Large Number Of SNPs Research Articles

Genome comparison of long-circulating field CnmeGV isolates from the same region

Cnaphalocrocis medinalis granulovirus (CnmeGV), belonging to Betabaculovirus cnamedinalis, can infect the rice pest, the rice leaf roller. In 1979, a CnmeGV isolate, CnmeGV-EP, was collected from Enping County, China. In 2014, we collected another CnmeGV isolate, CnmeGV-EPDH3, at the same location and obtained the complete virus genome sequence using Illumina and ONT sequencing technologies. By combining these two virus isolates, we updated the genome annotation of CnmeGV and conducted an in-depth analysis of its genome features. CnmeGV genome contains abundant tandem repeat sequences, and the repeating units in the homologous regions (hrs) exhibit overlapping and nested patterns. The genetic variations within EPDH3 population show the high stability of CnmeGV genome, and tandem repeats are the only region of high genetic variation in CnmeGV genome replication. Some defective viral genomes formed by recombination were found within the population. Comparison analysis of the two virus isolates collected from Enping showed that the proteins encoded by the CnmeGV-specific genes were less conserved relative to the baculovirus core genes. At the genomic level, there are a large number of SNPs and InDels between the two virus isolates, especially in and around the bro genes and hrs. Additionally, we discovered that CnmeGV acquired a segment of non-ORF sequence from its host, which does not provide any new proteins but rather serves as redundant genetic material integrated into the viral genome. Furthermore, we observed that the host's transposon piggyBac has inserted into some virus genes. Together, dsDNA viruses could acquire non-coding genetic material from their hosts to expand the size of their genomes. These findings provide new insights into the evolution of dsDNA viruses.

Genomic prediction of resistance to Hymenoscyphus fraxineus in common ash (Fraxinus excelsior L.) populations.

The increase in introduced insect pests and pathogens due to anthropogenic environmental changes has become a major concern for tree species worldwide. Common ash (Fraxinus excelsior L.) is one of such species facing a significant threat from the invasive fungal pathogen Hymenoscyphus fraxineus. Some studies have indicated that the susceptibility of ash to the pathogen is genetically determined, providing some hope for accelerated breeding programs that are aimed at increasing the resistance of ash populations. To address this challenge, we used a genomic selection strategy to identify potential genetic markers that are associated with resistance to the pathogen causing ash dieback. Through genome-wide association studies (GWAS) of 300 common ash individuals from 30 populations across Poland (ddRAD, dataset A), we identified six significant SNP loci with a p-value ≤1 × 10-4 associated with health status. To further evaluate the effectiveness of GWAS markers in predicting health status, we considered two genomic prediction scenarios. Firstly, we conducted cross-validation on dataset A. Secondly, we trained markers on dataset A and tested them on dataset B, which involved whole-genome sequencing of 20 individuals from two populations. Genomic prediction analysis revealed that the top SNPs identified via GWAS exhibited notably higher prediction accuracies compared to randomly selected SNPs, particularly with a larger number of SNPs. Cross-validation analyses using dataset A showcased high genomic prediction accuracy, predicting tree health status with over 90% accuracy across the top SNP sets ranging from 500 to 10,000 SNPs from the GWAS datasets. However, no significant results emerged for health status when the model trained on dataset A was tested on dataset B. Our findings illuminate potential genetic markers associated with resistance to ash dieback, offering support for future breeding programs in Poland aimed at combating ash dieback and bolstering conservation efforts for this invaluable tree species.

Narcolepsy type I-associated DNA methylation and gene expression changes in the human leukocyte antigen region

