Evidence map›Paper›PMID 42911344›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2027

Optimized DNA Extraction from Coffee Roots Colonized by Arbuscular Mycorrhizal Fungi Using a Commercial Kit.

Lorena Jacqueline Gómez-Godínez, Alejandra Ortiz-Gasca, José Luis Aguirre-Noyola, Magali Ruiz-Rivas, Sergio De Los Santos-Villalobos, Dora Trejo-Aguilar

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Article in Methods in molecular biology (Clifton, N.J.), 2027. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Lorena Jacqueline Gómez-GodínezCentro Nacional de Recursos Genéticos, INIFAP, Tepatitlán de Morelos, Jalisco, Mexico. gomez.lorena@inifap.gob.mx.
Alejandra Ortiz-GascaDoctorado en Micología Aplicada, Centro de Investigación en Micología Aplicada, Universidad Veracruzana, Xalapa, Veracruz, Mexico.
José Luis Aguirre-NoyolaCentro Nacional de Recursos Genéticos, INIFAP, Tepatitlán de Morelos, Jalisco, Mexico.
Magali Ruiz-RivasCampo Experimental Uruapan, INIFAP, Uruapan, Michoacán, Mexico.
Sergio De Los Santos-VillalobosCentro Nacional de Recursos Genéticos, INIFAP, Tepatitlán de Morelos, Jalisco, Mexico.
Dora Trejo-AguilarFacultad de Ciencias Agrícolas campus Xalapa, Universidad Veracruzana, Circuito Gonzalo Aguirre Beltran, s/n, 91090 Zona Universitaria, Xalapa, Veracruz, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The molecular identification of arbuscular mycorrhizal fungi (AMF) from root tissues can often be limited by the co-extraction of polysaccharides, phenolic compounds, and other PCR inhibitors, particularly in woody or highly lignified roots, where cell lysis is also often difficult. Although commercial extraction kits offer standardized workflows and reduce the handling of harmful reagents, the manufacturer's protocols are insufficient for root samples with high levels of secondary metabolites. This protocol describes the optimization of DNA extraction from coffee (Coffea arabica L.) roots colonized by AMF, based on the use of the commercial ZymoBIOMICS™ Quick-DNA fecal/soil Microbe Kit, designed for the rapid and simple isolation of microbial DNA and host cells from fecal and soil samples, incorporating a pre-maceration and pre-digestion step with proteinase K and β-mercaptoethanol. This modification significantly improves yield, DNA integrity, and PCR amplification of Glomeromycota-specific ribosomal markers (SSU/18S).

Indexed as

CoffeaDNA, FungalMycorrhizaePlant RootsPolymerase Chain ReactionSoil MicrobiologyDNA, FungalCoffea arabicaGlomeromycotaOptimization of commercial kitsRoot-associated fungiSSU ribosomal DNA

Identifiers

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Registered trials

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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.