SNP Pairs Research Articles

Genotyping SNPs in lignin biosynthesis gene (CAD1) and transcription factors (MYB1 and MYB2) exhibits association with wood density in teak (Tectona grandis L.f.).

Teak (Tectona grandis L.f.), an important source of tropical timber with immense economic value, is a highly outcrossing forest tree species. 150 unrelated accessions of teak (Tectona grandis L.f.) plus trees assembled as clones at National Teak Germplasm Bank, Chandrapur, Maharashtra, India was investigated for association mapping of candidate lignin biosynthesis gene (CAD1) and transcription factors (MYB1 and MYB2). The CAD1, MYB1 and MYB2 were amplified using specifically designed primers. The amplified sequences were then sequenced and genotyped for 112 SNPs/11 indels. We evaluated the association between SNPs and wood density in teak accessions using GLM and MLM statistical models, with Bonferroni correction applied. The teak accessions recorded an average wood density of 416.69kg.m-3 (CV 4.97%) and comprised of three loosely structured admixed sub-populations (K = 3), containing 72.05% genetic variation within sub-populations with low intragenic LD (0-21% SNP pairs) at P < 0.05 and high LD decay (33-934bp) at R2 = 0.1. GLM and MLM models discounting systematic biases (Q and K matrices) to avoid false discovery revealed five loci at rare variants (MAF 0.003) and three loci at common variants (MAF 0.05) to be significantly (P < 0.05) associated with the wood density. However, the stringent Bonferroni correction (4.06-7.04 × 10-4) yielded only a single associated locus (B1485C/A) from exon of MYB1 transcription factor, contributing to about 10.35% phenotypic variation in wood density trait. Scored SNP locus (B1485C/A) can be developed as a molecular probe for selection of improved planting stock with proven wood density trait for a large-scale teak plantation.

Assessment of linkage disequilibrium and haplotype block structure in indigenous cattle populations of Tamil Nadu, India usingwhole genome sequence data

Understanding the nature of linkage disequilibrium (LD) between molecular markers reflects the degree of non-random association between their alleles, which is essential for genome-wide association studies. The main objective of this study was to assess the chromosome-wise linkage disequilibrium and haplotype block structure in indigenous cattle breeds of Tamil Nadu, India. A total of 79 animals belonging to five indigenous cattle breeds were considered as single indigenous cattle population and three samples per breed were sequenced using Illumina NovaSeqTM 6000 and Illumina HiSeq 2500. The LD parameter (r2) was estimated for a total of 62,095,778 pair- wise SNPs for all autosomes. The chromosome-wise number of SNP pairs, mean r2±standard deviation and median r2 values were 2,141,234, 0.484±0.246 and 0.493, respectively. Chromosome-wise mean r2 of different distance bins were calculated and it showed the maximum r2 value of 0.839 at 31-70 kb distance for Chromosome 11 and minimum r2 value of zero for Chromosome 7, 11, 15, 20 and 29, respectively at a distance 71-100 kb. This study also revealed a total of 413, 277 haplotype blocks which covered 2.34% of the autosomal genome. There was a total of 1,589,118 SNPs distributed within the haplotype blocks, covering a total length of 53.62 mb. The results of the study suggest the need for breed-specific reference populations for indigenous cattle breeds, which have a greater density of molecular markers of economic significance and thereby to identify breed-specific haplotypes in future.

Interplay Between Genes from Peroxisome Biogenesis and Integrated Stress Response Pathways is Significantly Associated with Alzheimer’s Disease