Narcolepsy type 1 (NT1) is caused by a loss of hypothalamic orexin-producing cells, and autoreactive CD4+ and CD8+ T cells have been suggested to play a role in the autoimmune mechanism. Although NT1 showed a strong association with human leukocyte antigen (HLA)-DQB1*06:02, the responsible antigens remain unidentified. We analyzed array-based DNA methylation and gene expression data for the HLA region in CD4+ and CD8+ T cells that were separated from the peripheral blood mononuclear cells of Japanese subjects (NT1, N = 42; control, N = 42). As the large number of SNPs in the HLA region might interfere with the affinity of the array probes, we conducted a comprehensive assessment of the reliability of each probe. The criteria were based on a previous study reporting that the presence of frequent SNPs, especially on the 3′ side of the probe, makes the probe unreliable. We confirmed that 90.3% of the probes after general filtering in the HLA region do not include frequent SNPs, and are thus suitable for analysis, particularly in Japanese subjects. We then performed an association analysis, and found that several CpG sites in the HLA class II region of the patients were significantly hypomethylated in CD4+ and CD8+ T cells. This association was not detected when the effect of HLA-DQB1*06:02 was considered, suggesting that the hypomethylation was possibly derived from HLA-DQB1*06:02. Further RNA sequencing revealed reduced expression levels of HLA-DQB1 alleles other than HLA-DQB1*06:02 in the patients with NT1. Our results suggest the involvement of epigenetic and expressional changes in HLA-DQB1 in the pathogenesis of NT1.

Clinical characteristics and genetic analysis of a Chinese pedigree of type 2 diabetes complicated with interstitial lung disease.

Diabetes mellitus is a systemic metabolic disorder which may target the lungs and lead to interstitial lung disease. The clinical characteristics and mechanisms of type 2 diabetes mellitus (T2DM) complicated with interstitial lung disease (ILD) have been studied. However, little work has been done to assess genetic contributions to the development of T2DM complicated with ILD. A pedigree of T2DM complicated with ILD was investigated, and the whole genome re-sequencing was performed to identify the genetic variations in the pedigree. According to the literature, the most valuable genetic contributors to the pathogenesis of T2DM complicated with ILD were screened out, and the related cellular functional experiments were also performed. A large number of SNPs, InDels, SVs and CNVs were identified in eight subjects including two diabetic patients with ILD, two diabetic patients without ILD, and four healthy subjects from the pedigree. After data analysis according to the literature, MUC5B SNP rs2943512 (A > C) was considered to be an important potentially pathogenic gene mutation associated with the pathogenesis of ILD in T2DM patients. In vitro experiments showed that the expression of MUC5B in BEAS-2B cells was significantly up-regulated by high glucose stimulation, accompanied by the activation of ERK1/2 and the increase of IL-1β and IL-6. When silencing MUC5B by RNA interference, the levels of p-ERK1/2 as well as IL-1β and IL-6 in BEAS-2B cells were all significantly decreased. The identification of these genetic variants in the pedigree enriches our understanding of the potential genetic contributions to T2DM complicated with ILD. MUC5B SNP rs2943512 (A > C) or the up-regulated MUC5B in bronchial epithelial cells may be an important factor in promoting ILD inT2DM patients, laying a foundation for future exploration about the pathogenesis of T2DM complicated with ILD.

Meta-analysis of lung cancer in Chinese population in genetic predisposition

The prevention and diagnosis of lung cancer in the Chinese population has received extensive attention in past few years. Many studies have suggested that genetic predisposition may be a risk factor for lung cancer and an important means for early diagnosis of carcinoma of the lung. At present, the research on the molecular mechanism of lung cancer has been carried out on the whole genome, and a large number of SNPs have also been found in the Chinese population, these results suggest that the genetic predisposing factors of lung cancer in Chinese population are different from those in foreign population.

INADEQUATE NUMBER OF INFORMATIVE SNPs IN PRECLINICAL KARYOMAPPING TEST FOR PGT-M DEPENDS ON THE SELECTION OF REFERENCE

Karyomapping (KM) has changed the method of PGT-M drastically. KM shortened patients' long waiting period of conventional PCR. KM is advantageous because it has a larger number of SNPs than STR-linked markers of conventional PCR. However, there are cases in which KM cannot be applied due to an inadequate number of informative SNPs. In this study, we wanted to know if an inadequate number of informative SNPs is related to the reference among family members.

