Quantitative trait loci that control body weight and obesity in an F2 intercross between C57BL/6J and DDD.Cg-Ay mice

I have developed a congenic mouse strain for the A(y) allele at the agouti locus in an inbred DDD/Sgn strain, DDD.Cg-A(y). DDD.Cg-A(y) females are extremely obese and significantly heavier than B6.Cg-A(y) females. The objectives of this study were to determine the genetic basis of obesity in DDD.Cg-A(y) mice, and to determine whether or not their high body weight was due to the presence of DDD background-specific modifiers. I performed quantitative trait locus (QTL) analyses for body weight and body mass index in two types of F(2) mice [F2 A(y) (F(2) mice carrying the A(y) allele) and F(2) non-A(y) (F2 mice without the A(y) allele)] produced by crossing C57BL/6J females and DDD.Cg-A(y) males. The results of the QTL analysis of F(2) A(y) mice were very similar to those obtained for F(2) non-A(y) mice. It was unlikely that the high body weight of DDD.Cg-A(y) mice was due to the presence of specific modifiers. When both F(2) datasets were merged and analyzed, four significant body weight QTLs were identified on chromosomes 6, 9, and 17 (2 loci) and four significant obesity QTLs were identified on chromosomes 1, 6, 9, and 17. Although the presence of DDD background-specific modifiers was not confirmed, a multifactorial basis of obesity in DDD.Cg-A(y) females was thus revealed.     

Quantitative trait locus analysis of plasma cholesterol levels and body weight by controlling the effects of the Apoa2 allele in mice

Colleagues and I previously performed quantitative trait locus (QTL) analysis on plasma total-cholesterol (T-CHO) levels in C57BL/6J (B6) x RR F2 mice. We identified only one significant QTL (Cq6) on chromosome 1 in a region containing the Apoa2 gene locus, a convincing candidate gene for Cq6. Because Cq6 was a highly significant QTL, we considered that the detection of other potential QTLs might be hindered. In the present study, QTL analysis was performed in B6.KK-Apoa2b N(8) x RR F2 mice [B6.KK-Apoa2b N(8) is a partial congenic strain carrying the Apoa2b allele from the KK strain, and RR also has the Apoa2b allele] by controlling of the effects of the Apoa2 allele, for identifying additional QTLs. Although no significant QTLs were identified, 2 suggestive QTLs were found on chromosomes 2 and 3 in place of the effects of the Apoa2 allele. A significant body weight QTL was identified on chromosome 3 (Bwq7, peak LOD score 5.2); its effect on body weight was not significant in previously analyzed B6 x RR F2 mice. Suggestive body weight QTL that had been identified in B6 x RR F2 mice on chromosome 4 (LOD score 3.8) was not identified in B6.KK-Apoa2b N(8) x RR F2 mice. Thus, contrary to expectation, the genetic control of body weight was also altered significantly by controlling of the effects of the Apoa2 allele. The QTL mapping strategy by controlling of the effects of a major QTL facilitated the identification of additional QTLs.     

Apolipoprotein gene polymorphisms as cause of cholesterol QTLs in mice

Quantitative trait locus (QTL) analyses of plasma cholesterol levels were carried out in three sets of F(2) mice that were formed in a 'round-robin' manner from C57BL/6J, KK (-A(y)), and RR strains. Six QTLs were identified on chromosomes 1 (Cq1, Cq2, and Cq6), 3 (Cq3), and 9 (Cq4 and Cq5); of these, Cq2 colocalized with Cq6, and Cq4 colocalized with Cq5. The major candidate gene for Cq2 and Cq6 is Apoa2, and that for Cq4 and Cq5 is Apoa4. The adequacy of polymorphisms in candidate genes as cause of QTLs was investigated in this study. For Apoa2, three different alleles (Apoa2(a), Apoa2(b), and Apoa2(c)) are known. Since there was no significant physiologic difference between Apoa2(a) and Apoa2(c) alleles, previous hypothesis that Apoa2(b) was different from Apoa2(a) and Apoa2(c) in the ability to increase cholesterol levels was further supported. Presumably, G-to-A substitution at nucleotide 84 and/or C-to-T substitution at nucleotide 182 are crucial to make the Apoa2(b) unique. On the other hand, for Apoa4, the most striking polymorphism was the number of Glu-Gln-Ala/Val-Gln repeats in carboxyl end; however, this might not be responsible for QTLs. Instead, a silent mutation, C-to-T substitution at nucleotide 771, was shown to be completely correlated with the occurrence of QTLs in a total of six F(2) intercrosses. Provisionally, but reasonably, these base substitutions are qualified as primary causes that constitute QTL effect. The potential strategy for identifying genes and base substitutions underlying QTLs is discussed.     

