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Yeast Metabolic Engineering

Overview of attention for book
Cover of 'Yeast Metabolic Engineering'

Table of Contents

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    Book Overview
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    Chapter 1 An Overview on Selection Marker Genes for Transformation of Saccharomyces cerevisiae
  3. Altmetric Badge
    Chapter 2 Yeast Metabolic Engineering
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    Chapter 3 Tools for Genetic Engineering of the Yeast Hansenula polymorpha
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    Chapter 4 Molecular Tools and Protocols for Engineering the Acid-Tolerant Yeast Zygosaccharomyces bailii as a Potential Cell Factory
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    Chapter 5 Strains and Molecular Tools for Recombinant Protein Production in Pichia pastoris
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    Chapter 6 Methods for Efficient High-Throughput Screening of Protein Expression in Recombinant Pichia pastoris Strains
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    Chapter 7 Synthetic RNA Switches for Yeast Metabolic Engineering: Screening Recombinant Enzyme Libraries
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    Chapter 8 Generation of Arming Yeasts with Active Proteins and Peptides via Cell Surface Display System: Cell Surface Engineering, Bio-arming Technology
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    Chapter 9 Genetic Engineering of Industrial Saccharomyces cerevisiae Strains Using a Selection/Counter-selection Approach
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    Chapter 10 Evolutionary Engineering of Yeast
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    Chapter 11 Yeast Metabolic Engineering
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    Chapter 12 Yeast Metabolomics: Sample Preparation for a GC/MS-Based Analysis
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    Chapter 13 13 C-Based Metabolic Flux Analysis in Yeast: The Pichia pastoris Case
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    Chapter 14 Pathway Activity Profiling (PAPi): A Tool for Metabolic Pathway Analysis
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    Chapter 15 QTL Mapping by Pooled-Segregant Whole-Genome Sequencing in Yeast.
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    Chapter 16 Genome-scale metabolic models of yeast, methods for their reconstruction, and other applications.
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    Chapter 17 Model-Guided Identification of Gene Deletion Targets for Metabolic Engineering in Saccharomyces cerevisiae
  19. Altmetric Badge
    Chapter 18 Patents: a tool to bring innovation from the lab bench to the marketplace.
  20. Altmetric Badge
    Chapter 19 ERRATUM: Strains and Molecular Tools for Recombinant Protein Production in Pichia pastoris
Attention for Chapter 15: QTL Mapping by Pooled-Segregant Whole-Genome Sequencing in Yeast.
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Chapter title
QTL Mapping by Pooled-Segregant Whole-Genome Sequencing in Yeast.
Chapter number 15
Book title
Yeast Metabolic Engineering
Published in
Methods in molecular biology, January 2014
DOI 10.1007/978-1-4939-0563-8_15
Pubmed ID
Book ISBNs
978-1-4939-0562-1, 978-1-4939-0563-8
Authors

Thiago M Pais, María R Foulquié-Moreno, Johan M Thevelein, Thiago M. Pais, María R. Foulquié-Moreno, Johan M. Thevelein

Abstract

Quantitative trait locus (QTL) mapping by pooled-segregant whole-genome sequencing in yeast is a robust methodology for the simultaneous identification of superior genes involved in polygenic traits (e.g., high ethanol tolerance). By crossing two haploid strains with opposite phenotypes, being one of interest, the resulting diploid is sporulated, the meiotic segregants phenotyped, and a pool of selected segregants with the phenotype of interest assembled. The genotyping by pooled-segregant sequencing constitutes a fast and reliable methodology to map all QTL defining the trait of interest. The QTLs can be further analyzed by reciprocal hemizygosity analysis to identify the causative superior alleles that can subsequently be used for yeast strain improvement by targeted genetic engineering.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 23%
Student > Master 8 21%
Researcher 7 18%
Student > Bachelor 5 13%
Student > Doctoral Student 4 10%
Other 1 3%
Unknown 5 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 36%
Agricultural and Biological Sciences 14 36%
Computer Science 2 5%
Chemical Engineering 1 3%
Chemistry 1 3%
Other 1 3%
Unknown 6 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 April 2014.
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#20,879,072
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Outputs from Methods in molecular biology
#10,161
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#268,669
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Outputs of similar age from Methods in molecular biology
#411
of 587 outputs
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