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Fulltext YersiniaBase: a genomic resource and analysis platform for comparative analysis of Yersinia

Tan SY, Dutta A, Jakubovics NS, Ang MY, Siow CC, Mutha NV, et al.

BMC Bioinformatics, 2015;16:9.
PMID: 25591325 DOI: 10.1186/s12859-014-0422-y

Yersinia is a Gram-negative bacteria that includes serious pathogens such as the Yersinia pestis, which causes plague, Yersinia pseudotuberculosis, Yersinia enterocolitica. The remaining species are generally considered non-pathogenic to humans, although there is evidence that at least some of these species can cause occasional infections using distinct mechanisms from the more pathogenic species. With the advances in sequencing technologies, many genomes of Yersinia have been sequenced. However, there is currently no specialized platform to hold the rapidly-growing Yersinia genomic data and to provide analysis tools particularly for comparative analyses, which are required to provide improved insights into their biology, evolution and pathogenicity.

Matched MeSH terms: Genomics/methods*
Utility of public knowledge bases for the interpretation of comprehensive tumor molecular profiling results

Lebedeva A, Timokhin G, Ignatova E, Kavun A, Veselovsky E, Sharova M, et al.

Clin Exp Med, 2023 Oct;23(6):2663-2674.
PMID: 36752890 DOI: 10.1007/s10238-023-01011-6

With the growing use of comprehensive tumor molecular profiling (CTMP), the therapeutic landscape of cancer is rapidly evolving. NGS produces large amounts of genomic data requiring complex analysis and subsequent interpretation. We sought to determine the utility of publicly available knowledge bases (KB) for the interpretation of the cancer mutational profile in clinical practice. Analysis was performed across patients who previously underwent CTMP. Independent interpretation of the CTMP was performed manually, and then, the recommendations were compared to ones present in KBs (OncoKB, CIViC, CGI, CGA, VICC, MolecularMatch). A total of 222 CTMP reports from 222 patients with 932 genomic alterations (GA) were identified. For 368 targetable GA identified in 171 (77%) of the patients, 1381 therapy recommendations were compiled. Except for CGA, therapy ESCAT LOE I, II, IIIA and IIIB therapy options were equally represented in the majority of KB. Personalized treatment options with ESCAT LOE I-II were provided for 35 patients (16%); MolecularMatch/CIViC allowed to collect ESCAT I-II treatment options for 34 of them (97%), OncoKB/CGI-for 33 of them (94%). Employing VICC and CGA 6 (17%) and 20 (57%) of patients were left without ESCAT I or II treatment options. For 88 patients with ESCAT level III-B therapy recommendations: only 2 (2%), 3 (3%), 4 (5%) and 6 (7%) of patients were left without options with CIViC, MolecularMatch, CGI and OncoKB, and with VICC-12 (14%). Highest overlap ratio was observed for IIIA (0.81) biomarkers, with the comparable results for LOE I-II. Meanwhile, overlap ratio for ESCAT LOE IV was 0.22. Public KBs provide substantial information on ESCAT-I/R1 biomarkers, but the information on ESCAT II-IV and resistance biomarkers is underrepresented. Manual curation should be considered the gold standard for the CTMP interpretation.

Matched MeSH terms: Genomics/methods
Transcriptogenomics identification and characterization of RNA editing sites in human primary monocytes using high-depth next generation sequencing data

Leong WM, Ripen AM, Mirsafian H, Mohamad SB, Merican AF

Genomics, 2019 07;111(4):899-905.
PMID: 29885984 DOI: 10.1016/j.ygeno.2018.05.019

High-depth next generation sequencing data provide valuable insights into the number and distribution of RNA editing events. Here, we report the RNA editing events at cellular level of human primary monocyte using high-depth whole genomic and transcriptomic sequencing data. We identified over a ten thousand putative RNA editing sites and 69% of the sites were A-to-I editing sites. The sites enriched in repetitive sequences and intronic regions. High-depth sequencing datasets revealed that 90% of the canonical sites were edited at lower frequencies (<0.7). Single and multiple human monocytes and brain tissues samples were analyzed through genome sequence independent approach. The later approach was observed to identify more editing sites. Monocytes was observed to contain more C-to-U editing sites compared to brain tissues. Our results establish comparable pipeline that can address current limitations as well as demonstrate the potential for highly sensitive detection of RNA editing events in single cell type.

