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

Pearl millet [Cenchrus americanus (L.) Morrone] is a staple food for more than 90 million farmers in arid and semi-arid regions of sub-Saharan Africa, India and South Asia. We report the ∼1.79 Gb draft whole genome sequence of reference genotype Tift 23D2B1-P1-P5, which contains an estimated 38,579 genes. We highlight the substantial enrichment for wax biosynthesis genes, which may contribute to heat and drought tolerance in this crop. We resequenced and analyzed 994 pearl millet lines, enabling insights into population structure, genetic diversity and domestication. We use these resequencing data to establish marker trait associations for genomic selection, to define heterotic pools, and to predict hybrid performance. We believe that these resources should empower researchers and breeders to improve this important staple crop.

NGS-QCbox and Raspberry for Parallel, Automated and Rapid Quality Control Analysis of Large-Scale Next Generation Sequencing (Illumina) Data.

Rapid popularity and adaptation of next generation sequencing (NGS) approaches have generated huge volumes of data. High throughput platforms like Illumina HiSeq produce terabytes of raw data that requires quick processing. Quality control of the data is an important component prior to the downstream analyses. To address these issues, we have developed a quality control pipeline, NGS-QCbox that scales up to process hundreds or thousands of samples. Raspberry is an in-house tool, developed in C language utilizing HTSlib (v1.2.1) (http://htslib.org), for computing read/base level statistics. It can be used as stand-alone application and can process both compressed and uncompressed FASTQ format files. NGS-QCbox integrates Raspberry with other open-source tools for alignment (Bowtie2), SNP calling (SAMtools) and other utilities (bedtools) towards analyzing raw NGS data at higher efficiency and in high-throughput manner. The pipeline implements batch processing of jobs using Bpipe (https://github.com/ssadedin/bpipe) in parallel and internally, a fine grained task parallelization utilizing OpenMP. It reports read and base statistics along with genome coverage and variants in a user friendly format. The pipeline developed presents a simple menu driven interface and can be used in either quick or complete mode. In addition, the pipeline in quick mode outperforms in speed against other similar existing QC pipeline/tools. The NGS-QCbox pipeline, Raspberry tool and associated scripts are made available at the URL https://github.com/CEG-ICRISAT/NGS-QCbox and https://github.com/CEG-ICRISAT/Raspberry for rapid quality control analysis of large-scale next generation sequencing (Illumina) data.

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. Database URL: http://cicarvardb.icrisat.org.

An integrated SNP mining and utilization (ISMU) pipeline for next generation sequencing data.

Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software.

CicArMiSatDB: the chickpea microsatellite database.

BACKGROUND: Chickpea (Cicer arietinum) is a widely grown legume crop in tropical, sub-tropical and temperate regions. Molecular breeding approaches seem to be essential for enhancing crop productivity in chickpea. Until recently, limited numbers of molecular markers were available in the case of chickpea for use in molecular breeding. However, the recent advances in genomics facilitated the development of large scale markers especially SSRs (simple sequence repeats), the markers of choice in any breeding program. Availability of genome sequence very recently opens new avenues for accelerating molecular breeding approaches for chickpea improvement. DESCRIPTION: In order to assist genetic studies and breeding applications, we have developed a user friendly relational database named the Chickpea Microsatellite Database (CicArMiSatDB http://cicarmisatdb.icrisat.org). This database provides detailed information on SSRs along with their features in the genome. SSRs have been classified and made accessible through an easy-to-use web interface. CONCLUSIONS: This database is expected to help chickpea community in particular and legume community in general, to select SSRs of particular type or from a specific region in the genome to advance both basic genomics research as well as applied aspects of crop improvement.

De Novo transcriptome assembly (NGS) of Curcuma longa L. rhizome reveals novel transcripts related to anticancer and antimalarial terpenoids.

Herbal remedies are increasingly being recognised in recent years as alternative medicine for a number of diseases including cancer. Curcuma longa L., commonly known as turmeric is used as a culinary spice in India and in many Asian countries has been attributed to lower incidences of gastrointestinal cancers. Curcumin, a secondary metabolite isolated from the rhizomes of this plant has been shown to have significant anticancer properties, in addition to antimalarial and antioxidant effects. We sequenced the transcriptome of the rhizome of the 3 varieties of Curcuma longa L. using Illumina reversible dye terminator sequencing followed by de novo transcriptome assembly. Multiple databases were used to obtain a comprehensive annotation and the transcripts were functionally classified using GO, KOG and PlantCyc. Special emphasis was given for annotating the secondary metabolite pathways and terpenoid biosynthesis pathways. We report for the first time, the presence of transcripts related to biosynthetic pathways of several anti-cancer compounds like taxol, curcumin, and vinblastine in addition to anti-malarial compounds like artemisinin and acridone alkaloids, emphasizing turmeric's importance as a highly potent phytochemical. Our data not only provides molecular signatures for several terpenoids but also a comprehensive molecular resource for facilitating deeper insights into the transcriptome of C. longa.

Next generation sequencing and de novo transcriptome analysis of Costus pictus D. Don, a non-model plant with potent anti-diabetic properties.

BACKGROUND: Phyto-remedies for diabetic control are popular among patients with Type II Diabetes mellitus (DM), in addition to other diabetic control measures. A number of plant species are known to possess diabetic control properties. Costus pictus D. Don is popularly known as "Insulin Plant" in Southern India whose leaves have been reported to increase insulin pools in blood plasma. Next Generation Sequencing is employed as a powerful tool for identifying molecular signatures in the transcriptome related to physiological functions of plant tissues. We sequenced the leaf transcriptome of C. pictus using Illumina reversible dye terminator sequencing technology and used combination of bioinformatics tools for identifying transcripts related to anti-diabetic properties of C. pictus. RESULTS: A total of 55,006 transcripts were identified, of which 69.15% transcripts could be annotated. We identified transcripts related to pathways of bixin biosynthesis and geraniol and geranial biosynthesis as major transcripts from the class of isoprenoid secondary metabolites and validated the presence of putative norbixin methyltransferase, a precursor of Bixin. The transcripts encoding these terpenoids are known to be Peroxisome Proliferator-Activated Receptor (PPAR) agonists and anti-glycation agents. Sequential extraction and High Performance Liquid Chromatography (HPLC) confirmed the presence of bixin in C. pictus methanolic extracts. Another significant transcript identified in relation to anti-diabetic, anti-obesity and immuno-modulation is of Abscisic Acid biosynthetic pathway. We also report many other transcripts for the biosynthesis of antitumor, anti-oxidant and antimicrobial metabolites of C. pictus leaves. CONCLUSION: Solid molecular signatures (transcripts related to bixin, abscisic acid, and geranial and geraniol biosynthesis) for the anti-diabetic properties of C. pictus leaves and vital clues related to the other phytochemical functions like antitumor, anti-oxidant, immuno-modulatory, anti-microbial and anti-malarial properties through the secondary metabolite pathway annotations are reported. The data provided will be of immense help to researchers working in the treatment of DM using herbal therapies.