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Attention Score in Context
| Title |
Assessment of Genetic Variation and Population Structure of Diverse Rice Genotypes Adapted to Lowland and Upland Ecologies in Africa Using SNPs
|
|---|---|
| Published in |
Frontiers in Plant Science, April 2018
|
| DOI | 10.3389/fpls.2018.00446 |
| Pubmed ID | |
| Authors |
Marie Noelle Ndjiondjop, Kassa Semagn, Mounirou Sow, Baboucarr Manneh, Arnaud C. Gouda, Sèdjro B. Kpeki, Esther Pegalepo, Peterson Wambugu, Moussa Sié, Marilyn L. Warburton |
| Abstract |
Using interspecific crosses involving Oryza glaberrima Steud. as donor and O. sativa L. as recurrent parents, rice breeders at the Africa Rice Center developed several 'New Rice for Africa (NERICA)' improved varieties. A smaller number of interspecific and intraspecific varieties have also been released as 'Advanced Rice for Africa (ARICA)'. The objective of the present study was to investigate the genetic variation, relatedness, and population structure of 330 widely used rice genotypes in Africa using DArTseq-based single nucleotide polymorphisms (SNPs). A sample of 11 ARICAs, 85 NERICAs, 62 O. sativa spp. japonica, and 172 O. sativa spp. indica genotypes were genotyped with 27,560 SNPs using diversity array technology (DArT)-based sequencing (DArTseq) platform. Nearly 66% of the SNPs were polymorphic, of which 15,020 SNPs were mapped to the 12 rice chromosomes. Genetic distance between pairs of genotypes that belong to indica, japonica, ARICA, and NERICA varied from 0.016 to 0.623, from 0.020 to 0.692, from 0.075 to 0.763, and from 0.014 to 0.644, respectively. The proportion of pairs of genotypes with genetic distance > 0.400 was the largest within NERICAs (35.1% of the pairs) followed by ARICAs (18.2%), japonica (17.4%), and indica (5.6%). We found one pair of japonica, 11 pairs of indica, and 35 pairs of NERICA genotypes differing by <2% of the total scored alleles, which was due to 26 pairs of genotypes with identical pedigrees. Cluster analysis, principal component analysis, and the model-based population structure analysis all revealed two distinct groups corresponding to the lowland (primarily indica and lowland NERICAs) and upland (japonica and upland NERICAs) growing ecologies. Most of the interspecific lowland NERICAs formed a sub-group, likely caused by differences in the O. glaberrima genome as compared with the indica genotypes. Analysis of molecular variance revealed very great genetic differentiation (FST = 0.688) between the lowland and upland ecologies, and 31.2% of variation attributable to differences within cluster groups. About 8% (1,197 of 15,020) of the 15,020 SNPs were significantly (P < 0.05) different between the lowland and upland ecologies and formed contrasting haplotypes that could clearly discriminate lowland from upland genotypes. This is the first study using high density markers that characterized NERICA and ARICA varieties in comparison with indica and japonica varieties widely used in Africa, which could aid rice breeders on parent selection for developing new improved rice germplasm. |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 14% |
| United Kingdom | 1 | 14% |
| Unknown | 5 | 71% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 86% |
| Scientists | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 59 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 17% |
| Researcher | 9 | 15% |
| Student > Master | 6 | 10% |
| Student > Postgraduate | 3 | 5% |
| Lecturer | 2 | 3% |
| Other | 6 | 10% |
| Unknown | 23 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 26 | 44% |
| Biochemistry, Genetics and Molecular Biology | 3 | 5% |
| Unspecified | 1 | 2% |
| Environmental Science | 1 | 2% |
| Computer Science | 1 | 2% |
| Other | 2 | 3% |
| Unknown | 25 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 05 June 2018.
All research outputs
#6,174,782
of 23,031,582 outputs
Outputs from Frontiers in Plant Science
#3,307
of 20,570 outputs
Outputs of similar age
#108,482
of 329,279 outputs
Outputs of similar age from Frontiers in Plant Science
#95
of 443 outputs
Altmetric has tracked 23,031,582 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 20,570 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 83% 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 329,279 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 443 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.