↓ Skip to main content

Wheat Rust Diseases

Overview of attention for book
Cover of 'Wheat Rust Diseases'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Wheat Rust Surveillance: Field Disease Scoring and Sample Collection for Phenotyping and Molecular Genotyping
  3. Altmetric Badge
    Chapter 2 Field Pathogenomics: An Advanced Tool for Wheat Rust Surveillance
  4. Altmetric Badge
    Chapter 3 Race Typing of Puccinia striiformis on Wheat
  5. Altmetric Badge
    Chapter 4 Assessment of Aggressiveness of Puccinia striiformis on Wheat
  6. Altmetric Badge
    Chapter 5 Extraction of High Molecular Weight DNA from Fungal Rust Spores for Long Read Sequencing
  7. Altmetric Badge
    Chapter 6 Microsatellite Genotyping of the Wheat Yellow Rust Pathogen Puccinia striiformis
  8. Altmetric Badge
    Chapter 7 Computational Methods for Predicting Effectors in Rust Pathogens
  9. Altmetric Badge
    Chapter 8 Protein–Protein Interaction Assays with Effector–GFP Fusions in Nicotiana benthamiana
  10. Altmetric Badge
    Chapter 9 Proteome Profiling by 2D–Liquid Chromatography Method for Wheat–Rust Interaction
  11. Altmetric Badge
    Chapter 10 Investigating Gene Function in Cereal Rust Fungi by Plant-Mediated Virus-Induced Gene Silencing
  12. Altmetric Badge
    Chapter 11 Apoplastic Sugar Extraction and Quantification from Wheat Leaves Infected with Biotrophic Fungi
  13. Altmetric Badge
    Chapter 12 Genetic Analysis of Resistance to Wheat Rusts
  14. Altmetric Badge
    Chapter 13 Advances in Identification and Mapping of Rust Resistance Genes in Wheat
  15. Altmetric Badge
    Chapter 14 Chromosome Engineering Techniques for Targeted Introgression of Rust Resistance from Wild Wheat Relatives
  16. Altmetric Badge
    Chapter 15 Applications of Genomic Selection in Breeding Wheat for Rust Resistance
  17. Altmetric Badge
    Chapter 16 Rapid Phenotyping Adult Plant Resistance to Stem Rust in Wheat Grown under Controlled Conditions
  18. Altmetric Badge
    Chapter 17 Generation of Loss-of-Function Mutants for Wheat Rust Disease Resistance Gene Cloning
  19. Altmetric Badge
    Chapter 18 Isolation of Wheat Genomic DNA for Gene Mapping and Cloning
  20. Altmetric Badge
    Chapter 19 MutRenSeq: A Method for Rapid Cloning of Plant Disease Resistance Genes
  21. Altmetric Badge
    Chapter 20 Rapid Gene Isolation Using MutChromSeq
  22. Altmetric Badge
    Chapter 21 Rapid Identification of Rust Resistance Genes Through Cultivar-Specific De Novo Chromosome Assemblies
  23. Altmetric Badge
    Chapter 22 BSMV-Induced Gene Silencing Assay for Functional Analysis of Wheat Rust Resistance
  24. Altmetric Badge
    Chapter 23 Yeast as a Heterologous System to Functionally Characterize a Multiple Rust Resistance Gene that Encodes a Hexose Transporter
  25. Altmetric Badge
    Chapter 24 Biocontrol Agents for Controlling Wheat Rust
Attention for Chapter 5: Extraction of High Molecular Weight DNA from Fungal Rust Spores for Long Read Sequencing
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
34 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Extraction of High Molecular Weight DNA from Fungal Rust Spores for Long Read Sequencing
Chapter number 5
Book title
Wheat Rust Diseases
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-7249-4_5
Pubmed ID
Book ISBNs
978-1-4939-7248-7, 978-1-4939-7249-4
Authors

Benjamin Schwessinger, John P. Rathjen

Abstract

Wheat rust fungi are complex organisms with a complete life cycle that involves two different host plants and five different spore types. During the asexual infection cycle on wheat, rusts produce massive amounts of dikaryotic urediniospores. These spores are dikaryotic (two nuclei) with each nucleus containing one haploid genome. This dikaryotic state is likely to contribute to their evolutionary success, making them some of the major wheat pathogens globally. Despite this, most published wheat rust genomes are highly fragmented and contain very little haplotype-specific sequence information. Current long-read sequencing technologies hold great promise to provide more contiguous and haplotype-phased genome assemblies. Long reads are able to span repetitive regions and phase structural differences between the haplomes. This increased genome resolution enables the identification of complex loci and the study of genome evolution beyond simple nucleotide polymorphisms. Long-read technologies require pure high molecular weight DNA as an input for sequencing. Here, we describe a DNA extraction protocol for rust spores that yields pure double-stranded DNA molecules with molecular weight of >50 kilo-base pairs (kbp). The isolated DNA is of sufficient purity for PacBio long-read sequencing, but may require additional purification for other sequencing technologies such as Nanopore and 10× Genomics.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users 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 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 24%
Other 4 12%
Researcher 4 12%
Student > Bachelor 3 9%
Student > Master 3 9%
Other 2 6%
Unknown 10 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 29%
Agricultural and Biological Sciences 10 29%
Business, Management and Accounting 1 3%
Psychology 1 3%
Neuroscience 1 3%
Other 2 6%
Unknown 9 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 08 May 2018.
All research outputs
#13,661,887
of 23,577,654 outputs
Outputs from Methods in molecular biology
#3,637
of 13,353 outputs
Outputs of similar age
#210,333
of 423,887 outputs
Outputs of similar age from Methods in molecular biology
#320
of 1,073 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,353 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 72% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 423,887 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,073 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.