Integrated transcriptome, small RNA and degradome sequencing approaches provide insights into Ascochyta blight resistance in chickpea

Ascochyta blight (AB) is one of the major biotic stresses known to limit the chickpea production worldwide. To dissect the complex mechanisms of AB resistance in chickpea, three approaches, namely, transcriptome, small RNA and degradome sequencing were used. The transcriptome sequencing of 20 samples including two resistant genotypes, two susceptible genotypes and one introgression line under control and stress conditions at two time points (3rd and 7th day post inoculation) identified a total of 6767 differentially expressed genes (DEGs). These DEGs were mainly related to pathogenesis�related proteins, disease resistance genes like NBS�LRR, cell wall biosynthesis and various secondary metabolite synthesis genes. The small RNA sequencing of the samples resulted in the identification of 651 miRNAs which included 478 known and 173 novel miRNAs. A total of 297 miRNAs were differentially expressed between different genotypes, conditions and time points. Using degradome sequencing and in silico approaches, 2131 targets were predicted for 629 miRNAs. The combined analysis of both small RNA and transcriptome datasets identified 12 miRNA�mRNA interaction pairs that exhibited contrasting expression in resistant and susceptible genotypes and also, a subset of genes that might be post�transcriptionally silenced during AB infection. The comprehensive integrated analysis in the study provides better insights into the transcriptome dynamics and regulatory network components associated with AB stress in chickpea and, also offers candidate genes for chickpea improvement

Genome-Wide Discovery and Deployment of Insertions and Deletions Markers Provided Greater Insights on Species, Genomes, and Sections Relationships in the Genus Arachis

Small insertions and deletions (InDels) are the second most prevalent and the most abundant structural variations in plant genomes. In order to deploy these genetic variations for genetic analysis in genus Arachis, we conducted comparative analysis of the draft genome assemblies of both the diploid progenitor species of cultivated tetraploid groundnut (Arachis hypogaea L.) i.e., Arachis duranensis (A subgenome) and Arachis ipaënsis (B subgenome) and identified 515,223 InDels. These InDels include 269,973 insertions identified in A. ipaënsis against A. duranensis while 245,250 deletions in A. duranensis against A. ipaënsis. The majority of the InDels were of single bp (43.7%) and 2–10 bp (39.9%) while the remaining were >10 bp (16.4%). Phylogenetic analysis using genotyping data for 86 (40.19%) polymorphic markers grouped 96 diverse Arachis accessions into eight clusters mostly by the affinity of their genome. This study also provided evidence for the existence of “K” genome, although distinct from both the “A” and “B” genomes, but more similar to “B” genome. The complete homology between A. monticola and A. hypogaea tetraploid taxa showed a very similar genome composition. The above analysis has provided greater insights into the phylogenetic relationship among accessions, genomes, sub species and sections. These InDel markers are very useful resource for groundnut research community for genetic analysis and breeding applications

Genomic-enabled prediction models using multi-environment trials to estimate the effect of genotype × environment interaction on prediction accuracy in chickpea

Genomic selection (GS) by selecting lines prior to field phenotyping using genotyping data has the potential to enhance the rate of genetic gains. Genotype × environment (G × E) interaction inclusion in GS models can improve prediction accuracy hence aid in selection of lines across target environments. Phenotypic data on 320 chickpea breeding lines for eight traits for three seasons at two locations were recorded. These lines were genotyped using DArTseq (1.6 K SNPs) and Genotyping-by-Sequencing (GBS; 89 K SNPs). Thirteen models were fitted including main effects of environment and lines, markers, and/or naïve and informed interactions to estimate prediction accuracies. Three cross-validation schemes mimicking real scenarios that breeders might encounter in the fields were considered to assess prediction accuracy of the models (CV2: incomplete field trials or sparse testing; CV1: newly developed lines; and CV0: untested environments). Maximum prediction accuracies for different traits and different models were observed with CV2. DArTseq performed better than GBS and the combined genotyping set (DArTseq and GBS) regardless of the cross validation scheme with most of the main effect marker and interaction models. Improvement of GS models and application of various genotyping platforms are key factors for obtaining accurate and precise prediction accuracies, leading to more precise selection of candidates

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Phylogenomic analysis of UDP glycosyltransferase 1 multigene family in <it>Linum usitatissimum</it> identified genes with varied expression patterns

