Genotyping by sequencing-based linkage map construction and identification of quantitative trait loci for yield-related traits and oil content in Jatropha (Jatropha curcas L.).

BACKGROUND: Jatropha (Jatropha curcas L.) has been considered as a potential bioenergy crop and its genetic improvement is essential for higher seed yield and oil content which has been hampered due to lack of desirable molecular markers. METHODS AND RESULTS: An F2 population was created using an intraspecific cross involving a Central American line RJCA9 and an Asiatic species RJCS-9 to develop a dense genetic map and for Quantitative trait loci (QTL) identification. The genotyping-by-sequencing (GBS) approach was used to genotype the mapping population of 136 F2 individuals along with the two parental lines for classification of the genotypes based on single nucleotide polymorphism (SNPs). NextSeq 2500 sequencing technology provided a total of 517.23 million clean reads, with an average of ~ 3.8 million reads per sample. We analysed 411 SNP markers and developed 11 linkage groups. The total length of the genetic map was 4092.3 cM with an average marker interval of 10.04 cM. We have identified a total of 83 QTLs for various yield and oil content governing traits. The percentage of phenotypic variation (PV) was found to be in the range of 8.81 to 65.31%, and a QTL showed the maximum PV of 65.3% for a total seed number on the 6th linkage group (LG). CONCLUSIONS: The QTLs detected in this study for various phenotypic traits will lay down the path for marker-assisted breeding in the future and cloning of genes that are responsible for phenotypic variation.

Genome-Wide Computational Analysis and Validation of Potential Long Noncoding RNA-Mediated DNA-DNA-RNA Triplexes in the Human Genome.

Long noncoding RNAs are well studied for their regulatory actions through interaction with DNA regulating biological roles of DNA, RNA, or protein. However, direct binding of lncRNA with DNA is rarely demonstrated in experiments. The present protocol explains genome wide computational strategies to choose lncRNAs that can bind directly to the chromatin by forming highly stable DNA-DNA-RNA triplexes. The chapter also focuses on biophysical methods that can be used to validate the computationally derived lncRNA-gene targets in vitro.

Correction: MitoLSDB: A Comprehensive Resource to Study Genotype to Phenotype Correlations in Human Mitochondrial DNA Variations.

[This corrects the article DOI: 10.1371/journal.pone.0060066.].

Development of genome wide transposable elements based repeat junction markers in Jatropha (Jatropha curcas L.).

Jatropha curcas is a potential biodiesel crop and a highly adaptable species to various agro-climatic conditions. In this study, we have utilized transposable elements' (TE) repeat junctions (RJs) which are an important constituent of the genome, used to form a genome-wide molecular marker platform owing to its use in genomic studies of plants. We screened our previously generated Jatropha hybrid genome assembly of size 265 Mbp using RJPrimers pipeline software and identified a total of 1274 TE junctions. For the predicted RJs, we designed 2868 polymerase chain reaction (PCR) based RJ markers (RJMs) flanking the junction regions. In addition to marker design, the identified RJs were utilized to detect 225,517 TEs across the genome. The different types of transposable repeat elements mainly were scattered into Retro, LTR, Copia and Gypsy categories. The efficacy of the designed markers was tested by utilizing a subset of RJMs selected randomly. We have validated 96 randomly selected RJ primers in a group of 32 J. curcas genotypes and more than 90% of the markers effectively intensified as amplicons. Of these, 10 primers were shown to be polymorphic in estimating genetic diversity among the 32 Jatropha lines. UPGMA cluster analysis revealed the formation of two clusters such as A and B exhibiting 85.5% and 87% similarity coefficient respectively. The various RJMs identified in this study could be utilized as a significant asset in Jatropha functional genomics including genome determination, mapping and marker-assisted selection.

Exploitation of Hi-C sequencing for improvement of genome assembly and in-vitro validation of differentially expressing genes in Jatropha curcas L.

