Confirmation of quantitative trait loci affecting fatness in chickens

In this report we describe the analysis of an advanced intercross line (AIL) to confirm the quantitative trait locus (QTL) regions found for fatness traits in a previous study. QTL analysis was performed on chromosomes 1, 3, 4, 15, 18, and 27. The AIL was created by random intercrossing in each generation from generation 2 (G₂) onwards until generation 9 (G₉) was reached. QTL for abdominal fat weight (AFW) and/or percentage abdominal fat (AF%) on chromosomes 1, 3 and 27 were confirmed in the G₉ population. In addition, evidence for QTL for body weight at the age of 5 (BW5) and 7 (BW7) weeks and for the percentage of intramuscular fat (IF%) were found on chromosomes 1, 3, 15, and 27. Significant evidence for QTL was detected on chromosome 1 for BW5 and BW7. Suggestive evidence was found on chromosome 1 for AFW, AF% and IF%, on chromosome 15 for BW5, and on chromosome 27 for AF% and IF%. Furthermore, evidence on the chromosome-wise level was found on chromosome 3 for AFW, AF%, and BW7 and on chromosome 27 for BW5. For chromosomes 4 and 18, test statistics did not exceed the significance threshold.     

Mapping quantitative trait loci affecting fatness and breast muscle weight in meat-type chicken lines divergently selected on abdominal fatness

Quantitative trait loci (QTL) for abdominal fatness and breast muscle weight were investigated in a three-generation design performed by inter-crossing two experimental meat-type chicken lines that were divergently selected on abdominal fatness. A total of 585 F₂ male offspring from 5 F₁ sires and 38 F₁ dams were recorded at 8 weeks of age for live body, abdominal fat and breast muscle weights. One hundred-twenty nine microsatellite markers, evenly located throughout the genome and heterozygous for most of the F₁ sires, were used for genotyping the F₂ birds. In each sire family, those offspring exhibiting the most extreme values for each trait were genotyped. Multipoint QTL analyses using maximum likelihood methods were performed for abdominal fat and breast muscle weights, which were corrected for the effects of 8-week body weight, dam and hatching group. Isolated markers were assessed by analyses of variance. Two significant QTL were identified on chromosomes 1 and 5 with effects of about one within-family residual standard deviation. One breast muscle QTL was identified on GGA1 with an effect of 2.0 within-family residual standard deviation.     

Quantitative trait loci associated with fatness in a broiler–layer cross

An F₂ population established by crossing a broiler male line and a layer line was used to map quantitative trait loci (QTL) affecting abdominal fat weight, abdominal fat percentage and serum cholesterol and triglyceride concentrations. Two genetic models, the line-cross and the half-sib, were applied in the QTL analysis, both using the regression interval method. Three significant QTL and four suggestive QTL were mapped in the line-cross analysis and four significant and four suggestive QTL were mapped in the half-sib analysis. A total of five QTL were mapped for abdominal fat weight, six for abdominal fat percentage and four for triglyceride concentration in both analyses. New QTL associated with serum triglyceride concentration were mapped on GGA5, GGA23 and GG27. QTL mapped between markers LEI0029 and ADL0371 on GGA3 for abdominal fat percentage and abdominal fat weight and a suggestive QTL on GGA12 for abdominal fat percentage showed significant parent-of-origin effects. Some QTL mapped here match QTL regions mapped in previous studies using different populations, suggesting good candidate regions for fine-mapping and candidate gene searches.     

