Pathway deregulation and expression QTLs in response to Actinobacillus pleuropneumoniae infection in swine

Actinobacillus (A.) pleuropneumoniae is among the most important pathogens in pig. The agent causes severe economic losses due to decreased performance, the occurrence of acute or chronic pleuropneumonia, and an increase in death incidence. Since therapeutics cannot be used in a sustainable manner, and vaccination is not always available, new prophylactic measures are urgently needed. Recent research has provided evidence for a genetic predisposition in susceptibility to A. pleuropneumoniae in a Hampshire × German Landrace F2 family with 170 animals. The aim of the present study is to characterize the expression response in this family in order to unravel resistance and susceptibility mechanisms and to prioritize candidate genes for future fine mapping approaches. F2 pigs differed distinctly in clinical, pathological, and microbiological parameters after challenge with A. pleuropneumoniae. We monitored genome-wide gene expression from the 50 most and 50 least susceptible F2 pigs and identified 171 genes differentially expressed between these extreme phenotypes. We combined expression QTL analyses with network analyses and functional characterization using gene set enrichment analysis and identified a functional hotspot on SSC13, including 55 eQTL. The integration of the different results provides a resource for candidate prioritization for fine mapping strategies, such as TF, TFRC, RUNX1, TCN1, HP, CD14, among others.     

Identification of quantitative trait loci linked to Ceratocystis wilt resistance in cacao

Ceratocystis wilt (CW) in cacao (Theobroma cacao L.), caused by Ceratocystis cacaofunesta, is a drastic disease that results in plant death. The pathogen was recently identified in the major cacao-producing region of Brazil?CBahia. The identification of genetic markers tightly linked to disease resistance loci is a valuable tool for the development of resistant cultivars using marker-assisted selection (MAS). Branches of 143 six-year-old individuals of an F2 Sca 6?×?ICS 1 population were wounded by making a 3-mm deep cut with a sterile scalpel, and inoculated with a 20-??l drop of a spore suspension of 3?×?10⁴?CFU/ml. The inoculation method used allowed the population to be quantitatively phenotyped. The length of the xylem discoloration followed a continuous distribution. These results imply that the resistance was quantitatively inherited. Quantitative trait loci (QTL) analysis revealed two genomic regions (in linkage groups 3 and 9) associated with CW resistance. The QTL explained individually from 6.9 to 8.6?% of the phenotypic variation. The QTL identified are crucial for identifying genes for resistance and can be applied in the genetic breeding of cacao using MAS.     

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.     

Generation and exploration of a dense genetic map in a region of a QTL affecting corpora lutea in a Meishan × Yorkshire cross

Previously genomic scans revealed quantitative trait loci (QTL) on porcine Chromosome 8 (SSC8) as significantly affecting the number of corpora lutea (CL) in swine. In one study, statistical evidence for the putative QTL was found in the chromosomal region defined by the microsatellites (MS) SW205, SW444, SW206, and SW29. A Yeast Artificial Chromosome library was screened by using the corresponding primers for clones containing these MS by PCR. From five positive YAC clones, 10 additional MS were isolated and mapped to SSC8 with the INRA-University of Minnesota porcine Radiation Hybrid (IMpRH) panel. The genetic map position of the QTL has been refined by addition of these 10 markers. The QTL evaluation included pedigrees of F₂-intercross Meishan × Yorkshire design, with phenotypic data of 108 F₂ female offspring and genotypic data for 29 MS markers on SSC8. The analysis was performed by using the least squares regression method. The calculated QTL effect for CL obtained by the multilocus least squares method showed a maximum test statistic (F value = 13.98) at position 99 cM between three MS derived from YACs containing SW205 and SW1843 spanning an interval of 7.1 cM. The point-wise (nominal) P-value was 5.21 × 10⁻⁶ corresponding to a genome-wide P-value of 0.009. The additive QTL effect explained 17.4% of the phenotypic variance. Received: 23 December 2000 / Accepted: 07 May 2001     

Identification of QTLs Conferring Resistance to Deltamethrin in Culex pipiens pallens

