Comparative analysis of whole flower transcriptomes in the Zingiberales

The advancement of next generation sequencing technologies (NGS) has revolutionized our ability to generate large quantities of data at a genomic scale. Despite great challenges, these new sequencing technologies have empowered scientists to explore various relevant biological questions on non-model organisms, even in the absence of a complete sequenced reference genome. Here, we analyzed whole flower transcriptome libraries from exemplar species across the monocot order Zingiberales, using a comparative approach in order to gain insight into the evolution of the molecular mechanisms underlying flower development in the group. We identified 4,153 coding genes shared by all floral transcriptomes analyzed, and 1,748 genes that are only retrieved in the Zingiberales. We also identified 666 genes that are unique to the ginger lineage, and 2,001 that are only found in the banana group, while in the outgroup species Dichorisandra thyrsiflora J.C. Mikan (Commelinaceae) we retrieved 2,686 unique genes. It is possible that some of these genes underlie lineage-specific molecular mechanisms of floral diversification. We further discuss the nature of these lineage-specific datasets, emphasizing conserved and unique molecular processes with special emphasis in the Zingiberales. We also briefly discuss the strengths and shortcomings of de novo assembly for the study of developmental processes across divergent taxa from a particular order. Although this comparison is based exclusively on coding genes, with particular emphasis in transcription factors, we believe that the careful study of other regulatory mechanisms, such as non-coding RNAs, might reveal new levels of complexity, which were not explored in this work.

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Transgenic Epigenetics: Using Transgenic Organisms to Examine Epigenetic Phenomena

Genetics Research International ◽

10.1155/2012/689819 ◽

2012 ◽

Vol 2012 ◽

pp. 1-14 ◽

Cited By ~ 2

Author(s):

Lori A. McEachern

Keyword(s):

Molecular Mechanisms ◽

Model Organism ◽

Evolutionary Conservation ◽

Model Organisms ◽

Valuable Insight ◽

Epigenetic Control ◽

Transgenic Organisms ◽

Epigenetic Analysis ◽

Insight Into ◽

Epigenetic Processes

Non-model organisms are generally more difficult and/or time consuming to work with than model organisms. In addition, epigenetic analysis of model organisms is facilitated by well-established protocols, and commercially-available reagents and kits that may not be available for, or previously tested on, non-model organisms. Given the evolutionary conservation and widespread nature of many epigenetic mechanisms, a powerful method to analyze epigenetic phenomena from non-model organisms would be to use transgenic model organisms containing an epigenetic region of interest from the non-model. Interestingly, while transgenic Drosophila and mice have provided significant insight into the molecular mechanisms and evolutionary conservation of the epigenetic processes that target epigenetic control regions in other model organisms, this method has so far been under-exploited for non-model organism epigenetic analysis. This paper details several experiments that have examined the epigenetic processes of genomic imprinting and paramutation, by transferring an epigenetic control region from one model organism to another. These cross-species experiments demonstrate that valuable insight into both the molecular mechanisms and evolutionary conservation of epigenetic processes may be obtained via transgenic experiments, which can then be used to guide further investigations and experiments in the species of interest.

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The Making of Long-Lasting Memories: A Fruit Fly Perspective

Frontiers in Behavioral Neuroscience ◽

10.3389/fnbeh.2021.662129 ◽

2021 ◽

Vol 15 ◽

Author(s):

Camilla Roselli ◽

Mani Ramaswami ◽

Tamara Boto ◽

Isaac Cervantes-Sandoval

Keyword(s):

