Evidence map›Paper›PMID 31114935›Full record

ReviewScience China. Life sciences2019

Sequencing XMET genes to promote genotype-guided risk assessment and precision medicine.

Yaqiong Jin, Geng Chen, Wenming Xiao, Huixiao Hong, Joshua Xu, Yongli Guo, Wenzhong Xiao, Tieliu Shi, Leming Shi, Weida Tong and 1 more

Open access · greenAbstract readReview
In one paragraph

Review in Science China. Life sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 20% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
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

11 authors at 7 institutions in 2 countries.

Yaqiong JinBeijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China.
Geng ChenCenter for Bioinformatics and Computational Biology, and the Institute of Biomedical Sciences, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
Wenming XiaoNational Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
Huixiao HongNational Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
Joshua XuNational Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
Yongli GuoBeijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 100045, China.
Wenzhong XiaoDepartment of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA.
Tieliu ShiCenter for Bioinformatics and Computational Biology, and the Institute of Biomedical Sciences, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
Leming ShiState Key Laboratory of Genetic Engineering, School of Life Sciences and Cancer Center; Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, 200433, China.
Weida TongNational Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
Baitang NingNational Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA. baitang.ning@fda.hhs.gov.
United States Food and Drug Administration · USEast China Normal University · CNNational Center for Toxicological Research · USBeijing Children’s Hospital · CNCapital Medical University · CNFudan University Shanghai Cancer Center · CNMassachusetts General Hospital · US

Funding

Intramural FDA HHS FD999999
6 · The paper itself

Abstract

High-throughput next generation sequencing (NGS) is a shotgun approach applied in a parallel fashion by which the genome is fragmented and sequenced through small pieces and then analyzed either by aligning to a known reference genome or by de novo assembly without reference genome. This technology has led researchers to conduct an explosion of sequencing related projects in multidisciplinary fields of science. However, due to the limitations of sequencing-based chemistry, length of sequencing reads and the complexity of genes, it is difficult to determine the sequences of some portions of the human genome, leaving gaps in genomic data that frustrate further analysis. Particularly, some complex genes are difficult to be accurately sequenced or mapped because they contain high GC-content and/or low complexity regions, and complicated pseudogenes, such as the genes encoding xenobiotic metabolizing enzymes and transporters (XMETs). The genetic variants in XMET genes are critical to predicate inter-individual variability in drug efficacy, drug safety and susceptibility to environmental toxicity. We summarized and discussed challenges, wet-lab methods, and bioinformatics algorithms in sequencing "complex" XMET genes, which may provide insightful information in the application of NGS technology for implementation in toxicogenomics and pharmacogenomics.

Indexed as

Computational BiologyGene Expression Regulation, DevelopmentalGenome, HumanGenotypeHigh-Throughput Nucleotide SequencingHumansMembrane Transport ProteinsPrecision MedicinePromoter Regions, GeneticRisk AssessmentSequence Analysis, DNAXenobioticsMembrane Transport ProteinsXenobioticsnext generation sequencingpharmacogenomicsprecision medicinetoxicogenomicsxenobiotic metabolizing enzymes and transporters

Identifiers

PMID31114935
PMCPMC6612563
OpenAlexW2945510530

What OpenQuestion holds

Textmetadata
LicenceTDM
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.