Culex pipiens pallens is the most abundant Culex mosquito species in northern China and is an important vector of bancroftian filariasis and West Nile virus. Deltamethrin is an insecticide that is widely used for mosquito control, however resistance to this and other insecticides has become a major challenge in the control of vector-borne diseases that appear to be inherited quantitatively. Furthermore, the genetic basis of insecticide resistance remains poorly understood. In this study, quantitative trait loci (QTL) mapping of resistance to deltamethrin was conducted in F₂ intercross segregation populations using bulked segregation analysis (BSA) and amplified fragment length polymorphism markers (AFLP) in Culex pipiens pallens. A genetic linkage map covering 381 cM was constructed and a total of seven QTL responsible for resistance to deltamethrin were detected by composite interval mapping (CIM), which explained 95% of the phenotypic variance. The major QTL in linkage group 2 accounted for 62% of the variance and is worthy of further study. 12 AFLP markers in the map were cloned and the genomic locations of these marker sequences were determined by applying the Basic Local Alignment Search Tool (BLAST) tool to the genome sequence of the closely related Culex quinquefasciatus. Our results suggest that resistance to deltamethrin is a quantitative trait under the control of a major QTL in Culex pipiens pallens. Cloning of related AFLP markers confirm the potential utility for anchoring the genetic map to the physical map. The results provide insight into the genetic architecture of the trait.     

A Genome Scan for Quantitative Trait Loci Associated with Vibrio anguillarum Infection Resistance in Japanese Flounder (Paralichthys olivaceus) by Bulked Segregant Analysis

A recent genetic linkage map was employed to detect quantitative trait loci (QTLs) associated with Vibrio anguillarum resistance in Japanese flounder. An F1 family established and challenged with V. anguillarum in 2009 was used for QTL mapping. Of the 221 simple sequence repeat (SSR) markers used to detect polymorphisms in the parents of F1, 170 were confirmed to be polymorphic. The average distance between the markers was 10.6 cM. Equal amounts of genomic DNA from 15 fry that died early and from 15 survivors were pooled separately to constitute susceptible bulk and resistance bulk DNA. Bulked segregant analysis and QTL mapping were combined to detect candidate SSR markers and regions associated with the disease. A genome scan identified four polymorphic SSR markers, two of which were significantly different between susceptible and resistance bulk (P?=?0.008). These two markers were located in linkage group (LG) 7; therefore, all the SSR markers in LG7 were genotyped in all the challenged fry by single marker analysis. Using two different models, 11–17 SSR markers were detected with different levels of significance. To confirm the associations of these markers with the disease, composite interval mapping was employed to genotype all the challenged individuals. One and three QTLs, which explained more than 60 % of the phenotypic variance, were detected by the two models. Two of the QTLs were located at 48.6 cM. The common QTL may therefore be a major candidate region for disease resistance against V. anguillarum infection.     

A quantitative trait locus for oleic fatty acid content on Sus scrofa chromosome 7

A partial genome scan using microsatellite markers was conducted to detect quantitative trait loci (QTLs) for 10 fatty acid contents of backfat on 15 chromosomes in a porcine resource population. Two QTLs were discovered on Sus scrofa chromosome 4 (SSC4) and SSC7. The QTL on SSC4 was located between marker loci sw1336 and sw512, and this QTL was detected (P < 0.05) only for linoleic acid. Its position was in proximity of those mapped for linoleic acid content in previous studies. The QTL on SSC7 was mapped between markers swr1343 and sw2155, and it was significant (P < 0.05) only for oleic acid. A novelty of the QTL for oleic acid was suggested because the QTL was located far from any other QTLs previously mapped for fatness traits. The QTL on SSC7 explained 19% of phenotypic variation for oleic acid content. Further studies on fine mapping and positional comparative candidate gene analysis would be the next step toward better understanding of the genetic architecture of fatty acid contents.     