AbstractBackgroundPeroxisomes are single‐membrane organelles involved among other things in ether‐phospholipids production that plays an important role in axon myelination in the central nervous system. Disruptions in cytosolic receptor PEX5L (involved in protein import into peroxisome matrix) may lead to peroxisome malfunctioning and disturbance of myelin homeostasis, which, in turn, may contribute to developing Alzheimer’s disease (AD). Experimental studies showed that peroxisome dysfunction is associated with activation of the integrative stress response (ISR). Recent studies provide evidence that the EIF2AK4 gene, a sensor of amino acid deprivation in ISR, is involved in the AD regulation. It is, however, unclear whether interplay between PEX5L and EIF2A4 is associated with AD.MethodTo test the association of the interplay between PEX5L and EIF2AK4 genes with the late‐onset‐AD, we analyzed the Health and Retirement Study (HRS) data using logistic regression model with the interaction term. Education, sex, smoking status, and first five principal components were included as observed covariates. The binary AD outcome was defined as “0” if AD onset was at any age, and as “1” if a person survived to age 85+ and did not get AD during the life. Linkage Disequilibrium test and SNP‐clumping procedure were used to reduce number of tests in SNPxSNP interaction analysis.ResultInteractions between SNPs in fifteen SNP pairs (one SNP in EIF2AK4 gene and another in PEX5L gene) were significantly associated with decreased odds of AD, with effect sizes (β coefficients before the interaction term) ranging between 0.62‐0.69, and p‐values between 1.64E‐04 ‐ 2.12E‐05, with Bonferroni correction threshold = 1.67E‐04. Six SNPs from PEX5L (rs1404271, rs11708154, rs59018122, rs9836757, rs76133869, rs6443674) and five SNPs from EIF2AK4 (rs3207297, rs2279579, rs2291625, rs12591842, rs117584784) participated in such interactions.ConclusionIn this study, interactions between SNPs in EIF2AK4 and PEX5L genes were significantly associated with lower odds of AD in HRS participants. Our findings support the idea that the interplay between genes involved in cellular stress response pathway and peroxisome biogenesis can play a protective role in AD. These results also demonstrate how the knowledge from experimental research can be translated to human applications population‐based studies of AD.

PSXIV-21 Genetic Diversity in Mashona, a Sanga-Type Cattle from Southern Africa

Abstract Climate change projections suggest pervasive impacts on livestock performance, for which United States (US) producers will need to adjust. Fortuitously, the US has a broad array of genetic resources among its breeds with which to explore a genetic basis for increased resilience. Sanga-type cattle were developed in a tropical environment and are generally considered a long-formed taurine and indicine composite. Consequently, they may harbor unique genetic diversity which could be of utility to the US cattle industry. Mashona is a Sanga breed from southern Africa and has been imported into the US. Comparison of its genetic diversity to other breeds found in US tropical and subtropical environments has not been studied. To initiate evaluation of Mashona we evaluated 334 animals from Mashona (24), Tuli (12), Florida Cracker (20), Senepol (24), Brahman (68), Brangus (20), Romosinuano (20), Hereford (50), Angus (50) and Wagyu (56). Notably, Tuli is also a Sanga-type breed closely related to Mashona. All animals were genotyped with the BovineHD chip (777K SNP). Quality control included removal of loci with a minor allele frequency &amp;lt; 0.05 and a missingness rate &amp;gt; 0.1. For SNP pairs with r2 &amp;gt; 0.2 across all breeds, one SNP was chosen at random and removed. After quality control, 75,698 SNP remained for analysis. The first 4 principal components explained 15.5, 4.3, 3.1, and 2.4%, respectively, of the variation in the genomic relationship matrix. Mashona and Tuli tended to cluster close together for all the principal components (PC) evaluated. The first PC captured variation across the taurine-indicine axis with Hereford and Brahman at opposite extremes; Mashona clustered approximately midway between taurine and indicine breeds. Breed placement along PC4 highlighted separation of Sanga breeds from other breeds evaluated, though Mashona and Tuli each formed a distinct cluster. Ancestral groups were estimated using ADMIXTURE software for k = 3 to 15. Cross-validation error declined from 0.55 at k = 3 to 0.50 at k = 7, after which the error was relatively similar for greater values of k. As early as k = 4, Mashona and Tuli were found to be a distinct population. This group represented 61.7 to 99.9 and 59.5 to 74.9% of the estimated admixture for Mashona and Tuli, respectively. At k = 10, Mashona and Tuli branched into separate populations. Additional estimated ancestry in Mashona was primarily from groups representing Angus and Brahman, up to 15 and 9%, respectively. With progressive cluster number tropical cattle breeds were found to be distinct from one another and other taurine and indicine breeds. Collectively these results support Mashona being a genetically distinct population relative to breeds more commonly utilized in the US beef industry; such a broad array of genetic diversity suggests there may be substantial allele reservoirs capable of conferring selective advantages to counter negative impacts of climate change.

Genetic structure analysis in several populations of cattle using SNP genotypes

Parameters such as effective population size (Ne), runs of homozygosity (ROH), and inbreeding based on ROH (FROH) can give new insight into the level of genetic diversity for the population under selection. This research aimed to measure the extent of linkage disequilibrium (LD), effective population size (Ne), Haplotype Block Structure, and runs of homozygosity (ROHs) in several populations of cattle using SNP genotypes. In this study, that the average r 2 decreased with the increasing distance of SNP pairs. A general decrease in Ne can be seen for all four populations, indicating a loss of genetic diversity. The Iranian Holstein had the lowest level of genomic inbreeding at an ROH of 1, 5, 10 Mb, while the French Holstein had the highest. The maximum number of ROH is seen at a distance of less than 1 Mb, and the lowest number of ROH is seen at a distance of 10 Mb. The number of ROH decreases with increasing distance due to the increased recombination rate. This is a concern as an increase in inbreeding leads to a reduction in the effective population size, which was also evident in the study populations.

