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Milling properties and flour color are essential selection criteria in soft wheat breeding. However, high phenotypic screening costs restrict selection to relatively few breeding lines in late generations. To achieve marker-based selection of these traits in early generations, we performed genetic dissection of quality traits using three doubled haploid populations that shared the high-quality soft wheat variety Kitahonami as the paternal parent. An amplicon sequencing approach allowed effective construction of well-saturated linkage maps of the populations. Marker-based heritability estimates revealed that target quality traits had relatively high values, indicating the possibility of selection in early generations. Taking advantage of Chinese Spring reference sequences, joint linkage maps of the three populations were generated. Based on the maps, multifamily quantitative trait locus (QTL) analysis revealed a total of 86 QTLs for ten traits investigated. In terms of target quality traits, 12 QTLs were detected for flour yield, and 12 were detected for flour redness (a* value). Among these QTLs, six for flour yield and nine for flour a* were segregating in more than two populations. Some relationships among traits were explained by QTL collocations on chromosomes, especially group 7 chromosomes. Ten different ideotypes with various combinations of favorable alleles for the flour yield and flour a* QTLs were generated. Phenotypes of derivatives from these ideotypes were predicted to design ideal genotypes for high-quality wheat. Simulations revealed the possibility of breeding varieties with better quality than Kitahonami., Competing Interests: The authors have declared that no competing interests exist.

Key Message: Using newly developed euchromatin-derived genomic SSR markers and a flexible Bayesian mapping method, 13 significant agricultural QTLs were identified in a segregating population derived from a four-way cross of tomato. So far, many QTL mapping studies in tomato have been performed for progeny obtained from crosses between two genetically distant parents, e.g., domesticated tomatoes and wild relatives. However, QTL information of quantitative traits related to yield (e.g., flower or fruit number, and total or average weight of fruits) in such intercross populations would be of limited use for breeding commercial tomato cultivars because individuals in the populations have specific genetic backgrounds underlying extremely different phenotypes between the parents such as large fruit in domesticated tomatoes and small fruit in wild relatives, which may not be reflective of the genetic variation in tomato breeding populations. In this study, we constructed F 2 population derived from a cross between two commercial F 1 cultivars in tomato to extract QTL information practical for tomato breeding. This cross corresponded to a four-way cross, because the four parental lines of the two F 1 cultivars were considered to be the founders. We developed 2510 new expressed sequence tag (EST)-based (euchromatin-derived) genomic SSR markers and selected 262 markers from these new SSR markers and publicly available SSR markers to construct a linkage map. QTL analysis for ten agricultural traits of tomato was performed based on the phenotypes and marker genotypes of F 2 plants using a flexible Bayesian method. As results, 13 QTL regions were detected for six traits by the Bayesian method developed in this study.

Novel genomics-based approaches such as genome-wide association studies (GWAS) and genomic selection (GS) are expected to be useful in fruit tree breeding, which requires much time from the cross to the release of a cultivar because of the long generation time. In this study, a citrus parental population (111 varieties) and a breeding population (676 individuals from 35 full-sib families) were genotyped for 1,841 single nucleotide polymorphisms (SNPs) and phenotyped for 17 fruit quality traits. GWAS power and prediction accuracy were increased by combining the parental and breeding populations. A multi-kernel model considering both additive and dominance effects improved prediction accuracy for acidity and juiciness, implying that the effects of both types are important for these traits. Genomic best linear unbiased prediction (GBLUP) with linear ridge kernel regression (RR) was more robust and accurate than GBLUP with non-linear Gaussian kernel regression (GAUSS) in the tails of the phenotypic distribution. The results of this study suggest that both GWAS and GS are effective for genetic improvement of citrus fruit traits. Furthermore, the data collected from breeding populations are beneficial for increasing the detection power of GWAS and the prediction accuracy of GS.

FLOWERING LOCUS T (FT) is an important floral integrator whose functions are conserved across plant species. In soybean, two orthologs, FT2a and FT5a, play a major role in initiating flowering. Their expression in response to different photoperiods is controlled by allelic combinations at the maturity loci E1 to E4, generating variation in flowering time among cultivars. We determined the molecular basis of a quantitative trait locus (QTL) for flowering time in linkage group J (Chromosome 16). Fine-mapping delimited the QTL to a genomic region of 107kb that harbors FT5a We detected 15 DNA polymorphisms between parents with the early-flowering (ef) and late-flowering (lf) alleles in the promoter region, an intron, and the 3' untranslated region of FT5a, although the FT5a coding regions were identical. Transcript abundance of FT5a was higher in near-isogenic lines for ef than in those for lf, suggesting that different transcriptional activities or mRNA stability caused the flowering time difference. Single-nucleotide polymorphism (SNP) calling from re-sequencing data for 439 cultivated and wild soybean accessions indicated that ef is a rare haplotype that is distinct from common haplotypes including lf The ef allele at FT5a may play an adaptive role at latitudes where early flowering is desirable., (© The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.)

Because of increasing litter size in Western pig breeds, additional teats are desirable to increase the capacity for nursing offspring. We applied genome-wide SNP markers to detect QTL regions that affect teat number in a Duroc population. We phenotyped 1024 animals for total teat number. A total of 36 588 SNPs on autosomes were used in the analysis. The estimated heritability for teat number was 0.34 ± 0.05 on the basis of a genomic relationship matrix constructed from all SNP markers. Using a BayesC method, we identified a total of 18 QTL regions that affected teat number in Duroc pigs; 9 of the 18 regions were newly detected., (© 2015 Stichting International Foundation for Animal Genetics.)

