Unlinked Single Nucleotide Polymorphisms Research Articles

Population genomic analysis reveals geographic structure and climatic diversification for Macrophomina phaseolina isolated from soybean and dry bean across the United States, Puerto Rico, and Colombia.

Macrophomina phaseolina causes charcoal rot, which can significantly reduce yield and seed quality of soybean and dry bean resulting from primarily environmental stressors. Although charcoal rot has been recognized as a warm climate-driven disease of increasing concern under global climate change, knowledge regarding population genetics and climatic variables contributing to the genetic diversity of M. phaseolina is limited. This study conducted genome sequencing for 95M. phaseolina isolates from soybean and dry bean across the continental United States, Puerto Rico, and Colombia. Inference on the population structure using 76,981 single nucleotide polymorphisms (SNPs) revealed that the isolates exhibited a discrete genetic clustering at the continental level and a continuous genetic differentiation regionally. A majority of isolates from the United States (96%) grouped in a clade with a predominantly clonal genetic structure, while 88% of Puerto Rican and Colombian isolates from dry bean were assigned to a separate clade with higher genetic diversity. A redundancy analysis (RDA) was used to estimate the contributions of climate and spatial structure to genomic variation (11,421 unlinked SNPs). Climate significantly contributed to genomic variation at a continental level with temperature seasonality explaining the most variation while precipitation of warmest quarter explaining the most when spatial structure was accounted for. The loci significantly associated with multivariate climate were found closely to the genes related to fungal stress responses, including transmembrane transport, glycoside hydrolase activity and a heat-shock protein, which may mediate climatic adaptation for M. phaseolina. On the contrary, limited genome-wide differentiation among populations by hosts was observed. These findings highlight the importance of population genetics and identify candidate genes of M. phaseolina that can be used to elucidate the molecular mechanisms that underly climatic adaptation to the changing climate.

Reproductive isolation between diploid and tetraploid individuals in mixed‐cytotype populations of Lycium australe

Whole-genome duplication is considered a major mechanism of sympatric speciation due to the creation of strong and instantaneous reproductive barriers. Although postzygotic reproductive isolation between diploids and polyploids is often expected, the extent of reproductive incompatibility must be empirically determined and compared to patterns of genetic isolation to fully characterize the reproductive dynamics between cytotypes. We investigated reproductive compatibility between diploid and tetraploid Lycium australe in two mixed-cytotype populations using (1) controlled crossing experiments to evaluate fruit and seed production and (2) germination trials to test seed viability following homoploid and heteroploid crosses. We contrast these experiments with a single-nucleotide polymorphism (SNP) data set to measure genetic isolation between cytotypes and explore whether cytotype or population origin better explains patterns of genetic variation. Finally, we explore mating patterns using the observed germination rates of naturally produced seeds in each population. Although homoploid and heteroploid crosses resulted in similar fruit and seed production, reproductive isolation between co-occurring diploids and tetraploids was nearly complete, due to low seed viability following heteroploid crosses. Of 191,182 total SNPs, 21,679 were present in ≥90% of individuals and replicate runs using unlinked SNPs revealed strong clustering by cytotype and differentiation of tetraploids based on population origin. As often reported, diploid and tetraploid L. australe experience strong postzygotic isolation via hybrid seed inviability. Consistent with this result, cytotype explained a greater amount of variation in the SNP data set than population origin, despite some evidence of historical introgression.

A genome-wide association study to investigate genetic loci associated with primary glaucoma in American Cocker Spaniels.

To identify genetic associations with primary glaucoma (PG) in American Cocker Spaniels using a genome-wide association study (GWAS). A nationwide ambidirectional case-control cohort study was performed in American Cocker Spaniels that had an ophthalmic examination performed by a veterinarian. Ninety-four dogs with PG (cases) and 111 dogs without glaucoma (controls) met phenotypic criteria and had a blood sample collected after receiving informed owner consent. Genomic DNA was extracted from whole blood samples and genotyped (CanineHD BeadChip, Illumina Inc). A case-control GWAS using a linear mixed model was performed, and 3 significance thresholds were calculated (1) using a Bonferroni correction on all single nucleotide polymorphisms (SNPs) included in the GWAS, (2) using a Bonferroni correction on only the unlinked SNPs from a pruned data set, and (3) using 10,000 random phenotype permutations. Following genotype data quality control, 89 cases and 93 controls were included in the GWAS. We identified an association on canine chromosome (CFA10); however, it did not reach statistical significance. Potential candidate genes within the surrounding linkage disequilibrium interval include coiled-coil domain containing 85A (CCDC85A) and extracellular growth factor containing fibulin extracellular matrix protein 1 (EFEMP1). Primary glaucoma in the American Cocker Spaniel is a complex heterogeneous disease that may be influenced by a locus on CFA10. The candidate genes CCDC85A and EFEMP1 within the identified linkage disequilibrium interval have been shown to be involved in human open-angle glaucoma.

