Département Biologie et Amélioration des Plantes

The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

The first national single-step, full-information (phenotype, pedigree, and marker genotype) genetic evaluation was developed for final score of US Holsteins. Data included final scores recorded from 1955 to 2009 for 6,232,548 Holsteins cows. BovineSNP50 (Illumina, San Diego, CA) genotypes from the Cooperative Dairy DNA Repository (Beltsville, MD) were available for 6,508 bulls. Three analyses used a repeatability animal model as currently used for the national US evaluation. The first 2 analyses used final scores recorded up to 2004. The first analysis used only a pedigree-based relationship matrix. The second analysis used a relationship matrix based on both pedigree and genomic information (single-step approach). The third analysis used the complete data set and only the pedigree-based relationship matrix. The fourth analysis used predictions from the first analysis (final scores up to 2004 and only a pedigree-based relationship matrix) and prediction using a genomic based matrix to obtain genetic evaluation (multiple-step approach). Different allele frequencies were tested in construction of the genomic relationship matrix. Coefficients of determination between predictions of young bulls from parent average, single-step, and multiple-step approaches and their 2009 daughter deviations were 0.24, 0.37 to 0.41, and 0.40, respectively. The highest coefficient of determination for a single-step approach was observed when using a genomic relationship matrix with assumed allele frequencies of 0.5. Coefficients for regression of 2009 daughter deviations on parent-average, single-step, and multiple-step predictions were 0.76, 0.68 to 0.79, and 0.86, respectively, which indicated some inflation of predictions. The single-step regression coefficient could be increased up to 0.92 by scaling differences between the genomic and pedigree-based relationship matrices with little loss in accuracy of prediction. One complete evaluation took about 2h of computing time and 2.7 gigabytes of memory. Computing times for single-step analyses were slightly longer (2%) than for pedigree-based analysis. A national single-step genetic evaluation with the pedigree relationship matrix augmented with genomic information provided genomic predictions with accuracy and bias comparable to multiple-step procedures and could account for any population or data structure. Advantages of single-step evaluations should increase in the future when animals are pre-selected on genotypes.

In this review, recent developments and future prospects of obtaining a better understanding of the regulation of nitrogen use efficiency in the main crop species cultivated in the world are presented. In these crops, an increased knowledge of the regulatory mechanisms controlling plant nitrogen economy is vital for improving nitrogen use efficiency and for reducing excessive input of fertilizers, while maintaining an acceptable yield. Using plants grown under agronomic conditions at low and high nitrogen fertilization regimes, it is now possible to develop whole-plant physiological studies combined with gene, protein, and metabolite profiling to build up a comprehensive picture depicting the different steps of nitrogen uptake, assimilation, and recycling to the final deposition in the seed. A critical overview is provided on how understanding of the physiological and molecular controls of N assimilation under varying environmental conditions in crops has been improved through the use of combined approaches, mainly based on whole-plant physiology, quantitative genetics, and forward and reverse genetics approaches. Current knowledge and prospects for future agronomic development and application for breeding crops adapted to lower fertilizer input are explored, taking into account the world economic and environmental constraints in the next century.

Dense molecular markers are being used in genetic evaluation for parts of the population. This requires a two-step procedure where pseudo-data (for instance, daughter yield deviations) are computed from full records and pedigree data and later used for genomic evaluation. This results in bias and loss of information. One way to incorporate the genomic information into a full genetic evaluation is by modifying the numerator relationship matrix. A naive proposal is to substitute the relationships of genotyped animals with the genomic relationship matrix. However, this results in incoherencies because the genomic relationship matrix includes information on relationships among ancestors and descendants. In other words, using the pedigree-derived covariance between genotyped and ungenotyped individuals, with the pretense that genomic information does not exist, leads to inconsistencies. It is proposed to condition the genetic value of ungenotyped animals on the genetic value of genotyped animals via the selection index (e.g., pedigree information), and then use the genomic relationship matrix for the latter. This results in a joint distribution of genotyped and ungenotyped genetic values, with a pedigree-genomic relationship matrix H. In this matrix, genomic information is transmitted to the covariances among all ungenotyped individuals. The matrix is (semi)positive definite by construction, which is not the case for the naive approach. Numerical examples and alternative expressions are discussed. Matrix H is suitable for iteration on data algorithms that multiply a vector times a matrix, such as preconditioned conjugated gradients.

Plant genetic transformation was initiated and developed m the 80s thanks to the convergence of constant progress m the protocol of regeneratton from tissue culture, molecular techniques leading to well-expressed marker genes after transfer m plant cells, and the dtverslficatlon of DNA delivery methods.

