scholarly journals Genome rearrangements and megaplasmid loss in the filamentous bacteriumKitasatospora viridifaciensare associated with protoplast formation and regeneration

2019 ◽  
Author(s):  
Karina Ramijan ◽  
Zheren Zhang ◽  
Gilles P. van Wezel ◽  
D. Claessen
Keyword(s):  
Genomic Sequence ◽  
Sequence Data ◽  
Morphological Diversity ◽  
Protoplast Formation ◽  
Genetic Changes ◽  
Sequence Elements ◽  
The Right ◽  
Accession Code ◽  
Insertion Sequence Elements ◽  
Replicative Transposition

AbstractFilamentous Actinobacteria are multicellular bacteria with linear replicons.Kitasatospora viridifaciensDSM 40239 contains a linear 7.8 Mb chromosome and an autonomously replicating plasmid KVP1 of 1.7 Mb. Here we show that lysozyme-induced protoplast formation of the multinucleated mycelium ofK. viridifaciensdrives morphological diversity. Characterization and sequencing of an individual revertant colony that had lost the ability to differentiate revealed that the strain had not only lost most of KVP1 but also carried lesions in the right arm of the chromosome. Strikingly, the lesion sites were preceded by insertion sequence elements, suggesting that the rearrangements may have been caused by replicative transposition and homologous recombination between both replicons. These data indicate that protoplast formation is a stressful process that can lead to profound genetic changes.RepositoriesGenomic sequence data for strain B3.1 has been deposited in the NCBI SRA database under accession code SAMN11514356.

scholarly journals Comparative Sequence of Human and Mouse BAC Clones from the mnd2 Region of Chromosome 2p13

1999 ◽  
Vol 9 (1) ◽  
pp. 53-61 ◽  
Author(s):  
Wonhee Jang ◽  
Axin Hua ◽  
Sandra V. Spilson ◽  
Webb Miller ◽  
Bruce A. Roe ◽  
...  
Keyword(s):  
Genomic Dna ◽  
Genomic Sequence ◽  
Sequence Data ◽  
Lysyl Oxidase ◽  
Neuromuscular Disorder ◽  
Bac Clone ◽  
Link Type ◽  
Sequence Elements ◽  
Human And Mouse ◽  
Mouse Genomic

The mnd2 mutation on mouse chromosome 6 produces a progressive neuromuscular disorder. To determine the gene content of the 400-kb mnd2 nonrecombinant region, we sequenced 108 kb of mouse genomic DNA and 92 kb of human genomic sequence from the corresponding region of chromosome 2p13.3. Three genes with the indicated sizes and intergenic distances were identified:D6Mm5e (⩾81 kb)–787 bp–DOK (2 kb)–845 bp–LOR2 (⩾6 kb). D6Mm5e is expressed in many tissues at very low abundance and the predicted 526-residue protein contains no known functional domains. DOK encodes the p62dok rasGAP binding protein involved in signal transduction. LOR2 encodes a novel lysyl oxidase-related protein of 757 amino acid residues. We describe a simple search protocol for identification of conserved internal exons in genomic sequence. Evolutionary conservation proved to be a useful criterion for distinguishing between authentic exons and artifactual products obtained by exon amplification, RT–PCR, and 5′ RACE. Conserved noncoding sequence elements longer than 80 bp with ⩾75% nucleotide sequence identity comprise ∼1% of the genomic sequence in this region. Comparative analysis of this human and mouse genomic DNA sequence was an efficient method for gene identification and is independent of developmental stage or quantitative level of gene expression.[The sequence data described in this paper have been submitted to the GenBank data library under the following accession numbers: AC003061, mouse BAC clone 245c12; AC003065, human BAC clone h173(E10); AF053368, mouse Lor2 cDNA; AF084363, 108-kb contig from mouse BAC 245c12; AF084364, mouse D6Mm5ecDNA.]

PoGB-Pred: Prediction of Antifreeze Proteins Sequences using Amino Acid Composition with Feature Selection followed by a Sequential based Ensemble Approach

2020 ◽  
Vol 15 ◽  
Author(s):  
Affan Alim ◽  
Abdul Rafay ◽  
Imran Naseem
Keyword(s):  
Amino Acid ◽  
Dimension Reduction ◽  
Protein Identification ◽  
Cold Water ◽  
Genomic Sequence ◽  
Sequence Data ◽  
Antifreeze Proteins ◽  
Building Blocks ◽  
Gradient Boosting ◽  
Proposed Model

