Joint-multiple family linkage analysis predicts within-family variation better than single-family analysis of the maize nested association mapping population

Heredity (Edinb). 2015 Jun;114(6):552-63. doi: 10.1038/hdy.2014.123. Epub 2015 Jan 14.


Quantitative trait locus (QTL) mapping has been used to dissect the genetic architecture of complex traits and predict phenotypes for marker-assisted selection. Many QTL mapping studies in plants have been limited to one biparental family population. Joint analysis of multiple biparental families offers an alternative approach to QTL mapping with a wider scope of inference. Joint-multiple population analysis should have higher power to detect QTL shared among multiple families, but may have lower power to detect rare QTL. We compared prediction ability of single-family and joint-family QTL analysis methods with fivefold cross-validation for 6 diverse traits using the maize nested association mapping population, which comprises 25 biparental recombinant inbred families. Joint-family QTL analysis had higher mean prediction abilities than single-family QTL analysis for all traits at most significance thresholds, and was always better at more stringent significance thresholds. Most robust QTL (detected in >50% of data samples) were restricted to one family and were often not detected at high frequency by joint-family analysis, implying substantial genetic heterogeneity among families for complex traits in maize. The superior predictive ability of joint-family QTL models despite important genetic differences among families suggests that joint-family models capture sufficient smaller effect QTL that are shared across families to compensate for missing some rare large-effect QTL.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Chromosome Mapping / methods*
  • Genetic Linkage*
  • Genetic Markers
  • Genetics, Population
  • Models, Genetic*
  • Quantitative Trait Loci
  • Zea mays / genetics*


  • Genetic Markers