Characterization of Cq3, a quantitative trait locus that controls plasma cholesterol and phospholipid levels in mice

Cq3 was identified in C57BL/6J (B6) x KK-Ay F2 mice as a quantitative trait locus (QTL) that controls plasma cholesterol and phospholipid levels, and normolipidemic B6 allele was associated with increased lipids. Cq3 was statistically significant in F2-a/a, but not in F2-Ay/a; probably because the Cq3 effect was obscured by introduction of the Ay allele, which in itself has a strong hyperlipidemic effect. Because the peak LOD score for Cq3 was identified near D3Mit102 (49.7 cM) on chromosome 3, linkage analyses with microsatellite markers located at 49.7 cM were performed in KK x RR F2, B6 x RR F2, and KK x CF1 F2. However, even a suggestive QTL was not identified in any of the three F2. By testing all pairs of marker loci, I found a significant interaction between Cq3 and the Apoa2 locus, and F2 mice with the Apoa2(KK)/Apoa2(KK); D3Mit102(B6)/D3Mit102(B6) genotype had significantly higher cholesterol levels than did F2 mice with other genotypes. The results showed that the ;round-robin' strategy was not always applicable to the search for QTL genes; probably because specific gene-to-gene interaction limited the validity of the strategy to the utmost extent.     

Identification of the modifier locus that suppresses neonatal lethality in (♀DDD × ♂DH- Dh/+) F₁-Dh/+ male mice

Most F(1)-Dh/+ male mice resulting from a cross between inbred DDD strain females and DH-Dh/+ strain males exhibit growth retardation and die during the neonatal period. The lethality is caused by a combination of three independent gene loci, namely the Dh locus on chromosome 1, Grdhq1 locus on the X chromosome, and a putative Y chromosome-linked locus in some strains. Among these loci, Grdhq1 was previously mapped to a distal region of the X chromosome using progeny from♀(♀DDD × ♂DH-+/+) F(1) × ♂DH-Dh/+ mice. In this study, fine mapping of Grdhq1 was performed using progeny of ♀(♀DDD × ♂CAST/EiJ) F(1) ♂DH-Dh/+ mice. Contrary to expectation, Dh/+ male pups carrying the DDD allele at DXMit135 (genetic marker nearest to Grdhq1) survived to weaning. The presence of modifier loci that suppressed the lethality by impeding the action of Grdhq1 was suggested; therefore, a genome-wide scan was performed in the surviving Dh/+ males. As a result, a significant modifier locus was identified on proximal chromosome 11. This in turn suggested that Grdhq1 was located more distally than we had expected; that is, the actual location of Grdhq1 appeared to be near and/or distal to the Mid1 locus. Thus, the results revealed that the neonatal lethality in (DDD × DH-Dh/+) F(1)-Dh/+ males was caused by the fourth gene locus on chromosome 11 in addition to the above-mentioned three gene loci on chromosomes 1, X, and Y.     

Genetic analysis of litter size in mice

We performed quantitative trait locus (QTL) mapping analysis for litter size (total number of pups born and/or number of pups born alive) in 255 backcross mice derived from C57BL/6J and RR/Sgn inbred mice. We identified one significant QTL on chromosome 7 and 4 suggestive QTLs on chromosomes 3, 5, 10 and 13. In addition, two suggestive QTLs were identified on chromosomes 1 and 4 for the number of stillbirth. These results suggested that both litter size and number of stillbirth were heritable traits, although they were controlled by distinct genes. The RR allele was associated with reduced litter size and increased stillbirth at all QTLs. Therefore, RR mothers were observed to have reduced prolificacy in this particular genetic cross.     

