A molecular genome scan analysis to identify chromosomal regions influencing economic traits in the pig. I. Growth and body composition

Genome scans can be employed to identify chromosomal regions and eventually genes (quantitative trait loci or QTL) that control quantitative traits of economic importance. A three-generation resource family was developed by using two Berkshire grand sires and nine Yorkshire grand dams to detect QTL for growth and body composition traits in pigs. A total of 525 F₂ progeny were produced from 65 matings. All F₂ animals were phenotyped for birth weight, 16-day weight, growth rate, carcass weight, carcass length, back fat thickness, and loin eye area. Animals were genotyped for 125 microsatellite markers covering the genome. Least squares regression interval mapping was used for QTL detection. All carcass traits were adjusted for live weight at slaughter. A total of 16 significant QTL, as determined by a permutation test, were detected at the 5% chromosome-wise level for growth traits on Chromosomes (Chrs) 1, 2, 3, 4, 6, 7, 8, 9, 11, 13, 14, and X, of which two were significant at the 5% genome-wise level and two at the 1% genome-wise level (on Chrs 1, 2, and 4). For composition traits, 20 QTL were significant at the 5% chromosome-wise level (on Chrs 1, 4, 5, 6, 7, 12, 13, 14, 18), of which one was significant at the 5% genome-wise level and three were significant at the 1% genome-wise level (on Chrs 1, 5, and 7). For several QTL the favorable allele originated from the breed with the lower trait mean. Received: 29 November 2000 / Accepted: 27 March 2001     

Detection of quantitative trait loci for meat quality in a commercial slaughter pig cross

The primary goal of this study was to localize quantitative trait loci (QTL) affecting meat quality traits in swine. In total, 42 traits were scored on 305 F₂ individuals from a commercial slaughter pig cross in Norway. F₁ and F₂ individuals were genotyped for 29 markers on Chromosomes (Chrs) 4, 6, and 7, since previous studies had revealed QTL affecting meat quality traits on these chromosomes. The most evident result was detection of a QTL affecting amount of intramuscular fat on Chr 6. The QTL might also influence tenderness, whereas no effect was observed for back-fat thickness. Additionally, suggestive evidence for QTL affecting other meat quality traits was found on Chr 4 and Chr 7. Received: 16 June 2000 / Accepted: 5 December 2000     

Confirmation and dissection of QTL controlling resistanceto malaria in mice

We developed an F₁₁ AIL population from an F₁ cross of A/J (susceptible) and C57BL/6J (resistant) mouse strains. One thousand F₁₁ mice were challenged with P.c. chabaudi 54X, and 340 mice selected from the phenotypic extremes for susceptibility and resistance were genotyped for microsatellite markers on Chromosomes (Chrs) 5, 8, and 17. QTL originally detected in backcross and F₂ populations were confirmed on the three chromosomes within narrower genomic regions, by maximum likelihood and regression analyses. Each of the previously mapped QTL on Chrs 5 and 17 resolved into two linked QTLs. The distal and proximal QTLs on Chrs 5 and 17, respectively, map to the previously reported QTL.     

Genome-wide QTL analysis of meat quality-related traits in a large F2 intercross between Landrace and Korean native pigs

Background

We conducted a genome-wide linkage analysis to identify quantitative trait loci (QTL) that influence meat quality-related traits in a large F₂ intercross between Landrace and Korean native pigs. Thirteen meat quality-related traits of the m. longissimus lumborum et thoracis were measured in more than 830 F₂ progeny. All these animals were genotyped with 173 microsatellite markers located throughout the pig genome, and the GridQTL program based on the least squares regression model was used to perform the QTL analysis.

Results

We identified 23 genome-wide significant QTL in eight chromosome regions (SSC1, 2, 6, 7, 9, 12, 13, and 16) (SSC for Sus Scrofa) and detected 51 suggestive QTL in the 17 chromosome regions. QTL that affect 10 meat quality traits were detected on SSC12 and were highly significant at the genome-wide level. In particular, the QTL with the largest effect affected crude fat percentage and explained 22.5% of the phenotypic variance (F-ratio = 278.0 under the additive model, nominal P = 5.5 × 10⁻⁵⁵). Interestingly, the QTL on SSC12 that influenced meat quality traits showed an obvious trend for co-localization.

