عنوان

BiomeSeq:

شماره

TLpq2447316685

زبان متن نوشتاري يا گفتاري و مانند آن

انگلیسی

عنوان اصلي

BiomeSeq:

نام عام مواد

[Thesis]

نام نخستين پديدآور

Mulholland, Kelly Ann

عنوان اصلي به قلم نويسنده ديگر

A Quantitative Approach for the Analysis of Animal Microbiomes and Its Application in Characterizing the Microbial Ecology of Avian Species

نام ساير پديدآوران

Keeler, Calvin L.

نام ناشر، پخش کننده و غيره

University of Delaware

تاریخ نشرو بخش و غیره

2020

نام خاص و کميت اثر

255

جزئيات پايان نامه و نوع درجه آن

Ph.D.

کسي که مدرک را اعطا کرده

University of Delaware

امتياز متن

2020

متن يادداشت

Microbiomes are complex communities of microorganisms (including bacteria, eukaryotic viruses, fungi and bacteriophage) that inhabit a particular environment in animals and contribute to essential biological functions. The microorganisms within these environments interact with the host and each other in either symbiosis or dysbiosis, depending on the condition of the host as well as external factors. Disturbances within a microbiome may result in metabolic disturbances or disease in the host. The advancement of next generation sequencing methodologies has given rise to an increase in studies attempting to examine the microbial communities existing in a variety of animals. Readily accessible and cost-effective sequencing methodologies, as well as a number of user-friendly bioinformatics analysis software and databases for 16S rRNA sequencing data, provide the standard culture-independent approach for bacterial microbiome analysis. However, this approach cannot be extended to the characterization of eukaryotic viruses, bacteriophage and fungi. Therefore, elucidating the complete microbiome requires a new approach. Herein, we present BiomeSeq, a computational tool developed for the characterization of complete animal microbiomes using metagenomic sequencing data. BiomeSeq, and its accompanying databases, addresses the constraints of current computational tools by providing a comprehensive workflow that accurately identifies and quantifies each major component of the microbiome. BiomeSeq provides taxonomic information for each detected microorganism as well as normalized abundance, relative abundance, genome coverage and sample diversity values. The performance of this tool was successfully evaluated using both simulated and clinical samples. BiomeSeq is available as a software package and as an open-source and user-friendly container, allowing users to easily download, install and use the program with a few simple commands. The versatility of BiomeSeq, such as customizable parameters and accepting custom databases, allow this tool to facilitate a variety of unique investigations. BiomeSeq was utilized to detect and quantify microbial abundance and diversity of several avian microbiomes under various conditions. In one study, the respiratory tract of a healthy poultry broiler flock was examined at weekly intervals throughout its grow-out cycle from hatching to processing. As expected, the complexity and diversity of the viral community increased as the flock aged, while the timing and presence of several viral elements was consistent with the management practices of commercial broiler flocks. Additionally, correlations between bacteria and bacteriophage families were investigated and several highly positive correlations were identified. In a second study, the microbial ecology of the respiratory tract of a broiler flock clinically diagnosed with respiratory disease complex and a healthy broiler flock were compared. Changes in the composition and diversity of the viral, bacterial, and bacteriophage microbiomes were observed which were consistent with the complex etiology of this disease. In a final study, the ability of BiomeSeq to characterize a variety of microbiomes in different host species was demonstrated. The tool was successful in identifying microbial communities inhabiting three unique microbial niches, including the trachea, choanal cleft and cloaca in a healthy turkey flock.

موضوع مستند نشده

Animal sciences

موضوع مستند نشده

Bioinformatics

موضوع مستند نشده

Virology

مستند نام اشخاص تاييد نشده

Keeler, Calvin L.

مستند نام اشخاص تاييد نشده

Mulholland, Kelly Ann

نام الکترونيکي

فرمت انتشار

p

نوع ماده

[Thesis]

کد کاربرگه

276903

سطح دسترسي

a

تكميل شده

Y