Evidence map›Paper›PMID 29509991›Full record

ArticlePlant biotechnology journal2018

Use of a draft genome of coffee (Coffea arabica) to identify SNPs associated with caffeine content.

Hue T M Tran, Thiruvarangan Ramaraj, Agnelo Furtado, Leonard Slade Lee, Robert J Henry

Open access · goldAbstract readValidation Study
In one paragraph

Article in Plant biotechnology journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
5.1field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 66 citations in OpenAlex.

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  4. Evolution of the biochemistry underpinning purine alkaloid metabolism in plants.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

Hue T M TranQueensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, St Lucia, Qld, Australia.ORCID 0000-0003-0606-0525
Thiruvarangan RamarajNational Center for Genome Resources (NCGR), Santa Fe, NM, USA.
Agnelo FurtadoQueensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, St Lucia, Qld, Australia.
Leonard Slade LeeQueensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, St Lucia, Qld, Australia.
Robert J HenryQueensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, St Lucia, Qld, Australia.ORCID 0000-0002-4060-0292
The University of Queensland · AUNational Center for Genome Resources · US

Funding

Australian Research Council LP130100376
6 · The paper itself

Abstract

Arabica coffee (Coffea arabica) has a small gene pool limiting genetic improvement. Selection for caffeine content within this gene pool would be assisted by identification of the genes controlling this important trait. Sequencing of DNA bulks from 18 genotypes with extreme high- or low-caffeine content from a population of 232 genotypes was used to identify linked polymorphisms. To obtain a reference genome, a whole genome assembly of arabica coffee (variety K7) was achieved by sequencing using short read (Illumina) and long-read (PacBio) technology. Assembly was performed using a range of assembly tools resulting in 76 409 scaffolds with a scaffold N50 of 54 544 bp and a total scaffold length of 1448 Mb. Validation of the genome assembly using different tools showed high completeness of the genome. More than 99% of transcriptome sequences mapped to the C. arabica draft genome, and 89% of BUSCOs were present. The assembled genome annotated using AUGUSTUS yielded 99 829 gene models. Using the draft arabica genome as reference in mapping and variant calling allowed the detection of 1444 nonsynonymous single nucleotide polymorphisms (SNPs) associated with caffeine content. Based on Kyoto Encyclopaedia of Genes and Genomes pathway-based analysis, 65 caffeine-associated SNPs were discovered, among which 11 SNPs were associated with genes encoding enzymes involved in the conversion of substrates, which participate in the caffeine biosynthesis pathways. This analysis demonstrated the complex genetic control of this key trait in coffee.

Indexed as

Genome, PlantCaffeineCoffeaPolymorphism, Single NucleotideCaffeineArabica coffeeassociationcaffeinegenome annotationgenome assemblysingle nucleotide polymorphism discovery

Identifiers

PMID29509991
PMCPMC6131422
OpenAlexW2793662037

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.