Evidence for widespread epistatic interactions influencing Marek's disease virus viremia levels in chicken

Marek's disease (MD), a T cell lymphoma induced by the Marek's disease virus (MDV), is the main chronic infectious disease concern threatening the poultry industry. Enhancing genetic resistance to MD in commercial poultry is an attractive method to augment MD vaccines, which is currently the control method of choice. In order to implement this control strategy through marker-assisted selection (MAS), it is necessary to identify quantitative trait loci (QTL) or genes that influence MD incidence. Previous studies have demonstrated that it is possible to identify QTL that confer MD resistance in both experimental and commercial chickens. With the advent of the chicken genome sequence and new genomic tools, and evidence that interactions are important in understanding complex traits, the line 6 x 7 F(2) experimental resource population was re-evaluated with finer resolution for epistatic interactions. The F(2) population, consisting of 272 individuals and previously genotyped with 133 genetic markers, was combined along with 576 additional single nucleotide polymorphisms (SNPs) genotyped on 80 individuals in each of the distribution tails for MD and other associated traits, and tested for the presence of main effects and two-way epistatic interactions accounting for MD incidence, viremia titers, and length of survival. Main effects were generally not significant but a large number of highly significant interactions, involving loci located throughout the genome, were identified that account for MDV viremia titers in infected birds. These results suggest that resistance to MD is highly complex and will require the incorporation of epistatic interaction analyses and functional genomic approaches to reveal the underlying genetic basis.     

Genetic mapping of quantitative trait loci affecting susceptibility to Marek's disease virus induced tumors in F2 intercross chickens.

Marek''s disease (MD) is a lymphoproliferative disease caused by the MD virus (MDV), which costs the poultry industry nearly $1 billion annually. To identify quantitative trait loci (QTL) affecting MD susceptibility, the inbred lines 6(3) (MD resistant) and 7(2) (MD susceptible) were mated to create more than 300 F2 chickens. The F2 chickens were challenged with MDV JM strain, moderately virulent) at 1 wk of age and assessed for MD susceptibility. The QTL analysis was divided into three stages. In stage 1, 65 DNA markers selected from the chicken genetic maps were typed on the 40 most MD-susceptible and the 40 most MD-resistant F2 chickens, and 21 markers residing near suggestive QTL were revealed by analysis of variance (ANOVA). In stage 2, the suggestive markers plus available flanking markers were typed on 272 F2 chickens, and three suggestive QTL were identified by ANOVA. In stage 3, using the interval mapping program Map Manager and permutation tests, two significant and two suggestive MD QTL were identified on four chromosomal subregions. Three to five loci collected explained between 11 and 23% of the phenotypic MD variation, or 32-68% of the genetic variance. This study constitutes the first report in the domestic chicken on the mapping of non-major histocompatibility complex QTL affecting MD susceptibility.     

A genome-screen experiment to detect quantitative trait loci affecting resistance to facial eczema disease in sheep

Facial eczema (FE) is a secondary photosensitization disease arising from liver cirrhosis caused by the mycotoxin sporidesmin. The disease affects sheep, cattle, deer and goats, and costs the New Zealand sheep industry alone an estimated NZ$63M annually. A long-term sustainable solution to this century-old FE problem is to breed for disease-resistant animals by marker-assisted selection. As a step towards finding a diagnostic DNA test for FE sensitivity, we have conducted a genome-scan experiment to screen for quantitative trait loci (QTL) affecting this trait in Romney sheep. Four F₁ sires, obtained from reciprocal matings of FE resistant and susceptible selection-line animals, were used to generate four outcross families. The resulting half-sib progeny were artificially challenged with sporidesmin to phenotype their FE traits measured in terms of their serum levels of liver-specific enzymes, namely gamma-glutamyl transferase and glutamate dehydrogenase. In a primary screen using selective genotyping on extreme progeny of each family, a total of 244 DNA markers uniformly distributed over all 26 ovine autosomes (with an autosomal genome coverage of 79–91%) were tested for linkage to the FE traits. Data were analysed using Haley–Knott regression. The primary screen detected one significant and one suggestive QTL on chromosomes 3 and 8 respectively. Both the significant and suggestive QTL were followed up in a secondary screen where all progeny were genotyped and analysed; the QTL on chromosome 3 was significant in this analysis.     