Key Message: Wheat yellow mosaic virus resistance of Madsen is governed by two complementary QTLs, Qym1 and Qym2 , located on chromosome arms 2DL and 3BS. Wheat yellow mosaic, caused by Wheat yellow mosaic virus (WYMV), is one of the most serious wheat diseases in East Asia. In this study, recombinant inbred lines (RILs, F9) from a cross between cultivars Madsen (resistant) and Hokushin (susceptible) grown in a WYMV-infected nursery field were tested for the presence of WYMV in leaves by enzyme-linked immunosorbent assay (ELISA) and genotyped by using genome-wide molecular markers. Two major QTLs were detected: Qym1 located between Xgwm539 and Xgwm349 on chromosome 2DL and Qym2 located between Xbarc147 and Xwmc623 on chromosome 3BS. The resistance alleles for both QTLs originated from Madsen. The third QTL Qym3 located near Xwmc457 on chromosome 4D, where the resistant allele for this QTL originated from Hokushin. Although the Qym3 was rather minor, it was essential to complement Qym1 and Qym2 for complete avoidance of WYMV infection. Near-isogenic lines carrying the resistance QTLs were developed by repeated backcrosses using Madsen as the donor parent and Hokushin as the recurrent parent. The lines that were resistant to WYMV (as tested by ELISA) were homozygous for the Madsen alleles at both Qym1 and Qym2. Qym1 dominance was partial, whereas that of Qym2 was nearly complete. Qym1 was closely linked to Xwmc41; Qym2 was closely linked to Xwmc754. These markers will be useful in marker-assisted selection in wheat breeding for WYMV resistance; this study will facilitate cloning the WYMV resistance genes.

We performed a genome-wide association study using the porcine 60K SNP array to detect QTL regions for nine traits in a three-generational Duroc samples (n = 651), viz. generations 1, 2 and 3 from a population selected over five generations using a closed nucleus breeding scheme. We applied a linear mixed model for association mapping to detect SNP effects, adjusting for fixed effects (sex and season) and random polygenic effects (reflecting genetic relatedness), and derived a likelihood ratio statistic for each SNP using the efficient mixed-model association method. We detected a region on SSC6 for backfat thickness (BFT) and on SSC7 for cannon bone circumference (CANNON), with a genome-wide significance of P < 0.01 after Bonferroni correction. These regions had been detected previously in other pig populations. Six genes are located in the BFT-associated region, while the CANNON-associated region includes 66 genes. In the future, significantly associated SNPs, derived by sequencing the coding regions of the six genes in the BFT region, can be used in marker-assisted selection of BFT, whereas haplotypes constructed from the SSC7 region with strong LD can be used to select for the CANNON trait in our resource family., (© 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.)

Respiratory disease is the most important health concern for the swine industry. Genetic improvement for disease resistance is challenging because of the difficulty in obtaining good phenotypes related with disease resistance; however, identification of genes or markers associated with disease resistance can help in the genetic improvement of pig health. The purpose of our study was to investigate whether quantitative trait loci (QTL) associated with disease resistance were segregated in a purebred population of Landrace pigs that had been selected for meat production traits and mycoplasmal pneumonia of swine (MPS) scores over five generations. We analysed 1395 pigs from the base to the fifth generation of this population. Two respiratory disease traits [MPS scores and atrophic rhinitis (AR) scores] and 11 immune-capacity traits were measured in 630-1332 animals at 7 weeks of age and when the animal's body weight reached 105 kg. Each of the pigs, except sires in the base population, was genotyped using 109 microsatellite markers, and then, QTL analysis of the full-sib family population with a multi-generational pedigree structure was performed. Variance component analysis was used to detect QTL associated with MPS or AR scores, and the logarithm of odds (LOD) score and genotypic heritability of the QTL were estimated. Five significant (LOD > 2.51) and 18 suggestive (LOD > 1.35) QTL for respiratory disease traits and immune-capacity traits were detected. The significant QTL for Log-MPS score, located on S. scrofa chromosome 2, could explain 87% of the genetic variance of this score in this analysis. This is the first report of QTL associated with respiratory disease lesions., (© 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.)

In females, follicle-stimulating hormone (FSH) targets a FSH receptor (FSHR) expressed only on granulose cells, inducing maturation of the ovarian follicles. We hypothesized that genetic variants in the FSHR gene influence litter size by affecting the number of corpora lutea. We fine-mapped a region of Sus Scrofa chromosome 3 that contains quantitative trait loci for corpora lutea. Polymorphisms were detected in the exons and 5' flanking region of the porcine FSHR gene, a positional candidate for the statistically most significant of the quantitative trait loci. Finally, 248 F(2) animals from a Duroc and Meishan cross were genotyped for three FSHR SNPs at positions 74, 532 and 1166, and these were correlated with the phenotypes of litter size and corpus luteum number. Three haplotypes were identified: M1 (G/G/C), M2 (C/A/T) and D (C/A/C). In the F(2) population, the M1 haplotype was associated with a greater number of corpora lutea (P < 0.01) and also seemed to be associated with increased litter size, although the association was not significant (P = 0.2571). Some polymorphisms resulting in amino acid substitutions in these genes were excluded from the polymorphisms possibly responsible for the number of corpora lutea., (© 2011 The Authors. Animal Science Journal © 2011 Japanese Society of Animal Science.)

