Identification of quantitative trait loci for shank length and growth at different development stages in chicken

Shank length affects chicken leg health and longer shanks are a source of leg problems in heavy-bodied chickens. Identification of quantitative trait loci (QTL) affecting shank length traits may be of value to genetic improvement of these traits in chickens. A genome scan was conducted on 238 F₂ chickens from a reciprocal cross between the Silky Fowl and the White Plymouth Rock breeds using 125 microsatellite markers to detect static and developmental QTL affecting weekly shank length and growth (from 1 to 12 weeks) in chickens. Static QTL affected shank length from birth to time t , while developmental QTL affected shank growth from time t− 1 to time t . Seven static QTL on six chromosomes (GGA2, GGA3, GGA4, GGA7, GGA9 and GGA23) were detected at ages of 2, 3, 4, 5, 6, 7, 9 and 12 weeks, and six developmental QTL on five chromosomes (GGA1, GGA2, GGA4, GGA5 and GGA23) were detected for five shank growth periods, weeks 2–3, 4–5, 5–6, 10–11 and 11–12. A static QTL and a developmental QTL ( SQSL1 and DQSL2 ) were identified at GGA2 (between ADL0190 and ADL0152 ). SQSL1 explained 2.87–5.30% of the phenotypic variation in shank length from 3 to 7 weeks. DQSL2 explained 2.70% of the phenotypic variance of shank growth between 2 and 3 weeks. Two static and two developmental QTL were involved chromosome 4 and chromosome 23. Two chromosomes (GGA7 and GGA9) had static QTL but no developmental QTL and another two chromosomes (GGA1 and GGA5) had developmental QTL but no static QTL. The results of this study show that shank length and shank growth at different developmental stages involve different QTL.     

QTL for percentage of carcass and carcass parts in a broiler x layer cross

An F₂ experimental population, developed from a broiler layer cross, was used in a genome scan of QTL for percentage of carcass, carcass parts, shank and head. Up to 649 F₂ chickens from four paternal half‐sib families were genotyped with 128 genetic markers covering 22 linkage groups. Total map length was 2630 cM, covering approximately 63% of the genome. QTL interval mapping using regression methods was applied to line‐cross and half‐sib models. Under the line‐cross model, 12 genome‐wide significant QTL and 17 suggestive linkages for percentages of carcass parts, shank and head were mapped to 13 linkage groups (GGA1, 2, 3, 4, 5, 7, 8, 9, 11, 12, 14, 18 and 27). Under the paternal half‐sib model, six genome‐wide significant QTL and 18 suggestive linkages for percentages of carcass parts, shank and head were detected on nine chicken linkage groups (GGA1, 2, 3, 4, 5, 12, 14, 15 and 27), seven of which seemed to corroborate positions revealed by the previous model. Overall, three novel QTL of importance to the broiler industry were mapped (one significant for shank% on GGA3 and two suggestive for carcass and breast percentages on GGA14 and drums and thighs percentage on GGA15). One novel QTL for wings% was mapped to GGA3, six novel QTL (GGA1, 3, 7, 8, 9 and 27) and suggestive linkages (GGA2, 4, and 5) were mapped for head%, and suggestive linkages were identified for back% on GGA2, 11 and 12. In addition, many of the QTL mapped in this study confirmed QTL previously reported in other populations.     

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.     

Detection of quantitative trait loci for body weights and conformation traits in Beijing ducks

Quantitative trait loci (QTL) for body weights and conformation traits were detected in Beijing ducks. Traits included body weights (BW) at hatching and at 1-7 weeks of age; lengths of the body (BL), keel bone (KBL), shank (SL) and neck (NL) at 7 weeks of age; width of breast (BTW) at 7 weeks; and girths of shank (SG) and breast (BG) at 7 weeks. Using a half-sib analysis with a multiple-QTL model, linkage between the phenotypic traits and 95 microsatellite markers was studied. Six genome-wide suggestive QTL for three body weights and two conformation traits were identified in CAU1, CAU2, CAU6 and CAU12. Chromosome-wide significant QTL influencing one body weight trait and one conformation trait were located in CAU4 and CAU10 respectively. Twelve chromosome-wide suggestive QTL for six body weight traits and four conformation traits were found in seven linkage groups (CAU1, CAU2, CAU3, CAU4, CAU6, CAU10 and CAU12). In addition, the QTL in CAU6 at 21 and 73 cM jointly affected SG and explained 10.6% of the phenotypic variation. This study provides the first evidence for QTL involved in body weights and conformation traits in ducks, and will stimulate further investigations into the genetic architecture of these traits in this species.     