Matched MeSH terms: Genomics/methods*
Fulltext Towards complete and error-free genome assemblies of all vertebrate species

Rhie A, McCarthy SA, Fedrigo O, Damas J, Formenti G, Koren S, et al.

Nature, 2021 Apr;592(7856):737-746.
PMID: 33911273 DOI: 10.1038/s41586-021-03451-0

High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are available for only a few non-microbial species1-4. To address this issue, the international Genome 10K (G10K) consortium5,6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling highly accurate and nearly complete reference genomes. Here we present lessons learned from generating assemblies for 16 species that represent six major vertebrate lineages. We confirm that long-read sequencing technologies are essential for maximizing genome quality, and that unresolved complex repeats and haplotype heterozygosity are major sources of assembly error when not handled correctly. Our assemblies correct substantial errors, add missing sequence in some of the best historical reference genomes, and reveal biological discoveries. These include the identification of many false gene duplications, increases in gene sizes, chromosome rearrangements that are specific to lineages, a repeated independent chromosome breakpoint in bat genomes, and a canonical GC-rich pattern in protein-coding genes and their regulatory regions. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an international effort to generate high-quality, complete reference genomes for all of the roughly 70,000 extant vertebrate species and to help to enable a new era of discovery across the life sciences.

Matched MeSH terms: Genomics/methods*
Fulltext The rubber tree genome shows expansion of gene family associated with rubber biosynthesis

Lau NS, Makita Y, Kawashima M, Taylor TD, Kondo S, Othman AS, et al.

Sci Rep, 2016 06 24;6:28594.
PMID: 27339202 DOI: 10.1038/srep28594

Hevea brasiliensis Muell. Arg, a member of the family Euphorbiaceae, is the sole natural resource exploited for commercial production of high-quality natural rubber. The properties of natural rubber latex are almost irreplaceable by synthetic counterparts for many industrial applications. A paucity of knowledge on the molecular mechanisms of rubber biosynthesis in high yield traits still persists. Here we report the comprehensive genome-wide analysis of the widely planted H. brasiliensis clone, RRIM 600. The genome was assembled based on ~155-fold combined coverage with Illumina and PacBio sequence data and has a total length of 1.55 Gb with 72.5% comprising repetitive DNA sequences. A total of 84,440 high-confidence protein-coding genes were predicted. Comparative genomic analysis revealed strong synteny between H. brasiliensis and other Euphorbiaceae genomes. Our data suggest that H. brasiliensis's capacity to produce high levels of latex can be attributed to the expansion of rubber biosynthesis-related genes in its genome and the high expression of these genes in latex. Using cap analysis gene expression data, we illustrate the tissue-specific transcription profiles of rubber biosynthesis-related genes, revealing alternative means of transcriptional regulation. Our study adds to the understanding of H. brasiliensis biology and provides valuable genomic resources for future agronomic-related improvement of the rubber tree.

Matched MeSH terms: Genomics/methods
Fulltext The molecular epidemiology of multiple zoonotic origins of SARS-CoV-2

Pekar JE, Magee A, Parker E, Moshiri N, Izhikevich K, Havens JL, et al.

Science, 2022 Aug 26;377(6609):960-966.
PMID: 35881005 DOI: 10.1126/science.abp8337

Understanding the circumstances that lead to pandemics is important for their prevention. We analyzed the genomic diversity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) early in the coronavirus disease 2019 (COVID-19) pandemic. We show that SARS-CoV-2 genomic diversity before February 2020 likely comprised only two distinct viral lineages, denoted "A" and "B." Phylodynamic rooting methods, coupled with epidemic simulations, reveal that these lineages were the result of at least two separate cross-species transmission events into humans. The first zoonotic transmission likely involved lineage B viruses around 18 November 2019 (23 October to 8 December), and the separate introduction of lineage A likely occurred within weeks of this event. These findings indicate that it is unlikely that SARS-CoV-2 circulated widely in humans before November 2019 and define the narrow window between when SARS-CoV-2 first jumped into humans and when the first cases of COVID-19 were reported. As with other coronaviruses, SARS-CoV-2 emergence likely resulted from multiple zoonotic events.

