Time‐specific and pleiotropic quantitative trait loci coordinately modulate stem growth in Populus

In perennial woody plants, the coordinated increase of stem height and diameter during juvenile growth improves competitiveness (i.e. access to light); however, the factors underlying variation in stem growth remain unknown in trees. Here, we used linkage‐linkage disequilibrium (linkage‐LD) mapping to decipher the genetic architecture underlying three growth traits during juvenile stem growth. We used two Populus populations: a linkage mapping population comprising a full‐sib family of 1,200 progeny and an association mapping panel comprising 435 unrelated individuals from nearly the entire natural range of Populus tomentosa. We mapped 311 quantitative trait loci (QTL) for three growth traits at 12 timepoints to 42 regions in 17 linkage groups. Of these, 28 regions encompassing 233 QTL were annotated as 27 segmental homology regions (SHRs). Using SNPs identified by whole‐genome re‐sequencing of the 435‐member association mapping panel, we identified significant SNPs (P ≤ 9.4 × 10^?7) within 27 SHRs that affect stem growth at nine timepoints with diverse additive and dominance patterns, and these SNPs exhibited complex allelic epistasis over the juvenile growth period. Nineteen genes linked to potential causative alleles that have time‐specific or pleiotropic effects, and mostly overlapped with significant signatures of selection within SHRs between climatic regions represented by the association mapping panel. Five genes with potential time‐specific effects showed species‐specific temporal expression profiles during the juvenile stages of stem growth in five representative Populus species. Our observations revealed the importance of considering temporal genetic basis of complex traits, which will facilitate the molecular design of tree ideotypes.     

Dense‐map genome scan for dyslexia supports loci at 4q13, 16p12, 17q22; suggests novel locus at 7q36

Analysis of genetic linkage to dyslexia was performed using 133,165 array‐based SNPs genotyped in 718 persons from 101 dyslexia‐affected families. Results showed five linkage peaks with lod scores >2.3 (4q13.1, 7q36.1‐q36.2, 7q36.3, 16p12.1, and 17q22). Of these five regions, three have been previously implicated in dyslexia (4q13.1, 16p12.1, and 17q22), three have been implicated in attention‐deficit hyperactivity disorder (ADHD, which highly co‐occurs with dyslexia; 4q13.1, 7q36.3, 16p12.1) and four have been implicated in autism (a condition characterized by language deficits; 7q36.1‐q36.2, 7q36.3, 16p12.1, and 17q22). These results highlight the reproducibility of dyslexia linkage signals, even without formally significant lod scores, and suggest dyslexia predisposing genes with relatively major effects and locus heterogeneity. The largest lod score (2.80) occurred at 17q22 within the MSI2 gene, involved in neuronal stem cell lineage proliferation. Interestingly, the 4q13.1 linkage peak (lod 2.34) occurred immediately upstream of the LPHN3 gene, recently reported both linked and associated with ADHD. Separate analyses of larger pedigrees revealed lods >2.3 at 1–3 regions per family; one family showed strong linkage (lod 2.9) to a known dyslexia locus (18p11) not detected in our overall data, demonstrating the value of analyzing single large pedigrees. Association analysis identified no SNPs with genome‐wide significance, although a borderline significant SNP (P = 6 × 10^–7) occurred at 5q35.1 near FGF18, involved in laminar positioning of cortical neurons during development. We conclude that dyslexia genes with relatively major effects exist, are detectable by linkage analysis despite genetic heterogeneity, and show substantial overlapping predisposition with ADHD and autism.     

Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle

A genome‐wide association study of 2098 progeny‐tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine‐map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP‐by‐trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis‐related traits. Among them, 21 SNP‐by‐trait combinations exceeded the genome‐wide significant threshold. For 12 chromosomes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker‐based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL.     