Conclusions

Our results confirm several previously reported QTL. In addition, we identified novel QTL for meat quality traits, which together with the associated positional candidate genes improve the knowledge on the genetic structure that underlies genetic variation for meat quality traits in pigs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-014-0080-6) contains supplementary material, which is available to authorized users.     

A two‐step approach to map quantitative trait loci for meat quality in connected porcine F2 crosses considering main and epistatic effects

The aim of this study was to map QTL for meat quality traits in three connected porcine F₂ crosses comprising around 1000 individuals. The three crosses were derived from the founder breeds Chinese Meishan, European Wild Boar and Pietrain. The animals were genotyped genomewide for approximately 250 genetic markers, mostly microsatellites. They were phenotyped for seven meat quality traits (pH at 45 min and 24 h after slaughter, conductivity at 45 min and 24 h after slaughter, meat colour, drip loss and rigour). QTL mapping was conducted using a two‐step procedure. In the first step, the QTL were mapped using a multi‐QTL multi‐allele model that was tailored to analyse multiple connected F₂ crosses. It considered additive, dominance and imprinting effects. The major gene RYR1:g.1843C>T affecting the meat quality on SSC6 was included as a cofactor in the model. The mapped QTL were tested for pairwise epistatic effects in the second step. All possible epistatic effects between additive, dominant and imprinting effects were considered, leading to nine orthogonal forms of epistasis. Numerous QTL were found. The most interesting chromosome was SSC6. Not all genetic variance of meat quality was explained by RYR1:g.1843C>T. A small confidence interval was obtained, which facilitated the identification of candidate genes underlying the QTL. Epistasis was significant for the pairwise QTL on SSC12 and SSC14 for pH24 and for the QTL on SSC2 and SSC5 for rigour. Some evidence for additional pairwise epistatic effects was found, although not significant. Imprinting was involved in epistasis.     

Epistatic QTL pairs associated with meat quality and carcass composition traits in a porcine Duroc × Pietrain population

Background

Quantitative trait loci (QTL) analyses in pig have revealed numerous individual QTL affecting growth, carcass composition, reproduction and meat quality, indicating a complex genetic architecture. In general, statistical QTL models consider only additive and dominance effects and identification of epistatic effects in livestock is not yet widespread. The aim of this study was to identify and characterize epistatic effects between common and novel QTL regions for carcass composition and meat quality traits in pig.

Methods

Five hundred and eighty five F₂ pigs from a Duroc × Pietrain resource population were genotyped using 131 genetic markers (microsatellites and SNP) spread over the 18 pig autosomes. Phenotypic information for 26 carcass composition and meat quality traits was available for all F₂ animals. Linkage analysis was performed in a two-step procedure using a maximum likelihood approach implemented in the QxPak program.

Results

A number of interacting QTL was observed for different traits, leading to the identification of a variety of networks among chromosomal regions throughout the porcine genome. We distinguished 17 epistatic QTL pairs for carcass composition and 39 for meat quality traits. These interacting QTL pairs explained up to 8% of the phenotypic variance.

Conclusions

Our findings demonstrate the significance of epistasis in pigs. We have revealed evidence for epistatic relationships between different chromosomal regions, confirmed known QTL loci and connected regions reported in other studies. Considering interactions between loci allowed us to identify several novel QTL and trait-specific relationships of loci within and across chromosomes.     