Quantitative trait loci segregating in crosses between New Hampshire and White Leghorn chicken lines: I. egg production traits

A genome scan was performed to detect chromosomal regions that affect egg production traits in reciprocal crosses between two genetically and phenotypically extreme chicken lines: the partially inbred line New Hampshire (NHI) and the inbred line White Leghorn (WL77). The NHI line had been selected for high growth and WL77 for low egg weight before inbreeding. The result showed a highly significant region on chromosome 4 with multiple QTL for egg production traits between 19.2 and 82.1 Mb. This QTL region explained 4.3 and 16.1% of the phenotypic variance for number of eggs and egg weight in the F₂ population, respectively. The egg weight QTL effects are dependent on the direction of the cross. In addition, genome‐wide suggestive QTL for egg weight were found on chromosomes 1, 5, and 9, and for number of eggs on chromosomes 5 and 7. A genome‐wide significant QTL affecting age at first egg was mapped on chromosome 1. The difference between the parental lines and the highly significant QTL effects on chromosome 4 will further support fine mapping and candidate gene identification for egg production traits in chicken.     

Mapping quantitative trait loci regulating chicken body composition traits

Genome scans were conducted on an F₂ resource population derived from intercross of the White Plymouth Rock with the Silkies Fowl to detect QTL affecting chicken body composition traits. The population was genotyped with 129 microsatellite markers and phenotyped for 12 body composition traits on 238 F₂ individuals from 15 full-sib families. In total, 21 genome-wide QTL were found to be responsible for 11 traits, including two newly studied traits of proventriculus weight and shank girth. Three QTL were genome-wide significant: at 499 c m on GGA1 (explained 3.6% of phenotypic variance, P  < 0.01) and 51 c m on GGA5 (explained 3.3% of phenotypic variance, P  < 0.05) for the shank & claw weight and 502 c m on GGA1 (explained 1.4% of phenotypic variance, P  < 0.05) for wing weight. The QTL on GGA1 seemed to have pleiotropic effects, also affecting gizzard weight at 490 c m , shank girth at 489 c m and intestine length at 481 c m . It is suggested that further efforts be made to understand the possible pleiotropic effects of the QTL on GGA1 and that on GGA5 for two shank-related traits.     

Mapping quantitative trait loci affecting chicken body size traits via genome scanning

Body size traits reflect the condition of body development, are always mentioned when a breed is described, and are also targets in breeding programmes. In chicken, there are several reports focused on body size traits, such as shank length, tibia length or bone traits. However, no study was carried out on chest width (CW), chest depth (CD), body slope length (BL) and head width (HW) traits. In this study, genome scans were conducted on an F₂ resource population (238 F₂ individuals from 15 full‐sib families derived from an intercross of the White Plymouth Rock with the Silkies Fowl) to identify quantitative trait loci (QTL) associated with CW, CD, BL and HW from 7 to 12 weeks of age. In total, 21 significant or suggestive QTL were found that affected four body size traits. Four QTL reached 1% genome‐wide significance level: at 297 cM on GGA3 (associated with CW at 9 weeks of age), between 155 and 184 cM on GGA1 (affecting BL traits at 9 and 10 weeks of age), at 22 cM on GGA2 (related with BL traits at 12 weeks of age) and at 36 cM on GGA1 (for HW trait at 8 weeks of age).     

Genetic mapping of quantitative trait loci affecting susceptibility in chicken to develop pulmonary hypertension syndrome

Pulmonary hypertension syndrome (PHS), also referred to as ascites syndrome, is a growth-related disorder of chickens frequently observed in fast-growing broilers with insufficient pulmonary vascular capacity at low temperature and/or at high altitude. A cross between two genetically different broiler dam lines that originated from the White Plymouth Rock breed was used to produce a three-generation population. This population was used for the detection and localization of quantitative trait loci (QTL) affecting PHS-related traits. Ten full-sib families consisting of 456 G2 birds were typed with 420 microsatellite markers covering 24 autosomal chromosomes. Phenotypic observations were collected on 4202 G3 birds and a full-sib across family regression interval mapping approach was used to identify QTL. There was statistical evidence for QTL on chicken chromosome 2 (GGA2), GGA4 and GGA6. Suggestive QTL were found on chromosomes 5, 8, 10, 27 and 28. The most significant QTL were located on GGA2 for right and total ventricular weight as percentage of body weight (%RV and %TV respectively). A related trait, the ratio of right ventricular weight as percentage to total ventricular weight (RATIO), reached the suggestive threshold on this chromosome. All three QTL effects identified on GGA2 had their maximum test statistic in the region flanked by markers MCW0185 and MCW0245 (335-421 cM).     

