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Candidate lethal haplotypes and causal mutations in Angus cattle

Overview of attention for article published in BMC Genomics, October 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

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Title
Candidate lethal haplotypes and causal mutations in Angus cattle
Published in
BMC Genomics, October 2017
DOI 10.1186/s12864-017-4196-2
Pubmed ID
Authors

Jesse L. Hoff, Jared E. Decker, Robert D. Schnabel, Jeremy F. Taylor

Abstract

If unmanaged, high rates of inbreeding in livestock populations adversely impact their reproductive fitness. In beef cattle, historical selection strategies have increased the frequency of several segregating fatal autosomal recessive polymorphisms. Selective breeding has also decreased the extent of haplotypic diversity genome-wide. By identifying haplotypes for which homozygotes are not observed but would be expected based on their frequency, candidates for developmentally lethal recessive loci can be localized. This analysis comes without the need for observation of the loss-associated phenotype (e.g., failure to implant, first trimester abortion, deformity at birth). In this study, haplotypes were estimated for 3961 registered Angus individuals using 52,545 SNP loci using findhap v2, which exploited the complex pedigree among the individuals in this population. Seven loci were detected to possess haplotypes that were not observed in homozygous form despite a sufficiently high frequency and pedigree-based expectation of homozygote occurrence. These haplotypes were identified as candidates for harboring autosomal recessive lethal alleles. Of the genotyped individuals, 109 were resequenced to an average 27X depth of coverage to identify putative loss-of-function alleles genome-wide and had variants called using a custom in-house developed pipeline. For the candidate lethal-harboring haplotypes present in these bulls, sequence-called genotypes were used to identify concordant variants. In addition, whole-genome sequence imputation of variants was performed into the set of 3961 genotyped animals using the 109 resequenced animals to identify candidate lethal recessive variants at the seven loci. Following the imputation, no variants were identified that were fully concordant with the marker-based diplotypes. Selective breeding programs could utilize the predicted lethal haplotypes associated with SNP genotypes. Sequencing and other methods for identifying the causal variants underlying these haplotypes can allow for more efficient methods of management such as gene editing. These two methods in total will reduce the negative impacts of inbreeding on fertility and maximize overall genetic gains.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 16%
Student > Master 8 14%
Student > Doctoral Student 6 11%
Student > Ph. D. Student 6 11%
Other 3 5%
Other 9 16%
Unknown 15 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 45%
Biochemistry, Genetics and Molecular Biology 7 13%
Veterinary Science and Veterinary Medicine 3 5%
Medicine and Dentistry 3 5%
Unspecified 2 4%
Other 1 2%
Unknown 15 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 December 2017.
All research outputs
#4,614,691
of 23,544,006 outputs
Outputs from BMC Genomics
#1,870
of 10,789 outputs
Outputs of similar age
#80,920
of 328,275 outputs
Outputs of similar age from BMC Genomics
#36
of 203 outputs
Altmetric has tracked 23,544,006 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,789 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 82% 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 328,275 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 75% of its contemporaries.
We're also able to compare this research output to 203 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.