Amélioration Génétique et Adaptation des Plantes méditerranéennes et tropicales

Understanding the functional consequences of genetic variation, and how it affects complex human disease and quantitative traits, remains a critical challenge for biomedicine. We present an analysis of RNA sequencing data from 1641 samples across 43 tissues from 175 individuals, generated as part of the pilot phase of the Genotype-Tissue Expression (GTEx) project. We describe the landscape of gene expression across tissues, catalog thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants, describe complex network relationships, and identify signals from genome-wide association studies explained by eQTLs. These findings provide a systematic understanding of the cellular and biological consequences of human genetic variation and of the heterogeneity of such effects among a diverse set of human tissues.

Here we analyse genetic variation, population structure and diversity among 3,010 diverse Asian cultivated rice (Oryza sativa L.) genomes from the 3,000 Rice Genomes Project. Our results are consistent with the five major groups previously recognized, but also suggest several unreported subpopulations that correlate with geographic location. We identified 29 million single nucleotide polymorphisms, 2.4 million small indels and over 90,000 structural variations that contribute to within- and between-population variation. Using pan-genome analyses, we identified more than 10,000 novel full-length protein-coding genes and a high number of presence-absence variations. The complex patterns of introgression observed in domestication genes are consistent with multiple independent rice domestication events. The public availability of data from the 3,000 Rice Genomes Project provides a resource for rice genomics research and breeding.

INTRODUCTION: The PCR-based analysis of homologous genes has become one of the most powerful approaches for species detection and identification, particularly with the recent availability of Next Generation Sequencing platforms (NGS) making it possible to identify species composition from a broad range of environmental samples. Identifying species from these samples relies on the ability to match sequences with reference barcodes for taxonomic identification. Unfortunately, most studies of environmental samples have targeted ribosomal markers, despite the fact that the mitochondrial Cytochrome c Oxidase subunit I gene (COI) is by far the most widely available sequence region in public reference libraries. This is largely because the available versatile ("universal") COI primers target the 658 barcoding region, whose size is considered too large for many NGS applications. Moreover, traditional barcoding primers are known to be poorly conserved across some taxonomic groups. RESULTS: We first design a new PCR primer within the highly variable mitochondrial COI region, the "mlCOIintF" primer. We then show that this newly designed forward primer combined with the "jgHCO2198" reverse primer to target a 313 bp fragment performs well across metazoan diversity, with higher success rates than versatile primer sets traditionally used for DNA barcoding (i.e. LCO1490/HCO2198). Finally, we demonstrate how the shorter COI fragment coupled with an efficient bioinformatics pipeline can be used to characterize species diversity from environmental samples by pyrosequencing. We examine the gut contents of three species of planktivorous and benthivorous coral reef fish (family: Apogonidae and Holocentridae). After the removal of dubious COI sequences, we obtained a total of 334 prey Operational Taxonomic Units (OTUs) belonging to 14 phyla from 16 fish guts. Of these, 52.5% matched a reference barcode (>98% sequence similarity) and an additional 32% could be assigned to a higher taxonomic level using Bayesian assignment. CONCLUSIONS: The molecular analysis of gut contents targeting the 313 COI fragment using the newly designed mlCOIintF primer in combination with the jgHCO2198 primer offers enormous promise for metazoan metabarcoding studies. We believe that this primer set will be a valuable asset for a range of applications from large-scale biodiversity assessments to food web studies.