A strategy to identify positional candidate genes conferring Marek''s disease resistance by integrating DNA microarrays and genetic mapping

Marker-assisted selection (MAS) to enhance genetic resistance to Marek's disease (MD), a herpesvirus-induced T cell cancer in chicken, is an attractive alternative to augment control with vaccines. Our earlier studies indicate that there are many quantitative trait loci (QTL) containing one or more genes that confer genetic resistance to MD. Unfortunately, it is difficult to sufficiently resolve these QTL to identify the causative gene and generate tightly linked markers. One possible solution is to identify positional candidate genes by virtue of gene expression differences between MD resistant and susceptible chicken using deoxyribonucleic acid (DNA) microarrays followed by genetic mapping of the differentially-expressed genes. In this preliminary study, we show that DNA microarrays containing approximately 1200 genes or expressed sequence tags (ESTs) are able to reproducibly detect differences in gene expression between the inbred ADOL lines 63 (MD resistant) and 72 (MD susceptible) of uninfected and Marek's disease virus (MDV)-infected peripheral blood lymphocytes. Microarray data were validated by quantitative polymerase chain reaction (PCR) and found to be consistent with previous literature on gene induction or immune response. Integration of the microarrays with genetic mapping data was achieved with a sample of 15 genes. Twelve of these genes had mapped human orthologues. Seven genes were located on the chicken linkage map as predicted by the human-chicken comparative map, while two other genes defined a new conserved syntenic group. More importantly, one of the genes with differential expression is known to confer genetic resistance to MD while another gene is a prime positional candidate for a QTL.     

Identification of QTL for production traits in chickens

If the poultry industry hopes to continue to flourish, the identification of potential quantitative trait loci (QTL) for production-related traits must be pursued This remains true despite the sequencing of the chicken genome. In view of this need, a scan of the chicken genome using 72 microsatellite markers was carried out on a meat-type x egg-type resource population measured for production and egg quality traits. Using a Bayesian analysis, potential QTL for a number of traits were identified on several chromosomes. Evidence of eight QTL regions associated with a total of eight traits (specific gravity, albumin height, Haugh score, shell shape, total number of eggs, final body weight, gain, and feed efficiency) was found. Two of these regions, one spanning the area of 263/287 cM on GAA01 and the other spanning the area of 23/28 cM on GAA02, were associated with multiple QTL.     

大白×梅山猪资源家系生长性状QTL的检测

以大白猪和梅山猪为父母本建立F2 资源家系 ,在 2 0 0 0年 ,随机选留 6 6头F2 代个体 ,获得出生重、6 0日龄体重、出生至 6 0日龄平均日增重及 6 0日龄至屠宰前平均日增重的表型数据。结合 4 8个微卫星标记构建的猪 1、2、3、4、6和 7号染色体遗传连锁图谱 ,用线性模型最小二乘法对各数量性状进行QTL区间作图 ,利用置换法(permutation)确定显著性阈值。研究发现 ,猪 4号染色体上有一个染色体水平极显著 (P <0 0 1)的QTL影响 6 0日龄至屠宰前平均日增重 ,并达到基因组显著水平 (P <0 0 5 )。在染色体水平 ,出生至 6 0日龄平均日增重QTL位于 2号染色体 ,6 0日龄体重QTL位于 1号染色体。 6号染色体的出生至 6 0日龄平均日增重QTL达到建议显著水平     

Genomic approaches to analyzing natural variation in Arabidopsis thaliana

The genomics tools available for studying Arabidopsis thaliana are a great resource for researchers trying to characterize and understand the genetic basis of natural variation. Abundant polymorphic markers aid quantitative trait locus (QTL) mapping, the fully sequenced genome provides rapid identification of candidate loci, and extensive knockout collections allow those candidate loci to be tested. Combining QTL mapping of classic phenotypic traits with biochemical or expression analysis is providing mechanistic insight into the traits of interest. Conversely, natural variation studies are now being done on genomic traits such as methylation or chiasma frequency.     