Population genomic analyses reveal evidence for limited recombination in the superbug Candida auris in nature

Candida auris is a recently emerged, multidrug-resistant pathogenic yeast capable of causing a diversity of human infections worldwide. Genetic analyses based on whole-genome sequences have clustered strains in this species into five divergent clades, with each clade containing limited genetic variation and one of two mating types, MTLa or MTLα. The patterns of genetic variations suggest simultaneous emergence and clonal expansion of multiple clades of this pathogen across the world. At present, it is unclear whether recombination has played any role during the evolution of C. auris. In this study, we analyzed patterns of associations among single nucleotide polymorphisms in both the nuclear and the mitochondrial genomes of 1,285 strains to investigate potential signatures of recombination in natural C. auris populations. Overall, we found that polymorphisms in the nuclear and mitochondrial genomes clustered the strains similarly into the five clades, consistent with a lack of evidence for recombination among the clades after their divergence. However, variable percentages of SNP pairs showed evidence of phylogenetic incompatibility and linkage equilibrium among samples in both the nuclear and the mitochondrial genomes, with the percentages higher in the total population than those within individual clades. Our results are consistent with limited but greater frequency of recombination before the divergence of the clades than afterwards. SNPs at loci related to antifungal resistance showed frequencies of recombination similar to or lower than those observed for SNPs in other parts of the genome. Together, though very limited, evidence for the observed recombination for both before and after the divergence of the clades suggests the possibility for continuous genetic exchange in natural populations of this important yeast pathogen.

PSXIV-26 Selection footprints in Russian red cattle identified by linkage disequilibrium blocks based on SNP data

Abstract Among the variety of cattle breeds in Russia, the Russian red dual-purpose cattle breeds have great importance because of their ability to produce high milk yields as well as to provide excellent milk quality. The low census size of the Russian red cattle breeds requires development of programs for conservation of their biodiversity. Our study aimed to investigate selection footprints in Russian red cattle breeds, using high values of linkage disequilibrium (LD) in SNP haplotype blocks as indicators. For finding such LD blocks, we used the genotypes (≈35K SNPs) of Red Gorbatov (RGB, n = 26), Bestuzhev (BST,n = 27), and Suksun (SKS,n = 17) breeds, as well as Red Holstein (RH,n = 16) as an outgroup. Quality control and LD calculations for different distances were performed in Plink 1.90. Top 0.01% SNP pairs by LD value (0.9≤r2&amp;lt; 1.0) were selected for further analysis. The effective population size derived from LD patterns was estimated using SNeP tool. Comparison of LD values for 70 kb interval between breeds and chromosomes by MANOVA pairwise testing significantly distinguished RH/RGB and BST/SKS breeds (P &amp;lt; 0.05-0.001). LD values among chromosomes were 0.195–0.287 for RH, 0.194–0.272 for RGB, 0.172–0.237 for BST, and 0.157–0.217 for SKS. The SKS and BST breeds had higher Ne values (84 and 113, respectively) compared to RH (63) and RGB (79). Selection footprints by LD blocks in Russian red cattle genome covered several relevant genes on BTA1 (EPHA6,DGKG), BTA2 (LRP1B,THSD7B,STAT1), BTA5 (CPM,BAIAP2L2), BTA9 (TRDN,UTRN), BTA10 (KCNN2,CAPN3), BTA11 (SH3RF3,RABGAP1,RALGPS1), BTA14 (ZNF16,ARHGAP39,TOX,DGAT1), and BTA19 (MYH10), BTA22 (FHIT). Detected genes were found to be responsible for milk fat and protein contents, fatty acid composition, somatic cells score, fertility, feet and legs, and udder conformation traits. Our results can be useful for developing the breeding and conservation programs of the Russian red cattle genetic resources. The study was funded by RFBR within project No. 20-516-00020

MIDESP: Mutual Information-Based Detection of Epistatic SNP Pairs for Qualitative and Quantitative Phenotypes.

