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De novo sequencing and analysis of Lophophora williamsii transcriptome, and searching for putative genes involved in mescaline biosynthesis

Overview of attention for article published in BMC Genomics, September 2015
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  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

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Title
De novo sequencing and analysis of Lophophora williamsii transcriptome, and searching for putative genes involved in mescaline biosynthesis
Published in
BMC Genomics, September 2015
DOI 10.1186/s12864-015-1821-9
Pubmed ID
Authors

Enrique Ibarra-Laclette, Flor Zamudio-Hernández, Claudia Anahí Pérez-Torres, Victor A. Albert, Enrique Ramírez-Chávez, Jorge Molina-Torres, Araceli Fernández-Cortes, Carlos Calderón-Vázquez, José Luis Olivares-Romero, Alfredo Herrera-Estrella, Luis Herrera-Estrella

Abstract

Lophophora williamsii (commonly named peyote) is a small, spineless cactus with psychoactive alkaloids, particularly mescaline. Peyote utilizes crassulacean acid metabolism (CAM), an alternative form of photosynthesis that exists in succulents such as cacti and other desert plants. Therefore, its transcriptome can be considered an important resource for future research focused on understanding how these plants make more efficient use of water in marginal environments and also for research focused on better understanding of the overall mechanisms leading to production of plant natural products and secondary metabolites. In this study, two cDNA libraries were generated from L. williamsii. These libraries, representing buttons (tops of stems) and roots were sequenced using different sequencing platforms (GS-FLX, GS-Junior and PGM, respectively). A total of 5,541,550 raw reads were generated, which were assembled into 63,704 unigenes with an average length of 564.04 bp. A total of 25,149 unigenes (62.19 %) was annotated using public databases. 681 unigenes were found to be differentially expressed when comparing the two libraries, where 400 were preferentially expressed in buttons and 281 in roots. Some of the major alkaloids, including mescaline, were identified by GC-MS and relevant metabolic pathways were reconstructed using the Kyoto encyclopedia of genes and genomes database (KEGG). Subsequently, the expression patterns of preferentially expressed genes putatively involved in mescaline production were examined and validated by qRT-PCR. High throughput transcriptome sequencing (RNA-seq) analysis allowed us to efficiently identify candidate genes involved in mescaline biosynthetic pathway in L. williamsii; these included tyrosine/DOPA decarboxylase, hydroxylases, and O-methyltransferases. This study sets the theoretical foundation for bioassay design directed at confirming the participation of these genes in mescaline production.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 1%
Chile 1 1%
Unknown 85 98%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 15 17%
Student > Ph. D. Student 14 16%
Researcher 13 15%
Student > Master 10 11%
Student > Doctoral Student 6 7%
Other 12 14%
Unknown 17 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 26%
Biochemistry, Genetics and Molecular Biology 20 23%
Chemistry 8 9%
Pharmacology, Toxicology and Pharmaceutical Science 4 5%
Chemical Engineering 4 5%
Other 7 8%
Unknown 21 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 18 January 2023.
All research outputs
#6,328,614
of 24,076,257 outputs
Outputs from BMC Genomics
#2,548
of 10,900 outputs
Outputs of similar age
#70,237
of 271,361 outputs
Outputs of similar age from BMC Genomics
#72
of 284 outputs
Altmetric has tracked 24,076,257 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 10,900 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 76% 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 271,361 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 73% of its contemporaries.
We're also able to compare this research output to 284 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 74% of its contemporaries.