Quantitative trait loci segregating in crosses between New Hampshire and White Leghorn chicken lines: II. Muscle weight and carcass composition

In order to identify genetic factors influencing muscle weight and carcass composition in chicken, a linkage analysis was performed with 278 F₂ males of reciprocal crosses between the extremely different inbred lines New Hampshire (NHI) and White Leghorn (WL77). The NHI line had been selected for high meat yield and the WL77 for low egg weight before inbreeding. Highly significant quantitative trait loci (QTL) controlling body weight and the weights of carcass, breast muscle, drumsticks–thighs and wings were identified on GGA4 between 151.5 and 160.5 cM and on GGA27 between 4 and 52 cM. These genomic regions explained 13.7–40.2% and 5.3–13.8% of the phenotypic F₂ variances of the corresponding traits respectively. Additional genome‐wide highly significant QTL for the weight of drumsticks–thighs were mapped on GGA1, 5 and 7. Moreover, significant QTL controlling body weight were found on GGA2 and 11. The data obtained in this study can be used for increasing the mapping resolution and subsequent gene targeting on GGA4 and 27 by combining data with other crosses where the same QTL were found.     

Composite interval mapping and mixed models reveal QTL associated with performance and carcass traits on chicken chromosomes 1, 3, and 4

Interval mapping (IM) implemented in QTL Express or GridQTL is widely used, but presents some limitations, such as restriction to a fixed model, risk of mapping two QTL when there may be only one and no discrimination of two or more QTL using both cofactors located on the same and other chromosomes. These limitations were overcome with composite interval mapping (CIM). We reported QTL associated with performance and carcass traits on chicken chromosomes 1, 3, and 4 through implementation of CIM and analysis of phenotypic data using mixed models. Thirty-four microsatellite markers were used to genotype 360 F₂ chickens from crosses between males from a layer line and females from a broiler line. Sixteen QTL were mapped using CIM and 14 QTL with IM. Furthermore, of those 30 QTL, six were mapped only when CIM was used: for body weight at 35 days (first and third peaks on GGA4), body weight at 41 days (GGA1B and second peak on GGA4), and weights of back and legs (both on GGA4). Three new regions had evidence for QTL presence: one on GGA1B associated with feed intake 35–41 d at 404 cM (LEI0107-ADL0183) and two on GGA4 associated with weight of back at 163 cM (LEI0076-MCW0240) and weight gain 35–41 d, feed efficiency 35–41 d and weight of legs at 241 cM (LEI0085-MCW0174). We dissected one more linked QTL on GGA4, where three QTL for BW35 and two QTL for BW41 were mapped. Therefore, these new regions mapped here need further investigations using high-density SNP to confirm these QTL and identify candidate genes associated with those traits.     

Quantitative trait loci for bone traits segregating independently of those for growth in an F2 broiler x layer cross

An F2 broiler-layer cross was phenotyped for 18 skeletal traits at 6, 7 and 9 weeks of age and genotyped with 120 microsatellite markers. Interval mapping identified 61 suggestive and significant QTL on 16 of the 25 linkage groups for 16 traits. Thirty-six additional QTL were identified when the assumption that QTL were fixed in the grandparent lines was relaxed. QTL with large effects on the lengths of the tarsometatarsus, tibia and femur, and the weights of the tibia and femur were identified on GGA4 between 217 and 249 cM. Six QTL for skeletal traits were identified that did not co-locate with genome wide significant QTL for body weight and two body weight QTL did not coincide with skeletal trait QTL. Significant evidence of imprinting was found in ten of the QTL and QTL x sex interactions were identified for 22 traits. Six alleles from the broiler line for weight- and size-related skeletal QTL were positive. Negative alleles for bone quality traits such as tibial dyschondroplasia, leg bowing and tibia twisting generally originated from the layer line suggesting that the allele inherited from the broiler is more protective than the allele originating from the layer.     

