TABLE 2

Assessment of directional bias of allelic effects at trans-eQTL hotspots

ChromosomeMarker position (cM)No. of eQTLaNegativebPositivec% Bay-0d% ShaeP-valuef
I0.011641422286.613.42.37 × 10−26
I61.51353163374.595.52.00 × 10−53
I99.881935114226.473.61.38 × 10−7
I101.881861751194.15.99.52 × 10−41
II0.011202102817485.514.51.06 × 10−172
II13.59143913419893.26.81.35 × 10−291
II22.971821641890.19.96.16 × 10−34
II42.442528525230.299.80
II55.87710107001.498.64.64 × 10−122
III9.143813671496.33.74.68 × 10−89
III72.381622613616.084.07.48 × 10−14
III77.481633013318.481.65.27 × 10−12
IV55.40256255199.60.43.08 × 10−68
V63.541951237263.136.96.14 × 10−7
V66.482612451693.96.15.58 × 10−56
V70.704176934816.583.54.12 × 10−32
V75.512023716518.381.71.32 × 10−14
  • All eQTL with their LRT statistic maxima mapping to a marker at a trans-eQTL hotspot were analyzed for additive-effect estimates contributed by each parental allele. Permutation analysis established 133 eQTL as the significance threshold (α = 0.05) for declaring a significant trans-eQTL hotspot (see materials and methods). Within each hotspot, the number of eQTL with a negative additive-effect estimate (i.e., Bay-0 allele increased transcript level) was compared with the number of eQTL with a positive additive-effect estimate (i.e., Sha allele increased transcript level).

  • a Number of eQTL with LRT statistic maxima located at the marker.

  • b Number of eQTL with a negative additive-effect estimate.

  • c Number of eQTL with a positive additive-effect estimate.

  • d Percentage of transcripts positively influenced by the Bay-0 allele.

  • e Percentage of transcripts positively influenced by the Sha allele.

  • f P-values for χ2 test for significant deviation from expected 50% contribution from each allele.