Learning And Memory ◽

Neural Activity ◽

Molecular Mechanisms ◽

De Novo ◽

Fruit Fly ◽

Memory Formation ◽

Synaptic Activity ◽

Model Organisms ◽

Transient Wave ◽

Control Of Gene Expression

Understanding the nature of the molecular mechanisms underlying memory formation, consolidation, and forgetting are some of the fascinating questions in modern neuroscience. The encoding, stabilization and elimination of memories, rely on the structural reorganization of synapses. These changes will enable the facilitation or depression of neural activity in response to the acquisition of new information. In other words, these changes affect the weight of specific nodes within a neural network. We know that these plastic reorganizations require de novo protein synthesis in the context of Long-term memory (LTM). This process depends on neural activity triggered by the learned experience. The use of model organisms like Drosophila melanogaster has been proven essential for advancing our knowledge in the field of neuroscience. Flies offer an optimal combination of a more straightforward nervous system, composed of a limited number of cells, and while still displaying complex behaviors. Studies in Drosophila neuroscience, which expanded over several decades, have been critical for understanding the cellular and molecular mechanisms leading to the synaptic and behavioral plasticity occurring in the context of learning and memory. This is possible thanks to sophisticated technical approaches that enable precise control of gene expression in the fruit fly as well as neural manipulation, like chemogenetics, thermogenetics, or optogenetics. The search for the identity of genes expressed as a result of memory acquisition has been an active interest since the origins of behavioral genetics. From screenings of more or less specific candidates to broader studies based on transcriptome analysis, our understanding of the genetic control behind LTM has expanded exponentially in the past years. Here we review recent literature regarding how the formation of memories induces a rapid, extensive and, in many cases, transient wave of transcriptional activity. After a consolidation period, transcriptome changes seem more stable and likely represent the synthesis of new proteins. The complexity of the circuitry involved in memory formation and consolidation is such that there are localized changes in neural activity, both regarding temporal dynamics and the nature of neurons and subcellular locations affected, hence inducing specific temporal and localized changes in protein expression. Different types of neurons are recruited at different times into memory traces. In LTM, the synthesis of new proteins is required in specific subsets of cells. This de novo translation can take place in the somatic cytoplasm and/or locally in distinct zones of compartmentalized synaptic activity, depending on the nature of the proteins and the plasticity-inducing processes that occur. We will also review recent advances in understanding how localized changes are confined to the relevant synapse. These recent studies have led to exciting discoveries regarding proteins that were not previously involved in learning and memory processes. This invaluable information will lead to future functional studies on the roles that hundreds of new molecular actors play in modulating neural activity.

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Autophagosome biogenesis: From membrane growth to closure

The Journal of Cell Biology ◽

10.1083/jcb.202002085 ◽

2020 ◽

Vol 219 (6) ◽

Cited By ~ 11

Author(s):

Thomas J. Melia ◽

Alf H. Lystad ◽

Anne Simonsen

Keyword(s):

Molecular Mechanisms ◽

De Novo ◽

Membrane Vesicle ◽

Double Membrane ◽

The Core ◽

Membrane Modeling ◽

Membrane Growth ◽

Initial Discovery ◽

Insight Into ◽

Key Questions

Autophagosome biogenesis involves de novo formation of a membrane that elongates to sequester cytoplasmic cargo and closes to form a double-membrane vesicle (an autophagosome). This process has remained enigmatic since its initial discovery >50 yr ago, but our understanding of the mechanisms involved in autophagosome biogenesis has increased substantially during the last 20 yr. Several key questions do remain open, however, including, What determines the site of autophagosome nucleation? What is the origin and lipid composition of the autophagosome membrane? How is cargo sequestration regulated under nonselective and selective types of autophagy? This review provides key insight into the core molecular mechanisms underlying autophagosome biogenesis, with a specific emphasis on membrane modeling events, and highlights recent conceptual advances in the field.

