The nature and identification of quantitative trait loci: a community's view

  title={The nature and identification of quantitative trait loci: a community's view},
  author={Oduola Abiola and Joe M. Angel and Philip Avner and Alexander A. Bachmanov and John K. Belknap and Beth Bennett and Elizabeth P. Blankenhorn and David A. Blizard and Valerie J. Bolivar and Gundrun A Brockmann and Kari Johnson Buck and Jean-Francoise Bureau and William L. Casley and Elissa J. Chesler and James M. Cheverud and Gary A. Churchill and Melloni N. Cook and John C. Crabbe and Wim E Crusio and Ariel Darvasi and Gerald de Haan and Peter Dermant and Rebecca W. Doerge and Rosemary Elliot and Charles R. Farber and Lorraine Flaherty and Jonathan Flint and Howard K. Gershenfeld and John P Gibson and Jing Gu and Weikuan Gu and Heinz Himmelbauer and Robert Hitzemann and Hui-Chen Hsu and Kent W. Hunter and Fuad Iraqi and Ritsert C. Jansen and Thomas E. Johnson and Byron C. Jones and Gerd Kempermann and Frank Lammert and Lu Lu and Kenneth F. Manly and Douglas B Matthews and Juan F. Medrano and Margarete Mehrabian and Guy Mittlemann and Beverly A. Mock and Jeffrey S. Mogil and Xavier Montagutelli and Grant Morahan and John D. Mountz and Hiroki Nagase and Richard S. Nowakowski and Bruce F. O’Hara and Alexander Osadchuk and Beverly J. Paigen and Abraham A. Palmer and Jeremy Peirce and Daniel Pomp and Michael Rosemann and Glenn D. Rosen and Leonard C. Schalkwyk and Ze’ev Seltzer and Stephen H. Settle and Kazuhiro Shimomura and Siming Shou and James M. Sikela and Linda D Siracusa and Jimmy L. Spearow and Cory Teuscher and David W. Threadgill and Linda A. Toth and Ayo A. Toye and Csaba Vad{\'a}sz and Gary van Zant and Edward K. Wakeland and Robert W. Williams and Huang-Ge Zhang and Fei Zou},
  journal={Nature Reviews Genetics},
This white paper by eighty members of the Complex Trait Consortium presents a community's view on the approaches and statistical analyses that are needed for the identification of genetic loci that determine quantitative traits. Quantitative trait loci (QTLs) can be identified in several ways, but is there a definitive test of whether a candidate locus actually corresponds to a specific QTL? 

Genomics of the future: identification of quantitative trait loci in the mouse.

New tools such as genomic sequence, clone libraries, and new genomic-based methods offer new approaches to identify genes important in complex traits, and how these new tools and approaches will improve the ability to discover the genes important to human disease is reviewed.

Haplotyping a Quantitative Trait with a High-Density Map in Experimental Crosses

A statistical model for detecting and characterizing the nucleotide structure and organization of haplotypes that underlie QTL responsible for a quantitative trait in an F2 pedigree is developed and is flexible to be extended to model a complex network of genetic regulation that includes the interactions between different haplotypes and between haplotype and environments.

Complex trait approaches to the analysis of behaviour in the mouse

Mouse, human and other mammalian genetics has had most of its successes in identifying genes for traits with Mendelian inheritance, but identifying the responsible genes for these complex traits remains extremely difficult, but methods and resources are changing quickly.

Mapping Quantitative Trait Loci in Multiple Populations of Arabidopsis thaliana Identifies Natural Allelic Variation for Trichome Density

This work provides QTL mapping data for trichome density from four recombinant inbred mapping populations of Arabidopsis thaliana and suggests that the use of multiple populations holds great promise for better understanding the genetic architecture of natural variation.

Quantitative genetic variation: a post-modern view.

Molecular analysis of QTL suggests that coding variants underlie a fraction of quantitative variation and that variants that affect gene expression have a substantial role, supported by genomic experiments that combine expression profiling with classical genetic mapping approaches to reveal a remarkable wealth of quantitative heritable variation in the transcriptome.