Abstract Background The glycosylation process, catalyzed by ubiquitous glycosyltransferase (GT) family enzymes, is a prevalent modification of plant secondary metabolites that regulates various functions such as hormone homeostasis, detoxification of xenobiotics and biosynthesis and storage of secondary metabolites. Flax (Linum usitatissimum L.) is a commercially grown oilseed crop, important because of its essential fatty acids and health promoting lignans. Identification and characterization of UDP glycosyltransferase (UGT) genes from flax could provide valuable basic information about this important gene family and help to explain the seed specific glycosylated metabolite accumulation and other processes in plants. Plant genome sequencing projects are useful to discover complexity within this gene family and also pave way for the development of functional genomics approaches. Results Taking advantage of the newly assembled draft genome sequence of flax, we identified 137 UDP glycosyltransferase (UGT) genes from flax using a conserved signature motif. Phylogenetic analysis of these protein sequences clustered them into 14 major groups (A-N). Expression patterns of these genes were investigated using publicly available expressed sequence tag (EST), microarray data and reverse transcription quantitative real time PCR (RT-qPCR). Seventy-three per cent of these genes (100 out of 137) showed expression evidence in 15 tissues examined and indicated varied expression profiles. The RT-qPCR results of 10 selected genes were also coherent with the digital expression analysis. Interestingly, five duplicated UGT genes were identified, which showed differential expression in various tissues. Of the seven intron loss/gain positions detected, two intron positions were conserved among most of the UGTs, although a clear relationship about the evolution of these genes could not be established. Comparison of the flax UGTs with orthologs from four other sequenced dicot genomes indicated that seven UGTs were flax diverged. Conclusions Flax has a large number of UGT genes including few flax diverged ones. Phylogenetic analysis and expression profiles of these genes identified tissue and condition specific repertoire of UGT genes from this crop. This study would facilitate precise selection of candidate genes and their further characterization of substrate specificities and in planta functions.</p

Integrated transcriptome, small RNA and degradome sequencing approaches provide insights into Ascochyta blight resistance in chickpea

Ascochyta blight (AB) is one of the major biotic stresses known to limit the chickpea production worldwide. To dissect the complex mechanisms of AB resistance in chickpea, three approaches, namely, transcriptome, small RNA and degradome sequencing were used. The transcriptome sequencing of 20 samples including two resistant genotypes, two susceptible genotypes and one introgression line under control and stress conditions at two time points (3rd and 7th day post inoculation) identified a total of 6767 differentially expressed genes (DEGs). These DEGs were mainly related to pathogenesis-related proteins, disease resistance genes like NBS-LRR, cell wall biosynthesis and various secondary metabolite synthesis genes. The small RNA sequencing of the samples resulted in the identification of 651 miRNAs which included 478 known and 173 novel miRNAs. A total of 297 miRNAs were differentially expressed between different genotypes, conditions and time points. Using degradome sequencing and in silico approaches, 2131 targets were predicted for 629 miRNAs. The combined analysis of both small RNA and transcriptome datasets identified 12 miRNA-mRNA interaction pairs that exhibited contrasting expression in resistant and susceptible genotypes and also, a subset of genes that might be post-transcriptionally silenced during AB infection. The comprehensive integrated analysis in the study provides better insights into the transcriptome dynamics and regulatory network components associated with AB stress in chickpea and, also offers candidate genes for chickpea improvement

Genome-wide identification and characterization of microRNA genes and their targets in flax (Linum usitatissimum)

MicroRNAs (miRNAs) are small (20\u201324 nucleotide long) endogenous regulatory RNAs that play important roles in plant growth and development. They regulate gene expression at the post-transcriptional level by translational repression or target degradation and gene silencing. In this study, we identi\ufb01ed 116 conserved miRNAs belonging to 23 families from the \ufb02ax (Linumusitatissimum L.) genome using a computational approach. The precursor miRNAs varied in length; while most of the mature miRNAs were 21 nucleotide long, intergenic and showed conserved signatures of RNA polymerase II transcripts in their upstream regions. Promoter region analysis of the \ufb02ax miRNA genes indicated prevalence of MYB transcription factor binding sites. Four miRNA gene clusters containing members of three phylogenetic groups were identi\ufb01ed. Further, 142 target genes were predicted for these miRNAs and most of these represent transcriptional regulators. The miRNA encoding genes were expressed in diverse tissues as determined by digital expression analysis as well as real-time PCR. The expression of fourteen miRNAs and nine target genes was independently validated using the quantitative reverse transcription PCR (qRTPCR). This study suggests that a large number of conserved plant miRNAs are also found in \ufb02ax and these may play important roles in growth and development of \ufb02ax.Peer reviewed: YesNRC publication: Ye