In a previous study, we mapped two quantitative trait loci (QTL) approximately 50cM apart, both influencing the number of corpora lutea in pigs on chromosome 3. One locus included functional candidate genes for proteins related to specific aspects of fertility, such as the follicle-stimulating hormone receptor and the luteinizing hormone/choriogonadotropin receptor. However, specific genes related to the second locus have not yet been identified. This study aims to identify another candidate gene influencing the number of corpora lutea in pigs. Using 12 polymorphic markers, we fine-mapped a narrow region of pig chromosome 3 that had been shown to contain a QTL for corpora lutea. In the critical region, only 1 gene, autism susceptibility candidate 2 (AUTS2), was identified as a positional candidate. Our results demonstrate that the porcine AUTS2 gene consists of 19 exons with a complete open reading frame of 3768bp encoding an AUTS2 protein of 1256 amino acids. We screened the whole coding sequence and parts of the untranslated region for polymorphisms in an F(2) population of Duroc×Meishan crosses. We found 1 ins/del and 7 single nucleotide polymorphisms (SNP), including 2 nonsynonymous variants, c.943C>T in exon 7 and c.2828C>T in exon 19, resulting in P315S and A943V, respectively. The SNP c.943C>T within a proline-rich domain was genotyped in several breeds; the C allele occurred in all breeds, whereas the T allele occurred only in Meishan pigs. Using in situ hybridization, the mRNA expression of the AUTS2 gene was observed on granulosa cells in the porcine ovary and thus may be associated with hormone sensitivity., (Copyright © 2011 Elsevier B.V. All rights reserved.)

While testing a quantitative trait locus (QTL) for pork color in a cross population of pigs from the mating of Large White dams to a Japanese wild boar, our laboratory discovered a candidate gene (NUDT7) that might affect heme biosynthesis in porcine muscle. Therefore, this experiment was designed to test the effect of NUDT7 on heme biosynthesis in cultured myoblasts. Rat L6 myoblasts were transfected with a mammalian expression vector for pig NUDT7 immediately after the induction of cell differentiation, and samples were harvested at 2, 4, 6, and 8 days. Expression of exogenous NUDT7 mRNA was highest on day 4, when the heme content was substantially lower (P<0.01) than that of the control (14.2 vs. 63.9 pmol/10(5) cells). These results suggest that overexpression of pig NUDT7 may be associated with heme biosynthesis downregulation in skeletal muscle, which may partially explain differences in meat color among breeds of livestock., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

A QTL analysis for clubroot resistance (CR) of radish was performed using an F(2) population derived from a crossing of a CR Japanese radish and a clubroot-susceptible (CS) Chinese radish. F(3) plants obtained by selfing of F(2) plants were used for the CR tests. The potted seedlings were inoculated and the symptom was evaluated 6 weeks thereafter. The mean disease indexes of the F(3) plants were used for the phenotype of the F(2). The results of two CR tests were analyzed for the presence of QTL. A linkage map was constructed using AFLP and SSR markers; it spanned 554 cM and contained 18 linkage groups. A CR locus was observed in the top region of linkage group 1 in two tests. Therefore, the present results suggest that a large part of radish CR is controlled by a single gene or closely linked genes in this radish population, although minor effects of other genomic areas cannot be ruled out. The CR locus was named Crs1. Markers linked to Crs1 showed sequence homology to the genomic region of the top of chromosome 3 of Arabidopsis, as in the case of Crr3, a CR locus in Brassica rapa. These markers should be useful for breeding CR cultivars of radish. As Japanese radishes are known to be highly resistant or immune to clubroot, these markers may also be useful in the introgression of this CR gene to Brassica crops.

In the livestock industry, meat color has become important because consumer acceptance is subject to the appearance of the product in the marketplace. Our previous analyses of a whole genome QTL scan for various meat qualities using 2 F(2) families from Japanese wild boar (known as a red meat) x Large White and from Duroc x Chinese Jinhua suggested that a meat color (heme content) QTL is located on SSC6. The objective of this study was to fine-map this SSC6 meat color QTL and subsequently investigate positional candidate genes for polymorphisms that may cause changes in meat color. Therefore, we conducted interval mapping on SSC6 using an additional 9 gene markers through combined analyses of the 2 F(2) families of Japanese wild boar x Large White (353 progeny) and Duroc x Chinese Jinhua (204 progeny). Comparative analysis with humans, mice, and cattle suggested that there were 10 functional genes in the region. Among these genes, we suggested that a novel pig gene encoding a nudix (nucleoside diphosphate linked moiety X)-type motif 7 (NUDT7, a member of the nudix hydrolases) is a strong candidate for the QTL because the mouse Nudt7 is reported to hydrolyze succinyl-CoA, a substrate of the reaction limiting the rate of heme biosynthesis. We therefore determined the pig NUDT7 gene sequence including the 5' promoter region and explored genetic polymorphisms between Japanese wild boar and Large White. We identified 116 polymorphisms within the NUDT7 CDS or in the 5' region. None of the AA substitutions were associated with the meat color QTL; however, 3 polymorphisms were found in putative transcription factor recognition sites. We then investigated the differential expression of NUDT7 in Japanese wild boar and Large White by allele-specific quantitative real-time PCR. The expression level of the Large White type allele was greater than that of the Japanese wild-boar-type allele. Consequently, we speculated that the difference in meat color between Japanese wild boar and Large White is caused partly by differential expression of this candidate gene. Upregulation of NUDT7 expression in muscle may reduce succinyl-CoA content and thus reduce the level of heme biosynthesis.

