Establishment of quantitative RNAi-based forward genetics in Entamoeba histolytica and identification of genes required for growth

AbstractEntamoeba histolytica is a globally important pathogen that is dramatically understudied. Its challenging genome has limited tractability. To enable forward genetics, we constructed the first genome-wide E. histolytica RNAi knockdown mutant library. The library is designed to enable deep sequencing analysis for quantitative identification of mutants after selection. We developed a novel analysis pipeline to precisely define and quantify full-length gene fragments inferred from read mapping. We performed the first E. histolytica RNAi screen and identified slow growth mutants. Growth phenotypes were reproducible in independently generated mutants. Some of the genes targeted in slow growth mutants had annotated functions consistent with roles in growth or metabolism. Some targeted genes lacked annotation, supporting the power of forward genetics in uncovering gene function. This work opens up the possibility of applying genetics to improve understanding of this important pathogen. Moreover, the strategies behind this RNAi library, and its analysis, are novel, and can be applied to other organisms.

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Establishment of quantitative RNAi-based forward genetics in Entamoeba histolytica and identification of genes required for growth

PLoS Pathogens ◽

10.1371/journal.ppat.1010088 ◽

2021 ◽

Vol 17 (11) ◽

pp. e1010088

Author(s):

Akhila Bettadapur ◽

Samuel S. Hunter ◽

Rene L. Suleiman ◽

Maura C. Ruyechan ◽

Wesley Huang ◽

...

Keyword(s):

Entamoeba Histolytica ◽

Forward Genetics ◽

Cellular Growth ◽

Rnai Pathway ◽

Sequencing Analysis ◽

Genome Wide ◽

Truncation Mutant ◽

Illumina Deep Sequencing ◽

Quantitative Identification ◽

Deep Sequencing Analysis

While Entamoeba histolytica remains a globally important pathogen, it is dramatically understudied. The tractability of E. histolytica has historically been limited, which is largely due to challenging features of its genome. To enable forward genetics, we constructed and validated the first genome-wide E. histolytica RNAi knockdown mutant library. This library allows for Illumina deep sequencing analysis for quantitative identification of mutants that are enriched or depleted after selection. We developed a novel analysis pipeline to precisely define and quantify gene fragments. We used the library to perform the first RNAi screen in E. histolytica and identified slow growth (SG) mutants. Among genes targeted in SG mutants, many had annotated functions consistent with roles in cellular growth or metabolic pathways. Some targeted genes were annotated as hypothetical or lacked annotated domains, supporting the power of forward genetics in uncovering functional information that cannot be gleaned from databases. While the localization of neither of the proteins targeted in SG1 nor SG2 mutants could be predicted by sequence analysis, we showed experimentally that SG1 localized to the cytoplasm and cell surface, while SG2 localized to the cytoplasm. Overexpression of SG1 led to increased growth, while expression of a truncation mutant did not lead to increased growth, and thus aided in defining functional domains in this protein. Finally, in addition to establishing forward genetics, we uncovered new details of the unusual E. histolytica RNAi pathway. These studies dramatically improve the tractability of E. histolytica and open up the possibility of applying genetics to improve understanding of this important pathogen.

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Mutants of Chlamydomonas reinhardtii Deficient in Mitochondrial Complex I: Characterization of Two Mutations Affecting the nd1 Coding Sequence

Genetics ◽

10.1093/genetics/158.3.1051 ◽

2001 ◽

Vol 158 (3) ◽

pp. 1051-1060

Author(s):

Claire Remacle ◽

Denis Baurain ◽

Pierre Cardol ◽

René F Matagne

Keyword(s):

Mitochondrial Genome ◽

Chlamydomonas Reinhardtii ◽

Complex I ◽

Slow Growth ◽

Nadh:Ubiquinone Oxidoreductase ◽

Sequencing Analysis ◽

Mitochondrial Complex ◽

Genetical Analysis ◽

Complex I Activity

Abstract The mitochondrial rotenone-sensitive NADH:ubiquinone oxidoreductase (complex I) comprises more than 30 subunits, the majority of which are encoded by the nucleus. In Chlamydomonas reinhardtii, only five components of complex I are coded for by mitochondrial genes. Three mutants deprived of complex I activity and displaying slow growth in the dark were isolated after mutagenic treatment with acriflavine. A genetical analysis demonstrated that two mutations (dum20 and dum25) affect the mitochondrial genome whereas the third mutation (dn26) is of nuclear origin. Recombinational analyses showed that dum20 and dum25 are closely linked on the genetic map of the mitochondrial genome and could affect the nd1 gene. A sequencing analysis confirmed this conclusion: dum20 is a deletion of one T at codon 243 of nd1; dum25 corresponds to a 6-bp deletion that eliminates two amino acids located in a very conserved hydrophilic segment of the protein.