Quantitative trait loci associated with body weight and abdominal fat traits on chicken chromosomes 3, 5 and 7

Body weight and abdominal fat traits in meat-type chickens are complex and economically important factors. Our objective was to identify quantitative trait loci (QTL) responsible for body weight and abdominal fat traits in broiler chickens. The Northeast Agricultural University Resource Population (NEAURP) is a cross between broiler sires and Baier layer dams. We measured body weight and abdominal fat traits in the F(2) population. A total of 362 F(2) individuals derived from four F(1) families and their parents and F(0) birds were genotyped using 29 fluorescent microsatellite markers located on chromosomes 3, 5 and 7. Linkage maps for the three chromosomes were constructed and interval mapping was performed to identify putative QTLs. Nine QTL for body weight were identified at the 5% genome-wide level, while 15 QTL were identified at the 5% chromosome-wide level. Phenotypic variance explained by these QTL varied from 2.95 to 6.03%. In particular, a QTL region spanning 31 cM, associated with body weight at 1 to 12 weeks of age and carcass weight at 12 weeks of age, was first identified on chromosome 5. Three QTLs for the abdominal fat traits were identified at the 5% chromosome-wide level. These QTLs explained 3.42 to 3.59% of the phenotypic variance. This information will help direct prospective fine mapping studies and can facilitate the identification of underlying genes and causal mutations for body weight and abdominal fat traits.     

A comprehensive analysis of QTL for abdominal fat and breast muscle weights on chicken chromosome 5 using a multivariate approach

Quantitative trait loci (QTL) influencing the weight of abdominal fat (AF) and of breast muscle (BM) were detected on chicken chromosome 5 (GGA5) using two successive F₂ crosses between two divergently selected 'Fat' and 'Lean' INRA broiler lines. Based on these results, the aim of the present study was to identify the number, location and effects of these putative QTL by performing multitrait and multi-QTL analyses of the whole available data set. Data concerned 1186 F₂ offspring produced by 10 F₁ sires and 85 F₁ dams. AF and BM traits were measured on F₂ animals at slaughter, at 8 (first cross) or 9 (second cross) weeks of age. The F₀, F₁ and F₂ birds were genotyped for 11 microsatellite markers evenly spaced along GGA5. Before QTL detection, phenotypes were adjusted for the fixed effects of sex, F₂ design, hatching group within the design, and for body weight as a covariable. Univariate analyses confirmed the QTL segregation for AF and BM on GGA5 in male offspring, but not in female offspring. Analyses of male offspring data using multitrait and linked-QTL models led us to conclude the presence of two QTL on the distal part of GGA5, each controlling one trait. Linked QTL models were applied after correction of phenotypic values for the effects of these distal QTL. Several QTL for AF and BM were then discovered in the central region of GGA5, splitting one large QTL region for AF into several distinct QTL. Neither the 'Fat' nor the 'Lean' line appeared to be fixed for any QTL genotype. These results have important implications for prospective fine mapping studies and for the identification of underlying genes and causal mutations.     

Quantitative trait loci (QTL) for lean body mass and body length in MRL/MPJ and SJL/J F(2) mice

Studies on the genetic mechanisms involved in the regulation of lean body mass (LBM) in mammals are minimal, although LBM is associated with a competent immune system and an overall good (healthy) body functional status. In this study, we performed a high-density genome-wide scan using 633 (MRL/MPJ × SJL/J) F₂ intercross to identify the quantitative trait loci (QTL) involved in the regulation of LBM. We hypothesized that additional QTL can be identified using a different mouse cross (MRL/SJL cross). Ten QTL were identified for LBM on chromosomes (chrs) 2, 6, 7, 9,13 and 14. Of those ten, QTL on chrs 6, 7 and 14 were exclusive to LBM, while QTL on chrs 4 and 11 were exclusively body length. LBM QTL on chrs 2 and 9 overlap with those of size. Altogether, the ten LBM QTL explained 41.2% of phenotypic variance in F₂ mice. Five significantly interacting loci that may be involved in the regulation of LBM were identified and accounted for 24.4% of phenotypic variance explained by the QTL. Five epistatic interactions, contributing 22.9% of phenotypic variance, were identified for body length. Interacting loci on chr 2 may influence LBM by regulating body length. Therefore, epistatic interactions as well as single QTL effects play an important role in the regulation of LBM. Electronic Publication     

Quantitative trait loci segregating in crosses between New Hampshire and White Leghorn chicken lines: III. Fat deposition and intramuscular fat content

