Application of Distributive Conjugal DNA Transfer in Mycobacterium smegmatis To Establish a Genome-Wide Synthetic Genetic Array

ABSTRACT Genetic redundancy can obscure phenotypic effects of single-gene mutations. Two individual mutations may be viable separately but are lethal when combined, thus synthetically linking the two gene products in an essential process. Synthetic genetic arrays (SGAs), in which defined mutations are combined, provide a powerful approach to identify novel genetic interactions and redundant pathways. A genome-scale SGA can offer an initial assignment of function to hypothetical genes by uncovering interactions with known genes or pathways. Here, we take advantage of the chromosomal conjugation system of Mycobacterium smegmatis to combine individual donor and recipient mutations on a genome-wide scale. We demonstrated the feasibility of a high-throughput mycobacterial SGA (mSGA) screen by using mutants of esx3, fxbA, and recA as query genes, which were combined with an arrayed library of transposon mutants by conjugation. The mSGA identified interacting genes that we had predicted and, most importantly, identified novel interacting genes—encoding both proteins and a noncoding RNA (ncRNA). In combination with other molecular genetic approaches, the mSGA has great potential to both reduce the high number of conserved hypothetical protein annotations in mycobacterial genomes and further define mycobacterial pathways and gene interactions. IMPORTANCE Mycobacterium smegmatis is the model organism of choice for the study of mycobacterial pathogens, because it is a fast-growing nonpathogenic species harboring many genes that are conserved throughout mycobacteria. In this work, we describe a synthetic genetic array (mSGA) approach for M. smegmatis, which combines mutations on a genome-wide scale with high efficiency. Analysis of the double mutant strains enables the identification of interacting genes and pathways that are normally hidden by redundant biological pathways. The mSGA is a powerful genetic tool that enables functions to be assigned to the many conserved hypothetical genes found in all mycobacterial species.

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F-Box Genes in the Wheat Genome and Expression Profiling in Wheat at Different Developmental Stages

Genes ◽

10.3390/genes11101154 ◽

2020 ◽

Vol 11 (10) ◽

pp. 1154

Author(s):

Min Jeong Hong ◽

Jin-Baek Kim ◽

Yong Weon Seo ◽

Dae Yeon Kim

Keyword(s):

Developmental Stages ◽

Brachypodium Distachyon ◽

Triticum Aestivum L ◽

Wheat Genome ◽

Post Translational Modification ◽

Genome Wide ◽

A Genome ◽

High Sequence Homology ◽

Wide Scale

Genes of the F-box family play specific roles in protein degradation by post-translational modification in several biological processes, including flowering, the regulation of circadian rhythms, photomorphogenesis, seed development, leaf senescence, and hormone signaling. F-box genes have not been previously investigated on a genome-wide scale; however, the establishment of the wheat (Triticum aestivum L.) reference genome sequence enabled a genome-based examination of the F-box genes to be conducted in the present study. In total, 1796 F-box genes were detected in the wheat genome and classified into various subgroups based on their functional C-terminal domain. The F-box genes were distributed among 21 chromosomes and most showed high sequence homology with F-box genes located on the homoeologous chromosomes because of allohexaploidy in the wheat genome. Additionally, a synteny analysis of wheat F-box genes was conducted in rice and Brachypodium distachyon. Transcriptome analysis during various wheat developmental stages and expression analysis by quantitative real-time PCR revealed that some F-box genes were specifically expressed in the vegetative and/or seed developmental stages. A genome-based examination and classification of F-box genes provide an opportunity to elucidate the biological functions of F-box genes in wheat.

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Genome-wide mapping of unexplored essential regions in the Saccharomyces cerevisiae genome: evidence for hidden synthetic lethal combinations in a genetic interaction network

Nucleic Acids Research ◽

10.1093/nar/gku576 ◽

2014 ◽

Vol 42 (15) ◽

pp. 9838-9853 ◽

Cited By ~ 6

Author(s):

Saeed Kaboli ◽

Takuya Yamakawa ◽

Keisuke Sunada ◽

Tao Takagaki ◽

Yu Sasano ◽

...

Keyword(s):