In some crop species, germplasm collections consisting of a large number of accessions that include traditional landraces, modern cultivars and wild species have recently been established. Such collections are regarded as useful stocks of genes for breeding programs. However, to efficiently utilize these collections for plant breeding, understanding genetic variation in agronomic traits at the QTL level between the accessions is indispensable. One effective way to extract the actual QTL information included in these collections is to perform QTL analysis jointly for multiple families derived from crossing some accessions of the collection with a single reference line such as a standard commercial variety. We developed a Bayesian method for jointly analyzing QTL in such interconnected multiple families derived from a set of inbred lines crossed to the reference line, to detect QTL segregating between any of the inbred lines and the reference line. In this study, we considered multiple recombinant inbred lines, each of which was derived from crossing each of the inbred lines to the reference line. The method was evaluated through the use of simulated data sets for its efficiency in detecting QTL and identifying families segregating at each QTL.

A genome-wide scan for QTL affecting economically important traits in beef production was performed using an F(2) resource family from a Japanese Black x Limousin cross, where 186 F(2) animals were measured for growth, carcass, and meat-quality traits. All family members were genotyped for 313 informative microsatellite markers that spanned 2,382 cM of bovine autosomes. The centromeric region of BTA2 contained significant QTL (i.e., exceeding the genome-wide 5% threshold) for 5 carcass grading traits [LM area, beef marbling standards (BMS) number, luster, quality grade, and firmness), 8 computer image analysis (CIA) traits [LM lean area, ratio of fat area (RFA) to LM area, LM area, RFA to musculus (M.) trapezius area, M. trapezius lean area, M. semispinalis lean area, RFA to M. semispinalis area, and RFA to M. semispinalis capitis area], and 5 meat quality traits (contents of CP, crude fat, moisture, C16:1, and C18:2 of LM). A significant QTL for withers height was detected at 80.3 cM on BTA5. We detected significant QTL for the C14:0 content in backfat and C14:0 and C14:1 content in intermuscular fat around the 62.3 to 71.0 cM region on BTA19 and for C14:0, C14:1, C18:1, and C16:0 content and ratio of total unsaturated fatty acid content to total SFA content in intramuscular fat at 2 different regions on BTA19 (41.1 cM for C14:1 and 62.3 cM for the other 4 traits). Overall, we identified 9 significant QTL regions controlling 27 traits with genome-wide significance of 5%; of these, 22 traits exceeded the 1% genome-wide threshold. Some of the QTL affecting meat quality traits detected in this study might be the same QTL as previously reported. The QTL we identified need to be validated in commercial Japanese Black cattle populations.

Genomic imprinting is interpreted as a phenomenon, in which some genes inherited from one parent are not completely expressed due to modification of the genome caused during gametogenesis. Subsequently, the expression level of an allele at the imprinted gene is changed dependent on the parental origin, which is referred to as the parent-of-origin effect. In livestock, some QTL for reproductive performance and meat productivity have been reported to be imprinted. So far, methods detecting imprinted QTL have been proposed on the basis of interval mapping, where only a single QTL was tested at a time. In this study, we developed a Bayesian method for simultaneously mapping multiple QTL, allowing the inference about expression modes of QTL in an outbred F2 family. The inference about whether a QTL is Mendelian or imprinted was made using Markov chain Monte Carlo estimation by comparing the goodness-of-fits between models, assuming the presence and the absence of parent-of-origin effect at a QTL. We showed by the analyses of simulated data sets that the Bayesian method can effectively detect both Mendelian QTL and imprinted QTL.

Deficits in prepulse inhibition (PPI) are a biological marker for schizophrenia. To unravel the mechanisms that control PPI, we performed quantitative trait loci (QTL) analysis on 1,010 F2 mice derived by crossing C57BL/6 (B6) animals that show high PPI with C3H/He (C3) animals that show low PPI. We detected six major loci for PPI, six for the acoustic startle response, and four for latency to response peak, some of which were sex-dependent. A promising candidate on the Chromosome 10-QTL was Fabp7 (fatty acid binding protein 7, brain), a gene with functional links to the N-methyl-D-aspartic acid (NMDA) receptor and expression in astrocytes. Fabp7-deficient mice showed decreased PPI and a shortened startle response latency, typical of the QTL's proposed effects. A quantitative complementation test supported Fabp7 as a potential PPI-QTL gene, particularly in male mice. Disruption of Fabp7 attenuated neurogenesis in vivo. Human FABP7 showed altered expression in schizophrenic brains and genetic association with schizophrenia, which were both evident in males when samples were divided by sex. These results suggest that FABP7 plays a novel and crucial role, linking the NMDA, neurodevelopmental, and glial theories of schizophrenia pathology and the PPI endophenotype, with larger or overt effects in males. We also discuss the results from the perspective of fetal programming.

