| Title |
Combined QTL mapping, physiological and transcriptomic analyses to identify candidate genes involved in Brassica napus seed aging
|
|---|---|
| Published in |
Molecular Genetics and Genomics, July 2018
|
| DOI | 10.1007/s00438-018-1468-8 |
| Pubmed ID | |
| Authors |
Tengyue Wang, Lintao Hou, Hongju Jian, Feifei Di, Jiana Li, Liezhao Liu |
| Abstract |
Seed aging is an inevitable problem in the germplasm conservation of oil crops. Thus, clarifying the genetic mechanism of seed aging is important for rapeseed breeding. In this study, Brassica napus seeds were exposed to an artificial aging environment (40 °C and 90% relative humidity). Using a population of 172 recombinant inbred lines, 13 QTLs were detected on 8 chromosomes, which explained ~ 9.05% of the total phenotypic variation. The QTLs q2015AGIA-C08 and q2016AGI-C08-2 identified in the two environments were considered the same QTL. After artificial aging, lower germination index, increased relative electrical conductivity, malondialdehyde and proline content, and reduced soluble sugar, protein content and antioxidant enzyme activities were detected. Furthermore, seeds of extreme lines that were either left untreated (R0 and S0) or subjected to 15 days of artificial aging (R15 and S15) were used for transcriptome sequencing. In total, 2843, 1084, 429 and 1055 differentially expressed genes were identified in R15 vs. R0, S15 vs. S0, R0 vs. S0 and R15 vs. S15, respectively. Through integrated QTL mapping and RNA-sequencing analyses, seven genes, such as BnaA03g37460D, encoding heat shock transcription factor C1, and BnaA03g40360D, encoding phosphofructokinase 4, were screened as candidate genes involved in seed aging. Further researches on these candidate genes could broaden our understanding of the regulatory mechanisms of seed aging. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 26% |
| Student > Master | 5 | 26% |
| Student > Ph. D. Student | 2 | 11% |
| Professor | 1 | 5% |
| Student > Doctoral Student | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 4 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 12 | 63% |
| Biochemistry, Genetics and Molecular Biology | 2 | 11% |
| Unspecified | 1 | 5% |
| Unknown | 4 | 21% |
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 06 July 2018.
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#19,951,180
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Outputs of similar age from Molecular Genetics and Genomics
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