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Genomic Selection in the Era of Next Generation Sequencing for Complex Traits in Plant Breeding

Overview of attention for article published in Frontiers in Genetics, December 2016
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  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

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6 X users

Citations

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295 Dimensions

Readers on

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568 Mendeley
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Title
Genomic Selection in the Era of Next Generation Sequencing for Complex Traits in Plant Breeding
Published in
Frontiers in Genetics, December 2016
DOI 10.3389/fgene.2016.00221
Pubmed ID
Authors

Javaid A. Bhat, Sajad Ali, Romesh K. Salgotra, Zahoor A. Mir, Sutapa Dutta, Vasudha Jadon, Anshika Tyagi, Muntazir Mushtaq, Neelu Jain, Pradeep K. Singh, Gyanendra P. Singh, K. V. Prabhu

Abstract

Genomic selection (GS) is a promising approach exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. In plant breeding, it provides opportunities to increase genetic gain of complex traits per unit time and cost. The cost-benefit balance was an important consideration for GS to work in crop plants. Availability of genome-wide high-throughput, cost-effective and flexible markers, having low ascertainment bias, suitable for large population size as well for both model and non-model crop species with or without the reference genome sequence was the most important factor for its successful and effective implementation in crop species. These factors were the major limitations to earlier marker systems viz., SSR and array-based, and was unimaginable before the availability of next-generation sequencing (NGS) technologies which have provided novel SNP genotyping platforms especially the genotyping by sequencing. These marker technologies have changed the entire scenario of marker applications and made the use of GS a routine work for crop improvement in both model and non-model crop species. The NGS-based genotyping have increased genomic-estimated breeding value prediction accuracies over other established marker platform in cereals and other crop species, and made the dream of GS true in crop breeding. But to harness the true benefits from GS, these marker technologies will be combined with high-throughput phenotyping for achieving the valuable genetic gain from complex traits. Moreover, the continuous decline in sequencing cost will make the WGS feasible and cost effective for GS in near future. Till that time matures the targeted sequencing seems to be more cost-effective option for large scale marker discovery and GS, particularly in case of large and un-decoded genomes.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 568 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Netherlands 1 <1%
Belgium 1 <1%
Unknown 565 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 102 18%
Student > Ph. D. Student 88 15%
Student > Master 77 14%
Student > Doctoral Student 36 6%
Student > Bachelor 33 6%
Other 71 13%
Unknown 161 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 300 53%
Biochemistry, Genetics and Molecular Biology 43 8%
Medicine and Dentistry 6 1%
Computer Science 5 <1%
Engineering 5 <1%
Other 30 5%
Unknown 179 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 11 January 2019.
All research outputs
#7,402,075
of 22,925,760 outputs
Outputs from Frontiers in Genetics
#2,408
of 11,961 outputs
Outputs of similar age
#138,820
of 420,925 outputs
Outputs of similar age from Frontiers in Genetics
#18
of 43 outputs
Altmetric has tracked 22,925,760 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 11,961 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done well, scoring higher than 79% 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 420,925 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 43 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 58% of its contemporaries.