Institut National de la Recherche Agronomique

The human genome contains many thousands of long noncoding RNAs (lncRNAs). While several studies have demonstrated compelling biological and disease roles for individual examples, analytical and experimental approaches to investigate these genes have been hampered by the lack of comprehensive lncRNA annotation. Here, we present and analyze the most complete human lncRNA annotation to date, produced by the GENCODE consortium within the framework of the ENCODE project and comprising 9277 manually annotated genes producing 14,880 transcripts. Our analyses indicate that lncRNAs are generated through pathways similar to that of protein-coding genes, with similar histone-modification profiles, splicing signals, and exon/intron lengths. In contrast to protein-coding genes, however, lncRNAs display a striking bias toward two-exon transcripts, they are predominantly localized in the chromatin and nucleus, and a fraction appear to be preferentially processed into small RNAs. They are under stronger selective pressure than neutrally evolving sequences-particularly in their promoter regions, which display levels of selection comparable to protein-coding genes. Importantly, about one-third seem to have arisen within the primate lineage. Comprehensive analysis of their expression in multiple human organs and brain regions shows that lncRNAs are generally lower expressed than protein-coding genes, and display more tissue-specific expression patterns, with a large fraction of tissue-specific lncRNAs expressed in the brain. Expression correlation analysis indicates that lncRNAs show particularly striking positive correlation with the expression of antisense coding genes. This GENCODE annotation represents a valuable resource for future studies of lncRNAs.

Abstract This paper discusses the advantages and disadvantages of the different methods that separate net ecosystem exchange (NEE) into its major components, gross ecosystem carbon uptake (GEP) and ecosystem respiration ( R eco ). In particular, we analyse the effect of the extrapolation of night‐time values of ecosystem respiration into the daytime; this is usually done with a temperature response function that is derived from long‐term data sets. For this analysis, we used 16 one‐year‐long data sets of carbon dioxide exchange measurements from European and US‐American eddy covariance networks. These sites span from the boreal to Mediterranean climates, and include deciduous and evergreen forest, scrubland and crop ecosystems. We show that the temperature sensitivity of R eco , derived from long‐term (annual) data sets, does not reflect the short‐term temperature sensitivity that is effective when extrapolating from night‐ to daytime. Specifically, in summer active ecosystems the long‐term temperature sensitivity exceeds the short‐term sensitivity. Thus, in those ecosystems, the application of a long‐term temperature sensitivity to the extrapolation of respiration from night to day leads to a systematic overestimation of ecosystem respiration from half‐hourly to annual time‐scales, which can reach >25% for an annual budget and which consequently affects estimates of GEP. Conversely, in summer passive (Mediterranean) ecosystems, the long‐term temperature sensitivity is lower than the short‐term temperature sensitivity resulting in underestimation of annual sums of respiration. We introduce a new generic algorithm that derives a short‐term temperature sensitivity of R eco from eddy covariance data that applies this to the extrapolation from night‐ to daytime, and that further performs a filling of data gaps that exploits both, the covariance between fluxes and meteorological drivers and the temporal structure of the fluxes. While this algorithm should give less biased estimates of GEP and R eco , we discuss the remaining biases and recommend that eddy covariance measurements are still backed by ancillary flux measurements that can reduce the uncertainties inherent in the eddy covariance data.

This paper reports the genome sequence of domesticated tomato, a major crop plant, and a draft sequence for its closest wild relative; comparative genomics reveal very little divergence between the two genomes but some important differences with the potato genome, another important food crop in the genus Solanum. Tomato (Solanum lycopersicum) is a major crop plant and a model system for fruit development. Solanum is one of the largest angiosperm genera1 and includes annual and perennial plants from diverse habitats. Here we present a high-quality genome sequence of domesticated tomato, a draft sequence of its closest wild relative, Solanum pimpinellifolium2, and compare them to each other and to the potato genome (Solanum tuberosum). The two tomato genomes show only 0.6% nucleotide divergence and signs of recent admixture, but show more than 8% divergence from potato, with nine large and several smaller inversions. In contrast to Arabidopsis, but similar to soybean, tomato and potato small RNAs map predominantly to gene-rich chromosomal regions, including gene promoters. The Solanum lineage has experienced two consecutive genome triplications: one that is ancient and shared with rosids, and a more recent one. These triplications set the stage for the neofunctionalization of genes controlling fruit characteristics, such as colour and fleshiness.