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Genome-wide identification and characterization of long non-coding RNAs involved in flag leaf senescence of rice

Plant Molecular Biology ◽

10.1007/s11103-021-01121-3 ◽

2021 ◽

Author(s):

Xiaoping Huang ◽

Hongyu Zhang ◽

Qiang Wang ◽

Rong Guo ◽

Lingxia Wei ◽

...

Keyword(s):

Transcription Factors ◽

Leaf Senescence ◽

Flag Leaf ◽

Reduction Process ◽

Sequencing Analysis ◽

Biological Processes ◽

Genome Wide ◽

A Genome ◽

Non Coding Rnas ◽

Systematic Identification

Abstract Key message This study showed the systematic identification of long non-coding RNAs (lncRNAs) involving in flag leaf senescence of rice, providing the possible lncRNA-mRNA regulatory relationships and lncRNA-miRNA-mRNA ceRNA networks during leaf senescence. Abstract LncRNAs have been reported to play crucial roles in diverse biological processes. However, no systematic identification of lncRNAs associated with leaf senescence in plants has been studied. In this study, a genome-wide high throughput sequencing analysis was performed using rice flag leaves developing from normal to senescence. A total of 3953 lncRNAs and 38757 mRNAs were identified, of which 343 lncRNAs and 9412 mRNAs were differentially expressed. Through weighted gene co-expression network analysis (WGCNA), 22 continuously down-expressed lncRNAs targeting 812 co-expressed mRNAs and 48 continuously up-expressed lncRNAs targeting 1209 co-expressed mRNAs were considered to be significantly associated with flag leaf senescence. Gene Ontology results suggested that the senescence-associated lncRNAs targeted mRNAs involving in many biological processes, including transcription, hormone response, oxidation–reduction process and substance metabolism. Additionally, 43 senescence-associated lncRNAs were predicted to target 111 co-expressed transcription factors. Interestingly, 8 down-expressed lncRNAs and 29 up-expressed lncRNAs were found to separately target 12 and 20 well-studied senescence-associated genes (SAGs). Furthermore, analysis on the competing endogenous RNA (CeRNA) network revealed that 6 down-expressed lncRNAs possibly regulated 51 co-expressed mRNAs through 15 miRNAs, and 14 up-expressed lncRNAs possibly regulated 117 co-expressed mRNAs through 21 miRNAs. Importantly, by expression validation, a conserved miR164-NAC regulatory pathway was found to be possibly involved in leaf senescence, where lncRNA MSTRG.62092.1 may serve as a ceRNA binding with miR164a and miR164e to regulate three transcription factors. And two key lncRNAs MSTRG.31014.21 and MSTRG.31014.36 also could regulate the abscisic-acid biosynthetic gene BGIOSGA025169 (OsNCED4) and BGIOSGA016313 (NAC family) through osa-miR5809. The possible regulation networks of lncRNAs involving in leaf senescence were discussed, and several candidate lncRNAs were recommended for prior transgenic analysis. These findings will extend the understanding on the regulatory roles of lncRNAs in leaf senescence, and lay a foundation for functional research on candidate lncRNAs.

