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Attention Score in Context
| Title |
Construction of a high-density genetic map and QTLs mapping for sugars and acids in grape berries
|
|---|---|
| Published in |
BMC Plant Biology, February 2015
|
| DOI | 10.1186/s12870-015-0428-2 |
| Pubmed ID | |
| Authors |
Jie Chen, Nian Wang, Lin-Chuan Fang, Zhen-Chang Liang, Shao-Hua Li, Ben-Hong Wu |
| Abstract |
BackgroundQTLs controlling individual sugars and acids (fructose, glucose, malic acid and tartaric acid) in grape berries have not yet been identified. The present study aimed to construct a high-density, high-quality genetic map of a winemaking grape cross with a complex parentage (V. vinifera × V. amurensis) × ((V. labrusca × V. riparia) × V. vinifera), using next-generation restriction site-associated DNA sequencing, and then to identify loci related to phenotypic variability over three years.ResultsIn total, 1 826 SNP-based markers were developed. Of these, 621 markers were assembled into 19 linkage groups (LGs) for the maternal map, 696 for the paternal map, and 1 254 for the integrated map. Markers showed good linear agreement on most chromosomes between our genetic maps and the previously published V. vinifera reference sequence. However marker order was different in some chromosome regions, indicating both conservation and variation within the genome. Despite the identification of a range of QTLs controlling the traits of interest, these QTLs explained a relatively small percentage of the observed phenotypic variance. Although they exhibited a large degree of instability from year to year, QTLs were identified for all traits but tartaric acid and titratable acidity in the three years of the study; however only the QTLs for malic acid and ß ratio (tartaric acid-to-malic acid ratio) were stable in two years. QTLs related to sugars were located within ten LGs (01, 02, 03, 04, 07, 09, 11, 14, 17, 18), and those related to acids within three LGs (06, 13, 18). Overlapping QTLs in LG14 were observed for fructose, glucose and total sugar. Malic acid, total acid and ß ratio each had several QTLs in LG18, and malic acid also had a QTL in LG06. A set of 10 genes underlying these QTLs may be involved in determining the malic acid content of berries.ConclusionThe genetic map constructed in this study is potentially a high-density, high-quality map, which could be used for QTL detection, genome comparison, and sequence assembly. It may also serve to broaden our understanding of the grape genome. |
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 % |
|---|---|---|
| Unknown | 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 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Uruguay | 1 | 1% |
| France | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 71 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 21 | 28% |
| Researcher | 9 | 12% |
| Student > Master | 9 | 12% |
| Student > Bachelor | 4 | 5% |
| Student > Doctoral Student | 3 | 4% |
| Other | 7 | 9% |
| Unknown | 21 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 44 | 59% |
| Biochemistry, Genetics and Molecular Biology | 5 | 7% |
| Business, Management and Accounting | 1 | 1% |
| Unspecified | 1 | 1% |
| Social Sciences | 1 | 1% |
| Other | 1 | 1% |
| Unknown | 21 | 28% |
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 04 February 2015.
All research outputs
#15,821,622
of 23,498,099 outputs
Outputs from BMC Plant Biology
#1,501
of 3,310 outputs
Outputs of similar age
#213,703
of 355,750 outputs
Outputs of similar age from BMC Plant Biology
#38
of 88 outputs
Altmetric has tracked 23,498,099 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,310 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 41st percentile – i.e., 41% 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 355,750 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 88 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 52% of its contemporaries.