BACKGROUND AND AIM: A role for the intestinal microbial community (microbiota) in the onset and chronicity of Crohn's disease (CD) is strongly suspected. However, investigation of such a complex ecosystem is difficult, even with culture independent molecular approaches. METHODS: We used, for the first time, a comprehensive metagenomic approach to investigate the full range of intestinal microbial diversity. We used a fosmid vector to construct two libraries of genomic DNA isolated directly from faecal samples of six healthy donors and six patients with CD. Bacterial diversity was analysed by screening the two DNA libraries, each composed of 25,000 clones, for the 16S rRNA gene by DNA hybridisation. RESULTS: Among 1190 selected clones, we identified 125 non-redundant ribotypes mainly represented by the phyla Bacteroidetes and Firmicutes. Among the Firmicutes, 43 distinct ribotypes were identified in the healthy microbiota, compared with only 13 in CD (p<0.025). Fluorescent in situ hybridisation directly targeting 16S rRNA in faecal samples analysed individually (n=12) confirmed the significant reduction in the proportion of bacteria belonging to this phylum in CD patients (p<0.02). CONCLUSION: The metagenomic approach allowed us to detect a reduced complexity of the bacterial phylum Firmicutes as a signature of the faecal microbiota in patients with CD. It also indicated the presence of new bacterial species.

OBJECTIVE: to examine the clinical evidence reporting the prevalence of sarcopenia and the effect of nutrition and exercise interventions from studies using the consensus definition of sarcopenia proposed by the European Working Group on Sarcopenia in Older People (EWGSOP). METHODS: PubMed and Dialog databases were searched (January 2000-October 2013) using pre-defined search terms. Prevalence studies and intervention studies investigating muscle mass plus strength or function outcome measures using the EWGSOP definition of sarcopenia, in well-defined populations of adults aged ≥50 years were selected. RESULTS: prevalence of sarcopenia was, with regional and age-related variations, 1-29% in community-dwelling populations, 14-33% in long-term care populations and 10% in the only acute hospital-care population examined. Moderate quality evidence suggests that exercise interventions improve muscle strength and physical performance. The results of nutrition interventions are equivocal due to the low number of studies and heterogeneous study design. Essential amino acid (EAA) supplements, including ∼2.5 g of leucine, and β-hydroxy β-methylbutyric acid (HMB) supplements, show some effects in improving muscle mass and function parameters. Protein supplements have not shown consistent benefits on muscle mass and function. CONCLUSION: prevalence of sarcopenia is substantial in most geriatric settings. Well-designed, standardised studies evaluating exercise or nutrition interventions are needed before treatment guidelines can be developed. Physicians should screen for sarcopenia in both community and geriatric settings, with diagnosis based on muscle mass and function. Supervised resistance exercise is recommended for individuals with sarcopenia. EAA (with leucine) and HMB may improve muscle outcomes.

Biodiversity in agricultural landscapes can be increased with conversion of some production lands into 'more-natural'- unmanaged or extensively managed - lands. However, it remains unknown to what extent biodiversity can be enhanced by altering landscape pattern without reducing agricultural production. We propose a framework for this problem, considering separately compositional heterogeneity (the number and proportions of different cover types) and configurational heterogeneity (the spatial arrangement of cover types). Cover type classification and mapping is based on species requirements, such as feeding and nesting, resulting in measures of 'functional landscape heterogeneity'. We then identify three important questions: does biodiversity increase with (1) increasing heterogeneity of the more-natural areas, (2) increasing compositional heterogeneity of production cover types and (3) increasing configurational heterogeneity of production cover types? We discuss approaches for addressing these questions. Such studies should have high priority because biodiversity protection globally depends increasingly on maintaining biodiversity in human-dominated landscapes.