Matched MeSH terms: Genomics/methods
Suppression Subtractive Hybridization Versus Next-Generation Sequencing in Plant Genetic Engineering: Challenges and Perspectives

Sahebi M, Hanafi MM, Azizi P, Hakim A, Ashkani S, Abiri R

Mol Biotechnol, 2015 Oct;57(10):880-903.
PMID: 26271955 DOI: 10.1007/s12033-015-9884-z

Suppression subtractive hybridization (SSH) is an effective method to identify different genes with different expression levels involved in a variety of biological processes. This method has often been used to study molecular mechanisms of plants in complex relationships with different pathogens and a variety of biotic stresses. Compared to other techniques used in gene expression profiling, SSH needs relatively smaller amounts of the initial materials, with lower costs, and fewer false positives present within the results. Extraction of total RNA from plant species rich in phenolic compounds, carbohydrates, and polysaccharides that easily bind to nucleic acids through cellular mechanisms is difficult and needs to be considered. Remarkable advancement has been achieved in the next-generation sequencing (NGS) field. As a result of progress within fields related to molecular chemistry and biology as well as specialized engineering, parallelization in the sequencing reaction has exceptionally enhanced the overall read number of generated sequences per run. Currently available sequencing platforms support an earlier unparalleled view directly into complex mixes associated with RNA in addition to DNA samples. NGS technology has demonstrated the ability to sequence DNA with remarkable swiftness, therefore allowing previously unthinkable scientific accomplishments along with novel biological purposes. However, the massive amounts of data generated by NGS impose a substantial challenge with regard to data safe-keeping and analysis. This review examines some simple but vital points involved in preparing the initial material for SSH and introduces this method as well as its associated applications to detect different novel genes from different plant species. This review evaluates general concepts, basic applications, plus the probable results of NGS technology in genomics, with unique mention of feasible potential tools as well as bioinformatics.

Matched MeSH terms: Genomics/methods
Fulltext StaphyloBase: a specialized genomic resource for the staphylococcal research community

Heydari H, Mutha NV, Mahmud MI, Siow CC, Wee WY, Wong GJ, et al.

Database (Oxford), 2014;2014:bau010.
PMID: 24578355 DOI: 10.1093/database/bau010

With the advent of high-throughput sequencing technologies, many staphylococcal genomes have been sequenced. Comparative analysis of these strains will provide better understanding of their biology, phylogeny, virulence and taxonomy, which may contribute to better management of diseases caused by staphylococcal pathogens. We developed StaphyloBase with the goal of having a one-stop genomic resource platform for the scientific community to access, retrieve, download, browse, search, visualize and analyse the staphylococcal genomic data and annotations. We anticipate this resource platform will facilitate the analysis of staphylococcal genomic data, particularly in comparative analyses. StaphyloBase currently has a collection of 754 032 protein-coding sequences (CDSs), 19 258 rRNAs and 15 965 tRNAs from 292 genomes of different staphylococcal species. Information about these features is also included, such as putative functions, subcellular localizations and gene/protein sequences. Our web implementation supports diverse query types and the exploration of CDS- and RNA-type information in detail using an AJAX-based real-time search system. JBrowse has also been incorporated to allow rapid and seamless browsing of staphylococcal genomes. The Pairwise Genome Comparison tool is designed for comparative genomic analysis, for example, to reveal the relationships between two user-defined staphylococcal genomes. A newly designed Pathogenomics Profiling Tool (PathoProT) is also included in this platform to facilitate comparative pathogenomics analysis of staphylococcal strains. In conclusion, StaphyloBase offers access to a range of staphylococcal genomic resources as well as analysis tools for comparative analyses. Database URL: http://staphylococcus.um.edu.my/.

Matched MeSH terms: Genomics/methods*
Fulltext Singapore Genome Variation Project: a haplotype map of three Southeast Asian populations

Teo YY, Sim X, Ong RT, Tan AK, Chen J, Tantoso E, et al.

