Genome sequence analysis provides insights on genomic variation and late blight resistance genes in potato somatic hybrid (parents and progeny).

Wild Solanum species are the important resources for potato improvement. With the availability of potato genome and sequencing progress, knowledge about genomic resources is essential for novel genes discovery. Hence, the aim of this study was to decipher draft genome sequences of unique potato genotypes i.e. somatic hybrid P8 (J1), wild species S. pinnatisectum (J2), progeny MSH/14-112 (P8 × cv. Kufri Jyoti) (J3), and S. tuberosum dihaploid C-13 (J4). Draft genome sequencing using Illumina platform and reference-based assemblies with the potato genome yielded genome assembly size of 725.01 Mb (J1), 724.95 Mb (J2), 725.01 Mb (J3), and 809.59 Mb (J4). Further, 39,260 (J1), 25,711 (J2), 39,730 (J3) and 30,241 (J4) genes were identified and 17,411 genes were found common in the genotypes particularly late blight resistance genes (R3a, RGA2, RGA3, R1B-16, Rpi-blb2, Rpi and Rpi-vnt1). Gene ontology (GO) analysis showed that molecular function was predominant and signal transduction was major KEGG pathways. Further, gene enrichment analysis revealed dominance of metabolic process (GO: 0008152) in all the samples. Phylogeny analysis showed relatedness with potato and other plant species. Heterozygous single nucleotide polymorphism (SNP) was more than homozygous, and SNP in genic region was more than inter-genic region. Copy number variation (CNV) analysis indicated greater number of deletions than duplications. Sequence diversity and conserved motifs analysis revealed variation for late blight resistance genes. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis showed differential expression of late blight resistance genes. Our study provides insights on genome sequence, structural variation and late blight resistance genes in potato somatic hybrid (parents and progeny) for future research.

Physiological and genome-wide RNA-sequencing analyses identify candidate genes in a nitrogen-use efficient potato cv. Kufri Gaurav.

Nitrogen (N) is an important nutrient for plant growth. However, its excess application leads to environmental damage. Hence, improving nitrogen use efficiency (NUE) of plant is one of the plausible options to solve the problems. Aim of this study was to identify candidate genes involved in enhancing NUE in potato cv. Kufri Gaurav (N efficient). Plants were grown in aeroponic with two contrasting N regimes (low N: 0.75 mM, and high N: 7.5 mM). Higher NUE in Kufri Gaurav was observed in low N based on the parameters like NUE, NUpE (N uptake efficiency), NUtE (N utilization efficiency) and AgNUE (agronomic NUE). Further, global gene expression profiles in root, leaf and stolon tissues were analyzed by RNA-sequencing using Ion Proton™ System. Quality data (≥Q20) of 2.04-2.73 Gb per sample were mapped with the potato genome. Statistically significant (P ≤ 0.05) differentially expressed genes (DEGs) were identified such as 176 (up-regulated) and 30 (down-regulated) in leaves, 39 (up-regulated) and 105 (down-regulated) in roots, and 81 (up-regulated) and 694 (down-regulated) in stolons. The gene ontology (GO) terms like metabolic process, cellular process and catalytic activity were predominant. Our RT-qPCR analysis confirmed the gene expression profiles of RNA-seq. Overall, we identified candidate genes associated with improving NUE such as superoxide dismutase, GDSL esterase lipase, probable phosphatase 2C, high affinity nitrate transporters, sugar transporter, proline rich proteins, transcription factors (VQ motif, SPX domain, bHLH) etc. Our findings suggest that these candidate genes probably play crucial roles in enhancing NUE in potato.

Transcriptome analysis reveals interplay between hormones, ROS metabolism and cell wall biosynthesis for drought-induced root growth in wheat.

