1 + 1 = 3: Development and Validation of a SNP-Based Algorithm to Identify Genetic Contributions from Three Distinct Inbred Mouse Strains

State-of-the-art, genome-wide assessment of mouse genetic background uses single nucleotide polymorphism (SNP) PCR. As SNP analysis can use multiplex testing, it is amenable to high-throughput analysis and is the preferred method for shared resource facilities that offer genetic background assessment of mouse genomes. However, a typical individual SNP query yields only two alleles (A vs. B), limiting the application of this methodology to distinguishing contributions from no more than two inbred mouse strains. By contrast, simple sequence length polymorphism (SSLP) analysis yields multiple alleles but is not amenable to high-throughput testing. We sought to devise a SNP-based technique to identify donor strain origins when three distinct mouse strains potentially contribute to the genetic makeup of an individual mouse. A computational approach was used to devise a three-strain analysis (3SA) algorithm that would permit identification of three genetic backgrounds while still using a binary-output SNP platform. A panel of 15 mosaic mice with contributions from BALB/c, C57Bl/6, and DBA/2 genetic backgrounds was bred and analyzed using a genome-wide SNP panel using 1449 markers. The 3SA algorithm was applied and then validated using SSLP. The 3SA algorithm assigned 85% of 1449 SNPs as informative for the C57Bl/6, BALB/c, or DBA/2 backgrounds, respectively. Testing the panel of 15 F2 mice, the 3SA algorithm predicted donor strain origins genome-wide. Donor strain origins predicted by the 3SA algorithm correlated perfectly with results from individual SSLP markers located on five different chromosomes (n=70 tests). We have established and validated an analysis algorithm based on binary SNP data that can successfully identify the donor strain origins of chromosomal regions in mice that are bred from three distinct inbred mouse strains.     

Genetic control of renal tumorigenesis by the mouse Rtm1 locus

Background

The genetic basis of susceptibility to renal tumorigenesis has not yet been established in mouse strains. Mouse lines derived by bidirectional phenotypic selection on the basis of their maximal (AIRmax) or minimal (AIRmin) acute inflammatory responsiveness differ widely in susceptibility to spontaneous and urethane-induced renal tumorigenesis. To map the functional loci modulating renal tumor susceptibility in these mice, we carried out a genome-wide genetic linkage study, using SNP arrays, in an (AIRmax x AIRmin)F2 intercross population treated with a single urethane dose at 1 week of age and phenotyped for renal tumors at 35 weeks of age.

Results

AIRmax mice did not develop renal tumors spontaneously nor in response to urethane, whereas in AIRmin mice renal tumors formed spontaneously (in 52% of animals) and after urethane induction (89%). The tumors had a papillary morphology and were positive for alpha-methylacyl-CoA racemase and negative for CD10. By analysis of 879 informative SNPs in 662 mice, we mapped a single quantitative trait locus modulating the incidence of renal tumors in the (AIRmax x AIRmin)F2 intercross population. This locus, which we named Renal tumor modifier QTL 1 (Rtm1), mapped to chromosome 17 at 23.4 Mb (LOD score = 15.8), with SNPs rs3696835 and rs3719497 flanking the LOD score peak. The A allele of rs3719497 from AIRmin mice was associated with a 2.5-fold increased odds ratio for renal tumor development. The LOD score peak included the Tuberous sclerosis 2 (Tsc2) gene which has already been implicated in kidney disease: loss of function by germline retroviral insertion is associated with spontaneous renal tumorigenesis in the Eker rat, and heterozygous-null Tsc2^(+/-) mice develop renal cystadenomas.

Conclusions

We mapped Rtm1 as a single major locus modulating renal tumorigenesis in a murine intercross population. Thus, the AIR mouse lines can be considered a new genetic model for studying the role of germline and somatic molecular alterations in kidney neoplastic disease.     