Probably more than 25% of the proteins encoded by the nuclear genomes of multicellular eukaryotes are targeted to membrane-bound compartments by N-terminal targeting signals. The major signals are those for the endoplasmic reticulum, the mitochondria, and in plants, plastids. The most abundant of these targeted proteins are well-known and well-studied, but a large proportion remain unknown, including most of those involved in regulation of organellar gene expression or regulation of biochemical pathways. The discovery and characterization of these proteins by biochemical means will be long and difficult. An alternative method is to identify candidate organellar proteins via their characteristic N-terminal targeting sequences. We have developed a neural network-based approach (Predotar--Prediction of Organelle Targeting sequences) for identifying genes encoding these proteins amongst eukaryotic genome sequences. The power of this approach for identifying and annotating novel gene families has been illustrated by the discovery of the pentatricopeptide repeat family.

Loss or gain of DNA methylation can affect gene expression and is sometimes transmitted across generations. Such epigenetic alterations are thus a possible source of heritable phenotypic variation in the absence of DNA sequence change. However, attempts to assess the prevalence of stable epigenetic variation in natural and experimental populations and to quantify its impact on complex traits have been hampered by the confounding effects of DNA sequence polymorphisms. To overcome this problem as much as possible, two parents with little DNA sequence differences, but contrasting DNA methylation profiles, were used to derive a panel of epigenetic Recombinant Inbred Lines (epiRILs) in the reference plant Arabidopsis thaliana. The epiRILs showed variation and high heritability for flowering time and plant height ( approximately 30%), as well as stable inheritance of multiple parental DNA methylation variants (epialleles) over at least eight generations. These findings provide a first rationale to identify epiallelic variants that contribute to heritable variation in complex traits using linkage or association studies. More generally, the demonstration that numerous epialleles across the genome can be stable over many generations in the absence of selection or extensive DNA sequence variation highlights the need to integrate epigenetic information into population genetics studies.

The use of genetic maps based upon molecular markers has allowed the dissection of some of the factors underlying quantitative variation in crosses between inbred lines. For many species crossing inbred lines is not a practical proposition, although crosses between genetically very different outbred lines are possible. Here we develop a least squares method for the analysis of crosses between outbred lines which simultaneously uses information from multiple linked markers. The method is suitable for crosses where the lines may be segregating at marker loci but can be assumed to be fixed for alternative alleles at the major quantitative trait loci (QTLs) affecting the traits under analysis (e.g., crosses between divergent selection lines or breeds with different selection histories). The simultaneous use of multiple markers from a linkage group increases the sensitivity of the test statistic, and thus the power for the detection of QTLs, compared to the use of single markers or markers flanking an interval. The gain is greater for more closely spaced markers and for markers of lower information content. Use of multiple markers can also remove the bias in the estimated position and effect of a QTL which may result when different markers in a linkage group vary in their heterozygosity in the F1 (and thus in their information content) and are considered only singly or a pair at a time. The method is relatively simple to apply so that more complex models can be fitted than is currently possible by maximum likelihood. Thus fixed effects of background genotype can be fitted simultaneously with the exploration of a single linkage group which will increase the power to detect QTLs by reducing the residual variance. More complex models with several QTLs in the same linkage group and two-locus interactions between QTLs can similarly be examined. Thus least squares provides a powerful tool to extend the range of crosses from which QTLs can be dissected whilst at the same time allowing flexible and realistic models to be explored.

Shoot branching is inhibited by auxin transported down the stem from the shoot apex. Auxin does not accumulate in inhibited buds and so must act indirectly. We show that mutations in the MAX4 gene of Arabidopsis result in increased and auxin-resistant bud growth. Increased branching in max4 shoots is restored to wild type by grafting to wild-type rootstocks, suggesting that MAX4 is required to produce a mobile branch-inhibiting signal, acting downstream of auxin. A similar role has been proposed for the pea gene, RMS1. Accordingly, MAX4 and RMS1 were found to encode orthologous, auxin-inducible members of the polyene dioxygenase family.