The genome trilogy of Anopheles stephensi, an urban malaria vector, reveals structure of a locus associated with adaptation to environmental heterogeneity

Anopheles stephensi is the most menacing malaria vector to watch for in newly urbanising parts of the world. Its fitness is reported to be a direct consequence of the vector adapting to laying eggs in over-head water tanks with street-side water puddles polluted by oil and sewage. Large frequent inversions in the genome of malaria vectors are implicated in adaptation. We report the genome assembly of a strain of An. stephensi of the type-form, collected from a construction site from Chennai (IndCh) in 2016. The genome reported here with a L50 of 4, completes the trilogy of high-resolution genomes of strains with respect to a 16.5 Mbp 2Rb genotype in An. stephensi known to be associated with adaptation to environmental heterogeneity. Unlike the reported genomes of two other strains, STE2 (2R+b/2Rb) and UCI (2Rb/2Rb), IndCh is found to be homozygous for the standard form (2R+b/2R+b). Comparative genome analysis revealed base-level details of the breakpoints and allowed extraction of 22,650 segregating SNPs for typing this inversion in populations. Whole genome sequencing of 82 individual mosquitoes from diverse geographical locations reveal that one third of both wild and laboratory populations maintain the heterozygous genotype of 2Rb. The large number of SNPs can be tailored to 1740 exonic SNPs enabling genotyping directly from transcriptome sequencing. The genome trilogy approach accelerated the study of fine structure and typing of an important inversion in An. stephensi, putting the genome resources for this understudied species on par with the extensively studied malaria vector, Anopheles gambiae. We argue that the IndCh genome is relevant for field translation work compared to those reported earlier by showing that individuals from diverse geographical locations cluster with IndCh, pointing to significant convergence resulting from travel and commerce between cities, perhaps, contributing to the survival of the fittest strain.

Rank-invariant estimation of inbreeding coefficients

The two alleles an individual carries at a locus are identical by descent (ibd) if they have descended from a single ancestral allele in a reference population, and the probability of such identity is the inbreeding coefficient of the individual. Inbreeding coefficients can be predicted from pedigrees with founders constituting the reference population, but estimation from genetic data is not possible without data from the reference population. Most inbreeding estimators that make explicit use of sample allele frequencies as estimates of allele probabilities in the reference population are confounded by average kinships with other individuals. This means that the ranking of those estimates depends on the scope of the study sample and we show the variation in rankings for common estimators applied to different subdivisions of 1000 Genomes data. Allele-sharing estimators of within-population inbreeding relative to average kinship in a study sample, however, do have invariant rankings across all studies including those individuals. They are unbiased with a large number of SNPs. We discuss how allele sharing estimates are the relevant quantities for a range of empirical applications.

Genome sequence, transcriptome, and annotation of rodent malaria parasite Plasmodium yoelii nigeriensis N67

BackgroundRodent malaria parasites are important models for studying host-malaria parasite interactions such as host immune response, mechanisms of parasite evasion of host killing, and vaccine development. One of the rodent malaria parasites is Plasmodium yoelii, and multiple P. yoelii strains or subspecies that cause different disease phenotypes have been widely employed in various studies. The genomes and transcriptomes of several P. yoelii strains have been analyzed and annotated, including the lethal strains of P. y. yoelii YM (or 17XL) and non-lethal strains of P. y. yoelii 17XNL/17X. Genomic DNA sequences and cDNA reads from another subspecies P. y. nigeriensis N67 have been reported for studies of genetic polymorphisms and parasite response to drugs, but its genome has not been assembled and annotated.ResultsWe performed genome sequencing of the N67 parasite using the PacBio long-read sequencing technology, de novo assembled its genome and transcriptome, and predicted 5383 genes with high overall annotation quality. Comparison of the annotated genome of the N67 parasite with those of YM and 17X parasites revealed a set of genes with N67-specific orthology, expansion of gene families, particularly the homologs of the Plasmodium chabaudi erythrocyte membrane antigen, large numbers of SNPs and indels, and proteins predicted to interact with host immune responses based on their functional domains.ConclusionsThe genomes of N67 and 17X parasites are highly diverse, having approximately one polymorphic site per 50 base pairs of DNA. The annotated N67 genome and transcriptome provide searchable databases for fast retrieval of genes and proteins, which will greatly facilitate our efforts in studying the parasite biology and gene function and in developing effective control measures against malaria.

