↓ Skip to main content

Next-generation transcriptome sequencing, SNP discovery and validation in four market classes of peanut, Arachis hypogaea L.

Overview of attention for article published in Molecular Genetics and Genomics, February 2015
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 (74th percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
39 Dimensions

Readers on

mendeley
55 Mendeley
citeulike
1 CiteULike
Title
Next-generation transcriptome sequencing, SNP discovery and validation in four market classes of peanut, Arachis hypogaea L.
Published in
Molecular Genetics and Genomics, February 2015
DOI 10.1007/s00438-014-0976-4
Pubmed ID
Authors

Ratan Chopra, Gloria Burow, Andrew Farmer, Joann Mudge, Charles E. Simpson, Thea A. Wilkins, Michael R. Baring, Naveen Puppala, Kelly D. Chamberlin, Mark D. Burow

Abstract

Single-nucleotide polymorphisms, which can be identified in the thousands or millions from comparisons of transcriptome or genome sequences, are ideally suited for making high-resolution genetic maps, investigating population evolutionary history, and discovering marker-trait linkages. Despite significant results from their use in human genetics, progress in identification and use in plants, and particularly polyploid plants, has lagged. As part of a long-term project to identify and use SNPs suitable for these purposes in cultivated peanut, which is tetraploid, we generated transcriptome sequences of four peanut cultivars, namely OLin, New Mexico Valencia C, Tamrun OL07 and Jupiter, which represent the four major market classes of peanut grown in the world, and which are important economically to the US southwest peanut growing region. CopyDNA libraries of each genotype were used to generate 2 × 54 paired-end reads using an Illumina GAIIx sequencer. Raw reads were mapped to a custom reference consisting of Tifrunner 454 sequences plus peanut ESTs in GenBank, compromising 43,108 contigs; 263,840 SNP and indel variants were identified among four genotypes compared to the reference. A subset of 6 variants was assayed across 24 genotypes representing four market types using KASP chemistry to assess the criteria for SNP selection. Results demonstrated that transcriptome sequencing can identify SNPs usable as selectable DNA-based markers in complex polyploid species such as peanut. Criteria for effective use of SNPs as markers are discussed in this context.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 2%
Unknown 54 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 27%
Researcher 11 20%
Student > Doctoral Student 7 13%
Student > Master 5 9%
Professor 3 5%
Other 7 13%
Unknown 7 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 69%
Biochemistry, Genetics and Molecular Biology 5 9%
Environmental Science 2 4%
Unknown 10 18%
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 12 February 2015.
All research outputs
#16,721,208
of 25,373,627 outputs
Outputs from Molecular Genetics and Genomics
#2,699
of 3,318 outputs
Outputs of similar age
#211,836
of 361,202 outputs
Outputs of similar age from Molecular Genetics and Genomics
#9
of 39 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,318 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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 361,202 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 39 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 74% of its contemporaries.