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

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

Pearl millet genome sequence provides a resource to improve agronomic traits in arid environments

Pearl millet [Pennisetum glaucum (L.) R. Br., syn. Cenchrus americanus (L.) Morrone], is a staple food for over 90 million poor farmers in arid and semi-arid regions of sub-Saharan Africa and South Asia. We report the ~1.79 Gb genome sequence of reference genotype Tift 23D2B1-P1-P5, which contains an estimated 38,579 genes. Resequencing analysis of 994 (963 inbreds of the highly cross-pollinated cultigen, and 31 wild accessions) provides insights into population structure, genetic diversity, evolution and domestication history. In addition we demonstrated the use of re-sequence data for establishing marker trait associations, genomic selection and prediction of hybrid performance and defining heterotic pools. The genome wide variations and abiotic stress proteome data are useful resources for pearl millet improvement through deploying modern breeding tools for accelerating genetic gains in pearl millet.publishersversionPeer reviewe

Structural models of <i>CarF-box_PP2</i> and <i>CarF-box_LysM</i>.

<p>The 3D structures are shown as (A,D) ribbon diagram and (C,F) surface view. The F-box domains are labelled and shown in blue colour. The C-terminal domains, PP2 and LysM are shown in red. Conserved residues in the F-box domains (B,E) are shown in pink.</p

Gene structure of A) <i>CarF-box_PP2</i> B) <i>CarF-box_LysM</i>.

<p>Red boxes indicate exons, grey boxes are UTRs and lines between boxes indicate introns. Conserved domain organization as determined using NCBI conserved domain database (<a href="http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi/" target="_blank">http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi/</a>).</p

Subcellular localization of GFP-tagged <i>CarF-box_PP2</i> and <i>CarF-box_LysM</i> proteins.

<p>Transiently transformed tobacco leaf epidermal cells show enrichment of the <i>CarF-box_PP2</i> protein in the cytoplasm and <i>CarF-box_LysM</i> in the nucleus. A) Flourescence, B) Bright field, C) Merged and D) DAPI stained nuclei. 1) GFP only (Control) 2) <i>p35S</i>::<i>CarF-box_PP2-GFP</i>, 3) <i>p35S</i>::<i>CarF-box_LysM-GFP</i>. Scale bars = 50 μm.</p