The assembly of a reference genome sequence of bread wheat is challenging due to its specific features such as the genome size of 17 Gbp, polyploid nature and prevalence of repetitive sequences. BAC-by-BAC sequencing based on chromosomal physical maps, adopted by the International Wheat Genome Sequencing Consortium as the key strategy, reduces problems caused by the genome complexity and polyploidy, but the repeat content still hampers the sequence assembly. Availability of a high-resolution genomic map to guide sequence scaffolding and validate physical map and sequence assemblies would be highly beneficial to obtaining an accurate and complete genome sequence. Here, we chose the short arm of chromosome 7D (7DS) as a model to demonstrate for the first time that it is possible to couple chromosome flow sorting with genome mapping in nanochannel arrays and create a de novo genome map of a wheat chromosome. We constructed a high-resolution chromosome map composed of 371 contigs with an N50 of 1.3 Mb. Long DNA molecules achieved by our approach facilitated chromosome-scale analysis of repetitive sequences and revealed a ~800-kb array of tandem repeats intractable to current DNA sequencing technologies. Anchoring 7DS sequence assemblies obtained by clone-by-clone sequencing to the 7DS genome map provided a valuable tool to improve the BAC-contig physical map and validate sequence assembly on a chromosome-arm scale. Our results indicate that creating genome maps for the whole wheat genome in a chromosome-by-chromosome manner is feasible and that they will be an affordable tool to support the production of improved pseudomolecules.

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to “rescue” the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes.

Nitrogen is one of the most essential plant nutrients and one of the major factors limiting crop productivity. Having the goal to perform a more sustainable agriculture, there is a need to maximize biological nitrogen fixation, a feature of legumes. To enhance our understanding of the molecular mechanisms controlling the interaction between legumes and rhizobia, the symbiotic partner fixing and assimilating the atmospheric nitrogen for the plant, researchers took advantage of genetic and genomic resources developed across different legume models (e.g., Medicago truncatula, Lotus japonicus, Glycine max, and Phaseolus vulgaris) to identify key regulatory protein coding genes of the nodulation process. In this study, we are presenting the results of a comprehensive comparative genomic analysis to highlight orthologous and paralogous relationships between the legume genes controlling nodulation. Mining large transcriptomic datasets, we also identified several orthologous and paralogous genes characterized by the induction of their expression during nodulation across legume plant species. This comprehensive study prompts new insights into the evolution of the nodulation process in legume plant and will benefit the scientific community interested in the transfer of functional genomic information between species.

Abscission of flower pedicels and leaf petioles of tomato (Solanum lycopersicum) can be induced by flower removal or leaf deblading, respectively, which leads to auxin depletion, resulting in increased sensitivity of the abscission zone (AZ) to ethylene. However, the molecular mechanisms that drive the acquisition of abscission competence and its modulation by auxin gradients are not yet known. We used RNA-Sequencing (RNA-Seq) to obtain a comprehensive transcriptome of tomato flower AZ (FAZ) and leaf AZ (LAZ) during abscission. RNA-Seq was performed on a pool of total RNA extracted from tomato FAZ and LAZ, at different abscission stages, followed by de novo assembly. The assembled clusters contained transcripts that are already known in the Solanaceae (SOL) genomics and NCBI databases, and over 8823 identified novel tomato transcripts of varying sizes. An AZ-specific microarray, encompassing the novel transcripts identified in this study and all known transcripts from the SOL genomics and NCBI databases, was constructed to study the abscission process. Multiple probes for longer genes and key AZ-specific genes, including antisense probes for all transcripts, make this array a unique tool for studying abscission with a comprehensive set of transcripts, and for mining for naturally occurring antisense transcripts. We focused on comparing the global transcriptomes generated from the FAZ and the LAZ to establish the divergences and similarities in their transcriptional networks, and particularly to characterize the processes and transcriptional regulators enriched in gene clusters that are differentially regulated in these two AZs. This study is the first attempt to analyze the global gene expression in different AZs in tomato by combining the RNA-Seq technique with oligonucleotide microarrays. Our AZ-specific microarray chip provides a cost-effective approach for expression profiling and robust analysis of multiple samples in a rapid succession.

