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Genome-Wide Association Analysis of Age-Dependent Egg Weights in Chickens

Overview of attention for article published in Frontiers in Genetics, April 2018
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Title
Genome-Wide Association Analysis of Age-Dependent Egg Weights in Chickens
Published in
Frontiers in Genetics, April 2018
DOI 10.3389/fgene.2018.00128
Pubmed ID
Authors

Zhuang Liu, Congjiao Sun, Yiyuan Yan, Guangqi Li, Guiqin Wu, Aiqiao Liu, Ning Yang

Abstract

Egg weight (EW) is an economically-important trait and displays a consecutive increase with the hen's age. Because extremely large eggs cause a range of problems in the poultry industry, we performed a genome-wide association study (GWAS) in order to identify genomic variations that are associated with EW. We utilized the Affymetrix 600 K high density SNP array in a population of 1,078 hens at seven time points from day at first egg to 80 weeks age (EW80). Results reveal that a 90 Kb genomic region (169.42 Mb ~ 169.51 Mb) in GGA1 is significantly associated with EW36 and is also potentially associated with egg weight at 28, 56, and 66 week of age. The leading SNP could account for 3.66% of the phenotypic variation, while two promising genes (DLEU7 and MIR15A) can be mapped to this narrow significant region and may affect EW in a pleiotropic manner. In addition, one gene (CECR2 on GGA1) and two genes (MEIS1 and SPRED2 on GGA3), which involved in the processes of embryogenesis and organogenesis, were also considered to be candidates related to first egg weight (FEW) and EW56, respectively. Findings in our study could provide worthy theoretical basis to generate eggs of ideal size based on marker assisted breeding selection.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 15%
Student > Doctoral Student 3 11%
Researcher 3 11%
Student > Ph. D. Student 3 11%
Lecturer 1 4%
Other 3 11%
Unknown 10 37%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 41%
Biochemistry, Genetics and Molecular Biology 3 11%
Computer Science 1 4%
Chemistry 1 4%
Unknown 11 41%
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 15 May 2018.
All research outputs
#14,326,716
of 23,045,021 outputs
Outputs from Frontiers in Genetics
#3,940
of 12,100 outputs
Outputs of similar age
#184,108
of 326,650 outputs
Outputs of similar age from Frontiers in Genetics
#60
of 127 outputs
Altmetric has tracked 23,045,021 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,100 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 66% 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 326,650 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 127 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 51% of its contemporaries.