The sequencing and analysis of the banana genome is reported; these results inform plant phylogenetic relationships and genome evolution, and provide a resource for future genetic improvement of this important crop species. Bananas (Musa spp.) are a staple food and a major source of income in many tropical and subtropical countries. This paper reports the sequencing and analysis of the banana genome. This is the first non-grass monocotyledon to have its genome sequenced, providing an important bridge for comparative genome analysis in plants. Global banana production is under threat from increasingly well-adapted pests and diseases, so the availability of the genome sequence is an important resource for future crop development and improvement. Bananas (Musa spp.), including dessert and cooking types, are giant perennial monocotyledonous herbs of the order Zingiberales, a sister group to the well-studied Poales, which include cereals. Bananas are vital for food security in many tropical and subtropical countries and the most popular fruit in industrialized countries1. The Musa domestication process started some 7,000 years ago in Southeast Asia. It involved hybridizations between diverse species and subspecies, fostered by human migrations2, and selection of diploid and triploid seedless, parthenocarpic hybrids thereafter widely dispersed by vegetative propagation. Half of the current production relies on somaclones derived from a single triploid genotype (Cavendish)1. Pests and diseases have gradually become adapted, representing an imminent danger for global banana production3,4. Here we describe the draft sequence of the 523-megabase genome of a Musa acuminata doubled-haploid genotype, providing a crucial stepping-stone for genetic improvement of banana. We detected three rounds of whole-genome duplications in the Musa lineage, independently of those previously described in the Poales lineage and the one we detected in the Arecales lineage. This first monocotyledon high-continuity whole-genome sequence reported outside Poales represents an essential bridge for comparative genome analysis in plants. As such, it clarifies commelinid-monocotyledon phylogenetic relationships, reveals Poaceae-specific features and has led to the discovery of conserved non-coding sequences predating monocotyledon–eudicotyledon divergence.

The genus Citrus, comprising some of the most widely cultivated fruit crops worldwide, includes an uncertain number of species. Here we describe ten natural citrus species, using genomic, phylogenetic and biogeographic analyses of 60 accessions representing diverse citrus germ plasms, and propose that citrus diversified during the late Miocene epoch through a rapid southeast Asian radiation that correlates with a marked weakening of the monsoons. A second radiation enabled by migration across the Wallace line gave rise to the Australian limes in the early Pliocene epoch. Further identification and analyses of hybrids and admixed genomes provides insights into the genealogy of major commercial cultivars of citrus. Among mandarins and sweet orange, we find an extensive network of relatedness that illuminates the domestication of these groups. Widespread pummelo admixture among these mandarins and its correlation with fruit size and acidity suggests a plausible role of pummelo introgression in the selection of palatable mandarins. This work provides a new evolutionary framework for the genus Citrus. The origin, evolution and domestication of Citrus and the genealogy of the most important wild and cultivated citrus varieties. Citrus fruits are one of the most cultivated crops worldwide, yet the evolutionary relationships among citrus species remain uncertain. Daniel Rokhsar, Manuel Talon and colleagues analyse the genomes of 60 accessions that represent a diverse range of citrus species, including 30 newly sequenced citrus genomes. They characterize the diversity and evolution of citrus at the species level and identify interspecific citrus hybrids and admixtures—genetic mixing between previously isolated populations—that could be the result of human activities such as migration and agriculture. The authors identify 10 progenitor species and suggest that citrus originated in southeast Asia, diversifying during the late Miocene epoch through a rapid southeast Asian radiation that correlated with a changing climate, including the weakening of the monsoons. They also find extensive relatedness among mandarins and sweet oranges, showing a complex history of admixture during the domestication of these groups.

Multiple sequence alignment is a prerequisite for many evolutionary analyses. Multiple Alignment of Coding Sequences (MACSE) is a multiple sequence alignment program that explicitly accounts for the underlying codon structure of protein-coding nucleotide sequences. Its unique characteristic allows building reliable codon alignments even in the presence of frameshifts. This facilitates downstream analyses such as selection pressure estimation based on the ratio of nonsynonymous to synonymous substitutions. Here, we present MACSE v2, a major update with an improved version of the initial algorithm enriched with a complete toolkit to handle multiple alignments of protein-coding sequences. A graphical interface now provides user-friendly access to the different subprograms.

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 μmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

Coffee is a valuable beverage crop due to its characteristic flavor, aroma, and the stimulating effects of caffeine. We generated a high-quality draft genome of the species Coffea canephora, which displays a conserved chromosomal gene order among asterid angiosperms. Although it shows no sign of the whole-genome triplication identified in Solanaceae species such as tomato, the genome includes several species-specific gene family expansions, among them N-methyltransferases (NMTs) involved in caffeine production, defense-related genes, and alkaloid and flavonoid enzymes involved in secondary compound synthesis. Comparative analyses of caffeine NMTs demonstrate that these genes expanded through sequential tandem duplications independently of genes from cacao and tea, suggesting that caffeine in eudicots is of polyphyletic origin.