Saccharomyces Cerevisiae ◽

Genetic Interaction ◽

Interaction Network ◽

Essential Genes ◽

Genetic Interactions ◽

Lethal Gene ◽

Synthetic Lethal ◽

Genome Wide ◽

A Genome ◽

Wide Scale

Abstract Despite systematic approaches to mapping networks of genetic interactions in Saccharomyces cerevisiae, exploration of genetic interactions on a genome-wide scale has been limited. The S. cerevisiae haploid genome has 110 regions that are longer than 10 kb but harbor only non-essential genes. Here, we attempted to delete these regions by PCR-mediated chromosomal deletion technology (PCD), which enables chromosomal segments to be deleted by a one-step transformation. Thirty-three of the 110 regions could be deleted, but the remaining 77 regions could not. To determine whether the 77 undeletable regions are essential, we successfully converted 67 of them to mini-chromosomes marked with URA3 using PCR-mediated chromosome splitting technology and conducted a mitotic loss assay of the mini-chromosomes. Fifty-six of the 67 regions were found to be essential for cell growth, and 49 of these carried co-lethal gene pair(s) that were not previously been detected by synthetic genetic array analysis. This result implies that regions harboring only non-essential genes contain unidentified synthetic lethal combinations at an unexpectedly high frequency, revealing a novel landscape of genetic interactions in the S. cerevisiae genome. Furthermore, this study indicates that segmental deletion might be exploited for not only revealing genome function but also breeding stress-tolerant strains.

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Genome-wide polygenic analysis of multiple sclerosis markers

Neurology neuropsychiatry Psychosomatics ◽

10.14412/2074-2711-2021-1s-31-38 ◽

2021 ◽

Vol 13 (1S) ◽

pp. 31-38

Author(s):

Ya. R. Timasheva ◽

T. R. Nasibullin ◽

I. A. Tuktarova ◽

V. V. Erdman ◽

T. R. Galiullin ◽

...

Keyword(s):

Multiple Sclerosis ◽

Ethnic Groups ◽

Noncoding Rna ◽

Polymorphism Analysis ◽

Polymorphic Loci ◽

Lectin Domain ◽

Genome Wide ◽

A Genome ◽

Disease Associations ◽

Polygenic Analysis

Objective: to perform a genome-wide polygenic analysis of multiple sclerosis (MS) markers in the ethnic groups of Bashkirs, Russians, and Tatars living in the Republic of Bashkortostan (Russian Federation).Patients and methods. Genotyping was performed using allele-specific polymerase chain reaction (PCR) and PCR-restriction fragment length polymorphism analysis of genes of the human leukocyte differentiation antigens CD6 (rs17824933), CD40 (rs6074022), CD58 (rs2300747), CD86 (rs9282641), transcription factors SOX8 (rs2744148) and ZBTB46 (rs6062314), beta-mannosidase MANBA (rs228614), C-type lectin domain CLEC16A (rs12708716), ribosomal protein S6 kinase B1 RPS6KB1 (rs180515), and long noncoding RNA gene PVT1 (rs759648) in 644 patients with MS and 1408 controls. Multilocus analysis of the disease associations with combinations of genotypes and alleles of the studied polymorphic loci was performed using the APSampler algorithm.Results and discussion. We determined the distribution of genotype and allele frequencies of the studied polymorphic loci in the ethnic groups of Bashkirs, Russians, and Tatars. We also observed disease associations with CD58 (rs2300747) and RPS6KB1 (rs180515) polymorphic loci in Russian men, CD86 (rs9282641) in Russian, PVT1 (rs759648) in Tatar women, CD40 (rs6074022) in Bashkir men, and identified 19 combinations of genotypes and/or alleles significantly associated with MS.Conclusion. Based on the genome-wide polygenic analysis of MS markers, we identified ethno- and gender-specific combined markers of the disease susceptibility.

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Machine-learning annotation of human splicing branchpoints

10.1101/094003 ◽

2016 ◽

Cited By ~ 3

Author(s):

Bethany Signal ◽

Brian S Gloss ◽

Marcel E Dinger ◽

Timothy R Mercer

Keyword(s):

Machine Learning ◽

Learning Algorithm ◽

Gene Splicing ◽

Genetic Encoding ◽

Genome Wide ◽

Common Genetic Variants ◽

A Genome ◽

Wide Scale ◽

The Impact ◽

Splicing Patterns

ABSTRACTBackgroundThe branchpoint element is required for the first lariat-forming reaction in splicing. However due to difficulty in experimentally mapping at a genome-wide scale, current catalogues are incomplete.ResultsWe have developed a machine-learning algorithm trained with empirical human branchpoint annotations to identify branchpoint elements from primary genome sequence alone. Using this approach, we can accurately locate branchpoints elements in 85% of introns in current gene annotations. Consistent with branchpoints as basal genetic elements, we find our annotation is unbiased towards gene type and expression levels. A major fraction of introns was found to encode multiple branchpoints raising the prospect that mutational redundancy is encoded in key genes. We also confirmed all deleterious branchpoint mutations annotated in clinical variant databases, and further identified thousands of clinical and common genetic variants with similar predicted effects.ConclusionsWe propose the broad annotation of branchpoints constitutes a valuable resource for further investigations into the genetic encoding of splicing patterns, and interpreting the impact of common- and disease-causing human genetic variation on gene splicing.