Simple SummaryThe interactions between SNPs, which are known as epistasis, can strongly influence the phenotype. Their detection is still a challenge, which is made even more difficult through the existence of background associations that can hide correct epistatic interactions. To address the limitations of existing methods, we present in this study our novel method MIDESP for the detection of epistatic SNP pairs. It is the first mutual information-based method that can be applied to both qualitative and quantitative phenotypes and which explicitly accounts for background associations in the dataset.The interactions between SNPs result in a complex interplay with the phenotype, known as epistasis. The knowledge of epistasis is a crucial part of understanding genetic causes of complex traits. However, due to the enormous number of SNP pairs and their complex relationship to the phenotype, identification still remains a challenging problem. Many approaches for the detection of epistasis have been developed using mutual information (MI) as an association measure. However, these methods have mainly been restricted to case–control phenotypes and are therefore of limited applicability for quantitative traits. To overcome this limitation of MI-based methods, here, we present an MI-based novel algorithm, MIDESP, to detect epistasis between SNPs for qualitative as well as quantitative phenotypes. Moreover, by incorporating a dataset-dependent correction technique, we deal with the effect of background associations in a genotypic dataset to separate correct epistatic interaction signals from those of false positive interactions resulting from the effect of single SNP×phenotype associations. To demonstrate the effectiveness of MIDESP, we apply it on two real datasets with qualitative and quantitative phenotypes, respectively. Our results suggest that by eliminating the background associations, MIDESP can identify important genes, which play essential roles for bovine tuberculosis or the egg weight of chickens.

Risk of Colorectal Carcinoma May Predispose to the Genetic Variants of the GST, CYP450, and TP53 Genes Among Nonsmokers in the Saudi Community.

PurposeColorectal carcinoma (CRC) represents a considerable public health burden in Saudi Arabia. Several candidate genes and genetic variants have been associated with morbidity and mortality among patients with CRC. We explored whether allelic variants of the GSTM1, GSTT1, CYP450 (rs4646903 and rs1048943), and TP53 (rs1042522) genes predisposed nonsmoking Saudi individuals to increased risk for CRC.Patients and MethodsDNA from buccal cells of 158 participants (80 with CRC and 78 healthy controls) were analyzed for five SNPs using conventional PCR and TaqMan genotyping assays. The SNPStats software was utilized to choose the best interactive inheritance mode for selected SNPs (https://www.snpstats.net).ResultsThe mean age of diagnosis was 62.4±13.5 years (range, 40–83 years), with those aged 71–80 years and those aged 40–50 years accounting for the most diagnoses (35.7% and 28.6% of diagnosis, respectively). The GSTM1 and TP53 rs1042522 SNPs were associated with CRC (OR= 3.7; P< 0.0001, and OR= 1.6; P= 0.033, respectively). A plausible contribution to CRC was observed for the GSTM1 and TP53 rs1042522 SNPs (x2Yates= 14.7; P= 0.00013, and x2Yates= 11.2; P= 0.0008, respectively), while the GSTT1 null variant did not affect risk. Heterozygosity in the CYP450 (rs4646903 and rs1048943 SNPs) was associated with a significant risk for CRC. The GSTM1/GSTT1 and CYP450 rs4646903/rs1048943 SNP pairs were in linkage disequilibrium, and the associations were statistically significant (P= 0.01 and P= 4.6x10‒7, respectively).ConclusionThe GSTM1 and TP53 rs1042522 variants can increase the development of CRC in Saudi nonsmokers. Even the presence of one copy of a variant allele in the CYP1A1 gene can predispose CRC risk. Additional studies should also examine other SNP combinations with lifestyle factors that may help prevent, rather than facilitate, colorectal tumorigenesis.

Synonymous mutation in Growth Regulating Factor 15 of miR396a target sites enhances photosynthetic efficiency and heat tolerance in poplar.

Heat stress damages plant tissues and induces multiple adaptive responses. Complex and spatiotemporally specific interactions among transcription factors (TFs), microRNAs (miRNAs), and their targets play crucial roles in regulating stress responses. To explore these interactions and to identify regulatory networks in perennial woody plants subjected to heat stress, we integrated time-course RNA-seq, small RNA-seq, degradome sequencing, weighted gene correlation network analysis, and multi-gene association approaches in poplar. Results from Populus trichocarpa enabled us to construct a three-layer, highly interwoven regulatory network involving 15 TFs, 45 miRNAs, and 77 photosynthetic genes. Candidate gene association studies in a population of P. tomentosa identified 114 significant associations and 696 epistatic SNP-SNP pairs that were linked to 29 photosynthetic and growth traits (P<0.0001, q<0.05). We also identified miR396a and its target, Growth-Regulating Factor 15 (GRF15) as an important regulatory module in the heat-stress response. Transgenic plants of hybrid poplar (P. alba × P. glandulosa) overexpressing a GRF15 mRNA lacking the miR396a target sites exhibited enhanced heat tolerance and photosynthetic efficiency compared to wild-type plants. Together, our observations demonstrate that GRF15 plays a crucial role in responding to heat stress, and they highlight the power of this new, multifaceted approach for identifying regulatory nodes in plants.