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A9 Deep sequencing analysis to investigate the importance of within host genetic diversity and evolution of influenza A viruses for the development of resistance against neuraminidase inhibitors

Virus Evolution ◽

10.1093/ve/vew036.008 ◽

2017 ◽

Vol 3 (suppl_1) ◽

Author(s):

R. Roosenhoff ◽

A. van der Linden ◽

M. Schutten ◽

R.A.M. Fouchier

Keyword(s):

Genetic Diversity ◽

Deep Sequencing ◽

Influenza A ◽

Sequencing Analysis ◽

Neuraminidase Inhibitors ◽

Influenza A Viruses ◽

Development Of Resistance ◽

Host Genetic ◽

Deep Sequencing Analysis

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Identification of non-invasive miRNAs biomarkers for prostate cancer by deep sequencing analysis of urinary exosomes

Molecular Cancer ◽

10.1186/s12943-017-0726-4 ◽

2017 ◽

Vol 16 (1) ◽

Cited By ~ 66

Author(s):

Marta Rodríguez ◽

Cristina Bajo-Santos ◽

Nina P. Hessvik ◽

Susanne Lorenz ◽

Bastian Fromm ◽

...

Keyword(s):

Prostate Cancer ◽

Deep Sequencing ◽

Sequencing Analysis ◽

Non Invasive ◽

Urinary Exosomes ◽

Deep Sequencing Analysis

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Genome-Wide Analysis of Glucocorticoid-Responsive Transcripts in the Hypothalamic Paraventricular Region of Male Rats

Endocrinology ◽

10.1210/en.2018-00535 ◽

2018 ◽

Vol 160 (1) ◽

pp. 38-54 ◽

Cited By ~ 2

Author(s):

Keiichi Itoi ◽

Ikuko Motoike ◽

Ying Liu ◽

Sam Clokie ◽

Yasumasa Iwasaki ◽

...

Keyword(s):

Gene Expression ◽

Target Genes ◽

Receptor Gene ◽

Male Rats ◽

Regulatory Mechanisms ◽

High Dose ◽

Sequencing Analysis ◽

Reverse Transcription Pcr ◽

Genome Wide ◽

A Genome

Abstract Glucocorticoids (GCs) are essential for stress adaptation, acting centrally and in the periphery. Corticotropin-releasing factor (CRF), a major regulator of adrenal GC synthesis, is produced in the paraventricular nucleus of the hypothalamus (PVH), which contains multiple neuroendocrine and preautonomic neurons. GCs may be involved in diverse regulatory mechanisms in the PVH, but the target genes of GCs are largely unexplored except for the CRF gene (Crh), a well-known target for GC negative feedback. Using a genome-wide RNA-sequencing analysis, we identified transcripts that changed in response to either high-dose corticosterone (Cort) exposure for 12 days (12-day high Cort), corticoid deprivation for 7 days (7-day ADX), or acute Cort administration. Among others, canonical GC target genes were upregulated prominently by 12-day high Cort. Crh was upregulated or downregulated most prominently by either 7-day ADX or 12-day high Cort, emphasizing the recognized feedback effects of GC on the hypothalamic-pituitary-adrenal (HPA) axis. Concomitant changes in vasopressin and apelin receptor gene expression are likely to contribute to HPA repression. In keeping with the pleotropic cellular actions of GCs, 7-day ADX downregulated numerous genes of a broad functional spectrum. The transcriptome response signature differed markedly between acute Cort injection and 12-day high Cort. Remarkably, six immediate early genes were upregulated 1 hour after Cort injection, which was confirmed by quantitative reverse transcription PCR and semiquantitative in situ hybridization. This study may provide a useful database for studying the regulatory mechanisms of GC-dependent gene expression and repression in the PVH.

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Novel insight into the non-coding repertoire through deep sequencing analysis

Nucleic Acids Research ◽

10.1093/nar/gks228 ◽

2012 ◽

Vol 40 (11) ◽

pp. e86-e86 ◽

Cited By ~ 13

Author(s):

Ofer Isakov ◽

Roy Ronen ◽

Judit Kovarsky ◽

Aviram Gabay ◽

Ido Gan ◽

...

Keyword(s):

Deep Sequencing ◽

Sequencing Analysis ◽

Deep Sequencing Analysis ◽

Insight Into

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Clonal Lineages of Erysipelothrix rhusiopathiae Responsible for Acute Swine Erysipelas in Japan Identified by Using Genome-Wide Single-Nucleotide Polymorphism Analysis

Applied and Environmental Microbiology ◽

10.1128/aem.00130-17 ◽

2017 ◽

Vol 83 (11) ◽

Cited By ~ 12

Author(s):

Yohsuke Ogawa ◽

Kazumasa Shiraiwa ◽

Yoshitoshi Ogura ◽

Tadasuke Ooka ◽

Sayaka Nishikawa ◽

...