Quantitative Trait Loci for Metabolic Syndrome in the Hypertension Genetic Epidemiology Network Study

As part of the Hypertension Genetic Epidemiology Network study, genome scans were performed in two ethnicities on the categorical metabolic syndrome (MetS). Genome scans were performed also on the factor scores produced by factor analysis (quantitative MetS). Heritabilities were highest for the obesity‐insulin (INS) factor and lowest for blood pressure (BP) and central obesity. Seventeen unique putative quantitative trait loci (QTLs) yielded logarithm of the odds ratio (LOD) scores in excess of 1.7, 8 for blacks and 9 for whites. Important QTL findings in whites included an LOD score of 3.19 on chromosome 15q15 for the BP factor, 3.08 on chromosome 8p23 for the lipids‐INS factor, and 3.07 on chromosome 3p26 for the obesity‐INS factor. In blacks, after excluding type 2 diabetics, important QTLs were identified, including an LOD score of 2.77 on 13p12 for the obesity‐INS factor and 2.63 on chromosome 11q24 for the lipids‐INS factor. Categorical MetS had lower results than quantitative MetS. Notably, several loci identified overlap with those identified in other studies for a single or group of traits. The most promising candidate loci on 11q24 for lipids‐INS and 13p12 for obesity‐INS in blacks, 8p23 for lipids‐INS, 14q24 for obesity‐INS, and 15q15 for BP in whites warrant further investigation.     

Multivariate linkage scan for metabolic syndrome traits in families with type 2 diabetes

The purpose of this study was to evaluate evidence for linkage to interrelated quantitative features of the metabolic syndrome (MetS). Data on eight quantitative MetS traits (body weight, waist circumference, systolic and diastolic blood pressure, high‐density lipoprotein (HDL) cholesterol, triglycerides (TGs), and fasting glucose and insulin measurements) and a 10 cM genome scan were available for 78 white families (n = 532 subjects). These data were used to conduct multipoint, multivariate linkage analyses, including tests for coincident linkage and complete pleiotropy. The strongest evidence for linkage from the bivariate analyses was observed on chromosome 1 (1p22.2) (HDL‐TG; univariate lod score equivalent (lod_eq = 3.99)) with stronger results from the trivariate analysis at the same location (HDL‐TG‐Insulin; lod_eq = 4.32). Seven additional susceptibility regions (lod_eq scores >1.9) were observed (1p36, 1q23, 2q21.2, 8q23.3, 14q23.2, 14q32.11, and 20p11.21). The results from this study indicate that several correlated traits of the MetS are influenced by the same gene(s) that account for some of the clustering of the MetS features.     

Quantitative trait loci and candidate genes underlying genotype by environment interaction in the response of Arabidopsis thaliana to drought

Drought stress was imposed on two sets of Arabidopsis thaliana genotypes grown in sand under short‐day conditions and analysed for several shoot and root growth traits. The response to drought was assessed for quantitative trait locus (QTL) mapping in a genetically diverse set of Arabidopsis accessions using genome‐wide association (GWA) mapping, and conventional linkage analysis of a recombinant inbred line (RIL) population. Results showed significant genotype by environment interaction (G×E) for all traits in response to different watering regimes. For the RIL population, the observed G×E was reflected in 17 QTL by environment interactions (Q×E), while 17 additional QTLs were mapped not showing Q×E. GWA mapping identified 58 single nucleotide polymorphism (SNPs) associated with loci displaying Q×E and an additional 16 SNPs associated with loci not showing Q×E. Many candidate genes potentially underlying these loci were suggested. The genes for RPS3C and YLS7 were found to contain conserved amino acid differences when comparing Arabidopsis accessions with strongly contrasting drought response phenotypes, further supporting their candidacy. One of these candidate genes co‐located with a QTL mapped in the RIL population.     