Evidence for Divergent Selection on Immune Genes between the African Malaria Vectors, Anopheles coluzzii and A. gambiae.

Simple SummaryA comparison of the genomes of the African malaria vectors, Anopheles gambiae and A. coluzzii, revealed that immune genes are highly diverged. Although these two species frequently co-occur within a single site, they occur in distinct larval habitats. Our results taken in the context of known differences in the larval habitats occupied by these taxa support the hypothesis that observed genetic divergence may be driven by immune response to microbial agents specific to these habitats. Strict within species mating may have subsequently evolved in part to maintain immunocompetence which might be compromised by dysregulation of immune pathways in hybrids. We conclude that the evolution of immune gene divergence among this important group of species may serve as a useful model to explore ecological speciation in general.During their life cycles, microbes infecting mosquitoes encounter components of the mosquito anti-microbial innate immune defenses. Many of these immune responses also mediate susceptibility to malaria parasite infection. In West Africa, the primary malaria vectors are Anopheles coluzzii and A. gambiae sensu stricto, which is subdivided into the Bamako and Savanna sub-taxa. Here, we performed whole genome comparisons of the three taxa as well as genotyping of 333 putatively functional SNPs located in 58 immune signaling genes. Genome data support significantly higher differentiation in immune genes compared with a randomly selected set of non-immune genes among the three taxa (permutation test p < 0.001). Among the 58 genes studied, the majority had one or more segregating mutations (72.9%) that were significantly diverged among the three taxa. Genes detected to be under selection include MAP2K4 and Raf. Despite the genome-wide distribution of immune genes, a high level of linkage disequilibrium (r2 > 0.8) was detected in over 27% of SNP pairs. We discuss the potential role of immune gene divergence as adaptations to the different larval habitats associated with A. gambiae taxa and as a potential force driving ecological speciation in this group of mosquitoes.

High dimensional model representation of log likelihood ratio: binary classification with SNP data

BackgroundDeveloping binary classification rules based on SNP observations has been a major challenge for many modern bioinformatics applications, e.g., predicting risk of future disease events in complex conditions such as cancer. Small-sample, high-dimensional nature of SNP data, weak effect of each SNP on the outcome, and highly non-linear SNP interactions are several key factors complicating the analysis. Additionally, SNPs take a finite number of values which may be best understood as ordinal or categorical variables, but are treated as continuous ones by many algorithms.MethodsWe use the theory of high dimensional model representation (HDMR) to build appropriate low dimensional glass-box models, allowing us to account for the effects of feature interactions. We compute the second order HDMR expansion of the log-likelihood ratio to account for the effects of single SNPs and their pairwise interactions. We propose a regression based approach, called linear approximation for block second order HDMR expansion of categorical observations (LABS-HDMR-CO), to approximate the HDMR coefficients. We show how HDMR can be used to detect pairwise SNP interactions, and propose the fixed pattern test (FPT) to identify statistically significant pairwise interactions.ResultsWe apply LABS-HDMR-CO and FPT to synthetically generated HAPGEN2 data as well as to two GWAS cancer datasets. In these examples LABS-HDMR-CO enjoys superior accuracy compared with several algorithms used for SNP classification, while also taking pairwise interactions into account. FPT declares very few significant interactions in the small sample GWAS datasets when bounding false discovery rate (FDR) by 5%, due to the large number of tests performed. On the other hand, LABS-HDMR-CO utilizes a large number of SNP pairs to improve its prediction accuracy. In the larger HAPGEN2 dataset FTP declares a larger portion of SNP pairs used by LABS-HDMR-CO as significant.ConclusionLABS-HDMR-CO and FPT are interesting methods to design prediction rules and detect pairwise feature interactions for SNP data. Reliably detecting pairwise SNP interactions and taking advantage of potential interactions to improve prediction accuracy are two different objectives addressed by these methods. While the large number of potential SNP interactions may result in low power of detection, potentially interacting SNP pairs, of which many might be false alarms, can still be used to improve prediction accuracy.

Genome-Wide Search for SNP Interactions in GWAS Data: Algorithm, Feasibility, Replication Using Schizophrenia Datasets.