One way to use a crop germplasm collection directly to map QTLs without using line-crossing experiments is the whole genome association mapping. A major problem with association mapping is the presence of population structure, which can lead to both false positives and failure to detect genuine associations (i.e., false negatives). Particularly in highly selfing species such as Asian cultivated rice, high levels of population structure are expected and therefore the efficiency of association mapping remains almost unknown. Here, we propose an approach that combines a Bayesian method for mapping multiple QTLs with a regression method that directly incorporates estimates of population structure. That is, the effects due to both multiple QTLs and population structure were included in our statistical model. We evaluated the efficiency of our approach in simulated- and real-trait analyses of a rice germplasm collection. Simulation analyses based on real marker data showed that our model could suppress both false-positive and false-negative rates and the error of estimation of genetic effects over single QTL models, indicating that our model has statistically desirable attributes over single QTL models. As real traits, we analyzed the size and shape of milled rice grains and found significant markers that may be linked to QTLs reported previously. Association mapping should have good prospects in highly selfing species such as rice if proper methods are adopted. Our approach will be useful for the whole genome association mapping of various selfing crop species.

The number of vertebrae in pigs varies and is associated with meat productivity. Wild boars, which are ancestors of domestic pigs, have 19 vertebrae. In comparison, European commercial breeds have 21-23 vertebrae, probably owing to selective breeding for enlargement of body size. We previously identified two quantitative trait loci (QTL) for the number of vertebrae on Sus scrofa chromosomes (SSC) 1 and 7. These QTL explained an increase of more than two vertebrae. Here, we performed a map-based study to define the QTL region on SSC1. By using three F2 experimental families, we performed interval mapping and recombination analyses and defined the QTL within a 1.9-cM interval. Then we analyzed the linkage disequilibrium of microsatellite markers in this interval and found that 10 adjacent markers in a 300-kb region were almost fixed in European commercial breeds. Genetic variation of the markers was observed in Asian local breeds or wild boars. This region encoded an orphan nuclear receptor, germ cell nuclear factor (NR6A1, formerly known as GCNF), which contained an amino acid substitution (Pro192Leu) coincident with the QTL. This substitution altered the binding activity of NR6A1 to its corepressors, nuclear receptor-associated protein 80 (RAP80) and nuclear receptor corepressor 1 (NCOR1). In addition, somites of mouse embryos demonstrated expression of NR6A1 protein. Together, these results suggest that NR6A1 is a strong candidate for one of the QTL that influence number of vertebrae in pigs.

Understanding of the genetic control of female reproductive performance in pigs would offer the opportunity to utilize natural variation and improve selective breeding programs through marker-assisted selection. The Chinese Meishan is one of the most prolific pig breeds known, farrowing 3 to 5 more viable piglets per litter than Western breeds. This difference in prolificacy is attributed to the Meishan's superior prenatal survival. Our study utilized a 3-generation resource population, in which the founder grandparental animals were purebred Meishan and Duroc pigs, in a genome scan for QTL. Grandparent, F1, and F2 animals were genotyped for 180 microsatellite markers. Reproductive traits, including number of corpora lutea (number of animals = 234), number of fetuses per animal (n = 226), number of teats (n = 801), and total number born (n = 288), were recorded for F2 females. Genome-wide significance level thresholds of 1, 5, and 10% were calculated using a permutation approach. We identified 9 QTL for 3 traits at a 10% genome-wise significance level. Parametric interval mapping analysis indicated evidence of a 1% genome-wise significant QTL for corpora lutea on SSC 3. Nonparametric interval mapping for number of teats found 4 significant QTL on chromosomes SSC3 (P < 0.01), SSC7 (P < 0.01), SSC8 (P < 0.01), and SSC12 (P < 0.05). Partial imprinting of a QTL affecting teat number (P < 0.10) was detected on SSC8. Using the likelihood-ratio test for a categorical trait, 2 QTL for pin nipples were detected on SSC2 and SSC16 (P < 0.01). Fine mapping of the QTL regions will be required for their application to introgression programs and gene cloning.

Here, we analysed quantitative trait loci (QTL) for fatty acid composition, one of the factors affecting fat quality, in a Japanese wild boar x Large White cross. We found 25 significant effects for 17 traits at 13 positions at the 5% genome-wise level, of which 16 effects for 12 traits at 10 positions were significant at the 1% level. QTL for saturated fatty acids (SFA) in back fat were mapped to swine (Sus scrofa) chromosomes (SSC) 1p, 9 and 15. QTL for unsaturated fatty acids in back fat were mapped to SSC1p, 1q, 4, 5, 9, 15 and 17. Using a regression model that fits back fat thickness as a covariate, two of the QTL for linoleic acid content on SSC4 and SSC17 were not significant, but one QTL for total SFA composition was detected on SSC5 with correction for back fat thickness. Wild boar alleles at six of seven QTL tended to increase SFAs and to decrease unsaturated fatty acids. QTL for fatty acid composition in perirenal fat were mapped on SSC2, 3, 4, 5, 6, 14, 16 and X. QTL for melting point (in back fat samples) were mapped on SSC1, 2 and 15. Wild boar alleles in QTL on SSC1 and SSC15 were associated with elevated melting points whereas those on SSC2 were associated with lower melting point measurements.