The plant hormone auxin is thought to provide positional information for patterning during development. It is still unclear, however, precisely how auxin is distributed across tissues and how the hormone is sensed in space and time. The control of gene expression in response to auxin involves a complex network of over 50 potentially interacting transcriptional activators and repressors, the auxin response factors (ARFs) and Aux/IAAs. Here, we perform a large-scale analysis of the Aux/IAA-ARF pathway in the shoot apex of Arabidopsis, where dynamic auxin-based patterning controls organogenesis. A comprehensive expression map and full interactome uncovered an unexpectedly simple distribution and structure of this pathway in the shoot apex. A mathematical model of the Aux/IAA-ARF network predicted a strong buffering capacity along with spatial differences in auxin sensitivity. We then tested and confirmed these predictions using a novel auxin signalling sensor that reports input into the signalling pathway, in conjunction with the published DR5 transcriptional output reporter. Our results provide evidence that the auxin signalling network is essential to create robust patterns at the shoot apex.

Zhong-Jian Liu, Lai-Qiang Huang, Yi-Bo Luo, Hong-Hwa Chen and Yves Van de Peer report the first genome sequence of a crassulacean acid metabolism (CAM) plant, the orchid Phalaenopsis equestris. They identify genes encoding CAM pathway enzymes and find that gene duplication was likely a key process in the evolution of CAM photosynthesis. Orchidaceae, renowned for its spectacular flowers and other reproductive and ecological adaptations, is one of the most diverse plant families. Here we present the genome sequence of the tropical epiphytic orchid Phalaenopsis equestris, a frequently used parent species for orchid breeding. P. equestris is the first plant with crassulacean acid metabolism (CAM) for which the genome has been sequenced. Our assembled genome contains 29,431 predicted protein-coding genes. We find that contigs likely to be underassembled, owing to heterozygosity, are enriched for genes that might be involved in self-incompatibility pathways. We find evidence for an orchid-specific paleopolyploidy event that preceded the radiation of most orchid clades, and our results suggest that gene duplication might have contributed to the evolution of CAM photosynthesis in P. equestris. Finally, we find expanded and diversified families of MADS-box C/D-class, B-class AP3 and AGL6-class genes, which might contribute to the highly specialized morphology of orchid flowers.

BACKGROUND: The oil palm (Elaeis guineensis Jacq.) is a perennial monocotyledonous tropical crop species that is now the world's number one source of edible vegetable oil, and the richest dietary source of provitamin A. While new elite genotypes from traditional breeding programs provide steady yield increases, the long selection cycle (10-12 years) and the large areas required to cultivate oil palm make genetic improvement slow and labor intensive. Molecular breeding programs have the potential to make significant impacts on the rate of genetic improvement but the limited molecular resources, in particular the lack of molecular markers for agronomic traits of interest, restrict the application of molecular breeding schemes for oil palm. RESULTS: In the current study, 6,103 non-redundant ESTs derived from cDNA libraries of developing vegetative and reproductive tissues were annotated and searched for simple sequence repeats (SSRs). Primer pairs from sequences flanking 289 EST-SSRs were tested to detect polymorphisms in elite breeding parents and their crosses. 230 of these amplified PCR products, 88 of which were polymorphic within the breeding material tested. A detailed analysis and annotation of the EST-SSRs revealed the locations of the polymorphisms within the transcripts, and that the main functional category was related to transcription and post-transcriptional regulation. Indeed, SSR polymorphisms were found in sequences encoding AP2-like, bZIP, zinc finger, MADS-box, and NAC-like transcription factors in addition to other transcriptional regulatory proteins and several RNA interacting proteins. CONCLUSIONS: The identification of new EST-SSRs that detect polymorphisms in elite breeding material provides tools for molecular breeding strategies. The identification of SSRs within transcripts, in particular those that encode proteins involved in transcriptional and post-transcriptional regulation, will allow insight into the functional roles of these proteins by studying the phenotypic traits that cosegregate with these markers. Finally, the oil palm EST-SSRs derived from vegetative and reproductive development will be useful for studies on the evolution of the functional diversity within the palm family.