QTL analysis of body weight and carcass body length traits in an F2 intercross between Landrace and Korean native pigs

Growth traits, such as body weight and carcass body length, directly affect productivity and economic efficiency in the livestock industry. We performed a genome‐wide linkage analysis to detect the quantitative trait loci (QTL) that affect body weight, growth curve parameters and carcass body length in an F₂ intercross between Landrace and Korean native pigs. Eight phenotypes related to growth were measured in approximately 1000 F₂ progeny. All experimental animals were subjected to genotypic analysis using 173 microsatellite markers located throughout the pig genome. The least squares regression approach was used to conduct the QTL analysis. For body weight traits, we mapped 16 genome‐wide significant QTL on SSC1, 3, 5, 6, 8, 9 and 12 as well as 22 suggestive QTL on SSC2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 16 and 17. On SSC12, we identified a major QTL affecting body weight at 140 days of age that accounted for 4.3% of the phenotypic variance, which was the highest test statistic (F‐ratio = 45.6 under the additive model, nominal P = 2.4 × 10^?11) observed in this study. We also showed that there were significant QTL on SSC2, 5, 7, 8, 9 and 12 affecting carcass body length and growth curve parameters. Interestingly, the QTL on SSC2, 3, 5, 6, 8, 9, 10, 12 and 17 influencing the growth‐related traits showed an obvious trend for co‐localization. In conclusion, the identified QTL may play an important role in investigating the genetic structure underlying the phenotypic variation of growth in pigs.     

New retinal light damage QTL in mice with the light-sensitive RPE65 LEU variant

The purpose of this study was to determine the QTL that influence acute, light-induced retinal degeneration differences between the BALB/cByJ and 129S1/SvImJ mouse strains. Five- to 6-week-old F₂ progeny of an intercross between the two strains were exposed to 15,000 LUX of white light for 1 h after their pupils were dilated, placed in the dark for 16 h, and kept for 10–12 days in dim cyclic light before retinal rhodopsin was measured spectrophotometrically. This was used as the quantitative trait for retinal degeneration. Neither gender nor pigmentation had a significant influence on the amount of rhodopsin after light exposure in the F₂ progeny. For genetic study, DNAs of the 27–36 F₂ progeny with the highest and 27–36 F₂ with the lowest levels of rhodopsin after light exposure were genotyped with 71 dinucleotide repeat markers spanning the genome. Any marker with a 95% probability of being associated with phenotype was tested in all 289 F₂ progeny. Data were analyzed with Map Manager QTX. Significant QTL were found on mouse Chrs 1 and 4, and suggestive QTL on Chrs 6 and 2. The four QTL together equal an estimated 78% of the total genetic effect, and each of the QTL represents a gene with BALB/c susceptible alleles. The Chr 6 QTL is in the same region as a highly significant age-related retinal degeneration QTL found previously. Identification of these QTL is a first step toward identifying the modifier genes/alleles they represent, and identification of the modifiers may provide important information for human retinal diseases that are accelerated by light exposure.     

Genome-wide identification of quantitative trait loci for carcass composition and meat quality in a large-scale White Duroc × Chinese Erhualian resource population

Carcass and meat quality traits are economically important in pigs. In this study, 17 carcass composition traits and 23 meat quality traits were recorded in 1028 F₂ animals from a White Duroc × Erhualian resource population. All pigs in this experimental population were genotyped for 194 informative markers covering the entire porcine genome. Seventy-seven genome-wide significant quantitative trait loci (QTL) for carcass traits and 68 for meat quality were mapped to 34 genomic regions. These results not only confirmed many previously reported QTL but also revealed novel regions associated with the measured traits. For carcass traits, the most prominent QTL was identified for carcass length and head weight at 57 cM on SSC7, which explained up to 50% of the phenotypic variance and had a 95% confidence interval of only 3 cM. Moreover, QTL for kidney and spleen weight and lengths of cervical vertebrae were reported for the first time in pigs. For meat quality traits, two significant QTL on SSC5 and X were identified for both intramuscular fat content and marbling score in the longissimus muscle, while three significant QTL on SSC1 and SSC9 were found exclusively for IMF. Both LM and the semimembranous muscle showed common QTL for colour score on SSC4, 5, 7, 8, 13 and X and discordant QTL on other chromosomes. White Duroc alleles at a majority of QTL detected were favourable for carcass composition, while favourable QTL alleles for meat quality originated from both White Duroc and Erhualian.     