We previously mapped a locus for porcine intramuscular fat content (IMF) by linkage analysis to a 17.1-cM chromosome interval on Sus scrofa chromosome 7 (SSC7) flanked by microsatellite markers SW1083 and SW581. In this study, we identified 34 microsatellite markers and 14 STSs from the 17.1-cM IMF quantitative trait loci (QTL) region corresponding to HSA14q and aligned those loci using the INRA-University of Minnesota porcine radiation hybrid (IMpRH) panel. We then constructed a 5.2-Mb porcine bacterial artificial chromosome (BAC) contig of this region that was aligned using the RH panel. Finally, the IMF QTL was fine-mapped to 12.6 cM between SJ169 and MM70 at the 0.1% chromosome-wise significance level by genotyping the previously studied F2 resource family with 17 additional microsatellites. We also demonstrated that the SJ169-MM70 interval spans approximately 3.0 Mb and contains at least 12 genes: GALC, GPR65, KCNK10, SPATA7, PTPN21, FLJ11806, EML5, TTC8, CHES1, CAP2P1, CHORDC2P and C14orf143.

Many traits including shapes and colors of flowers, fruits and seeds in plants, as well as coat colors and some behavioral properties in animals, are recorded in discrete categories. If categories are ordered, genetic analyses of the categorical traits are often performed using the threshold model, which considers a latent continuous variable, called the liability, underlying a trait and assumes the monotonic relationship between the phenotype and the liability. In some categorical traits, however, descriptions of phenotypes are purely nominal and the phenotypic scores cannot be ordered. The threshold model is unreasonable for the analyses of such unordered categorical traits. In this study, we developed a method for interval mapping of loci affecting unordered categorical traits with more than two categories. The probability of the phenotype of an individual falling in each of the categories was expressed by a polychotomous logistic model, in which the log-odds for each category relative to the reference category were assumed to follow a linear model including genotype at a locus affecting a trait as covariate. Based on the model, the interval mapping using a maximum likelihood method was devised for the analysis of complex categorical traits described with unordered categories. We confined ourselves to the case of F2 populations derived from a cross between two inbred lines, although this approach can easily be extended to the analyses for other populations of general structures. As results of analyses of simulated data show, the method showed high efficiency in detecting the loci affecting unordered categorical traits.

The objective of the research was to identify QTL affecting the number of vertebrae in swine, one of the major determining factors of growth and body composition. Previously, we reported a QTL for the number of vertebrae located on SSC1qter (terminal band of the q arm of SSC 1) in an F2 family produced by crossing a Göttingen miniature male with two Meishan females. Eight other swine families were subsequently produced by crosses between different breeds of European, Asian, and miniature pigs. In these families, the QTL on SSC1qter for the number of vertebrae was detected. Unlike the Asian alleles, all European alleles in this study had the effect of increasing the number of vertebrae by 0.44 to 0.69 and acted additively without dominance. The Göttingen miniature sire, for which we previously reported a smaller additive effect, seemed to be heterozygous at the QTL. In the present study, another QTL was found for the number of vertebrae on SSC7. This QTL was not fixed in the European pigs used as parents in our experimental families, and some of the European alleles increased the number of vertebrae. A half-sib analysis confirmed that this QTL was segregating in a commercial Large White population. Analysis in an F2 family in which the parental pigs were fixed for alternative alleles revealed that the effects of the QTL on SSC1 and on SSC7 were additive and similar in size. The two QTL acted independently without epistatic effects and explained an increase of more than two vertebrae.

In this paper, we propose a new Bayesian method for QTL analysis in outbred F2 families based on Markov chain Monte Carlo (MCMC) estimation allowing inference about whether each of F0 founders (grandparents) is homozygous or heterozygous at QTL. This, in turn, allows us to select a model accurately explaining observations of phenotypes for F2 individuals. The proposed method performs the fitting a statistical model of the two possible QTL states in each F0 grandparent, that is, homozygous and heterozygous at QTL, and gives a posterior distribution for the QTL states in each F0 grandparent. We confine ourselves to the discrimination of two QTL states, homozygous or heterozygous, for each of the F0 grandparents without taking into consideration whether common alleles are shared by F0 grandparents. The statistical model includes allelic effects and dominance effects for each QTL. The number of parameters representing allelic effects and dominance effects is therefore changed depending on the QTL states. A Reversible Jump MCMC technique is used for transition between the models of different dimensions. The effectiveness of the proposed method was investigated using simulation experiments. It was practicable to estimate the QTL states of F0 grandparents as well as the number, the locations and the effects of QTL segregating in an outbred F2 family.