猪部分内脏器官性状和乳头数的QTL检测

对内脏器官重量性状的QTL定位研究,所见报道不多;对于猪的繁殖性状,尚需做进一步的探讨。本研究在总共214头(180头F2个体)组成的资源家系中,在猪的SSC4、SSC6、SSC7、SSC8 和 SSC13上共选取39个微卫星标记,检测了8种内脏器官的重量性状:心重 (HW)、肺重 (LW)、肝 胆重 (LGW)、脾重 (SPW)、胃重 (STW)、小肠重(SIW)、大肠重(LIW) 和肾重(KW);其他一些胴体性状:胴体长性状1(自第一颈椎,CL1)、胴体长性状2(自第一胸椎,CL2)、肋骨数(RNS)和繁殖性状乳头数(TNS)的QTL定位。结果表明,检测到3个染色体极显著水平的QTL(P≤0.01),它们是HW QTL定位在SSC6上30 cM处,RNS QTL定位在SSC7上115 cM处和TNS QTL定位在SSC7上 110 cM处;另外6个染色体显著水平的QTL(P≤0.05)是:LW(SSC13上119 cM处)、LGW(SSC6上94 cM处)、SPW(SSC8上106 cM处)、SIW(SSC 4上0 cM处)、LIW(SSC 4上170 cM 处)和TNS(SSC 6上95 cM处)。上述QTL解释的表型变异从 0.04% 到 14.06%,有些位点的 QTL 可以解释表型变异的 10%以上,如 HW 的 QTL 解释表型变异的9.52%、SIW的QTL解释表型变异的13.47%、定位在SSC6上的TNS QTL解释表型变异的14.06%,而定位在 SSC7上的TNS QTL解释表型变异的11.30%。多数内脏器官重量性状的QTL定位结果未见报道。胴体长未见显著水平的QTL,而在SSC7上定位染色体极显著水平的肋骨数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.     

Three novel quantitative trait loci for skin thickness in swine identified by linkage and genome‐wide association studies

Skin is the largest organ in the pig body and plays a key role in protecting the body against pathogens and excessive water loss. Deciphering the genetic basis of swine skin thickness would enrich our knowledge about the skin. To identify the loci for porcine skin thickness, we first performed a genome scan with 194 microsatellite markers in a White Duroc × Erhualian F₂ intercross. We identified three genome‐wide significant QTL on pig chromosomes (SSC) 4, 7 and 15 using linkage analysis. The most significant QTL was found on SSC7 with a small confidence interval of ~5 cM, explaining 23.9 percent of phenotypic variance. Further, we conducted a genome‐wide association study (GWAS) using Illumina PorcineSNP60 Beadchips for the F₂ pedigree and a population of Chinese Sutai pigs. We confirmed significant QTL in the F₂ pedigree and replicated QTL on SSC15 in Chinese Sutai pigs. A meta‐analysis of GWASs on both populations detected a genomic region associated with skin thickness on SSC4. GWAS results were generally consistent with QTL mapping. Identical‐by‐descent analysis defined QTL on SSC7 in a 683‐kb region harboring an interesting candidate gene: HMGA1. On SSC15, the linkage disequilibrium analysis showed a haplotype block of 2.20 Mb that likely harbors the gene responsible for skin thickness. Our findings provide novel insights into the genetic basis of swine skin thickness, which would benefit further understanding of porcine skin function.     

Quantitative Trait Loci (QTL) Associated with Resistance to a Monogenean Parasite (Benedenia seriolae) in Yellowtail (Seriola quinqueradiata) through Genome Wide Analysis

Benedenia infections caused by the monogenean fluke ectoparasite Benedenia seriolae seriously impact marine finfish aquaculture. Genetic variation has been inferred to play a significant role in determining the susceptibility to this parasitic disease. To evaluate the genetic basis of Benedenia disease resistance in yellowtail (Seriola quinqueradiata), a genome-wide and chromosome-wide linkage analyses were initiated using F₁ yellowtail families (n = 90 per family) based on a high-density linkage map with 860 microsatellite and 142 single nucleotide polymorphism (SNP) markers. Two major quantitative trait loci (QTL) regions on linkage groups Squ2 (BDR-1) and Squ20 (BDR-2) were identified. These QTL regions explained 32.9–35.5% of the phenotypic variance. On the other hand, we investigated the relationship between QTL for susceptibility to B. seriolae and QTL for fish body size. The QTL related to growth was found on another linkage group (Squ7). As a result, this is the first genetic evidence that contributes to detailing phenotypic resistance to Benedenia disease, and the results will help resolve the mechanism of resistance to this important parasitic infection of yellowtail.     