28 Genomic prediction for marbling score in Hanwoo cattle using sequence data

Abstract As sequence information becomes available for some livestock species, there is a question on the amount of non-redundant information that may be embedded in the extra millions of SNPs or in causative variants within sequence. The objective of this study was to assess the gain in accuracy by using imputed whole-genome and selected SNP from sequence data in a beef cattle population. The dataset consisted of marbling score phenotypes for 545K Hanwoo cattle and pedigree information for 1.3M, of which 1,160 were genotyped for 50K SNPs. Imputation was done first to 777K and then to whole-genome sequence (WGS), which comprised 11,146,536 SNPs. Additionally, differentially expressed genes (DEG) and their 321,614 harboring SNPs were identified based on RNA-seq analysis of animals with high and low marbling score. An extra scenario combined 50K with DEG SNPs. Genomic predictions were obtained using GBLUP and single-step GBLUP (ssGBLUP) with and without weights, and BayesR. The last method could not be used for the WGS data because of the large number of SNPs. Predictive ability was calculated as the correlation between phenotypes adjusted for fixed effects and GEBV for 169 young animals. For all the methods, WGS and DEG had a slightly negative impact on predictive ability. Both GBLUP and BayesR had similar performances when using 50K, DEG, and 50K+ DEG, with predictive abilities equal to 0.19, 0.16, and 0.18, respectively. Predictive ability for ssGBLUP was 0.27, 0.26, and 0.27, in the aforementioned order. Using WGS, predictive ability for GBLUP was 0.17 and for ssGBLUP was 0.26. Weighting SNP differently did not improve predictions. As ssGBLUP uses all data available, not only genotyped animals with phenotypes as the other methods, it is more robust for genomic predictions. No gain in accuracy was observed, possibly because the selected sequence variants were not causative.

LDBlockShow: a fast and convenient tool for visualizing linkage disequilibrium and haplotype blocks based on variant call format files.

The triangular correlation heatmap aiming to visualize the linkage disequilibrium (LD) pattern and haplotype block structure of SNPs is ubiquitous component of population-based genetic studies. However, current tools suffered from the problem of time and memory consuming. Here, we developed LDBlockShow, an open source software, for visualizing LD and haplotype blocks from variant call format files. It is time and memory saving. In a test dataset with 100 SNPs from 60000 subjects, it was at least 10.60 times faster and used only 0.03-13.33% of physical memory as compared with other tools. In addition, it could generate figures that simultaneously display additional statistical context (e.g. association P-values) and genomic region annotations. It can also compress the SVG files with a large number of SNPs and support subgroup analysis. This fast and convenient tool will facilitate the visualization of LD and haplotype blocks for geneticists.

Abstract P5-07-06: Performance of a polygenic risk score combined with clinical assessment for breast cancer risk

Abstract Background: Polygenic risk scores (PRS) based on a large number of SNPs associated with breast cancer have recently been made available in combination with multigene panel testing for clinical management of breast cancer risk. Breast cancer risk assessment has historically been performed using various non-genetic risk models, which predict lifetime risk of breast cancer in unaffected women based on personal and family history information. While clinical use of PRS in combination with these models continues to increase, the predictive performance of a PRS combined with clinical information in real-world patient populations has not been thoroughly investigated. Methods: We assessed a 100-SNP breast cancer PRS in combination with the Tyrer-Cuzick model-estimated lifetime breast cancer risk in 5,374 Caucasian women from the case-control Mayo Clinic Breast Cancer Study (MCBCS), comprised of 3,373 breast cancer cases and 2,001 unaffected controls seen at Mayo Clinic from 2004 to 2016. Clinical, family history, and demographic information was collected on all MCBCS participants via questionnaires and medical record review. SNPs were selected for the PRS if they exceeded genome-wide significance in ≥2 large-scale breast cancer genome wide association studies (GWAS) in women of European descent. Selected SNPs were then used to construct a population standardized PRS, accounting for per-allele odds ratios reported in the largest GWAS to date and population-specific allele frequencies. PRS and Tyrer-Cuzick model associations with breast cancer and related clinical features were tested using multivariate logistic regression. Results: Among cases and controls, mean±SD age at diagnosis and study enrollment was 56.4±12.4 and 56.2±14.1, respectively. Approximately 36.9% of cases and 16.9% of controls had ≥1 first- or second-degree relative with breast or ovarian cancer, respectively. Among unaffected women, the median (IQR) estimated lifetime risk of breast cancer to age 85 based on Tyrer-Cuzick alone was 8.3% (6.9%), and 2.6% had a clinically actionable lifetime risk of ≥20%. The mean±SD sum of the risk alleles across 100 SNPs was significantly higher for cases vs. controls (94.8±6.3 vs. 92.7±6.2, p<0.001). Compared to women in the lowest quartile of PRS, those in the 2nd, 3rd and 4th quartiles were 1.47 (95% CI: 1.26-1.72), 1.87 (95% CI: 1.60-2.19), and 2.22 (95% CI: 1.89-2.61) times more likely to have breast cancer after adjustment for age and family history. The AUC was 0.59 (95% CI: 0.58-0.61) for PRS and 0.60 (95% CI: 0.58-0.61) for Tyrer-Cuzick model estimated risk alone; but when combined, the model achieved an AUC of 0.63 (95% CI: 0.62-0.65). Among unaffected women, 6.7% had ≥20% lifetime risk of breast cancer based on the combined PRS-clinical model. Conclusions: These findings suggest that the 100-SNP PRS significantly improves estimation of breast cancer risk based on non-genetic models, and can be used to further identify women at increased lifetime risk who would otherwise not be identified by clinical assessment alone. Citation Format: Mary Helen Black, Shuwei Li, Holly LaDuca, Sebastian Armasu, Eric C. Polley, Patrick Fitz-Gibbon, Chris G. Scott, Stacey J. Winham, Janet E. Olson, Kathryn J. Ruddy, Celine M. Vachon, Fergus J. Couch. Performance of a polygenic risk score combined with clinical assessment for breast cancer risk [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-07-06.

