Abstract
While the identification of causal genes of quantitative trait loci (QTL) remains a difficult problem in the post-genome era, the number of QTL continues to accumulate, mainly identified using the recombinant inbred (RI) strains. Over the last decade, hundreds of publications have reported nearly a thousand QTL identified from RI strains. We hypothesized that the inaccuracy of most of these QTL makes it difficult to identify causal genes. Using data from RI strains derived from C57BL/6J (B6) X DBA/2J (D2), we tested the possibility of detection of reliable QTL with different numbers of strains in the same trait in five different traits. Our results indicated that studies using RI strains of less than 30 in general have a higher probability of failing to detect reliable QTL. Errors in many studies could include false positive loci, switches between QTL with small and major effects, and missing the real major loci. The similar data was obtained from a RI strain population derived from a different pair of parents and a RI strain population of rat. Thus, thousands of reported QTL from studies of RI strains may need to be double-checked for accuracy before proceeding to causal gene identification.
Highlights
Different approaches have been tried to improve and simplify the quantitative trait loci (QTL) mapping and candidate selection
Number of strains testing To test the minimal number of recombinant inbred (RI) strains required to produce the reproducible QTL, we conducted a series of analysis with data of TNFa cytokine expression levels measured two days after infection with H5N1 influenza A virus (GeneNetwork ID: 12971; [12]) of 43 BXD strains, two parental strains, and an F1
Minimum number of RI strains for precisely detection of QTL for TNFa cytokine expression levels
Summary
Different approaches have been tried to improve and simplify the QTL mapping and candidate selection. It is well known that a significant difference exists between recombinant inbred (RI) strains and available standard inbred strains currently in the Jackson laboratory (http://www.jax.org/) and other mouse resource centers. Both phenotypic traits and genomic regions of RI strains can be tracked down to one of the two parental strains. In 2005, Ioannidis used statistic simulation showing that for most study designs and settings, it is more likely for a research claim to be false than true [5] because of the sample sizes and experimental variations While it received much attention, Goodman and Greenland [6] pointed out that the model employed in the paper constitutes a ‘‘proof’’ that most published medical research claims are false
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