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The salinity stress tolerance in plants has been studied enormously, reflecting its agronomic relevance. Despite the extensive research, limited success has been achieved in relation to the plant tolerance mechanism. The beneficial interaction between Piriformospora indica and rice could essentially improve the performance of the plant during salt stress. In this study, the transcriptomic data between P. indica treated and untreated rice roots were compared under control and salt stress conditions. Overall, 661 salt-responsive differentially expressed genes (DEGs) were detected with 161 up- and 500 down-regulated genes in all comparison groups. Gene ontology analyses indicated the DEGs were mainly enriched in "auxin-activated signaling pathway", "water channel activity", "integral component of plasma membrane", "stress responses", and "metabolic processes". Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the DEGs were primarily related to "Zeatin biosynthesis", "Fatty acid elongation", "Carotenoid biosynthesis", and "Biosynthesis of secondary metabolites". Particularly, genes related to cell wall modifying enzymes (e.g. invertase/pectin methylesterase inhibitor protein and arabinogalactans), phytohormones (e.g. Auxin-responsive Aux/IAA gene family, ent-kaurene synthase, and 12-oxophytodienoate reductase) and receptor-like kinases (e.g. AGC kinase and receptor protein kinase) were induced in P. indica colonized rice under salt stress condition. The differential expression of these genes implies that the coordination between hormonal crosstalk, signaling, and cell wall dynamics contributes to the higher growth and tolerance in P. indica-inoculated rice. Our results offer a valuable resource for future functional studies on salt-responsive genes that should improve the resilience and adaptation of rice against salt stress.

Soybean (Glycine max [L.] Merr.) is a major crop in animal feed and human nutrition, mainly for its rich protein and oil contents. The remarkable rise in soybean transcriptome studies over the past 5 years generated an enormous amount of RNA-seq data, encompassing various tissues, developmental conditions and genotypes. In this study, we have collected data from 1298 publicly available soybean transcriptome samples, processed the raw sequencing reads and mapped them to the soybean reference genome in a systematic fashion. We found that 94% of the annotated genes (52 737/56 044) had detectable expression in at least one sample. Unsupervised clustering revealed three major groups, comprising samples from aerial, underground and seed/seed-related parts. We found 452 genes with uniform and constant expression levels, supporting their roles as housekeeping genes. On the other hand, 1349 genes showed heavily biased expression patterns towards particular tissues. A transcript-level analysis revealed that 95% (70 963 of 74 490) of the assembled transcripts have intron chains exactly matching those from known transcripts, whereas 3256 assembled transcripts represent potentially novel splicing isoforms. The dataset compiled here constitute a new resource for the community, which can be downloaded or accessed through a user-friendly web interface at http://venanciogroup.uenf.br/resources/. This comprehensive transcriptome atlas will likely accelerate research on soybean genetics and genomics.

Plants possess a unique transcriptional regulatory system in which two related MYB-related transcription factors (TFs) coordinate gene expression according to phosphate (Pi) and nitrogen (N) availability. The Phosphorus Starvation Response (PSR) type TFs are transcriptional activators integrating the cellular Pi sensing machinery and gene regulation majorly under Pi starvation. The Hypersensitivity To Low Pi-Elicited Primary Root Shortening (HRS) type TFs are transcriptional repressors integrating the Pi and N availability signals through different feedback loops. They are highly connected through multiple signaling loops to finetune the transcriptional responses according to nutrient availability. Molecular functions of these TFs are fairly uncovered in model systems; however, how plants evolved this activator-repressor system is currently unknown. In this study, using sensitive evolutionary analysis, we identified a stepwise origin of the PSR-HRS regulatory system in plants. The PSR TFs were originated before the split of Prasinodermophyta and Chlorophyta. The HRS TFs were originated later in the Streptrophycean algae. We also identified the asymmetric expansion of this TF repertoire in land plants majorly shaped by genome duplication and triplication events. The phylogenetic reconstruction coupled with motif analysis revealed that the origin of the specific accessory motifs is a major contributing factor in the functional divergence which led to the evolution of different sub-families preceding the angiosperm radiation. The spatiotemporal gene expression analysis in different developmental stages and nutrient availability conditions in angiosperms identified a critical role of expression divergence in shaping the functions of these TF families which is essential for adaptive plasticity of plants.