Identification of quantitative trait loci for bruchid (Caryedon serratus Olivier) resistance components in cultivated groundnut (Arachis hypogaea L.)

Groundnut bruchid (Caryedon serratus Olivier) is a major storage insect pest that significantly lowers the quality and market acceptance of the produce. Screening for resistance against groundnut bruchid in field conditions is difficult due to the variation in environmental factors and possible occurrence of biotypes. Hence, identification of tightly linked markers or quantitative trait loci (QTLs) is needed for selection and pyramiding of resistance genes for durable resistance. A population of recombinant inbred lines derived from a cross between VG 9514 (resistant) and TAG 24 (susceptible) was screened for five component traits of bruchid resistance in 2 years. The same population was genotyped with 221 polymorphic marker loci. A genetic linkage map covering 1,796.7 cM map distance was constructed with 190 marker loci in cultivated groundnut. QTL analysis detected thirteen main QTLs for four components of bruchid resistance in nine linkage groups and 31 epistatic QTLs for total developmental period (TDP). Screening in 2 years for bruchid resistance identified two common main QTLs. The common QTL for TDP, qTDP-b08, explained 57–82 % of phenotypic variation, while the other common QTL for adult emergence, qAE2010/11-a02, explained 13–21 % of phenotypic variation. Additionally, three QTLs for TDP, adult emergence and number of holes and one QTL for pod weight loss were identified which explained 14–39 % of phenotypic variation. This is the first report on identification of multiple main and epistatic loci for bruchid resistance in groundnut.     

Detection of quantitative trait loci for teat number and female reproductive traits in Meishan × Large White F2 pigs

A quantitative trait locus (QTL) analysis of female reproductive data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. Six F1 boars and 23 F1 sows, progeny of six LW boars and six MS sows, produced 573 F2 females and 530 F2 males. Six traits, i.e. teat number (TN), age at puberty (AP), ovulation rate (OR), weight at mating (WTM), number of viable embryos (NVE) and embryo survival (ES) at 30 days of gestation were analysed. Animals were genotyped for a total of 137 markers covering the entire porcine genome. Analyses were carried out based on interval mapping methods, using a line-cross (LC) regression and a half-full sib (HFS) maximum likelihood test. Genome-wide (GW) highly significant (P < 0.001) QTL were detected for WTM on SSC 7 and for AP on SSC 13. They explained, respectively, 14.5% and 8.9% of the trait phenotypic variance. Other GW significant (P < 0.05) QTL were detected for TN on SSC 3, 7, 8, 16 and 17, for OR on SSC 4 and 5, and for ES on SSC 9. Two additional chromosome-wide significant (P < 0.05) QTL were detected for TN, three for WTM, four for AP, three for OR, three for NVE and two for ES. With the exception of the two above-mentioned loci, the QTL explained from 1.2% to 4.6% of trait phenotypic variance. QTL alleles were in most cases not fixed in the grand-parental populations and Meishan alleles were not systematically associated with higher reproductive performance.     

Saturation and mapping of a majorFusarium head blight resistance QTL on chromosome 3BS of Sumai 3 wheat

Fusarium head blight (FHB) is a destructive disease in wheat. The major quantitative trait locus (QTL) on 3BS from Sumai 3 and its derivatives has been used as a major source of the resistance to FHB worldwide, but the discrepancy in reported location of the major QTL could block its using in map based cloning and marker assisted selection. In this study, Chinese Spring-Sumai 3 chromosome 3B substitution line was used as resistant parent of the mapping population to reduce the confounded effect of genetic background in Sumai 3. The major QTL region was saturated with the Sequence Tagged Microsatellite (STM) and Sequence Tagged Site (STS) markers. A linkage map of chromosome 3B with 36 markers covering a genetic distance of 112.4 cM was constructed. Twelve new markers were inserted into the chromosome region where the major QTL was located. The average interval distance between markers was 1.5 cM. Multiple QTL Models (MQM) mapping indicated that the major QTL was located in the interval ofXgwm533 — Xsts9-1, and explained 45.6% of phenotypic variation of the resistance to FHB. The SSR (simple sequence repeat) markerXgwm533 and STM markerXstm748tcac are closely linked to the major QTL.     