Establishment of “The Gene Mine”: a resource for rapid identification of complex trait genes

The establishment of an experimental genetic reference population, the Collaborative Cross, in which both genetic diversity and mapping power are maximized, is described, which will be a powerful resource for characterization of essentially any mouse phenotype that has a genetic basis.

Quantitative Trait Locus (QTL) Isogenic Recombinant Analysis: A Method for High-Resolution Mapping of QTL Within a Single Population

This work presents an alternative method that significantly speeds up QTL fine mapping by using one segregating population, focusing at an early stage on the informative individuals in the population only, and the efforts in population genotyping and phenotyping are significantly reduced as compared to prior methods.

Limitation of Number of Strains and Persistence of False Positive Loci in QTL Mapping Using Recombinant Inbred Strains

The results indicated that studies using RI strains of less than 30 in general have a higher probability of failing to detect reliable QTL, and thousands of reported QTL from studies of RI strains may need to be double-checked for accuracy before proceeding to causal gene identification.

Gene Expression Profiling as a Tool for Positional Cloning of Genes-Shortcut or the Longest Way Round

This review uses the identification of quantitative trait loci in arthritis animal models as an illustrative example that “very likely candidate genes” identified by genomic/proteomics is not necessarily the same as true QTL underlying genes.

Average semivariance yields accurate estimates of the fraction of marker-associated genetic variance and heritability in complex trait analyses

The accuracy of statistical methods for estimating the fraction of marker-associated genetic variance (p) and heritability for large-effect loci underlying complex phenotypes, and it is found that commonly used statistical methods overestimate p and .



Enabling population and quantitative genomics.

The set of community-wide genetic and molecular resources, including panels of specific types of inbred lines and high density resequencing and SNP detection, that will facilitate studies of quantitative traits to the nucleotide level are discussed.

The roads from phenotypic variation to gene discovery: mutagenesis versus QTLs

In model organisms, chemical mutagenesis provides a powerful alternative to natural, polygenic variation (for example, quantitative trait loci (QTLs)) for identifying functional pathways and complex

The genetic architecture of quantitative traits.

  • T. Mackay
  • Biology
    Annual review of genetics
  • 2001
Complete genome sequences and improved technologies for polymorphism detection will greatly advance the genetic dissection of quantitative traits in model organisms, which will open avenues for exploration of homologous QTL in related taxa.

Finding Genes That Underlie Complex Traits

This work proposes standards for proof of gene discovery in complex traits and evaluates the nature of the genes identified to date, and demonstrates the insights that can be expected from the accelerating pace of geneiscovery in this field.

Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results

Specific standards designed to maintain rigor while also promoting communication are proposed for the interpretation of linkage results in genetic studies under way for many complex traits.

Permutation tests for multiple loci affecting a quantitative character.

Two extensions of the permutation-based method for estimating empirical threshold values are presented, which yield critical values that can be used to construct tests for the presence of minor QTL effects while accounting for effects of known major QTL.

Analysing complex genetic traits with chromosome substitution strains

This work describes a different approach in which a panel of chromosome substitution strains (CSSs) is used for QTL mapping, and discusses the construction, applications and advantages of CSSs compared with conventional crosses for detecting and analysing QTLs, including those that have weak phenotypic effects.

Quantitative genetics and mouse behavior.

The mouse has proven to be a superb model in which to investigate the genetic basis for quantitative differences in complex behaviors and to map the chromosomal regions that regulate variation with the goal of eventually identifying the gene polymorphisms that reside in these regions.

High-resolution mapping of quantitative trait loci in outbred mice

Using the HS mice, an outbred stock of mice for which the entire genealogy is known, a QTL influencing a psychological trait in mice is mapped to a 0.8-cM interval on chromosome 1, which makes QTLs accessible to positional cloning.


The development of seven recombinant-inbred (RI) strains at eight histocompatibility (H) loci and the use of such information in identifying H loci, searching for H gene function, and assisting linkage testing procedures is described.