Keyword search (4,163 papers available)

"Transcriptomics" Keyword-tagged Publications:

Title Authors PubMed ID
1 A Bacteroides synthetic biology toolkit to build an in vivo malabsorption biosensor McCallum G; Burckhardt JC; He J; Hong A; Potvin-Trottier L; Tropini C; 41610848
BIOLOGY
2 An examination of the quinic acid utilization genes in Aspergillus niger reveals the involvement of two pH-dependent permeases Sgro M; Reid ID; Arentshorst M; Ram AFJ; Tsang A; 40853219
GENOMICS
3 em Candida albicans /em : a historical overview of investigations into an important human pathogen Shrivastava M; Whiteway M; 40522159
BIOLOGY
4 Transcriptomics identify the triggering of citrate export as the key event caused by manganese deficiency in Aspergillus niger Fekete E; Bíró V; Márton A; Bakondi-Kovács I; Sándor E; Kovács B; Geoffrion N; Tsang A; Kubicek CP; Karaffa L; 39377610
CSFG
5 Functional analysis of the protocatechuate branch of the β-ketoadipate pathway in Aspergillus niger Sgro M; Chow N; Olyaei F; Arentshorst M; Geoffrion N; Ram AFJ; Powlowski J; Tsang A; 37399977
BIOLOGY
6 Identification of Genes Involved in the Degradation of Lignocellulose Using Comparative Transcriptomics Gruninger RJ; Tsang A; McAllister TA; 37149538
CSFG
7 An Evolutionarily Conserved Transcriptional Activator-Repressor Module Controls Expression of Genes for D-Galacturonic Acid Utilization in Aspergillus niger. Niu J, Alazi E, Reid ID, Arentshorst M, Punt PJ, Visser J, Tsang A, Ram AF 28049705
CSFG
8 Identification of Genes Involved in the Degradation of Lignocellulose Using Comparative Transcriptomics. Gruninger RJ, Reid I, Forster RJ, Tsang A, McAllister TA 28417376
CSFG
9 Introduction: Overview of Fungal Genomics. de Vries RP, Grigoriev IV, Tsang A 29876804
CSFG

 

Title:Identification of Genes Involved in the Degradation of Lignocellulose Using Comparative Transcriptomics.
Authors:Gruninger RJReid IForster RJTsang AMcAllister TA
Link:https://www.ncbi.nlm.nih.gov/pubmed/28417376?dopt=Abstract
DOI:10.1007/978-1-4939-6899-2_21
Publication:Methods in molecular biology (Clifton, N.J.)
Keywords:Carbohydrate active enzymeFungiNeocallimastigomycotaRNA-SeqTranscriptomics
PMID:28417376 Category:Methods Mol Biol Date Added:2019-06-07
Dept Affiliation: CSFG
1 Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, 5403 1st Ave. South, Lethbridge, AB, Canada, T1J 4B1. robert.gruninger@agr.gc.ca.
2 Centre for Structural and Functional Genomics, Concordia University, Montreal, QC, Canada.
3 Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, 5403 1st Ave. South, Lethbridge, AB, Canada, T1J 4B1.

Description:

Identification of Genes Involved in the Degradation of Lignocellulose Using Comparative Transcriptomics.

Methods Mol Biol. 2017;1588:279-298

Authors: Gruninger RJ, Reid I, Forster RJ, Tsang A, McAllister TA

Abstract

Lignocellulosic biomass represents an abundant, renewable resource that can be used to produce biofuels, low-cost livestock feed, and high-value chemicals. The potential of this resource has led to intensive research efforts to develop cost effective methods to breakdown lignocellulose. The efficiency with which the anaerobic fungi (phylum Neocallimastigomycota) degrade plant biomass is well recognized and in recent years has received renewed interest. Transcriptomics has been used to identify enzymes that are expressed by these fungi and are involved in the degradation of a range of lignocellulose feedstocks. The transcriptome is the entire complement of coding and noncoding RNA transcripts that are expressed by a cell under a particular set of conditions. Monitoring changes in gene expression can provide fundamental information about the biology of an organism. Here we outline a general methodology that will enable researchers to conduct comparative transcriptomic studies with the goal of identifying enzymes involved in the degradation of the plant cell wall. The method described here includes growth of fungal cultures, isolation and sequencing of RNA, and a basic description of data analysis for bioinformatic identification of differentially expressed transcripts.

PMID: 28417376 [PubMed - indexed for MEDLINE]





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