Jatropha curcas is one of the major sources of renewable energy due to potential use of its oil as a biofuel. The genome of this crop is constituted by the high content of repetitive elements. We employed the Hi-C proximity ligation technique to re-scaffold our existing hybrid genome assembly of an elite genotype (RJC1) developed using Illumina and Pacbio technologies. We assembled 99.81% of non-truncated reads to achieve 266.80 Mbp of the genome with an N50 value of 1.58 Mb. Furthermore, we compared the efficiency of Hi-C-augmented genome assembly with the hybrid genome assembly and observed a ~ 50% reduction in scaffolds and a tenfold increase in the N50 value. The gene ontology analysis revealed the identification of terms for molecular function (45.52%), cellular component (33.47%), and biological function (20.99%). Comparative genomic analysis of 13-plant species showed the conservation of 414 lipid metabolizing genes identified in the KEGG pathway analysis. Differential gene expression (DGE) studies were conducted in the healthy and Jatropha mosaic virus-infected leaves via RNA-seq analysis and observed gene expression changes for 2185 genes. Out of these, we observed 546 genes having more than two-fold change of transcript level and among these 259 genes were down-regulated and 287 genes were up-regulated. To validate RNA-seq data, two DEGs were selected for gene expression analysis using qRT-PCR and the data was in correlation with in silico results. RNA-seq analysis further shows the identification of some of the candidate genes and may be useful to develop JMV resistant plants after functional validation. This Hi-C genome assembly provides a detailed accurate reference genome which could be utilized to improve Jatropha and other economically important Euphorbiaceae family members.

De Novo Sequencing and Hybrid Assembly of the Biofuel Crop Jatropha curcas L.: Identification of Quantitative Trait Loci for Geminivirus Resistance.

Jatropha curcas is an important perennial, drought tolerant plant that has been identified as a potential biodiesel crop. We report here the hybrid de novo genome assembly of J. curcas generated using Illumina and PacBio sequencing technologies, and identification of quantitative loci for Jatropha Mosaic Virus (JMV) resistance. In this study, we generated scaffolds of 265.7 Mbp in length, which correspond to 84.8% of the gene space, using Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis. Additionally, 96.4% of predicted protein-coding genes were captured in RNA sequencing data, which reconfirms the accuracy of the assembled genome. The genome was utilized to identify 12,103 dinucleotide simple sequence repeat (SSR) markers, which were exploited in genetic diversity analysis to identify genetically distinct lines. A total of 207 polymorphic SSR markers were employed to construct a genetic linkage map for JMV resistance, using an interspecific F2 mapping population involving susceptible J. curcas and resistant Jatropha integerrima as parents. Quantitative trait locus (QTL) analysis led to the identification of three minor QTLs for JMV resistance, and the same has been validated in an alternate F2 mapping population. These validated QTLs were utilized in marker-assisted breeding for JMV resistance. Comparative genomics of oil-producing genes across selected oil producing species revealed 27 conserved genes and 2986 orthologous protein clusters in Jatropha. This reference genome assembly gives an insight into the understanding of the complex genetic structure of Jatropha, and serves as source for the development of agronomically improved virus-resistant and oil-producing lines.

Distinct and Modular Organization of Protein Interacting Sites in Long Non-coding RNAs.

Background: Long non-coding RNAs (lncRNAs), are being reported to be extensively involved in diverse regulatory roles and have exhibited numerous disease associations. LncRNAs modulate their function through interaction with other biomolecules in the cell including DNA, RNA, and proteins. The availability of genome-scale experimental datasets of RNA binding proteins (RBP) motivated us to understand the role of lncRNAs in terms of its interactions with these proteins. In the current report, we demonstrate a comprehensive study of interactions between RBP and lncRNAs at a transcriptome scale through extensive analysis of the crosslinking and immunoprecipitation (CLIP) experimental datasets available for 70 RNA binding proteins. Results: Our analysis suggests that density of interaction sites for these proteins was significantly higher for specific sub-classes of lncRNAs when compared to protein-coding transcripts. We also observe a positional preference of these RBPs across lncRNA and protein coding transcripts in addition to a significant co-occurrence of RBPs having similar functions, suggesting a modular organization of these elements across lncRNAs. Conclusion: The significant enrichment of RBP sites across some lncRNA classes is suggestive that these interactions might be important in understanding the functional role of lncRNA. We observed a significant enrichment of RBPs which are involved in functional roles such as silencing, splicing, mRNA processing, and transport, indicating the potential participation of lncRNAs in such processes.

Genome-wide computational analysis of potential long noncoding RNA mediated DNA:DNA:RNA triplexes in the human genome.