Comparative genomic analysis and identification of pathogenicity islands of hypervirulent ST-17 Streptococcus agalactiae Brazilian strain

Streptococcus agalactiae are important pathogenic bacteria that cause severe infections in humans, especially neonates. The mechanism by which ST-17 causes invasive infections than other STs is not well understood. In this study, we sequenced the first genome of a S. agalactiae ST-17 strain isolated in Brazil using the Illumina HiSeq 2500 technology. S. agalactiae GBS90356 ST-17 belongs to the capsular type III and was isolated from a neonatal with a fatal case of meningitis. The genome presented a size of 2.03 Mbp and a G + C content of 35.2%. S. agalactiae has 706 genes in its core genome and an open pan-genome with a size of 5.020 genes, suggesting a high genomic plasticity. GIPSy software was used to identify 10 Pathogenicity islands (PAIs) which corresponded to 15% of the genome size. IslandViewer4 corroborated the prediction of six PAIs. The pathogenicity islands showed important virulence factors genes for S. agalactiae e.g. neu, cps, dlt, fbs, cfb, lmb. SignalP detected 20 proteins with signal peptides among the 352 proteins found in PAIs, which 60% were located in the SagPAI_5. SagPAI_2 and 5 were mainly detected in ST-17 strains studied. Moreover, we identified 51 unique genes, 9 recombination regions and a large number of SNPs with an average of 760.3 polymorphisms, which can be related with high genomic plasticity and virulence during host-pathogen interactions. Our results showed implications for pathogenesis, evolution, concept of species and in silico analysis value to understand the epidemiology and genome plasticity of S. agalactiae.

Genetic diversity and population structure of the Mediterranean sesame core collection with use of genome-wide SNPs developed by double digest RAD-Seq.

The Mediterranean sesame core collection contains agro-morphologically superior sesame accessions from geographically diverse regions in four continents. In the present investigation, the genetic diversity and population structure of this collection was analyzed with 5292 high-quality SNPs discovered by double-digest restriction site associated DNA (ddRAD) sequencing, a cost-effective and flexible next-generation sequencing method. The genetic distance between pairs of accessions varied from 0.023 to 0.524. The gene diversity was higher in accessions from Asia than from America, Africa, and Europe. The highest genetic differentiation was observed between accessions collected from America and Europe. Structure analysis showed the presence of three subpopulations among the sesame accessions, and only six accessions were placed in an admixture group. Phylogenetic tree and principal coordinate analysis clustered the accessions based on their countries of origin. However, no clear division was evident among the sesame accessions with regard to their continental locations. This result was supported by an AMOVA analysis, which revealed a genetic variation among continental groups of 5.53% of the total variation. The large number of SNPs clearly indicated that the Mediterranean sesame core collection is a highly diverse genetic resource. The collection can be exploited by breeders to select appropriate accessions that will provide high genetic gain in sesame improvement programs. The high-quality SNP data generated here should also be used in genome-wide association studies to explore qualitative trait loci and SNPs related to economically and agronomically important traits in sesame.