Further characterization of diabetes mellitus and body weight loss in males of the congenic mouse strain DDD.Cg-Ay

The A^y allele at the agouti locus causes obesity and promotes linear growth in mice. However, body weight gain stops between 16 and 17 weeks after birth, and then, body weight decreases gradually in DDD.Cg-A^y male mice. Body weight loss is a consequence of diabetes mellitus, which is genetically controlled mainly by a quantitative trait locus (QTL) on chromosome 4. This study aimed to further characterize diabetes mellitus and body weight loss in DDD.Cg-A^y males. The number of β-cells was markedly reduced, and plasma insulin levels were very low in the DDD.Cg-A^y males. Using a backcross progeny of DDD × (B6 × DDD.Cg-A^y) F₁-A^y, we identified one significant QTL for plasma insulin levels on distal chromosome 4, which was coincidental with QTL for hyperglycemia and lower body weight. The DDD allele was associated with decreased plasma insulin levels. When the DDD.Cg-A^y males were housed under three different housing conditions [group housing (4 or 5 DDD.Cg-A^y and DDD males), individual housing (single DDD.Cg-A^y male) and single male housing with females (single DDD.Cg-A^y male with DDD.Cg-A^y or DDD females)], diabetes mellitus and body weight loss were most severely expressed in individually housed mice. Thus, the severity of diabetes and body weight loss in the DDD.Cg-A^y males was strongly influenced by the housing conditions. These results demonstrate that both genetic and nongenetic environmental factors are involved in the development of diabetes mellitus and body weight loss in the DDD.Cg-A^y males.     

A proximal genomic region of mouse chromosome 10 contains quantitative trait loci affecting fatness

Body weight and fatness are quantitative traits of agricultural and medical importance. In previous genome‐wide quantitative trait locus (QTL) analyses, two QTLs for body weight and weight gain at an early postnatal growth period were discovered on mouse chromosome 10 from a gene pool of wild subspecies mice, Mus musculus castaneus. In this study, we developed a congenic strain with an approximately 63‐Mb wild‐derived genomic region on which the two growth QTLs could be located, by recurrent backcrossing to the common inbred strain C57BL/6J. We compared body weights at 1–10 weeks of age, body weight gains at 1–3, 3–6 and 6–10 weeks, internal organ weights and body lengths between the congenic strain developed and C57BL/6J. Unfortunately, no effects of the two growth QTLs on body weights and weight gains were confirmed. However, at least two new QTLs affecting fatness traits were discovered within the introgressed congenic region. The wild‐derived allele at one QTL increased body mass index, whereas at another one it decreased white fat pad weight and adiposity index. Thus, the congenic mouse strain developed here is a useful model animal for understanding the genetic and molecular basis of fat deposition in livestock as well as humans.     

Genetic analysis of low survival rate of pups in RR/Sgn inbred mice

Newborn offspring of the inbred mouse RR/Sgn strain have a low survival rate prior to weaning. We hypothesized that this is a consequence of an inferior nurturing ability of RR/Sgn mothers and that RR/Sgn mothers have a tendency to lose their pups. We performed quantitative trait locus (QTL) mapping for inferior nurturing ability and tendency to lose pups in RR/Sgn mothers. The number of pups was adjusted to 6 per dam on the day of delivery, and the number of surviving pups and their total weight (litter weight) were scored at 12 days after birth. Nurturing ability was evaluated by litter weight, and tendency to lose pups was evaluated by scoring whether or not the mothers lost their pups. For litter weight, we identified one significant QTL on chromosome 4 and three suggestive QTLs on chromosomes 7, 9 and 17. The RR/Sgn allele was associated with lower litter weight at all loci. For the tendency to lose pups, we identified three suggestive QTLs on chromosomes 4, 9 and 16. The RR/Sgn allele was associated with an increased tendency to lose pups at all loci. These results supported our hypothesis that the low survival rate phenotype was attributable, at least in part, to a phenotype whereby mothers display inferior nurturing ability and a tendency to lose pups. Thus, it suggests that these two traits share genetic basis.     