Genome Res, 2009 Nov;19(11):2154-62.
PMID: 19700652 DOI: 10.1101/gr.095000.109

The Singapore Genome Variation Project (SGVP) provides a publicly available resource of 1.6 million single nucleotide polymorphisms (SNPs) genotyped in 268 individuals from the Chinese, Malay, and Indian population groups in Southeast Asia. This online database catalogs information and summaries on genotype and phased haplotype data, including allele frequencies, assessment of linkage disequilibrium (LD), and recombination rates in a format similar to the International HapMap Project. Here, we introduce this resource and describe the analysis of human genomic variation upon agglomerating data from the HapMap and the Human Genome Diversity Project, providing useful insights into the population structure of the three major population groups in Asia. In addition, this resource also surveyed across the genome for variation in regional patterns of LD between the HapMap and SGVP populations, and for signatures of positive natural selection using two well-established metrics: iHS and XP-EHH. The raw and processed genetic data, together with all population genetic summaries, are publicly available for download and browsing through a web browser modeled with the Generic Genome Browser.

Matched MeSH terms: Genomics/methods
Fulltext Seqping: gene prediction pipeline for plant genomes using self-training gene models and transcriptomic data

Chan KL, Rosli R, Tatarinova TV, Hogan M, Firdaus-Raih M, Low EL

BMC Bioinformatics, 2017 Jan 27;18(Suppl 1):1426.
PMID: 28466793 DOI: 10.1186/s12859-016-1426-6

BACKGROUND: Gene prediction is one of the most important steps in the genome annotation process. A large number of software tools and pipelines developed by various computing techniques are available for gene prediction. However, these systems have yet to accurately predict all or even most of the protein-coding regions. Furthermore, none of the currently available gene-finders has a universal Hidden Markov Model (HMM) that can perform gene prediction for all organisms equally well in an automatic fashion.
RESULTS: We present an automated gene prediction pipeline, Seqping that uses self-training HMM models and transcriptomic data. The pipeline processes the genome and transcriptome sequences of the target species using GlimmerHMM, SNAP, and AUGUSTUS pipelines, followed by MAKER2 program to combine predictions from the three tools in association with the transcriptomic evidence. Seqping generates species-specific HMMs that are able to offer unbiased gene predictions. The pipeline was evaluated using the Oryza sativa and Arabidopsis thaliana genomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis showed that the pipeline was able to identify at least 95% of BUSCO's plantae dataset. Our evaluation shows that Seqping was able to generate better gene predictions compared to three HMM-based programs (MAKER2, GlimmerHMM and AUGUSTUS) using their respective available HMMs. Seqping had the highest accuracy in rice (0.5648 for CDS, 0.4468 for exon, and 0.6695 nucleotide structure) and A. thaliana (0.5808 for CDS, 0.5955 for exon, and 0.8839 nucleotide structure).
CONCLUSIONS: Seqping provides researchers a seamless pipeline to train species-specific HMMs and predict genes in newly sequenced or less-studied genomes. We conclude that the Seqping pipeline predictions are more accurate than gene predictions using the other three approaches with the default or available HMMs.

Matched MeSH terms: Genomics/methods*
Recombinant vaccines

Barnard RT

Expert Rev Vaccines, 2010 May;9(5):461-3.
PMID: 20450319 DOI: 10.1586/erv.10.48

The Recombinant Vaccines: Strategies for Candidate Discovery and Vaccine Delivery conference, organized by EuroSciCon, hosted a group of UK-based and international scientists from as far afield as Malaysia and Australia. Genomic analyses of pathogens and elucidation of mechanisms of pathogenesis has advanced candidate discovery and development of vaccines. Therefore, it was timely that this conference featured, in addition to detailed expositions of target selection and clinical trials, presentations on manufacturability, scale-up and delivery of vaccines. Ten talks were presented. This meeting report describes the key topics presented and the themes that emerged from this conference.

Matched MeSH terms: Genomics/methods
RNomic identification and evaluation of npcTB_6715, a non-protein-coding RNA gene as a potential biomarker for the detection of Mycobacterium tuberculosis

Kanniappan P, Ahmed SA, Rajasekaram G, Marimuthu C, Ch'ng ES, Lee LP, et al.