Quantitative Trait Loci (QTL) and Mendelian Trait Loci (MTL) Analysis in Prunus: a Breeding Perspective and Beyond

Trait loci analysis, a classic procedure in quantitative (quantitative trait loci, QTL) and qualitative (Mendelian trait loci, MTL) genetics, continues to be the most important approach in studies of gene labeling in Prunus species from the Rosaceae family. Since 2011, the number of published Prunus QTLs and MTLs has doubled. With increased genomic resources, such as whole genome sequences and high-density genotyping platforms, trait loci analysis can be more readily converted to markers that can be directly utilized in marker-assisted breeding. To provide this important resource to the community and to integrate it with other genomic, genetic, and breeding data, a global review of the QTLs and MTLs linked to agronomic traits in Prunus has been performed and the data made available in the Genome Database for Rosaceae. We describe detailed information on 760 main QTLs and MTLs linked to a total of 110 agronomic traits related to tree development, pest and disease resistance, flowering, ripening, and fruit and seed quality. Access to these trait loci enables the application of this information in the post-genomic era, characterized by the availability of a high-quality peach reference genome and new high-throughput DNA and RNA analysis technologies.     

Identification of Quantitative Trait Loci Associated with Resistance to Viral Haemorrhagic Septicaemia (VHS) in Turbot (Scophthalmus maximus): A Comparison Between Bacterium,Parasite and Virus Diseases

One of the main objectives of genetic breeding programs in turbot industry is to reduce disease-related mortality. In the present study, a genome scan to detect quantitative trait loci (QTL) affecting resistance and survival to viral haemorrhagic septicaemia (VHS) was carried out. Three full-sib families with approximately 90 individuals each were genotyped and evaluated by linear regression and maximum likelihood approaches. In addition, a comparison between QTL detected for resistance and survival time to other important bacterial and parasite diseases affecting turbot (furunculosis and scuticociliatosis) was also carried out. Finally, the relationship between QTL affecting resistance/survival time to the virus and growth-related QTL was also evaluated. Several genomic regions controlling resistance and survival time to VHS were detected. Also significant associations between the evaluated traits and genotypes at particular markers were identified, explaining up to 14 % of the phenotypic variance. Several genomic regions controlling general and specific resistance to different diseases in turbot were detected. A preliminary gene mining approach identified candidate genes related to general or specific immunity. This information will be valuable to develop marker-assisted selection programs and to discover candidate genes related to disease resistance to improve turbot production.     

Comparative genetics in sugarcane enables structured map enhancement and validation of marker-trait associations

As sugarcane is a complex polyaneuploid with many chromosomes, large numbers of markers are required to generate genetic maps with reasonable levels of genome coverage. Comparative mapping was investigated as an approach for both quantitative trait loci (QTL) validation and genetic map enhancement in sugarcane. More than 1000 SSR and AFLP markers were scored in a bi-parental Australian sugarcane population (Q3) that was segregating widely for sugar content-related traits. Two maps were constructed, one for each parent. The Q117 (female) and MQ77-340 (male) maps each contained almost 400 markers distributed onto approximately 100 linkage groups (LGs), of which nearly half could be assigned to homology groups (HGs) on the basis of SSRs. Then, using common SSR and AFLP markers, the two Q3 parental maps were aligned with the maps of the French cultivar, R570, and of the Australian cultivar, Q165^A (A denotes variety covered by Australian plant breeding rights). As a result of comparative mapping, all ten HGs in the Q117 map, and all eleven HGs in the MQ77-340 map could be re-assigned to seven of the expected eight sugarcane HGs, revealing that one sugarcane HG was not covered at all in either Q3 parental map, and that other HGs were poorly represented. QTL analysis in the Q3 population identified approximately 75 marker-trait associations (MTAs) from approximately 18 chromosomal regions or putative QTL in each map for three sugar content-related traits. QTL location appeared to be consistent between the 4 maps; two of the eight HGs were observed to contain MTAs for brix in two or three maps, strongly suggesting the location of sugar content-related trait loci in these HGs. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Mapping quantitative trait loci associated with southern leaf blight resistance in maize (Zea mays L.)