Recent biotechnology advances allow for multiple types of omics data, such as transcriptomic, proteomic or metabolomic data sets to be integrated. The problem of feature selection has been addressed several times in the context of classification, but needs to be handled in a specific manner when integrating data. In this study, we focus on the integration of two-block data that are measured on the same samples. Our goal is to combine integration and simultaneous variable selection of the two data sets in a one-step procedure using a Partial Least Squares regression (PLS) variant to facilitate the biologists' interpretation. A novel computational methodology called ;;sparse PLS" is introduced for a predictive analysis to deal with these newly arisen problems. The sparsity of our approach is achieved with a Lasso penalization of the PLS loading vectors when computing the Singular Value Decomposition. Sparse PLS is shown to be effective and biologically meaningful. Comparisons with classical PLS are performed on a simulated data set and on real data sets. On one data set, a thorough biological interpretation of the obtained results is provided. We show that sparse PLS provides a valuable variable selection tool for highly dimensional data sets.

This article presents a method to combine QTL results from different independent analyses. This method provides a modified Akaike criterion that can be used to decide how many QTL are actually represented by the QTL detected in different experiments. This criterion is computed to choose between models with one, two, three, etc., QTL. Simulations are carried out to investigate the quality of the model obtained with this method in various situations. It appears that the method allows the length of the confidence interval of QTL location to be consistently reduced when there are only very few "actual" QTL locations. An application of the method is given using data from the maize database available online at http://www. agron.missouri.edu/.

To study the consequences of hybridization and genome duplication on polyploid genome evolution and adaptation, we used independently formed hybrids (Spartina x townsendii and Spartina x neyrautii) that originated from natural crosses between Spartina alterniflora, an American introduced species, and the European native Spartina maritima. The hybrid from England, S. x townsendii, gave rise to the invasive allopolyploid, salt-marsh species, Spartina anglica. Recent studies indicated that allopolyploid speciation may be associated with rapid genetic and epigenetic changes. To assess this in Spartina, we performed AFLP (amplified fragment length polymorphism) and MSAP (methylation sensitive amplification polymorphism) on young hybrids and the allopolyploid. By comparing the subgenomes in the hybrids and the allopolyploid to the parental species, we inferred structural changes that arose repeatedly in the two independently formed hybrids. Surprisingly, 30% of the parental methylation patterns are altered in the hybrids and the allopolyploid. This high level of epigenetic regulation might explain the morphological plasticity of Spartina anglica and its larger ecological amplitude. Hybridization rather than genome doubling seems to have triggered most of the methylation changes observed in Spartina anglica.

The immune system is known to be involved in the early phase of scrapie pathogenesis. However, the infection route of naturally occurring scrapie and its spread within the host are not entirely known. In this study, the pathogenesis of scrapie was investigated in sheep of three PrP genotypes, from 2 to 9 months of age, which were born and raised together in a naturally scrapie-affected Romanov flock. The kinetics of PrP(Sc) accumulation in sheep organs were determined by immunohistochemistry. PrP(Sc) was detected only in susceptible VRQ/VRQ sheep, from 2 months of age, with an apparent entry site at the ileal Peyer's patch as well as its draining mesenteric lymph node. At the cellular level, PrP(Sc) deposits were associated with CD68-positive cells of the dome area and B follicles before being detected in follicular dendritic cells. In 3- to 6-month-old sheep, PrP(Sc) was detected in most of the gut-associated lymphoid tissues (GALT) and to a lesser extent in more systemic lymphoid formations such as the spleen or the mediastinal lymph node. All secondary lymphoid organs showed a similar intensity of PrP(Sc)-immunolabelling at 9 months of age. At this time-point, PrP(Sc) was also detected in the autonomic myenteric nervous plexus and in the nucleus parasympathicus nervi X of the brain stem. These data suggest that natural scrapie infection occurs by the oral route via infection of the Peyer's patches followed by replication in the GALT. It may then spread to the central nervous system through the autonomic nervous fibres innervating the digestive tract.

Since their colonization of terrestrial ecosystems, plants have developed numerous strategies to cope with the diverse biotic and abiotic challenges that are a consequence of their sedentary life cycle. One of the most successful strategies is

Prediction of genetic merit or disease risk using genetic marker information is becoming a common practice for selection of livestock and plant species. For the successful application of genome-wide marker-assisted selection (GWMAS), genomic predictions should be accurate and unbiased. The effect of selection on bias and accuracy of genomic predictions was studied in two simulated animal populations under weak or strong selection and with several heritabilities. Prediction of genetic values was by best-linear unbiased prediction (BLUP) using data either from relatives summarized in pseudodata for genotyped individuals (multiple-step method) or using all available data jointly (single-step method). The single-step method combined genomic- and pedigree-based relationship matrices. Predictions by the multiple-step method were biased. Predictions by a single-step method were less biased and more accurate but under strong selection were less accurate. When genomic relationships were shifted by a constant, the single-step method was unbiased and the most accurate. The value of that constant, which adjusts for non-random selection of genotyped individuals, can be derived analytically.