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Emerging Technologies for Genome-Wide Profiling of DNA Breakage

Frontiers in Genetics ◽

10.3389/fgene.2020.610386 ◽

2021 ◽

Vol 11 ◽

Author(s):

Matthew J. Rybin ◽

Melina Ramic ◽

Natalie R. Ricciardi ◽

Philipp Kapranov ◽

Claes Wahlestedt ◽

...

Keyword(s):

Genome Instability ◽

Dna Double Strand Breaks ◽

Single Nucleotide ◽

Strand Breaks ◽

Single Strand Breaks ◽

Genome Wide ◽

A Genome ◽

Wide Scale ◽

Nucleotide Resolution ◽

Genomic Regions

Genome instability is associated with myriad human diseases and is a well-known feature of both cancer and neurodegenerative disease. Until recently, the ability to assess DNA damage—the principal driver of genome instability—was limited to relatively imprecise methods or restricted to studying predefined genomic regions. Recently, new techniques for detecting DNA double strand breaks (DSBs) and single strand breaks (SSBs) with next-generation sequencing on a genome-wide scale with single nucleotide resolution have emerged. With these new tools, efforts are underway to define the “breakome” in normal aging and disease. Here, we compare the relative strengths and weaknesses of these technologies and their potential application to studying neurodegenerative diseases.

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The Genetics and Genomics of Asthma

Annual Review of Genomics and Human Genetics ◽

10.1146/annurev-genom-083117-021651 ◽

2018 ◽

Vol 19 (1) ◽

pp. 223-246 ◽

Cited By ~ 14

Author(s):

Saffron A.G. Willis-Owen ◽

William O.C. Cookson ◽

Miriam F. Moffatt

Keyword(s):

Sequence Variation ◽

Human Microbiome ◽

Technological Advances ◽

Genome Wide ◽

A Genome ◽

Wide Range ◽

Health And Disease ◽

Wide Scale ◽

Genetics And Genomics ◽

The Individual

Asthma is a common, clinically heterogeneous disease with strong evidence of heritability. Progress in defining the genetic underpinnings of asthma, however, has been slow and hampered by issues of inconsistency. Recent advances in the tools available for analysis—assaying transcription, sequence variation, and epigenetic marks on a genome-wide scale—have substantially altered this landscape. Applications of such approaches are consistent with heterogeneity at the level of causation and specify patterns of commonality with a wide range of alternative disease traits. Looking beyond the individual as the unit of study, advances in technology have also fostered comprehensive analysis of the human microbiome and its varied roles in health and disease. In this article, we consider the implications of these technological advances for our current understanding of the genetics and genomics of asthma.

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Host Genetic Factors Associated with Vaginal Microbiome Composition in Kenyan Women

mSystems ◽

10.1128/msystems.00502-20 ◽

2020 ◽

Vol 5 (4) ◽

Cited By ~ 2

Author(s):

Supriya D. Mehta ◽

Drew R. Nannini ◽

Fredrick Otieno ◽

Stefan J. Green ◽

Walter Agingu ◽

...

Keyword(s):

Racial Differences ◽

Genome Wide Association Study ◽

Vaginal Microbiome ◽

Content Type ◽

Microbiome Composition ◽

Genome Wide ◽

A Genome ◽

Kenyan Women ◽

Host Genetic ◽

Women Of African Descent

ABSTRACT Bacterial vaginosis (BV) affects 20% of women worldwide and is associated with adverse reproductive health outcomes and increased risk for HIV. Typically, BV represents a shift in the vaginal microbiome from one that is dominated by Lactobacillus to one that is diverse. Persistent racial differences in BV and diverse vaginal microbiome composition overlap with racial disparities in risks for HIV and sexually transmitted infection, especially among women of African descent. Risk factors for BV and nonoptimal vaginal microbiome include sexual practices, yet racial differences persist when adjusted for behavioral factors, suggesting a host genetic component. Here, we perform a genome-wide association study on vaginal microbiome traits in Kenyan women. Linear regression and logistic regression were performed, adjusting for age and principal components of genetic ancestry, to evaluate the association between Lactobacillus crispatus, Lactobacillus iners, Gardnerella vaginalis, Shannon diversity index, and community state type (CST) with host genetic single nucleotide polymorphisms (SNPs). We identified novel genomic loci associated with the vaginal microbiome traits, though no SNP reached genome-wide significance. During pathway enrichment analysis, Toll-like receptors (TLRs), cytokine production, and other components of innate immune response were associated with L. crispatus, L. iners, and CST. Multiple previously reported genomic loci were replicated, including IL-8 (Shannon, CST), TIRAP (L. iners, Shannon), TLR2 (Shannon, CST), MBL2 (L. iners, G. vaginalis, CST), and MYD88 (L. iners, Shannon). These genetic associations suggest a role for the innate immune system and cell signaling in vaginal microbiome composition and susceptibility to nonoptimal vaginal microbiome. IMPORTANCE Globally, bacterial vaginosis (BV) is a common condition in women. BV is associated with poorer reproductive health outcomes and HIV risk. Typically, BV represents a shift in the vaginal microbiome from one that is dominated by Lactobacillus to one that is diverse. Despite many women having similar exposures, the prevalence of BV and nonoptimal vaginal microbiome is increased for women of African descent, suggesting a possible role for host genetics. We conducted a genome-wide association study of important vaginal microbiome traits in Kenyan women. We identified novel genetic loci and biological pathways related to mucosal immunity, cell signaling, and infection that were associated with vaginal microbiome traits; we replicated previously reported loci associated with mucosal immune response. These results provide insight into potential host genetic influences on vaginal microbiome composition and can guide larger longitudinal studies, with genetic and functional comparison across microbiome sites within individuals and across populations.