Detection of rare nematode resistance Rhg1 haplotypes in Glycine soja and a novel Rhg1 α-SNAP.

This study pursued the hypothesis that wild plant germplasm accessions carrying alleles of interest can be identified using available single nucleotide polymorphism (SNP) genotypes for particular alleles of other (unlinked) genes that contribute to the trait of interest. The soybean cyst nematode (SCN, Heterodera glycines [HG]) resistance locus Rhg1 is widely used in farmed soybean [Glycine max (L.) Merr.]. The two known resistance-conferring haplotypes, rhg1-a and rhg1-b, typically contain three or seven to 10 tandemly duplicated Rhg1 segments, respectively. Each Rhg1 repeat carries four genes, including Glyma.18G022500, which encodes unusual isoforms of the vesicle-trafficking chaperone α-SNAP. Using SoySNP50K data for NSFRAN07 allele presence, we discovered a new Rhg1 haplotype, rhg1-ds, in six accessions of wild soybean, Glycine soja Siebold & Zucc. (0.5% of the ∼1,100 G. soja accessions in the USDA collection). The α-SNAP encoded by rhg1-ds is unique at an important site of amino acid variation and shares with the rhg1-a and rhg1-b α-SNAP proteins the traits of cytotoxicity and altered N-ethylmaleimide sensitive factor (NSF) protein interaction. Copy number assays indicate three repeats of rhg1-ds. G. soja PI 507613 and PI 507623 exhibit resistance to HG type 2.5.7 SCN populations, in part because of contributions from other loci. In a segregating F2 population, rhg1-b and rhg1-ds made statistically indistinguishable contributions to resistance to a partially virulent HG type 2.5.7 SCN population. Hence, the unusual multigene copy number variation Rhg1 haplotype was present but rare in ancestral G. soja and was present in accessions that offer multiple traits for SCN resistance breeding. The accessions were initially identified for study based on an unlinked SNP.

Genomic signatures of natural selection at phenology-related genes in a widely distributed tree species Fagus sylvatica L

BackgroundDiversity among phenology-related genes is predicted to be a contributing factor in local adaptations seen in widely distributed plant species that grow in climatically variable geographic areas, such as forest trees. European beech (Fagus sylvatica L.) is widespread, and is one of the most important broadleaved tree species in Europe; however, its potential for adaptation to climate change is a matter of uncertainty, and little is known about the molecular basis of climate change-relevant traits like bud burst.ResultsWe explored single nucleotide polymorphisms (SNP) at candidate genes related to bud burst in beech individuals sampled across 47 populations from Europe. SNP diversity was monitored for 380 candidate genes using a sequence capture approach, providing 2909 unlinked SNP loci. We used two complementary analytical methods to find loci significantly associated with geographic variables, climatic variables (expressed as principal components), or phenotypic variables (spring and autumn phenology, height, survival). Redundancy analysis (RDA) was used to detect candidate markers across two spatial scales (entire study area and within subregions). We revealed 201 candidate SNPs at the broadest scale, 53.2% of which were associated with phenotypic variables. Additive polygenic scores, which provide a measure of the cumulative signal across significant candidate SNPs, were correlated with a climate variable (first principal component, PC1) related to temperature and precipitation availability, and spring phenology. However, different genotype-environment associations were identified within Southeastern Europe as compared to the entire geographic range of European beech.ConclusionsEnvironmental conditions play important roles as drivers of genetic diversity of phenology-related genes that could influence local adaptation in European beech. Selection in beech favors genotypes with earlier bud burst under warmer and wetter habitats within its range; however, selection pressures may differ across spatial scales.

By Animal, Water, or Wind: Can Dispersal Mode Predict Genetic Connectivity in Riverine Plant Species?