Quantitative trait loci affecting eggshell traits in an F(2) population

Good eggshell quality is important for both table egg quality and chicken reproductive performance. Weak eggshells cause economic losses in all production steps. Poor eggshell quality also poses increased risk for Salmonella infections. Eggshell quality has been a difficult trait to improve by traditional breeding, as it can be measured only for females and it is difficult and expensive to measure. Breeding for improved shell quality may therefore benefit from the use of marker-assisted selection. In an effort to find markers linked to eggshell quality, we have used an F(2) population of 668 females to map quantitative trait loci (QTL) affecting eggshell traits (eggshell deformation, breaking force, weight). By using 160 microsatellite markers on 27 chromosomes, we found 11 genome-wide and 15 suggestive QTL for shell traits measured at different times during production. Loci affecting the deformation were found on chromosomes 1, 2, 6, 10, 14 and Z. Loci affecting the breaking force were detected on chromosomes 2, 3, 10, 12 and Z. Loci affecting the shell weight were detected on chromosomes 6, 12, 24 and Z. Each QTL explains between 1.5% and 4.6% of the phenotypic variance, adding up to 10-15% of total phenotypic variance explained for the different traits. No epistatic effects were observed between loci affecting eggshell traits. Because the effects for quality are mainly additive, these results provide a basis for further characterization of the loci to identify closely linked markers to be used in marker-assisted selection.     

Quantitative trait loci for performance traits in a broiler × layer cross

An F₂ resource population, derived from a broiler × layer cross, was used to map quantitative trait loci (QTL) for body weights at days 1, 35 and 41, weight gain, feed intake, feed efficiency from 35 to 41 days and intestinal length. Up to 577 F₂ chickens were genotyped with 103 genetic markers covering 21 linkage groups. A preliminary QTL mapping report using this same population focused exclusively on GGA1. Regression methods were applied to line-cross and half-sib models for QTL interval mapping. Under the line-cross model, eight QTL were detected for body weight at 35 days (GGA2, 3 and 4), body weight at 41 days (GGA2, 3, 4 and 10) and intestine length (GGA4). Under the half-sib model, using sire as common parent, five QTL were detected for body weight at day 1 (GGA3 and 18), body weight at 35 days (GGA2 and 3) and body weight at 41 days (GGA3). When dam was used as common parent, seven QTL were mapped for body weight at day 1 (GGA2), body weight at day 35 (GGA2, 3 and 4) and body weight at day 41 (GGA2, 3 and 4). Growth differences in chicken lines appear to be controlled by a chronological change in a limited number of chromosomal regions.     

Quantitative trait loci for red blood cell traits in swine

Haematological traits are essential diagnostic parameters in veterinary practice but knowledge on the genetic architecture controlling variability of erythroid traits is sparse, especially in swine. To identify QTL for erythroid traits in the pig, haematocrit (HCT), haemoglobin (HB), erythrocyte counts (RBC) and mean corpuscular haemoglobin content (MCHC) were measured in 139 F₂ pigs from a Meishan/Pietrain family, before and after challenge with the protozoan pathogen Sarcocystis miescheriana . The pigs passed through three stages representing acute disease, reconvalescence and chronic disease. Forty-three single QTL controlling erythroid traits were identified on 16 chromosomes. Twelve of the QTL were significant at the genome-wide level while 31 were significant at a chromosome-wide level. Because erythroid traits varied with health and disease status, QTL influencing the erythroid phenotypes showed specific health/disease patterns. Regions on SSC5, 7, 8, 12 and 13 contained QTL for baseline erythroid traits, while the other QTL regions affected distinct stages of the disease model. Single QTL explained 9–17% of the phenotypic variance in the F₂ animals. Related traits were partly under common genetic influence. Our analysis confirms that erythroid trait variation differs between Meishan and Pietrain breeds and that this variation is associated with multiple chromosomal regions.     