Three generations of a swine family produced by crossing a Japanese wild boar and three Large White female pigs were used to map QTL for various production traits. Here we report the results of QTL analyses for skeletal muscle fiber composition and meat quality traits based on phenotypic data of 353 F(2) animals and genotypic data of 225 markers covering almost the entire pig genome for all of the F(2) animals as well as their F(1) parents and F(0) grandparents. The results of a genome scan using least squares regression interval mapping provided evidence that QTL (<1% genome-wise error rate) affected the proportion of the number of type IIA muscle fibers on SSC2, the number of type IIB on SSC14, the relative area (RA) of type I on SSCX, the RA of type IIA on SSC6, the RA of type IIB on SSC6 and SSC14, the Minolta a* values of loin on SSC4 and SSC6, the Minolta b* value of loin on SSC15, and the hematin content of the LM on SSC6. Quantitative trait loci (<5% genome-wise error rate) were found for the number of type I on SSC1, SSC14, and SSCX, for the number of type IIA on SSC14, for the number of type IIB on SSC2, for the RA of type IIA on SSC2, for the Minolta b* value of loin on SSC3, for the pH of loin on SSC15, and for the i.m. fat content on SSC15. Twenty-four QTL were detected for 11 traits at the 5% genome-wise level. Some traits were associated with each other, so the 24 QTL were located on 11 genomic regions. In five QTL located on SSC2, SSC6, and SSC14, each wild boar allele had the effect of increasing types I and IIA muscle fibers and decreasing type IIB muscle fibers. These effects are expected to improve meat quality.

Several quantitative trait loci (QTL) have been detected on SSC1qter (Sus scrofa chromosome 1qter), including QTL for the number of vertebrae, as reported in our previous study. To provide the tools for analysis of QTLs on SSC1qter, we constructed a comparative map of swine and human. In addition, we identified 26 swine STSs and mapped 16 of them on SSC1qter using the INRA - University of Minnesota porcine radiation hybrid (IMpRH) panel. We screened a BAC library using these swine STSs and developed 35 new polymorphic microsatellite markers from the BAC clones, of which 26 were informative in our reference family. We also mapped nine microsatellite markers we had isolated previously. Consequently a total of 44 new polymorphic microsatellite markers were located within a 60-cM region of SSC1qter, spanning from SW1092 to the telomere.

In the present paper, we proposed a statistical procedure based on composite interval mapping for accurate analysis of quantitative trait loci (QTL) for individuals sampled from an outcrossing population with two-generation families consisting of the sampled individuals and F1 progenies obtained by crossing them as parental individuals. In the proposed procedure, haplotypes of markers of parental individuals were reconstructed based on the genotypes of F1 progenies and QTL analyses with composite interval mapping were conducted separately for each of parents as well as jointly for both parents. A least squares method was applied to the composite interval mapping, where some of markers were selected as cofactors to absorb the variation induced by QTL located elsewhere in the genome. The procedure was evaluated for the efficiency in detecting QTL and the precision of estimates of locations and effects of QTL using simulations. It was shown that QTL with interaction between paternal and maternal alleles was effectively detected by joint analysis of both parents, while a QTL segregating only in one parent, closely linked to a QTL segregating only in the other parent, was successfully detected by analyzing separately each of the parents with inclusion of markers of both parents. The proposed procedure can provide detailed genetic information useful for marker assisted breeding in an outcrossing species such as forest trees.

We constructed a pig F2 resource population by crossing a Meishan sow and a Duroc boar to locate economically important trait loci. The F2 generation was composed of 865 animals (450 males and 415 females) from four F1 males and 24 F1 females and was genotyped for 180 informative microsatellite markers spanning 2,263.6 cM of the whole pig genome. Results of the genome scan showed evidence for significant quantitative trait loci (<1% genomewise error rate) affecting weight at 30 d and average daily gain on Sus scrofa chromosome (SSC) 6, carcass yield on SSC 7, backfat thickness on SSC 7 and SSC X, vertebra number on SSC 1 and SSC 7, loin muscle area on SSC 1 and SSC 7, moisture on SSC 13, intramuscular fat content on SSC 7, and testicular weight on SSC 3 and SSC X. Moreover, 5% genomewise significant QTL were found for birth weight on SSC 7, average daily gain on SSC 4, carcass length on SSC 6, SSC 7, and SSC X and lightness (L value) on SSC 3. We identified 38 QTL for 28 traits at the 5% genomewise level. Of the 38 QTL, 24 QTL for 17 traits were significant at the 1% genomewise level. Analysis of marker genotypes supported the breed of origin results and provided further evidence that a suggestive QTL for circumference of cannon bone also was segregating within the Meishan parent. We identified genomic regions related with growth and meat quality traits. Fine mapping will be required for their application in introgression programs and gene cloning.

Comparative mapping studies facilitate the identification of genes located in quantitative trait locus (QTL) regions in domestic animals by utilizing information from the human genome. Radiation hybrid (RH) mapping is effective for this purpose because of its high resolution in ordered gene mapping on chromosomes. We constructed an RH map of pig chromosome 7, by adding 23 markers associated with genes. This RH map clearly demonstrated the mosaic of homology between pig chromosome 7 (SSC7) and human chromosomes 6, 14 and 15 at a 'gene' level, and was confirmed by linkage analysis. Clarification of the homology of SSC7 to human chromosomes will contribute to the elucidation of the gene(s) responsible for QTL detected on this chromosome.