Next-generation sequencing (NGS) technologies have emerged as a powerful tool in the field of molecular biology and clinical applications. With the magnitude and efficiency of sequencing that can now be accomplished, NGS technologies have revolutionized the field of genomics and clinical diagnosis. The competence of NGS technologies has provided unprecedented opportunities to researchers to address an increasingly diverse range of biologic problems. Consistent efforts have been made by researchers and healthcare providers to translate the potential of NGS into clinical applications. Disease diagnostics, pathogen detection, and genetic mutations are some of the growing clinical areas where NGS is widely used. However, there are major challenges in translational bioinformatics that include storage and interpretation of complex datasets that require high computational power and requirement of well-trained professionals. Moreover, a combined effort between data analysts, geneticists, and physicians is required for the best NGS clinical applications. This chapter highlights the main aspects of NGS in clinical applications, recent advancements, and the significance of insights gained for future directions.

The coronavirus disease of 2019 (COVID-19), outbreak has hit millions of people and claiming thousands of lives worldwide. In times of unforeseen adversity like COVID-19, big data and advanced technologies are one of the few effective means to combat fast-disseminating flu for which vaccines are yet unknown. Today, many countries are employing big data, machine learning, and other digital tools to track and control this pandemic. In addition, the big data analytics propelled comparative genomic studies of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) strains have opened the door to information on mutations, virulence, evolutionary selection, and more. This has enabled the pharmaceutical and healthcare industries to improve diagnostics, aid drug discovery, and develop personalized medicine strategies. The recurrent mutations and genetic diversity identified in SARS-CoV-2 strains provide the basis to develop a cocktail of vaccines and also facilitate to develop region-specific diagnostic tools, thereby decreasing the chances of failures in testing in the fields. This chapter highlights the chief aspects of big data in current COVID-19 outbreak to figure out the best responses to fight against SARS-CoV-2 and future pandemics. Many software and applications have been developed to track and predict the infection. Similarly, mobile apps are launched for COVID-19 preliminary diagnosis and advanced diagnosis is achieved by medical image processing assisted by AI technologies. Therefore, the big data analytics has accelerated the processes of tracking, prediction, diagnosis and prognosis that have facilitated the health workers, scientists, epidemiologists, and policy makers to make more informed decisions in fighting SARS-CoV-2.

Given their remarkable beneficial effects on plant growth, several Azospirillum isolates currently integrate the formulations of various commercial inoculants. Our research group isolated a new strain, Azospirillum sp. UENF-412522, from passion fruit rhizoplane. This isolate uses carbon sources that are partially distinct from closely-related Azospirillum isolates. Scanning electron microscopy analysis and population counts demonstrate the ability of Azospirillum sp. UENF-412522 to colonize the surface of passion fruit roots. In vitro assays demonstrate the ability of Azospirillum sp. UENF-412522 to fix atmospheric nitrogen, to solubilize phosphate and to produce indole-acetic acid. Passion fruit plantlets inoculated with Azospirillum sp. UENF-41255 showed increased shoot and root fresh matter, as well as root dry matter, further highlighting its biotechnological potential for agriculture. We sequenced the genome of Azospirillum sp. UENF-412522 to investigate the genetic basis of its plant-growth promotion properties. We identified the key nif genes for nitrogen fixation, the complete PQQ operon for phosphate solubilization, the acdS gene that alleviates ethylene effects on plant growth, and the napCAB operon, which produces nitrite under anoxic conditions. We also found several genes conferring resistance to common soil antibiotics, which are critical for Azospirillum sp. UENF-412522 survival in the rhizosphere. Finally, we also assessed the Azospirillum pangenome and highlighted key genes involved in plant growth promotion. A phylogenetic reconstruction of the genus was also conducted. Our results support Azospirillum sp. UENF-412522 as a good candidate for bioinoculant formulations focused on plant growth promotion in sustainable systems.

Soybean (Glycine max [L.] Merr.) is a major crop in animal feed and human nutrition, mainly for its rich protein and oil contents. The remarkable rise in soybean transcriptome studies over the past five years generated an enormous amount of RNA-seq data, encompassing various tissues, developmental conditions, and genotypes. In this study, we have collected data from 1,298 publicly available soybean transcriptome samples, processed the raw sequencing reads, and mapped them to the soybean reference genome in a systematic fashion. We found that 94% of the annotated genes (52,737/56,044) had detectable expression in at least one sample. Unsupervised clustering revealed three major groups, comprising samples from aerial, underground, and seed/seed-related parts. We found 452 genes with uniform and constant expression levels, supporting their roles as housekeeping genes. On the other hand, 1,349 genes showed heavily biased expression patterns towards particular tissues. A transcript-level analysis revealed that 95% (70,963/74,490) of the known transcripts overlap with those reported here, whereas 3,256 assembled transcripts represent potentially novel splicing isoforms. The dataset compiled here constitute a new resource for the community, which can be downloaded or accessed through a user-friendly web interface at http://venanciogroup.uenf.br/resources/. This comprehensive transcriptome atlas will likely accelerate research on soybean genetics and genomics.