34 Present and future of genomic test reporting in the cattle industry

Abstract A series of custom low density (LD) SNP genotyping platforms have been created over the years. Recognized by the GeneSeek Genomic Profiler (GGP) nomenclature, these SNP arrays have increased in size as new versions were created, such as: GGP-LD-v1 (n = 8,762), GGP-LD-v2 (n = 20,057), GGP-LD-v3 (n = 26,151), GGP-LD-v4 (n = 30,108), and GGP Bovine 50K (n = 47,843), all of which contained a base of the Illumina Bovine LD array (n = 7,931) and then added SNPs to provide maximum information content (Shannon Entropy) and optimal genomic coverage into target populations without specific restrictions on overlap to historical commercial arrays such as the Illumina Bovine 50K (n = 54,001). Our approach has been to select SNP content which originated on the Illumina Bovine HD array (n = 777,962) or the GGP F250 functional SNP array (n = 221,115). This approach produced GGPs which: 1) have a larger number of SNPs that meet quality control metrics for minor allele frequency and Hardy-Weinberg segregation testing; 2) have superior imputation accuracy to the Illumina HD array in target populations; and 3) have causative SNPs or SNPs in closer LD with causative mutations for functional genomics studies and increased utility across populations. These design features have not always been utilized by users of the GGP portfolio. In some cases, users have imputed from GGP content back to the Illumina Bovine 50K SNP content within their population because that was the earliest process they developed in their evaluation system. This approach ignores the innovation and potential utility designed into the GGP chips for breeders within those organizations. We do not look back to prior SNP arrays for content definition for the purpose of bridging content from current arrays to the past. Instead, our vision is to continue to innovate, on a routine basis, which SNPs we provide to customers, so that their genetic evaluations can continue to evolve and improve into the future.

Predictive modeling of schizophrenia from genomic data: Comparison of polygenic risk score with kernel support vector machines approach.

A major controversy in psychiatric genetics is whether nonadditive genetic interaction effects contribute to the risk of highly polygenic disorders. We applied a support vector machines (SVMs) approach, which is capable of building linear and nonlinear models using kernel methods, to classify cases from controls in a large schizophrenia case–control sample of 11,853 subjects (5,554 cases and 6,299 controls) and compared its prediction accuracy with the polygenic risk score (PRS) approach. We also investigated whether SVMs are a suitable approach to detecting nonlinear genetic effects, that is, interactions. We found that PRS provided more accurate case/control classification than either linear or nonlinear SVMs, and give a tentative explanation why PRS outperforms both multivariate regression and linear kernel SVMs. In addition, we observe that nonlinear kernel SVMs showed higher classification accuracy than linear SVMs when a large number of SNPs are entered into the model. We conclude that SVMs are a potential tool for assessing the presence of interactions, prior to searching for them explicitly.

Developing genome-wide SNPs and constructing an ultrahigh-density linkage map in oil palm

Oil palm (Elaeis guineensis Jacq.) is the leading oil-producing crops and the most important edible oil resource worldwide. DNA markers and genetic linkage maps are essential resources for marker-assisted selection to accelerate genetic improvement. We conducted RAD-seq on an Illumina NextSeq500 to discover genome-wide SNPs, and used the SNPs to construct a linkage map for an oil palm (Tenera) population derived from a cross between a Deli Dura and an AVROS Pisifera. The RAD-seq produced 1,076 million single-end reads across the breeding population containing 155 trees. Mining this dataset detected 510,251 loci. After filtering out loci with low accuracy and more than 20% missing data, 11,394 SNPs were retained. Using these SNPs, in combination with 188 anchor SNPs and 123 microsatellites, we constructed a linkage map containing 10,023 markers covering 16 chromosomes. The map length is 2,938.2 cM with an average marker space of 0.29 cM. The large number of SNPs will supply ample choices of DNA markers in analysing the genetic diversity, population structure and evolution of oil palm. This high-density linkage map will contribute to mapping quantitative trait loci (QTL) for important traits, thus accelerating oil palm genetic improvement.

