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Legume Genomics

Overview of attention for book
Cover of 'Legume Genomics'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 The Model Legume Genomes
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    Chapter 2 Fluorescent In Situ Hybridization (FISH) on Pachytene Chromosomes as a Tool for Genome Characterization
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    Chapter 3 Targeted Mutagenesis for Functional Analysis of Gene Duplication in Legumes
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    Chapter 4 RNA-Seq for Transcriptome Analysis in Non-model Plants.
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    Chapter 5 Functional analysis of legume genome arrays.
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    Chapter 6 Genome-Wide Identification of MicroRNAs in Medicago truncatula by High-Throughput Sequencing
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    Chapter 7 Determining Abundance of MicroRNAs and Other Small RNAs in Legumes
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    Chapter 8 Forward Genetics Screening of Medicago truncatula Tnt1 Insertion Lines.
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    Chapter 9 Reverse Genetics in Medicago truncatula Using a TILLING Mutant Collection
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    Chapter 10 High-Throughput and Targeted Genotyping of Lotus japonicus LORE1 Insertion Mutants
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    Chapter 11 Legume Genomics
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    Chapter 12 Gene Silencing in Medicago truncatula Roots Using RNAi.
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    Chapter 13 Molecular Markers for Genetics and Plant Breeding: The MFLP Marker System and Its Application in Narrow-Leafed Lupin ( Lupinus angustifolius )
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    Chapter 14 Stable Transformation of Medicago truncatula cv. Jemalong for Gene Analysis Using Agrobacterium tumefaciens
  16. Altmetric Badge
    Chapter 15 Legume Genomics
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    Chapter 16 Subcellular Localization of Transiently Expressed Fluorescent Fusion Proteins
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    Chapter 17 Proteomics and the Analysis of Nodulation
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    Chapter 18 Phosphoproteomic Analysis of Peptides
  20. Altmetric Badge
    Chapter 19 Plant Metabolomics: From Experimental Design to Knowledge Extraction
Attention for Chapter 4: RNA-Seq for Transcriptome Analysis in Non-model Plants.
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

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Chapter title
RNA-Seq for Transcriptome Analysis in Non-model Plants.
Chapter number 4
Book title
Legume Genomics
Published in
Methods in molecular biology, January 2013
DOI 10.1007/978-1-62703-613-9_4
Pubmed ID
Book ISBNs
978-1-62703-612-2, 978-1-62703-613-9
Authors

Rohini Garg, Mukesh Jain, Garg, Rohini, Jain, Mukesh

Abstract

Sequencing of mRNA using next-generation sequencing (NGS) technologies (RNA-seq) has the potential to reveal unprecedented complexity of the transcriptomes. The transcriptome sequencing of an organism provides quick insights into the gene space, opportunity to isolate genes of interest, development of functional markers, quantitation of gene expression, and comparative genomic studies. Although becoming cheaper, transcriptome sequencing still remains an expensive endeavor. Further, the assembly of millions and billions of RNA-seq reads to construct the complete transcriptome poses great informatics challenges. Here, first we outline various important issues from experimental design to data analysis, including various strategies of transcriptome assembly, which need substantial consideration for a successful RNA-seq experiment. Further, we describe a method for using RNA-seq to characterize the transcriptome of a plant species, taking the example of a legume crop plant chickpea. Our aim is to provide a quick start guide to the nonexpert researchers for NGS-based transcriptome analysis.

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 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 2 2%
United Kingdom 1 1%
Slovenia 1 1%
Canada 1 1%
Unknown 80 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 21%
Researcher 17 20%
Student > Master 16 19%
Student > Bachelor 5 6%
Student > Postgraduate 5 6%
Other 12 14%
Unknown 12 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 47 55%
Biochemistry, Genetics and Molecular Biology 14 16%
Medicine and Dentistry 2 2%
Unspecified 1 1%
Environmental Science 1 1%
Other 1 1%
Unknown 19 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 06 September 2013.
All research outputs
#3,539,431
of 22,719,618 outputs
Outputs from Methods in molecular biology
#847
of 13,083 outputs
Outputs of similar age
#37,509
of 280,759 outputs
Outputs of similar age from Methods in molecular biology
#30
of 341 outputs
Altmetric has tracked 22,719,618 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,083 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 93% 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 280,759 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 341 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.