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Genetic diversity trend in Indian rice varieties: an analysis using SSR markers

Overview of attention for article published in BMC Genetics, September 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#30 of 774)
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

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2 blogs
twitter
3 tweeters

Citations

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39 Dimensions

Readers on

mendeley
65 Mendeley
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1 CiteULike
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Title
Genetic diversity trend in Indian rice varieties: an analysis using SSR markers
Published in
BMC Genetics, September 2016
DOI 10.1186/s12863-016-0437-7
Pubmed ID
Authors

Nivedita Singh, Debjani Roy Choudhury, Gunjan Tiwari, Amit Kumar Singh, Sundeep Kumar, Kalyani Srinivasan, R. K. Tyagi, A. D. Sharma, N. K. Singh, Rakesh Singh

Abstract

The knowledge of the extent and pattern of diversity in the crop species is a prerequisite for any crop improvement as it helps breeders in deciding suitable breeding strategies for their future improvement. Rice is the main staple crop in India with the large number of varieties released every year. Studies based on the small set of rice genotypes have reported a loss in genetic diversity especially after green revolution. However, a detailed study of the trend of diversity in Indian rice varieties is lacking. SSR markers have proven to be a marker of choice for studying the genetic diversity. Therefore, the present study was undertaken with the aim to characterize and assess trends of genetic diversity in a large set of Indian rice varieties (released between 1940-2013), conserved in the National Gene Bank of India using SSR markers. A set of 729 Indian rice varieties were genotyped using 36 HvSSR markers to assess the genetic diversity and genetic relationship. A total of 112 alleles was amplified with an average of 3.11 alleles per locus with mean Polymorphic Information Content (PIC) value of 0.29. Cluster analysis grouped these varieties into two clusters whereas the model based population structure divided them into three populations. AMOVA study based on hierarchical cluster and model based approach showed 3 % and 11 % variation between the populations, respectively. Decadal analysis for gene diversity and PIC showed increasing trend from 1940 to 2005, thereafter values for both the parameters showed decreasing trend between years 2006-2013. In contrast to this, allele number demonstrated increasing trend in these varieties released and notified between1940 to 1985, it remained nearly constant during 1986 to 2005 and again showed an increasing trend. Our results demonstrated that the Indian rice varieties harbors huge amount of genetic diversity. However, the trait based improvement program in the last decades forced breeders to rely on few parents, which resulted in loss of gene diversity during 2006 to 2013. The present study indicates the need for broadening the genetic base of Indian rice varieties through the use of diverse parents in the current breeding program.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
Benin 1 2%
Brazil 1 2%
Unknown 62 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 26%
Researcher 14 22%
Student > Master 10 15%
Student > Postgraduate 4 6%
Student > Doctoral Student 4 6%
Other 9 14%
Unknown 7 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 55%
Biochemistry, Genetics and Molecular Biology 9 14%
Computer Science 3 5%
Unspecified 1 2%
Business, Management and Accounting 1 2%
Other 4 6%
Unknown 11 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 24 January 2017.
All research outputs
#701,573
of 11,029,749 outputs
Outputs from BMC Genetics
#30
of 774 outputs
Outputs of similar age
#28,222
of 258,509 outputs
Outputs of similar age from BMC Genetics
#3
of 31 outputs
Altmetric has tracked 11,029,749 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 774 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 96% 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 258,509 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 89% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.