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High-throughput physical map anchoring via BAC-pool sequencing

Overview of attention for article published in BMC Plant Biology, April 2015
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Title
High-throughput physical map anchoring via BAC-pool sequencing
Published in
BMC Plant Biology, April 2015
DOI 10.1186/s12870-015-0429-1
Pubmed ID
Authors

Kateřina Cviková, Federica Cattonaro, Michael Alaux, Nils Stein, Klaus FX Mayer, Jaroslav Doležel, Jan Bartoš

Abstract

Physical maps created from large insert DNA libraries, typically cloned in BAC vector, are valuable resources for map-based cloning and de novo genome sequencing. The maps are most useful if contigs of overlapping DNA clones are anchored to chromosome(s), and ordered along them using molecular markers. Here we present a novel approach for anchoring physical maps, based on sequencing three-dimensional pools of BAC clones from minimum tilling path. We used physical map of wheat chromosome arm 3DS to validate the method with two different DNA sequence datasets. The first comprised 567 genes ordered along the chromosome arm based on syntenic relationship of wheat with the sequenced genomes of Brachypodium, rice and sorghum. The second dataset consisted of 7,136 SNP-containing sequences, which were mapped genetically in Aegilops tauschii, the donor of the wheat D genome. Mapping of sequence reads from individual BAC pools to the first and the second datasets enabled unambiguous anchoring 447 and 311 3DS-specific sequences, respectively, or 758 in total. We demonstrate the utility of the novel approach for BAC contig anchoring based on mass parallel sequencing of three-dimensional pools prepared from minimum tilling path of physical map. The existing genetic markers as well as any other DNA sequence could be mapped to BAC clones in a single in silico experiment. The approach reduces significantly the cost and time needed for anchoring and is applicable to any genomic project involving the construction of anchored physical map.

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Mendeley readers

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Geographical breakdown

Country Count As %
Germany 1 6%
Unknown 15 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 31%
Student > Ph. D. Student 3 19%
Other 2 13%
Student > Master 2 13%
Professor 1 6%
Other 2 13%
Unknown 1 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 75%
Computer Science 1 6%
Unknown 3 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 20 June 2016.
All research outputs
#17,758,492
of 22,805,349 outputs
Outputs from BMC Plant Biology
#1,879
of 3,244 outputs
Outputs of similar age
#180,653
of 264,625 outputs
Outputs of similar age from BMC Plant Biology
#25
of 49 outputs
Altmetric has tracked 22,805,349 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,244 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 35th percentile – i.e., 35% 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 264,625 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.