Southern leaf blight (SLB) caused by the fungus Cochliobolus heterostrophus (Drechs.) Drechs. is a major foliar disease of maize worldwide. Our objectives were to identify quantitative trait loci (QTL) for resistance to SLB and flowering traits in recombinant inbred line (RIL) population derived from the cross of inbred lines LM5 (resistant) and CM140 (susceptible). A set of 207 RILs were phenotyped for resistance to SLB at three time intervals for two consecutive years. Four putative QTL for SLB resistance were detected on chromosomes 3, 8 and 9 that accounted for 54% of the total phenotypic variation. Days to silking and anthesis–silking interval (ASI) QTL were located on chromosomes 6, 7 and 9. A comparison of the obtained results with the published SLB resistance QTL studies suggested that the detected bins 9.03/02 and 8.03/8.02 are the hot spots for SLB resistance whereas novel QTL were identified in bins 3.08 and 8.01/8.04. The linked markers are being utilized for marker‐assisted mobilization of QTL conferring resistance to SLB in elite maize backgrounds. Fine mapping of identified QTL will facilitate identification of candidate genes underlying SLB resistance.     

A genome‐wide scan for quantitative trait loci affecting respiratory disease and immune capacity in Landrace pigs

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.     

A QTL for osteoporosis detected in an F2 population derived from White Leghorn chicken lines divergently selected for bone index

Osteoporosis, resulting from progressive loss of structural bone during the period of egg-laying in hens, is associated with an increased susceptibility to bone breakage. To study the genetic basis of bone strength, an F(2) cross was produced from lines of hens that had been divergently selected for bone index from a commercial pedigreed White Leghorn population. Quantitative trait loci (QTL) affecting the bone index and component traits of the index (tibiotarsal and humeral strength and keel radiographic density) were mapped using phenotypic data from 372 F(2) individuals in 32 F(1) families. Genotypes for 136 microsatellite markers in 27 linkage groups covering approximately 80% of the genome were analysed for association with phenotypes using within-family regression analyses. There was one significant QTL on chromosome 1 for bone index and the component traits of tibiotarsal and humeral breaking strength. Additive effects for tibiotarsal breaking strength represented 34% of the trait standard deviation and 7.6% of the phenotypic variance of the trait. These QTL for bone quality in poultry are directly relevant to commercial populations.     

Genetic architecture of the dog: sexual size dimorphism and functional morphology

Purebred dogs are a valuable resource for genetic analysis of quantitative traits. Quantitative traits are complex, controlled by many genes that are contained within regions of the genome known as quantitative trait loci (QTL). The genetic architecture of quantitative traits is defined by the characteristics of these genes: their number, the magnitude of their effects, their positions in the genome and their interactions with each other. QTL analysis is a valuable tool for exploring genetic architecture, and highlighting regions of the genome that contribute to the variation of a trait within a population.     