Role of Nicotine Dependence on the Relationship between Variants in the Nicotinic Receptor Genes and Risk of Lung Adenocarcinoma

Several variations in the nicotinic receptor genes have been identified to be associated with both lung cancer risk and smoking in the genome-wide association (GWA) studies. However, the relationships among these three factors (genetic variants, nicotine dependence, and lung cancer) remain unclear. In an attempt to elucidate these relationships, we applied mediation analysis to quantify the impact of nicotine dependence on the association between the nicotinic receptor genetic variants and lung adenocarcinoma risk. We evaluated 23 single nucleotide polymorphisms (SNPs) in the five nicotinic receptor related genes (CHRNB3, CHRNA6, and CHRNA5/A3/B4) previously reported to be associated with lung cancer risk and smoking behavior and 14 SNPs in the four ‘control’ genes (TERT, CLPTM1L, CYP1A1, and TP53), which were not reported in the smoking GWA studies. A total of 661 lung adenocarcinoma cases and 1,347 controls with a smoking history, obtained from the Environment and Genetics in Lung Cancer Etiology case-control study, were included in the study. Results show that nicotine dependence is a mediator of the association between lung adenocarcinoma and gene variations in the regions of CHRNA5/A3/B4 and accounts for approximately 15% of this relationship. The top two CHRNA3 SNPs associated with the risk for lung adenocarcinoma were rs1051730 and rs12914385 (p-value = 1.9×10⁻¹⁰ and 1.1×10⁻¹⁰, respectively). Also, these two SNPs had significant indirect effects on lung adenocarcinoma risk through nicotine dependence (p = 0.003 and 0.007). Gene variations rs2736100 and rs2853676 in TERT and rs401681 and rs31489 in CLPTM1L had significant direct associations on lung adenocarcinoma without indirect effects through nicotine dependence. Our findings suggest that nicotine dependence plays an important role between genetic variants in the CHRNA5/A3/B4 region, especially CHRNA3, and lung adenocarcinoma. This may provide valuable information for understanding the pathogenesis of lung adenocarcinoma and for conducting personalized smoking cessation interventions.     

Identification of Pyrus Single Nucleotide Polymorphisms (SNPs) and Evaluation for Genetic Mapping in European Pear and Interspecific Pyrus Hybrids

We have used new generation sequencing (NGS) technologies to identify single nucleotide polymorphism (SNP) markers from three European pear (Pyrus communis L.) cultivars and subsequently developed a subset of 1096 pear SNPs into high throughput markers by combining them with the set of 7692 apple SNPs on the IRSC apple Infinium® II 8K array. We then evaluated this apple and pear Infinium® II 9K SNP array for large-scale genotyping in pear across several species, using both pear and apple SNPs. The segregating populations employed for array validation included a segregating population of European pear (‘Old Home’בLouise Bon Jersey’) and four interspecific breeding families derived from Asian (P. pyrifolia Nakai and P. bretschneideri Rehd.) and European pear pedigrees. In total, we mapped 857 polymorphic pear markers to construct the first SNP-based genetic maps for pear, comprising 78% of the total pear SNPs included in the array. In addition, 1031 SNP markers derived from apple (13% of the total apple SNPs included in the array) were polymorphic and were mapped in one or more of the pear populations. These results are the first to demonstrate SNP transferability across the genera Malus and Pyrus. Our construction of high density SNP-based and gene-based genetic maps in pear represents an important step towards the identification of chromosomal regions associated with a range of horticultural characters, such as pest and disease resistance, orchard yield and fruit quality.     

Genome wide association (GWA) study for early onset extreme obesity supports the role of fat mass and obesity associated gene (FTO) variants

Background

Obesity is a major health problem. Although heritability is substantial, genetic mechanisms predisposing to obesity are not very well understood. We have performed a genome wide association study (GWA) for early onset (extreme) obesity.

