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Using whole-genome sequences of the LG/J and SM/J inbred mouse strains to prioritize quantitative trait genes and nucleotides

Overview of attention for article published in BMC Genomics, May 2015
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Title
Using whole-genome sequences of the LG/J and SM/J inbred mouse strains to prioritize quantitative trait genes and nucleotides
Published in
BMC Genomics, May 2015
DOI 10.1186/s12864-015-1592-3
Pubmed ID
Authors

Igor Nikolskiy, Donald F Conrad, Sung Chun, Justin C Fay, James M Cheverud, Heather A Lawson

Abstract

The laboratory mouse is the most commonly used model for studying variation in complex traits relevant to human disease. Here we present the whole-genome sequences of two inbred strains, LG/J and SM/J, which are frequently used to study variation in complex traits as diverse as aging, bone-growth, adiposity, maternal behavior, and methamphetamine sensitivity. We identified small nucleotide variants (SNVs) and structural variants (SVs) in the LG/J and SM/J strains relative to the reference genome and discovered novel variants in these two strains by comparing their sequences to other mouse genomes. We find that 39% of the LG/J and SM/J genomes are identical-by-descent (IBD). We characterized amino-acid changing mutations using three algorithms: LRT, PolyPhen-2 and SIFT. We also identified polymorphisms between LG/J and SM/J that fall in regulatory regions and highly informative transcription factor binding sites (TFBS). We intersected these functional predictions with quantitative trait loci (QTL) mapped in advanced intercrosses of these two strains. We find that QTL are both over-represented in non-IBD regions and highly enriched for variants predicted to have a functional impact. Variants in QTL associated with metabolic (231 QTL identified in an F16 generation) and developmental (41 QTL identified in an F34 generation) traits were interrogated and we highlight candidate quantitative trait genes (QTG) and nucleotides (QTN) in a QTL on chr13 associated with variation in basal glucose levels and in a QTL on chr6 associated with variation in tibia length. We show how integrating genomic sequence with QTL reduces the QTL search space and helps researchers prioritize candidate genes and nucleotides for experimental follow-up. Additionally, given the LG/J and SM/J phylogenetic context among inbred strains, these data contribute important information to the genomic landscape of the laboratory mouse.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 24%
Librarian 2 8%
Professor > Associate Professor 2 8%
Student > Master 2 8%
Professor 1 4%
Other 1 4%
Unknown 11 44%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 20%
Biochemistry, Genetics and Molecular Biology 3 12%
Medicine and Dentistry 2 8%
Linguistics 1 4%
Social Sciences 1 4%
Other 1 4%
Unknown 12 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 13 February 2016.
All research outputs
#14,931,785
of 23,881,329 outputs
Outputs from BMC Genomics
#5,848
of 10,793 outputs
Outputs of similar age
#141,227
of 268,867 outputs
Outputs of similar age from BMC Genomics
#153
of 252 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,793 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 41st percentile – i.e., 41% 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 268,867 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 252 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.