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Next-generation genome sequencing can be used to rapidly characterise sequences flanking T-DNA insertions in random insertional mutants of Leptosphaeria maculans

Overview of attention for article published in Fungal Biology and Biotechnology, December 2014
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Title
Next-generation genome sequencing can be used to rapidly characterise sequences flanking T-DNA insertions in random insertional mutants of Leptosphaeria maculans
Published in
Fungal Biology and Biotechnology, December 2014
DOI 10.1186/s40694-014-0010-y
Pubmed ID
Authors

Kylie Chambers, Rohan GT Lowe, Barbara J Howlett, Manuel Zander, Jacqueline Batley, Angela P Van de Wouw, Candace E Elliott

Abstract

Banks of mutants with random insertions of T-DNA from Agrobacterium tumefaciens are often used in forward genetics approaches to identify phenotypes of interest. Upon identification of mutants of interest, the flanking sequences of the inserted T-DNA must be identified so that the mutated gene can be characterised. However, for many fungi, this task is not trivial as widely used PCR-based methods such as thermal asymmetric interlaced polymerase chain reaction (TAIL-PCR) are not successful. Next-generation Illumina sequencing was used to locate T-DNA insertion sites in four mutants of Leptosphaeria maculans, a fungal plant pathogen. Sequence reads of up to 150 bp and coverage ranging from 6 to 24 times, were sufficient for identification of insertion sites in all mutants. All T-DNA border sequences were truncated to different extents. Additionally, next-generation sequencing revealed chromosomal rearrangements associated with the insertion in one of the mutants. Next-generation sequencing is a cost-effective and rapid method of identifying sites of T-DNA insertions, and associated genomic rearrangements in Leptosphaeria maculans and potentially in other fungal species.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 22%
Student > Doctoral Student 4 17%
Researcher 4 17%
Student > Bachelor 2 9%
Student > Master 2 9%
Other 2 9%
Unknown 4 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 57%
Computer Science 2 9%
Biochemistry, Genetics and Molecular Biology 2 9%
Environmental Science 1 4%
Social Sciences 1 4%
Other 1 4%
Unknown 3 13%
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 16 December 2015.
All research outputs
#18,432,465
of 22,835,198 outputs
Outputs from Fungal Biology and Biotechnology
#127
of 140 outputs
Outputs of similar age
#261,202
of 360,533 outputs
Outputs of similar age from Fungal Biology and Biotechnology
#5
of 5 outputs
Altmetric has tracked 22,835,198 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 140 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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