Construction of a linkage map based on a <Emphasis Type="Italic">Lathyrus sativus</Emphasis> backcross population and preliminary investigation of QTLs associated with resistance to ascochyta blight

A linkage map of the Lathyrus sativus genome was constructed using 92 backcross individuals derived from a cross between an accession resistant (ATC 80878) to ascochyta blight caused by Mycosphaerella pinodes and a susceptible accession (ATC 80407). A total of 64 markers were mapped on the backcross population, including 47 RAPD, seven sequence-tagged microsatellite site and 13 STS/CAPS markers. The map comprised nine linkage groups, covered a map distance of 803.1 cM, and the average spacing between markers was 15.8 cM. Quantitative trait loci (QTL) associated with ascochyta blight resistance were detected using single-point analysis and simple and composite interval mapping. The backcross population was evaluated for stem resistance in temperature-controlled growth room trials. One significant QTL, QTL1, was located on linkage group 1 and explained 12% of the phenotypic variation in the backcross population. A second suggestive QTL, QTL2, was detected on linkage group 2 and accounted for 9% of the trait variation. The L. sativus R-QTL regions detected may be targeted for future intergenus transfer of the trait into accessions of the closely related species Pisum sativum.     

QTL affecting stress response to crowding in a rainbow trout broodstock population

Background

Genomic analyses have the potential to impact selective breeding programs by identifying markers that serve as proxies for traits which are expensive or difficult to measure. Also, identifying genes affecting traits of interest enhances our understanding of their underlying biochemical pathways. To this end we conducted genome scans of seven rainbow trout families from a single broodstock population to identify quantitative trait loci (QTL) having an effect on stress response to crowding as measured by plasma cortisol concentration. Our goal was to estimate the number of major genes having large effects on this trait in our broodstock population through the identification of QTL.

Results

A genome scan including 380 microsatellite markers representing 29 chromosomes resulted in the de novo construction of genetic maps which were in good agreement with the NCCCWA genetic map. Unique sets of QTL were detected for two traits which were defined after observing a low correlation between repeated measurements of plasma cortisol concentration in response to stress. A highly significant QTL was detected in three independent analyses on Omy16, many additional suggestive and significant QTL were also identified. With linkage-based methods of QTL analysis such as half-sib regression interval mapping and a variance component method, we determined that the significant and suggestive QTL explain about 40-43% and 13-27% of the phenotypic trait variation, respectively.

Conclusions

The cortisol response to crowding stress is a complex trait controlled in a sub-sample of our broodstock population by multiple QTL on at least 8 chromosomes. These QTL are largely different from others previously identified for a similar trait, documenting that population specific genetic variants independently affect cortisol response in ways that may result in different impacts on growth. Also, mapping QTL for multiple traits associated with stress response detected trait specific QTL which indicate the significance of the first plasma cortisol measurement in defining the trait. Fine mapping these QTL can lead towards the identification of genes affecting stress response and may influence approaches to selection for this economically important stress response trait.

     

The genetic architecture of the behavioral ontogeny of foraging in honeybee workers

The initiation of foraging during the life course of honeybee workers is of central interest to understanding the division of labor in social insects, a central theme in sociobiology and behavioral research. It also provides one of the most complex phenotypic traits in biological systems because of the interaction of various external, social, and individual factors. This study reports on a comprehensive investigation of the genetic architecture of the age of foraging initiation in honeybees. It comprises an estimation of genetic variation, the study of candidate loci, and two complementary quantitative trait loci (QTL) maps using two selected, continually bred lines of honeybees. We conclude that considerable genetic variation exists between the selected lines for this central life history component. The study reveals direct pleiotropic and epistatic effects of candidate loci (including previously identified QTL for foraging behavior). Furthermore, two maps of the honeybee genome were constructed from over 400 AFLP markers. Both maps confirm the extraordinary recombinational size of the honeybee genome. On the basis of these maps, we report four new significant QTL and two more suggestive QTL that influence the initiation of foraging.     