The ability of roots to grow under drought stress is an adaptive trait for crop plants especially under rain fed and restricted irrigation regime. To unravel the molecular mechanism of drought induced-root growth, root transcriptomes of two wheat genotypes viz. Raj3765 and HD2329, with contrasting root growth under drought stress were analyzed. Drought stress significantly enhanced total root length in Raj3765 as compared to that of HD2329. RNA-seq analysis led to the identification of 2783 and 2638 differentially expressed genes (DEGs) in Raj3765 and HD2329, respectively, under drought stress as compared with non-stress conditions. Functional annotation, gene ontology and MapMan analysis of the DEGs revealed differential regulation of genes for pathways associated with root growth and stress tolerance. Drought stress significantly upregulated auxin receptor (AFB2) and ABA responsive transcription factors (MYB78, WRKY18 and GBF3) in roots of Raj3765. Although certain genes for ethylene pathway were downregulated in both the genotypes, ACC oxidase and 2OG-Fe(II) oxygenase were upregulated only in Raj3765 which might contribute to maintenance of a basal ethylene level to maintain root growth. Several genes related to cell wall biosynthesis and ROS metabolism were significantly upregulated in Raj3765. Genes related to gibberellic acid, jasmonic acid and phenylpropanoid pathways were downregulated in roots of both the genotypes under drought stress. Our analysis suggests that a coordinated yet complex interplay between hormones, cellular tolerance, cell wall synthesis and ROS metabolism are required for drought induced root growth in wheat.

Structural, Functional, and Evolutionary Characterization of Major Drought Transcription Factors Families in Maize.

Drought is one of the major threats to the maize yield especially in subtropical production systems. Understanding the genes and regulatory mechanisms of drought tolerance is important to sustain the yield. Transcription factors (TFs) play a major role in gene regulation under drought stress. In the present study, a set of 15 major TF families comprising 1,436 genes was structurally and functionally characterized. The functional annotation indicated that the genes were involved in ABA signaling, ROS scavenging, photosynthesis, stomatal regulation, and sucrose metabolism. Duplication was identified as the primary force in divergence and expansion of TF families. Phylogenetic relationship was developed for individual TF and combined TF families. Phylogenetic analysis clustered the genes into specific and mixed groups. Gene structure analysis revealed that more number of genes were intron-rich as compared to intron-less. Drought-responsive cis-regulatory elements such as ABREA, ABREB, DRE1, and DRECRTCOREAT have been identified. Expression and interaction analyses identified leaf-specific bZIP TF, GRMZM2G140355, as a potential contributor toward drought tolerance in maize. Protein-protein interaction network of 269 drought-responsive genes belonging to different TFs has been provided. The information generated on structural and functional characteristics, expression, and interaction of the drought-related TF families will be useful to decipher the drought tolerance mechanisms and to breed drought-tolerant genotypes in maize.

nifPred: Proteome-Wide Identification and Categorization of Nitrogen-Fixation Proteins of Diaztrophs Based on Composition-Transition-Distribution Features Using Support Vector Machine.

As inorganic nitrogen compounds are essential for basic building blocks of life (e.g., nucleotides and amino acids), the role of biological nitrogen-fixation (BNF) is indispensible. All nitrogen fixing microbes rely on the same nitrogenase enzyme for nitrogen reduction, which is in fact an enzyme complex consists of as many as 20 genes. However, the occurrence of six genes viz., nifB, nifD, nifE, nifH, nifK, and nifN has been proposed to be essential for a functional nitrogenase enzyme. Therefore, identification of these genes is important to understand the mechanism of BNF as well as to explore the possibilities for improving BNF from agricultural sustainability point of view. Further, though the computational tools are available for the annotation and phylogenetic analysis of nifH gene sequences alone, to the best of our knowledge no tool is available for the computational prediction of the above mentioned six categories of nitrogen-fixation (nif) genes or proteins. Thus, we proposed an approach, which is first of its kind for the computational identification of nif proteins encoded by the six categories of nif genes. Sequence-derived features were employed to map the input sequences into vectors of numeric observations that were subsequently fed to the support vector machine as input. Two types of classifier were constructed: (i) a binary classifier for classification of nif and non-nitrogen-fixation (non-nif) proteins, and (ii) a multi-class classifier for classification of six categories of nif proteins. Higher accuracies were observed for the combination of composition-transition-distribution (CTD) feature set and radial kernel, as compared to the other feature-kernel combinations. The overall accuracies were observed >90% in both binary and multi-class classifications. The developed approach further achieved >92% accuracy, while evaluated with blind (independent) test datasets. The developed approach also produced higher accuracy in identifying nif proteins, while evaluated using proteome-wide datasets of several species. Furthermore, we established a prediction server nifPred (http://webapp.cabgrid.res.in/nifPred) to assist the scientific community for proteome-wide identification of six categories of nif proteins. Besides, the source code of nifPred is also available at https://github.com/PrabinaMeher/nifPred. The developed web server is expected to supplement the transcriptional profiling and comparative genomics studies for the identification and functional annotation of genes related to BNF.

ir-HSP: Improved Recognition of Heat Shock Proteins, Their Families and Sub-types Based On g-Spaced Di-peptide Features and Support Vector Machine.

Heat shock proteins (HSPs) play a pivotal role in cell growth and variability. Since conventional approaches are expensive and voluminous protein sequence information is available in the post-genomic era, development of an automated and accurate computational tool is highly desirable for prediction of HSPs, their families and sub-types. Thus, we propose a computational approach for reliable prediction of all these components in a single framework and with higher accuracy as well. The proposed approach achieved an overall accuracy of ~84% in predicting HSPs, ~97% in predicting six different families of HSPs, and ~94% in predicting four types of DnaJ proteins, with bench mark datasets. The developed approach also achieved higher accuracy as compared to most of the existing approaches. For easy prediction of HSPs by experimental scientists, a user friendly web server ir-HSP is made freely accessible at http://cabgrid.res.in:8080/ir-hsp. The ir-HSP was further evaluated for proteome-wide identification of HSPs by using proteome datasets of eight different species, and ~50% of the predicted HSPs in each species were found to be annotated with InterPro HSP families/domains. Thus, the developed computational method is expected to supplement the currently available approaches for prediction of HSPs, to the extent of their families and sub-types.

Comparative Analysis of CDPK Family in Maize, Arabidopsis, Rice, and Sorghum Revealed Potential Targets for Drought Tolerance Improvement.

Calcium dependent protein kinases (CDPKs) play significant role in regulation of plant growth and development in response to various stresses including drought. A set of 32 CDPK genes identified in maize were further used for searching of orthologs in the model plant Arabidopsis (72) and major food crops such as rice (78) and sorghum (91). We comprehensively studied the phylogenetic relationship, annotations, gene duplications, gene structure, divergence time, 3-D protein structures and tissue-specific drought induced expression of CDPK genes in all four species. Variation in intron frequency in the studied species was one of the reasons for the functional diversity of CDPK genes to various stress responses. Protein kinase and protein kinase C phosphorylation site domains were the most conserved motifs identified in all species. Four groups were identified from the sequence-based phylogenetic analysis, in which maize CDPKs were clustered in group III. Expression data showed that the CDPK genes were highly expressed in leaf of maize, rice, and sorghum whereas in Arabidopsis the maximum expression was observed in root. The expression assay showed 5, 6, 11, and 9 were the commonly and differentially expressed drought-related orthologous genes in maize, Arabidopsis, rice, and sorghum, respectively. 3-D protein structure were predicted for the nine genes (Arabidopsis: 2, maize: 2, rice: 3, and sorghum: 2) showing differential expression in at least three species. The predicted 3-D structures were further evaluated and validated by Ramachandran plot, ANOLEA, ProSA, and Verify-3D. The superimposed 3-D structure of drought-related orthologous proteins retained similar folding pattern owing to their conserved nature. Functional annotation revealed the involvement of CDPK genes in various pathways such as osmotic homeostasis, cell protection, and root growth. The interactions of CDPK genes in various pathways play crucial role in imparting drought tolerance through different ABA and MAPK signaling cascades. These selected candidate genes could be targeted in development of drought tolerant genotypes in maize, rice, and sorghum through appropriate breeding approaches. Our comparative experiments of CDPK genes could also be extended in the drought stress breeding programmes of the related species.

Utilization of Molecular, Phenotypic, and Geographical Diversity to Develop Compact Composite Core Collection in the Oilseed Crop, Safflower (Carthamus tinctorius L.) through Maximization Strategy.

Safflower (Carthamus tinctorius L.) is a dryland oilseed crop yielding high quality edible oil. Previous studies have described significant phenotypic variability in the crop and used geographical distribution and phenotypic trait values to develop core collections. However, the molecular diversity component was lacking in the earlier collections thereby limiting their utility in breeding programs. The present study evaluated the phenotypic variability for 12 agronomically important traits during two growing seasons (2011-12 and 2012-13) in a global reference collection of 531 safflower accessions, assessed earlier by our group for genetic diversity and population structure using AFLP markers. Significant phenotypic variation was observed for all the agronomic traits in the representative collection. Cluster analysis of phenotypic data grouped the accessions into five major clusters. Accessions from the Indian Subcontinent and America harbored maximal phenotypic variability with unique characters for a few traits. MANOVA analysis indicated significant interaction between genotypes and environment for both the seasons. Initially, six independent core collections (CC1-CC6) were developed using molecular marker and phenotypic data for two seasons through POWERCORE and MSTRAT. These collections captured the entire range of trait variability but failed to include complete genetic diversity represented in 19 clusters reported earlier through Bayesian analysis of population structure (BAPS). Therefore, we merged the three POWERCORE core collections (CC1-CC3) to generate a composite core collection, CartC1 and three MSTRAT core collections (CC4-CC6) to generate another composite core collection, CartC2. The mean difference percentage, variance difference percentage, variable rate of coefficient of variance percentage, coincidence rate of range percentage, Shannon's diversity index, and Nei's gene diversity for CartC1 were 11.2, 43.7, 132.4, 93.4, 0.47, and 0.306, respectively while the corresponding values for CartC2 were 9.3, 58.8, 124.6, 95.8, 0.46, and 0.301. Each composite core collection represented the complete range of phenotypic and genetic variability of the crop including 19 BAPS clusters. This is the first report describing development of core collections in safflower using molecular marker data with phenotypic values and geographical distribution. These core collections will facilitate identification of genetic determinants of trait variability and effective utilization of the prevalent diversity in crop improvement programs.

Genome-wide development and deployment of informative intron-spanning and intron-length polymorphism markers for genomics-assisted breeding applications in chickpea.

The discovery and large-scale genotyping of informative gene-based markers is essential for rapid delineation of genes/QTLs governing stress tolerance and yield component traits in order to drive genetic enhancement in chickpea. A genome-wide 119169 and 110491 ISM (intron-spanning markers) from 23129 desi and 20386 kabuli protein-coding genes and 7454 in silico InDel (insertion-deletion) (1-45-bp)-based ILP (intron-length polymorphism) markers from 3283 genes were developed that were structurally and functionally annotated on eight chromosomes and unanchored scaffolds of chickpea. A much higher amplification efficiency (83%) and intra-specific polymorphic potential (86%) detected by these markers than that of other sequence-based genetic markers among desi and kabuli chickpea accessions was apparent even by a cost-effective agarose gel-based assay. The genome-wide physically mapped 1718 ILP markers assayed a wider level of functional genetic diversity (19-81%) and well-defined phylogenetics among domesticated chickpea accessions. The gene-derived 1424 ILP markers were anchored on a high-density (inter-marker distance: 0.65cM) desi intra-specific genetic linkage map/functional transcript map (ICC 4958×ICC 2263) of chickpea. This reference genetic map identified six major genomic regions harbouring six robust QTLs mapped on five chromosomes, which explained 11-23% seed weight trait variation (7.6-10.5 LOD) in chickpea. The integration of high-resolution QTL mapping with differential expression profiling detected six including one potential serine carboxypeptidase gene with ILP markers (linked tightly to the major seed weight QTLs) exhibiting seed-specific expression as well as pronounced up-regulation especially in seeds of high (ICC 4958) as compared to low (ICC 2263) seed weight mapping parental accessions. The marker information generated in the present study was made publicly accessible through a user-friendly web-resource, "Chickpea ISM-ILP Marker Database". The designing of multiple ISM and ILP markers (2-5 markers/gene) from an individual gene (transcription factor) with numerous aforementioned desirable genetic attributes can widen the user-preference to select suitable primer combination for simultaneous large-scale assaying of functional allelic variation, natural allelic diversity, molecular mapping and expression profiling of genes among chickpea accessions. This will essentially accelerate the identification of functionally relevant molecular tags regulating vital agronomic traits for genomics-assisted crop improvement by optimal resource expenses in chickpea.

