scholarly journals Fungal Genomic Resources for Strain Identification and Diversity Analysis of 1900 Fungal Species

2021 ◽  
Vol 7 (4) ◽  
pp. 288
Author(s):  
Mir Asif Iquebal ◽  
Sarika Jaiswal ◽  
Vineet Kumar Mishra ◽  
Rahul Singh Jasrotia ◽  
Ulavappa B. Angadi ◽  
...  
Keyword(s):  
Genome Sequence ◽  
In Silico ◽  
Sequence Data ◽  
Fungal Species ◽  
Genomic Research ◽  
Whole Genome Sequence ◽  
Strain Identification ◽  
Diversity Analysis ◽  
Whole Genome

Identification and diversity analysis of fungi is greatly challenging. Though internal transcribed spacer (ITS), region-based DNA fingerprinting works as a “gold standard” for most of the fungal species group, it cannot differentiate between all the groups and cryptic species. Therefore, it is of paramount importance to find an alternative approach for strain differentiation. Availability of whole genome sequence data of nearly 2000 fungal species are a promising solution to such requirement. We present whole genome sequence-based world’s largest microsatellite database, FungSatDB having >19M loci obtained from >1900 fungal species/strains using >4000 assemblies across globe. Genotyping efficacy of FungSatDB has been evaluated by both in-silico and in-vitro PCR. By in silico PCR, 66 strains of 8 countries representing four continents were successfully differentiated. Genotyping efficacy was also evaluated by in vitro PCR in four fungal species. This approach overcomes limitation of ITS in species, strain signature, and diversity analysis. It can accelerate fungal genomic research endeavors in agriculture, industrial, and environmental management.

scholarly journals Clostridium botulinum Group II Isolate Phylogenomic Profiling Using Whole-Genome Sequence Data

2015 ◽  
Vol 81 (17) ◽  
pp. 5938-5948 ◽  
Author(s):  
K. A. Weedmark ◽  
P. Mabon ◽  
K. L. Hayden ◽  
D. Lambert ◽  
G. Van Domselaar ◽  
...  
Keyword(s):  
Genome Sequence ◽  
In Silico ◽  
Clostridium Botulinum ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Snp Analysis ◽  
Whole Genome ◽  
Content Type ◽  
Genome Sequence Data ◽  
Group Ii

ABSTRACTClostridium botulinumgroup II isolates (n= 163) from different geographic regions, outbreaks, and neurotoxin types and subtypes were characterizedin silicousing whole-genome sequence data. Two clusters representing a variety of botulinum neurotoxin (BoNT) types and subtypes were identified by multilocus sequence typing (MLST) and core single nucleotide polymorphism (SNP) analysis. While one cluster included BoNT/B4/F6/E9 and nontoxigenic members, the other comprised a wide variety of different BoNT/E subtype isolates and a nontoxigenic strain.In silicoMLST and core SNP methods were consistent in terms of clade-level isolate classification; however, core SNP analysis showed higher resolution capability. Furthermore, core SNP analysis correctly distinguished isolates by outbreak and location. This study illustrated the utility of next-generation sequence-based typing approaches for isolate characterization and source attribution and identified discrete SNP loci and MLST alleles for isolate comparison.

scholarly journals Genomic insights into the host specific adaptation of the Pneumocystis genus

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Ousmane H. Cissé ◽  
Liang Ma ◽  
John P. Dekker ◽  
Pavel P. Khil ◽  
Jung-Ho Youn ◽  
...  
Keyword(s):  
Host Specificity ◽  
Genome Sequence ◽  
Molecular Basis ◽  
Sequence Data ◽  
Host Adaptation ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Specific Adaptation ◽  
Genetic Features

AbstractPneumocystis jirovecii, the fungal agent of human Pneumocystis pneumonia, is closely related to macaque Pneumocystis. Little is known about other Pneumocystis species in distantly related mammals, none of which are capable of establishing infection in humans. The molecular basis of host specificity in Pneumocystis remains unknown as experiments are limited due to an inability to culture any species in vitro. To explore Pneumocystis evolutionary adaptations, we have sequenced the genomes of species infecting macaques, rabbits, dogs and rats and compared them to available genomes of species infecting humans, mice and rats. Complete whole genome sequence data enables analysis and robust phylogeny, identification of important genetic features of the host adaptation, and estimation of speciation timing relative to the rise of their mammalian hosts. Our data reveals insights into the evolution of P. jirovecii, the sole member of the genus able to infect humans.

TIGER: inferring DNA replication timing from whole-genome sequence data

2021 ◽  
Author(s):  
Amnon Koren ◽  
Dashiell J Massey ◽  
Alexa N Bracci
Keyword(s):  
Dna Replication ◽  
Genome Sequence ◽  
Genomic Dna ◽  
Sequence Data ◽  
Replication Timing ◽  
Whole Genome Sequence ◽  
Supplementary Information ◽  
Whole Genome ◽  
Genome Sequence Data ◽  
Dna Replication Timing

Abstract Motivation Genomic DNA replicates according to a reproducible spatiotemporal program, with some loci replicating early in S phase while others replicate late. Despite being a central cellular process, DNA replication timing studies have been limited in scale due to technical challenges. Results We present TIGER (Timing Inferred from Genome Replication), a computational approach for extracting DNA replication timing information from whole genome sequence data obtained from proliferating cell samples. The presence of replicating cells in a biological specimen leads to non-uniform representation of genomic DNA that depends on the timing of replication of different genomic loci. Replication dynamics can hence be observed in genome sequence data by analyzing DNA copy number along chromosomes while accounting for other sources of sequence coverage variation. TIGER is applicable to any species with a contiguous genome assembly and rivals the quality of experimental measurements of DNA replication timing. It provides a straightforward approach for measuring replication timing and can readily be applied at scale. Availability and Implementation TIGER is available at https://github.com/TheKorenLab/TIGER. Supplementary information Supplementary data are available at Bioinformatics online

scholarly journals Whole genome sequence data of Mycobacterium tuberculosis XDR strain, isolated from patient in Kazakhstan

Data in Brief ◽  
2020 ◽  
Vol 33 ◽  
pp. 106416
Author(s):  
Asset Daniyarov ◽  
Askhat Molkenov ◽  
Saule Rakhimova ◽  
Ainur Akhmetova ◽  
Zhannur Nurkina ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Genome Sequence ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Data

scholarly journals Elucidating the genetic basis of an oligogenic birth defect using whole genome sequence data in a non-model organism, Bubalus bubalis

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Lynsey K. Whitacre ◽  
Jesse L. Hoff ◽  
Robert D. Schnabel ◽  
Sara Albarella ◽  
Francesca Ciotola ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Birth Defect ◽  
Genetic Basis ◽  
Sequence Data ◽  
Model Organism ◽  
Bubalus Bubalis ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Data
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