Methodology/Principal Findings

a) GWA (Genome-Wide Human SNP Array 5.0 comprising 440,794 single nucleotide polymorphisms) for early onset extreme obesity based on 487 extremely obese young German individuals and 442 healthy lean German controls; b) confirmatory analyses on 644 independent families with at least one obese offspring and both parents. We aimed to identify and subsequently confirm the 15 SNPs (minor allele frequency ≥10%) with the lowest p-values of the GWA by four genetic models: additive, recessive, dominant and allelic. Six single nucleotide polymorphisms (SNPs) in FTO (fat mass and obesity associated gene) within one linkage disequilibrium (LD) block including the GWA SNP rendering the lowest p-value (rs1121980; log-additive model: nominal p = 1.13×10⁻⁷, corrected p = 0.0494; odds ratio (OR)_CT 1.67, 95% confidence interval (CI) 1.22–2.27; OR_TT 2.76, 95% CI 1.88–4.03) belonged to the 15 SNPs showing the strongest evidence for association with obesity. For confirmation we genotyped 11 of these in the 644 independent families (of the six FTO SNPs we chose only two representing the LD bock). For both FTO SNPs the initial association was confirmed (both Bonferroni corrected p<0.01). However, none of the nine non-FTO SNPs revealed significant transmission disequilibrium.

Conclusions/Significance

Our GWA for extreme early onset obesity substantiates that variation in FTO strongly contributes to early onset obesity. This is a further proof of concept for GWA to detect genes relevant for highly complex phenotypes. We concurrently show that nine additional SNPs with initially low p-values in the GWA were not confirmed in our family study, thus suggesting that of the best 15 SNPs in the GWA only the FTO SNPs represent true positive findings.     

Gemcitabine and Arabinosylcytosin Pharmacogenomics: Genome-Wide Association and Drug Response Biomarkers

Cancer patients show large individual variation in their response to chemotherapeutic agents. Gemcitabine (dFdC) and AraC, two cytidine analogues, have shown significant activity against a variety of tumors. We previously used expression data from a lymphoblastoid cell line-based model system to identify genes that might be important for the two drug cytotoxicity. In the present study, we used that same model system to perform a genome-wide association (GWA) study to test the hypothesis that common genetic variation might influence both gene expression and response to the two drugs. Specifically, genome-wide single nucleotide polymorphisms (SNPs) and mRNA expression data were obtained using the Illumina 550K® HumanHap550 SNP Chip and Affymetrix U133 Plus 2.0 GeneChip, respectively, for 174 ethnically-defined “Human Variation Panel” lymphoblastoid cell lines. Gemcitabine and AraC cytotoxicity assays were performed to obtain IC₅₀ values for the cell lines. We then performed GWA studies with SNPs, gene expression and IC₅₀ of these two drugs. This approach identified SNPs that were associated with gemcitabine or AraC IC₅₀ values and with the expression regulation for 29 genes or 30 genes, respectively. One SNP in IQGAP2 (rs3797418) was significantly associated with variation in both the expression of multiple genes and gemcitabine and AraC IC₅₀. A second SNP in TGM3 (rs6082527) was also significantly associated with multiple gene expression and gemcitabine IC50. To confirm the association results, we performed siRNA knock down of selected genes with expression that was associated with rs3797418 and rs6082527 in tumor cell and the knock down altered gemcitabine or AraC sensitivity, confirming our association study results. These results suggest that the application of GWA approaches using cell-based model systems, when combined with complementary functional validation, can provide insights into mechanisms responsible for variation in cytidine analogue response.     

Identification of a Functional Genetic Variant at 16q12.1 for Breast Cancer Risk: Results from the Asia Breast Cancer Consortium

Genetic factors play an important role in the etiology of breast cancer. We carried out a multi-stage genome-wide association (GWA) study in over 28,000 cases and controls recruited from 12 studies conducted in Asian and European American women to identify genetic susceptibility loci for breast cancer. After analyzing 684,457 SNPs in 2,073 cases and 2,084 controls in Chinese women, we evaluated 53 SNPs for fast-track replication in an independent set of 4,425 cases and 1,915 controls of Chinese origin. Four replicated SNPs were further investigated in an independent set of 6,173 cases and 6,340 controls from seven other studies conducted in Asian women. SNP rs4784227 was consistently associated with breast cancer risk across all studies with adjusted odds ratios (95% confidence intervals) of 1.25 (1.20−1.31) per allele (P = 3.2×10⁻²⁵) in the pooled analysis of samples from all Asian samples. This SNP was also associated with breast cancer risk among European Americans (per allele OR  = 1.19, 95% CI  = 1.09−1.31, P = 1.3×10⁻⁴, 2,797 cases and 2,662 controls). SNP rs4784227 is located at 16q12.1, a region identified previously for breast cancer risk among Europeans. The association of this SNP with breast cancer risk remained highly statistically significant in Asians after adjusting for previously-reported SNPs in this region. In vitro experiments using both luciferase reporter and electrophoretic mobility shift assays demonstrated functional significance of this SNP. These results provide strong evidence implicating rs4784227 as a functional causal variant for breast cancer in the locus 16q12.1 and demonstrate the utility of conducting genetic association studies in populations with different genetic architectures.     

