Evidence map›Paper›PMID 24860578›Full record

ArticleFrontiers in plant science2014

Developing market class specific InDel markers from next generation sequence data in Phaseolus vulgaris L.

Samira Mafi Moghaddam, Qijian Song, Sujan Mamidi, Jeremy Schmutz, Rian Lee, Perry Cregan, Juan M Osorno, Phillip E McClean

Abstract read
In one paragraph

Article in Frontiers in plant science, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed.

  1. Article
  2. Genetic Variation Study of Several Romanian Pepper (International journal of molecular sciences · 2024
    Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. The Common BeanFrontiers in plant science · 2022
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Comparative Chloroplast Genomes ofBioMed research international · 2019
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Samira Mafi MoghaddamGenomics and Bioinformatics Program, North Dakota State University Fargo, ND, USA ; Department of Plant Sciences, North Dakota State University Fargo, ND, USA.
Qijian SongSoybean Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service Beltsville, MD, USA.
Sujan MamidiGenomics and Bioinformatics Program, North Dakota State University Fargo, ND, USA ; Department of Plant Sciences, North Dakota State University Fargo, ND, USA.
Jeremy SchmutzHudsonAlpha Institute Huntsville, AL, USA.
Rian LeeDepartment of Plant Sciences, North Dakota State University Fargo, ND, USA.
Perry CreganSoybean Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service Beltsville, MD, USA.
Juan M OsornoDepartment of Plant Sciences, North Dakota State University Fargo, ND, USA.
Phillip E McCleanGenomics and Bioinformatics Program, North Dakota State University Fargo, ND, USA ; Department of Plant Sciences, North Dakota State University Fargo, ND, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Next generation sequence data provides valuable information and tools for genetic and genomic research and offers new insights useful for marker development. This data is useful for the design of accurate and user-friendly molecular tools. Common bean (Phaseolus vulgaris L.) is a diverse crop in which separate domestication events happened in each gene pool followed by race and market class diversification that has resulted in different morphological characteristics in each commercial market class. This has led to essentially independent breeding programs within each market class which in turn has resulted in limited within market class sequence variation. Sequence data from selected genotypes of five bean market classes (pinto, black, navy, and light and dark red kidney) were used to develop InDel-based markers specific to each market class. Design of the InDel markers was conducted through a combination of assembly, alignment and primer design software using 1.6× to 5.1× coverage of Illumina GAII sequence data for each of the selected genotypes. The procedure we developed for primer design is fast, accurate, less error prone, and higher throughput than when they are designed manually. All InDel markers are easy to run and score with no need for PCR optimization. A total of 2687 InDel markers distributed across the genome were developed. To highlight their usefulness, they were employed to construct a phylogenetic tree and a genetic map, showing that InDel markers are reliable, simple, and accurate.

Indexed as

common beangenetic mapInDel markermarket classnext generation sequencingphylogenetics

Identifiers

PMID24860578
PMCPMC4026720

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.