J Cell Mol Med, 2017 10;21(10):2276-2283.
PMID: 28756649 DOI: 10.1111/jcmm.13148

Technological advances in RNA biology greatly improved transcriptome profiling during the last two decades. Besides the discovery of many small RNAs (sRNA) that are involved in the physiological and pathophysiological regulation of various cellular circuits, it becomes evident that the corresponding RNA genes might also serve as potential biomarkers to monitor the progression of disease and treatment. sRNA gene candidate npcTB_6715 was previously identified via experimental RNomic (unpublished data), and we report its application as potential biomarker for the detection of Mycobacterium tuberculosis (MTB) in patient samples. For proof of principle, we developed a multiplex PCR assay and report its validation with 500 clinical cultures, positive for Mycobacteria. The analysis revealed 98.9% sensitivity, 96.1% specificity, positive and negative predictive values of 98.6% and 96.8%, respectively. These results underscore the diagnostic value of the sRNA gene as diagnostic marker for the specific detection of MTB in clinical samples. Its successful application and the general ease of PCR-based detection compared to standard bacterial culture techniques might be the first step towards 'point-of-care' diagnostics of Mycobacteria. To the best of our knowledge, this is the first time for the design of diagnostic applications based on sRNA genes, in Mycobacteria.

Matched MeSH terms: Genomics/methods
Fulltext Pre-extinction Demographic Stability and Genomic Signatures of Adaptation in the Woolly Rhinoceros

Lord E, Dussex N, Kierczak M, Díez-Del-Molino D, Ryder OA, Stanton DWG, et al.

Curr Biol, 2020 10 05;30(19):3871-3879.e7.
PMID: 32795436 DOI: 10.1016/j.cub.2020.07.046

Ancient DNA has significantly improved our understanding of the evolution and population history of extinct megafauna. However, few studies have used complete ancient genomes to examine species responses to climate change prior to extinction. The woolly rhinoceros (Coelodonta antiquitatis) was a cold-adapted megaherbivore widely distributed across northern Eurasia during the Late Pleistocene and became extinct approximately 14 thousand years before present (ka BP). While humans and climate change have been proposed as potential causes of extinction [1-3], knowledge is limited on how the woolly rhinoceros was impacted by human arrival and climatic fluctuations [2]. Here, we use one complete nuclear genome and 14 mitogenomes to investigate the demographic history of woolly rhinoceros leading up to its extinction. Unlike other northern megafauna, the effective population size of woolly rhinoceros likely increased at 29.7 ka BP and subsequently remained stable until close to the species' extinction. Analysis of the nuclear genome from a ∼18.5-ka-old specimen did not indicate any increased inbreeding or reduced genetic diversity, suggesting that the population size remained steady for more than 13 ka following the arrival of humans [4]. The population contraction leading to extinction of the woolly rhinoceros may have thus been sudden and mostly driven by rapid warming in the Bølling-Allerød interstadial. Furthermore, we identify woolly rhinoceros-specific adaptations to arctic climate, similar to those of the woolly mammoth. This study highlights how species respond differently to climatic fluctuations and further illustrates the potential of palaeogenomics to study the evolutionary history of extinct species.

Matched MeSH terms: Genomics/methods
Fulltext MycoCAP - Mycobacterium Comparative Analysis Platform

Choo SW, Ang MY, Dutta A, Tan SY, Siow CC, Heydari H, et al.

Sci Rep, 2015 Dec 15;5:18227.
PMID: 26666970 DOI: 10.1038/srep18227

Mycobacterium spp. are renowned for being the causative agent of diseases like leprosy, Buruli ulcer and tuberculosis in human beings. With more and more mycobacterial genomes being sequenced, any knowledge generated from comparative genomic analysis would provide better insights into the biology, evolution, phylogeny and pathogenicity of this genus, thus helping in better management of diseases caused by Mycobacterium spp.With this motivation, we constructed MycoCAP, a new comparative analysis platform dedicated to the important genus Mycobacterium. This platform currently provides information of 2108 genome sequences of at least 55 Mycobacterium spp. A number of intuitive web-based tools have been integrated in MycoCAP particularly for comparative analysis including the PGC tool for comparison between two genomes, PathoProT for comparing the virulence genes among the Mycobacterium strains and the SuperClassification tool for the phylogenic classification of the Mycobacterium strains and a specialized classification system for strains of Mycobacterium abscessus. We hope the broad range of functions and easy-to-use tools provided in MycoCAP makes it an invaluable analysis platform to speed up the research discovery on mycobacteria for researchers. Database URL: http://mycobacterium.um.edu.my.

Matched MeSH terms: Genomics/methods*
Fulltext Museomics for reconstructing historical floristic exchanges: Divergence of stone oaks across Wallacea

Strijk JS, Binh HT, Ngoc NV, Pereira JT, Slik JWF, Sukri RS, et al.