Development of a SNP genotyping panel for genetic monitoring of the laboratory mouse

We have developed a genotyping system for detecting genetic contamination in the laboratory mouse based on assaying single-nucleotide polymorphism (SNP) markers positioned on all autosomes and the X chromosome. This system provides a fast, reliable, and cost-effective way for genetic monitoring, while maintaining a very high degree of confidence. We describe the allelic distribution of 235 SNPs in 48 mouse strains, thereby creating a database of polymorphisms useful for genotyping purposes. The SNP markers used in this study were chosen from publicly available SNP databases. Four genotyping methods were evaluated, and dynamic two-tube allele-specific PCR assays were developed for each marker and tested on a set of 48 inbred mouse strains. The minimal number of assays sufficient to distinguish groups consisting of different numbers of mouse strains was estimated, and a panel of 28 SNPs sufficient to distinguish virtually all of the inbred strains tested was selected. Amplifluor SNP detection assays were developed for these markers and tested on an extended list of 96 strains. This panel was used as a genetic quality control approach to monitor the genotypes of nearly 300 inbred, wild-derived, congenic, consomic, and recombinant inbred strains maintained at The Jackson Laboratory. We have concluded that this marker panel is sufficient for genetic contamination monitoring in colonies containing a large number of genetically diverse mouse strains and that reduced versions of the panel could be implemented in facilities housing a lower number of strains.     

Development and Evaluation of a Genome-Wide 6K SNP Array for Diploid Sweet Cherry and Tetraploid Sour Cherry

High-throughput genome scans are important tools for genetic studies and breeding applications. Here, a 6K SNP array for use with the Illumina Infinium® system was developed for diploid sweet cherry (Prunus avium) and allotetraploid sour cherry (P. cerasus). This effort was led by RosBREED, a community initiative to enable marker-assisted breeding for rosaceous crops. Next-generation sequencing in diverse breeding germplasm provided 25 billion basepairs (Gb) of cherry DNA sequence from which were identified genome-wide SNPs for sweet cherry and for the two sour cherry subgenomes derived from sweet cherry (avium subgenome) and P. fruticosa (fruticosa subgenome). Anchoring to the peach genome sequence, recently released by the International Peach Genome Initiative, predicted relative physical locations of the 1.9 million putative SNPs detected, preliminarily filtered to 368,943 SNPs. Further filtering was guided by results of a 144-SNP subset examined with the Illumina GoldenGate® assay on 160 accessions. A 6K Infinium® II array was designed with SNPs evenly spaced genetically across the sweet and sour cherry genomes. SNPs were developed for each sour cherry subgenome by using minor allele frequency in the sour cherry detection panel to enrich for subgenome-specific SNPs followed by targeting to either subgenome according to alleles observed in sweet cherry. The array was evaluated using panels of sweet (n = 269) and sour (n = 330) cherry breeding germplasm. Approximately one third of array SNPs were informative for each crop. A total of 1825 polymorphic SNPs were verified in sweet cherry, 13% of these originally developed for sour cherry. Allele dosage was resolved for 2058 polymorphic SNPs in sour cherry, one third of these being originally developed for sweet cherry. This publicly available genomics resource represents a significant advance in cherry genome-scanning capability that will accelerate marker-locus-trait association discovery, genome structure investigation, and genetic diversity assessment in this diploid-tetraploid crop group.     