Seed dispersal is crucial to gene flow among plant populations. Although the effects of geographic distance and barriers to gene flow are well studied in many systems, it is unclear how seed dispersal mediates gene flow in conjunction with interacting effects of geographic distance and barriers. To test whether distinct seed dispersal modes (i.e., hydrochory, anemochory, and zoochory) have a consistent effect on the level of genetic connectivity (i.e., gene flow) among populations of riverine plant species, we used unlinked single-nucleotide polymorphisms (SNPs) for eight co-distributed plant species sampled across the Rio Branco, a putative biogeographic barrier in the Amazon basin. We found that animal-dispersed plant species exhibited higher levels of genetic diversity and lack of inbreeding as a result of the stronger genetic connectivity than plant species whose seeds are dispersed by water or wind. Interestingly, our results also indicated that the Rio Branco facilitates gene dispersal for all plant species analyzed, irrespective of their mode of dispersal. Even at a small spatial scale, our findings suggest that ecology rather than geography play a key role in shaping the evolutionary history of plants in the Amazon basin. These results may help improve conservation and management policies in Amazonian riparian forests, where degradation and deforestation rates are high.

Case-only analysis of gene–gene interactions in inflammatory bowel disease

Background Gene–gene interactions (G × G) potentially play a role in the etiology of complex human diseases, including inflammatory bowel disease (IBD), and may partially explain their ‘missing heritability’. Methods Using the largest genotype dataset available for IBD (16,636 Crohn’s disease (CD) and 12,888 ulcerative colitis (UC) cases) we analyzed G × G with the powerful case-only (CO) design. We studied 169 single nucleotide polymorphisms (SNPs) for CD (156 for UC), previously shown to be associated with the respective diseases. To ensure the validity of the CO design, we confined our analysis to pairs of unlinked SNPs. We used principal component analysis at the center level to adjust for possible causes of genotypic association other than G × G, such as population stratification and genotyping batch effects. Results from center-wise logistic regression analyses were combined by a random effects meta-analysis. Results A number of nominally significant (p < .05) G × G interactions were observed, but none of these withstood the Bonferroni multiple testing correction. However, one SNP pair, comprising rs26528 in the IL27 gene and rs9297145 in the KPNA7 gene region was characterized by an interaction odds ratio of 1.18 (95% CI: 1.10–1.27) for CD and a p-value of 7.75 × 10−6. Owing to the concurrent role of the IL27 and KPNA7 genes in NF-κB signaling, a master regulator of pro- and anti-inflammatory processes in IBD, the observed interaction also has biological plausibility. Conclusions We were able to exemplify the utility of the CO design for analyzing G × G, but had to recognize that such interactions are probably scarce for IBD.

Full Bayesian Comparative Phylogeography from Genomic Data.

A challenge to understanding biological diversification is accounting for community-scale processes that cause multiple, co-distributed lineages to co-speciate. Such processes predict non-independent, temporally clustered divergences across taxa. Approximate-likelihood Bayesian computation (ABC) approaches to inferring such patterns from comparative genetic data are very sensitive to prior assumptions and often biased toward estimating shared divergences. We introduce a full-likelihood Bayesian approach, ecoevolity, which takes full advantage of information in genomic data. By analytically integrating over gene trees, we are able to directly calculate the likelihood of the population history from genomic data, and efficiently sample the model-averaged posterior via Markov chain Monte Carlo algorithms. Using simulations, we find that the new method is much more accurate and precise at estimating the number and timing of divergence events across pairs of populations than existing approximate-likelihood methods. Our full Bayesian approach also requires several orders of magnitude less computational time than existing ABC approaches. We find that despite assuming unlinked characters (e.g., unlinked single-nucleotide polymorphisms), the new method performs better if this assumption is violated in order to retain the constant characters of whole linked loci. In fact, retaining constant characters allows the new method to robustly estimate the correct number of divergence events with high posterior probability in the face of character-acquisition biases, which commonly plague loci assembled from reduced-representation genomic libraries. We apply our method to genomic data from four pairs of insular populations of Gekko lizards from the Philippines that are not expected to have co-diverged. Despite all four pairs diverging very recently, our method strongly supports that they diverged independently, and these results are robust to very disparate prior assumptions.