Detection of quantitative trait loci for fat androstenone levels in pigs

A QTL analysis of fat androstenone levels from a three-generation experimental cross between Large White and Meishan pig breeds was carried out. A total of 485 F2 males grouped in 24 full-sib families, their 29 parents and 12 grandparents were typed for 137 markers distributed over the entire porcine genome. The F2 male population was measured for fat androstenone levels at 100, 120, 140, and 160 d of age and at slaughter around 80 kg liveweight. Statistical analyses were performed using two interval mapping methods: a line-cross (LC) regression method, which assumes alternative alleles are fixed in founder lines, and a half- full-sib (HFS) maximum likelihood method, where allele substitution effects were estimated within each half- and full-sib family. Both methods revealed genomewide significant gene effects on chromosomes 3, 7, and 14. The QTL explained, respectively, 7 to 11%, 11 to 15%, and 6 to 8% of phenotypic variance. Three additional significant QTL explaining 4 to 7% of variance were detected on chromosomes 4 and 9 using LC method and on chromosome 6 using HFS method. Suggestive QTL were also obtained on chromosomes 2, 10, 11, 13, and 18. Meishan alleles were associated with higher androstenone levels, except on chromosomes 7, 10, and 13, although 10 and 13 additive effects were near zero. The QTL had essentially additive effects, except on chromosomes 4, 10, and 13. No evidence of linked QTL or imprinting effects on androstenone concentration could be found across the entire porcine genome. The steroid chromosome P450 21-hydroxylase (CYP21) and cytochrome P450 cholesterol side chain cleavage subfamily XIA (CYP11A) loci were investigated as possible candidate genes for the chromosome 7 QTL. No mutation of coding sequence has been found for CYP21. Involvement of a candidate regulatory mutation of CYP11A gene proposed by others can be excluded in our animals.     

Quantitative trait loci for leg weakness traits in a Landrace purebred population

Leg weakness in pigs is a serious problem in the pig industry. We performed a whole genome quantitative trait locus (QTL) analysis to find QTLs affecting leg weakness traits in the Landrace population. Half-sib progeny ( n  = 522) with five sires were measured for leg weakness traits. Whole genome QTL mapping was performed using a half-sib regression-based method using 190 microsatellite markers. No experiment-wide significant QTLs affecting leg weakness traits were detected. However, at the 5% chromosome-wide level, QTLs affecting leg weakness traits were detected on chromosomes 1, 3, 10 and 11 with QTL effects ranging from 0.07 to 0.11 of the phenotypic variance. At the 1% chromosome-wide level, QTLs affecting rear feet score and total leg score were detected on chromosomes 2 and 3 with QTL effects of 0.11 and 0.13 of the phenotypic variance, respectively. On chromosome 3 and 10, some QTLs found in this study were located at nearby positions. The present study is one of the first reports of QTLs affecting fitness related traits such as leg weakness traits, that segregate within the Landrace population. The study also provides useful information for studying QTLs in purebred populations.     

A whole-genome scan for quantitative trait loci affecting teat number in pigs

A whole-genome scan was conducted using 132 microsatellite markers to identify chromosomal regions that have an effect on teat number. For this purpose, an experimental cross between Chinese Meishan pigs and five commercial Dutch pig lines was used. Linkage analyses were performed using interval mapping by regression under line cross models including a test for imprinting effects. The whole-genome scan revealed highly significant evidence for three quantitative trait loci (QTL) affecting teat number, of which two were imprinted. Paternally expressed (i.e., maternally imprinted) QTL were found on chromosomes 2 and 12. A Mendelian expressed QTL was found on chromosome 10. The estimated additive effects showed that, for the QTL on chromosomes 10 and 12, the Meishan allele had a positive effect on teat number, but, for the QTL on chromosome 2, the Meishan allele had a negative effect on teat number. This study shows that imprinting may play an important role in the expression of teat number.     