Background: Proteins contribute significantly in every task of cellular life. Their functions encompass the building and repairing of tissues in human bodies and other organisms. Hence they are the building blocks of bones, muscles, cartilage, skin, and blood. Similarly, antifreeze proteins are of prime significance for organisms that live in very cold areas. With the help of these proteins, the cold water organisms can survive below zero temperature and resist the water crystallization process which may cause the rupture in the internal cells and tissues. AFP’s have attracted attention and interest in food industries and cryopreservation. Objective: With the increase in the availability of genomic sequence data of protein, an automated and sophisticated tool for AFP recognition and identification is in dire need. The sequence and structures of AFP are highly distinct, therefore, most of the proposed methods fail to show promising results on different structures. A consolidated method is proposed to produce the competitive performance on highly distinct AFP structure. Methods: In this study, we propose to use machine learning-based algorithms Principal Component Analysis (PCA) followed by Gradient Boosting (GB) for antifreeze protein identification. To analyze the performance and validation of the proposed model, various combinations of two segments composition of amino acid and dipeptide are used. PCA, in particular, is proposed to dimension reduction and high variance retaining of data which is followed by an ensemble method named gradient boosting for modelling and classification. Results: The proposed method obtained the superfluous performance on PDB, Pfam and Uniprot dataset as compared with the RAFP-Pred method. In experiment-3, by utilizing only 150 PCA components a high accuracy of 89.63 was achieved which is superior to the 87.41 utilizing 300 significant features reported for the RAFP-Pred method. Experiment-2 is conducted using two different dataset such that non-AFP from the PISCES server and AFPs from Protein data bank. In this experiment-2, our proposed method attained high sensitivity of 79.16 which is 12.50 better than state-of-the-art the RAFP-pred method. Conclusion: AFPs have a common function with distinct structure. Therefore, the development of a single model for different sequences often fails to AFPs. A robust results have been shown by our proposed model on the diversity of training and testing dataset. The results of the proposed model outperformed compared to the previous AFPs prediction method such as RAFP-Pred. Our model consists of PCA for dimension reduction followed by gradient boosting for classification. Due to simplicity, scalability properties and high performance result our model can be easily extended for analyzing the proteomic and genomic dataset.

scholarly journals Special Issue: Genetic Basis of Phenotypic Variation in Drosophila and Other Insects

Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1212
Author(s):  
J. Spencer Johnston ◽  
Carl E. Hjelmen
Keyword(s):  
Next Generation Sequencing ◽  
Genetic Basis ◽  
Genomic Sequence ◽  
Sequence Data ◽  
Complete Genomic Sequence ◽  
Special Issue ◽  
Model Species ◽  
Road Map ◽  
Generation Sequencing ◽  
Complete Genomic

Next-generation sequencing provides a nearly complete genomic sequence for model and non-model species alike; however, this wealth of sequence data includes no road map [...]

scholarly journals Genome sequences of human cytomegalovirus strain TB40/E variants propagated in fibroblasts and epithelial cells

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Ahmed Al Qaffas ◽  
Salvatore Camiolo ◽  
Mai Vo ◽  
Alexis Aguiar ◽  
Amine Ourahmane ◽  
...  
Keyword(s):  
Epithelial Cells ◽  
Human Cytomegalovirus ◽  
Viral Entry ◽  
Sequence Data ◽  
Laboratory Strain ◽  
Serial Passage ◽  
Wild Type Virus ◽  
Protein Coding ◽  
Genetic Changes ◽  
Long Read

AbstractThe advent of whole genome sequencing has revealed that common laboratory strains of human cytomegalovirus (HCMV) have major genetic deficiencies resulting from serial passage in fibroblasts. In particular, tropism for epithelial and endothelial cells is lost due to mutations disrupting genes UL128, UL130, or UL131A, which encode subunits of a virion-associated pentameric complex (PC) important for viral entry into these cells but not for entry into fibroblasts. The endothelial cell-adapted strain TB40/E has a relatively intact genome and has emerged as a laboratory strain that closely resembles wild-type virus. However, several heterogeneous TB40/E stocks and cloned variants exist that display a range of sequence and tropism properties. Here, we report the use of PacBio sequencing to elucidate the genetic changes that occurred, both at the consensus level and within subpopulations, upon passaging a TB40/E stock on ARPE-19 epithelial cells. The long-read data also facilitated examination of the linkage between mutations. Consistent with inefficient ARPE-19 cell entry, at least 83% of viral genomes present before adaptation contained changes impacting PC subunits. In contrast, and consistent with the importance of the PC for entry into endothelial and epithelial cells, genomes after adaptation lacked these or additional mutations impacting PC subunits. The sequence data also revealed six single noncoding substitutions in the inverted repeat regions, single nonsynonymous substitutions in genes UL26, UL69, US28, and UL122, and a frameshift truncating gene UL141. Among the changes affecting protein-coding regions, only the one in UL122 was strongly selected. This change, resulting in a D390H substitution in the encoded protein IE2, has been previously implicated in rendering another viral protein, UL84, essential for viral replication in fibroblasts. This finding suggests that IE2, and perhaps its interactions with UL84, have important functions unique to HCMV replication in epithelial cells.

scholarly journals Identification and characterization of Fep15, a new selenocysteine-containing member of the Sep15 protein family

2006 ◽  
Vol 394 (3) ◽  
pp. 575-579 ◽  
Author(s):  
Sergey V. Novoselov ◽  
Deame Hua ◽  
Alexey V. Lobanov ◽  
Vadim N. Gladyshev
Keyword(s):  
Mammalian Cells ◽  
Insertion Sequence ◽  
Phylogenetic Analyses ◽  
Dependent Manner ◽  
Putative Active Site ◽  
A Genome ◽  
Sequence Elements ◽  
Identification And Characterization ◽  
Insertion Sequence Elements