High cryptic species diversity is revealed by genome-wide polymorphisms in a wild relative of banana, Musa itinerans, and implications for its conservation in subtropical China

BackgroundSpecies delimitation is a challenging but essential task in conservation biology. Morphologically similar species are sometimes difficult to recognize even after examination by experienced taxonomists. With the advent of molecular approaches in species delimitation, this hidden diversity has received much recent attention. In addition to DNA barcoding approaches, analytical tools based on the multi-species coalescence model (MSC) have been developed for species delimitation. Musa itinerans is widely distributed in subtropical Asia, and at least six varieties have been documented. However, the number of evolutionarily distinct lineages remains unknown.ResultsUsing genome resequencing data of five populations (making up four varieties), we examined genome-wide variation and found four varieties that were evolutionary significant units. A Bayesian Phylogenetics and Phylogeography (BP&P) analysis using 123 single copy nuclear genes support three speciation events of M. itinerans varieties with robust posterior speciation probabilities; However, a Bayes factor delimitation of species with genomic data (BFD*) analysis using 1201 unlinked single nucleotide polymorphisms gave decisive support for a five-lineage model. When reconciling divergence time estimates with a speciation time scale, a modified three-lineage model was consistent with that of BP&P, in which the speciation time of two varieties (M. itinerans var. itinerans and M. itinerans var. lechangensis) were dated to 26.2 kya and 10.7 kya, respectively. In contrast, other two varieties (M. itinerans var. chinensis and M. itinerans var. guangdongensis) diverged only 3.8 kya in the Anthropocene; this may be a consequence of genetic drift rather than a speciation event.ConclusionOur results showed that the M. itinerans species complex harbours high cryptic species diversity. We recommend that M. itinerans var. itinerans and M. itinerans var. lechangensis be elevated to subspecies status, and the extremely rare latter subspecies be given priority for conservation. We also recommend that the very recently diverged M. itinerans var. chinensis and M. itinerans var. guangdongensis should be merged under the subspecies M. itinerans var. chinensis. Finally, we speculate that species delimitation of recently diverged lineages may be more effective using genome-wide bi-allelic SNP markers with BFD* than by using unlinked loci and BP&P.

Genome sequencing and conservation genomics in the Scandinavian wolverine population.

Genetic approaches have proved valuable to the study and conservation of endangered populations, especially for monitoring programs, and there is potential for further developments in this direction by extending analyses to the genomic level. We assembled the genome of the wolverine (Gulo gulo), a mustelid that in Scandinavia has recently recovered from a significant population decline, and obtained a 2.42Gb draft sequence representing >85% of the genome and including >21,000protein-coding genes. We then performed whole-genome resequencing of 10Scandinavian wolverines for population genomic and demographic analyses. Genetic diversity was among the lowest detected in a red-listed population (mean genome-wide nucleotide diversity of 0.05%). Results of the demographic analyses indicated a long-term decline of the effective population size (Ne ) from 10,000well before the last glaciation to <500 after this period. Current Ne appeared even lower. The genome-wide FIS level was 0.089 (possibly signaling inbreeding), but this effect was not observed when analyzing a set of highly variable SNP markers, illustrating that such markers can give a biased picture of the overall character of genetic diversity. We found significant population structure, which has implications for population connectivity and conservation. We used an integrated microfluidic circuit chip technology to develop an SNP-array consisting of 96 highly informative markers that, together with a multiplex pre-amplification step, was successfully applied to low-quality DNA from scat samples. Our findings will inform management, conservation, and genetic monitoring of wolverines and serve as a genomic roadmap that can be applied to other endangered species. The approach used here can be generally utilized in other systems, but we acknowledge the trade-off between investing in genomic resources and direct conservation actions.

Structured mating: Patterns and implications.

Genetic similarity of spouses can reflect factors influencing mate choice, such as physical/behavioral characteristics, and patterns of social endogamy. Spouse correlations for both genetic ancestry and measured traits may impact genotype distributions (Hardy Weinberg and linkage equilibrium), and therefore genetic association studies. Here we evaluate white spouse-pairs from the Framingham Heart Study (FHS) original and offspring cohorts (N = 124 and 755, respectively) to explore spousal genetic similarity and its consequences. Two principal components (PCs) of the genome-wide association (GWA) data were identified, with the first (PC1) delineating clines of Northern/Western to Southern European ancestry and the second (PC2) delineating clines of Ashkenazi Jewish ancestry. In the original (older) cohort, there was a striking positive correlation between the spouses in PC1 (r = 0.73, P = 3x10-22) and also for PC2 (r = 0.80, P = 7x10-29). In the offspring cohort, the spouse correlations were lower but still highly significant for PC1 (r = 0.38, P = 7x10-28) and for PC2 (r = 0.45, P = 2x10-39). We observed significant Hardy-Weinberg disequilibrium for single nucleotide polymorphisms (SNPs) loading heavily on PC1 and PC2 across 3 generations, and also significant linkage disequilibrium between unlinked SNPs; both decreased with time, consistent with reduced ancestral endogamy over generations and congruent with theoretical calculations. Ignoring ancestry, estimates of spouse kinship have a mean significantly greater than 0, and more so in the earlier generations. Adjusting kinship estimates for genetic ancestry through the use of PCs led to a mean spouse kinship not different from 0, demonstrating that spouse genetic similarity could be fully attributed to ancestral assortative mating. These findings also have significance for studies of heritability that are based on distantly related individuals (kinship less than 0.05), as we also demonstrate the poor correlation of kinship estimates in that range when ancestry is or is not taken into account.