In this study, we looked for potential gene-gene interaction in susceptibility to schizophrenia by an exhaustive searching for SNP–SNP interactions in 3 GWAS datasets (phs000021:phg000013, phs000021:phg000014, phs000167) using our recently published algorithm. The search space for SNP–SNP interaction was confined to 8 biologically plausible ways of interaction under dominant-dominant or recessive-recessive modes. First, we performed our search of all pair-wise combination of 729,454 SNPs after filtering by SNP genotype quality. All possible pairwise interactions of any 2 SNPs (5 × 1011) were exhausted to search for significant interaction which was defined by p-value of chi-square tests. Nine out the top 10 interactions, protein coding genes were partnered with non-coding RNA (ncRNA) which suggested a new alternative insight into interaction biology other than the frequently sought-after protein–protein interaction. Therefore, we extended to look for replication among the top 10,000 interaction SNP pairs and high proportion of concurrent genes forming the interaction pairs were found. The results indicated that an enrichment of signals over noise was present in the top 10,000 interactions. Then, replications of SNP–SNP interaction were confirmed for 14 SNPs-pairs in both replication datasets. Biological insight was highlighted by a potential binding between FHIT (protein coding gene) and LINC00969 (lncRNA) which showed a replicable interaction between their SNPs. Both of them were reported to have expression in brain. Our study represented an early attempt of exhaustive interaction analysis of GWAS data which also yield replicated interaction and new insight into understanding of genetic interaction in schizophrenia.

Further evidence for the association of GAL, GALR1and NPY1Rvariants with opioid dependence.

Aim: Heroin addiction is a chronic, relapsing disease that has genetic and environmental, including drug-induced, contributions. Stress influences the development of addictions. This study was conducted to determine if variants in stress-related genes are associated with opioid dependence (OD). Patients & methods: One hundred and twenty variants in 26 genes were analyzed in 597 Dutch subjects. Patients included 281 OD in methadone maintenance with or without heroin-assisted treatment and 316 controls. Results: Twelve SNPs in seven genes showed a nominally significant association with OD. Experiment-wise significant associations (p < 0.05) were found for three SNP pairs, through an interaction effect: NPY1R/GAL rs4691910/rs1893679, NPY1R/GAL rs4691910/rs3136541 and GALR1/GAL rs9807208/rs3136541. Conclusion: This study lends more evidence to previous reports of association of stress-related variants with heroin dependence.

Whole genome re-sequencing of sweet cherry (Prunus avium L.) yields insights into genomic diversity of a fruit species

Sweet cherries, Prunus avium L. (Rosaceae), are gaining importance due to their perenniallity and nutritional attributes beneficial for human health. Interestingly, sweet cherry cultivars exhibit a wide range of phenotypic diversity in important agronomic traits, such as flowering time and defense reactions against pathogens. In this study, whole-genome resequencing (WGRS) was employed to characterize genetic variation, population structure and allelic variants in a panel of 20 sweet cherry and one wild cherry genotypes, embodying the majority of cultivated Greek germplasm and a representative of a local wild cherry elite phenotype. The 21 genotypes were sequenced in an average depth of coverage of 33.91×. and effective mapping depth, to the genomic reference sequence of ‘Satonishiki’ cultivar, between 22.21× to 36.62×. Discriminant analysis of principal components (DAPC) with SNPs revealed two clusters of genotypes. There was a rapid linkage disequilibrium decay, as the majority of SNP pairs with r2 in near complete disequilibrium (>0.8) were found at physical distances less than 10 kb. Functional analysis of the variants showed that the genomic ratio of non-synonymous/synonymous (dN/dS) changes was 1.78. The higher dN frequency in the Greek cohort of sweet cherry could be the result of artificial selection pressure imposed by breeding, in combination with the vegetative propagation of domesticated cultivars through grafting. The majority of SNPs with high impact (e.g., stop codon gaining, frameshift), were identified in genes involved in flowering time, dormancy and defense reactions against pathogens, providing promising resources for future breeding programs. Our study has established the foundation for further large scale characterization of sweet cherry germplasm, enabling breeders to incorporate diverse germplasm and allelic variants to fine tune flowering and maturity time and disease resistance in sweet cherry cultivars.

Gene-by-gene interactions associated with the risk of conotruncal heart defects.

