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Attention Score in Context
| Title |
Whole-genome resequencing of wild and cultivated cannabis reveals the genetic structure and adaptive selection of important traits
|
|---|---|
| Published in |
BMC Plant Biology, July 2022
|
| DOI | 10.1186/s12870-022-03744-0 |
| Pubmed ID | |
| Authors |
Xuan Chen, Hong-Yan Guo, Qing-Ying Zhang, Lu Wang, Rong Guo, Yi-Xun Zhan, Pin Lv, Yan-Ping Xu, Meng-Bi Guo, Yuan Zhang, Kun Zhang, Yan-Hu Liu, Ming Yang |
| Abstract |
Cannabis is an important industrial crop species whose fibre, seeds, flowers and leaves are widely used by humans. The study of cannabinoids extracted from plants has been popular research topic in recent years. China is one of the origins of cannabis and one of the few countries with wild cannabis plants. However, the genetic structure of Chinese cannabis and the degree of adaptive selection remain unclear. The main morphological characteristics of wild cannabis in China were assessed. Based on whole-genome resequencing SNPs, Chinese cannabis could be divided into five groups in terms of geographical source and ecotype: wild accessions growing in the northwestern region; wild accessions growing in the northeastern region; cultivated accessions grown for fibre in the northeastern region; cultivated accessions grown for seed in northwestern region, and cultivated accessions in southwestern region. We further identified genes related to flowering time, seed germination, seed size, embryogenesis, growth, and stress responses selected during the process of cannabis domestication. The expression of flowering-related genes under long-day (LD) and short-day (SD) conditions showed that Chinese cultivated cannabis is adapted to different photoperiods through the regulation of Flowering locus T-like (FT-like) expression. This study clarifies the genetic structure of Chinese cannabis and offers valuable genomic resources for cannabis breeding. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 25 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 16% |
| Student > Bachelor | 3 | 12% |
| Student > Doctoral Student | 2 | 8% |
| Student > Postgraduate | 1 | 4% |
| Student > Ph. D. Student | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 14 | 56% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 20% |
| Biochemistry, Genetics and Molecular Biology | 3 | 12% |
| Medicine and Dentistry | 2 | 8% |
| Nursing and Health Professions | 1 | 4% |
| Unknown | 14 | 56% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 29 August 2023.
All research outputs
#15,058,979
of 24,348,815 outputs
Outputs from BMC Plant Biology
#1,143
of 3,418 outputs
Outputs of similar age
#199,560
of 421,219 outputs
Outputs of similar age from BMC Plant Biology
#15
of 96 outputs
Altmetric has tracked 24,348,815 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,418 research outputs from this source. They receive a mean Attention Score of 3.0. This one has gotten more attention than average, scoring higher than 64% 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 421,219 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 50% of its contemporaries.
We're also able to compare this research output to 96 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.