Sec (selenocysteine) is a rare amino acid in proteins. It is co-translationally inserted into proteins at UGA codons with the help of SECIS (Sec insertion sequence) elements. A full set of selenoproteins within a genome, known as the selenoproteome, is highly variable in different organisms. However, most of the known eukaryotic selenoproteins are represented in the mammalian selenoproteome. In addition, many of these selenoproteins have cysteine orthologues. Here, we describe a new selenoprotein, designated Fep15, which is distantly related to members of the 15 kDa selenoprotein (Sep15) family. Fep15 is absent in mammals, can be detected only in fish and is present in these organisms only in the selenoprotein form. In contrast with other members of the Sep15 family, which contain a putative active site composed of Sec and cysteine, Fep15 has only Sec. When transiently expressed in mammalian cells, Fep15 incorporated Sec in an SECIS- and SBP2 (SECIS-binding protein 2)-dependent manner and was targeted to the endoplasmic reticulum by its N-terminal signal peptide. Phylogenetic analyses of Sep15 family members suggest that Fep15 evolved by gene duplication.

Integrating genomics into the taxonomy and systematics of the Bacteria and Archaea

2014 ◽  
Vol 64 (Pt_2) ◽  
pp. 316-324 ◽  
Author(s):  
Jongsik Chun ◽  
Fred A. Rainey
Keyword(s):  
Genomic Sequence ◽  
Sequence Data ◽  
Original Research ◽  
Rrna Gene ◽  
New Taxon ◽  
Genome Sequences ◽  
Microbial World ◽  
Content Type ◽  
Link Type ◽  
Type Strains

The polyphasic approach used today in the taxonomy and systematics of the Bacteria and Archaea includes the use of phenotypic, chemotaxonomic and genotypic data. The use of 16S rRNA gene sequence data has revolutionized our understanding of the microbial world and led to a rapid increase in the number of descriptions of novel taxa, especially at the species level. It has allowed in many cases for the demarcation of taxa into distinct species, but its limitations in a number of groups have resulted in the continued use of DNA–DNA hybridization. As technology has improved, next-generation sequencing (NGS) has provided a rapid and cost-effective approach to obtaining whole-genome sequences of microbial strains. Although some 12 000 bacterial or archaeal genome sequences are available for comparison, only 1725 of these are of actual type strains, limiting the use of genomic data in comparative taxonomic studies when there are nearly 11 000 type strains. Efforts to obtain complete genome sequences of all type strains are critical to the future of microbial systematics. The incorporation of genomics into the taxonomy and systematics of the Bacteria and Archaea coupled with computational advances will boost the credibility of taxonomy in the genomic era. This special issue of International Journal of Systematic and Evolutionary Microbiology contains both original research and review articles covering the use of genomic sequence data in microbial taxonomy and systematics. It includes contributions on specific taxa as well as outlines of approaches for incorporating genomics into new strain isolation to new taxon description workflows.

scholarly journals Comparative Species Divergence across Eight Triplets of Spiny Lizards (Sceloporus) Using Genomic Sequence Data

2013 ◽  
Vol 5 (12) ◽  
pp. 2410-2419 ◽  
Author(s):  
Adam D. Leaché ◽  
Rebecca B. Harris ◽  
Max E. Maliska ◽  
Charles W. Linkem
Keyword(s):  
Genomic Sequence ◽  
Sequence Data ◽  
Species Divergence

Predicting Chromosome Flexibility from the Genomic Sequence Based on Deep Learning Neural Networks

2021 ◽  
Vol 16 ◽  
Author(s):  
Jinghao Peng ◽  
Jiajie Peng ◽  
Haiyin Piao ◽  
Zhang Luo ◽  
Kelin Xia ◽  
...  
Keyword(s):  
Deep Learning ◽  
High Performance ◽  
Genomic Sequence ◽  
Sequence Data ◽  
Function Analysis ◽  
Double Helix ◽  
Gm12878 Cell ◽  
Genomic Sequence Analysis ◽  
And Function ◽  
Nuclear Processes

Background: The open and accessible regions of the chromosome are more likely to be bound by transcription factors which are important for nuclear processes and biological functions. Studying the change of chromosome flexibility can help to discover and analyze disease markers and improve the efficiency of clinical diagnosis. Current methods for predicting chromosome flexibility based on Hi-C data include the flexibility-rigidity index (FRI) and the Gaussian network model (GNM), which have been proposed to characterize chromosome flexibility. However, these methods require the chromosome structure data based on 3D biological experiments, which is time-consuming and expensive. Objective: Generally, the folding and curling of the double helix sequence of DNA have a great impact on chromosome flexibility and function. Motivated by the success of genomic sequence analysis in biomolecular function analysis, we hope to propose a method to predict chromosome flexibility only based on genomic sequence data. Method: We propose a new method (named "DeepCFP") using deep learning models to predict chromosome flexibility based on only genomic sequence features. The model has been tested in the GM12878 cell line. Results: The maximum accuracy of our model has reached 91%. The performance of DeepCFP is close to FRI and GNM. Conclusion: The DeepCFP can achieve high performance only based on genomic sequence.

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