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Genomics of medulloblastoma: from Giemsa-banding to next-generation sequencing in 20 years

Neurosurgical FOCUS ◽

10.3171/2009.10.focus09218 ◽

2010 ◽

Vol 28 (1) ◽

pp. E6 ◽

Cited By ~ 39

Author(s):

Paul A. Northcott ◽

James T. Rutka ◽

Michael D. Taylor

Keyword(s):

Next Generation Sequencing ◽

Molecular Mechanisms ◽

Genomic Medicine ◽

Prognostic Significance ◽

Next Generation ◽

Sequencing Technologies ◽

Disease Stratification ◽

Insight Into ◽

Generation Sequencing

Advances in the field of genomics have recently enabled the unprecedented characterization of the cancer genome, providing novel insight into the molecular mechanisms underlying malignancies in humans. The application of high-resolution microarray platforms to the study of medulloblastoma has revealed new oncogenes and tumor suppressors and has implicated changes in DNA copy number, gene expression, and methylation state in its etiology. Additionally, the integration of medulloblastoma genomics with patient clinical data has confirmed molecular markers of prognostic significance and highlighted the potential utility of molecular disease stratification. The advent of next-generation sequencing technologies promises to greatly transform our understanding of medulloblastoma pathogenesis in the next few years, permitting comprehensive analyses of all aspects of the genome and increasing the likelihood that genomic medicine will become part of the routine diagnosis and treatment of medulloblastoma.

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The Dfam community resource of transposable element families, sequence models, and genome annotations

Mobile DNA ◽

10.1186/s13100-020-00230-y ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Jessica Storer ◽

Robert Hubley ◽

Jeb Rosen ◽

Travis J. Wheeler ◽

Arian F. Smit

Keyword(s):

Transposable Element ◽

De Novo ◽

Consensus Sequence ◽

Model Organisms ◽

Community Resource ◽

Open Access Database ◽

Genome Annotations ◽

Protein Alignments ◽

Insight Into

AbstractDfam is an open access database of repetitive DNA families, sequence models, and genome annotations. The 3.0–3.3 releases of Dfam (https://dfam.org) represent an evolution from a proof-of-principle collection of transposable element families in model organisms into a community resource for a broad range of species, and for both curated and uncurated datasets. In addition, releases since Dfam 3.0 provide auxiliary consensus sequence models, transposable element protein alignments, and a formalized classification system to support the growing diversity of organisms represented in the resource. The latest release includes 266,740 new de novo generated transposable element families from 336 species contributed by the EBI. This expansion demonstrates the utility of many of Dfam’s new features and provides insight into the long term challenges ahead for improving de novo generated transposable element datasets.

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De novo transcriptome assembly of the Italian white truffle (Tuber magnatum Pico)

10.1101/461483 ◽

2018 ◽

Cited By ~ 1

Author(s):

Federico Vita ◽

Amedeo Alpi ◽

Edoardo Bertolini

Keyword(s):

Molecular Mechanisms ◽

De Novo ◽

Transcriptome Assembly ◽

Rna Seq ◽

Genetic Studies ◽

Protein Coding ◽

Important Species ◽

White Truffle ◽

Tuber Magnatum ◽

Insight Into

AbstractThe Italian white truffle (Tuber magnatum Pico) is a gastronomic delicacy that dominates the worldwide truffle market. Despite its importance, the genomic resources currently available for this species are still limited. Here we present the first de novo transcriptome assembly of T. magnatum. Illumina RNA-seq data were assembled using a single-k-mer approach into 22,932 transcripts with N50 of 1,524 bp. Our approach allowed to predict and annotate 12,367 putative protein coding sequences, reunited in 6,723 loci. In addition, we identified 2,581 gene-based SSR markers. This work provides the first publicly available reference transcriptome for genomics and genetic studies providing insight into the molecular mechanisms underlying the biology of this important species.