In this study, a genome scan was performed to detect genomic loci that affect fat deposition in white adipose tissues and muscles in 278 F ₂ males of reciprocal crosses between the genetically and phenotypically extreme inbred chicken lines New Hampshire (NHI) and White Leghorn (WL77). Genome‐wide highly significant quantitative trait loci (QTL) influencing fat deposition in white adipose tissues were found on GGA2 and 4. The peak QTL positions for different visceral and subcutaneous white adipose tissues were located between 41.4 and 112.4 Mb on GGA2 and between 76.2 and 78.7 Mb on GGA4, which explained 4.2–10.4% and 4.3–11.6% respectively of the phenotypic F ₂ variances. Contrary to our expectations, the QTL allele descending from the lean line WL77 on GGA4 led to increased fat deposition. We suggest a transgressive action of the obesity allele only if it is not in the genetic background of the line WL77. Additional highly significant loci for subcutaneous adipose tissue mass were identified on GGA12 and 15. For intramuscular fat content, a suggestive QTL was located on GGA14. The analysed crosses provide a valuable resource for further fine mapping of fatness genes and subsequent gene discovery.     

Identification of a major QTL for silique length and seed weight in oilseed rape (Brassica napus L.)

Silique length (SL) and seed weight (SW) are two important yield-related traits controlled by quantitative trait loci (QTL) in oilseed rape (Brassica napus L.). The genetic bases underlying these two traits are largely unknown at present. In this study, we conducted QTL analyses for SL and SW using 186 recombinant inbred lines (RILs) derived from a cross between S1, an EMS mutant with extremely long siliques and large seeds, and S2, an inbred line with regular silique length and seed size. RILs were grown in Wuhan in the 2008/09 (SS09) and 2009/10 (SS10) growing seasons, and mean SL and SW for each line were investigated. Ten non-redundant QTL were identified for SL. Of these, a major QTL, cqSLA9, consistently explained as much as 53.4% of SL variation across environments. The others are minor QTL and individually explained less than 10% of the SL variation. Nine non-redundant QTL were identified for SW. Of which, one major QTL, cqSWA9, explained as much as 28.2% of the total SW variation in the SS09 and SS10 environments. In addition, three additive by additive interactions with small effects were detected for SL, and no interactions were detected for SW. Interestingly, the two major QTL, cqSLA9 for SL and cqSWA9 for SW colocalized in the same chromosomal region and were integrated into a unique QTL, uqA9. The S1 allele at this locus increases both SL and SW, suggesting that uqA9 has pleiotropic effects on both SL and SW. The existence and effect of uqA9 was confirmed in genetically different RILs derived from the cross between S1 and No2127, a resynthesized DH line having regular silique length and seed size. Individuals in one residual heterozygous line for cqSLA9 showed significant difference in silique length. The results in this study revealed that silique length in the S1 mutant is mainly controlled by the cqSLA9 locus, which will be suitable for fine mapping and marker-assisted selection in rapeseed breeding for high yield.     

Genome-Wide Linkage Analysis Identifies Loci for Testicle and Ovary Traits in Chickens

Development of testes or ovaries is critical to chicken breeders. Understanding the genetic mechanisms influencing the development of the testes and ovaries could enhance selection efforts which target reproductive traits. The linkage analysis was conducted within an F2 population derived from Beijing-You chickens and a commercial broiler line. The results have identified one quantitative trait loci (QTL, designated T1) for bilateral testicular weight (TW) and the percentage of TW to carcass weight, and five QTLs (designated O1–O5) for ovary weight (follicle-free, OW) and the percentage of OW to carcass weight. For the testes traits, QTL T1 is located between 6.55 and 8.56 Mb on GGA13. Especially, the gene gamma-amino butyric acid A receptor, alpha 1 (GABRA1) located near the T1 peak. For ovarian traits, QTL O2 was located at 29.31 Mb on GGA7. G protein-coupled receptor 39 (GPR39) present at the O2 peak was expressed at higher levels within the reproductive tract. It is also involved in the regulation of several reproductive functions. Other QTL peaks and the genes’ function in the ovary and testes need to be evaluated. The QTLs and the genes identified in this study could provide valuable information for establishing reproductive traits in chickens, and need further investigation.     