Exome genotyping, linkage disequilibrium and population structure in loblolly pine (Pinus taeda L.).

BackgroundLoblolly pine (Pinus taeda L.) is one of the most widely planted and commercially important forest tree species in the USA and worldwide, and is an object of intense genomic research. However, whole genome resequencing in loblolly pine is hampered by its large size and complexity and a lack of a good reference. As a valid and more feasible alternative, entire exome sequencing was hence employed to identify the gene-associated single nucleotide polymorphisms (SNPs) and to genotype the sampled trees.ResultsThe exons were captured in the ADEPT2 association mapping population of 375 clonally-propagated loblolly pine trees using NimbleGen oligonucleotide hybridization probes, and then exome-enriched genomic DNA fragments were sequenced using the Illumina HiSeq 2500 platform. Oligonucleotide probes were designed based on 199,723 exons (≈49 Mbp) partitioned from the loblolly pine reference genome (PineRefSeq v. 1.01). The probes covered 90.2 % of the target regions. Capture efficiency was high; on average, 67 % of the sequence reads generated for each tree could be mapped to the capture target regions, and more than 70 % of the captured target bases had at least 10X sequencing depth per tree. A total of 972,720 high quality SNPs were identified after filtering. Among them, 53 % were located in coding regions (CDS), 5 % in 5’ or 3’ untranslated regions (UTRs) and 42 % in non-target and non-coding regions, such as introns and adjacent intergenic regions collaterally captured. We found that linkage disequilibrium (LD) decayed very rapidly, with the correlation coefficient (r2) between pairs of SNPs linked within single scaffolds decaying to half maximum (r2 = 0.22) within 55 bp, to r2 = 0.1 within 192 bp, and to r2 = 0.05 within 451 bp. Population structure analysis using unlinked SNPs demonstrated the presence of two main distinct clusters representing western and eastern parts of the loblolly pine range included in our sample of trees.ConclusionsThe obtained results demonstrated the efficiency of exome capture for genotyping species such as loblolly pine with a large and complex genome. The highly diverse genetic variation reported in this study will be a valuable resource for future genetic and genomic research in loblolly pine.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3081-8) contains supplementary material, which is available to authorized users.

Species limits, interspecific hybridization and phylogeny in the cryptic land snail complex Pyramidula: The power of RADseq data

Restriction site-associated DNA sequencing (RADseq) was used to jointly assess phylogenetic relationships, interspecific hybridization and species delimitation in the cryptic, non-model land snail complex Pyramidula. A robust phylogeny was inferred using a matrix of concatenated sequences of almost 1,500,000bp long, containing >97,000 polymorphic sites. Maximum likelihood analyses fully resolved the phylogenetic relationships among species and drastically improved phylogenetic trees obtained from mtDNA and nDNA gene trees (COI, 16S rRNA, 5.8S rRNA, ITS2 and 28S rRNA sequence data). The best species delimitation scenario was selected on the basis of 875 unlinked single nucleotide polymorphisms, showing that nine Pyramidula species should be distinguished in Europe. Applying D-statistics provided no or weak evidence of interspecific hybridization among Pyramidula, except for some evidence of gene flow between two species.

Joint effect of unlinked genotypes: application to type 2 diabetes in the EPIC-Potsdam case-cohort study.

Analyzing multiple single nucleotide polymorphisms (SNPs) is a promising approach to finding genetic effects beyond single-locus associations. We proposed the use of multilocus stepwise regression (MSR) to screen for allele combinations as a method to model joint effects, and compared the results with the often used genetic risk score (GRS), conventional stepwise selection, and the shrinkage method LASSO. In contrast to MSR, the GRS, conventional stepwise selection, and LASSO model each genotype by the risk allele doses. We reanalyzed 20 unlinked SNPs related to type 2 diabetes (T2D) in the EPIC-Potsdam case-cohort study (760 cases, 2193 noncases). No SNP-SNP interactions and no nonlinear effects were found. Two SNP combinations selected by MSR (Nagelkerke's R² = 0.050 and 0.048) included eight SNPs with mean allele combination frequency of 2%. GRS and stepwise selection selected nearly the same SNP combinations consisting of 12 and 13 SNPs (Nagelkerke's R² ranged from 0.020 to 0.029). LASSO showed similar results. The MSR method showed the best model fit measured by Nagelkerke's R² suggesting that further improvement may render this method a useful tool in genetic research. However, our comparison suggests that the GRS is a simple way to model genetic effects since it does not consider linkage, SNP-SNP interactions, and no non-linear effects.

