↓ Skip to main content

The promise and challenges of characterizing genome‐wide structural variants: A case study in a critically endangered parrot

Overview of attention for article published in Molecular Ecology Resources, March 2023
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 (82nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
17 X users
bluesky
1 Bluesky user

Readers on

mendeley
30 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.
Article details
Title
The promise and challenges of characterizing genome‐wide structural variants: A case study in a critically endangered parrot
Published in
Molecular Ecology Resources, March 2023
DOI 10.1111/1755-0998.13783
Pubmed ID
Authors
Abstract

There is growing interest in the role of structural variants (SVs) as drivers of local adaptation and speciation. From a biodiversity genomics perspective, the characterisation of genome-wide SVs provides an exciting opportunity to complement single nucleotide polymorphisms (SNPs). However, little is known about the impacts of SV discovery and genotyping strategies on the characterisation of genome-wide SV diversity within and among populations. Here, we explore a near whole-species resequence dataset, and long-read sequence data for a subset of highly represented individuals in the critically endangered kākāpō (Strigops habroptilus). We demonstrate that even when using a highly contiguous reference genome, different discovery and genotyping strategies can significantly impact the type, size and location of SVs characterised genome-wide. Further, we found that the mean number of SVs in each of two kākāpō lineages differed both within and across generations. These combined results suggest that genome-wide characterisation of SVs remains challenging at the population-scale. We are optimistic that increased accessibility to long-read sequencing and advancements in bioinformatic approaches including multi-reference approaches like genome graphs will alleviate at least some of the challenges associated with resolving SV characteristics below the species level. In the meantime, we address caveats, highlight considerations, and provide recommendations for the characterization of genome-wide SVs in biodiversity genomic research.

Login to access the Attention Digest and the Sentiment Analysis related to this output.

Timeline Attention over time Attention Score history
Login to access the full charts related to this output.
Activity
Login to access the full charts related to this output.
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 demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Login to view Mendeley reader trends over time.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 5 17%
Student > Master 4 13%
Other 2 7%
Student > Ph. D. Student 2 7%
Student > Postgraduate 2 7%
Other 1 3%
Unknown 14 47%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 7 23%
Biochemistry, Genetics and Molecular Biology 4 13%
Veterinary Science and Veterinary Medicine 2 7%
Nursing and Health Professions 1 3%
Earth and Planetary Sciences 1 3%
Other 1 3%
Unknown 14 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 28 January 2024.
All research outputs
#5,793,974
of 34,279,751 outputs
Outputs from Molecular Ecology Resources
#627
of 2,129 outputs
Outputs of similar age
#80,373
of 449,613 outputs
Outputs of similar age from Molecular Ecology Resources
#17
of 46 outputs
Altmetric has tracked 34,279,751 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,129 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.9. This one has gotten more attention than average, scoring higher than 70% 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 449,613 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 82% of its contemporaries.
We're also able to compare this research output to 46 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 63% of its contemporaries.