Genome-wide association analyses for meat quality traits in Chinese Erhualian pigs and a Western Duroc?×?(Landrace × Yorkshire) commercial population

Background

Understanding the genetic mechanisms that underlie meat quality traits is essential to improve pork quality. To date, most quantitative trait loci (QTL) analyses have been performed on F₂ crosses between outbred pig strains and have led to the identification of numerous QTL. However, because linkage disequilibrium is high in such crosses, QTL mapping precision is unsatisfactory and only a few QTL have been found to segregate within outbred strains, which limits their use to improve animal performance. To detect QTL in outbred pig populations of Chinese and Western origins, we performed genome-wide association studies (GWAS) for meat quality traits in Chinese purebred Erhualian pigs and a Western Duroc × (Landrace × Yorkshire) (DLY) commercial population.

Methods

Three hundred and thirty six Chinese Erhualian and 610 DLY pigs were genotyped using the Illumina PorcineSNP60K Beadchip and evaluated for 20 meat quality traits. After quality control, 35 985 and 56 216 single nucleotide polymorphisms (SNPs) were available for the Chinese Erhualian and DLY datasets, respectively, and were used to perform two separate GWAS. We also performed a meta-analysis that combined P-values and effects of 29 516 SNPs that were common to Erhualian, DLY, F₂ and Sutai pig populations.

Results

We detected 28 and nine suggestive SNPs that surpassed the significance level for meat quality in Erhualian and DLY pigs, respectively. Among these SNPs, ss131261254 on pig chromosome 4 (SSC4) was the most significant (P = 7.97E-09) and was associated with drip loss in Erhualian pigs. Our results suggested that at least two QTL on SSC12 and on SSC15 may have pleiotropic effects on several related traits. All the QTL that were detected by GWAS were population-specific, including 12 novel regions. However, the meta-analysis revealed seven novel QTL for meat characteristics, which suggests the existence of common underlying variants that may differ in frequency across populations. These QTL regions contain several relevant candidate genes.

Conclusions

These findings provide valuable insights into the molecular basis of convergent evolution of meat quality traits in Chinese and Western breeds that show divergent phenotypes. They may contribute to genetic improvement of purebreds for crossbred performance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0120-x) contains supplementary material, which is available to authorized users.     

Genetic dissection of ``OLETF', a rat model for non-insulin-dependent diabetes mellitus

To elucidate the genetic factors underlying non-insulin-dependent diabetes mellitus (NIDDM), we performed genome-wide quantitative trait locus (QTL) analysis, using the Otsuka Long-Evans Tokushima Fatty (OLETF) rat. The OLETF rat is an excellent animal model of NIDDM because the features of the disease closely resemble human NIDDM. Genetic dissection with two kinds of F2 intercross progeny, from matings between the OLETF rat and non-diabetic control rats F344 or BN, allowed us to identify on Chromosome (Chr) 1 a major QTL associated with features of NIDDM that was common to both crosses. We also mapped two additional significant loci, on Chrs 7 and 14, in the (OLETF × F344)F₂ cross alone, and designated these three loci as Diabetes mellitus, OLETF type Dmo 1, Dmo2 and Dmo3 respectively. With regard to suggestive QTLs, we found loci on Chrs 10, 11, and 16 that were common to both crosses, as well as loci on Chrs 5 and 12 in the (OLETF × F344)F₂ cross and on Chrs 4 and 13 in the (OLETF × BN)F₂ cross. Our results showed that NIDDM in the OLETF rat is polygenic and demonstrated that different genetic backgrounds could affect ``fitness' for QTLs and produce different phenotypic effects from the same locus. Received: 9 October 1997 / Accepted: 29 January 1998     

Identification of novel QTL for black tea quality traits and drought tolerance in tea plants (<Emphasis Type="Italic">Camellia sinensis</Emphasis>)