QTL modulating ear size and erectness in pigs

Ear size and erectness are important conformation measurements in pigs. An F(2) population established by crossing European Large White (small, erect ears) with Chinese Meishan (large, flop ears) was used to study the genetic influence of the two ear traits for the first time. A linkage map incorporating 152 markers on 18 autosomal chromosomes was utilised in a genome scan for QTL. Significant QTL were found on SSC1, 5, 7, 9 and 12 for the two traits. The QTL on SSC5 and SSC7 had major effects and were significant at the genome-wide level (P < 0.01). The QTL on SSC1 for ear erectness also had a major effect and was genome-wide significant (P < 0.01). The 95% confidence interval (CI) of the ear size QTL on SSC5 spanned only 4 cM. The QTL on SSC7 for the two ear traits each had a CI of <20 cM, and their positions overlapped with those of the major QTL affecting subcutaneous fat depths on the same chromosome. This study provides insights on the complex genetic influences underlying pig ear traits and will facilitate positional candidate gene analysis to identify causative DNA variants.     

Comparative mapping of Raphanus sativus genome using Brassica markers and quantitative trait loci analysis for the Fusarium wilt resistance trait

Fusarium wilt (FW), caused by the soil-borne fungal pathogen Fusarium oxysporum is a serious disease in cruciferous plants, including the radish (Raphanus sativus). To identify quantitative trait loci (QTL) or gene(s) conferring resistance to FW, we constructed a genetic map of R. sativus using an F₂ mapping population derived by crossing the inbred lines ‘835’ (susceptible) and ‘B2’ (resistant). A total of 220 markers distributed in 9 linkage groups (LGs) were mapped in the Raphanus genome, covering a distance of 1,041.5 cM with an average distance between adjacent markers of 4.7 cM. Comparative analysis of the R. sativus genome with that of Arabidopsis thaliana and Brassica rapa revealed 21 and 22 conserved syntenic regions, respectively. QTL mapping detected a total of 8 loci conferring FW resistance that were distributed on 4 LGs, namely, 2, 3, 6, and 7 of the Raphanus genome. Of the detected QTL, 3 QTLs (2 on LG 3 and 1 on LG 7) were constitutively detected throughout the 2-year experiment. QTL analysis of LG 3, flanked by ACMP0609 and cnu_mBRPGM0085, showed a comparatively higher logarithm of the odds (LOD) value and percentage of phenotypic variation. Synteny analysis using the linked markers to this QTL showed homology to A. thaliana chromosome 3, which contains disease-resistance gene clusters, suggesting conservation of resistance genes between them.     

Identification of genomic regions involved in resistance against Sclerotinia sclerotiorum from wild Brassica oleracea

The lack of resistant source has greatly restrained resistance breeding of rapeseed (Brassica napus, AACC) against Sclerotinia sclerotiorum which causes severe yield losses in rapeseed production all over the world. Recently, several wild Brassica oleracea accessions (CC) with high level of resistance have been identified (Mei et al. in Euphytica 177:393–400, 2011), bringing a new hope to improve Sclerotinia resistance of rapeseed. To map quantitative trait loci (QTL) for Sclerotinia resistance from wild B. oleracea, an F2 population consisting of 149 genotypes, with several clones of each genotypes, was developed from one F1 individual derived from the cross between a resistant accession of wild B. oleracea (B. incana) and a susceptible accession of cultivated B. oleracea var. alboglabra. The F2 population was evaluated for Sclerotinia reaction in 2009 and 2010 under controlled condition. Significant differences among genotypes and high heritability for leaf and stem reaction indicated that genetic components accounted for a large portion of the phenotypic variance. A total of 12 QTL for leaf resistance and six QTL for stem resistance were identified in 2 years, each explaining 2.2–28.4 % of the phenotypic variation. The combined effect of alleles from wild B. oleracea reduced the relative susceptibility by 22.5 % in leaves and 15 % in stems on average over 2 years. A 12.8-cM genetic region on chromosome C09 of B. oleracea consisting of two major QTL intervals for both leaf and stem resistance was assigned into a 2.7-Mb genomic region on chromosome A09 of B. rapa, harboring about 30 putative resistance-related genes. Significant negative corrections were found between flowering time and relative susceptibility of leaf and stem. The association of flowering time with Sclerotinia resistance is discussed.     