Detection of QTL for immune response to sheep red blood cells in laying hens

The aim of this study is to detect quantitative trait loci (QTL) involved in the regulation of the primary and the secondary immune response to sheep red blood cells (SRBC) in a resource population using microsatellite DNA markers. The F2 resource population originates from a cross of two divergently selected lines for either high (H line) or low (L line) primary antibody response to SRBC. The F2 population consisted of six half-sib families, three families per each of reciprocal crosses. Total antibody titres to SRBC were determined by agglutination in serum from all birds. F2, F1 and F0 generations were genotyped for 170 microsatellite markers, using a whole-genome scan approach. The half-sib and the line-cross analyses were performed to determine QTL regions associated with regulation of the immune response. In the half-sib analysis, four QTL for SRBC primary response have been identified: on GGA3, GGA5, GGA16 and GGA23. No QTL was identified for SRBC secondary response under the half-sib model. In the line-cross analysis, three QTL were identified on GGA10, GGA16 and GGA27 for SRBC primary response and five QTL were identified on GGA6, GGA9, GGA15, GGA16 and GGA27 for SRBC secondary response. Subsequently, the family contribution of individual families to the QTL was analysed. The family with the largest contribution was genotyped with additional microsatellite markers in the QTL region on GGA5. The extended half-sib analysis with additional genotype information results in narrowing down the QTL region on GGA5.     

粳稻蒸煮食味品质相关性状的QTL分析

以沈农265和丽江新团黑谷杂交衍生的重组自交系群体(RILs)为实验材料,对12个粳稻(Oryza sativa subsp.japonica)蒸煮食味品质相关性状进行QTL分析。共检测到29个蒸煮食味品质相关的QTLs,分布于除第8染色体外的11条染色体上,LOD值介于2.50–16.47之间,加性效应值为–132.69–471.85,单个QTL贡献率为10.36%–73.24%。在第6染色体RM508–RM253区域检测到1个蒸煮营养食味品质多效性QTL簇,其中q AC6表型贡献率最大,解释73.24%的表型变异;在第10染色体PM166–RM258区域检测到2个与蒸煮食味品质相关的QTLs,分别是控制口感的q CTS10和综合评分的q CCS10。此外,检测到15个与RVA特征谱相关的QTLs,在第6染色体RM253–RM402区域检测到3个与RVA谱特征值相关的QTLs,表型贡献率均大于12%。这些定位结果将为粳稻蒸煮食味相关品质的分子遗传机理研究奠定基础。     

A new intervarietal linkage map and its application for quantitative trait locus analysis of "gigas" features in bread wheat.

A doubled-haploid (DH) population from an intervarietal cross between the Japanese cultivar 'Fukuho-komugi' and the Israeli wheat line 'Oligoculm' was produced by means of wheat x maize crosses. One hundred seven DH lines were genotyped to construct a simple sequence repeat (SSR) based linkage map with RFLP, RAPD, and inter-simple sequence repeat markers. Out of 570 loci genotyped, 330 were chosen based on their positions on the linkage map to create a "framework" map for quantitative trait locus (QTL) analysis. Among the 28 linkage groups identified, 25 were assigned to the 21 chromosomes of wheat. The total map length was 3948 cM, including the three unassigned linkage groups (88 cM), and the mean interval between loci was 12.0 cM. Loci with segregation distortion were clustered on chromosomes 1A, 4B, 4D, 5A, 6A, 6B, and 6D. After vernalization, the DH lines were evaluated for spike number per plant (SN) and spike length (SL) in a greenhouse under 24-h daylength to assess the "gigas" features (extremely large spikes and leaves) of 'Oligoculm'. The DH lines were also autumn-sown in the field in two seasons (1990-1991 and 1997-1998) for SN and SL evaluation. QTL analysis was performed by composite interval mapping (CIM) with the framework map to detect QTLs for SN and SL. A major QTL on 1AS, which was stable in both greenhouse and field conditions, was found to control SN. This QTL was close to the glume pubescence locus (Hg) and explained up to 62.9% of the total phenotypic variation. The 'Oligoculm' allele restricted spike number. The SSR locus Xpsp2999 was the closest locus to this QTL and is considered to be a possible marker for restricted tillering derived from 'Oligoculm'. Eight QTLs were detected for SL. The largest QTL detected on 2DS was common to the greenhouse and field environments. It explained up to 33.3% of the total phenotypic variation. The second largest QTL on 1AS was common to the greenhouse and the 1997-1998 season. The position of this QTL was close to that for the SN detected on 1AS. The association between SN and SL is discussed.     