BACKGROUND: Only a handful of long noncoding RNAs have been functionally characterized. They are known to modulate regulation through interacting with other biomolecules in the cell: DNA, RNA and protein. Though there have been detailed investigations on lncRNA-miRNA and lncRNA-protein interactions, the interaction of lncRNAs with DNA have not been studied extensively. In the present study, we explore whether lncRNAs could modulate genomic regulation by interacting with DNA through the formation of highly stable DNA:DNA:RNA triplexes. METHODS: We computationally screened 23,898 lncRNA transcripts as annotated by GENCODE, across the human genome for potential triplex forming sequence stretches (PTS). The PTS frequencies were compared across 5'UTR, CDS, 3'UTR, introns, promoter and 1000 bases downstream of the transcription termination sites. These regions were annotated by mapping to experimental regulatory regions, classes of repeat regions and transcription factors. We validated few putative triplex mediated interactions where lncRNA-gene pair interaction is via pyrimidine triplex motif using biophysical methods. RESULTS: We identified 20,04,034 PTS sites to be enriched in promoter and intronic regions across human genome. Additional analysis of the association of PTS with core promoter elements revealed a systematic paucity of PTS in all regulatory regions, except TF binding sites. A total of 25 transcription factors were found to be associated with PTS. Using an interaction network, we showed that a subset of the triplex forming lncRNAs, have a positive association with gene promoters. We also demonstrated an in vitro interaction of one lncRNA candidate with its predicted gene target promoter regions. CONCLUSIONS: Our analysis shows that PTS are enriched in gene promoter and largely associated with simple repeats. The current study suggests a major role of a subset of lncRNAs in mediating chromatin organization modulation through CTCF and NSRF proteins.

Navigating the dynamic landscape of long noncoding RNA and protein-coding gene annotations in GENCODE.

BACKGROUND: Our understanding of the transcriptional potential of the genome and its functional consequences has undergone a significant change in the last decade. This has been largely contributed by the improvements in technology which could annotate and in many cases functionally characterize a number of novel gene loci in the human genome. Keeping pace with advancements in this dynamic environment and being able to systematically annotate a compendium of genes and transcripts is indeed a formidable task. Of the many databases which attempted to systematically annotate the genome, GENCODE has emerged as one of the largest and popular compendium for human genome annotations. RESULTS: The analysis of various versions of GENCODE revealed that there was a constant upgradation of transcripts for both protein-coding and long noncoding RNA (lncRNAs) leading to conflicting annotations. The GENCODE version 24 accounts for 4.18 % of the human genome to be transcribed which is an increase of 1.58 % from its first version. Out of 2,51,614 transcripts annotated across GENCODE versions, only 21.7 % had consistency. We also examined GENCODE consortia categorized transcripts into 70 biotypes out of which only 17 remained stable throughout. CONCLUSIONS: In this report, we try to review the impact on the dynamicity with respect to gene annotations, specifically (lncRNA) annotations in GENCODE over the years. Our analysis suggests a significant dynamism in gene annotations, reflective of the evolution and consensus in nomenclature of genes. While a progressive change in annotations and timely release of the updates make the resource reliable in the community, the dynamicity with each release poses unique challenges to its users. Taking cues from other experiments with bio-curation, we propose potential avenues and methods to mend the gap.

Screening currency notes for microbial pathogens and antibiotic resistance genes using a shotgun metagenomic approach.

Fomites are a well-known source of microbial infections and previous studies have provided insights into the sojourning microbiome of fomites from various sources. Paper currency notes are one of the most commonly exchanged objects and its potential to transmit pathogenic organisms has been well recognized. Approaches to identify the microbiome associated with paper currency notes have been largely limited to culture dependent approaches. Subsequent studies portrayed the use of 16S ribosomal RNA based approaches which provided insights into the taxonomical distribution of the microbiome. However, recent techniques including shotgun sequencing provides resolution at gene level and enable estimation of their copy numbers in the metagenome. We investigated the microbiome of Indian paper currency notes using a shotgun metagenome sequencing approach. Metagenomic DNA isolated from samples of frequently circulated denominations of Indian currency notes were sequenced using Illumina Hiseq sequencer. Analysis of the data revealed presence of species belonging to both eukaryotic and prokaryotic genera. The taxonomic distribution at kingdom level revealed contigs mapping to eukaryota (70%), bacteria (9%), viruses and archae (~1%). We identified 78 pathogens including Staphylococcus aureus, Corynebacterium glutamicum, Enterococcus faecalis, and 75 cellulose degrading organisms including Acidothermus cellulolyticus, Cellulomonas flavigena and Ruminococcus albus. Additionally, 78 antibiotic resistance genes were identified and 18 of these were found in all the samples. Furthermore, six out of 78 pathogens harbored at least one of the 18 common antibiotic resistance genes. To the best of our knowledge, this is the first report of shotgun metagenome sequence dataset of paper currency notes, which can be useful for future applications including as bio-surveillance of exchangeable fomites for infectious agents.