Identification of loci controlling adaptation in Chinese soya bean landraces via a combination of conventional and bioclimatic GWAS

Landraces often contain genetic diversity that has been lost in modern cultivars, including alleles that confer enhanced local adaptation. To comprehensively identify loci associated with adaptive traits in soya bean landraces, for example flowering time, a population of 1938 diverse landraces and 97 accessions of the wild progenitor of cultivated soya bean, Glycine soja was genotyped using tGBS^®. Based on 99 085 high‐quality SNPs, landraces were classified into three sub‐populations which exhibit geographical genetic differentiation. Clustering was inferred from STRUCTURE, principal component analyses and neighbour‐joining tree analyses. Using phenotypic data collected at two locations separated by 10 degrees of latitude, 17 trait‐associated SNPs (TASs) for flowering time were identified, including a stable locus Chr12:5914898 and previously undetected candidate QTL/genes for flowering time in the vicinity of the previously cloned flowering genes, E1 and E2. Using passport data associated with the collection sites of the landraces, 27 SNPs associated with adaptation to three bioclimatic variables (temperature, daylength, and precipitation) were identified. A series of candidate flowering genes were detected within linkage disequilibrium (LD) blocks surrounding 12 bioclimatic TASs. Nine of these TASs exhibit significant differences in flowering time between alleles within one or more of the three individual sub‐populations. Signals of selection during domestication and/or subsequent landrace diversification and adaptation were detected at 38 of the 44 flowering and bioclimatic TASs. Hence, this study lays the groundwork to begin breeding for novel environments predicted to arise following global climate change.     

The Human Obesity Gene Map: The 1998 Update

PÉRUSSE, LOUIS, YVON C. CHAGNON, JOHN WEISNAGEL, AND CLAUDE BOUCHARD. The human obesity gene map: the 1998 update. Obes Res. 1999;7:111–129. An update of the human obesity gene map incorporating published results up to the end of October 1998 is presented. Evidence from the human obesity cases caused by single gene mutations; other Mendelian disorders exhibiting obesity as a clinical feature; quantitative trait loci uncovered in human genome-wide scans and in crossbreeding experiments with mouse, rat, and pig models; association and case-control studies with candidate genes; and linkage studies with genes and other markers is reviewed. The most noticeable changes from the 1997 update is the number of obesity cases due to single gene mutations that increased from three cases due to mutations in two genes to 25 cases due to 12 mutations in seven genes. A look at the obesity gene map depicted in Figure 1 reveals that putative loci affecting obesity-related phenotypes are found on all but chromosome Y of the human chromosomes. Some chromosomes show at least three putative loci related to obesity on both arms (1, 2, 3, 6, 7, 8, 9, 11, 17, 19, 20, and X) and several on one chromosome arm only (4q, 5q, 10q, 12q, 13q, 15q, 16p, and 22q). The number of genes and other markers that have been associated or linked with human obesity phenotypes is increasing very rapidly and now approaches 27.     

Genome-wide linkage scan for the metabolic syndrome: the GENNID study

In the United States, the metabolic syndrome (MetS) constitutes a major public health problem with over 47 million persons meeting clinical criteria for MetS. Numerous studies have suggested genetic susceptibility to MetS. The goals of this study were (i) to identify susceptibility loci for MetS in well-characterized families with type 2 diabetes (T2D) in four ethnic groups and (ii) to determine whether evidence for linkage varies across the four groups. The GENNID study (Genetics of NIDDM) is a multicenter study established by the American Diabetes Association in 1993 and comprises a comprehensive, well-characterized resource of T2D families from four ethnic groups (whites, Mexican Americans, African Americans, and Japanese Americans). Principal component factor analysis (PCFA) was used to define quantitative phenotypes of the MetS. Variance components linkage analysis was conducted using microsatellite markers from a 10-cM genome-wide linkage scan, separately in each of the four ethnic groups. Three quantitative MetS factors were identified by PCFA and used as phenotypes for MetS: (i) a weight/waist factor, (ii) a blood pressure factor, and (iii) a lipid factor. Evidence for linkage to each of these factors was observed. For each ethnic group, our results suggest that several regions harbor susceptibility genes for the MetS. The strongest evidence for linkage for MetS phenotypes was observed on chromosome 2 (2q12.1-2q13) in the white sample and on chromosome 3 (3q26.1-3q29) in the Mexican-American sample. In conclusion, the results suggest that several regions harbor MetS susceptibility genes and that heterogeneity may exist across groups.     

Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping

Kernel size‐related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P < 2.25 × 10^?6) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P < 1 × 10^?3) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable‐effect SNPs and the co‐localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co‐localized SNPs, of which zma‐miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1, CUC2 and NAC6 in vitro. Overexpression of zma‐miR164e resulted in the down‐regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker‐assisted selection (MAS) for high‐yield breeding in maize.     

Multiple Genes Influence BMI on Chromosome 7q31–34: The NHLBI Family Heart Study

The National Heart, Lung, and Blood Institute Family Heart Study (FHS) genome‐wide linkage scan identified a region of chromosome 7q31–34 with a lod score of 4.9 for BMI at D7S1804 (131.9 Mb). We report the results of linkage and association to BMI in this region for two independent FHS samples. The first sample includes 225 FHS pedigrees with evidence of linkage to 7q31–34, using 1,132 single‐nucleotide polymorphisms (SNPs) and 7 microsatellites. The second represents a case–control sample (318 cases; BMI >25 and 325 controls; BMI <25) derived from unrelated FHS participants who were not part of the genome scan. The latter set was genotyped for 606 SNPs, including 37 SNPs with prior evidence for association in the linked families. Although variance components linkage analysis using only SNPs generated a peak lod score that coincided with the original linkage scan at 131.9 Mb, a conditional linkage analysis showed evidence of a second quantitative trait locus (QTL) near 143 cM influencing BMI. Three SNPs (rs161339, rs12673281, and rs1993068) located near the three genes pleiotrophin (PTN), diacylglycerol (DAG) kinase iota (DGKι), and cholinergic receptor, muscarinic 2 (CHRM2) demonstrated significant association in both linked families (P = 0.0005, 0.002, and 0.03, respectively) and the case–control sample (P = 0.01, 0.0003, and 0.03, respectively), regardless of the genetic model tested. These findings suggest that several genes may be associated with BMI in the 7q31–34 region.     

Insight in glioma susceptibility through an analysis of 6p22.3, 12p13.33-12.1, 17q22-23.2 and 18q23 SNP genotypes in familial and non-familial glioma

The risk of glioma has consistently been shown to be increased twofold in relatives of patients with primary brain tumors (PBT). A recent genome-wide linkage study of glioma families provided evidence for a disease locus on 17q12-21.32, with the possibility of four additional risk loci at 6p22.3, 12p13.33-12.1, 17q22-23.2, and 18q23. To identify the underlying genetic variants responsible for the linkage signals, we compared the genotype frequencies of 5,122 SNPs mapping to these five regions in 88 glioma cases with and 1,100 cases without a family history of PBT (discovery study). An additional series of 84 familial and 903 non-familial cases were used to replicate associations. In the discovery study, 12 SNPs showed significant associations with family history of PBT (P?相似文献   

A genome-wide linkage scan for quantitative trait loci underlying obesity related phenotypes in 434 Caucasian families

To identify quantitative trait loci (QTLs) that contribute to obesity, we performed a large-scale whole genome linkage scan (WGS) involving 4,102 individuals from 434 Caucasian families. The most pronounced linkage evidence was found at the genomic region 20p11-12 for fat mass (LOD = 3.31) and percentage fat mass (PFM) (LOD = 2.92). We also identified several regions showing suggestive linkage signals (threshold LOD = 1.9) for obesity phenotypes, including 5q35, 8q13, 10p12, and 17q11.     

A genome-wide association study of seed protein and oil content in soybean

Background

Association analysis is an alternative to conventional family-based methods to detect the location of gene(s) or quantitative trait loci (QTL) and provides relatively high resolution in terms of defining the genome position of a gene or QTL. Seed protein and oil concentration are quantitative traits which are determined by the interaction among many genes with small to moderate genetic effects and their interaction with the environment. In this study, a genome-wide association study (GWAS) was performed to identify quantitative trait loci (QTL) controlling seed protein and oil concentration in 298 soybean germplasm accessions exhibiting a wide range of seed protein and oil content.

