of a single-nucleotide polymorphism (SNP) array for coffee trees. A total of 8580 unique and informative SNPs were selected from C. canephora and C. arabica sequencing data, with 40% of the SNP located in annotated genes. In particular, this array contains 227 markers associated to 149 genes and traits of agronomic importance. Among these, 7065 SNPs (~82.3%) were scorable and evenly distributed over the genome with a mean distance of 54.4 Kb between markers. With this array, we improved the Robusta high-density genetic map by adding 1307 SNP markers, whereas 945 SNPs were found segregating in the Arabica mapping progeny. A panel of C. canephora accessions was successfully discriminated and over 70% of the SNP markers were transferable across the three species. Furthermore, the canephora-derived subgenome of C. arabica was shown to be more closely related to C. canephora accessions from northern Uganda than to other current populations. These validated SNP markers and high-density genetic maps will be useful to molecular genetics and for innovative approaches in coffee breeding.

Two disjunct Pleistocene populations and anisotropic postglacial expansion shaped the current genetic structure of the relict plant Amborella trichopoda.

Past climate fluctuations shaped the population dynamics of organisms in space and time, and have impacted their present intra-specific genetic structure. Demo-genetic modelling allows inferring the way past demographic and migration dynamics have determined this structure. Amborella trichopoda is an emblematic relict plant endemic to New Caledonia, widely distributed in the understory of non-ultramafic rainforests. We assessed the influence of the last glacial climates on the demographic history and the paleo-distribution of 12 Amborella populations covering the whole current distribution. We performed coalescent genetic modelling of these dynamics, based on both whole-genome resequencing and microsatellite genotyping data. We found that the two main genetic groups of Amborella were shaped by the divergence of two ancestral populations during the last glacial maximum. From 12,800 years BP, the South ancestral population has expanded 6.3-fold while the size of the North population has remained stable. Recent asymmetric gene flow between the groups further contributed to the phylogeographical pattern. Spatially explicit coalescent modelling allowed us to estimate the location of ancestral populations with good accuracy (< 22 km) and provided indications regarding the mid-elevation pathways that facilitated post-glacial expansion.

Language: A fresh concept to integrate syntactic and semantic information in life sciences.

Several fields in biology tend to view the concept of information from one or the other of two extreme positions. Exclusionists base their stance of total rejection on gene-centrism and gene-determinism, typified by the recently-established endo-Darwinist school of life sciences. At the other end of the spectrum, there is total acceptance, as in the newly developed information-centred paradigms that populate biosemiotics. We propose in this paper to split the informational concepts into two irreducible (but linked) poles: the syntactic (concerned with the quantification of the information structure or complexity in a system), and the semantic (concerned with the organization rules and causality weights of interactions in a system). We claim that the past and present uses of the concept could then be classified as various degrees of oscillation between the two poles. The concept of language presents itself as a good tool with which to bridge the syntactic and the semantic poles, combining as it does the form-related and the meaning-related aspects of information, while methodologically supporting formal grammatical models in life sciences. We aim to show, at the same time, that neither of these poles alone can suffice to efficiently and holistically describe, model, and predict natural phenomena.

The Amborella vacuolar processing enzyme family.

Most vacuolar proteins are synthesized on rough endoplasmic reticulum as proprotein precursors and then transported to the vacuoles, where they are converted into their respective mature forms by vacuolar processing enzymes (VPEs). In the case of the seed storage proteins, this process is of major importance, as it conditions the establishment of vigorous seedlings. Toward the goal of identifying proteome signatures that could be associated with the origin and early diversification of angiosperms, we previously characterized the 11S-legumin-type seed storage proteins from Amborella trichopoda, a rainforest shrub endemic to New Caledonia that is also the probable sister to all other angiosperms (Amborella Genome Project, 2013). In the present study, proteomic and genomic approaches were used to characterize the VPE family in this species. Three genes were found to encode VPEs in the Amborella's genome. Phylogenetic analyses showed that the Amborella sequences grouped within two major clades of angiosperm VPEs, indicating that the duplication that generated the ancestors of these clades occurred before the most recent common ancestor of living angiosperms. A further important duplication within the VPE family appears to have occurred in common ancestor of the core eudicots, while many more recent duplications have also occurred in specific taxa, including both Arabidopsis thaliana and Amborella. An analysis of natural genetic variation for each of the three Amborella VPE genes revealed the absence of selective forces acting on intronic and exonic single-nucleotide polymorphisms among several natural Amborella populations in New Caledonia.