Analysis of genetic diversity and population structure of rice germplasm from north-eastern region of India and development of a core germplasm set.

The North-Eastern region (NER) of India, comprising of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland and Tripura, is a hot spot for genetic diversity and the most probable origin of rice. North-east rice collections are known to possess various agronomically important traits like biotic and abiotic stress tolerance, unique grain and cooking quality. The genetic diversity and associated population structure of 6,984 rice accessions, originating from NER, were assessed using 36 genome wide unlinked single nucleotide polymorphism (SNP) markers distributed across the 12 rice chromosomes. All of the 36 SNP loci were polymorphic and bi-allelic, contained five types of base substitutions and together produced nine types of alleles. The polymorphic information content (PIC) ranged from 0.004 for Tripura to 0.375 for Manipur and major allele frequency ranged from 0.50 for Assam to 0.99 for Tripura. Heterozygosity ranged from 0.002 in Nagaland to 0.42 in Mizoram and gene diversity ranged from 0.006 in Arunachal Pradesh to 0.50 in Manipur. The genetic relatedness among the rice accessions was evaluated using an unrooted phylogenetic tree analysis, which grouped all accessions into three major clusters. For determining population structure, populations K = 1 to K = 20 were tested and population K = 3 was present in all the states, with the exception of Meghalaya and Manipur where, K = 5 and K = 4 populations were present, respectively. Principal Coordinate Analysis (PCoA) showed that accessions were distributed according to their population structure. AMOVA analysis showed that, maximum diversity was partitioned at the individual accession level (73% for Nagaland, 58% for Arunachal Pradesh and 57% for Tripura). Using POWERCORE software, a core set of 701 accessions was obtained, which accounted for approximately 10% of the total NE India collections, representing 99.9% of the allelic diversity. The rice core set developed will be a valuable resource for future genomic studies and crop improvement strategies.

Analysis of sequence variability in the pig CART gene and association of polymorphism with fatness traits in a F2 population.

CART (cocaine- and amphetamine-regulated transcript) peptides are neuromodulators that are involved in appetite control and energy homeostasis. It can inhibit food intake and reduce body weight that have received much attention, but a direct and comprehensive relationship with pigs differing in fatness which could be applied to breeding well has not been established. This study aims to search for polymorphism within the porcine CART gene and evaluate the effect of specific genotypes with regards to an association with fatness traits in a F2 population consisting of 230 individuals. Screening of 2264 bp DNA fragment covering the entire CART gene revealed 29 mutations and four indels (insertion or a deletion), in which four unlinked SNPs (single-nucleotide polymorphisms) could be digested by enzymes and subsequently genotyped in two purebreds and a F2 population. Landrace (lean-type), one of purebreds, presented significantly higher CART expression level than Lantang (obese-type) in most tissues studied. Association analysis revealed that three SNPs (T415C, C640T and C847T) displayed significantly association (p < 0.05) with fatness traits. Additionally, they are in almost complete linkage disequilibrium. Western blotting experiments on these three SNPs loci revealed difference in CART expression among individuals with different genotypes, and the individuals with lower average live backfat thickness (BFAW) expressed CART protein at a bit higher level than others. Our study screened and mapped the genetic variations in the porcine CART gene, and confirmed three functional SNPs which are promising molecular markers for pig production traits.

Evaluation of 41 candidate gene variants for obesity in the EPIC-Potsdam cohort by multi-locus stepwise regression.

