Evidence map›Paper›PMID 25772476›Full record

ReviewPhysics of life reviews2015

Mapping complex traits as a dynamic system.

Lidan Sun, Rongling Wu

Abstract readReview
In one paragraph

Review in Physics of life reviews, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Graph statistics theory of individualized quantitative genetics under haplotype-resolved genome assembly.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Article
  4. Article
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  7. Review
  8. Article
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  11. Competition-cooperation mechanism betweenFrontiers in microbiology · 2023
    Article
  12. The genetic architecture of trait covariation inFrontiers in plant science · 2023
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Lidan SunNational Engineering Research Center for Floriculture, College of Landscape Architecture, Beijing Forestry University, Beijing 100083, China; Center for Statistical Genetics, Departments of Public Health Sciences and Statistics, The Pennsylvania State University, Hershey, PA 17033, USA.
Rongling WuCenter for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China; Center for Statistical Genetics, Departments of Public Health Sciences and Statistics, The Pennsylvania State University, Hershey, PA 17033, USA. Electronic address: rwu@bjfu.edu.cn.

Funding

Data Coordinating Center for the NHLBI Asthma Network (AsthmaNet)U10HL098115 · NHLBI · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI MAUGER, DAVID T. · 2009 to 2015
$57.6M
Penn State Clinical and Translational Science InstituteUL1TR000127 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI SINOWAY, LAWRENCE I · 2012 to 2015
$17.1M
Constitutive and Agent-Based Multiscale Models to Improve Vein Graft SurvivalU01HL119178 · NHLBI · UNIVERSITY OF FLORIDA · PI BERCELI, SCOTT A, GARBEY, MARC · 2013 to 2018
$2.7M
NCATS NIH HHS UL1 TR000127NHLBI NIH HHS 1U10HL098115NHLBI NIH HHS U01 HL119178NHLBI NIH HHS U10 HL098115
6 · The paper itself

Abstract

Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a "system" in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states.

Indexed as

AlgorithmsChromosome MappingModels, GeneticQuantitative Trait LociSystems BiologyComputational BiologyGene-Environment InteractionGenotypeHumansPhenotypePlantsComplex traitFunctional mappingGenetic mappingNetwork mappingQuantitative trait lociSystems mapping

Identifiers

PMID25772476
PMCPMC5467743

What OpenQuestion holds

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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.