Mapping of quantitative trait loci affecting eggshell quality on chromosome 9 in an F2 intercross between two chicken lines divergently selected for eggshell strength

Broken and cracked eggshells are major causes of significant economic losses to the egg production industry. The quantitative trait loci (QTL) on chromosome 9 influencing the quality of eggshells were identified by analysing an intercross between two parent lines developed from the same founder population by a two-way selection for eggshell strength with non-destructive deformation conducted over 14 generations. Chromosome-wide highly significant ( P  <   0.01) QTL associated with egg weight (EW), short length of egg (SLE), long length of egg (LLE) and eggshell weight were mapped to the distal region of chromosome 9. Among the QTL affecting EW, SLE and LLE, ovocalyxin-32 was identified as a potential candidate gene influencing eggshell traits. Marker-assisted selection based on these QTL could be used to develop strategies for reducing the breakage and cracking of eggs in commercial layer houses.     

Mapping of quantitative trait loci on porcine chromosome 4

A F₂ population derived from a cross between European Large White and Chinese Meishan pigs was established in order to study the genetic basis of breed differences for growth and fat traits. Chromosome 4 was chosen for initial study as previous work had revealed quantitative trait loci (QTLs) on this chromosome affected growth and fat traits in a Wild Boar × Large White cross. Individuals in the F₂ population were typed for nine markers spanning a region of approximately 124 c m . We found evidence for QTLs affecting growth between weaning and the end of test (additive effect: 43·4 g/day) and fat depth measured in the mid-back position (additive effect: 1·82 mm). There was no evidence of interactions between the QTLs and sex, grandparents or F₁ sires, suggesting that the detected QTLs were fixed for alternative alleles in the Meishan and Large White breeds. Comparison of locations suggests that these QTLs could be the same as those found in the Wild Boar × Large White cross.     

Quantitative trait loci analysis of phytate and phosphate concentrations in seeds and leaves of Brassica rapa

Phytate, being the major storage form of phosphorus in plants, is considered to be an anti-nutritional substance for human, because of its ability to complex essential micronutrients. In the present study, we describe the genetic analysis of phytate and phosphate concentrations in Brassica rapa using five segregating populations, involving eight parental accessions representing different cultivar groups. A total of 25 quantitative trait loci (QTL) affecting phytate and phosphate concentrations in seeds and leaves were detected, most of them located in linkage groups R01, R03, R06 and R07. Two QTL affecting seed phytate (SPHY), two QTL affecting seed phosphate (SPHO), one QTL affecting leaf phosphate and one major QTL affecting leaf phytate (LPHY) were detected in at least two populations. Co-localization of QTL suggested single or linked loci to be involved in the accumulation of phytate or phosphate in seeds or leaves. Some co-localizing QTL for SPHY and SPHO had parental alleles with effects in the same direction suggesting that they control the total phosphorus concentration. For other QTL, the allelic effect was opposite for phosphate and phytate, suggesting that these QTL are specific for the phytate pathway.     

Mapping of quantitative trait loci affecting behaviour in swine

Behavioural indices in vertebrates are under genetic control at least to some extent. In spite of significant behavioural problems in farm animals, information on the genetic background of behaviour is sparse. The aim of this study was to map QTL for behavioural indices in swine under healthy conditions and after infection with Sarcocystis miescheriana , as behaviour can be significantly influenced by disease . This well-described parasite model subsequently leads to acute (day 14 p.i.), subclinical (day 28 p.i.) and chronic disease (day 42 p.i.), allowing the study and comparison of the behaviour of pigs under four different states of health or disease. The study was based on a well-described Pietrain/Meishan F₂ family that has recently allowed the detection of QTL for disease resistance. We have mapped six genome-wide significant and 24 chromosome-wide significant QTL for six behavioural indices in swine. Six of these QTL (i.e. 20% of total QTL) showed effects on behavioural traits of the healthy pigs (day 0). Some of them (QTL on SSC11 and 18) lost influence on behavioural activities during disease, while the effects of others (QTL on SSC5, SSC8) partly remained during the whole experiment, although with different effects on the distinct behavioural indices. The disease model has been of high relevance to detect effects of gene loci on behavioural indices. Considering the importance of segregating alleles and environmental conditions that allow the identification of the phenotype, we conclude that there are indeed QTL with interesting effects on behavioural indices in swine.     