BackgroundThe development of conotruncal heart defects (CTDs) involves a complex relationship among genetic variants and maternal lifestyle factors. In this article, we focused on the interactions between 13 candidate genes within folate, homocysteine, and transsulfuration pathways for potential association with CTD risk.MethodsTargeted sequencing was used for 328 case‐parental triads enrolled in the National Birth Defects Prevention Study (NBDPS). To evaluate the interaction of two genes, we applied a conditional logistic regression model for all possible SNP pairs within two respective genes by contrasting the affected infants with their pseudo‐controls. The findings were replicated in an independent sample of 86 NBDPS case‐parental triads genotyped by DNA microarrays. The results of two studies were further integrated by a fixed‐effect meta‐analysis.ResultsOne SNP pair (i.e., rs4764267 and rs6556883) located in gene MGST1 and GLRX, respectively, was found to be associated with CTD risk after multiple testing adjustment using simpleM, a modified Bonferroni correction approach (nominal p‐value of 4.62e‐06; adjusted p‐value of .04). Another SNP pair (i.e., rs11892646 and rs56219526) located in gene DNMT3A and MTRR, respectively, achieved marginal significance after multiple testing adjustment (adjusted p‐value of .06).ConclusionFurther studies with larger sample sizes are needed to confirm and elucidate these potential interactions.

Genome Data Allow in silico Pharmacogenetic Studies Using the Genetic Makeup of Both the Individual Patient As Well As the Disease

Pharmacogenomics is becoming more and more important due to personalized medicine. To understand the association between the genetic background of a patient and the response to a tailored treatment would strongly influence the choice of therapy and reduce trial-and-error strategies. Various screening assays have been established, e.g. to test the impact of acquired gene mutations in cancer on the response to different agents and combinations in cell culture models. In the era of genome data, in silico analyses are becoming an interesting tool and the hope is growing to predict a patient's response to therapy by association studies using the genetic makeup of both, the individual patient as well as the disease. The aim of this study was to get insights into the genetic background of AML patients refractory to treatment and to investigate associations of polymorphisms (SNPs) in cancer treatment target genes and disease associated mutations contributing to an altered response to treatment. The cohort consisted of 247 AML patients diagnosed by cytomorphology following the WHO classification. All patients were treated intensively with a standard chemotherapy protocol such as 7+3 and response to treatment was assessed after first and second induction. Following ELN guidelines patients were grouped into responder (group 1), showing cytomorphological complete remission after first induction (n=186), and treatment failure (group 2) with only partial remission or progressive disease after second induction (n=61). Whole genome sequencing (WGS) was performed with 90x coverage for all samples at diagnosis to assess their mutational profiles as well as their germline background. In depth analyses were restricted to exonic SNPs of 217 drug target genes (DrugBank 5; Schärfe et al., 2017) associated with cancer treatments and 20 recurrently mutated genes in AML. Morphologic subtypes as well as mutation frequencies in AML genes were similar in the responder and treatment failure groups. In total 9,742 unique SNPs were found with a median of 1,603 per patient. 37% of these SNPs were found in single patients only and another 27% were found in less than 5% of the cases. SNPs and somatic variants for the addressed genes were combined into a single matrix and co-occurrences of two variants were assessed by matrix multiplication for each group. First, we were interested in group-specific co-occurrences of SNPs and somatic variants. Here we found considerably less co-occurrences in group 1 compared to group 2. All identified co-occurrences in group 1 were unique whereas 772 co-occurrences could be found in more than one patient in group 2. For group 2 a co-occurrence network was created based on recurrent combinations of somatic variants and missense germline variants (figure A). 51% of the patients from group 2 were involved in these interactions, while group 1 did not show any recurrent co-occurrences. It was interesting to note that IDH2, KMT2A-PTD, SF3B1 and TP53 recurrently co-occurred with multiple missense SNPs. Second, we addressed the association of two SNPs in the investigated drug target genes. Looking at SNPs co-occurring in at least 10% of the patients again reflected the heterogeneity of group 1, showing no recurrently co-occurring SNPs, while group 2 showed 6 SNP pairs associated with MAPK family signaling cascades (figure B). Last, it was noteworthy that multiple non-coding SNPs were found in the 3'UTR of the drug target genes. These variants showed a higher frequency in group 2 compared to group 1. SNPs in the 3'UTR region might modify mRNA - miRNA interactions by creating, abolishing, or changing the miRNA-binding sites (figure C). Recently multiple miR-SNPs have been described that were prognostic for treatment outcome, suggesting a potential as predictive biomarkers. In conclusion, WGS data allow comprehensive genome wide but also targeted association analyses. We found three different mechanisms potentially altering treatment sensitivity based on the genetic makeup of individual patients. 1) Association of somatic mutations and SNPs located in drug target genes, 2) association of two SNPs, and 3) SNPs in the 3'UTR modulating miRNA interaction. All three mechanisms occurred only in the refractory AML cases and not in the responder group. This study shows the power of genomic data and in silico analyses that are the basis for future tools to predict response to treatment for individual patients. Disclosures Meggendorfer: MLL Munich Leukemia Laboratory: Employment. Walter:MLL Munich Leukemia Laboratory: Employment. Hutter:MLL Munich Leukemia Laboratory: Employment. Baer:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