Abstract Oaks are an important part of our natural and cultural heritage. Not only are they ubiquitous in our most common landscapes 1 but they have also supplied human societies with invaluable services, including food and shelter, since prehistoric times 2 . With 450 species spread throughout Asia, Europe and America 3 , oaks constitute a critical global renewable resource. The longevity of oaks (several hundred years) probably underlies their emblematic cultural and historical importance. Such long-lived sessile organisms must persist in the face of a wide range of abiotic and biotic threats over their lifespans. We investigated the genomic features associated with such a long lifespan by sequencing, assembling and annotating the oak genome. We then used the growing number of whole-genome sequences for plants (including tree and herbaceous species) to investigate the parallel evolution of genomic characteristics potentially underpinning tree longevity. A further consequence of the long lifespan of trees is their accumulation of somatic mutations during mitotic divisions of stem cells present in the shoot apical meristems. Empirical 4 and modelling 5 approaches have shown that intra-organismal genetic heterogeneity can be selected for 6 and provides direct fitness benefits in the arms race with short-lived pests and pathogens through a patchwork of intra-organismal phenotypes 7 . However, there is no clear proof that large-statured trees consist of a genetic mosaic of clonally distinct cell lineages within and between branches. Through this case study of oak, we demonstrate the accumulation and transmission of somatic mutations and the expansion of disease-resistance gene families in trees.

Sugarcane (Saccharum spp.) is a major crop for sugar and bioenergy production. Its highly polyploid, aneuploid, heterozygous, and interspecific genome poses major challenges for producing a reference sequence. We exploited colinearity with sorghum to produce a BAC-based monoploid genome sequence of sugarcane. A minimum tiling path of 4660 sugarcane BAC that best covers the gene-rich part of the sorghum genome was selected based on whole-genome profiling, sequenced, and assembled in a 382-Mb single tiling path of a high-quality sequence. A total of 25,316 protein-coding gene models are predicted, 17% of which display no colinearity with their sorghum orthologs. We show that the two species, S. officinarum and S. spontaneum, involved in modern cultivars differ by their transposable elements and by a few large chromosomal rearrangements, explaining their distinct genome size and distinct basic chromosome numbers while also suggesting that polyploidization arose in both lineages after their divergence.

Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2 ]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10% of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2 ] and temperature.

Abstract The Para rubber tree ( Hevea brasiliensis ) is an economically important tropical tree species that produces natural rubber, an essential industrial raw material. Here we present a high-quality genome assembly of this species (1.37 Gb, scaffold N50 = 1.28 Mb) that covers 93.8% of the genome (1.47 Gb) and harbours 43,792 predicted protein-coding genes. A striking expansion of the REF/SRPP (rubber elongation factor/small rubber particle protein) gene family and its divergence into several laticifer-specific isoforms seem crucial for rubber biosynthesis. The REF/SRPP family has isoforms with sizes similar to or larger than SRPP1 (204 amino acids) in 17 other plants examined, but no isoforms with similar sizes to REF1 (138 amino acids), the predominant molecular variant. A pivotal point in Hevea evolution was the emergence of REF1, which is located on the surface of large rubber particles that account for 93% of rubber in the latex (despite constituting only 6% of total rubber particles, large and small). The stringent control of ethylene synthesis under active ethylene signalling and response in laticifers resolves a longstanding mystery of ethylene stimulation in rubber production. Our study, which includes the re-sequencing of five other Hevea cultivars and extensive RNA-seq data, provides a valuable resource for functional genomics and tools for breeding elite Hevea cultivars.

BACKGROUND: Witches' broom disease (WBD) of cacao (Theobroma cacao L.), caused by Moniliophthora perniciosa, is the most important limiting factor for the cacao production in Brazil. Hence, the development of cacao genotypes with durable resistance is the key challenge for control the disease. Proteomic methods are often used to study the interactions between hosts and pathogens, therefore helping classical plant breeding projects on the development of resistant genotypes. The present study compared the proteomic alterations between two cacao genotypes standard for WBD resistance and susceptibility, in response to M. perniciosa infection at 72 h and 45 days post-inoculation; respectively the very early stages of the biotrophic and necrotrophic stages of the cacao x M. perniciosa interaction. RESULTS: A total of 554 proteins were identified, being 246 in the susceptible Catongo and 308 in the resistant TSH1188 genotypes. The identified proteins were involved mainly in metabolism, energy, defense and oxidative stress. The resistant genotype showed more expressed proteins with more variability associated with stress and defense, while the susceptible genotype exhibited more repressed proteins. Among these proteins, stand out pathogenesis related proteins (PRs), oxidative stress regulation related proteins, and trypsin inhibitors. Interaction networks were predicted, and a complex protein-protein interaction was observed. Some proteins showed a high number of interactions, suggesting that those proteins may function as cross-talkers between these biological functions. CONCLUSIONS: We present the first study reporting the proteomic alterations of resistant and susceptible genotypes in the T. cacao x M. perniciosa pathosystem. The important altered proteins identified in the present study are related to key biologic functions in resistance, such as oxidative stress, especially in the resistant genotype TSH1188, that showed a strong mechanism of detoxification. Also, the positive regulation of defense and stress proteins were more evident in this genotype. Proteins with significant roles against fungal plant pathogens, such as chitinases, trypsin inhibitors and PR 5 were also identified, and they may be good resistance markers. Finally, important biological functions, such as stress and defense, photosynthesis, oxidative stress and carbohydrate metabolism were differentially impacted with M. perniciosa infection in each genotype.