The loss of organic and inorganic carbon from roots into soil underpins nearly all the major changes that occur in the rhizosphere. In this review we explore the mechanistic basis of organic carbon and nitrogen flow in the rhizosphere. It is clear that C and N flow in the rhizosphere is extremely complex, being highly plant and environment dependent and varying both spatially and temporally along the root. Consequently, the amount and type of rhizodeposits (e.g. exudates, border cells, mucilage) remains highly context specific. This has severely limited our capacity to quantify and model the amount of rhizodeposition in ecosystem processes such as C sequestration and nutrient acquisition. It is now evident that C and N flow at the soil–root interface is bidirectional with C and N being lost from roots and taken up from the soil simultaneously. Here we present four alternative hypotheses to explain why high and low molecular weight organic compounds are actively cycled in the rhizosphere. These include: (1) indirect, fortuitous root exudate recapture as part of the root’s C and N distribution network, (2) direct re-uptake to enhance the plant’s C efficiency and to reduce rhizosphere microbial growth and pathogen attack, (3) direct uptake to recapture organic nutrients released from soil organic matter, and (4) for inter-root and root–microbial signal exchange. Due to severe flaws in the interpretation of commonly used isotopic labelling techniques, there is still great uncertainty surrounding the importance of these individual fluxes in the rhizosphere. Due to the importance of rhizodeposition in regulating ecosystem functioning, it is critical that future research focuses on resolving the quantitative importance of the different C and N fluxes operating in the rhizosphere and the ways in which these vary spatially and temporally.

An ordered draft sequence of the 17-gigabase hexaploid bread wheat ( Triticum aestivum ) genome has been produced by sequencing isolated chromosome arms. We have annotated 124,201 gene loci distributed nearly evenly across the homeologous chromosomes and subgenomes. Comparative gene analysis of wheat subgenomes and extant diploid and tetraploid wheat relatives showed that high sequence similarity and structural conservation are retained, with limited gene loss, after polyploidization. However, across the genomes there was evidence of dynamic gene gain, loss, and duplication since the divergence of the wheat lineages. A high degree of transcriptional autonomy and no global dominance was found for the subgenomes. These insights into the genome biology of a polyploid crop provide a springboard for faster gene isolation, rapid genetic marker development, and precise breeding to meet the needs of increasing food demand worldwide.

To select candidate populations of wild species to be given priority for conservation, genetic criteria gained from the study of molecular markers may be useful. Traditionally, diversity measures such as expected heterozygosity or percentage of polymorphic loci have been considered. For conservation we propose instead that priority should be given to measures of allelic richness. To standardize the results of allelic richness across populations, we used the technique of rarefaction. This technique allows evaluation of the expected number of different alleles among equal‐sized samples drawn from several different populations. We also show how the contribution of each population to total diversity can be partitioned into two components. The first is related to the level of diversity of the population and the second to its divergence from the other populations. For conservation purposes the uniqueness of a population—in terms of its allelic composition—may be at least as important as its diversity level. These new descriptors are illustrated by means of isozyme and chloroplast DNA data obtained for an endangered tree species, the argan tree of Morocco ( Argania spinosa (L.) Skeels). With these analyses the conservation value of the argan tree populations, especially those of two isolates present in the north of the country, can be better appreciated. The methods proposed to identify priority areas for conservation of the genetic resources of the argan tree are compared to those sometimes advocated in the case of reserve design, where one of the goals is to maximize species richness. Identificacón de Poblaciones para su Conservación en Base a Marcadores Genéticos Los criterios genéticos obtenidos del estudio de marcadores moleculares podrían ser útiles para seleccionar poblaciones de vida silvestre como candidatos con prioridad para su conservación. Tradicionalmente se consideran medidas de la diversidad como son la heterocigocidad esperada, o el porcentaje de loci polimórficos. Para medidas de conservación, nosotros proponemos en su lugar que la prioridad se enfoque en medidas de riqueza alélica. Para estandarizar los resultados de riqueza alélica entre problaciones, utilizamos una técnica de vacuidad. Esta técnica permite evaluar el número esperado de alelos entre muestras de igual tamaño obtenidas de diferentes poblaciones. Mostramos como la contribución de cada población a la diversidad total puede ser repartida en dos componentes; el primero esta relacionado con el nivel de diversidad de la población y el segundo con su divergencia de las otras poblaciones. Para propósitos de conservación, la singularidad de una población (en forma de composición alélica) puede ser por lo menos tan importante como lo es su nivel de diversidad, Estos nuevos elementos descriptivos son ilustrados mediante el uso de datos de DNA de isozima y cloroplasto para una especie de árbol en peligro, el árbol argan de Morocco ( Argania spinosa (L.) Skeels). Con estos análisis, el valor de conservación de las poblaciones del árbol argan puede ser apreciado mejor, especialmente para aquellas provenientes de dos grupos aislados del norte del país. Los métodos propuestos para la identificación de áreas prioritarias para la conservación de los recursos genéticos del árbol argan son comparados con aquellos utilizados en el diseño de reservas, donde una de las metas es la maximización de la riqueza de especies.