Gibberellins (GA) are key positive regulators of seed germination. Although the GA effects on seed germination have been studied in a number of species, little is known about the transcriptional reprogramming modulated by GA during this phase in species other than Arabidopsis thaliana. Here we report the transcriptome analysis of soybean embryonic axes during germination in the presence of paclobutrazol (PBZ), a GA biosynthesis inhibitor. We found a number of differentially expressed cell wall metabolism genes, supporting their roles in cell expansion during germination. Several genes involved in the biosynthesis and signaling of other phytohormones were also modulated, indicating an intensive hormonal crosstalk at the embryonic axis. We have also found 26 photosynthesis genes that are up-regulated by PBZ at 24 hours after imbibition (HAI) and down-regulated at 36 HAI, which led us to suggest that this is part of a strategy to implement an autotrophic growth program in the absence of GA-driven mobilization of reserves. Finally, 30 transcription factors (mostly from the MYB, bHLH, and bZIP families) were down-regulated by PBZ and are likely downstream GA targets that will drive transcriptional changes during germination.

History of metabolism originates with yeast making bread. In fact, study based on "Yeast" was so crucial in the development of the field of biochemistry that the word "enzyme" is derived from the Greek word meaning leavened (yeast). Yeast has always been a point of interest as a eukaryotic model system to demonstrate the metabolites and their function. In recent times their metabolites are widely studied to predict their role in various pathways. Many traditional and analytical techniques have been employed, but its study through metabolomics is of recent interest in research. The present review focuses on details about yeast metabolomics based on preliminary research on various analytical techniques along with computational approaches. The review also aimed to highlight machine learning and various inceptions of yeast metabolomics.

Gibberellins (GA) are key positive regulators of seed germination. Although the GA effects on seed germination have been studied in a number of species, little is known about the transcriptional reprogramming modulated by GA during this phase in species other than Arabidopsis thaliana. Here we report the transcriptome analysis of soybean embryonic axes during germination in the presence of paclobutrazol (PBZ), a GA biosynthesis inhibitor. We found a number of differentially expressed cell wall metabolism genes, supporting their roles in cell expansion during germination. Several genes involved in the biosynthesis and signaling of other phytohormones were also modulated, indicating an intensive hormonal crosstalk at the embryonic axis. We have also found 26 photosynthesis genes that are up-regulated by PBZ at 24 hours of imbibition (HAI) and down-regulated at 36 HAI, which led us to suggest that this is part of a strategy to implement an autotrophic growth program in the absence of GA-driven mobilization of reserves. Finally, 30 transcription factors (mostly from the MYB, bHLH and bZIP families) that are down-regulated by PBZ and are likely downstream GA targets that will drive transcriptional changes during germination.

Here we uncover the major evolutionary events shaping the evolution of the GID1 family of gibberellin receptors in land plants at the sequence, structure and gene expression levels. Gibberellic acid (gibberellin, GA) controls key developmental processes in the life cycle of land plants. By interacting with the GIBBERELLIN INSENSITIVE DWARF1 (GID1) receptor, GA regulates the expression of a wide range of genes through different pathways. Here we report the systematic identification and classification of GID1s in 54 plants genomes, encompassing from bryophytes and lycophytes, to several monocots and eudicots. We investigated the evolutionary relationship of GID1s using a comparative genomics framework and found strong support for a previously proposed phylogenetic classification of this family in land plants. We identified lineage-specific expansions of particular subfamilies (i.e. GID1ac and GID1b) in different eudicot lineages (e.g. GID1b in legumes). Further, we found both, shared and divergent structural features between GID1ac and GID1b subgroups in eudicots that provide mechanistic insights on their functions. Gene expression data from several species show that at least one GID1 gene is expressed in every sampled tissue, with a strong bias of GID1b expression towards underground tissues and dry legume seeds (which typically have low GA levels). Taken together, our results indicate that GID1ac retained canonical GA signaling roles, whereas GID1b specialized in conditions of low GA concentrations. We propose that this functional specialization occurred initially at the gene expression level and was later fine-tuned by mutations that conferred greater GA affinity to GID1b, including a Phe residue in the GA-binding pocket. Finally, we discuss the importance of our findings to understand the diversification of GA perception mechanisms in land plants.

