Fine mapping of a distal chromosome 4 QTL affecting growth and muscle mass in a chicken advanced intercross line

Abstract

In our previous research, QTL analysis in an F 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 F , F and F in an advanced intercross line that had been established from the initial F 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.

Reducing the interval of a growth QTL on chromosome 4 in laying hens

“…In a previous study, we found a highly significant QTL (3.4 Mb, from 73 629 630 to 77 032 597 bp) on chicken chromosome (GGA) 4 affecting growth in an advanced intercross population (AIL) produced from an initial cross between an inbred New Hampshire line (NHI) and White Leghorn (WL77) line (Lyu et al . ). In the current study, a purebred high‐performing white layer line (WLA) with White Leghorn origin was used (Lieboldt et al .…”

“…To better overlay the results of the current results in WLA population with the previous study in the NHI × WL77 AIL, the top marker in the AIL study—rs314961352 at 75 451 915 bp on GGA4—was genotyped in the WLA population using allele‐specific PCR, as described previously (Lyu et al . ). Analysis of genotypes for this marker in relation to growth traits further confirmed the significant effect on daily weight gain from 8 to 14 weeks in the WLA population (LOD = 5.71; Table ).…”

“…The encoding genes ligand‐dependent nuclear receptor corepressor like protein ( LCORL ), non‐SMC condensin I complex subunit G ( NCAPG ), LIM domain binding protein 2 ( LDB2 ), transmembrane anterior posterior transformation protein 1 homolog ( TAPT1 ), prominin 1 ( PROM1 ), fibroblast growth factor binding protein 1 and 2 ( FGFBP1 and FGFBP2 respectively) and CD38 molecule ( CD38 ), which we had previously suggested as potential genes for chicken growth, are located in the identified narrowed down interval on GGA4 (Lyu et al . ). It is worth noting that the LCORL‐NCAPG locus has been identified as a locus associated with body size in humans, cattle and horses (Soranzo et al .…”

Genomic approaches and bioinformatics tools to identify genomic regions for economic traits and their applications in chicken breeding programs

“…Genotyping and sequencing: Genome-wide linkage analysis using 123 microsatellite (short sequence repeats; SSR) and single nucleotide polymorphism (SNP) loci were sued to map QTL covering 25 chromosomes (for detail see Goraga et al 2012;Nassar et al 2012Nassar et al , 2015. Chicken 60K and 600K SNP chips as well as whole genome sequencing were used to fine map and characterize the major growth QTL in the distal part of chromosome 4 (for detail see Lyu et al 2017).…”

“…Pairwise tests of LD were performed for used markers in every generation using the SHESIS software platform (http://analysis.biox.cn/myAnalysis.php). We used the LME4 package in R (version 3.1.3) to perform the association analysis between genotypes and growth or body composition traits (see Lyu et al 2017 for detail).…”