Mammalian cells were observed to die under conditions in which nutrients were depleted and, simultaneously, macroautophagy was inhibited either genetically (by a small interfering RNA targeting Atg5, Atg6/Beclin 1-1, Atg10, or Atg12) or pharmacologically (by 3-methyladenine, hydroxychloroquine, bafilomycin A1, or monensin). Cell death occurred through apoptosis (type 1 cell death), since it was reduced by stabilization of mitochondrial membranes (with Bcl-2 or vMIA, a cytomegalovirus-derived gene) or by caspase inhibition. Under conditions in which the fusion between lysosomes and autophagosomes was inhibited, the formation of autophagic vacuoles was enhanced at a preapoptotic stage, as indicated by accumulation of LC3-II protein, ultrastructural studies, and an increase in the acidic vacuolar compartment. Cells exhibiting a morphology reminiscent of (autophagic) type 2 cell death, however, recovered, and only cells with a disrupted mitochondrial transmembrane potential were beyond the point of no return and inexorably died even under optimal culture conditions. All together, these data indicate that autophagy may be cytoprotective, at least under conditions of nutrient depletion, and point to an important cross talk between type 1 and type 2 cell death pathways.

Barley (Hordeum vulgare L.) is among the world’s earliest domesticated and most important crop plants. It is diploid with a large haploid genome of 5.1 gigabases (Gb). Here we present an integrated and ordered physical, genetic and functional sequence resource that describes the barley gene-space in a structured whole-genome context. We developed a physical map of 4.98 Gb, with more than 3.90 Gb anchored to a high-resolution genetic map. Projecting a deep whole-genome shotgun assembly, complementary DNA and deep RNA sequence data onto this framework supports 79,379 transcript clusters, including 26,159 ‘high-confidence’ genes with homology support from other plant genomes. Abundant alternative splicing, premature termination codons and novel transcriptionally active regions suggest that post-transcriptional processing forms an important regulatory layer. Survey sequences from diverse accessions reveal a landscape of extensive single-nucleotide variation. Our data provide a platform for both genome-assisted research and enabling contemporary crop improvement. An integrated high-resolution genetic, physical and shotgun sequence assembly of the barley genome, one of the earliest domesticated and most important crops, is described; it will provide a platform for genome-assisted research and future crop improvement. Two groups in this issue report the compilation and analysis of the genome sequences of major cereal crops — bread wheat and barley — providing important resources for future crop improvement. Bread wheat accounts for one-fifth of the calories consumed by humankind. It has a very large and complex hexaploid genome of 17 Gigabases. Michael Bevan and colleagues have analysed the genome using 454 pyrosequencing and compared it with diploid ancestral and progenitor genomes. The authors discovered significant loss of gene family members upon polyploidization and domestication, and expansion of gene classes that may be associated with crop productivity. Barley is one of the earliest domesticated plant crops. Although diploid, it has a very large genome of 5.1 Gigabases. Nils Stein and colleagues describe a physical map anchored to a high-resolution genetic map, on top of which they have overlaid a deep whole-genome shotgun assembly, cDNA and RNA-seq data to provide the first in-depth genome-wide survey of the barley genome.

