| Title |
Genetic analysis of glucosinolate variability in broccoli florets using genome-anchored single nucleotide polymorphisms
|
|---|---|
| Published in |
Theoretical and Applied Genetics, May 2015
|
| DOI | 10.1007/s00122-015-2517-x |
| Pubmed ID | |
| Authors |
Allan F. Brown, Gad G. Yousef, Robert W. Reid, Kranthi K. Chebrolu, Aswathy Thomas, Christopher Krueger, Elizabeth Jeffery, Eric Jackson, John A. Juvik |
| Abstract |
The identification of genetic factors influencing the accumulation of individual glucosinolates in broccoli florets provides novel insight into the regulation of glucosinolate levels in Brassica vegetables and will accelerate the development of vegetables with glucosinolate profiles tailored to promote human health. Quantitative trait loci analysis of glucosinolate (GSL) variability was conducted with a B. oleracea (broccoli) mapping population, saturated with single nucleotide polymorphism markers from a high-density array designed for rapeseed (Brassica napus). In 4 years of analysis, 14 QTLs were associated with the accumulation of aliphatic, indolic, or aromatic GSLs in floret tissue. The accumulation of 3-carbon aliphatic GSLs (2-propenyl and 3-methylsulfinylpropyl) was primarily associated with a single QTL on C05, but common regulation of 4-carbon aliphatic GSLs was not observed. A single locus on C09, associated with up to 40 % of the phenotypic variability of 2-hydroxy-3-butenyl GSL over multiple years, was not associated with the variability of precursor compounds. Similarly, QTLs on C02, C04, and C09 were associated with 4-methylsulfinylbutyl GSL concentration over multiple years but were not significantly associated with downstream compounds. Genome-specific SNP markers were used to identify candidate genes that co-localized to marker intervals and previously sequenced Brassica oleracea BAC clones containing known GSL genes (GSL-ALK, GSL-PRO, and GSL-ELONG) were aligned to the genomic sequence, providing support that at least three of our 14 QTLs likely correspond to previously identified GSL loci. The results demonstrate that previously identified loci do not fully explain GSL variation in broccoli. The identification of additional genetic factors influencing the accumulation of GSL in broccoli florets provides novel insight into the regulation of GSL levels in Brassicaceae and will accelerate development of vegetables with modified or enhanced GSL profiles. |
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 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 35% |
| Student > Ph. D. Student | 5 | 25% |
| Professor | 1 | 5% |
| Student > Doctoral Student | 1 | 5% |
| Student > Bachelor | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 4 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 55% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Chemistry | 1 | 5% |
| Medicine and Dentistry | 1 | 5% |
| Unknown | 6 | 30% |
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 02 May 2015.
All research outputs
#19,201,293
of 23,794,258 outputs
Outputs from Theoretical and Applied Genetics
#3,124
of 3,565 outputs
Outputs of similar age
#194,875
of 265,617 outputs
Outputs of similar age from Theoretical and Applied Genetics
#23
of 40 outputs
Altmetric has tracked 23,794,258 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 3,565 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 6th percentile – i.e., 6% 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 265,617 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.