ObjectiveObesity has become a leading preventable cause of morbidity and mortality in many parts of the world. It is thought to originate from multiple genetic and environmental determinants. The aim of the current study was to introduce haplotype-based multi-locus stepwise regression (MSR) as a method to investigate combinations of unlinked single nucleotide polymorphisms (SNPs) for obesity phenotypes.MethodsIn 2,122 healthy randomly selected men and women of the EPIC-Potsdam cohort, the association between 41 SNPs from 18 obesity-candidate genes and either body mass index (BMI, mean = 25.9 kg/m2, SD = 4.1) or waist circumference (WC, mean = 85.2 cm, SD = 12.6) was assessed. Single SNP analyses were done by using linear regression adjusted for age, sex, and other covariates. Subsequently, MSR was applied to search for the ‘best’ SNP combinations. Combinations were selected according to specific AICc and p-value criteria. Model uncertainty was accounted for by a permutation test.ResultsThe strongest single SNP effects on BMI were found for TBC1D1 rs637797 (β = −0.33, SE = 0.13), FTO rs9939609 (β = 0.28, SE = 0.13), MC4R rs17700144 (β = 0.41, SE = 0.15), and MC4R rs10871777 (β = 0.34, SE = 0.14). All these SNPs showed similar effects on waist circumference. The two ‘best’ six-SNP combinations for BMI (global p-value = 3.45⋅10–6 and 6.82⋅10–6) showed effects ranging from −1.70 (SE = 0.34) to 0.74 kg/m2 (SE = 0.21) per allele combination. We selected two six-SNP combinations on waist circumference (global p-value = 7.80⋅10–6 and 9.76⋅10–6) with an allele combination effect of −2.96 cm (SE = 0.76) at maximum. Additional adjustment for BMI revealed 15 three-SNP combinations (global p-values ranged from 3.09⋅10–4 to 1.02⋅10–2). However, after carrying out the permutation test all SNP combinations lost significance indicating that the statistical associations might have occurred by chance.ConclusionMSR provides a tool to search for risk-related SNP combinations of common traits or diseases. However, the search process does not always find meaningful SNP combinations in a dataset.

Improved estimation of inbreeding and kinship in pigs using optimized SNP panels

BackgroundTraditional breeding programs consider an average pairwise kinship between sibs. Based on pedigree information, the relationship matrix is used for genetic evaluations disregarding variation due to Mendelian sampling. Therefore, inbreeding and kinship coefficients are either over or underestimated resulting in reduction of accuracy of genetic evaluations and genetic progress. Single nucleotide polymorphism (SNPs) can be used to estimate pairwise kinship and individual inbreeding more accurately. The aim of this study was to optimize the selection of markers and determine the required number of SNPs for estimation of kinship and inbreeding.ResultsA total of 1,565 animals from three commercial pig populations were analyzed for 28,740 SNPs from the PorcineSNP60 Beadchip. Mean genomic inbreeding was higher than pedigree-based estimates in lines 2 and 3, but lower in line 1. As expected, a larger variation of genomic kinship estimates was observed for half and full sibs than for pedigree-based kinship reflecting Mendelian sampling. Genomic kinship between father-offspring pairs was lower (0.23) than the estimate based on pedigree (0.26). Bootstrap analyses using six reduced SNP panels (n = 500, 1000, 1500, 2000, 2500 and 3000) showed that 2,000 SNPs were able to reproduce the results very close to those obtained using the full set of unlinked markers (n = 7,984-10,235) with high correlations (inbreeding r > 0.82 and kinship r > 0.96) and low variation between different sets with the same number of SNPs.ConclusionsVariation of kinship between sibs due to Mendelian sampling is better captured using genomic information than the pedigree-based method. Therefore, the reduced sets of SNPs could generate more accurate kinship coefficients between sibs than the pedigree-based method. Variation of genomic kinship of father-offspring pairs is recommended as a parameter to determine accuracy of the method rather than correlation with pedigree-based estimates. Inbreeding and kinship coefficients can be estimated with high accuracy using ≥2,000 unlinked SNPs within all three commercial pig lines evaluated. However, a larger number of SNPs might be necessary in other populations or across lines.

Empirical comparison of single nucleotide polymorphisms and microsatellites for population and demographic analyses of bowhead whales

Interest in bowhead whale stock structure has been high due to the species’ extreme historical depletion, differential rates of recovery, the potential effects of climate change, and the need to set appropriate quotas for aboriginal hunts. We present an analysis of 42 linked and unlinked single nucleotide polymorphisms (SNPs) among 3 bowhead whale stocks and within the Bering/Chukchi/Beaufort Seas (BCB) stock, and compare results with previously published results of mtDNA control region sequences and 22 microsatellites. We performed tests of population structure (FST, χ2, STRUCTURE), population assignment, and estimates of effective population size (Ne), and evaluated different numbers of loci and samples to estimate the relative statistical power of SNPs and microsatellites. Results indicate that this number of SNPs provides similar power to microsatellites to detect low levels of differentiation (FST = 0.005−0.03) between bowhead populations with sample sizes of at least 20 per population. Neither marker performed well for Bayesian analysis of population structure (STRUCTURE) for the strata that had high diversity coupled with low differentiation. This example is valuable in cautioning against use of STRUCTURE to exclude demographic independence of relatively abundant populations. Microsatellites provided greater precision for estimates of Ne and for assignment tests. All 3 genetic marker types are consistent with the BCB stock being a single population. For microsatellites, differences were found between individuals born before 1949 and those born after 1979. SNPs are continuing to prove valuable as tools for understanding structure and demography of populations, and are likely to prove beneficial for long-term monitoring of bowhead whales.