[1] We upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE). We trained MTE to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use. We applied the trained MTEs to generate global flux fields at a 0.5° × 0.5° spatial resolution and a monthly temporal resolution from 1982 to 2008. Cross-validation analyses revealed good performance of MTE in predicting among-site flux variability with modeling efficiencies (MEf) between 0.64 and 0.84, except for NEE (MEf = 0.32). Performance was also good for predicting seasonal patterns (MEf between 0.84 and 0.89, except for NEE (0.64)). By comparison, predictions of monthly anomalies were not as strong (MEf between 0.29 and 0.52). Improved accounting of disturbance and lagged environmental effects, along with improved characterization of errors in the training data set, would contribute most to further reducing uncertainties. Our global estimates of LE (158 ± 7 J × 1018 yr−1), H (164 ± 15 J × 1018 yr−1), and GPP (119 ± 6 Pg C yr−1) were similar to independent estimates. Our global TER estimate (96 ± 6 Pg C yr−1) was likely underestimated by 5–10%. Hot spot regions of interannual variability in carbon fluxes occurred in semiarid to semihumid regions and were controlled by moisture supply. Overall, GPP was more important to interannual variability in NEE than TER. Our empirically derived fluxes may be used for calibration and evaluation of land surface process models and for exploratory and diagnostic assessments of the biosphere.

The human intestinal tract harbors a complex microbial ecosystem which plays a key role in nutrition and health. Although this microbiota has been studied in great detail by culture techniques, microscopic counts on human feces suggest that 60 to 80% of the observable bacteria cannot be cultivated. Using comparative analysis of cloned 16S rRNA gene (rDNA) sequences, we have investigated the bacterial diversity (both cultivated and noncultivated bacteria) within an adult-male fecal sample. The 284 clones obtained from 10-cycle PCR were classified into 82 molecular species (at least 98% similarity). Three phylogenetic groups contained 95% of the clones: the Bacteroides group, the Clostridium coccoides group, and the Clostridium leptum subgroup. The remaining clones were distributed among a variety of phylogenetic clusters. Only 24% of the molecular species recovered corresponded to described organisms (those whose sequences were available in public databases), and all of these were established members of the dominant human fecal flora (e.g., Bacteroides thetaiotaomicron, Fusobacterium prausnitzii, and Eubacterium rectale). However, the majority of generated rDNA sequences (76%) did not correspond to known organisms and clearly derived from hitherto unknown species within this human gut microflora.

In the present paper, we summarize and further develop recent reseach in the estimation of the variance of sterelogical estimators based on systematic sampling. In particular, it is emphasized that the relevant estimation procedure depends on the sampling density. The validity of the variance estimation is examined in a collection of data sets, obtained by systematic sampling. Practical recommendations are also provided in a separate section.

The aim of the ecospat package is to make available novel tools and methods to support spatial analyses and modeling of species niches and distributions in a coherent workflow. The package is written in the R language (R Development Core Team) and contains several features, unique in their implementation, that are complementary to other existing R packages. Pre‐modeling analyses include species niche quantifications and comparisons between distinct ranges or time periods, measures of phylogenetic diversity, and other data exploration functionalities (e.g. extrapolation detection, ExDet). Core modeling brings together the new approach of ensemble of small models (ESM) and various implementations of the spatially‐explicit modeling of species assemblages (SESAM) framework. Post‐modeling analyses include evaluation of species predictions based on presence‐only data (Boyce index) and of community predictions, phylogenetic diversity and environmentally‐constrained species co‐occurrences analyses. The ecospat package also provides some functions to supplement the ‘biomod2’ package (e.g. data preparation, permutation tests and cross‐validation of model predictive power). With this novel package, we intend to stimulate the use of comprehensive approaches in spatial modelling of species and community distributions.

Source-to-sink transport of sugar is one of the major determinants of plant growth and relies on the efficient and controlled distribution of sucrose (and some other sugars such as raffinose and polyols) across plant organs through the phloem. However, sugar transport through the phloem can be affected by many environmental factors that alter source/sink relationships. In this paper, we summarize current knowledge about the phloem transport mechanisms and review the effects of several abiotic (water and salt stress, mineral deficiency, CO2, light, temperature, air, and soil pollutants) and biotic (mutualistic and pathogenic microbes, viruses, aphids, and parasitic plants) factors. Concerning abiotic constraints, alteration of the distribution of sugar among sinks is often reported, with some sinks as roots favored in case of mineral deficiency. Many of these constraints impair the transport function of the phloem but the exact mechanisms are far from being completely known. Phloem integrity can be disrupted (e.g., by callose deposition) and under certain conditions, phloem transport is affected, earlier than photosynthesis. Photosynthesis inhibition could result from the increase in sugar concentration due to phloem transport decrease. Biotic interactions (aphids, fungi, viruses…) also affect crop plant productivity. Recent breakthroughs have identified some of the sugar transporters involved in these interactions on the host and pathogen sides. The different data are discussed in relation to the phloem transport pathways. When possible, the link with current knowledge on the pathways at the molecular level will be highlighted.