Computational approaches towards understanding human long non-coding RNA biology.

Long non-coding RNAs (lncRNAs) form the largest class of non-protein coding genes in the human genome. While a small subset of well-characterized lncRNAs has demonstrated their significant role in diverse biological functions like chromatin modifications, post-transcriptional regulation, imprinting etc., the functional significance of a vast majority of them still remains an enigma. Increasing evidence of the implications of lncRNAs in various diseases including cancer and major developmental processes has further enhanced the need to gain mechanistic insights into the lncRNA functions. Here, we present a comprehensive review of the various computational approaches and tools available for the identification and annotation of long non-coding RNAs. We also discuss a conceptual roadmap to systematically explore the functional properties of the lncRNAs using computational approaches.

The Zebrafish GenomeWiki: a crowdsourcing approach to connect the long tail for zebrafish gene annotation.

A large repertoire of gene-centric data has been generated in the field of zebrafish biology. Although the bulk of these data are available in the public domain, most of them are not readily accessible or available in nonstandard formats. One major challenge is to unify and integrate these widely scattered data sources. We tested the hypothesis that active community participation could be a viable option to address this challenge. We present here our approach to create standards for assimilation and sharing of information and a system of open standards for database intercommunication. We have attempted to address this challenge by creating a community-centric solution for zebrafish gene annotation. The Zebrafish GenomeWiki is a 'wiki'-based resource, which aims to provide an altruistic shared environment for collective annotation of the zebrafish genes. The Zebrafish GenomeWiki has features that enable users to comment, annotate, edit and rate this gene-centric information. The credits for contributions can be tracked through a transparent microattribution system. In contrast to other wikis, the Zebrafish GenomeWiki is a 'structured wiki' or rather a 'semantic wiki'. The Zebrafish GenomeWiki implements a semantically linked data structure, which in the future would be amenable to semantic search. Database URL: http://genome.igib.res.in/twiki.

Distinct patterns of genetic variations in potential functional elements in long noncoding RNAs.

Non-protein-coding RNAs have increasingly been shown to be an important class of regulatory RNAs having significant roles in regulation of gene expression. The long noncoding RNA (lncRNA) gene family presently constitutes a large number of noncoding RNA (ncRNA) loci almost equaling the number of protein-coding genes. Nevertheless, the biological roles and mechanisms of the majority of lncRNAs are poorly understood, with exceptions of a very few well-studied candidates. The availability of genome-scale variation datasets, and increasing number of variant loci from genome-wide association studies falling in lncRNA loci have motivated us to understand the patterns of genomic variations in lncRNA loci, their potential functional correlates, and selection in populations. In the present study, we have performed a comprehensive analysis of genomic variations in lncRNA loci. We analyzed for patterns and distributions of genomic variations with respect to potential functional domains in lncRNAs. The analysis reveals a distinct distribution of variations in subclasses of long ncRNAs and in potential functional domains of lncRNAs. We further examined signals of selections and allele frequencies of these prioritized set of lncRNAs. To the best of our knowledge, this is the first and comprehensive large-scale analysis of genetic variations in long ncRNAs.

lncRNome: a comprehensive knowledgebase of human long noncoding RNAs.

The advent of high-throughput genome scale technologies has enabled us to unravel a large amount of the previously unknown transcriptionally active regions of the genome. Recent genome-wide studies have provided annotations of a large repertoire of various classes of noncoding transcripts. Long noncoding RNAs (lncRNAs) form a major proportion of these novel annotated noncoding transcripts, and presently known to be involved in a number of functionally distinct biological processes. Over 18,000 transcripts are presently annotated as lncRNA, and encompass previously annotated classes of noncoding transcripts including large intergenic noncoding RNA, antisense RNA and processed pseudogenes. There is a significant gap in the resources providing a stable annotation, cross-referencing and biologically relevant information. lncRNome has been envisioned with the aim of filling this gap by integrating annotations on a wide variety of biologically significant information into a comprehensive knowledgebase. To the best of our knowledge, lncRNome is one of the largest and most comprehensive resources for lncRNAs. Database URL: http://genome.igib.res.in/lncRNome.