The completion of the genome sequences of both rice and Magnaporthe oryzae has strengthened the position of rice blast disease as a model to study plant-pathogen interactions in monocotyledons. Genetic studies of blast resistance in rice were established in Japan as early as 1917. Despite such long-term study, examples of cultivars with durable resistance are rare, partly due to our limited knowledge of resistance mechanisms. A rising number of blast resistance genes and quantitative trait loci (QTL) have been genetically described, and some have been characterized during the last 20 years. Using the rice genome sequence, can we now go a step further toward a better understanding of the genetics of blast resistance by combining all these results? Is such knowledge appropriate and sufficient to improve breeding for durable resistance? A review of bibliographic references identified 85 blast resistance genes and approximately 350 QTL, which we mapped on the rice genome. These data provide a useful update on blast resistance genes as well as new insights to help formulate hypotheses about the molecular function of blast QTL, with special emphasis on QTL for partial resistance. All these data are available from the OrygenesDB database.

In a context where agricultural practices in Europe are likely to go toward extensive systems with lower inputs, it is important to determine the genetic improvement of winter wheat ( Triticum aestivum L.) not only in high‐input agricultural systems but also in low‐input systems. This study assesses the improvement in agronomic traits of winter wheat cultivars cultivated in France during the second half of the 20th century at four agronomic treatments: two levels of fungicide were combined with two levels of nitrogen fertilizer. Fourteen cultivars introduced between 1946 and 1992 were grown for two years (1994 and 1995) at five locations. Selection played a major role in the increase in winter wheat yield after 1946. The contribution of selection to this increase depended on the agronomic treatment and varied from one third to one half. Reduction of height was the most important factor. New cultivars with shorter straw expressed higher harvest index values and more consistent higher yields since they were less susceptible to lodging. The ability to produce more kernels from a given total above‐ground biomass was the second factor. The number of kernels per unit area had increased over time without alteration of the weight of the kernels. The negative relationship between 1000‐kernel weight and kernel number/m 2 was therefore shifted and new cultivars were thus able to fill more kernels than older entries. Modern cultivars used N more efficiently than their predecessors. The future challenge will be to obtain, in low‐input systems, the same genetic gains as in high‐input systems.

Mention d'édition : 3rd ed.

The origins of the classic European wine grapes (Vitis vinifera) have been the subject of much speculation. In a search for parental relationships, microsatellite loci were analyzed in more than 300 grape cultivars. Sixteen wine grapes that have long been grown in northeastern France, including 'Chardonnay', 'Gamay noir', 'Aligoté', and 'Melon', have microsatellite genotypes consistent with their being the progeny of a single pair of parents, 'Pinot' and 'Gouais blanc', both of which were widespread in this region in the Middle Ages. Parentage analysis at 32 microsatellite loci provides statistical support for these relationships.

Cinnamoyl CoA:NADP oxidoreductase (CCR, EC 1.2.1.44) catalyzes the conversion of cinnamoyl CoA esters to their corresponding cinnamaldehydes, i.e. the first specific step in the synthesis of the lignin monomers. The cloning of a cDNA encoding CCR in Eucalyptus gunnii (EUCCR) is reported here. The identity of the EUCCR cDNA was demonstrated by comparison with peptide sequence data from purified CCR and functional expression of the recombinant enzyme in Escherichia coli. Sequence analysis revealed remarkable homologies with dihydroflavonol-4-reductase (DFR), the first enzyme of the anthocyanin biosynthetic pathway. Moreover, significant similarities were found with mammalian 3 beta-hydroxysteroid dehydrogenase and bacterial UDP-galactose-4-epimerase, suggesting that CCR shared a common ancestor with these enzymes and can therefore be considered as a new member of the mammalian 3 beta-hydroxysteroid dehydrogenase/ plant dihydroflavonol reductase superfamily. In Eucalyptus gunnii, CCR is encoded by one gene containing four introns whose positions are similar to those of introns I, II, III and V in DFR genes from dicots. In agreement with the involvement of CCR in lignification, the CCR transcript was shown to be expressed in lignified organs, i.e. root and stem tissues, and was localized mainly in young differentiating xylem. On the other hand, its abundance in Eucalyptus leaves suggests that monolignols may be precursors of end products other than lignins. This first characterization of a gene corresponding to CCR opens new possibilities to genetically engineer plants with lower lignin content. This is particularly important for woody plants such as Eucalyptus which are used for pulp making.