Identification of Major QTL for Waterlogging Tolerance Using Genome-Wide Association and Linkage Mapping of Maize Seedlings

To investigate the genetic basis of maize seedling response to waterlogging, we performed a genome-wide association study in 144 maize inbred lines, measuring length, fresh and dry weight of roots and shoots under normal and waterlogged conditions using 45,868 SNPs. This panel was divided into three subgroups based on the population structure results and the LD decay distance was 180 kb. A biparental advanced backcross (AB) population was also used to detect quantitative trait loci (QTL). In a comparison of 16 different models, principal components analysis (PCA/top PC3)?+?K was found to be best for reduction of false-positive associations for further analysis. A whole-genome scan detected four strong peak signals (P <?2.18?×?10^?5) significantly associated with the waterlogging response on chromosomes 5, 6 and 9. SNP4784, SNP200, SNP298, and SNP6314 showed significant association with corresponding traits under waterlogging and explained 14.99–19.36 %, 15.75–17.64 %, 16.08 % and 15.44 % of the phenotypic variation, respectively. The identified SNPs were located in GRMZM2G012046, GRMZM2G009808, GRMZM2G137108 and GRMZM2G369629 (AGPV1). SNP4784 (GRMZM2G012046) was colocalized with the major QTL that was identified with the same traits in the AB population. Forty-seven SNPs significantly associated (P?<?2.18?×?10^?4) with six traits in association mapping were identified and, among these, 33 SNPs were already reported in literature as waterlogging-related traits. These results will help elucidate the genetic basis of differential responses and tolerance to waterlogging stress among maize inbred lines, and provide novel loci for improvement of waterlogging tolerance of maize inbred lines using marker-assisted selection.     

SNP rs10248565 in HDAC9 as a novel genomic aberration biomarker of lung adenocarcinoma in non-smoking women

Background

Numerous efforts have been made to elucidate the etiology and improve the treatment of lung cancer, but the overall five-year survival rate is still only 15%. Although cigarette smoking is the primary risk factor for lung cancer, only 7% of female lung cancer patients in Taiwan have a history of smoking. Since cancer results from progressive accumulation of genetic aberrations, genomic rearrangements may be early events in carcinogenesis.

Results

In order to identify biomarkers of early-stage adenocarcinoma, the genome-wide DNA aberrations of 60 pairs of lung adenocarcinoma and adjacent normal lung tissue in non-smoking women were examined using Affymetrix Genome-Wide Human SNP 6.0 arrays. Common copy number variation (CNV) regions were identified by ≥30% of patients with copy number beyond 2 ± 0.5 of copy numbers for each single nucleotide polymorphism (SNP) and at least 100 continuous SNP variant loci. SNPs associated with lung adenocarcinoma were identified by McNemar’s test. Loss of heterozygosity (LOH) SNPs were identified in ≥18% of patients with LOH in the locus. Aberration of SNP rs10248565 at HDAC9 in chromosome 7p21.1 was identified from concurrent analyses of CNVs, SNPs, and LOH.

Conclusion

The results elucidate the genetic etiology of lung adenocarcinoma by demonstrating that SNP rs10248565 may be a potential biomarker of cancer susceptibility.     

Assignment of a locus for mouse lung tumor susceptibility to proximal Chromosome 19

Previous studies have hypothesized that at least three genetic loci contribute to differences in pulmonary adenoma susceptibility between mouse strains A/J and C57BL/6J. One gene that may confer susceptibility to lung tumorigenesis is the Kras protooncogene. To identify other relevant loci involved in this polygenic trait, we determined tumor multiplicity in 56 randomly chosen N-ethyl-N-nitrosourea-treated (A/J×C57BL/6J) N1×C57BL/6 backcross (AB6N2) progeny and correlated it with genotypes at 77 microsatellite markers spanning the genome. A correlation of lung tumor multiplicity phenotypes with genotypes of microsatellite markers on distal Chromosome (Chr) 6 in the Kras region (Pas1) was confirmed, and a new region on Chr 19 (designated Pas3) was identified that also contributes to susceptibility. Linkage analysis on Chr 19 with 270 AB6N2 mice localized the region flanked by D19Mit42 and D19Mit19 that is most closely associated with lung tumor susceptibility. The Pas3 locus may be an enhancer of the susceptibility locus on Chr 6.     