MitoLSDB: a comprehensive resource to study genotype to phenotype correlations in human mitochondrial DNA variations.

Human mitochondrial DNA (mtDNA) encodes a set of 37 genes which are essential structural and functional components of the electron transport chain. Variations in these genes have been implicated in a broad spectrum of diseases and are extensively reported in literature and various databases. In this study, we describe MitoLSDB, an integrated platform to catalogue disease association studies on mtDNA (http://mitolsdb.igib.res.in). The main goal of MitoLSDB is to provide a central platform for direct submissions of novel variants that can be curated by the Mitochondrial Research Community. MitoLSDB provides access to standardized and annotated data from literature and databases encompassing information from 5231 individuals, 675 populations and 27 phenotypes. This platform is developed using the Leiden Open (source) Variation Database (LOVD) software. MitoLSDB houses information on all 37 genes in each population amounting to 132397 variants, 5147 unique variants. For each variant its genomic location as per the Revised Cambridge Reference Sequence, codon and amino acid change for variations in protein-coding regions, frequency, disease/phenotype, population, reference and remarks are also listed. MitoLSDB curators have also reported errors documented in literature which includes 94 phantom mutations, 10 NUMTs, six documentation errors and one artefactual recombination. MitoLSDB is the largest repository of mtDNA variants systematically standardized and presented using the LOVD platform. We believe that this is a good starting resource to curate mtDNA variants and will facilitate direct submissions enhancing data coverage, annotation in context of pathogenesis and quality control by ensuring non-redundancy in reporting novel disease associated variants.

Systematic transcriptome wide analysis of lncRNA-miRNA interactions.

BACKGROUND: Long noncoding RNAs (lncRNAs) are a recently discovered class of non-protein coding RNAs, which have now increasingly been shown to be involved in a wide variety of biological processes as regulatory molecules. The functional role of many of the members of this class has been an enigma, except a few of them like Malat and HOTAIR. Little is known regarding the regulatory interactions between noncoding RNA classes. Recent reports have suggested that lncRNAs could potentially interact with other classes of non-coding RNAs including microRNAs (miRNAs) and modulate their regulatory role through interactions. We hypothesized that lncRNAs could participate as a layer of regulatory interactions with miRNAs. The availability of genome-scale datasets for Argonaute targets across human transcriptome has prompted us to reconstruct a genome-scale network of interactions between miRNAs and lncRNAs. RESULTS: We used well characterized experimental Photoactivatable-Ribonucleoside-Enhanced Crosslinking and Immunoprecipitation (PAR-CLIP) datasets and the recent genome-wide annotations for lncRNAs in public domain to construct a comprehensive transcriptome-wide map of miRNA regulatory elements. Comparative analysis revealed that in addition to targeting protein-coding transcripts, miRNAs could also potentially target lncRNAs, thus participating in a novel layer of regulatory interactions between noncoding RNA classes. Furthermore, we have modeled one example of miRNA-lncRNA interaction using a zebrafish model. We have also found that the miRNA regulatory elements have a positional preference, clustering towards the mid regions and 3' ends of the long noncoding transcripts. We also further reconstruct a genome-wide map of miRNA interactions with lncRNAs as well as messenger RNAs. CONCLUSIONS: This analysis suggests widespread regulatory interactions between noncoding RNAs classes and suggests a novel functional role for lncRNAs. We also present the first transcriptome scale study on miRNA-lncRNA interactions and the first report of a genome-scale reconstruction of a noncoding RNA regulatory interactome involving lncRNAs.

Dynamic expression of long non-coding RNAs (lncRNAs) in adult zebrafish.