Identification and validation of QTL for Sclerotinia midstalk rot resistance in sunflower by selective genotyping

Midstalk rot, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is an important cause of yield loss in sunflower (Helianthus annuus L.). Objectives of this study were to: (1) estimate the number, genomic positions and genetic effects of quantitative trait loci (QTL) for resistance to midstalk rot in line TUB-5-3234, derived from an interspecific cross; (2) determine congruency of QTL between this line and other sources of resistance; and (3) make inferences about the efficiency of selective genotyping (SG) in detecting QTL conferring midstalk rot resistance in sunflower. Phenotypic data for three resistance (stem lesion, leaf lesion and speed of fungal growth) and two morphological (leaf length and leaf length with petiole) traits were obtained from 434 F₃ families from cross CM625 (susceptible) × TUB-5-3234 (resistant) under artificial infection in field experiments across two environments. The SG was applied by choosing the 60 most resistant and the 60 most susceptible F₃ families for stem lesion. For genotyping of the respective F₂ plants, 78 simple sequence repeat markers were used. Genotypic variances were highly significant for all traits. Heritabilities and genotypic correlations between resistance traits were moderate to high. Three to four putative QTL were detected for each resistance trait explaining between 40.8% and 72.7% of the genotypic variance ( ). Two QTL for stem lesion showed large genetic effects and corroborated earlier findings from the cross NDBLOS_sel (resistant) × CM625 (susceptible). Our results suggest that SG can be efficiently used for QTL detection and the analysis of congruency for resistance genes across populations.     

Constructing high-density genetic maps for polyploid sugarcane (<Emphasis Type="Italic">Saccharum</Emphasis> spp.) and identifying quantitative trait loci controlling brown rust resistance

Sugarcane (Saccharum spp.) is an important economic crop for producing edible sugar and bioethanol. Brown rust has long been a major disease impacting sugarcane production worldwide. Resistance resource and markers linked to resistance are valuable tools for disease resistance improvement. An F₁ segregating population derived from a cross between two hybrid sugarcane clones, brown rust-susceptible CP95-1039 and brown rust-resistant CP88-1762, were genotyped using genotyping by sequencing approach and also phenotyped in a replicated field trial. Single nucleotide polymorphism (SNP) and presence/absence markers were called with seven different pipelines to maximize reliable marker identification. High-density maps were constructed for both parental clones with a total map length of 4224.4 cM, and a marker density of one marker per 1.7 cM for CP95-1039, and a total map length of 4373.2 cM, and one marker per 2.0 cM for CP88-1762. Among the seven SNP callers, Tassel and Genome Analysis ToolKit performed better than other callers in single-dose SNP detection and contribution to genetic maps. Two major quantitative trait loci (QTL) controlling brown rust resistance were identified, which can explain 21 and 30% of the phenotypic variation, respectively. The genetic maps generated here will improve our understanding of sugarcane’s complex genome structure and discovery of underlying sequence variations controlling agronomic traits. The putative QTL controlling brown rust resistance can effectively be utilized in sugarcane breeding programs to expedite the selection process of brown rust resistance after validation.     

Detection of quantitative trait loci for body weights and conformation traits in Beijing ducks

Quantitative trait loci (QTL) for body weights and conformation traits were detected in Beijing ducks. Traits included body weights (BW) at hatching and at 1-7 weeks of age; lengths of the body (BL), keel bone (KBL), shank (SL) and neck (NL) at 7 weeks of age; width of breast (BTW) at 7 weeks; and girths of shank (SG) and breast (BG) at 7 weeks. Using a half-sib analysis with a multiple-QTL model, linkage between the phenotypic traits and 95 microsatellite markers was studied. Six genome-wide suggestive QTL for three body weights and two conformation traits were identified in CAU1, CAU2, CAU6 and CAU12. Chromosome-wide significant QTL influencing one body weight trait and one conformation trait were located in CAU4 and CAU10 respectively. Twelve chromosome-wide suggestive QTL for six body weight traits and four conformation traits were found in seven linkage groups (CAU1, CAU2, CAU3, CAU4, CAU6, CAU10 and CAU12). In addition, the QTL in CAU6 at 21 and 73 cM jointly affected SG and explained 10.6% of the phenotypic variation. This study provides the first evidence for QTL involved in body weights and conformation traits in ducks, and will stimulate further investigations into the genetic architecture of these traits in this species.