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

CicArVarDB: SNP and InDel database for advancing genetics research and breeding applications in chickpea

Molecular markers are valuable tools for breeders to help accelerate crop improvement. High throughput sequencing technologies facilitate the discovery of large-scale variations such as single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs). Sequencing of chickpea genome along with re-sequencing of several chickpea lines has enabled the discovery of 4.4 million variations including SNPs and InDels. Here we report a repository of 1.9 million variations (SNPs and InDels) anchored on eight pseudomolecules in a custom database, referred as CicArVarDB that can be accessed at http://cicarvardb.icrisat.org/. It includes an easy interface for users to select variations around specific regions associated with quantitative trait loci, with embedded webBLAST search and JBrowse visualisation. We hope that this database will be immensely useful for the chickpea research community for both advancing genetics research as well as breeding applications for crop improvement

Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea

Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013-14 and 2014-15). A total of 52.02 billion clean reads containing 4.67 TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69 cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas

Genome-Wide Identification, Characterization, and Expression Analysis of Small RNA Biogenesis Purveyors Reveal Their Role in Regulation of Biotic Stress Responses in Three Legume Crops

Biotic stress in legume crops is one of the major threats to crop yield and productivity. Being sessile organisms, plants have evolved a myriad of mechanisms to combat different stresses imposed on them. One such mechanism, deciphered in the last decade, is small RNA (sRNA) mediated defense in plants. Small RNAs (sRNAs) have emerged as one of the major players in gene expression regulation in plants during developmental stages and under stress conditions. They are known to act both at transcriptional and post-transcriptional levels. Dicer-like (DCL), Argonaute (AGO), and RNA dependent RNA polymerase (RDR) constitute the major components of sRNA biogenesis machinery and are known to play a significant role in combating biotic and abiotic stresses. This study is, therefore, focused on identification and characterization of sRNA biogenesis proteins in three important legume crops, namely chickpea, pigeonpea, and groundnut. Phylogenetic analysis of these proteins between legume species classified them into distinct clades and suggests the evolutionary conservation of these genes across the members of Papillionidoids subfamily. Variable expression of sRNA biogenesis genes in response to the biotic stresses among the three legumes indicate the possible existence of specialized regulatory mechanisms in different legumes. This is the first ever study to understand the role of sRNA biogenesis genes in response to pathogen attacks in the studied legumes

Development and Application of High-Density Axiom Cajanus SNP Array with 56K SNPs to Understand the Genome Architecture of Released Cultivars and Founder Genotypes

As one of the major outputs of next-generation sequencing (NGS), a large number of genome-wide single-nucleotide polymorphisms (SNPs) have been developed in pigeonpea [Cajanus cajan (L.) Huth.]. However, SNPs require a genotyping platform or assay to be used in different evolutionary studies or in crop improvement programs. Therefore, we developed an Axiom Cajanus SNP array with 56K SNPs uniformly distributed across the genome and assessed its utility in a genetic diversity study. From the whole-genome resequencing (WGRS) data on 104 pigeonpea lines, ∼2 million sequence variations (SNPs and insertion–deletions [InDels]) were identified, from which a subset of 56,512 unique and informative sequence variations were selected to develop the array. The Axiom Cajanus SNP array developed was used for genotyping 103 pigeonpea lines encompassing 63 cultivars released between 1960 and 2014 and 40 breeding, germplasm, and founder lines. Genotyping data thus generated on 103 pigeonpea lines provided 51,201 polymorphic SNPs and InDels. Genetic diversity analysis provided in-depth insights into the genetic architecture and trends in temporal diversity in pigeonpea cultivars. Therefore, the continuous use of the high-density Axiom Cajanus SNP array developed will accelerate high-resolution trait mapping, marker-assisted breeding, and genomic selection efforts in pigeonpea

In Silico Prediction and Analysis of Caenorhabditis EF-hand Containing Proteins

Calcium (Ca+2) is a ubiquitous messenger in eukaryotes including Caenorhabditis. Ca+2-mediated signalling processes are usually carried out through well characterized proteins like calmodulin (CaM) and other Ca+2 binding proteins (CaBP). These proteins interact with different targets and activate it by bringing conformational changes. Majority of the EF-hand proteins in Caenorhabditis contain Ca+2 binding motifs. Here, we have performed homology modelling of CaM-like proteins using the crystal structure of Drosophila melanogaster CaM as a template. Molecular docking was applied to explore the binding mechanism of CaM-like proteins and IQ1 motif which is a ∼25 residues and conform to the consensus sequence (I, L, V)QXXXRXXXX(R,K) to serve as a binding site for different EF hand proteins. We made an attempt to identify all the EF-hand (a helix-loop-helix structure characterized by a 12 residues loop sequence involved in metal coordination) containing proteins and their Ca+2 binding affinity in Caenorhabditis by analysing the complete genome sequence. Docking studies revealed that F165, F169, L29, E33, F44, L57, M61, M96, M97, M108, G65, V115, F93, N104, E144 of CaM-like protein is involved in the interaction with IQ1 motif. A maximum of 170 EF-hand proteins and 39 non-EF-hand proteins with Ca+2/metal binding motif were identified. Diverse proteins including enzyme, transcription, translation and large number of unknown proteins have one or more putative EF-hands. Phylogenetic analysis revealed seven major classes/groups that contain some families of proteins. Various domains that we identified in the EF-hand proteins (uncharacterized) would help in elucidating their functions. It is the first report of its kind where calcium binding loop sequences of EF-hand proteins were analyzed to decipher their calcium affinities. Variation in Ca+2-binding affinity of EF-hand CaBP could be further used to study the behaviour of these proteins. Our analyses postulated that Ca+2 is likely to be key player in Caenorhabditis cell signalling

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability