Microbiome of Pukzing Cave in India shows high antimicrobial activity against plant and animal pathogens

Pukzing cave, the largest cave of Mizoram, India was explored for bacterial diversity. Culture dependent method revealed 235 bacterial isolates using three different treatments. Identity of the microbial species was confirmed by 16S rDNA sequencing. The highest bacterial population was recovered from heat treatment (n = 97;41.2%) followed by normal (n = 79;33.6%) and cold treatment (n = 59;25.1%) indicating dominance of moderate thermophiles. Antimicrobial potential of isolates showed 20.4% isolates having antimicrobial ability against tested pathogens. Amplicon sequencing of PKSI, PKSII and NRP specific genes revealed presence of AMP genes in the microbial population. Six microbial pathogens were selected for screening as they are well known for different disease cause organism in various fields such as agriculture and human health. Cave environment harbors unique microbial flora and hypervariable region V4 is more informative. Higher activity of AMP assay against these microbes indicates that cave microbial communities could be potential source of future genomic resources.

Harmonizing technological advances in phenomics and genomics for enhanced salt tolerance in rice from a practical perspective

Half of the global human population is dependent on rice as a staple food crop and more than 25% increase in rice productivity is required to feed the global population by 2030. With increase in irrigation, global warming and rising sea level, rising salinity has become one of the major challenges to enhance the rice productivity. Since the loss on this account is to the tune of US$12 billion per annum, it necessitates the global attention. In the era of technological advancement, substantial progress has been made on phenomics and genomics data generation but reaping benefit of this in rice salinity variety development in terms of cost, time and precision requires their harmonization. There is hardly any comprehensive holistic review for such combined approach. Present review describes classical salinity phenotyping approaches having morphological, physiological and biochemical components. It also gives a detailed account of invasive and non-invasive approaches of phenomic data generation and utilization. Classical work of rice salinity QLTs mapping in the form of chromosomal atlas has been updated. This review describes how QTLs can be further dissected into QTN by GWAS and transcriptomic approaches. Opportunities and progress made by transgenic, genome editing, metagenomics approaches in combating rice salinity problems are discussed. Major aim of this review is to provide a comprehensive over-view of hitherto progress made in rice salinity tolerance research which is required to understand bridging of phenotype based breeding with molecular breeding. This review is expected to assist rice breeders in their endeavours by fetching greater harmonization of technological advances in phenomics and genomics for better pragmatic approach having practical perspective.

Uncovering Genomic Regions Associated With 36 Agro-Morphological Traits in Indian Spring Wheat Using GWAS

Wheat genetic improvement by integration of advanced genomic technologies is one way of improving productivity. To facilitate the breeding of economically important traits in wheat, SNP loci and underlying candidate genes associated with the 36 agro-morphological traits were studied in a diverse panel of 404 genotypes. By using Breeders' 35K Axiom array in a comprehensive genome-wide association study covering 4364.79 cM of the wheat genome and applying a compressed mixed linear model, a total of 146 SNPs (-log10 P ≥ 4) were found associated with 23 traits out of 36 traits studied explaining 3.7-47.0% of phenotypic variance. To reveal this a subset of 260 genotypes was characterized phenotypically for six quantitative traits [days to heading (DTH), days to maturity (DTM), plant height (PH), spike length (SL), awn length (Awn_L), and leaf length (Leaf_L)] under five environments. Gene annotations mined ∼38 putative candidate genes which were confirmed using tissue and stage specific gene expression data from RNA Seq. We observed strong co-localized loci for four traits (glume pubescence, SL, PH, and awn color) on chromosome 1B (24.64 cM) annotated five putative candidate genes. This study led to the discovery of hitherto unreported loci for some less explored traits (such as leaf sheath wax, awn attitude, and glume pubescence) besides the refined chromosomal regions of known loci associated with the traits. This study provides valuable information of the genetic loci and their potential genes underlying the traits such as awn characters which are being considered as important contributors toward yield enhancement.

Development of species specific putative miRNA and its target prediction tool in wheat (Triticum aestivum L.)

MicroRNA are 20-24 nt, non-coding, single stranded molecule regulating traits and stress response. Tissue and time specific expression limits its detection, thus is major challenge in their discovery. Wheat has limited 119 miRNAs in MiRBase due to limitation of conservation based methodology where old and new miRNA genes gets excluded. This is due to origin of hexaploid wheat by three successive hybridization, older AA, BB and younger DD subgenome. Species specific miRNA prediction (SMIRP concept) based on 152 thermodynamic features of training dataset using support vector machine learning approach has improved prediction accuracy to 97.7%. This has been implemented in TamiRPred ( http://webtom.cabgrid.res.in/tamirpred ). We also report highest number of putative miRNA genes (4464) of wheat from whole genome sequence populated in database developed in PHP and MySQL. TamiRPred has predicted 2092 (>45.10%) additional miRNA which was not predicted by miRLocator. Predicted miRNAs have been validated by miRBase, small RNA libraries, secondary structure, degradome dataset, star miRNA and binding sites in wheat coding region. This tool can accelerate miRNA polymorphism discovery to be used in wheat trait improvement. Since it predicts chromosome-wise miRNA genes with their respective physical location thus can be transferred using linked SSR markers. This prediction approach can be used as model even in other polyploid crops.

PolyMorphPredict: A Universal Web-Tool for Rapid Polymorphic Microsatellite Marker Discovery From Whole Genome and Transcriptome Data

Microsatellites are ubiquitously distributed, polymorphic repeat sequence valuable for association, selection, population structure and identification. They can be mined by genomic library, probe hybridization and sequencing of selected clones. Such approach has many limitations like biased hybridization and selection of larger repeats. In silico mining of polymorphic markers using data of various genotypes can be rapid and economical. Available tools lack in some or other aspects like: targeted user defined primer generation, polymorphism discovery using multiple sequence, size and number limits of input sequence, no option for primer generation and e-PCR evaluation, transferability, lack of complete automation and user-friendliness. They also lack the provision to evaluate published primers in e-PCR mode to generate additional allelic data using re-sequenced data of various genotypes for judicious utilization of previously generated data. We developed the tool (PolyMorphPredict) using Perl, R, Java and launched at Apache which is available at http://webtom.cabgrid.res.in/polypred/. It mines microsatellite loci and computes primers from genome/transcriptome data of any species. It can perform e-PCR using published primers for polymorphism discovery and across species transferability of microsatellite loci. Present tool has been evaluated using five species of different genome size having 21 genotypes. Though server is equipped with genomic data of three species for test run with gel simulation, but can be used for any species. Further, polymorphism predictability has been validated using in silico and in vitro PCR of four rice genotypes. This tool can accelerate the in silico microsatellite polymorphism discovery in re-sequencing projects of any species of plant and animal for their diversity estimation along with variety/breed identification, population structure, MAS, QTL and gene discovery, traceability, parentage testing, fungal diagnostics and genome finishing.

Transcriptomic signature of drought response in pearl millet (Pennisetum glaucum (L.) and development of web-genomic resources

Pearl millet, (Pennisetum glaucum L.), an efficient (C4) crop of arid/semi-arid regions is known for hardiness. Crop is valuable for bio-fortification combating malnutrition and diabetes, higher caloric value and wider climatic resilience. Limited studies are done in pot-based experiments for drought response at gene-expression level, but field-based experiment mimicking drought by withdrawal of irrigation is still warranted. We report de novo assembly-based transcriptomic signature of drought response induced by irrigation withdrawal in pearl millet. We found 19983 differentially expressed genes, 7595 transcription factors, gene regulatory network having 45 hub genes controlling drought response. We report 34652 putative markers (4192 simple sequence repeats, 12111 SNPs and 6249 InDels). Study reveals role of purine and tryptophan metabolism in ABA accumulation mediating abiotic response in which MAPK acts as major intracellular signal sensing drought. Results were validated by qPCR of 13 randomly selected genes. We report the first web-based genomic resource ( http://webtom.cabgrid.res.in/pmdtdb/ ) which can be used for candidate genes-based SNP discovery programs and trait-based association studies. Looking at climatic change, nutritional and pharmaceutical importance of this crop, present investigation has immense value in understanding drought response in field condition. This is important in germplasm management and improvement in endeavour of pearl millet productivity.

MiSNPDb: a web-based genomic resources of tropical ecology fruit mango (Mangifera indica L.) for phylogeography and varietal differentiation

Mango is one of the most important fruits of tropical ecological region of the world, well known for its nutritive value, aroma and taste. Its world production is >45MT worth >200 billion US dollars. Genomic resources are required for improvement in productivity and management of mango germplasm. There is no web-based genomic resources available for mango. Hence rapid and cost-effective high throughput putative marker discovery is required to develop such resources. RAD-based marker discovery can cater this urgent need till whole genome sequence of mango becomes available. Using a panel of 84 mango varieties, a total of 28.6 Gb data was generated by ddRAD-Seq approach on Illumina HiSeq 2000 platform. A total of 1.25 million SNPs were discovered. Phylogenetic tree using 749 common SNPs across these varieties revealed three major lineages which was compared with geographical locations. A web genomic resources MiSNPDb, available at http://webtom.cabgrid.res.in/mangosnps/ is based on 3-tier architecture, developed using PHP, MySQL and Javascript. This web genomic resources can be of immense use in the development of high density linkage map, QTL discovery, varietal differentiation, traceability, genome finishing and SNP chip development for future GWAS in genomic selection program. We report here world’s first web-based genomic resources for genetic improvement and germplasm management of mango.

Computational deciphering of biotic stress associated genes in tomato (Solanum lycopersicum)

Tomato (Solanum lycopersicum) is one of the major vegetable plant and a model system for fruit development. Its global importance is due to its lycopene pigment which has anti-oxidative and anti-cancerous properties. Though > 1.5 M biotic stress associated ESTs of tomato are available but cumulative analysis to predict genes is warranted. Availability of whole genome de novo assembly can advantageously be used to map them over different chromosome. Further, available 0.14 M catalogued markers can be used to introgress specific desirable genes in varietal improvement program. We report here 57 novel genes associated with biotic stress of tomato along with 50 genes having physical location over different chromosomes. We also report 52 cis-regulating elements and 69 putative miRNAs which are involved in regulation of these biotic stresses associated genes. These putative candidate genes associated with biotic stress can be used in molecular breeding in the endeavor of tomato productivity along with its sustainable germplasm management.

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ESts related to biotic stress were collected and assembled into contigs.

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Total 57 novel genes were computationally mined from the assembled contigs.

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Among the predicted novel gene, 50 genes were mapped on tomato genome.

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52 cis-regulating elements and 69 putative miRNAs were predicted for the novel genes.

Draft whole genome sequence of groundnut stem rot fungus Athelia rolfsii revealing genetic architect of its pathogenicity and virulence

Groundnut (Arachis hypogaea L.) is an important oil seed crop having major biotic constraint in production due to stem rot disease caused by fungus, Athelia rolfsii causing 25–80% loss in productivity. As chemical and biological combating strategies of this fungus are not very effective, thus genome sequencing can reveal virulence and pathogenicity related genes for better understanding of the host-parasite interaction. We report draft assembly of Athelia rolfsii genome of ~73 Mb having 8919 contigs. Annotation analysis revealed 16830 genes which are involved in fungicide resistance, virulence and pathogenicity along with putative effector and lethal genes. Secretome analysis revealed CAZY genes representing 1085 enzymatic genes, glycoside hydrolases, carbohydrate esterases, carbohydrate-binding modules, auxillary activities, glycosyl transferases and polysaccharide lyases. Repeat analysis revealed 11171 SSRs, LTR, GYPSY and COPIA elements. Comparative analysis with other existing ascomycotina genome predicted conserved domain family of WD40, CYP450, Pkinase and ABC transporter revealing insight of evolution of pathogenicity and virulence. This study would help in understanding pathogenicity and virulence at molecular level and development of new combating strategies. Such approach is imperative in endeavour of genome based solution in stem rot disease management leading to better productivity of groundnut crop in tropical region of world.

Low-depth shotgun sequencing resolves complete mitochondrial genome sequence of Labeo rohita

Labeo rohita, popularly known as rohu, is a widely cultured species in whole Indian subcontinent. In the present study, we used in-silico approach to resolve complete mitochondrial genome of rohu. Low-depth shotgun sequencing using Roche 454 GS FLX (Branford, Connecticut, USA) followed by de novo assembly in CLC Genomics Workbench version 7.0.4 (Aarhus, Denmark) revealed the complete mitogenome of L. rohita to be 16 606 bp long (accession No. KR185963). It comprised of 13 protein-coding genes, 22 tRNAs, 2 rRNAs and 1 putative control region. The gene order and organization are similar to most vertebrates. The mitogenome in the present investigation has 99% similarity with that of previously reported mitogenomes of rohu and this is also evident from the phylogenetic study using maximum-likelihood (ML) tree method. This study was done to determine the feasibility, accuracy and reliability of low-depth sequence data obtained from NGS platform as compared to the Sanger sequencing. Thus, NGS technology has proven to be competent and a rapid in-silico alternative to resolve the complete mitochondrial genome sequence, thereby reducing labors and time.

Locus minimization in breed prediction using artificial neural network approach

Molecular markers, viz. microsatellites and single nucleotide polymorphisms, have revolutionized breed identification through the use of small samples of biological tissue or germplasm, such as blood, carcass samples, embryos, ova and semen, that show no evident phenotype. Classical tools of molecular data analysis for breed identification have limitations, such as the unavailability of referral breed data, causing increased cost of collection each time, compromised computational accuracy and complexity of the methodology used. We report here the successful use of an artificial neural network (ANN) in background to decrease the cost of genotyping by locus minimization. The webserver is freely accessible (http://nabg.iasri.res.in/bisgoat) to the research community. We demonstrate that the machine learning (ANN) approach for breed identification is capable of multifold advantages such as locus minimization, leading to a drastic reduction in cost, and web availability of reference breed data, alleviating the need for repeated genotyping each time one investigates the identity of an unknown breed. To develop this model web implementation based on ANN, we used 51,850 samples of allelic data of microsatellite-marker-based DNA fingerprinting on 25 loci covering 22 registered goat breeds of India for training. Minimizing loci to up to nine loci through the use of a multilayer perceptron model, we achieved 96.63% training accuracy. This server can be an indispensable tool for identification of existing breeds and new synthetic commercial breeds, leading to protection of intellectual property in case of sovereignty and bio-piracy disputes. This server can be widely used as a model for cost reduction by locus minimization for various other flora and fauna in terms of variety, breed and/or line identification, especially in conservation and improvement programs.

Analysis and functional annotation of expressed sequence tags of water buffalo

An elucidated genome of domestic livestock river buffalo will contribute enormously to economy and better understanding of genome evolution as well. An attempt is made to obtain genomic information on buffalo, based on total Expressed Sequence Tags (ESTs) of Bubalus bubalis available in public domain. These ESTs were annotated and classified into 15 different functional categories based on their homology to the known proteins. Interestingly, 41.79% of the contigs were found to be buffalo specific novel ESTs with respect to other species used in analysis which needs further studies. Also, 224 pSNPs (putative Single Nucleotide Polymorphism) were detected. This study will provide a home base for further genomic studies of buffalo and comparative studies enabling a starting point for the genome annotation of the organism. Supplementary materials are available for this article online.

PIPEMicroDB: microsatellite database and primer generation tool for pigeonpea genome

Molecular markers play a significant role for crop improvement in desirable characteristics, such as high yield, resistance to disease and others that will benefit the crop in long term. Pigeonpea (Cajanus cajan L.) is the recently sequenced legume by global consortium led by ICRISAT (Hyderabad, India) and been analysed for gene prediction, synteny maps, markers, etc. We present PIgeonPEa Microsatellite DataBase (PIPEMicroDB) with an automated primer designing tool for pigeonpea genome, based on chromosome wise as well as location wise search of primers. Total of 123 387 Short Tandem Repeats (STRs) were extracted from pigeonpea genome, available in public domain using MIcroSAtellite tool (MISA). The database is an online relational database based on ‘three-tier architecture’ that catalogues information of microsatellites in MySQL and user-friendly interface is developed using PHP. Search for STRs may be customized by limiting their location on chromosome as well as number of markers in that range. This is a novel approach and is not been implemented in any of the existing marker database. This database has been further appended with Primer3 for primer designing of selected markers with left and right flankings of size up to 500 bp. This will enable researchers to select markers of choice at desired interval over the chromosome. Furthermore, one can use individual STRs of a targeted region over chromosome to narrow down location of gene of interest or linked Quantitative Trait Loci (QTLs). Although it is an in silico approach, markers’ search based on characteristics and location of STRs is expected to be beneficial for researchers.

Database URL:http://cabindb.iasri.res.in/pigeonpea/

Biotic stress resistance in agriculture through antimicrobial peptides

Antimicrobial peptides (AMPs) are the hosts' defense molecules against microbial pathogens and gaining extensive research attention worldwide. These have been reported to play vital role of host innate immunity in response to microbial challenges. AMPs can be used as a natural antibiotic as an alternative of their chemical counterpart for protection of plants/animals against diseases. There are a number of sources of AMPs including prokaryotic and eukaryotic organisms and are present, both in vertebrates and invertebrates. AMPs can be classified as cationic or anionic, based on net charges. Large number of databases and tools are available in the public domain which can be used for development of new genetically modified disease resistant varieties/breeds for agricultural production. The results of the biotechnological research as well as genetic engineering related to AMPs have shown high potential for reduction of economic losses of agricultural produce due to pathogens. In this article, an attempt has been made to introduce the role of AMPs in relation to plants and animals. Their functional and structural characteristics have been described in terms of its role in agriculture. Different sources of AMPs and importance of these sources has been reviewed in terms of its availability. This article also reviews the bioinformatics resources including different database tools and algorithms available in public domain. References of promising biotechnology research in relation to AMPs, prospects of AMPs for further development of genetically modified varieties/breeds are highlighted. AMPs are valuable resource for students, researchers, educators and medical and industrial personnel.

Determination of MHC binding peptides and epitopes from non-structural movement (NSm) protein of groundnut bud necrosis virus

Groundnut bud necrosis virus (GBNV) is recognized as one of the most economically important viruses and is known to affect several crops including peanut, potato, tomato and soybean. For managing plant virus diseases, determination of their causal agents' identity at an early stage of crop is a pre-requisite. In the present study, NSm protein of GBNV has been used to predict out MHC binding peptides and epitopes that are highly suitable for antigenicity. Eighteen peptide regions were found to have high affinity. Few of these NSm protein TAP transporters are 126- RRYMHISRL with score 11.638, 125- NRRYMHISR with score 10.280, 46- AIMNKAKTL with score 7.762, 120- PTWNSNRRY with score 7.632 and 171- ASLKDPMCF with score 7.277. The support vector machine (SVM) based approach predicted MHCII-IAb peptide regions, 45- SAIMNKAKT, 151- ASLIDPNKM, 23- PAVKKENNR, 229- PIAAENNTC, (optimal score 0.938); MHCII-IAd peptide regions, 208- YAKGVGFAS, 101- NDSLVGNGN, 55- NGKQYVSSG, 63-GDSSVLGTY, (optimal score 0.852); MHCII-IAg7 peptide regions, 277- LQKAAERLA, 145- SKNNVKASL, 228- TPIAAENNT, 276- SLQKAAERL, (optimal score 1.640); and MHCII- RT1.B peptide regions, 193- TPKQCMQLN, 195- KQCMQLNLT, 246- KVIQSAALI, 166- IISRQASLK, (optimal score 0.800) as binders from NSm protein. The most suitable predicted segments in NSm protein of GBNV virus found in the study are 164- KIIISRQASLKDPMCFIFHLNWS- 186 and 237-CDVVPINRAKVIQSAALIEACKLMIP-262. These two fragments, obtained from non-structural movement protein with average propensity 1.016, are high-efficiency binders and may, therefore be used in cross protection to provide resistance against GBNV and develop GBNV specific antibodies that can be exploited in sero-diagnostics.