Genome-wide generation and use of informative intron-spanning and intron-length polymorphism markers for high-throughput genetic analysis in rice.

We developed genome-wide 84634 ISM (intron-spanning marker) and 16510 InDel-fragment length polymorphism-based ILP (intron-length polymorphism) markers from genes physically mapped on 12 rice chromosomes. These genic markers revealed much higher amplification-efficiency (80%) and polymorphic-potential (66%) among rice accessions even by a cost-effective agarose gel-based assay. A wider level of functional molecular diversity (17-79%) and well-defined precise admixed genetic structure was assayed by 3052 genome-wide markers in a structured population of indica, japonica, aromatic and wild rice. Six major grain weight QTLs (11.9-21.6% phenotypic variation explained) were mapped on five rice chromosomes of a high-density (inter-marker distance: 0.98 cM) genetic linkage map (IR 64 x Sonasal) anchored with 2785 known/candidate gene-derived ISM and ILP markers. The designing of multiple ISM and ILP markers (2 to 4 markers/gene) in an individual gene will broaden the user-preference to select suitable primer combination for efficient assaying of functional allelic variation/diversity and realistic estimation of differential gene expression profiles among rice accessions. The genomic information generated in our study is made publicly accessible through a user-friendly web-resource, "Oryza ISM-ILP marker" database. The known/candidate gene-derived ISM and ILP markers can be enormously deployed to identify functionally relevant trait-associated molecular tags by optimal-resource expenses, leading towards genomics-assisted crop improvement in rice.

Genome-wide association mapping of salinity tolerance in rice (Oryza sativa).

Salinity tolerance in rice is highly desirable to sustain production in areas rendered saline due to various reasons. It is a complex quantitative trait having different components, which can be dissected effectively by genome-wide association study (GWAS). Here, we implemented GWAS to identify loci controlling salinity tolerance in rice. A custom-designed array based on 6,000 single nucleotide polymorphisms (SNPs) in as many stress-responsive genes, distributed at an average physical interval of <100 kb on 12 rice chromosomes, was used to genotype 220 rice accessions using Infinium high-throughput assay. Genetic association was analysed with 12 different traits recorded on these accessions under field conditions at reproductive stage. We identified 20 SNPs (loci) significantly associated with Na(+)/K(+) ratio, and 44 SNPs with other traits observed under stress condition. The loci identified for various salinity indices through GWAS explained 5-18% of the phenotypic variance. The region harbouring Saltol, a major quantitative trait loci (QTLs) on chromosome 1 in rice, which is known to control salinity tolerance at seedling stage, was detected as a major association with Na(+)/K(+) ratio measured at reproductive stage in our study. In addition to Saltol, we also found GWAS peaks representing new QTLs on chromosomes 4, 6 and 7. The current association mapping panel contained mostly indica accessions that can serve as source of novel salt tolerance genes and alleles. The gene-based SNP array used in this study was found cost-effective and efficient in unveiling genomic regions/candidate genes regulating salinity stress tolerance in rice.

Features of 5'-splice-site efficiency derived from disease-causing mutations and comparative genomics.

Many human diseases, including Fanconi anemia, hemophilia B, neurofibromatosis, and phenylketonuria, can be caused by 5'-splice-site (5'ss) mutations that are not predicted to disrupt splicing, according to position weight matrices. By using comparative genomics, we identify pairwise dependencies between 5'ss nucleotides as a conserved feature of the entire set of 5'ss. These dependencies are also conserved in human-mouse pairs of orthologous 5'ss. Many disease-associated 5'ss mutations disrupt these dependencies, as can some human SNPs that appear to alter splicing. The consistency of the evidence signifies the relevance of this approach and suggests that 5'ss SNPs play a role in complex diseases.