Genomic-enabled prediction models using multi-environment trials to estimate the effect of genotype × environment interaction on prediction accuracy in chickpea

Genomic selection (GS) by selecting lines prior to field phenotyping using genotyping data has the potential to enhance the rate of genetic gains. Genotype × environment (G × E) interaction inclusion in GS models can improve prediction accuracy hence aid in selection of lines across target environments. Phenotypic data on 320 chickpea breeding lines for eight traits for three seasons at two locations were recorded. These lines were genotyped using DArTseq (1.6 K SNPs) and Genotyping-by-Sequencing (GBS; 89 K SNPs). Thirteen models were fitted including main effects of environment and lines, markers, and/or naïve and informed interactions to estimate prediction accuracies. Three cross-validation schemes mimicking real scenarios that breeders might encounter in the fields were considered to assess prediction accuracy of the models (CV2: incomplete field trials or sparse testing; CV1: newly developed lines; and CV0: untested environments). Maximum prediction accuracies for different traits and different models were observed with CV2. DArTseq performed better than GBS and the combined genotyping set (DArTseq and GBS) regardless of the cross validation scheme with most of the main effect marker and interaction models. Improvement of GS models and application of various genotyping platforms are key factors for obtaining accurate and precise prediction accuracies, leading to more precise selection of candidates

Hieracium sabaudum

Flax (<i>Linum usitatissimum</i> L.) seeds are an important source of food and feed due to the presence of various health promoting compounds, making it a nutritionally and economically important plant. An in-depth analysis of the proteome of developing flax seed is expected to provide significant information with respect to the regulation and accumulation of such storage compounds. Therefore, a proteomic analysis of seven seed developmental stages (4, 8, 12, 16, 22, 30, and 48 days after anthesis) in a flax variety, NL-97 was carried out using a combination of 1D-SDS-PAGE and LC-MS^E methods. A total 1716 proteins were identified and their functional annotation revealed that a majority of them were involved in primary metabolism, protein destination, storage and energy. Three carbon assimilatory pathways appeared to operate in flax seeds. Reverse transcription quantitative PCR of selected 19 genes was carried out to understand their roles during seed development. Besides storage proteins, methionine synthase, RuBisCO and <i>S</i>-adenosylmethionine synthetase were highly expressed transcripts, highlighting their importance in flax seed development. Further, the identified proteins were mapped onto developmental seed specific expressed sequence tag (EST) libraries of flax to obtain transcriptional evidence and 81% of them had detectable expression at the mRNA level. This study provides new insights into the complex seed developmental processes operating in flax

Proteome Profiling of Flax (<i>Linum usitatissimum</i>) Seed: Characterization of Functional Metabolic Pathways Operating during Seed Development

Flax (<i>Linum usitatissimum</i> L.) seeds are an important source of food and feed due to the presence of various health promoting compounds, making it a nutritionally and economically important plant. An in-depth analysis of the proteome of developing flax seed is expected to provide significant information with respect to the regulation and accumulation of such storage compounds. Therefore, a proteomic analysis of seven seed developmental stages (4, 8, 12, 16, 22, 30, and 48 days after anthesis) in a flax variety, NL-97 was carried out using a combination of 1D-SDS-PAGE and LC-MS^E methods. A total 1716 proteins were identified and their functional annotation revealed that a majority of them were involved in primary metabolism, protein destination, storage and energy. Three carbon assimilatory pathways appeared to operate in flax seeds. Reverse transcription quantitative PCR of selected 19 genes was carried out to understand their roles during seed development. Besides storage proteins, methionine synthase, RuBisCO and <i>S</i>-adenosylmethionine synthetase were highly expressed transcripts, highlighting their importance in flax seed development. Further, the identified proteins were mapped onto developmental seed specific expressed sequence tag (EST) libraries of flax to obtain transcriptional evidence and 81% of them had detectable expression at the mRNA level. This study provides new insights into the complex seed developmental processes operating in flax