Tea (Camellia sinensis) contains polyphenols and caffeine which have been found to be of popular interest in tea quality. Tea production relies on well-distributed rainfall which influence tea quality. Phenotypic data for two segregating tea populations TRFK St 504 and TRFK St 524 were collected and used to identify the quantitative trait loci (QTL) influencing tea biochemical and drought stress traits based on a consensus genetic map constructed using the DArTseq platform. The populations comprised 261 F₁ clonal progeny. The map consisted of 15 linkage groups which corresponds to chromosome haploid number of tea plant (2n?=?2×?=?30) and spanned 1260.1 cM with a mean interval of 1.1 cM between markers. A total of 16 phenotypic traits were assessed in the two populations. Both interval and multiple QTL mapping revealed a total of 47 putative QTL in the 15 LGs associated with tea quality and percent relative water content at a significant genome-wide threshold of 5%. In total, six caffeine QTL, 25 catechins QTL, three theaflavins QTL, nine QTL for tea taster score, and three QTL for percent relative water contents were detected. Out of these 47 QTL, 19 QTL were identified for ten traits in three main regions on LG01, LG02, LG04, LG12, LG13, and LG14. The QTL associated with caffeine, individual catechins, and theaflavins were clustered mostly in LG02 and LG04 but in different regions on the map. The explained variance by each QTL in the population ranged from 5.5 to 56.6%, with an average of 9.9%. Identification of QTL that are tightly linked to markers associated with black tea quality coupled with UPLC assay may greatly accelerate development of novel tea cultivars owing to its amenability at seedling stage. In addition, validated molecular markers will contribute greatly to adoption of marker-assisted selection (MAS) for drought tolerance and tea quality improvement.     

Quantitative trait locus and haplotype mapping in closely related inbred strains identifies a locus for open field behavior

Quantitative trait locus (QTL) mapping in the mouse typically utilizes inbred strains that exhibit significant genetic and phenotypic diversity. The development of dense SNP panels in a large number of inbred strains has eliminated the need to maximize genetic diversity in QTL studies as plenty of SNP markers are now available for almost any combination of strains. We conducted a QTL mapping experiment using both a backcross (N₂) and an intercross (F₂) between two genetically similar inbred mouse strains: C57BL/6J (B6) and C57L/J (C57). A set of additive QTLs for activity behaviors was identified on Chrs 1, 9, 13, and 15. We also identified additive QTLs for anxiety-related behaviors on Chrs 7, 9, and 16. A QTL on Chr 11 is sex-specific, and we revealed pairwise interactions between QTLs on Chrs 1 and 13 and Chrs 10 and 18. The Chr 9 activity QTL accounts for the largest amount of phenotypic variance and was not present in our recent analysis of a B6 × C58/J (C58) intercross (Bailey et al. in Genes Brain Behav 7:761–769, 2008). To narrow this QTL interval, we used a dense SNP haplotype map with over 7 million real and imputed SNP markers across 74 inbred mouse strains (Szatkiewicz et al. in Mamm Genome 19(3):199–208, 2008). Evaluation of shared and divergent haplotype blocks among B6, C57, and C58 strains narrowed the Chr 9 QTL interval considerably and highlights the utility of QTL mapping in closely related inbred strains.     

QTL analysis of white blood cell, platelet and red blood cell-related traits in an F2 intercross between Landrace and Korean native pigs

Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F₂ intercross between Landrace and Korean native pigs. Eight blood‐related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F₂ progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome‐wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood‐related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker‐assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans.     

Mapping quantitative trait loci for yield components and morphological traits in an advanced backcross population between Oryza grandiglumis and the O. sativa japonica cultivar Hwaseongbyeo

