QTL experiments in pigs are often analysed separately, although similar or same founder breeds are frequently used to establish the experimental design. The aim of the present study was to jointly analyse three porcine F 2-crosses for six growth and four muscling traits. The crosses were a Meishan × Pietrain cross, a Wild Boar × Pietrain cross, and a Wild Boar × Meishan cross. In some cases, same founder animals were used to establish the crosses. 966 F 2-individuals were genotyped for 242 genetic markers (mostly microsatellites) and phenotyped for birth weight, 21 and 35 day weight, slaughter weight, carcass length, food conversion ratio, ham meat weight, shoulder meat weight, loin and neck meat weight, and meat area. A multi-allele multi-QTL model was applied that estimated an additive QTL effect for each founder breed and parental origin (either paternally or maternally derived), and a dominant QTL effect for each cross. This model was previously introduced in plant breeding. Numerous QTL were mapped on the autosomes. Most QTL were localised on SSC1, 2, 3, 4, 6 and 8, and no QTL were on SSC9, 11, 13, 15, 17 and 18. The confidence intervals were short in many cases. QTL with an exceptionally high test statistic were found for carcass length on SSC1, 4, 7 and 17. The coefficient of variation was remarkably small for this trait, which suggests that carcass length is affected by only a few genes with large effects. Positional and functional candidates underlying promising QTL are suggested for further study.

Comprehensive human genetic maps were constructed on the basis of nearly 1 million genotypes from eight CEPH families; they incorporated >8,000 short tandem-repeat polymorphisms (STRPs), primarily from Généthon, the Cooperative Human Linkage Center, the Utah Marker Development Group, and the Marshfield Medical Research Foundation. As part of the map building process, 0.08% of the genotypes that resulted in tight double recombinants and that largely, if not entirely, represent genotyping errors, mutations, or gene-conversion events were removed. The total female, male, and sex-averaged lengths of the final maps were 44, 27, and 35 morgans, respectively. Numerous (267) sets of STRPs were identified that represented the exact same loci yet were developed independently and had different primer pairs. The distributions of the total number of recombination events per gamete, among the eight mothers of the CEPH families, were significantly different, and this variation was not due to maternal age. The female:male ratio of genetic distance varied across individual chromosomes in a remarkably consistent fashion, with peaks at the centromeres of all metacentric chromosomes. The new linkage maps plus much additional information, including a query system for use in the construction of reliably ordered maps for selected subsets of markers, are available from the Marshfield Website.

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Recent research has emphasized the importance of the metabolic cluster, which includes glucose intolerance, dyslipidemia, and high blood pressure, as a strong predictor of the obesity-related morbidities and premature mortality. Fundamental to this association, commonly referred to as the metabolic syndrome, is the close interaction between abdominal fat patterning, total body adiposity, and insulin resistance. As the initial step in identifying major genetic loci influencing these phenotypes, we performed a genomewide scan by using a 10-centiMorgan map in 2,209 individuals distributed over 507 nuclear Caucasian families. Pedigreebased analysis using a variance components linkage model demonstrated a quantitative trait locus (QTL) on chromosome 3 (3q27) strongly linked to six traits representing these fundamental phenotypes [logarithm of odds (lod) scores ranged from 2.4 to 3.5]. This QTL exhibited possible epistatic interaction with a second QTL on chromosome 17 (17p12) strongly linked to plasma leptin levels (lod ‫؍‬ 5.0). Situated at these epistatic QTLs are candidate genes likely to influence two biologic precursor pathways of the metabolic syndrome. O besity is a common and chronic disorder associated with decreased longevity and increased morbidity from a variety of diseases, including type 2 diabetes mellitus, hypertension, stroke, and coronary heart disease (1). Fat distribution, specifically the pattern known as upper-body, abdominal, or visceral obesity, is a major predictor of the adverse metabolic profile predisposing to these health risks (2). Thus, abdominal-visceral fat size has emerged as a significant precursor of glucose intolerance, hyperinsulinemia, elevated plasma triglycerides, decreased high density lipoprotein-cholesterol, and increased blood pressure (3). Fundamental to this metabolic milieu are close interactions between total body adiposity, abdominalvisceral fat size, and insulin resistance. Reaven (4) provided evidence to suggest that resistance to insulin-stimulated glucose uptake is associated with a series of related metabolic variables, termed ''syndrome X,'' which cluster in the same individual and include glucose intolerance, disturbed plasma lipids, and high blood pressure (4). Because of close similarities of these features with those associated with abdominal obesity, the more collective term metabolic syndrome was introduced (5).The etiology of the abdominal obesity-metabolic syndrome is complex and is thought to involve metabolic, neuroendocrine, and genetic interactions. A metabolic-neuroendocrine cascade has been proposed in which increased free fatty acid flux from the highly lipolytic visceral adipocytes, together with imbalances in sex hormones, could cause the insulin resistance and hyperinsulinemia, with their metabolic consequences (6). Weight gain with preferential deposition of adipocytes in the abdominal-visceral region is considered secondary to adoption of Westernized diet, activity lifestyle, and reactivity to emotional, intellectual, and physical stresses (5...