Composite interval mapping (CIM) has been successfully applied to the detection of QTL in experimental animals and plants. However, practical analyses based on CIM have been reported mainly for populations derived from cross between inbred lines. There are few studies on QTL analyses with CIM in outbred populations. To evaluate the applicability of CIM to outbred populations is prerequisite for the fine mapping of QTL in industrial animals such as pig and chicken. Some markers are usually not fully informative in outbred populations. In application of CIM to outbred populations, the influence of inclusion of such uninformative markers used as covariates on the efficiency of CIM should be investigated. In this paper a least-squares method for CIM was formalized in an F(2) population derived by crossing two outbred lines. The efficiencies of CIM were evaluated for outbred populations in comparison with simple interval mapping (SIM) for several cases of marker informativeness using simulations. By incorporating markers linked to a tested position as well as those unlinked, CIM showed a higher efficiency to separate two linked QTL over SIM. The efficiency of dissection was enhanced as the marker informativeness was increased. The power of CIM to detect an isolated QTL was improved by excluding markers linked to a tested position from covariates and higher than SIM regardless of marker informativeness. In conclusion, CIM is a useful procedure for the analysis of QTL in outbred populations even under low marker informativeness.

A genome-wide scan for QTL affecting economically important traits in beef production was performed using an F2 resource family from a Japanese Black × Limousin cross, where 186 F2 animals were measured for growth, carcass, and meat-quality traits. All family members were genotyped for 313 informative microsatellite markers that spanned 2,382 cM of bovine autosomes. The centromeric region of BTA2 contained significant QTL (i.e., exceeding the genomewide 5% threshold) for 5 carcass grading traits [LM area, beef marbling standards (BMS) number, luster, quality grade, and firmness), 8 computer image analysis (CIA) traits [LM lean area, ratio of fat area (RFA) to LM area, LM area, RFA to musculus (M.) trapezius area, M. trapezius lean area, M. semispinalis lean area, RFA to M. semispinalis area, and RFA to M. semispinalis capitis area], and 5 meat quality traits (contents of CP, crude fat, moisture, C16:1, and C18:2 of LM). A significant QTL for withers height was detected at 80.3 cM on BTA5. We detected significant QTL for the C 14:0 content in backfat and C14:0 and C 14:1 content in intermuscular fat around the 62.3 to 71.0 cM region on BTA19 and for C14:0, C14:1, C18:1, and C16:0 content and ratio of total unsaturated fatty acid content to total SFA content in intramuscular fat at 2 different regions on BTA19 (41.1 cM for C14:1 and 62.3 cM for the other 4 traits). Overall, we identified 9 significant QTL regions controlling 27 traits with genomewide significance of 5%; of these, 22 traits exceeded the 1% genome-wide threshold. Some of the QTL affecting meat quality traits detected in this study might be the same QTL as previously reported. The QTL we identified need to be validated in commercial Japanese Black cattle populations. [ABSTRACT FROM AUTHOR]

Understanding of the genetic control of female reproductive performance in pigs would offer the opportunity to utilize natural variation and improve selective breeding programs through marker-assisted selection. The Chinese Meishan is one of the most prolific pig breeds known, farrowing 3 to 5 more viable piglets per litter than Western breeds. This difference in prolificacy is attributed to the Meishan's superior prenatal survival. Our study utilized a 3-generation resource population, in which the founder grandparental animals were purebred Meishan and Duroc pigs, in a genome scan for QTL. Grandparent, F1, and F2 animals were genotyped for 180 microsatellite markers. Reproductive traits, including number of corpora lutea (number of animals = 234), number of fetuses per animal (n = 226), number of teats (n = 801), and total number born (n = 288), were recorded for F2 females. Genome- wide significance level thresholds of 1, 5, and 10% were calculated using a permutation approach. We identified 9 QTL for 3 traits at a 10% genome-wise significance level. Parametric interval mapping analysis indicated evidence of a 1% genome-wise significant QTL for corpora lutea on SSC 3. Nonparametric interval mapping for number of teats found 4 significant QTL on chromosomes SSC3 (P < 0.01), SSC7 (P < 0.01), SSC8 (P < 0.01), and SSC12 (P < 0.05). Partial imprinting of a QTL affecting teat number (P < 0.10) was detected on SSC8. Using the likelihood-ratio test for a categorical trait, 2 QTL for pin nipples were detected on SSC2 and SSC16 (P < 0.01). Fine mapping of the QTL regions will be required for their application to introgression programs and gene cloning. [ABSTRACT FROM AUTHOR]

Here, we analysed quantitative trait loci (QTL) for fatty acid composition, one of the factors affecting fat quality, in a Japanese wild boar × Large White cross. We found 25 significant effects for 17 traits at 13 positions at the 5% genome-wise level, of which 16 effects for 12 traits at 10 positions were significant at the 1% level. QTL for saturated fatty acids (SFA) in back fat were mapped to swine ( Sus scrofa) chromosomes (SSC) 1p, 9 and 15. QTL for unsaturated fatty acids in back fat were mapped to SSC1p, 1q, 4, 5, 9, 15 and 17. Using a regression model that fits back fat thickness as a covariate, two of the QTL for linoleic acid content on SSC4 and SSC17 were not significant, but one QTL for total SFA composition was detected on SSC5 with correction for back fat thickness. Wild boar alleles at six of seven QTL tended to increase SFAs and to decrease unsaturated fatty acids. QTL for fatty acid composition in perirenal fat were mapped on SSC2, 3, 4, 5, 6, 14, 16 and X. QTL for melting point (in back fat samples) were mapped on SSC1, 2 and 15. Wild boar alleles in QTL on SSC1 and SSC15 were associated with elevated melting points whereas those on SSC2 were associated with lower melting point measurements. [ABSTRACT FROM AUTHOR]