Introgression has been achieved from wild species Oryza grandiglumis (2n=48, CCDD, Acc. No. 101154) into O. sativa subsp. japonica cv. Hwaseongbyeo as a recurrent parent. An advanced introgression (backcross) line, HG101, produced from a single plant from BC₅F₃ families resembled Hwaseongbyeo, but it showed differences from Hwaseongbyeo in several traits, including days to heading and culm length. To detect the introgressions, 450 microsatellite markers of known chromosomal position were used for the parental survey. Of the 450 markers, 51 (11.3%) detected O. grandiglumis segments in HG101. To characterize the effects of alien genes introgressed into HG101, an F_2:3 population (150 families) from the cross Hwaseongbyeo/HG101 was developed and evaluated for 13 agronomic traits. Several lines outperformed Hwaseongbyeo in several traits, including days to heading. Genotypes were determined for 150 F₂ plants using simple sequence repeat markers. Qualitative trait locus (QTL) analysis was carried out to determine the relationship between marker genotype and the traits evaluated. A total of 39 QTL and 1 gene conferring resistance to blast isolate were identified using single-point analysis. Phenotypic variation associated with each QTL ranged from 4.2 to 30.5%. For 18 (46.2%) of the QTL identified in this study, the O. grandiglumis-derived alleles contributed a desirable agronomic effect despite the overall undesirable characteristics of the wild phenotype. Favorable wild alleles were detected for days to heading, spikelets per panicle, and grain shape traits. Grain shape QTL for grain weight, thickness, and width identified in the F_2:3 lines were further confirmed based on the F₄ progeny test. The confirmed locus, tgw2 for grain weight is of particular interest because of its independence from undesirable height and maturity. Several QTL controlling amylose content and grain traits have not been detected in the previous QTL studies between Oryza cultivars, indicating potentially novel alleles from O. grandiglumis. The QTL detected in this study could be a rich source of natural genetic variation underlying the evolution and breeding of rice.     

Quantitative trait locus analysis of serum insulin, triglyceride, total cholesterol and phospholipid levels in the (SM/J x A/J)F2 mice.

Quantitative trait locus (QTL) analysis of serum insulin, triglyceride, total cholesterol and phospholipid levels at 10 weeks of age was performed in 321 F2 offspring from SM/J and A/J mice. Interval mapping revealed a total of 22 suggestive QTLs affecting the four traits: two insulin QTLs on Chromosomes (Chrs) 6 and 8; six triglyceride QTLs on Chrs 4, 8, 9, 11, 12 and 19; six total-cholesterol QTLs on Chrs 1, 3, 4, 14, 17 and 19; and eight phospholipid QTLs on Chrs 2, 3, 4, 6, 8, 10 and 19. Gender influenced the expression of eight of the suggestive QTLs. The total-cholesterol QTLs on Chrs 4, 14 and 17, the triglyceride QTL on Chr 9 and the phospholipid QTL on Chr 4 were specific to females. The phospholipid QTLs on Chrs 2 and 6 and the insulin QTL on Chr 8 were specific to males. In addition, common QTLs involved in the regulation of some of the traits were identified. The female-specific QTL on Chr 4 appeared to be involved in the regulation of total cholesterol and phospholipid levels. The QTL on Chr 8 affected insulin and phospholipid levels, whereas the Chr 19 QTL was common to the three lipid parameters.     

Mapping and fine mapping of quantitative trait loci for the number of vertebrae in a White Duroc × Chinese Erhualian intercross resource population

The number of vertebrae is associated with body size and meat production in pigs. To identify quantitative trait loci (QTL) for the number of vertebrae, phenotypic values were measured in 1029 individuals from a White Duroc × Chinese Erhualian intercross F₂ population. A whole genome scan was performed with 194 microsatellite markers in the F₂ population. Four genome‐wide significant QTL and eight chromosome‐wide significant QTL for the number of vertebrae were identified on pig chromosomes (SSC) 1, 2, 6, 7, 10 and 12. The most significant QTL was detected on SSC7 with a confidence interval of 1 cM, explaining 42.32% of the phenotypic variance in the thoracic vertebral number. The significant QTL on SSC1, 2 and 7 confirmed previous reports. A panel of 276 animals representing seven Western and Chinese breeds was genotyped with 34 microsatellite markers in the SSC7 QTL region. No obvious selective sweep effect was observed in the tested breeds, indicating that intensive selection for enlarged body size in Western commercial breeds did not wipe out the genetic variability in the QTL region. The Q alleles for increased vertebral number originated from both Chinese Erhualian and White Duroc founder animals. A haplotype block of approximately 900 kb was found to be shared by all Q‐bearing chromosomes of F₁ sires except for one distinct Q chromosome. The critical region harbours the newly reported VRTN gene associated with vertebral number. Further investigations are required to confirm whether VRTN or two other positional candidate genes, PROX2 and FOS, cause the QTL effect.     