PLoS One, 2020;15(5):e0232936.
PMID: 32442164 DOI: 10.1371/journal.pone.0232936

Natural history collections and tropical tree diversity are both treasure troves of biological and evolutionary information, but their accessibility for scientific study is impeded by a number of properties. DNA in historical specimens is generally highly fragmented, complicating the recovery of high-grade genetic material. Furthermore, our understanding of hyperdiverse, wide-spread tree assemblages is obstructed by extensive species ranges, fragmented knowledge of tropical tree diversity and phenology, and a widespread lack of species-level diagnostic characters, prohibiting the collecting of readily identifiable specimens which can be used to build, revise or strengthen taxonomic frameworks. This, in turn, delays the application of downstream conservation action. A sizable component of botanical collections are sterile-thus eluding identification and are slowing down progress in systematic treatments of tropical biodiversity. With rapid advances in genomics and bioinformatic approaches to biodiversity research, museomics is emerging as a new field breathing life into natural collections that have been built up over centuries. Using MIGseq (multiplexed ISSR genotyping by sequencing), we generated 10,000s of short loci, for both freshly collected materials and museum specimens (aged >100 years) of Lithocarpus-a widespread tropical tree genus endemic to the Asian tropics. Loci recovery from historical and recently collected samples was not affected by sample age and preservation history of the study material, underscoring the reliability and flexibility of the MIGseq approach. Phylogenomic inference and biogeographic reconstruction across insular Asia, highlights repeated migration and diversification patterns between continental regions and islands. Results indicate that co-occurring insular species at the extremity of the distribution range are not monophyletic, raising the possibility of multiple independent dispersals along the outer edge of Wallacea. This suggests that dispersal of large seeded tree genera throughout Malesia and across Wallacea may have been less affected by large geographic distances and the presence of marine barriers than generally assumed. We demonstrate the utility of MIGseq in museomic studies using non-model taxa, presenting the first range-wide genomic assessment of Lithocarpus and tropical Fagaceae as a proof-of-concept. Our study shows the potential for developing innovative genomic approaches to improve the capture of novel evolutionary signals using valuable natural history collections of hyperdiverse taxa.

Matched MeSH terms: Genomics/methods*
Fulltext Multi-platform discovery of haplotype-resolved structural variation in human genomes

Chaisson MJP, Sanders AD, Zhao X, Malhotra A, Porubsky D, Rausch T, et al.

Nat Commun, 2019 04 16;10(1):1784.
PMID: 30992455 DOI: 10.1038/s41467-018-08148-z

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs (≥50 bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.

Matched MeSH terms: Genomics/methods*
Fulltext Microbial Contributions for Rice Production: From Conventional Crop Management to the Use of 'Omics' Technologies

Doni F, Suhaimi NSM, Mispan MS, Fathurrahman F, Marzuki BM, Kusmoro J, et al.

Int J Mol Sci, 2022 Jan 10;23(2).
PMID: 35054923 DOI: 10.3390/ijms23020737

Rice, the main staple food for about half of the world's population, has had the growth of its production stagnate in the last two decades. One of the ways to further improve rice production is to enhance the associations between rice plants and the microbiome that exists around, on, and inside the plant. This article reviews recent developments in understanding how microorganisms exert positive influences on plant growth, production, and health, focusing particularly on rice. A variety of microbial species and taxa reside in the rhizosphere and the phyllosphere of plants and also have multiple roles as symbiotic endophytes while living within plant tissues and even cells. They alter the morphology of host plants, enhance their growth, health, and yield, and reduce their vulnerability to biotic and abiotic stresses. The findings of both agronomic and molecular analysis show ways in which microorganisms regulate the growth, physiological traits, and molecular signaling within rice plants. However, many significant scientific questions remain to be resolved. Advancements in high-throughput multi-omics technologies can be used to elucidate mechanisms involved in microbial-rice plant associations. Prospectively, the use of microbial inoculants and associated approaches offers some new, cost-effective, and more eco-friendly practices for increasing rice production.