Results

A total of 55,159 single nucleotide polymorphisms (SNPs) were genotyped using various methods including Illumina Infinium and GoldenGate assays and 31,954 markers with minor allele frequency >0.10 were used to estimate linkage disequilibrium (LD) in heterochromatic and euchromatic regions. In euchromatic regions, the mean LD (r ² ) rapidly declined to 0.2 within 360 Kbp, whereas the mean LD declined to 0.2 at 9,600 Kbp in heterochromatic regions. The GWAS results identified 40 SNPs in 17 different genomic regions significantly associated with seed protein. Of these, the five SNPs with the highest associations and seven adjacent SNPs were located in the 27.6-30.0 Mbp region of Gm20. A major seed protein QTL has been previously mapped to the same location and potential candidate genes have recently been identified in this region. The GWAS results also detected 25 SNPs in 13 different genomic regions associated with seed oil. Of these markers, seven SNPs had a significant association with both protein and oil.

Conclusions

This research indicated that GWAS not only identified most of the previously reported QTL controlling seed protein and oil, but also resulted in narrower genomic regions than the regions reported as containing these QTL. The narrower GWAS-defined genome regions will allow more precise marker-assisted allele selection and will expedite positional cloning of the causal gene(s).     

Genomic architecture of ecologically divergent body shape in a pair of sympatric crater lake cichlid fishes

Determining the genetic bases of adaptations and their roles in speciation is a prominent issue in evolutionary biology. Cichlid fish species flocks are a prime example of recent rapid radiations, often associated with adaptive phenotypic divergence from a common ancestor within a short period of time. In several radiations of freshwater fishes, divergence in ecomorphological traits — including body shape, colour, lips and jaws — is thought to underlie their ecological differentiation, specialization and, ultimately, speciation. The Midas cichlid species complex (Amphilophus spp.) of Nicaragua provides one of the few known examples of sympatric speciation where species have rapidly evolved different but parallel morphologies in young crater lakes. This study identified significant QTL for body shape using SNPs generated via ddRAD sequencing and geometric morphometric analyses of a cross between two ecologically and morphologically divergent, sympatric cichlid species endemic to crater Lake Apoyo: an elongated limnetic species (Amphilophus zaliosus) and a high‐bodied benthic species (Amphilophus astorquii). A total of 453 genome‐wide informative SNPs were identified in 240 F₂ hybrids. These markers were used to construct a genetic map in which 25 linkage groups were resolved. Seventy‐two segregating SNPs were linked to 11 QTL. By annotating the two most highly supported QTL‐linked genomic regions, genes that might contribute to divergence in body shape along the benthic–limnetic axis in Midas cichlid sympatric adaptive radiations were identified. These results suggest that few genomic regions of large effect contribute to early stage divergence in Midas cichlids.     

Genome‐wide linkage analysis for human longevity: Genetics of Healthy Aging Study

Clear evidence exists for heritability of human longevity, and much interest is focused on identifying genes associated with longer lives. To identify such longevity alleles, we performed the largest genome‐wide linkage scan thus far reported. Linkage analyses included 2118 nonagenarian Caucasian sibling pairs that have been enrolled in 15 study centers of 11 European countries as part of the Genetics of Healthy Aging (GEHA) project. In the joint linkage analyses, we observed four regions that show linkage with longevity; chromosome 14q11.2 (LOD = 3.47), chromosome 17q12‐q22 (LOD = 2.95), chromosome 19p13.3‐p13.11 (LOD = 3.76), and chromosome 19q13.11‐q13.32 (LOD = 3.57). To fine map these regions linked to longevity, we performed association analysis using GWAS data in a subgroup of 1228 unrelated nonagenarian and 1907 geographically matched controls. Using a fixed‐effect meta‐analysis approach, rs4420638 at the TOMM40/APOE/APOC1 gene locus showed significant association with longevity (P‐value = 9.6 × 10^?8). By combined modeling of linkage and association, we showed that association of longevity with APOEε4 and APOEε2 alleles explain the linkage at 19q13.11‐q13.32 with P‐value = 0.02 and P‐value = 1.0 × 10^?5, respectively. In the largest linkage scan thus far performed for human familial longevity, we confirm that the APOE locus is a longevity gene and that additional longevity loci may be identified at 14q11.2, 17q12‐q22, and 19p13.3‐p13.11. As the latter linkage results are not explained by common variants, we suggest that rare variants play an important role in human familial longevity.     