Thanks to genome-scale diversity data, present-day studies can provide a detailed view of how natural and cultivated species adapt to their environment and particularly to environmental gradients. However, due to their sensitivity, up-to-date studies might be more sensitive to undocumented demographic effects such as the pattern of migration and the reproduction regime. In this study, we provide guidelines for the use of popular or recently developed statistical methods to detect footprints of selection. We simulated 100 populations along a selective gradient and explored different migration models, sampling schemes and rates of self-fertilization. We investigated the power and robustness of eight methods to detect loci potentially under selection: three designed to detect genotype-environment correlations and five designed to detect adaptive differentiation (based on F(ST) or similar measures). We show that genotype-environment correlation methods have substantially more power to detect selection than differentiation-based methods but that they generally suffer from high rates of false positives. This effect is exacerbated whenever allele frequencies are correlated, either between populations or within populations. Our results suggest that, when the underlying genetic structure of the data is unknown, a number of robust methods are preferable. Moreover, in the simulated scenario we used, sampling many populations led to better results than sampling many individuals per population. Finally, care should be taken when using methods to identify genotype-environment correlations without correcting for allele frequency autocorrelation because of the risk of spurious signals due to allele frequency correlations between populations.

Early detection of salt stress is vital for plant survival and growth. Still, the molecular processes controlling early salt stress perception and signaling are not fully understood. Here, we identified salt-responsive ERF1 (SERF1), a rice (Oryza sativa) transcription factor (TF) gene that shows a root-specific induction upon salt and hydrogen peroxide (H2O2) treatment. Loss of SERF1 impairs the salt-inducible expression of genes encoding members of a mitogen-activated protein kinase (MAPK) cascade and salt tolerance-mediating TFs. Furthermore, we show that SERF1-dependent genes are H2O2 responsive and demonstrate that SERF1 binds to the promoters of MAPK kinase kinase6 (MAP3K6), MAPK5, dehydration-responsive element bindinG2A (DREB2A), and zinc finger protein179 (ZFP179) in vitro and in vivo. SERF1 also directly induces its own gene expression. In addition, SERF1 is a phosphorylation target of MAPK5, resulting in enhanced transcriptional activity of SERF1 toward its direct target genes. In agreement, plants deficient for SERF1 are more sensitive to salt stress compared with the wild type, while constitutive overexpression of SERF1 improves salinity tolerance. We propose that SERF1 amplifies the reactive oxygen species-activated MAPK cascade signal during the initial phase of salt stress and translates the salt-induced signal into an appropriate expressional response resulting in salt tolerance.

The development of functional-structural plant models requires an increasing amount of computer modelling. All these models are developed by different teams in various contexts and with different goals. Efficient and flexible computational frameworks are required to augment the interaction between these models, their reusability, and the possibility to compare them on identical datasets. In this paper, we present an open-source platform, OpenAlea, that provides a user-friendly environment for modellers, and advanced deployment methods. OpenAlea allows researchers to build models using a visual programming interface and provides a set of tools and models dedicated to plant modelling. Models and algorithms are embedded in OpenAlea 'components' with well defined input and output interfaces that can be easily interconnected to form more complex models and define more macroscopic components. The system architecture is based on the use of a general purpose, high-level, object-oriented script language, Python, widely used in other scientific areas. We present a brief rationale that underlies the architectural design of this system and we illustrate the use of the platform to assemble several heterogeneous model components and to rapidly prototype a complex modelling scenario.

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