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De novo profiling of long non-coding RNAs involved in MC-LR–induced liver injury in whitefish: discovery and perspectives

10.21203/rs.3.rs-62335/v1 ◽

2020 ◽

Author(s):

Maciej Florczyk ◽

Paweł Brzuzan ◽

Maciej Woźny

Keyword(s):

Liver Injury ◽

Molecular Mechanisms ◽

Liver Toxicity ◽

De Novo ◽

Sequence Data ◽

Regulation Of Gene Expression ◽

Model Organisms ◽

Coregonus Lavaretus ◽

Digital Repository ◽

Non Coding Rnas

Abstract BackgroundMicrocystin-LR (MC-LR) is a potent hepatotoxin for which a substantial gap in knowledge persists regarding the underlying molecular mechanisms of liver toxicity and injury. Although long non-coding RNAs (lncRNAs) have been extensively studied in model organisms, and their roles have been identified in various cellular processes including participation in regulation of gene expression together with microRNAs, our knowledge concerning the role of lncRNAs in liver injury is limited even in mammals. Given that lncRNAs show low levels of sequence conservation, their role becomes even more unclear in non-model organisms without an annotated genome, like whitefish (Coregonus lavaretus). The objective of this study was to discover and profile aberrantly expressed polyadenylated lncRNAs that are involved in MC-LR–induced liver injury in whitefish.ResultsUsing polyA-enriched RNA-Seq data, we de novo assembled a high quality whitefish liver transcriptome. This enabled us to find 94 differentially expressed (DE) putative evolutionary-conserved lncRNAs (orthologous to known lncRNAs in other species), such as MALAT1, HOTTIP, HOTAIR or HULC and 4,429 DE putative novel whitefish lncRNAs, which differed from annotated protein-coding transcripts (PCTs) in terms of minimum free energy, GC base-pair content and length. Additionally, we identified DE non-coding transcripts that might be 3’ autonomous untranslated regions of mRNAs (3’UTRs). We found that, in response to MC-LR treatment, these potential 3’UTRs could either be coexpressed with PCTs from the same mRNA, or the 3’UTRs were upregulated while the corresponding PCTs were downregulated, suggesting 3’UTR-dependent gene regulation.ConclusionsTo our knowledge this is the first report on aberrantly expressed lncRNAs in MC-LR–induced liver injury in whitefish. We found both evolutionary conserved lncRNAs as well as novel whitefish lncRNAs that could serve as biomarkers of severe and chronic liver injury. The lncRNA sequence data files and raw sequence files are available in the Dryad Digital Repository and the NCBI Sequence Read Archive, respectively.

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The Dfam Community Resource of Transposable Element Families, Sequence Models, and Genome Annotations

10.21203/rs.3.rs-76062/v1 ◽

2020 ◽

Author(s):

Jessica Storer ◽

Robert Hubley ◽

Jeb Rosen ◽

Travis Wheeler ◽

Arian F.A. Smit

Keyword(s):

Transposable Element ◽

De Novo ◽

Consensus Sequence ◽

Model Organisms ◽

Community Resource ◽

Genome Annotations ◽

Protein Alignments ◽

Insight Into ◽

Proof Of Principle

Abstract The 3.0-3.2 releases of Dfam (https://dfam.org) represent an evolution from a proof-of-principle collection of transposable element families in model organisms into a community resource for a broad range of species and for both curated and uncurated datasets. In addition, releases since Dfam 3.0 provide auxiliary consensus sequence models, transposable element protein alignments, and a formalized classification system to support the growing diversity of organisms represented in the resource. The latest release includes 266,740 new de novo generated transposable element families from 336 species contributed by the EBI. This expansion demonstrates the utility of many of Dfam’s new features and provides insight into the long term challenges ahead for improving de novo generated transposable element datasets.

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Rest is Required to Learn an Appetitively-Reinforced Operant Task in Drosophila

10.1101/2020.08.28.272047 ◽

2020 ◽

Author(s):

Timothy D. Wiggin ◽

Yung-Yi Hsiao ◽

Jeffrey B. Liu ◽

Robert Huber ◽

Leslie C. Griffith

Keyword(s):