Genomic arrangement of salinity tolerance QTLs in salmonids: A comparative analysis of Atlantic salmon (Salmo salar) with Arctic charr (Salvelinus alpinus) and rainbow trout (

ABSTRACT: BACKGROUND: Quantitative trait locus (QTL) studies show that variation in salinity tolerance in Arctic charr and rainbow trout has a genetic basis, even though both these species have low to moderate salinity tolerance capacities. QTL were observed to localize to homologous linkage group segments within putative chromosomal regions possessing multiple candidate genes. We compared salinity tolerance QTL in rainbow trout and Arctic charr to those detected in a higher salinity tolerant species, Atlantic salmon. The highly derived karyotype of Atlantic salmon allows for the assessment of whether disparity in salinity tolerance in salmonids is associated with differences in genetic architecture. To facilitate these comparisons, we examined the genomic synteny patterns of key candidate genes in the other model teleost fishes that have experienced three whole-genome duplication (3R) events which preceded a fourth (4R) whole genome duplication event common to all salmonid species. RESULTS: Nine linkage groups contained chromosome-wide significant QTL (AS-2, -4p, -4q, -5, -9, -12p, -12q, -14q -17q, -22, and [MINUS SIGN]23), while a single genome-wide significant QTL was located on AS-4q. Salmonid genomes shared the greatest marker homology with the genome of three-spined stickleback. All linkage group arms in Atlantic salmon were syntenic with at least one stickleback chromosome, while 18 arms had multiple affinities. Arm fusions in Atlantic salmon were often between multiple regions bearing salinity tolerance QTL. Nine linkage groups in Arctic charr and six linkage group arms in rainbow trout currently have no synteny alignments with stickleback chromosomes, while eight rainbow trout linkage group arms were syntenic with multiple stickleback chromosomes. Rearrangements in the stickleback lineage involving fusions of ancestral arm segments could account for the 21 chromosome pairs observed in the stickleback karyotype. CONCLUSIONS: Salinity tolerance in salmonids from three genera is to some extent controlled by the same loci. Synteny between QTL in salmonids and candidate genes in stickleback suggests genetic variation at candidate gene loci could affect salinity tolerance in all three salmonids investigated. Candidate genes often occur in pairs on chromosomes, and synteny patterns indicate these pairs are generally conserved in 2R, 3R, and 4R genomes. Synteny maps also suggest that the Atlantic salmon genome contains three larger syntenic combinations of candidate genes that are not evident in any of the other 2R, 3R, or 4R genomes examined. These larger synteny tracts appear to have resulted from ancestral arm fusions that occurred in the Atlantic salmon ancestor. We hypothesize that the superior hypo-osmoregulatory efficiency that is characteristic of Atlantic salmon may be related to these clusters.     