Quantitative trait loci for body weight, condition factor and age at sexual maturation in Arctic charr (Salvelinus alpinus): comparative analysis with rainbow trout (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar)

In salmonid fishes, life-history changes may often be coupled to early individual growth trajectories. We identified quantitative trait loci (QTL) for body weight (BW), condition factor (K) and age at sexual maturation (MT) in two full-sib families of Arctic charr (Salvelinus alpinus) to ascertain if QTL for MT were confounded with BW QTL intervals. Three significant QTL for BW, three QTL for MT and one significant QTL for K were identified. A BW QTL with major effect was localized to linkage group 8 (AC-8) and explained more than 34% of the phenotypic variation. Markers on AC-8 have previously been identified as being associated with variation in fork length and BW in this species. Similarly, a major QTL (PEV = 23%) with an influence on the female MT was localized to AC-23. Some of these regions are homologous to those in the genomes of rainbow trout (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar), where similar QTL effects have been detected. Our results also suggest the conservation of MT QTL on the homeologous linkage group pair AC-3/24 in Arctic charr. We further identified chromosomal regions that harbor QTL for multiple traits. In particular, markers on AC-4, -20 and -36 had detectable QTL for all traits studied. Significant MT QTL detected on AC-23, -24, and -27 were autonomous of any BW QTL regions, suggesting that the regulation of MT may be more independent of BW control within this species than in other species of salmonids.     

Fatness QTL on chicken chromosome 5 and interaction with sex

Quantitative trait loci (QTL) affecting fatness in male chickens were previously identified on chromosome 5 (GGA5) in a three-generation design derived from two experimental chicken lines divergently selected for abdominal fat weight. A new design, established from the same pure lines, produced 407 F2 progenies (males and females) from 4 F1-sire families. Body weight and abdominal fat were measured on the F₂ at 9 wk of age. In each sire family, selective genotyping was carried out for 48 extreme individuals for abdominal fat using seven microsatellite markers from GGA5. QTL analyses confirmed the presence of QTL for fatness on GGA5 and identified a QTL by sex interaction. By crossing one F1 sire heterozygous at the QTL with lean line dams, three recombinant backcross 1 (BC1) males were produced and their QTL genotypes were assessed in backcross 2 (BC2) progenies. These results confirmed the QTL by sex interaction identified in the F2 generation and they allow mapping of the female QTL to less than 8 Mb at the distal part of the GGA5. They also indicate that fat QTL alleles were segregating in both fat and lean lines.     

Quantitative trait loci that harbor genes regulating muscle size in (MRL/MPJ x SJL/J) F(2) mice

The genetic mechanisms that determine muscle size have not been elucidated, even though it is a key musculoskeletal parameter that reflects muscle strength. In this study, we performed a high-density genome-wide scan using 633 (MRL/MPJ × SJL/J) F₂ intercross 7-week-old mice to identify quantitative trait loci (QTL) involved in the determination of muscle size. Significant QTL were identified for muscle size and body length. Muscle size (adjusted by body length) QTL were identified on chromosomes 7, 9, 11, 14 (two QTL) and 17, which together explained 19.2% of phenotypic variance in F₂ mice, while body length QTL were located on chromosome 2 (two QTL), 9, 11 and 17 which accounted for 28.3% of phenotypic variance in F₂ mice. Three significant epistatic interactions between different QTL positions from muscle size and body length were identified (P <0.01) on chromosomes 2, 9, 14 and 17, which explained 16.1% of the variance in F₂ mice. Electronic Publication     

Quantitative trait loci for body weight in the intercross between SM/J and A/J mice.

We performed a genome-wide quantitative trait locus (QTL) analysis of body weight at 10 weeks of age in a population of 321 intercross offspring from SM/J and A/J mice, progenitor strains of SMXA recombinant inbred strains. Interval mapping revealed two significant QTLs, Bwq3 (body weight QTL3) and Bwq4, on Chromosomes (Chrs) 8 and 18 respectively, and five suggestive QTLs on Chrs 2, 6, 7, 15 and 19. Bwq3 and Bwq4 explained 6% of the phenotypic variance. The SM/J alleles at both QTLs increased body weight, though the SM/J mouse was smaller than the A/J mouse. On the other hand, four of the five suggestive QTLs detected had male-specific effects on body weight and the remainder was female-specific. These suggestive QTLs explained 5-6% of the phenotypic variance and all the SM/J alleles decreased body weight.