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Current knowledge in lentil genomics and its application for crop improvement

Overview of attention for article published in Frontiers in Plant Science, February 2015
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  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

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Title
Current knowledge in lentil genomics and its application for crop improvement
Published in
Frontiers in Plant Science, February 2015
DOI 10.3389/fpls.2015.00078
Pubmed ID
Authors

Shiv Kumar, Karthika Rajendran, Jitendra Kumar, Aladdin Hamwieh, Michael Baum

Abstract

Most of the lentil growing countries face a certain set of abiotic and biotic stresses causing substantial reduction in crop growth, yield, and production. Until-to date, lentil breeders have used conventional plant breeding techniques of selection-recombination-selection cycle to develop improved cultivars.These techniques have been successful in mainstreaming some of the easy-to-manage monogenic traits. However, in case of complex quantitative traits, these conventional techniques are less precise. As most of the economic traits are complex, quantitative, and often influenced by environments and genotype-environment interaction, the genetic improvement of these traits becomes difficult. Genomics assisted breeding is relatively powerful and fast approach to develop high yielding varieties more suitable to adverse environmental conditions. New tools such as molecular markers and bioinformatics are expected to generate new knowledge and improve our understanding on the genetics of complex traits. In the past, the limited availability of genomic resources in lentil could not allow breeders to employ these tools in mainstream breeding program.The recent application of the next generation sequencing and genotyping by sequencing technologies has facilitated to speed up the lentil genome sequencing project and large discovery of genome-wide single nucleotide polymorphism (SNP) markers. Currently, several linkage maps have been developed in lentil through the use of expressed sequenced tag (EST) derived simple sequence repeat (SSR) and SNP markers.These maps have emerged as useful genomic resources to identify quantitative trait loci imparting tolerance to biotic and abiotic stresses in lentil. In this review, the current knowledge on available genomic resources and its application in lentil breeding program are discussed.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 <1%
Italy 1 <1%
France 1 <1%
Unknown 109 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 22%
Researcher 18 16%
Student > Master 12 11%
Student > Doctoral Student 7 6%
Professor > Associate Professor 6 5%
Other 12 11%
Unknown 32 29%
Readers by discipline Count As %
Agricultural and Biological Sciences 51 46%
Biochemistry, Genetics and Molecular Biology 14 13%
Engineering 3 3%
Linguistics 1 <1%
Unspecified 1 <1%
Other 5 4%
Unknown 37 33%
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 23 March 2015.
All research outputs
#13,929,642
of 22,782,096 outputs
Outputs from Frontiers in Plant Science
#7,256
of 20,073 outputs
Outputs of similar age
#129,043
of 255,192 outputs
Outputs of similar age from Frontiers in Plant Science
#81
of 239 outputs
Altmetric has tracked 22,782,096 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 20,073 research outputs from this source. They receive a mean Attention Score of 4.0. This one has gotten more attention than average, scoring higher than 60% 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 255,192 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 239 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 61% of its contemporaries.