Gibberellic acid (gibberellins, GA) controls key developmental processes in the life-cycle of land plants. By interacting with the GIBBERELLIN INSENSITIVE DWARF1 (GID1) receptor, GA regulates the expression of a wide range of genes through different pathways. Here we report the systematic identification and classification of GID1s in 52 plants genomes, encompassing from bryophytes and lycophytes, to several monocots and eudicots. We investigated the evolutionary relationship of GID1s using a comparative genomics framework and found strong support a previously proposed phylogenetic classification of this family in land plants. We identified lineage-specific expansions of particular subfamilies (i.e. GID1ac and GID1b) in different eudicot lineages (e.g. GID1b in legumes). Further, we found both, shared and divergent structural features between GID1ac and GID1b subgroups in eudicots, which provide mechanistic insights on their functions. Gene expression data from several species show that at least one GID1 gene is expressed in every sampled tissue, with a strong bias of GID1b expression towards underground tissues and dry legume seeds (typically with low GA levels). Taken together, our results support that GID1ac retained canonical GA signaling roles, whereas GID1b specialized in conditions of low GA concentrations. We propose that this functional specialization occurred initially at the gene expression level and was later fine-tuned by specific mutations that conferred greater GA affinity to GID1b, including a Phe residue in the GA-binding pocket. Finally, we discuss the importance of our findings to understand the diversification of GA perception mechanisms in land plants.

Transcription factors (TFs) are the key players in gene expression and their study is highly significant for shedding light on the molecular mechanisms and evolutionary history of organisms. During host-pathogen interaction, extensive reprogramming of gene expression facilitated by TFs is likely to occur in both host and pathogen. To date, the knowledge about TF repertoire in filamentous fungi is in infancy. The necrotrophic fungus Ascochyta rabiei, that causes destructive Ascochyta blight (AB) disease of chickpea (Cicer arietinum), demands more comprehensive study for better understanding of Ascochyta-legume pathosystem. In the present study, we performed the genome-wide identification and analysis of TFs in A. rabiei. Taking advantage of A. rabiei genome sequence, we used a bioinformatic approach to predict the TF repertoire of A. rabiei. For identification and classification of A. rabiei TFs, we designed a comprehensive pipeline using a combination of BLAST and InterProScan software. A total of 381 A. rabiei TFs were predicted and divided into 32 fungal specific families of TFs. The gene structure, domain organization and phylogenetic analysis of abundant families of A. rabiei TFs were also carried out. Comparative study of A. rabiei TFs with that of other necrotrophic, biotrophic, hemibiotrophic, symbiotic, and saprotrophic fungi was performed. It suggested presence of both conserved as well as unique features among them. Moreover, cis-acting elements on promoter sequences of earlier predicted A. rabiei secretome were also identified. With the help of published A. rabiei transcriptome data, the differential expression of TF and secretory protein coding genes was analyzed. Furthermore, comprehensive expression analysis of few selected A. rabiei TFs using quantitative real-time polymerase chain reaction revealed variety of expression patterns during host colonization. These genes were expressed in at least one of the time points tested post infection. Overall, this study illustrates the first genome-wide identification and analysis of TF repertoire of A. rabiei. This work would provide the basis for further studies to dissect role of TFs in the molecular mechanisms during A. rabiei-chickpea interactions.

Despite the great morphological diversity of insects, there is a regularity in their digestive functions, which is apparently related to their physiology. In the present work we report thede novomidgut transcriptomes of four non-model insects from four distinct orders:Spodoptera frugiperda(Lepidoptera),Musca domestica(Diptera),Tenebrio molitor(Coleoptera) andDysdercus peruvianus(Hemiptera). We employed a computational strategy to merge assemblies obtained with two different algorithms, which substantially increased the quality of the final transcriptomes. Unigenes were annotated and analyzed using the eggNOG database, which allowed us to assign some level of functional and evolutionary information to 79.7% to 93.1% of the transcriptomes. We found interesting transcriptional patterns, such as: i) the intense use of lysozymes in digestive functions ofM. domesticalarvae, which are streamlined and adapted to feed on bacteria; ii) the up-regulation of orthologous UDP-glycosyl transferase and cytochrome P450 genes in the whole midguts different species, supporting the presence of an ancient defense frontline to counter xenobiotics; iii) evidence supporting roles for juvenile hormone binding proteins in the midgut physiology, probably as a way to activate genes that help fight anti-nutritional substances (e.g. protease inhibitors). The results presented here shed light on the digestive and structural properties of the digestive systems of these distantly related species. Furthermore, the produced datasets will also be useful for scientists studying these insects.