While there is a lot of literature from a natural or technical sciences perspective on different forms of digitalization in agriculture (big data, internet of things, augmented reality, robotics, sensors, 3D printing, system integration, ubiquitous connectivity, artificial intelligence, digital twins, and blockchain among others), social science researchers have recently started investigating different aspects of digital agriculture in relation to farm production systems, value chains and food systems. This has led to a burgeoning but scattered social science body of literature. There is hence lack of overview of how this field of study is developing, and what are established, emerging, and new themes and topics. This is where this article aims to make a contribution, beyond introducing this special issue which presents seventeen articles dealing with social, economic and institutional dynamics of precision farming, digital agriculture, smart farming or agriculture 4.0. An exploratory literature review shows that five thematic clusters of extant social science literature on digitalization in agriculture can be identified: 1) Adoption, uses and adaptation of digital technologies on farm; 2) Effects of digitalization on farmer identity, farmer skills, and farm work; 3) Power, ownership, privacy and ethics in digitalizing agricultural production systems and value chains; 4) Digitalization and agricultural knowledge and innovation systems (AKIS); and 5) Economics and management of digitalized agricultural production systems and value chains. The main contributions of the special issue articles are mapped against these thematic clusters, revealing new insights on the link between digital agriculture and farm diversity, new economic, business and institutional arrangements both on-farm, in the value chain and food system, and in the innovation system, and emerging ways to ethically govern digital agriculture. Emerging lines of social science enquiry within these thematic clusters are identified and new lines are suggested to create a future research agenda on digital agriculture, smart farming and agriculture 4.0. Also, four potential new thematic social science clusters are also identified, which so far seem weakly developed: 1) Digital agriculture socio-cyber-physical-ecological systems conceptualizations; 2) Digital agriculture policy processes; 3) Digitally enabled agricultural transition pathways; and 4) Global geography of digital agriculture development. This future research agenda provides ample scope for future interdisciplinary and transdisciplinary science on precision farming, digital agriculture, smart farming and agriculture 4.0.

International audience

Abstract Geneland is a computer package that allows to make use of georeferenced individual multilocus genotypes for the inference of the number of populations and of the spatial location of genetic discontinuities between those populations. Main assumptions of the method are: (i) the number of populations is unknown and all values are considered a priori equally likely, (ii) populations are spread over areas given by a union of some polygons of unknown location in the spatial domain, (iii) Hardy–Weinberg equilibrium is assumed within each population and (iv) allele frequencies in each population are unknown and treated as random variable either following the so‐called Dirichlet model or Falush model. Different algorithms implemented in Geneland to perform inferences are first briefly presented. Then major running steps and outputs (i.e. histogram of number of populations and map of posterior probabilities of population membership) are illustrated from the analysis of a simulated data set, which was also produced by Geneland.

In response to different environmental stresses, eIF2α phosphorylation represses global translation coincident with preferential translation of ATF4, a master regulator controlling the transcription of key genes essential for adaptative functions. Here, we establish that the eIF2α/ATF4 pathway directs an autophagy gene transcriptional program in response to amino acid starvation or endoplasmic reticulum stress. The eIF2α-kinases GCN2 and PERK and the transcription factors ATF4 and CHOP are also required to increase the transcription of a set of genes implicated in the formation, elongation and function of the autophagosome. We also identify three classes of autophagy genes according to their dependence on ATF4 and CHOP and the binding of these factors to specific promoter cis elements. Furthermore, different combinations of CHOP and ATF4 bindings to target promoters allow the trigger of a differential transcriptional response according to the stress intensity. Overall, this study reveals a novel regulatory role of the eIF2α-ATF4 pathway in the fine-tuning of the autophagy gene transcription program in response to stresses.