Assessment of Platycodon grandiflorum germplasm resources from northern Anhui province based on ISSR analysis

Nie, Chao; Liu, Ruijiao; Li, Shangbo; Li, Yanyan

doi:10.1007/s11033-014-3721-5

Cited by 4 publications

(4 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…High value have been reported in Portulaca oleracea (Ip = 0.515) (Alam et al, 2015). Further, the average value for PPBs was found to be 31.98% that was lower than that of Platycodon longiflorum (PPBs = 55.67%) (Nie et al, 2014). Low genetic diversity within populations has been reported in other plant species, such as Taxus fuana (Shah et al, 2008) and Monimopetalum chinense (Xie et al, 2005).…”

Section: Genetic Diversitymentioning

confidence: 84%

“…It was observed that the genetic diversity of D. beecheyana var. pubescens (PPBs = 90.27%, Hes = 0.2497) at the species level was higher than that of the shortlived perennial species Blysmus sinocompressus (PPBs = 74.76%, Hes = 0.1668) (Hu et al, 2016) and mating breeding system species Platycodon grandiflorum (PPBs = 76.29%, Hes = 0.2326) (Nie et al, 2014). At the population level, the average Hep in D. beecheyana var.…”

Section: Genetic Diversitymentioning

confidence: 92%

“…pubescens collected from different regions in Fujian and Guangxi Provinces. Moreover, due to limited information based on ISSR marker few related report about the genetic diversity was compared with other species, such as mango (Luo et al, 2011), cucumber and apricot (Li et al, 2014), and Platycodon grandiflorus (Nie et al, 2014). These analyses provided insights into the germplasm resources and genetic relationships of natural bamboos populations that can help inbreeding improved varieties and for conservation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Genetic Diversity Analysis of Dendrocalamopsis Beecheyana Var. Pubescens Based on Issr Markers

He¹

2019

Appl. Ecol. Env. Res.

View full text Add to dashboard Cite

Dendrocalamopsis beecheyana var. pubescens is native to the southern provinces of China. In this study, the genetic diversity of 17 accessions from 6 populations of Fujian and Guangxi provinces were assessed. Genetic diversity was estimated using ISSR (inter-simple sequence repeat) markers. Sixteen selected primers produced 185 ISSR loci, of which 167 (90.27%) were found to be polymorphic. Dendrogram analyses revealed that the 17 accessions formed six major groups, whil e the six populations were clustered into three major groups. A high genetic diversity was identified at the species level, with the percentage of polymorphic band (PPB), Nei's gene diversity (He) and Shannon's information index (I) was found to be 90.27%, 0.2497, and 0.3949, respectively. In addition, Nei's differentiation coefficient (Gst) was relatively high (0.5399) and a low rate of gene flow (Nm) of 0.4261 was observed. The results clearly show that there is a high degree of genetic variation at the species level and a low degree of genetic variation at the population level. Moreover, ISSR molecular markers could be effectively utilized for the characterization of D. beecheyana var. pubescens accessions and identification of the relationships within populations.

show abstract

Section: Genetic Diversitymentioning

confidence: 84%

Section: Genetic Diversitymentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Genetic Diversity Analysis of Dendrocalamopsis Beecheyana Var. Pubescens Based on Issr Markers

He¹

2019

Appl. Ecol. Env. Res.

View full text Add to dashboard Cite

show abstract

“…From each cultivated plant population, a number of leaves were selected to accept the natural solar radiation. The gas exchange measurement (Nie et al, 2014) was carried out by a portable optical gas analysis system (LI-6400, Li-CorInc, Lincoln NE, USA). The control of the environmental factors in the leaf chamber was 20 °C, the concentration of the gas source…”

Section: Determination Of Photosynthetic Rate Of Leavesmentioning

confidence: 99%

Photosynthetic Physiological Characteristics of Four Medicinal Plants

Ying-jie¹

2019

Appl. Ecol. Env. Res.

View full text Add to dashboard Cite

The objective of this research was the study of research on the photosynthetic characteristics of four kinds of medicinal plants, to provide a reliable reference for the high quality cultivation of these four plants. Methods: the four kinds of medicinal plants were as the experimental materials. The photosynthetic rate, chlorophyll content, carotenoid content and photosynthesis of four medicinal plants were determined. The effects of net photosynthetic rate on photosynthetic effective radiation were studied, and the water use efficiency and transpiration rate were calculated. Results: through the comparison of net photosynthetic rate, it can be seen that the average photosynthetic rate, chlorophyll content and carotene content of the four medicinal plants are very different in the growing season. Conclusion: Platycodon grandiflorum has a wide range of adaptability to light intensity. It can not only utilize intense light efficiently, but also has shade tolerance. It is suggested to be cultivated in an intense light environment; North Atractylodes has high light utilization rate, but poor shade tolerance, it is suitable for cultivation in direct sunlight environment; Carthamustinctorious and Menthahaplocalyxhas have strong shade tolerance, but are not resistant to intense light, and can adopt intercropping.

show abstract

Machine learning, transcriptome, and genotyping chip analyses provide insights into SNP markers identifying flower color in Platycodon grandiflorus

Shin

Subramaniyam

et al. 2021

Sci Rep

View full text Add to dashboard Cite

Bellflower is an edible ornamental gardening plant in Asia. For predicting the flower color in bellflower plants, a transcriptome-wide approach based on machine learning, transcriptome, and genotyping chip analyses was used to identify SNP markers. Six machine learning methods were deployed to explore the classification potential of the selected SNPs as features in two datasets, namely training (60 RNA-Seq samples) and validation (480 Fluidigm chip samples). SNP selection was performed in sequential order. Firstly, 96 SNPs were selected from the transcriptome-wide SNPs using the principal compound analysis (PCA). Then, 9 among 96 SNPs were later identified using the Random forest based feature selection method from the Fluidigm chip dataset. Among six machines, the random forest (RF) model produced higher classification performance than the other models. The 9 SNP marker candidates selected for classifying the flower color classification were verified using the genomic DNA PCR with Sanger sequencing. Our results suggest that this methodology could be used for future selection of breeding traits even though the plant accessions are highly heterogeneous.

show abstract

Assessment of Platycodon grandiflorum germplasm resources from northern Anhui province based on ISSR analysis

Cited by 4 publications

References 15 publications

Genetic Diversity Analysis of Dendrocalamopsis Beecheyana Var. Pubescens Based on Issr Markers

Genetic Diversity Analysis of Dendrocalamopsis Beecheyana Var. Pubescens Based on Issr Markers

Photosynthetic Physiological Characteristics of Four Medicinal Plants

Machine learning, transcriptome, and genotyping chip analyses provide insights into SNP markers identifying flower color in Platycodon grandiflorus

Contact Info

Product

Resources

About