Keyword(s):

Polymorphism Analysis ◽

Whole Genome ◽

Sequencing Analysis ◽

Erysipelothrix Rhusiopathiae ◽

Single Nucleotide ◽

Content Type ◽

Genome Wide ◽

Wide Range ◽

Swine Erysipelas ◽

Lineage Iv

ABSTRACTErysipelothrix rhusiopathiaecauses swine erysipelas, an important infectious disease in the swine industry. In Japan, the incidence of acute swine erysipelas due toE. rhusiopathiaeserovar 1a has recently increased markedly. To study the genetic relatedness of the strains from the recent cases, we analyzed 34E. rhusiopathiaeserovar 1a swine isolates collected between 1990 and 2011 and further investigated the possible association of the live Koganei 65-0.15 vaccine strain (serovar 1a) with the increase in cases. Pulsed-field gel electrophoresis analysis revealed no marked variation among the isolates; however, sequencing analysis of a hypervariable region in the surface-protective antigen A gene (spaA) revealed that the strains isolated after 2007 exhibited the samespaAgenotype and could be differentiated from older strains. Phylogenetic analysis based on genome-wide single-nucleotide polymorphisms (SNPs) revealed that the Japanese strains examined were closely related, showing a relatively small number of SNPs among them. The strains were classified into four major lineages, with Koganei 65-0.15 (lineage III) being phylogenetically separated from the other three lineages. The strains isolated after 2007 and the two older strains constituted one major lineage (lineage IV) with a specificspaAgenotype (M203/I257-SpaA), while the recent isolates were further divided into two geographic groups. The remaining older isolates belonged to either lineage I, with the I203/L257-SpaA type, or lineage II, with the I203/I257-SpaA type. These results indicate that the recent increased incidence of acute swine erysipelas in Japan is associated with two sublineages of lineage IV, which have independently evolved in two different geographic regions.IMPORTANCEUsing large-scale whole-genome sequence data fromErysipelothrix rhusiopathiaeisolates from a wide range of hosts and geographic origins, a recent study clarified the existence of three distinct clades (clades 1, 2, and 3) that are found across multiple continents and host species, representing both livestock and wildlife, and an “intermediate” clade between clade 2 and the dominant clade 3 within the species. In this study, we found that theE. rhusiopathiaeJapanese strains examined exhibited remarkably low levels of genetic diversity and confirmed that all of the Japanese and Chinese swine isolates examined in this study belong to clonal lineages within the intermediate clade. We report thatspaAgenotyping ofE. rhusiopathiaestrains is a practical alternative to whole-genome sequencing analysis of theE. rhusiopathiaeisolates from eastern Asian countries.

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Mapping ribonucleotides embedded in genomic DNA to single-nucleotide resolution using Ribose-Map

10.1101/2020.08.27.267153 ◽

2020 ◽

Author(s):

Alli L. Gombolay ◽

Francesca Storici

Keyword(s):

Computing Time ◽

Wide Distribution ◽

Sequencing Analysis ◽

Sequencing Data ◽

Single Nucleotide ◽

Genome Wide ◽

Hands On ◽

Nucleotide Resolution ◽

User Friendly ◽

Single Nucleotide Resolution

ABSTRACTRibose-Map is a user-friendly, standardized bioinformatics toolkit for the comprehensive analysis of ribonucleotide sequencing experiments. It allows researchers to map the locations of ribonucleotides in DNA to single-nucleotide resolution and identify biological signatures of ribonucleotide incorporation. In addition, it can be applied to data generated using any currently available high-throughput ribonucleotide sequencing technique, thus standardizing the analysis of ribonucleotide sequencing experiments and allowing direct comparisons of results. This protocol describes in detail how to use Ribose-Map to analyze raw ribonucleotide sequencing data, including preparing the reads for analysis, locating the genomic coordinates of ribonucleotides, exploring the genome-wide distribution of ribonucleotides, determining the nucleotide sequence context of ribonucleotides, and identifying hotspots of ribonucleotide incorporation. Ribose-Map does not require background knowledge of ribonucleotide sequencing analysis and assumes only basic command-line skills. The protocol requires less than 3 hr of computing time for most datasets and about 30 min of hands-on time.

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