Crowdsourced benchmarking of taxonomic metagenome profilers: lessons learned from the sbv IMPROVER Microbiomics challenge.

BACKGROUND: Selection of optimal computational strategies for analyzing metagenomics data is a decisive step in determining the microbial composition of a sample, and this procedure is complex because of the numerous tools currently available. The aim of this research was to summarize the results of crowdsourced sbv IMPROVER Microbiomics Challenge designed to evaluate the performance of off-the-shelf metagenomics software as well as to investigate the robustness of these results by the extended post-challenge analysis. In total 21 off-the-shelf taxonomic metagenome profiling pipelines were benchmarked for their capacity to identify the microbiome composition at various taxon levels across 104 shotgun metagenomics datasets of bacterial genomes (representative of various microbiome samples) from public databases. Performance was determined by comparing predicted taxonomy profiles with the gold standard. RESULTS: Most taxonomic profilers performed homogeneously well at the phylum level but generated intermediate and heterogeneous scores at the genus and species levels, respectively. kmer-based pipelines using Kraken with and without Bracken or using CLARK-S performed best overall, but they exhibited lower precision than the two marker-gene-based methods MetaPhlAn and mOTU. Filtering out the 1% least abundance species-which were not reliably predicted-helped increase the performance of most profilers by increasing precision but at the cost of recall. However, the use of adaptive filtering thresholds determined from the sample's Shannon index increased the performance of most kmer-based profilers while mitigating the tradeoff between precision and recall. CONCLUSIONS: kmer-based metagenomic pipelines using Kraken/Bracken or CLARK-S performed most robustly across a large variety of microbiome datasets. Removing non-reliably predicted low-abundance species by using diversity-dependent adaptive filtering thresholds further enhanced the performance of these tools. This work demonstrates the applicability of computational pipelines for accurately determining taxonomic profiles in clinical and environmental contexts and exemplifies the power of crowdsourcing for unbiased evaluation.

Transcriptome and Co-Expression Network Analyses Identify Key Genes Regulating Nitrogen Use Efficiency in Brassica juncea L.

Nitrate is the main source of inorganic nitrogen for plants, which also act as signaling molecule. Present study was aimed to understand nitrate regulatory mechanism in Brassica juncea cultivars, with contrasting nitrogen-use-efficiency (NUE) viz. Pusa Bold (PB, high-NUE) and Pusa Jai Kisan (PJK, low-NUE), employing RNA-seq approach. A total of 4031, 3874 and 3667 genes in PB and 2982, 2481 and 2843 genes in PJK were differentially expressed in response to early, low (0.25 mM KNO3), medium (2 mM KNO3) and high (4 mM KNO3) nitrate treatments, respectively, as compared to control (0 mM KNO3). Genes of N-uptake (NRT1.1, NRT1.8, and NRT2.1), assimilation (NR1, NR2, NiR, GS1.3, and Fd-GOGAT) and remobilization (GDH2, ASN2-3 and ALaT) were highly-upregulated in PB than in PJK in response to early nitrate treatments. We have also identified transcription factors and protein kinases that were rapidly induced in response to nitrate, suggesting their involvement in nitrate-mediated signaling. Co-expression network analysis revealed four nitrate specific modules in PB, enriched with GO terms like, "Phenylpropanoid pathway", "Nitrogen compound metabolic process" and "Carbohydrate metabolism". The network analysis also identified HUB transcription factors like mTERF, FHA, Orphan, bZip and FAR1, which may be the key regulators of nitrate-mediated response in B. juncea.

Comparative Transcriptome Analysis of Chinary, Assamica and Cambod tea (Camellia sinensis) Types during Development and Seasonal Variation using RNA-seq Technology.

Tea quality and yield is influenced by various factors including developmental tissue, seasonal variation and cultivar type. Here, the molecular basis of these factors was investigated in three tea cultivars namely, Him Sphurti (H), TV23 (T), and UPASI-9 (U) using RNA-seq. Seasonal variation in these cultivars was studied during active (A), mid-dormant (MD), dormant (D) and mid-active (MA) stages in two developmental tissues viz. young and old leaf. Development appears to affect gene expression more than the seasonal variation and cultivar types. Further, detailed transcript and metabolite profiling has identified genes such as F3'H, F3'5'H, FLS, DFR, LAR, ANR and ANS of catechin biosynthesis, while MXMT, SAMS, TCS and XDH of caffeine biosynthesis/catabolism as key regulators during development and seasonal variation among three different tea cultivars. In addition, expression analysis of genes related to phytohormones such as ABA, GA, ethylene and auxin has suggested their role in developmental tissues during seasonal variation in tea cultivars. Moreover, differential expression of genes involved in histone and DNA modification further suggests role of epigenetic mechanism in coordinating global gene expression during developmental and seasonal variation in tea. Our findings provide insights into global transcriptional reprogramming associated with development and seasonal variation in tea.

Genome-wide regulatory dynamics of G-quadruplexes in human malaria parasite Plasmodium falciparum.