Long non-coding RNAs (lncRNA) represent an assorted class of transcripts having little or no protein coding capacity and have recently gained importance for their function as regulators of gene expression. Molecular studies on lncRNA have uncovered multifaceted interactions with protein coding genes. It has been suggested that lncRNAs are an additional layer of regulatory switches involved in gene regulation during development and disease. LncRNAs expressing in specific tissues or cell types during adult stages can have potential roles in form, function, maintenance and repair of tissues and organs. We used RNA sequencing followed by computational analysis to identify tissue restricted lncRNA transcript signatures from five different tissues of adult zebrafish. The present study reports 442 predicted lncRNA transcripts from adult zebrafish tissues out of which 419 were novel lncRNA transcripts. Of these, 77 lncRNAs show predominant tissue restricted expression across the five major tissues investigated. Adult zebrafish brain expressed the largest number of tissue restricted lncRNA transcripts followed by cardiovascular tissue. We also validated the tissue restricted expression of a subset of lncRNAs using independent methods. Our data constitute a useful genomic resource towards understanding the expression of lncRNAs in various tissues in adult zebrafish. Our study is thus a starting point and opens a way towards discovering new molecular interactions of gene expression within the specific adult tissues in the context of maintenance of organ form and function.

Integrative transcriptome analysis suggest processing of a subset of long non-coding RNAs to small RNAs.

BACKGROUND: The availability of sequencing technology has enabled understanding of transcriptomes through genome-wide approaches including RNA-sequencing. Contrary to the previous assumption that large tracts of the eukaryotic genomes are not transcriptionally active, recent evidence from transcriptome sequencing approaches have revealed pervasive transcription in many genomes of higher eukaryotes. Many of these loci encode transcripts that have no obvious protein-coding potential and are designated as non-coding RNA (ncRNA). Non-coding RNAs are classified empirically as small and long non-coding RNAs based on the size of the functional RNAs. Each of these classes is further classified into functional subclasses. Although microRNAs (miRNA), one of the major subclass of ncRNAs, have been extensively studied for their roles in regulation of gene expression and involvement in a large number of patho-physiological processes, the functions of a large proportion of long non-coding RNAs (lncRNA) still remains elusive. We hypothesized that some lncRNAs could potentially be processed to small RNA and thus could have a dual regulatory output. RESULTS: Integration of large-scale independent experimental datasets in public domain revealed that certain well studied lncRNAs harbor small RNA clusters. Expression analysis of the small RNA clusters in different tissue and cell types reveal that they are differentially regulated suggesting a regulated biogenesis mechanism. CONCLUSIONS: Our analysis suggests existence of a potentially novel pathway for lncRNA processing into small RNAs. Expression analysis, further suggests that this pathway is regulated. We argue that this evidence supports our hypothesis, though limitations of the datasets and analysis cannot completely rule out alternate possibilities. Further in-depth experimental verification of the observation could potentially reveal a novel pathway for biogenesis.

Conceptual approaches for lncRNA drug discovery and future strategies.

INTRODUCTION: Long non-coding RNAs (lncRNAs) are a recently discovered class of non-coding functional RNA which has attracted immense research interest. The growing corpus of literature in the field provides ample evidence to suggest the important role of lncRNAs as regulators in a wide spectrum of biological processes. Recent evidence also suggests the role of lncRNAs in the pathophysiology of disease processes. AREAS COVERED: The authors discuss a conceptual framework for understanding lncRNA-mediated regulation as a function of its interaction with other biomolecules in the cell. They summarize the mechanisms of the known functions of lncRNAs in light of this conceptual framework, and suggest how this insight could help in discovering novel targets for drug discovery. They also argue how certain emerging technologies could be of immense utility, both in discovering potential therapeutic targets as well as in further therapeutic development. EXPERT OPINION: The authors propose how the field could immensely benefit from methodologies and technologies from six emerging fields in molecular and computational biology. They also suggest a futuristic area of lncRNAs design as a potential offshoot of synthetic biology, which would be an attractive field, both for discovery of targets as well as a therapeutic strategy.

FishMap Zv8 update--a genomic regulatory map of zebrafish.

The advancements in genomics technologies and the amenability to large-scale computational analysis have contributed immensely to the understanding of the zebrafish genome, its organization, and its functional correlates. Translating genomics information into biological meaning would require integration and amenability of data and tools. FishMap is a community resource for genomic datasets on zebrafish created with a vision to provide relevant and readily available information to zebrafish researchers. The present update of FishMap has kept up with the availability of the latest zebrafish genome assembly (Zv8). In this update, particular emphasis has been given to noncoding RNAs and noncoding RNA-mediated regulation in addition to genomic regulatory motifs, which are emerging areas of vertebrate biology. FishMap Zv8 update also features a sequence mapping and analysis server. Consistent with its commitment to make the information freely available to the community, FishMap features options to share data between compatible resources in addition to making it amenable to programmatic access. FishMap Zv8 update is available at http://fishmap2.igib.res.in.