Quantitative trait loci associated with chemical composition of the chicken carcass

Major objectives of the poultry industry are to increase meat production and to reduce carcass fatness, mainly abdominal fat. Information on growth performance and carcass composition are important for the selection of leaner meat chickens. To enhance our understanding of the genetic architecture underlying the chemical composition of chicken carcasses, an F₂ population developed from a broiler × layer cross was used to map quantitative trait loci (QTL) affecting protein, fat, water and ash contents in chicken carcasses. Two genetic models were applied in the QTL analysis: the line‐cross and the half‐sib models, both using the regression interval mapping method. Six significant and five suggestive QTL were mapped in the line‐cross analysis, and four significant and six suggestive QTL were mapped in the half‐sib analysis. A total of eleven QTL were mapped for fat (ether extract), five for protein, four for ash and one for water contents in the carcass using both analyses. No study to date has reported QTL for carcass chemical composition in chickens. Some QTL mapped here for carcass fat content match, as expected, QTL regions previously associated with abdominal fat in the same or in different populations, and novel QTL for protein, ash and water contents in the carcass are presented here. The results described here also reinforce the need for fine mapping and to perform multi‐trait analyses to better understand the genetic architecture of these traits.     

Identification of quantitative trait loci associated with egg quality, egg production, and body weight in an F2 resource population of chickens

Egg production and egg quality are complex sex-limited traits that may benefit from the implementation of marker-assisted selection. The primary objective of the current study was to identify quantitative trait loci (QTL) associated with egg traits, egg production, and body weight in a chicken resource population. Layer (White Leghorn hens) and broiler (Cobb-Cobb roosters) lines were crossed to generate an F2 population of 508 hens over seven hatches. Phenotypes for 29 traits (weekly body weight from hatch to 6 weeks, egg traits including egg, albumen, yolk, and shell weight, shell thickness, shell puncture score, percentage of shell, and egg shell colour at 35 and 55 weeks of age, as well as egg production between 16 and 55 weeks of age) were measured in hens of the resource population. Genotypes of 120 microsatellite markers on 28 autosomal groups were determined, and interval mapping was conducted to identify putative QTL. Eleven QTL tests representing two regions on chromosomes 2 and 4 surpassed the 5% genome-wise significance threshold. These QTL influenced egg colour, egg and albumen weight, percent shell, body weight, and egg production. The chromosome 4 QTL region is consistent with multiple QTL studies that define chromosome 4 as a critical region significantly associated with a variety of traits across multiple resource populations. An additional 64 QTL tests surpassed the 5% chromosome-wise significance threshold.     

Quantitative trait loci for white blood cell numbers in swine

Differential white blood cell counts are essential diagnostic parameters in veterinary practice but knowledge on the genetic architecture controlling variability of leucocyte numbers and relationships is sparse, especially in swine. Total leucocyte numbers (Leu) and the differential leucocyte counts, i.e. the fractions of lymphocytes (Lym), polymorphonuclear leucocytes [neutrophils (Neu), eosinophils (Eos) and basophils (Bas)] and monocytes (Mon) were measured in 139 F₂ pigs from a Meishan/Pietrain family, before and after challenge with the protozoan pathogen Sarcocystis miescheriana for genome-wide quantitative trait loci (QTL) analysis. After infection, the pigs passed through three stages representing acute disease, reconvalescence and chronic disease. Nine genome-wide significant and 29 putative, single QTL controlling leucocyte traits were identified on 15 chromosomes. Because leucocyte traits varied with health and disease status, QTL influencing the leucocyte phenotypes showed specific health/disease patterns. Regions on SSC1, 8 and 12 contained QTL for baseline leucocyte traits. Other QTL regions reached control on leucocyte traits only at distinct stages of the disease model. Two-thirds of the QTL have not been described before. Single QTL explained up to 19% of the phenotypic variance in the F₂ animals. Related traits were partly under common genetic influence. Our analysis confirms that leucocyte trait variation is associated with multiple chromosomal regions.     