Drosophila Melanogaster ◽

Operant Conditioning ◽

Food Reward ◽

Molecular Mechanisms ◽

Genetic Model ◽

Fruit Fly ◽

Model Organisms ◽

Neural Basis ◽

Operant Task ◽

Insight Into

ABSTRACTMaladaptive operant conditioning contributes to development of neuropsychiatric disorders. Candidate genes have been identified that contribute to this maladaptive plasticity, but the neural basis of operant conditioning in genetic model organisms remains poorly understood. The fruit fly Drosophila melanogaster is a versatile genetic model organism that readily forms operant associations with punishment stimuli. However, operant conditioning with a food reward has not been demonstrated in flies, limiting the types of neural circuits that can be studied. Here we present the first sucrose-reinforced operant conditioning paradigm for flies. Flies of both sexes walk along a Y-shaped track with reward locations at the terminus of each hallway. When flies turn in the reinforced direction at the center of the track, sucrose is presented at the end of the hallway. Only flies that rest during training show evidence of learning the reward contingency. Flies rewarded independently of their behavior do not form a learned association but have the same amount of rest as trained flies, showing that rest is not driven by learning. Optogenetically-induced rest does not promote learning, indicating that rest is not sufficient for learning the operant task. We validated the sensitivity of this assay to detect the effect of genetic manipulations by testing the classic learning mutant dunce. Dunce flies are learning impaired in the Y-Track task, indicating a likely role for cAMP in the operant coincidence detector. This novel training paradigm will provide valuable insight into the molecular mechanisms of disease and the link between sleep and learning.SIGNIFICANCE STATEMENTOperant conditioning and mental health are deeply intertwined: maladaptive conditioning contributes to many pathologies, while therapeutic operant conditioning is a frequently used tool in talk therapy. Unlike drug interventions which target molecules or mechanisms, it is not known how operant conditioning changes the brain to promote wellness or distress. To gain mechanistic insight into how this form of learning works, we developed a novel operant training task for the fruit fly Drosophila melanogaster. We made three key discoveries. First, flies are able to learn an operant task to find food reward. Second, rest during training is necessary for learning. Third, the dunce gene is necessary for both classical and operant conditioning in flies, indicating that they may share molecular mechanisms.

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Twelve quick steps for genome assembly and annotation in the classroom

PLoS Computational Biology ◽

10.1371/journal.pcbi.1008325 ◽

2020 ◽

Vol 16 (11) ◽

pp. e1008325

Author(s):

Hyungtaek Jung ◽

Tomer Ventura ◽

J. Sook Chung ◽

Woo-Jin Kim ◽

Bo-Hye Nam ◽

...

Keyword(s):

Genome Assembly ◽

De Novo ◽

Repetitive Sequences ◽

Genome Project ◽

Model Organisms ◽

High Quality ◽

Sequencing Technologies ◽

A Genome ◽

Sequencing Platforms ◽

High Quality Genome

Eukaryotic genome sequencing and de novo assembly, once the exclusive domain of well-funded international consortia, have become increasingly affordable, thus fitting the budgets of individual research groups. Third-generation long-read DNA sequencing technologies are increasingly used, providing extensive genomic toolkits that were once reserved for a few select model organisms. Generating high-quality genome assemblies and annotations for many aquatic species still presents significant challenges due to their large genome sizes, complexity, and high chromosome numbers. Indeed, selecting the most appropriate sequencing and software platforms and annotation pipelines for a new genome project can be daunting because tools often only work in limited contexts. In genomics, generating a high-quality genome assembly/annotation has become an indispensable tool for better understanding the biology of any species. Herein, we state 12 steps to help researchers get started in genome projects by presenting guidelines that are broadly applicable (to any species), sustainable over time, and cover all aspects of genome assembly and annotation projects from start to finish. We review some commonly used approaches, including practical methods to extract high-quality DNA and choices for the best sequencing platforms and library preparations. In addition, we discuss the range of potential bioinformatics pipelines, including structural and functional annotations (e.g., transposable elements and repetitive sequences). This paper also includes information on how to build a wide community for a genome project, the importance of data management, and how to make the data and results Findable, Accessible, Interoperable, and Reusable (FAIR) by submitting them to a public repository and sharing them with the research community.

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