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Intracellular Staphylococcus aureus Perturbs the Host Cell Ca2+ Homeostasis To Promote Cell Death

mBio ◽

10.1128/mbio.02250-20 ◽

2020 ◽

Vol 11 (6) ◽

pp. e02250-20

Author(s):

Kathrin Stelzner ◽

Ann-Cathrin Winkler ◽

Chunguang Liang ◽

Aziza Boyny ◽

Carsten P. Ade ◽

...

Keyword(s):

Staphylococcus Aureus ◽

Cell Death ◽

Host Cell ◽

Intracellular Bacterium ◽

Tissue Destruction ◽

Content Type ◽

Host Cell Death ◽

Genome Wide ◽

A Genome ◽

Spread Of Infection

ABSTRACTThe opportunistic human pathogen Staphylococcus aureus causes serious infectious diseases that range from superficial skin and soft tissue infections to necrotizing pneumonia and sepsis. While classically regarded as an extracellular pathogen, S. aureus is able to invade and survive within human cells. Host cell exit is associated with cell death, tissue destruction, and the spread of infection. The exact molecular mechanism employed by S. aureus to escape the host cell is still unclear. In this study, we performed a genome-wide small hairpin RNA (shRNA) screen and identified the calcium signaling pathway as being involved in intracellular infection. S. aureus induced a massive cytosolic Ca2+ increase in epithelial host cells after invasion and intracellular replication of the pathogen. This was paralleled by a decrease in endoplasmic reticulum Ca2+ concentration. Additionally, calcium ions from the extracellular space contributed to the cytosolic Ca2+ increase. As a consequence, we observed that the cytoplasmic Ca2+ rise led to an increase in mitochondrial Ca2+ concentration, the activation of calpains and caspases, and eventually to cell lysis of S. aureus-infected cells. Our study therefore suggests that intracellular S. aureus disturbs the host cell Ca2+ homeostasis and induces cytoplasmic Ca2+ overload, which results in both apoptotic and necrotic cell death in parallel or succession.IMPORTANCE Despite being regarded as an extracellular bacterium, the pathogen Staphylococcus aureus can invade and survive within human cells. The intracellular niche is considered a hideout from the host immune system and antibiotic treatment and allows bacterial proliferation. Subsequently, the intracellular bacterium induces host cell death, which may facilitate the spread of infection and tissue destruction. So far, host cell factors exploited by intracellular S. aureus to promote cell death are only poorly characterized. We performed a genome-wide screen and found the calcium signaling pathway to play a role in S. aureus invasion and cytotoxicity. The intracellular bacterium induces a cytoplasmic and mitochondrial Ca2+ overload, which results in host cell death. Thus, this study first showed how an intracellular bacterium perturbs the host cell Ca2+ homeostasis.

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A Clustering Approach for Motif Discovery in ChIP-Seq Dataset

Entropy ◽

10.3390/e21080802 ◽

2019 ◽

Vol 21 (8) ◽

pp. 802

Author(s):

Chun-xiao Sun ◽

Yu Yang ◽

Hua Wang ◽

Wen-hu Wang

Keyword(s):

Dna Sequences ◽

Motif Discovery ◽

Simulated Data ◽

Data Set ◽

Genome Wide ◽

A Genome ◽

Wide Scale ◽

Clustering Approach ◽

Ap Clustering ◽

Generation Sequencing

Chromatin immunoprecipitation combined with next-generation sequencing (ChIP-Seq) technology has enabled the identification of transcription factor binding sites (TFBSs) on a genome-wide scale. To effectively and efficiently discover TFBSs in the thousand or more DNA sequences generated by a ChIP-Seq data set, we propose a new algorithm named AP-ChIP. First, we set two thresholds based on probabilistic analysis to construct and further filter the cluster subsets. Then, we use Affinity Propagation (AP) clustering on the candidate cluster subsets to find the potential motifs. Experimental results on simulated data show that the AP-ChIP algorithm is able to make an almost accurate prediction of TFBSs in a reasonable time. Also, the validity of the AP-ChIP algorithm is tested on a real ChIP-Seq data set.

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