↓ Skip to main content

Strategies for optimizing BioNano and Dovetail explored through a second reference quality assembly for the legume model, Medicago truncatula

Overview of attention for article published in BMC Genomics, August 2017
Altmetric Badge

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 (80th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

twitter
17 X users

Citations

dimensions_citation
55 Dimensions

Readers on

mendeley
104 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.
Title
Strategies for optimizing BioNano and Dovetail explored through a second reference quality assembly for the legume model, Medicago truncatula
Published in
BMC Genomics, August 2017
DOI 10.1186/s12864-017-3971-4
Pubmed ID
Authors

Karen M. Moll, Peng Zhou, Thiruvarangan Ramaraj, Diego Fajardo, Nicholas P. Devitt, Michael J. Sadowsky, Robert M. Stupar, Peter Tiffin, Jason R. Miller, Nevin D. Young, Kevin A. T. Silverstein, Joann Mudge

Abstract

Third generation sequencing technologies, with sequencing reads in the tens- of kilo-bases, facilitate genome assembly by spanning ambiguous regions and improving continuity. This has been critical for plant genomes, which are difficult to assemble due to high repeat content, gene family expansions, segmental and tandem duplications, and polyploidy. Recently, high-throughput mapping and scaffolding strategies have further improved continuity. Together, these long-range technologies enable quality draft assemblies of complex genomes in a cost-effective and timely manner. Here, we present high quality genome assemblies of the model legume plant, Medicago truncatula (R108) using PacBio, Dovetail Chicago (hereafter, Dovetail) and BioNano technologies. To test these technologies for plant genome assembly, we generated five assemblies using all possible combinations and ordering of these three technologies in the R108 assembly. While the BioNano and Dovetail joins overlapped, they also showed complementary gains in continuity and join numbers. Both technologies spanned repetitive regions that PacBio alone was unable to bridge. Combining technologies, particularly Dovetail followed by BioNano, resulted in notable improvements compared to Dovetail or BioNano alone. A combination of PacBio, Dovetail, and BioNano was used to generate a high quality draft assembly of R108, a M. truncatula accession widely used in studies of functional genomics. As a test for the usefulness of the resulting genome sequence, the new R108 assembly was used to pinpoint breakpoints and characterize flanking sequence of a previously identified translocation between chromosomes 4 and 8, identifying more than 22.7 Mb of novel sequence not present in the earlier A17 reference assembly. Adding Dovetail followed by BioNano data yielded complementary improvements in continuity over the original PacBio assembly. This strategy proved efficient and cost-effective for developing a quality draft assembly compared to traditional reference assemblies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 17 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 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 104 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 25%
Student > Ph. D. Student 25 24%
Student > Master 10 10%
Student > Doctoral Student 6 6%
Other 5 5%
Other 13 13%
Unknown 19 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 53 51%
Biochemistry, Genetics and Molecular Biology 20 19%
Computer Science 5 5%
Engineering 2 2%
Unspecified 1 <1%
Other 3 3%
Unknown 20 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 21 March 2018.
All research outputs
#3,509,539
of 24,162,141 outputs
Outputs from BMC Genomics
#1,301
of 10,914 outputs
Outputs of similar age
#63,011
of 320,850 outputs
Outputs of similar age from BMC Genomics
#38
of 226 outputs
Altmetric has tracked 24,162,141 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,914 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 88% 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 320,850 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 80% of its contemporaries.
We're also able to compare this research output to 226 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.