A time-dependent genome-wide SNP-SNP interaction analysis of chicken body weight

BackgroundThe important property of the quantitative traits of model organisms is time-dependent. However, the methodology for investigating the genetic interaction network over time is still lacking. Our study aims to provide insights into the mechanistic basis of epistatic interactions affecting the phenotypes of model organisms.ResultsWe performed an exhaustive genome-wide search for significant SNP-SNP interactions associated with male birds’ body weight (BW) (n = 475) at multiple time points (day of hatch (BW0) and 1, 3, 5, and 7 weeks (BW1, BW3, BW5, and BW7)). Statistical analysis detected 67, four, and two significant SNP pairs associated with BW0, BW1, and BW3, respectively, with a significance threshold at 8.67 × 10− 12 (Bonferroni-adjusted: 1%). Meanwhile, no significant SNP pairs associated with BW5 and BW7 were found. The SNP-SNP interaction networks of BW0, BW1, and BW3 were built and annotated.ConclusionsWith strong annotated information and a strict significant threshold, SNP-SNP interactions underpinned the gene-gene interactions that might occur between chromosomes or within the same chromosome. Comparing and combing the networks, the results indicated that the genetic network for chicken body weight was dynamic and time-dependent.

Linkage disequilibrium and effective population size in Gir cattle selected for yearling weight.

Linkage disequilibrium (LD) plays an important role in genomic selection and mapping of quantitative trait loci (QTL). This study investigated the pattern of LD and effective population size (Ne ) in Gir cattle selected for yearling weight. For this purpose, 173 animals with imputed genotypes (from 18 animals genotyped with the Illumina BovineHD BeadChip and 155 animals genotyped with the Bovine LDv4 panel) were analysed. The LD was evaluated at distances of 25-50kb, 50-100kb, 100-500kb and 0.5-1Mb. The Ne was estimated based on 5 past generations. The r2 values (a measure of LD) were, respectively, .35, .29, .18 and .032 for the distances evaluated. The LD estimates decreased with increasing distance of SNP pairs and LD persisted up to a distance of 100kb (r2 =.29). The Ne was greater in generations 4 and 5 (24 and 30 animals, respectively) and declined drastically after the last generation (12 animals). The results showed high levels of LD and low Ne , which were probably due to the loss of genetic variability as a consequence of the structure of the Gir population studied.

Study of whole genome linkage disequilibrium patterns of Iranian water buffalo breeds using the Axiom Buffalo Genotyping 90K Array.

Accuracy of genome-wide association studies, and the successful implementation of genomic selection depends on the level of linkage disequilibrium (LD) across the genome and also the persistence of LD phase between populations. In the present study LD between adjacent SNPs and LD decay between SNPs was calculated in three Iranian water buffalo populations. Persistence of LD phase was evaluated across these populations and effective population size (Ne) was estimated from corrected r2 information. A set of 404 individuals from three Iranian buffalo populations were genotyped with the Axiom Buffalo Genotyping 90K Array. Average r2 and |D'| between adjacent SNP pairs across all chromosomes was 0.27 and 0.66 for AZI, 0.29 and 0.68 for KHU, and 0.32 and 0.72 for MAZ. The LD between the SNPs decreased with increasing physical distance from 100Kb to 1Mb between markers, from 0.234 to 0.018 for AZI, 0.254 to 0.034 for KHU, and 0.297 to 0.119 for MAZ, respectively. These results indicate that a density of 90K SNP is sufficient for genomic analyses relying on long range LD (e.g. GWAS and genomic selection). The persistence of LD phase decreased with increasing marker distances across all the populations, but remained above 0.8 for AZI and KHU for marker distances up to 100Kb. For multi-breed genomic evaluation, the 90K SNP panel is suitable for AZI and KHU buffalo breeds. Estimated effective population sizes for AZI, KHU and MAZ were 477, 212 and 32, respectively, for recent generations. The estimated effective population sizes indicate that the MAZ is at risk and requires careful management.