You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
High-density genetic map construction and QTLs analysis of grain yield-related traits in Sesame (Sesamum indicum L.) based on RAD-Seq techonology
|
|---|---|
| Published in |
BMC Plant Biology, October 2014
|
| DOI | 10.1186/s12870-014-0274-7 |
| Pubmed ID | |
| Authors |
Kun Wu, Hongyan Liu, Minmin Yang, Ye Tao, Huihui Ma, Wenxiong Wu, Yang Zuo, Yingzhong Zhao |
| Abstract |
BackgroundSesame (Sesamum indicum L., 2n¿=¿26) is an important oilseed crop with an estimated genome size of 369 Mb. The genetic basis, including the number and locations of quantitative trait loci (QTLs) of sesame grain yield and quality remain poorly understood, due in part to the lack of reliable markers and genetic maps. Here we report on the construction of a hitherto most high-density genetic map of sesame using the restriction-site associated DNA sequencing (RAD-seq) combined with 89 PCR markers, and the identification of grain yield-related QTLs using a recombinant inbred line (RIL) population.ResultIn total, 3,769 single-nucleotide polymorphism (SNP) markers were identified from RAD-seq, and 89 polymorphic PCR markers were identified including 44 expressed sequence tag-simple sequence repeats (EST-SSRs), 10 genomic-SSRs and 35 Insertion-Deletion markers (InDels). The final map included 1,230 markers distributed on 14 linkage groups (LGs) and was 844.46 cM in length with an average of 0.69 cM between adjacent markers. Using this map and RIL population, we detected 13 QTLs on 7 LGs and 17 QTLs on 10 LGs for seven grain yield-related traits by the multiple interval mapping (MIM) and the mixed linear composite interval mapping (MCIM), respectively. Three major QTLs had been identified using MIM with R2¿>¿10.0% or MCIM with ha 2¿>¿5.0%. Two co-localized QTL groups were identified that partially explained the correlations among five yield-related traits.ConclusionThree thousand eight hundred and four pairs of new DNA markers including SNPs and InDels were developed by RAD-seq, and a so far most high-density genetic map was constructed based on these markers in combination with SSR markers. Several grain yield-related QTLs had been identified using this population and genetic map. We report here the first QTL mapping of yield-related traits with a high-density genetic map using a RIL population in sesame. Results of this study solidified the basis for studying important agricultural traits and implementing marker-assisted selection (MAS) toward genetic improvement in sesame. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 80 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 22 | 28% |
| Researcher | 11 | 14% |
| Student > Master | 6 | 8% |
| Student > Bachelor | 4 | 5% |
| Student > Doctoral Student | 4 | 5% |
| Other | 13 | 16% |
| Unknown | 20 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 46 | 57% |
| Biochemistry, Genetics and Molecular Biology | 8 | 10% |
| Unspecified | 2 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 1% |
| Business, Management and Accounting | 1 | 1% |
| Other | 1 | 1% |
| Unknown | 21 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 October 2014.
All research outputs
#18,381,794
of 22,768,097 outputs
Outputs from BMC Plant Biology
#2,083
of 3,237 outputs
Outputs of similar age
#182,635
of 255,612 outputs
Outputs of similar age from BMC Plant Biology
#40
of 63 outputs
Altmetric has tracked 22,768,097 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,237 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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 255,612 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.