Reference
Sequential congenic segment analysis:
The authors propose an alternative to 'common segment' congenic strain analysis to identify QTL. They have proposed calling the alternative method 'sequential' anaylsis. It is based on a unique principal of QTL analysis where each strain, corresponding to a single genotype, is tested individually for QTL effects rather than testing the congenic panel collectively for common effects across heterogeneous backgrounds.
The sequential method is based on comparing phenotypes for sequential pairs of congenic strains, beginning with the strain with the shortest congenic segment and the host strain, and then in a stepwise fashion to strains with progressively longer, overlapping congenic segments. If the phenotypes for the strain with the shortest congenic segment and the host strain differ significantly, the conclusion is that at least one QTL maps to the congenic segment. Next, the congenic strain with the next longer, overlapping segment is compared to the previous congenic strain. If the introduced segment has a QTL the phenotypes for the first and second congenic strains will differ significantly, assigning a QTL to the chromosome segment that differs between the two strains. The process is repeated until each strain in the panel has been tested once and only once.
A panel of 15 congenic strains was derived from the C57BL/6J-Chr6A/J/NaJ chromosome substitution strain (CSS-A6);
a panel of 9 congenic strains was derived from the C57BL/6J-Chr10A/J/NaJ chromosome substitution strain (CSS-A10); and
a panel of 7 congenic strains derived from C57BL/6J-Chr13A/J/NaJ chromosome substitution strains (CSS-A13). Each panel collectively spans the length of the chromosome, and the congenic segments are bounded on one end by a telomere, except of 6C15 and 13C25 strains.
Experiment
For the CSS-A6 and the CSS-A10 congenic panels five traits related to diet-induced obesity and metabolic disease were studied. Males from the two congenic panels as well as the C57BL/6J host and the A/J donor strains were weaned at 3 weeks of age. At 35 days old they were placed on either a high fat, simple-carbohydrate diet or a low-fat complex-carbohydrate diet for app 100 days; at which point they were weighed and various metabolic traits were measured. Body mass index (BMI) was the focus for the CSS-A6 panel and blood gluscose (GLU) and insulin levels as well as HOMA for the CSS-A10 panel. Timing of vaginal puberty (age of vaginal opening, VO) and body weight (BW) at VO for females were the focus of the CSS-A13 strain and the seven congenic strains in the CSS-A13 panel.
The sequential method provided unambiguous evidence for four QTL on substituted chromosome 10:
Fig.1.B. - The significant difference between 10C1 (B6.A-rs29331213/10C1Na) and C57BL/6J revealed a QTL, Gluq4 (blood glucose QTL 4) in the A/J derived segment in the 10C1 strain.
The significantly elevated glucose level in 10C2 (B6.A-(rs13480792-rs29331213)/10C2Na versus 10C1 identified a QTL, Gluq3 (blood glucose QTL 3) in the congenic segment unique to the 10C2 strain between markers at 120 and 126 Mb.
The reduced glucose level in 10C6 (B6.A-(D10Mit230-rs29331213)/10C6Na) compared with 10C5 (B6.A-(D10Mit70-rs29331213)/10C5Na) evidenced a third QTL, Gluq2 (blood glucose QTL 2) between markers at 92 and 104 Mb.
The elevated glucose level in 10C7 (B6.A-(rs13480651-rs29331213)/10C7Na) compared with 10C6 evidenced a fourth QTL Gluq1 (blood glucose QTL 1 ) between marker 68 and 92 Mb.
Comparison p values for Gluq1-4 Fig.1, B.
Fig.1.E. - Also in the CSS-A10 panel the plasma cholesterol levels differed significantly between the panel strains and C57BL/6J. The sequential method provided unambiguous evidence for four QTL:
The significant difference between 10C1 (B6.A-rs29331213/10C1Na) and C57BL/6J located Pcholq1 (plasma cholesterol QTL 1) in the segment distal to 126 Mb.
The significantly higher plasma cholsterol for 10C2 (B6.A-(rs13480792-rs29331213)/10C2Na compared with 10C1 revealed a second QTL, Pcholq2 (plasma cholesterol QTL 2) in the segment that was unique to the 10C2 strain between markers 120 and 126 Mb.
Significantly lower cholsterol levels between strains 10C5 (B6.A-(D10Mit70-rs29331213)/10C5Na) and 10C6 (B6.A-(D10Mit230-rs29331213)/10C6Na) provided evidence for a third QTL, Pcholq3 (plasma cholesterol QTL 3) between markers at 82 and 103 Mb on congenic segment 10C6.
The fourth QTL, Pcholq4 (plasma cholesterol QTL 4) was identified in the differences between strains 10C7 (B6.A-(rs13480651-rs29331213)/10C7Na) and 10C6 (B6.A-(D10Mit230-rs29331213)/10C6Na) between markers at 67 and 89 Mb on congenic segment 10C7, which increased the cholesterol levels.
Fig.1.C. - Also in the CSS-A10 congenic panel the INS level in CSS-A10 was reduced sixfold compared to that in C57BL/6J. There was compelling evidence for two QTL.
The significant difference between 10C3 (B6.A-(D10Mit180-rs29331213)/10C3Na) and 10C4 (B6.A-(rs29367042-rs29331213)/10C4Na) provided evidence (p=0.02) for QTL Insq1 (insulin QTL 1) mapping between marker at 104 and 120 Mb in congenic segment 10C4.
The differences between 10C5 (B6.A-(D10Mit70-rs29331213)/10C5Na) and 10C6 (B6.A (D10Mit230-rs29331213)/10C6Na) reveals evidence of another QTL (p=0.009), Insq2 (insulin QTL 2) in congenic segment 10C6 between 92 and 104 Mb.
Curator Note: Insq1 (J:66233) and Insq2 (J:64138) were previously mapped using different mapping populations than use here. We consider the current study a separate mapping study mapping unique QTL which we have named Insq12 and Insq13, respectively.
Fig.1 D. - The HOMA (homeostatic model assessment) level in CSS-A10 congenic panel was significantly reduced relative to that of C57BL/6J, suggesting at least one QTL on Chr 10. The sequential method revealed strong evidence for three QTL, Homaq1-3.
In the 10C1 (B6.A-(rs29331213/10C1Na) comparison with C57BL/6J, Homaq1 (p=0.02) is located in the most telomeric interval, telomeric to the marker at 126 Mb in congenic segment 10C1.
The significantly lower HOMA in 10C4 (B6.A-(rs29367042-rs29331213)/10C4Na) versus 10C3 (B6.A-(D10Mit180-rs29331213)/10C3Na) reveals Homqa2 (p=0.04) in the segment between markers at 104 and 118 Mb. which is unique between the two strains.
The still lower HOMA in 10C6 (B6.A-(D10Mit230-rs29331213)/10C6Na) compared to 10C5 (B6.A-(D10Mit70-rs29331213)/10C5Na) revealed Homaq3 (p=0.005)in the unique segment in the 10C6 strain between markers 82 and 103 Mb.
With these results the authors conclude that the sequential method performs better than the common-segment, interval mapping and multiple linear regression methods.
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