The AT-rich genome of P. falciparum has uniquely localized G-rich stretches that have propensity to form G-quadruplexes. However, their global occurrence and potential biological roles in the parasite are poorly explored. Our genome-wide analysis revealed unique enrichment of quadruplexes in P. falciparum genome which was remarkably different from other Plasmodium species. A distinct predominance of quadruplexes was observed in nuclear and organellar genes that participate in antigenic variation, pathogenesis, DNA/RNA regulation, metabolic and protein quality control processes. Data also suggested association of quadruplexes with SNPs and DNA methylation. Furthermore, analysis of steady state mRNA (RNA-seq) and polysome-associated mRNA (Ribosome profiling) data revealed stage-specific differences in translational efficiency of quadruplex harboring genes. Taken together, our findings hint towards existence of regulatory dynamics associated with quadruplexes that may modulate translational efficiency of quadruplex harboring genes to provide survival advantage to the parasite against host immune response and antimalarial drug pressure.

Identifying wrong assemblies in de novo short read primary sequence assembly contigs.

With the advent of short-reads-based genome sequencing approaches, large number of organisms are being sequenced all over the world. Most of these assemblies are done using some de novo short read assemblers and other related approaches. However, the contigs produced this way are prone to wrong assembly. So far, there is a conspicuous dearth of reliable tools to identify mis-assembled contigs. Mis-assemblies could result from incorrectly deleted or wrongly arranged genomic sequences. In the present work various factors related to sequence, sequencing and assembling have been assessed for their role in causing mis-assembly by using different genome sequencing data. Finally, some mis-assembly detecting tools have been evaluated for their ability to detect the wrongly assembled primary contigs, suggesting a lot of scope for improvement in this area. The present work also proposes a simple unsupervised learning-based novel approach to identify mis-assemblies in the contigs which was found performing reasonably well when compared to the already existing tools to report mis-assembled contigs. It was observed that the proposed methodology may work as a complementary system to the existing tools to enhance their accuracy.

De novo transcriptome sequencing and analysis for Venturia inaequalis, the devastating apple scab pathogen.

Venturia inaequalis is the causal agent of apple scab, one of the most devastating diseases of apple. Due to several distinct features, it has emerged as a model fungal pathogen to study various aspects of hemibiotrophic plant pathogen interactions. The present study reports de novo assembling, annotation and characterization of the transcriptome of V. inaequalis. Venturia transcripts expressed during its growth on laboratory medium and that expressed during its biotrophic stage of infection on apple were sequenced using Illumina RNAseq technology. A total of 94,350,055 reads (50 bp read length) specific to Venturia were obtained after filtering. The reads were assembled into 62,061 contigs representing 24,571 unique genes. GO analysis suggested prevalence of genes associated with biological process categories like metabolism, transport and response to stimulus. Genes associated with molecular function like binding, catalytic activities and transferase activities were found in majority. EC and KEGG pathway analyses suggested prevalence of genes encoding kinases, proteases, glycoside hydrolases, cutinases, cytochrome P450 and transcription factors. The study has identified several putative pathogenicity determinants and candidate effectors in V. inaequalis. A large number of transcripts encoding membrane transporters were identified and comparative analysis revealed that the number of transporters encoded by Venturia is significantly more as compared to that encoded by several other important plant fungal pathogens. Phylogenomics analysis indicated that V. inaequalis is closely related to Pyrenophora tritici-repentis (the causal organism of tan spot of wheat). In conclusion, the findings from this study provide a better understanding of the biology of the apple scab pathogen and have identified candidate genes/functions required for its pathogenesis. This work lays the foundation for facilitating further research towards understanding this host-pathogen interaction.

De novo sequencing and characterization of Picrorhiza kurrooa transcriptome at two temperatures showed major transcriptome adjustments.

BACKGROUND: Picrorhiza kurrooa Royle ex Benth. is an endangered plant species of medicinal importance. The medicinal property is attributed to monoterpenoids picroside I and II, which are modulated by temperature. The transcriptome information of this species is limited with the availability of few hundreds of expressed sequence tags (ESTs) in the public databases. In order to gain insight into temperature mediated molecular changes, high throughput de novo transcriptome sequencing and analyses were carried out at 15 °C and 25 °C, the temperatures known to modulate picrosides content. RESULTS: Using paired-end (PE) Illumina sequencing technology, a total of 20,593,412 and 44,229,272 PE reads were obtained after quality filtering for 15 °C and 25 °C, respectively. Available (e.g., De-Bruijn/Eulerian graph) and in-house developed bioinformatics tools were used for assembly and annotation of transcriptome. A total of 74,336 assembled transcript sequences were obtained, with an average coverage of 76.6 and average length of 439.5. Guanine-cytosine (GC) content was observed to be 44.6%, while the transcriptome exhibited abundance of trinucleotide simple sequence repeat (SSR; 45.63%) markers.Large scale expression profiling through "read per exon kilobase per million (RPKM)", showed changes in several biological processes and metabolic pathways including cytochrome P450s (CYPs), UDP-glycosyltransferases (UGTs) and those associated with picrosides biosynthesis. RPKM data were validated by reverse transcriptase-polymerase chain reaction using a set of 19 genes, wherein 11 genes behaved in accordance with the two expression methods. CONCLUSIONS: Study generated transcriptome of P. kurrooa at two different temperatures. Large scale expression profiling through RPKM showed major transcriptome changes in response to temperature reflecting alterations in major biological processes and metabolic pathways, and provided insight of GC content and SSR markers. Analysis also identified putative CYPs and UGTs that could help in discovering the hitherto unknown genes associated with picrosides biosynthesis.