Development and Validation of a 20K Single Nucleotide Polymorphism (SNP) Whole Genome Genotyping Array for Apple (Malus × domestica Borkh)

High-density SNP arrays for genome-wide assessment of allelic variation have made high resolution genetic characterization of crop germplasm feasible. A medium density array for apple, the IRSC 8K SNP array, has been successfully developed and used for screens of bi-parental populations. However, the number of robust and well-distributed markers contained on this array was not sufficient to perform genome-wide association analyses in wider germplasm sets, or Pedigree-Based Analysis at high precision, because of rapid decay of linkage disequilibrium. We describe the development of an Illumina Infinium array targeting 20K SNPs. The SNPs were predicted from re-sequencing data derived from the genomes of 13 Malus × domestica apple cultivars and one accession belonging to a crab apple species (M. micromalus). A pipeline for SNP selection was devised that avoided the pitfalls associated with the inclusion of paralogous sequence variants, supported the construction of robust multi-allelic SNP haploblocks and selected up to 11 entries within narrow genomic regions of ±5 kb, termed focal points (FPs). Broad genome coverage was attained by placing FPs at 1 cM intervals on a consensus genetic map, complementing them with FPs to enrich the ends of each of the chromosomes, and by bridging physical intervals greater than 400 Kbps. The selection also included ∼3.7K validated SNPs from the IRSC 8K array. The array has already been used in other studies where ∼15.8K SNP markers were mapped with an average of ∼6.8K SNPs per full-sib family. The newly developed array with its high density of polymorphic validated SNPs is expected to be of great utility for Pedigree-Based Analysis and Genomic Selection. It will also be a valuable tool to help dissect the genetic mechanisms controlling important fruit quality traits, and to aid the identification of marker-trait associations suitable for the application of Marker Assisted Selection in apple breeding programs.     

Linkage disequilibrium and genome-wide association analysis for anthocyanin pigmentation and fruit color in eggplant

Background

The genome-wide association (GWA) approach represents an alternative to biparental linkage mapping for determining the genetic basis of trait variation. Both approaches rely on recombination to re-arrange the genome, and seek to establish correlations between phenotype and genotype. The major advantages of GWA lie in being able to sample a much wider range of the phenotypic and genotypic variation present, in being able to exploit multiple rounds of historical recombination in many different lineages and to include multiple accessions of direct relevance to crop improvement.

Results

A 191 accessions eggplant (Solanum melongena L.) association panel, comprising a mixture of breeding lines, old varieties and landrace selections originating from Asia and the Mediterranean Basin, was SNP genotyped and scored for anthocyanin pigmentation and fruit color at two locations over two years. The panel formed two major clusters, reflecting geographical provenance and fruit type. The global level of linkage disequilibrium was 3.4 cM. A mixed linear model appeared to be the most appropriate for GWA. A set of 56 SNP locus/phenotype associations was identified and the genomic regions harboring these loci were distributed over nine of the 12 eggplant chromosomes. The associations were compared with the location of known QTL for the same traits.

Conclusion

The GWA mapping approach was effective in validating a number of established QTL and, thanks to the wide diversity captured by the panel, was able to detect a series of novel marker/trait associations.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-896) contains supplementary material, which is available to authorized users.     

Genotyping pooled DNA using 100K SNP microarrays: a step towards genomewide association scans

The identification of quantitative trait loci (QTLs) of small effect size that underlie complex traits poses a particular challenge for geneticists due to the large sample sizes and large numbers of genetic markers required for genomewide association scans. An efficient solution for screening purposes is to combine single nucleotide polymorphism (SNP) microarrays and DNA pooling (SNP-MaP), an approach that has been shown to be valid, reliable and accurate in deriving relative allele frequency estimates from pooled DNA for groups such as cases and controls for 10K SNP microarrays. However, in order to conduct a genomewide association study many more SNP markers are needed. To this end, we assessed the validity and reliability of the SNP-MaP method using Affymetrix GeneChip^® Mapping 100K Array set. Interpretable results emerged for 95% of the SNPs (nearly 110000 SNPs). We found that SNP-MaP allele frequency estimates correlated 0.939 with allele frequencies for 97605 SNPs that were genotyped individually in an independent population; the correlation was 0.971 for 26 SNPs that were genotyped individually for the 1028 individuals used to construct the DNA pools. We conclude that extending the SNP-MaP method to the Affymetrix GeneChip^® Mapping 100K Array set provides a useful screen of >100000 SNP markers for QTL association scans.     