We report here the genome sequence of Pandoraea sp. ISTKB, a betaproteobacterium isolated from rhizospheric soil in the backwaters of Alappuzha, Kerala, India. The strain is alkalotolerant and grows on medium containing lignin as a sole carbon source. Genes and pathways related to lignin degradation were complemented by genomic analysis.

The Serratia sp. strain ISTD04 has been identified as a carbon dioxide (CO 2 )-sequestering bacterium isolated from marble mining rocks in the Umra area, Rajasthan, India. This strain grows chemolithotrophically on media that contain sodium bicarbonate (NaHCO 3 ) as the sole carbon source. Here, we report the genome sequence of 5.07 Mb Serratia sp. ISTD04.

Constant evolutionary pressure acting on pathogens refines their molecular strategies to attain successful pathogenesis. Recent studies have shown that pathogenicity mechanisms of necrotrophic fungi are far more intricate than earlier evaluated. However, only a few studies have explored necrotrophic fungal pathogens. Ascochyta rabiei is a necrotrophic fungus that causes devastating blight disease of chickpea (Cicer arietinum). Here, we report a 34.6 megabase draft genome assembly of A. rabiei. The genome assembly covered more than 99% of the gene space and 4,259 simple sequence repeats were identified in the assembly. A total of 10,596 high confidence protein-coding genes were predicted which includes a large and diverse inventory of secretory proteins, transporters and primary and secondary metabolism enzymes reflecting the necrotrophic lifestyle of A. rabiei. A wide range of genes encoding carbohydrate-active enzymes capable for degradation of complex polysaccharides were also identified. Comprehensive analysis predicted a set of 758 secretory proteins including both classical and non-classical secreted proteins. Several of these predicted secretory proteins showed high cysteine content and numerous tandem repeats. Together, our analyses would broadly expand our knowledge and offer insights into the pathogenesis and necrotrophic lifestyle of fungal phytopathogens.

In this study, we systematically identify Old Yellow Enzymes (OYEs) from a diverse range of economically important fungi representing different ecology and lifestyle. Using active site residues and sequence alignments, we present a classification for these proteins into three distinct classes including a novel class (Class III) and assign names to sequences. Our in-depth phylogenetic analysis suggests a complex history of lineage-specific expansion and contraction for the OYE gene family in fungi. Comparative analyses reveal remarkable diversity in the number and classes of OYE among fungi. Quantitative real-time PCR (qRT-PCR) of Ascochyta rabiei OYEs indicates differential expression of OYE genes during oxidative stress and plant infection. This study shows relationship of OYE with fungal ecology and lifestyle, and provides a foundation for future functional analysis and characterization of OYE gene family.

Old Yellow Enzyme (OYE1) was the first flavin-dependent enzyme identified and characterized in detail by the entire range of physical techniques. Irrespective of this scrutiny, true physiological role of the enzyme remains a mystery. In a recent study, we systematically identified OYE proteins from various fungi and classified them into three classes viz. Class I, II and III. However, there is no information about the structural organization of Class III OYEs, eukaryotic Class II OYEs and Class I OYEs of filamentous fungi. Ascochyta rabiei, a filamentous phytopathogen which causes Ascochyta blight (AB) in chickpea possesses six OYEs (ArOYE1-6) belonging to the three OYE classes. Here we carried out comparative homology modeling of six ArOYEs representing all the three classes to get an in depth idea of structural and functional aspects of fungal OYEs. The predicted 3D structures of A. rabiei OYEs were refined and evaluated using various validation tools for their structural integrity. Analysis of FMN binding environment of Class III OYE revealed novel residues involved in interaction. The ligand para-hydroxybenzaldehyde (PHB) was docked into the active site of the enzymes and interacting residues were analyzed. We observed a unique active site organization of Class III OYE in comparison to Class I and II OYEs. Subsequently, analysis of stereopreference through structural features of ArOYEs was carried out, suggesting differences in R/S selectivity of these proteins. Therefore, our comparative modeling study provides insights into the FMN binding, active site organization and stereopreference of different classes of ArOYEs and indicates towards functional differences of these enzymes. This study provides the basis for future investigations towards the biochemical and functional characterization of these enigmatic enzymes.