Fine mapping and imprinting analysis for fatness trait QTLs in pigs

Quantitative trait loci (QTL) for fatness traits were reported recently in an experimental Meishan × Large White and Landrace F₂ cross. To further investigate the regions on pig Chr 2 (SSC2), SSC4, and SSC7, 25 additional markers from these regions were typed on 800 animals (619 F₂ animals, their F₁ parents, and F₀ grandfathers). Compared with the published maps, a modified order of markers was observed for SSC4 and SSC7. QTL analyses were performed both within the half-sib families as well as across families (line cross). Furthermore, a QTL model accounting for imprinting effects was tested. Information content could be increased considerably on all three chromosomes. Evidence for the backfat thickness QTL on SSC7 was increased, and the location could be reduced to a 33-cM confidence interval. The QTL for intramuscular fat on SSC4 could not be detected in this half-sib analysis, whereas under the line cross model a suggestive QTL on a different position on SSC4 was detected. For SSC2, in the half-sib analysis, a suggestive QTL for backfat thickness was detected with the best position at 26 cM. Imprinting analysis, however, revealed a genome-wise, significant, paternally expressed QTL on SSC2 with the best position at 63 cM. Our results suggest that this QTL is different from the previously reported paternally expressed QTL for muscle mass and fat deposition on the distal tip of SSC2p. Received: 15 October 1999 / Accepted: 21 February 2000     

Quantitative trait loci affecting growth in high growth (hg) mice

A genome-wide scan was performed in order to identify Quantitative Trait Loci (QTL) associated with growth in a population segregating high growth (hg), a partially recessive mutation that enhances growth rate and body size in the mouse. A sample of 262 hg/hg mice was selected from a C57BL/6J-hg/hg× CAST/EiJ F₂ cross and typed with 79 SSLP markers distributed across the genome. Eight significant loci were identified through interval mapping. Loci on Chromosomes (Chrs) 2 and 8 affected the growth rate of F₂ mice. Loci on Chr 2 and 11 affected growth rate and carcass lean mass (protein and ash). A locus on Chr 9 modified femur length and another one in Chr 17 affected both carcass lean mass and femur length, but none of these had significant effects on growth rate. Loci on Chrs 5 and 9 modified carcass fat content. Additive effects were positive for C57BL/6J alleles, except for the two loci affecting carcass fatness. Typing of selected markers in 274 +/+ F₂ mice revealed significant interactions between hg and other growth QTL, which were detected as changes in gene action (additive or dominant) and in allele substitution effects. Knowledge about interactions between loci, especially when major genes are involved, will help in the identification of positional candidate genes and in the understanding of the complex genetic regulation of growth rate and body size in mammals. Received: 29 June 2000 / Accepted: 22 November 2000     

Association of AFLP and SSR markers with agronomic and fibre quality traits in <Emphasis Type="Italic">Gossypium hirsutum</Emphasis> L.

Molecular markers linked to QTL contributing to agronomic and fibre quality traits would be useful for cotton improvement. We have attempted to tag yield and fibre quality traits with AFLP and SSR markers using F₂ and F₃ populations of a cross between two Gossypium hirsutum varieties, PS56-4 and RS2013. Out of 50 AFLP primer combinations and 177 SSR primer pairs tested, 32 AFLP and four SSR primers were chosen for genotyping F₂ individuals. Marker-trait associations were studied for eight agronomic and five fibre quality traits through simple and multiple regression analysis (MRA) using a set of 92 AFLP polymorphic loci and four SSR markers. Simple linear regression analysis (SLRA) identified 23 markers for eight different traits whereas multiple regression analysis identified 30 markers for at least one of the 13 traits. SSR marker BNL 3502 was consistently identified to be associated with fibre strength. While all the markers identified in SLRA were also detected in MRA, as many as 16 of the 30 markers were identified to be associated with respective traits in both F₂ and F₃ generations. The markers explained up to 41 per cent of phenotypic variation for individual traits. A number of markers were found to be associated with multiple traits suggesting clustering of QTLs for fibre quality traits in cotton.