Matched MeSH terms: Genomics/methods
Metabolomics and its role in understanding cellular responses in plants

Bhalla R, Narasimhan K, Swarup S

Plant Cell Rep, 2005 Dec;24(10):562-71.
PMID: 16220342

A natural shift is taking place in the approaches being adopted by plant scientists in response to the accessibility of systems-based technology platforms. Metabolomics is one such field, which involves a comprehensive non-biased analysis of metabolites in a given cell at a specific time. This review briefly introduces the emerging field and a range of analytical techniques that are most useful in metabolomics when combined with computational approaches in data analyses. Using cases from Arabidopsis and other selected plant systems, this review highlights how information can be integrated from metabolomics and other functional genomics platforms to obtain a global picture of plant cellular responses. We discuss how metabolomics is enabling large-scale and parallel interrogation of cell states under different stages of development and defined environmental conditions to uncover novel interactions among various pathways. Finally, we discuss selected applications of metabolomics.

Matched MeSH terms: Genomics/methods
MALDI Mass Spectrometry Imaging of Early- and Late-Stage Serous Ovarian Cancer Tissue Reveals Stage-Specific N-Glycans

Briggs MT, Condina MR, Ho YY, Everest-Dass AV, Mittal P, Kaur G, et al.

Proteomics, 2019 11;19(21-22):e1800482.
PMID: 31364262 DOI: 10.1002/pmic.201800482

Epithelial ovarian cancer is one of the most fatal gynecological malignancies in adult women. As studies on protein N-glycosylation have extensively reported aberrant patterns in the ovarian cancer tumor microenvironment, obtaining spatial information will uncover tumor-specific N-glycan alterations in ovarian cancer development and progression. matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is employed to investigate N-glycan distribution on formalin-fixed paraffin-embedded ovarian cancer tissue sections from early- and late-stage patients. Tumor-specific N-glycans are identified and structurally characterized by porous graphitized carbon-liquid chromatography-electrospray ionization-tandem mass spectrometry (PGC-LC-ESI-MS/MS), and then assigned to high-resolution images obtained from MALDI-MSI. Spatial distribution of 14 N-glycans is obtained by MALDI-MSI and 42 N-glycans (including structural and compositional isomers) identified and structurally characterized by LC-MS. The spatial distribution of oligomannose, complex neutral, bisecting, and sialylated N-glycan families are localized to the tumor regions of late-stage ovarian cancer patients relative to early-stage patients. Potential N-glycan diagnostic markers that emerge include the oligomannose structure, (Hex)6 + (Man)3 (GlcNAc)2 , and the complex neutral structure, (Hex)2 (HexNAc)2 (Deoxyhexose)1 + (Man)3 (GlcNAc)2 . The distribution of these markers is evaluated using a tissue microarray of early- and late-stage patients.

Matched MeSH terms: Genomics/methods
Fulltext Jerantinine A induces tumor-specific cell death through modulation of splicing factor 3b subunit 1 (SF3B1)

Chung FF, Tan PF, Raja VJ, Tan BS, Lim KH, Kam TS, et al.

Sci Rep, 2017 02 15;7:42504.
PMID: 28198434 DOI: 10.1038/srep42504

Precursor mRNA (pre-mRNA) splicing is catalyzed by a large ribonucleoprotein complex known as the spliceosome. Numerous studies have indicated that aberrant splicing patterns or mutations in spliceosome components, including the splicing factor 3b subunit 1 (SF3B1), are associated with hallmark cancer phenotypes. This has led to the identification and development of small molecules with spliceosome-modulating activity as potential anticancer agents. Jerantinine A (JA) is a novel indole alkaloid which displays potent anti-proliferative activities against human cancer cell lines by inhibiting tubulin polymerization and inducing G2/M cell cycle arrest. Using a combined pooled-genome wide shRNA library screen and global proteomic profiling, we showed that JA targets the spliceosome by up-regulating SF3B1 and SF3B3 protein in breast cancer cells. Notably, JA induced significant tumor-specific cell death and a significant increase in unspliced pre-mRNAs. In contrast, depletion of endogenous SF3B1 abrogated the apoptotic effects, but not the G2/M cell cycle arrest induced by JA. Further analyses showed that JA stabilizes endogenous SF3B1 protein in breast cancer cells and induced dissociation of the protein from the nucleosome complex. Together, these results demonstrate that JA exerts its antitumor activity by targeting SF3B1 and SF3B3 in addition to its reported targeting of tubulin polymerization.

Matched MeSH terms: Genomics/methods

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