SNP genotyping for the genetic monitoring of laboratory mice by using a microarray-based method with dualcolour fluorescence hybridisation

Ensuring the genetic homogeneity of the mice used in laboratory experiments contributes to the Reduction aspect of the Three Rs, by maximising the quality of the data obtained from any animals that are used for these purposes, and ultimately reducing the numbers of animals used. Single nucleotide polymorphism (SNP) genotyping is especially suitable for use in the analysis of the genetic purity of model organisms such as the mouse, because bi-allelic markers remain fully informative when used to characterise crosses between inbred strains. Here, we attempted to apply a microarray-based method for a SNP marker to monitor the genetic quality of inbred mouse strains, so as to validate the reliability, stability and applicability of this SNP genotyping panel. The amplified PCR products containing four different SNP loci from four inbred mouse strains were spotted and immobilised onto amino-modified glass slides to generate a microarray. This was then interrogated through hybridisation with dual-colour probes, to determine the SNP genotypes of each sample. The results indicated that this microarray-based method could effectively determine the genotypes of the four selected SNPs with a high degree of accuracy. We have developed a new SNP genotyping technique for effective use in the genetic monitoring of inbred mouse strains.     

The Identification of Two Head Smut Resistance-Related QTL in Maize by the Joint Approach of Linkage Mapping and Association Analysis

Head smut, caused by the fungus Sphacelotheca reiliana (Kühn) Clint, is a devastating threat to maize production. In this study, QTL mapping of head smut resistance was performed using a recombinant inbred line (RIL) population from a cross between a resistant line “QI319” and a susceptible line “Huangzaosi” (HZS) with a genetic map constructed from genotyping-by-sequencing (GBS) data and composed of 1638 bin markers. Two head smut resistance QTL were identified, located on Chromosome 2 (q2.09HR) and Chromosome 5 (q5.03HR), q2.09HR is co-localized with a previously reported QTL for head smut resistance, and the effect of q5.03HR has been validated in backcross populations. It was also observed that pyramiding the resistant alleles of both QTL enhanced the level of resistance to head smut. A genome-wide association study (GWAS) using 277 diverse inbred lines was processed to validate the mapped QTL and to identify additional head smut resistance associations. A total of 58 associated SNPs were detected, which were distributed in 31 independent regions. SNPs with significant association to head smut resistance were detected within the q2.09HR and q5.03HR regions, confirming the linkage mapping results. It was also observed that both additive and epistastic effects determine the genetic architecture of head smut resistance in maize. As shown in this study, the combined strategy of linkage mapping and association analysis is a powerful approach in QTL dissection for disease resistance in maize.     

Linkage disequilibrium in crossbred and pure line chickens

Background

Both genome-wide association (GWA) studies and genomic selection depend on the level of non-random association of alleles at different loci, i.e. linkage disequilibrium (LD), across the genome. Therefore, characterizing LD is of fundamental importance to implement both approaches. In this study, using a 60K single nucleotide polymorphism (SNP) panel, we estimated LD and haplotype structure in crossbred broiler chickens and their component pure lines (one male and two female lines) and calculated the consistency of LD between these populations.

Results

The average level of LD (measured by r²) between adjacent SNPs across the chicken autosomes studied here ranged from 0.34 to 0.40 in the pure lines but was only 0.24 in the crossbred populations, with 28.4% of adjacent SNP pairs having an r² higher than 0.3. Compared with the pure lines, the crossbred populations consistently showed a lower level of LD, smaller haploblock sizes and lower haplotype homozygosity on macro-, intermediate and micro-chromosomes. Furthermore, correlations of LD between markers at short distances (0 to 10 kb) were high between crossbred and pure lines (0.83 to 0.94).

Conclusions

Our results suggest that using crossbred populations instead of pure lines can be advantageous for high-resolution QTL (quantitative trait loci) mapping in GWA studies and to achieve good persistence of accuracy of genomic breeding values over generations in genomic selection. These results also provide useful information for the design and implementation of GWA studies and genomic selection using crossbred populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0098-4) contains supplementary material, which is available to authorized users.