Mapping QTL for fat area ratios and serum leptin concentrations in a Duroc purebred population

The reduction of extra subcutaneous, intermuscular and abdominal fat is important to increase the carcass lean percentage of pigs. Image analyses of fat area ratios were effective for estimation of separated fat in pig carcasses. Serum concentrations of leptin are useful as physiological predictors of fat accumulation in pigs. The objectives of the present study were to perform a quantitative trait locus (QTL) analysis for fat area ratios and serum leptin concentrations in a Duroc purebred population. Pigs (n = 226 to 538) were measured for fat area ratios of carcass cross‐sections at the fifth to sixth thoracic vertebrae, half body length and last thoracic vertebra using an image analysis system, and serum leptin concentration. In total, animals were genotyped for 129 markers and used for QTL analysis. For fat area ratios, four significant and 12 suggestive QTLs were detected on chromosomes 1, 6, 7, 8, 9, 12 and 13. Significant QTLs were detected on the same region of chromosome 6, which was located near a leptin receptor gene. For serum leptin concentrations, two significant and two suggestive QTLs were detected on chromosomes 6, 9, and 16, and the QTLs on chromosome 6 were also in the same region for fat area ratios.     

Genome-wide linkage and QTL mapping in porcine F2 families generated from Pietrain, Meishan and Wild Boar crosses

Three informative pig F₂ families based on European Wild Boar (W), Meishan (M) and Pietrain (P) crosses have been used for genome‐wide linkage and quantitative trait loci (QTL) analysis. Altogether 129 microsatellites, 56 type I loci and 46 trait definitions (specific to growth, fattening, fat deposition, muscling, meat quality, stress resistance and body conformation) were included in the study. In the linkage maps of M × P, W × P and W × M families, average spacing of markers were 18.4, 19.7 and 18.8 cM, the numbers of informative meioses were 582, 534 and 625, and the total lengths of autosomes measured were 27.3, 26.0 and 26.2 Morgan units, respectively. Maternal maps were on average 1.3 times longer than paternal maps. QTLs contributing more than 3% of F₂ phenotypic variance could be identified at p < 0.05 chromosome‐wide level. Differences in the numbers and positions of QTLs were observed between families. Genome‐wide significant QTL effects were mapped for growth and fattening traits on eight chromosomes (1, 2, 4, 13, 14, 17, 18 and X), for fat deposition traits on seven chromosomes (1, 2, 3, 4, 6, 7 and X), for muscling traits on 11 chromosomes (1, 2, 3, 4, 6, 7, 8, 12, 14, 15 and X), for meat quality and stress resistance traits on seven chromosomes (2, 3, 6, 13, 16, 18 and X), and QTLs for body‐conformation traits were detected on 14 chromosomes. Closely correlated traits showed similar QTL profiles within families. Major QTL effects for meat quality and stress resistance traits were found on SSC6 in the interval RYR1‐A1BG in the W × P and M × P families, and could be attributed to segregation of the RYR1 allele T derived from Pietrain, whereas no effect in the corresponding SSC6 interval was found in family W × M, where Wild Boar and Meishan both contributed the RYR1 allele C. QTL positions were mostly similar in two of the three families for body conformation traits and for growth, fattening, fat deposition and muscling traits, especially on SSC4 (interval SW1073‐NGFB). QTLs with large effects were also mapped on SSC7 in the major histocompatibility complex (MHC) (interval CYP21A2‐S0102) and affected body length, weight of head and many other traits. The identification of DNA variants in genes causative for the QTLs requires further fine mapping of QTL intervals and a positional cloning. However, for these subsequent steps, the genome‐wide QTL mapping in F₂ families represents an essential starting point and is therefore significant for animal breeding.     

Identification of quantitative trait loci affecting female reproductive traits in a multigeneration Meishan-White composite swine population.