Molecular mapping of a new source of Fusarium wilt resistance in tetraploid cotton (Gossypium hirsutum L.)

Fusarium wilt (FW) disease is an economically important disease of cotton worldwide and a major cause of crop losses in Australia and many other cotton-producing countries. Symptoms include wilting, vascular browning and death. Australian races of the causal agent Fusarium oxysporum f. sp. vasinfectum (Fov) are genetically distinct from those in other countries and are thought to have evolved from indigenous races. New sources of resistance for breeding are rare, as cotton cultivars with significant FW resistance against Fov isolates from other cotton-producing regions are usually susceptible to Australian Fov races. MCU-5, an Upland Indian cotton cultivar, has been identified as having improved resistance to Australian Fov and is being used to breed new commercial cultivars with higher resistance to FW. To investigate the genetic basis of the FW resistance in MCU-5, QTL analysis was performed on 244 F3 and 244 F4 families derived from an intraspecific cross between MCU-5 and Siokra 1-4, a cultivar highly sensitive to Australian Fov races. Resistance, as measured by leaf symptoms, vascular browning and survival, showed low to moderate heritability between generations. MCU-5 resistance to FW was found to be complex with three quantitative trait loci (QTL) identified in the F3, and eight in the F4, that explained between 9 and 41% of the phenotypic variation. The QTL were located on four linkage groups including chromosomes A6 (Chr 6), D4 (Chr 22) and D6 (Chr 25), with two QTL located in similar regions to previously identified FW resistance from the Sea Island cultivar Pima 3-79. The QTL identified in this study represent the first targets for marker-assisted selection of FW resistance in Australia.     

Quantitative trait loci mapping for fatty acid contents in the backfat on porcine chromosomes 1, 13, and 18

A partial genome scan using microsatellite markers was conducted in order to detect quantitative trait loci (QTLs) for 10 fatty acid contents of the backfat in a pig reference population. Two QTLs were found by studying SSC1, SSC13, and SSC18, where QTLs had already been identified for backfat thickness. A QTL was located between marker loci S0113 and SW974 on chromosome 1; this QTL was only significantly detected (P < 0.05) for linoleic acid. The other QTL was discovered between markers S0062 and S0120 on chromosome 18, and its significance only showed (P < 0.05) for myristic acid. The two QTLs mapped to the same location as the backfat thickness QTL. A third of the phenotypic variation was explained for linoleic acid by the QTL on chromosome 1, and a quarter for myristic acid by the QTL on chromosome 18. Further studies on fine mapping and positional comparative candidate gene analyses will be the next step toward a better understanding of the genetic architecture of fatty acid contents.     

Identification of quantitative trait loci for resistance to Verticillium wilt and yield parameters in hop (Humulus lupulus L.)

Verticillium wilt (VW) can cause substantial yield loss in hop particularly with the outbreaks of the lethal strain of Verticillium albo-atrum. To elucidate genetic control of VW resistance in hop, an F₁ mapping population derived from a cross of cultivar Wye Target, with the predicted genetic basis of resistance, and susceptible male breeding line BL2/1 was developed to assess wilting symptoms and to perform QTL mapping. The genetic linkage map, constructed with 203 markers of various types using a pseudo-testcross strategy, formed ten major linkage groups (LG) of the maternal and paternal maps, covering 552.98 and 441.1 cM, respectively. A significant QTL for VW resistance was detected at LOD 7 on a single chromosomal region on LG03 of both parental maps, accounting for 24.2–26.0 % of the phenotypic variance. QTL analysis for alpha-acid content and yield parameters was also performed on this map. QTLs for these traits were also detected and confirmed our previously detected QTLs in a different pedigree and environment. The work provides the basis for exploration of QTL flanking markers for possible use in marker-assisted selection.