Quantitative trait loci mapping in dairy cattle: review and meta-analysis

From an extensive review of public domain information on dairy cattle quantitative trait loci (QTL), we have prepared a draft online QTL map for dairy production traits. Most publications (45 out of 55 reviewed) reported QTL for the major milk production traits (milk, fat and protein yield, and fat and protein concentration (%)) and somatic cell score. Relatively few QTL studies have been reported for more complex traits such as mastitis, fertility and health. The collated QTL map shows some chromosomal regions with a high density of QTL, as well as a substantial number of QTL at single chromosomal locations. To extract the most information from these published records, a meta-analysis was conducted to obtain consensus on QTL location and allelic substitution effect of these QTL. This required modification and development of statistical methodologies. The meta-analysis indicated a number of consensus regions, the most striking being two distinct regions affecting milk yield on chromosome 6 at 49 cM and 87 cM explaining 4.2 and 3.6 percent of the genetic variance of milk yield, respectively. The first of these regions (near marker BM143) affects five separate milk production traits (protein yield, protein percent, fat yield, fat percent, as well as milk yield).     

High resolution mapping and identification of new quantitative trait loci (QTL) affecting susceptibility to Marek's disease

Marek's disease (MD) is a lymphoproliferative disease of chickens that costs the poultry industry approximately $1 billion annually. Genetic resistance to MD is gaining increased attention to augment vaccinal control as disease outbreaks occur more frequently. Previously, analysis of a 272 F2 White Leghorn resource population measured for many MD traits and genotyped for 78 microsatellite markers revealed two and four quantitative trait loci (QTL) with significant and suggestive association, respectively, to one or more MD associated traits. Additional genetic markers have since been scored on the MD resource population to increase QTL resolution and genome coverage. Saturation of four of the QTL regions with 17 markers revealed five new QTL while 32 markers extended the genome coverage by 400 + CM and uncovered three more QTL. QTL analysis by single-point and interval mapping algorithms agreed well when marker saturation was approximately 20 CM or less. Currently 127 genetic markers cover approximately 68% of the genome that contain up to 14 MD QTL associated to one or more MD trait; seven at the significant level and seven at the suggestive level. Individually each QTL accounts for 2-10% of the variation and, in general, resistance was dominant although the resistant allele may come from either parental line. This study suggests that a limited number of genomic regions play a major role in the genetic control of MD resistance. Markers linked to these loci may be useful for selection of MD resistant stock by the poultry industry following verification of the association within their breeding populations.     

Genetic mapping of quantitative trait loci affecting body weight, egg character and egg production in F2 intercross chickens

Phenotypic measurements of chicken egg character and production traits are restricted to mature females only. Marker assisted selection of immature chickens using quantitative trait loci (QTL) has the potential to accelerate the genetic improvement of these traits in the chicken population. The QTL for 12 traits (i.e. body weight (BW), six for egg character, three for egg shell colour and two for egg production) of chickens were identified. An F2 population comprising 265 female chickens obtained by crossing White Leghorn and Rhode Island Red breeds and genotyped for 123 microsatellite markers was used for detecting QTL. Ninety-six markers were mapped on 25 autosomal linkage groups, and 13 markers were mapped on one Z chromosomal linkage group. Eight previous unmapped markers were assigned to their respective chromosomes in this study. Significant QTL were detected for BW on chromosomes 4 and 27, egg weight on chromosome 4, the short length of egg on chromosome 4, and redness of egg shell colour (using the L*a*b* colour system) on chromosome 11. A significant QTL on the Z chromosome was linked with age at first egg. Significant QTL could account for 6-19% of the phenotypic variance in the F2 population.