Genetic diversity, population structure, and linkage disequilibrium of elite and local apple accessions from Belgium using the IRSC array

The identification of molecular markers associated with economic and quality traits will help improve breeding for new apple (Malus × domestica Borkh.) cultivars. Tools such as the 8K apple SNP array developed by the RosBREED consortium allow for high-throughput genotyping of SNP polymorphisms within collections. However, genetic characterization and the identification of population stratification and kinship within germplasm collections is a fundamental prerequisite for identifying robust marker–trait associations. In this study, a collection of apple germplasm originally developed for plant architectural studies and consisting of both non-commercial/local and elite accessions was genotyped using the 8K apple SNP array to identify cryptic relationships between accessions, to analyze population structure and to calculate the linkage disequilibrium (LD). A total of nine pairs of synonyms and several triploids accessions were identified within the 130 accessions genotyped. In addition, most of the known parent-child relations were confirmed, and several putative, previously unknown parent-child relations were identified among the local accessions. No clear subgroups could be identified although some separation between local and elite accessions was evident. The study of LD showed a rapid decay in our collection, indicating that a larger number of SNPs is necessary to perform whole genome association mapping. Finally, an association mapping effort for architectural traits was carried out on a small number of accessions to estimate the feasibility of this approach.

A Genome-Wise Association Study of A Quantitative Alcoholism Trait Using A Full Genetic Model Identifies Significant SNP Heritability From Dominance And Epistatic Interactions

Most psychiatric diseases are complex diseases involving polygenes, environment, and their interactions. Although genome-wide association studies (GWASs) revolutionized the genetic dissection of many diseases, only a very small portion of heritability has been accounted for, i.e. there was a remarkable limitation as missing heritability. Here, we demonstrate that perturbations arising from gene-gene interactions, including dominance and epistasis, and conditions of comorbidity substantially influence the complex trait of alcohol dependence symptom count (ADSC). We conducted a GWAS of ADSC by using a mixed liner approach in a full genetic model considering additive, dominance, epistasis and their interactions with ethnicity, as well as conditions of comorbid substance dependences, in the dataset of the Study of Addiction: Genetics and Environment with 3838 subjects. Twenty quantitative trait single nucleotide polymorphisms (QTSs) showed significant associations with ADSC (experiment-wise P < 0.05 based on permutation test), including four in previously reported genes (ADH1C, PKNOX2, CPE, and KCNB2), supporting the overall validity of the analysis. Two QTSs within or near ADH1C showed significant association in a dominance inheritance mode, and increased the phenotype value of ADSC when the effect of comorbid opiate or marijuana dependence was controlled. Significant association was also identified in variants within 4 novel genes (RGS6, FMN1, NRM, and BPTF), 2 noncoding RNA and 2 epistasis loci. QTS rs7616413, located near PTPRG encoding a protein tyrosine phosphatase (PTP) receptor, interacted with rs10090742 within ANGPT1 encoding a PTP, in an additive × additive or dominance × additive manner. The detected QTSs contributed to about 20% of total heritability, in which dominance and epistasis effects accounted for over 50%. In comparison, the original analysis of the dataset using the conventional approach of GWAS failed to detect a genome-wide association with alcohol dependence. Our analysis discloses a much larger number of SNPs or epistasis for a quantitative trait of a psychiatric disorder, and may represent an important stride toward solving the problem of missing heritability. This approach can be employed in GWASs and precision medicine of many other psychiatric disorders such as schizophrenia, major depression et al.

Topological Data Analysis Generates High-Resolution, Genome-wide Maps of Human Recombination

Meiotic recombination is a fundamental evolutionary process driving diversity in eukaryotes. In mammals, recombination is known to occur preferentially at specific genomic regions. Using topological data analysis (TDA), a branch of applied topology that extracts global features from large data sets, we developed an efficient method for mapping recombination at fine scales. When compared to standard linkage-based methods, TDA can deal with a larger number of SNPs and genomes without incurring prohibitive computational costs. We applied TDA to 1,000 Genomes Project data and constructed high-resolution whole-genome recombination maps of seven human populations. Our analysis shows that recombination is generally under-represented within transcription start sites. However, the binding sites of specific transcription factors are enriched for sites of recombination. These include transcription factors that regulate the expression of meiosis- and gametogenesis-specific genes, cell cycle progression, and differentiation blockage. Additionally, our analysis identifies an enrichment for sites of recombination at repeat-derived loci matched by piwi-interacting RNAs.