Plant diseases cause extensive yield loss of crops worldwide, and secretory ‘warfare’ occurs between plants and pathogenic organisms all the time. Filamentous plant pathogens have evolved the ability to manipulate host processes and facilitate colonization through secreting effectors inside plant cells. The stresses from hosts and environment can drive the genome dynamics of plant pathogens. Remarkable advances in plant pathology have been made owing to these adaptable genome regions of several lineages of filamentous phytopathogens. Characterization new effectors and interaction analyses between pathogens and plants have provided molecular insights into the plant pathways perturbed during the infection process. In this mini-review, we highlight promising approaches of identifying novel effectors based on the genome plasticity. We also discuss the interaction mechanisms between plants and their filamentous pathogens and outline the possibilities of effector gene expression under epigenetic control that will be future directions for research.

The large amounts of transcriptome data available for Arabidopsis thaliana makes a compelling case for the need to generalize results across studies and extract the most robust and meaningful information possible from them. Various studies seeking to identify water-stress responsive genes only partially overlap in their results. The aim of this work was to combine transcriptomic studies in a systematic way that identifies commonalities in response, taking into account variation among studies due to batch effects as well as sampling variation, while also identifying the effect of study specific variables, such as the method of applying water stress, and the part of the plant mRNA was extracted from. We used meta-analysis, the quantitative synthesis of independent research results, to summarize expression responses to water stress across studies, and meta-regression to model the contribution of covariates that can affect gene expression. We found that some genes with small but consistent differential responses become evident only when results are synthesized across experiments and are missed in individual studies. We also identified genes with expression responses attributable to different plant parts and to alternative methods for inducing water stress. Our results indicate that meta-analysis and meta-regression provide a powerful approach for identifying a robust gene set which is less sensitive to idiosyncratic results and can quantify study characteristics that result in contrasting gene expression responses across studies. Combining meta-analysis with individual analyses can contribute to a richer understanding of the biology of water-stress responses and may prove valuable in other gene expression studies.

Arsenic is a toxic metalloid known to generate an important oxidative stress in cells. In the present study we focused our attention on an alga related to the genus Coccomyxa, exhibiting an extraordinary capacity to resist high concentrations of arsenite and arsenate. The integrated analysis of high throughput transcriptomic data and non-targeted metabolomic approaches highlighted multiple levels of protection against arsenite. Indeed, Coccomyxa sp. Carn induced a set of transporters potentially preventing the accumulation of this metalloid in the cells and presented a distinct arsenic metabolism in comparison to an other species more sensitive to that compound, i.e. Euglena gracilis, especially in regard to arsenic methylation. Interestingly, Coccomyxa sp. Carn was characterized by a remarkable accumulation of the strong antioxidant glutathione (GSH). Such observation could explain the apparent low oxidative stress in its the intracellular compartment, as suggested by the transcriptomic analysis. In particular, the high amount of GSH in the cell could play an important role for the tolerance to arsenate, as suggested by its partial oxidation into GSSG in presence of this metalloid. Our results therefore reveal that this alga has acquired multiple and original defense mechanisms allowing the colonization of extreme ecosystems such as AMDs.

During ripening, the fruits of the olive tree (Olea europaea L.) undergo a progressive chromatic change characterized by the formation of a red-brown “spot” which gradually extends on the epidermis and in the innermost part of the mesocarp. This event finds an exception in the Leucocarpa cultivar, in which we observe a destabilized equilibrium between the metabolisms of chlorophyll and other pigments, particularly the anthocyanins whose switch-off during maturation promotes the white coloration of fruits. Despite its importance, genomic information on the olive tree is still lacking. Different RNA-seq libraries were generated from drupes of “Leucocarpa” and “Cassanese” olive genotypes, sampled at 100 and 130 days after flowering (DAF), and were used in order to identify transcripts involved in the main phenotypic changes of fruits during maturation and their corresponding expression patterns. A total of 103,359 transcripts were obtained and 3792 and 3064 were differentially expressed in “Leucocarpa” and “Cassanese” genotypes, respectively, during 100–130 DAF transition. Among them flavonoid and anthocyanin related transcripts such as phenylalanine ammonia lyase (PAL), cinnamate 4-hydroxylase (C4H), 4-coumarate-CoA ligase (4CL), chalcone synthase (CHS), chalcone isomerase (CHI), flavanone 3-hydroxylase (F3H), flavonol 3′-hydrogenase (F3′H), flavonol 3′5 ′-hydrogenase (F3′5′H), flavonol synthase (FLS), dihydroflavonol 4-reductase (DFR), anthocyanidin synthase (ANS), UDP-glucose:anthocianidin: flavonoid glucosyltransferase (UFGT) were identified. These results contribute to reducing the current gap in information regarding metabolic processes, including those linked to fruit pigmentation in the olive.