Fine mapping of a distal chromosome 4 QTL affecting growth and muscle mass in a chicken advanced intercross line. (26th January 2017)

• Record Type: Journal Article
• Authors: Lyu, S.; Arends, D.; Nassar, M. K.; Brockmann, G. A.
• Is Part Of: Animal genetics. Volume 48:Number 3(2017)
• Page Start: 295
• Page End: 302
• Publication Date: 2017-01-26
• Subjects: association analysis -- body composition -- bone mass -- New Hampshire -- single nucleotide polymorphism -- White Leghorn; Animal genetics -- Periodicals; 572.8
• DOI: 10.1111/age.12532
• Languages: English
• ISSNs: 0268-9146

Abstract

Summary: In our previous research, QTL analysis in an F2 cross between the inbred New Hampshire (NHI) and White Leghorn (WL77) lines revealed a growth QTL in the distal part of chromosome 4. To physically reduce the chromosomal interval and the number of potential candidate genes, we performed fine mapping using individuals of generations F10, F11 and F12 in an advanced intercross line that had been established from the initial F2 mapping population. Using nine single nucleotide polymorphism (SNP) markers within the QTL region for an association analysis with several growth traits from hatch to 20 weeks and body composition traits at 20 weeks, we could reduce the confidence interval from 26.9 to 3.4 Mb. Within the fine mapped region, markers rs14490774, rs314961352 and rs318175270 were in full linkage disequilibrium (D′ = 1.0) and showed the strongest effect on growth and muscle mass (LOD ≥ 4.00). This reduced region contains 30 genes, compared to 292 genes in the original region. Chicken 60 K and 600 K SNP chips combined with DNA sequencing of the parental lines were used to call mutations in the reduced region. In the narrowed‐down region, 489 sequence variants were detected between NHI and WL77. The most deleterious variants are a missense variant in ADGRA3 (SIFT = 0.02) and a frameshift deletion in the functional unknown gene ENSGALG00000014401 in NHI chicken. In addition, five synonymous variants were discovered in genes PPARGC1A, ADGRA3, PACRGL, SLIT2 and FAM184B . In our study, the confidence interval and the number of potential genes could be reduced 8‐ and 10‐ fold respectively. Further research will focus on functional effects of mutant genes.