A multigeneration crossbred Meishan-White composite resource population was used to identify quantitative trait loci (QTL) for age at first estrus (AP) and the components of litter size: ovulation rate (OR; number of ova released in an estrous period) and uterine capacity (UC). The population was established by reciprocally mating Meishan (ME) and White composite (WC) pigs. Resultant F1 females were mated to either ME or WC boars to produce backcross progeny (BC) of either 3/4 WC 1/4 ME or 1/4 WC 3/4 ME. To produce the next generation (F3), 3/4 WC 1/4 ME animals were mated to 1/4 WC 3/4 ME animals yielding half-blood (1/2 WC 1/2 ME) progeny. A final generation (F4) was produced by inter se mating F3 animals. Measurements for AP and OR were recorded on 101 BC, 389 F3, and 110 F4 gilts, and UC data were from 101 BC and 110 F4 first parity litters. A genomic scan was conducted with markers (n = 157) spaced approximately 20 cM apart. All parental, F1, BC, and F4 animals but only 84 F3 animals were genotyped and included in this study. The QTL analysis fitted a QTL at 1-cM intervals throughout the genome, and QTL effects were tested using approximate genome-wide significance levels. For OR, a significant (E[false positive] < .05) QTL was detected on chromosome 8, suggestive (E[false positive] < 1.0) QTL were detected on chromosomes 3 and 10, and two additional regions were detected that may possess a QTL (E[false positive] < 2.0) on chromosomes 9 and 15. Two regions possessed suggestive evidence for QTL affecting AP on chromosomes 1 and 10, and one suggestive region on chromosome 8 was identified for UC. Further analyses of other populations of swine are necessary to determine the extent of allelic variation at the identified QTL.     

Genetic mapping of the QTL affecting body weight in chickens using a F2 family

1. To identify the quantitative trait loci (QTL) affecting growth in chickens, we carried out QTL analysis on chicken growth traits using a population of 227 F2 crosses between a Satsumadori (slow-growing, light-weight Japanese native breed used as a meat chicken) male and a White Plymouth Rock (early-maturing, heavy weight broiler). 2. We chose 78 microsatellite loci from 331 publicly available on 14 linkage groups, with respect to their utility and location. 3. Two QTLs affecting body weight at 13 and 16 weeks were mapped at 220 cM on chromosome 1 (LOD scores, 2.8 and 4.5, respectively, at 13 and 16 weeks), and at 60 cM on chromosome 2 (LOD scores, 6.2 and 8.1, respectively, at 13 and 16 weeks). 4. The closest loci to the QTLs were LEI71 on chromosome 1 and LMU13 and MCW184 on chromosome 2. 5. The sites of the QTLs agreed closely with those already reported. Therefore, it seems likely that QTLs affecting growth of chickens are located at these sites.     

Genetic linkage mapping of quantitative trait loci for behavioral and neuroendocrine stress response traits in pigs

A QTL analysis of behavioral and neuroendocrine responses to a "novel environment" stress was conducted in a three-generation experimental cross between Meishan and Large White pig breeds. A total of 186 F2 males and 182 F2 females were studied for their behavioral and neuroendocrine reactivity to a novel environment test at 6 wk of age. Locomotion, vocalization, and defecation rate, as well as exploration time, were measured for 10 min. Blood samples were taken immediately before and after the test to measure plasma levels of ACTH, cortisol, and glucose. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using two interval mapping methods: a line-cross regression method, where founder lines were assumed to be fixed for different QTL alleles, and a half-/full-sib maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Both methods revealed a highly significant gene effect for poststress cortisol level (P < 0.001) and a significant effect for basal cortisol level (P < 0.05) at the end of the q arm of chromosome 7, explaining, respectively, 20% and 7% of the phenotypic variance. Meishan alleles are associated with higher cortisol levels and are partially dominant (for poststress levels) over Large White alleles. Other significant gene effects on biological measures were detected on chromosomes 1 and 17 (ACTH response to stress), 3, 5, and 8 (glucose levels). The SSC 17 QTL explains 12% of the phenotypic variance of poststress ACTH levels, with a suggestive evidence of imprinting effects. Meishan alleles are associated with lower poststress ACTH levels. Gene effects of low amplitude only were found for behavioral reactivity traits. Considering the effects of stress neuroendocrine systems on energy fluxes and protein deposition, and the importance of stress reactivity for meat quality and animal welfare, these results open new perspectives for pig selection.     

Detection and characterization of quantitative trait loci for meat quality traits in pigs.