Abstract B85: Genetic variation in the base excision repair pathway, environmental risk factors and colorectal adenoma risk

Abstract Background: Three inter-related and consistent factors emerging from the epidemiological literature for colorectal adenoma are cigarette smoking, alcohol intake, and dietary folate levels. Oxidative damage caused by these three factors can be repaired through the base excision repair pathway (BER). The ability to repair such damage may be modified by common genetic variants in BER pathway genes. In a sigmoidoscopy based study, we examined associations between 182 haplotype tagging single nucleotide polymorphisms (SNPs), which captured common genetic variation in 14 BER genes, and colorectal adenoma risk. Additionally, the interaction effects between SNPs and cigarette smoking, alcohol intake, and dietary folate levels were examined. Methods: We used data and samples from 721 cases and 736 controls enrolled in a University of Southern California/Kaiser Permanente sigmoidoscopy-based study of risk factors for colorectal adenomas. Genotype data on 182 haplotype tagging SNPs were obtained using the Golden Gate Assay (Illumina, Inc). Using logistic regression, per allele odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for the association between SNPs and colorectal adenoma risk. Using multinomial logistic regression, per allele ORs and 95% CIs for each SNP were calculated after stratifying on adenoma location (rectal versus left colon) and adenoma size (&amp;lt; 1 cm versus ≥ 1cm). Adenoma, adenoma location and adenoma size associations were corrected for multiple testing for all SNPs within each gene using the multiple testing correction method implemented in the R package PACT, and additionally for the 14 different genes within the BER pathway using the Bonferroni method. Interaction effects between SNPs and smoking, alcohol and dietary folate intake on colorectal adenoma risk were tested using logistic regression models and corrected for within each gene and additionally for the 14 different genes within the BER pathway using the Bonferroni method. Results: Among African-Americans we observed an increased risk of adenoma with APEX1 rs17111750 (OR = 2.19; 95%CI = 1.36-3.55; pACT = 0.013). Among Asian-Pacific Islanders we observed an increased risk of adenoma with FEN1 rs108499 (OR = 2.12; 95%CI = 1.30-3.45; pACT = 0.009). Among the entire study population, an increased risk of rectal adenoma was observed for two unlinked SNPs in the NEIL2 gene: NEIL2 rs7015453 (OR = 1.72; 95%CI = 1.24-2.39; pACT =0.025) and rs3757949 (OR=1.58; 95%CI= 1.18-2.13; pACT = 0.044). Both NEIL2 SNPs showed evidence of statistically significant heterogeneity of the ORs by adenoma location (rs7015453, p = 0.003; rs3757949, p = 0.004). The association between smoking (pack-years) and adenoma risk was modified by MUTYH rs10890324 (interaction pgene = 0.009). The association between alcohol intake and adenoma risk was modified by LIG3 rs1052536 (interaction pgene = 0.028). The association between dietary folate intake and adenoma risk was modified by two unlinked LIG3 SNPs (rs1052536 interaction pgene = 0.009; rs3744358 interaction pgene = 0.048) and one XRCC1 SNP (rs3213344 interaction pgene = 0.046). Conclusions: The findings support our hypothesis that genetic variation in DNA repair genes can modify the association of key colorectal adenoma risk factors. Our findings support a role for oxidative damage induced by these exposures on colorectal cancer formation. Citation Format: Roman Corral, Juan Pablo Lewinger, Amit D. Joshi, A. Joan Levine, David Van Den Berg, Robert W. Haile, Mariana C. Stern. Genetic variation in the base excision repair pathway, environmental risk factors, and colorectal adenoma risk. [abstract]. In: Proceedings of the Eleventh Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2012 Oct 16-19; Anaheim, CA. Philadelphia (PA): AACR; Cancer Prev Res 2012;5(11 Suppl):Abstract nr B85.