Meta-analysis of genome-wide linkage studies in BMI and obesity

Objective: The objective was to provide an overall assessment of genetic linkage data of BMI and BMI‐defined obesity using a nonparametric genome scan meta‐analysis. Research Methods and Procedures: We identified 37 published studies containing data on over 31,000 individuals from more than >10,000 families and obtained genome‐wide logarithm of the odds (LOD) scores, non‐parametric linkage (NPL) scores, or maximum likelihood scores (MLS). BMI was analyzed in a pooled set of all studies, as a subgroup of 10 studies that used BMI‐defined obesity, and for subgroups ascertained through type 2 diabetes, hypertension, or subjects of European ancestry. Results: Bins at chromosome 13q13.2‐ q33.1, 12q23‐q24.3 achieved suggestive evidence of linkage to BMI in the pooled analysis and samples ascertained for hypertension. Nominal evidence of linkage to these regions and suggestive evidence for 11q13.3‐22.3 were also observed for BMI‐defined obesity. The FTO obesity gene locus at 16q12.2 also showed nominal evidence for linkage. However, overall distribution of summed rank p values <0.05 is not different from that expected by chance. The strongest evidence was obtained in the families ascertained for hypertension at 9q31.1‐qter and 12p11.21‐q23 (p < 0.01). Conclusion: Despite having substantial statistical power, we did not unequivocally implicate specific loci for BMI or obesity. This may be because genes influencing adiposity are of very small effect, with substantial genetic heterogeneity and variable dependence on environmental factors. However, the observation that the FTO gene maps to one of the highest ranking bins for obesity is interesting and, while not a validation of this approach, indicates that other potential loci identified in this study should be investigated further.     

A genome‐wide association study to detect genetic variation for postpartum dysgalactia syndrome in five commercial pig breeding lines

Postpartum dysgalactia syndrome (PDS) in sows is an important disease after parturition with a relevant economic impact, affecting the health and welfare of both sows and piglets. The genetic background of this disease has been discussed and its heritability estimated, but further genetic analyses are lacking in detail. The aim of the current study was to detect loci affecting the susceptibility to PDS through a genome‐wide association approach. The study was designed as a family‐based association study with matched sampling of affected sows and healthy half‐ or full‐sib control sows on six farms. For the study, 597 sows (322 affected vs. 275 healthy control sows) were genotyped on 62 163 single nucleotide polymorphisms (SNPs) using the Illumina PorcineSNP60 BeadChip. After quality control, 585 sows (314 affected vs. 271 healthy control sows) and 49 740 SNPs remained for further analysis. Statistics were performed mainly with the r package genabel and included a principal component analysis. A statistically significant genome‐wide associated SNP was identified on porcine chromosome (SSC) 17. Further promising results with moderate significance were detected on SSC 13 and on an unplaced scaffold with an older annotation on SSC 15. The PRICKLE2 and NRP2 genes were identified as candidate genes near associated SNPs. Several quantitative trait loci (QTL) have been previously described in these genomic regions, including QTL for mammary gland condition, as teat number and non‐functional nipples QTL, as well as QTL for body temperature and gestation length.     

Association mapping of morphological traits in wild and captive zebra finches: reliable within,but not between populations

Identifying causal genetic variants underlying heritable phenotypic variation is a long‐standing goal in evolutionary genetics. We previously identified several quantitative trait loci (QTL) for five morphological traits in a captive population of zebra finches (Taeniopygia guttata) by whole‐genome linkage mapping. We here follow up on these studies with the aim to narrow down on the quantitative trait variants (QTN) in one wild and three captive populations. First, we performed an association study using 672 single nucleotide polymorphisms (SNPs) within candidate genes located in the previously identified QTL regions in a sample of 939 wild‐caught zebra finches. Then, we validated the most promising SNP–phenotype associations (n = 25 SNPs) in 5228 birds from four populations. Genotype–phenotype associations were generally weak in the wild population, where linkage disequilibrium (LD) spans only short genomic distances. In contrast, in captive populations, where LD blocks are large, apparent SNP effects on morphological traits (i.e. associations) were highly repeatable with independent data from the same population. Most of those SNPs also showed significant associations with the same trait in other captive populations, but the direction and magnitude of these effects varied among populations. This suggests that the tested SNPs are not the causal QTN but rather physically linked to them, and that LD between SNPs and causal variants differs between populations due to founder effects. While the identification of QTN remains challenging in nonmodel organisms, we illustrate that it is indeed possible to confirm the location and magnitude of QTL in a population with stable linkage between markers and causal variants.