In an experimental cross between Meishan and Dutch Large White and Landrace lines, 785 F2 animals with carcass information and their parents were typed for molecular markers covering the entire porcine genome. Linkage was studied between these markers and eight meat quality traits. Quantitative trait locus analyses were performed using interval mapping by regression under two genetic models: 1) the line-cross approach, where the founder lines were assumed to be fixed for different QTL alleles and 2) a half-sib model where a unique allele substitution effect was fitted within each of the 38 half-sib families. The line-cross approach included tests for genomic imprinting and sex-specific QTL effects. In total, three genome-wide significant and 26 suggestive QTL were detected. The significant QTL on chromosomes 3, 4, and 13, affecting meat color, were only detected under the half-sib model. Failure of the line-cross approach to detect the meat color QTL suggests that the founder lines have similar allele frequencies for these QTL. This study provides information on new QTL affecting meat quality traits. It also shows the benefit of analyzing experimental data under different genetic and statistical models.     

水稻饲料营养含量的QTL定位分析

应用85个SSR标记,对普通野生稻与粳稻台中65为亲本建立的F₂群体进行基因检测,构建了覆盖水稻基因组12条染色体的SSR分子标记连锁图,采用Mapmaker/QTL1.0统计软件对决定水稻饲用营养价值的粗蛋白、粗纤维、粗脂肪、粗灰分、硅酸和可溶性糖含量的基因座位进行了定位分析。结果定位了影响粗蛋白含量的3个QTLs,影响粗脂肪含量的1个QTL,影响可溶性糖含量的3个QTLs,影响硅酸含量的2个QTLs,这9个QTLs分别位于第1,2,4,7,8,9,10和11染色体上。其中主效QTL4个,分别是影响粗脂肪含量的qCEE-1(贡献率56.8%),影响可溶性糖含量的qCWSC-4(贡献率23.1%)和qCWSC-7(贡献率25.0%),影响硅酸含量的qCS-9(贡献率15.9%),其余5个为微效QTL。没有检测到影响粗纤维含量和粗灰分含量的QTL。     

Detection of single nucleotide polymorphisms associated with ultrasonic backfat depth in a segregating Meishan x White Composite population

Multiple genomic scans have identified QTL for backfat deposition across the porcine genome. The objective of this study was to detect SNP and genomic regions associated with ultrasonic backfat. A total of 74 SNP across 5 chromosomes (SSC 1, 3, 7, 8, and 10) were selected based on their proximity to backfat QTL or to QTL for other traits of interest in the experimental population. Gilts were also genotyped for a SNP thought to influence backfat in the thyroxine-binding globulin gene (TBG) on SSC X. Genotypic data were collected on 298 gilts, divided between the F8 and F10 generations of the US Meat Animal Research Center Meishan resource population (composition, one-quarter Meishan). Backfat depths were recorded by ultrasound from 3 locations along the back at approximately 210 and 235 d of age in the F8 and F10 generations, respectively. Ultrasound measures were averaged for association analyses. Regressors for additive, dominant, and parent-of-origin effects of each SNP were calculated using genotypic probabilities computed by allelic peeling algorithms in GenoProb. The association model included the fixed effects of scan date and TBG genotype, the covariates of weight and SNP regressors, and random additive polygenic effects to account for genetic similarities between animals not explained by known genotypes. Variance components for polygenic effects and error were estimated using MTDFREML. Initially, each SNP was fitted (once with and once without parent-of-origin effects) separately due to potential multi-collinearity between regressions of closely linked markers. To form a final model, all significant SNP across chromosomes were included in a common model and were individually removed in successive iterations based on their significance. Across all analyses, TBG was significant, with an additive effect of approximately 1.2 to 1.6 mm of backfat. Three SNP on SSC3 remained in the final model even though few studies have identified QTL for backfat on this chromosome. Two of these SNP exhibited irregular parent-of-origin effects and may not have been detected in other genome scans. One significant SNP on SSC7 remained in the final, backward-selected model; the estimated effect of this marker was similar in magnitude and direction to previously identified QTL. This SNP can potentially be used to introgress the leaner Meishan allele into commercial swine populations.