Large Number Of Single Nucleotide Polymorphisms Research Articles

Insights into the structure–function relationship of missense mutations in the human TOP2A protein in ovarian cancer

Topoisomerase 2-alpha (TOP2A) is a nuclear protein that is responsible for the maintenance of the topological state of DNA. TOP2A is highly upregulated in ovarian cancer, and its copy number is an important prognosis factor. A large number of single-nucleotide polymorphism (SNP), insertion, and deletion mutations have been reported in TOP2A. Thus, a structural and functional study of missense SNPs was carried out to screen potentially damaging mutations. The 193 non-synonymous SNPs in the coding region of TOP2A in the dbSNP database were selected for in silico analysis. The deleterious SNPs were screened using sorting intolerant from tolerant (SIFT), PolyPhen-2, SNAP2, and SNPs&Go, and we obtained four possibly damaging SNPs at the end (Y481C, N7741, E922K, and R1514W). Mutants Y481C and E922K were predicted to be highly deleterious and showed decreased protein stability compared with native proteins, as predicted by I-Mutant 3. We used the SWISS-MODEL to model the structure of these two mutants, and the structural attributes of modeled mutants were studied using Hope Project, solvent accessibility-based protein–protein interface identification and recognition (SPPIDER), SRide, and HBAT, which predicted small variations from the native protein. Molecular dynamics simulation demonstrated a decrease in root mean square deviation (RMSD) and the radius of gyration of two mutants, which is relative to the native protein. The molecular docking of TOP2A with etoposide suggests that mutations may lead to resistance to TOP2A-targeted chemotherapy. In addition, the relative expression analysis performed by qRT-PCR also reveals that there is a three-fold increase in the expression levels of the TOP2A protein in ovarian adenoma cancer cell lines. Our analysis reveals that Y481C and E922K are highly damaging variants of TOP2A, which alter the protein dynamics and may be implicated in causing ovarian cancer.

Genomic Insights into Pluralibacter gergoviae Sheds Light on Emergence of a Multidrug-Resistant Species Circulating between Clinical and Environmental Settings.

Pluralibacter gergoviae is a member of the Enterobacteriaceae family that has been reported sporadically. Although P. gergoviae strains exhibiting multidrug-resistant profiles have been identified an in-depth genomic analysis focusing on antimicrobial resistance (AMR) has been lacking, and was therefore performed in this study. Forty-eight P. gergoviae strains, isolated from humans, animals, foods, and the environment during 1970-2023, were analyzed. A large number of single-nucleotide polymorphisms were found, indicating a highly diverse population. Whilst P. gergoviae strains were found to be circulating at the One Health interface, only human and environmental strains exhibited multidrug resistance genotypes. Sixty-one different antimicrobial resistance genes (ARGs) were identified, highlighting genes encoding mobile colistin resistance, carbapenemases, and extended-spectrum β-lactamases. Worryingly, the co-occurrence of mcr-9.1, blaKPC-2, blaCTX-M-9, and blaSHV-12, as well as mcr-10.1, blaNDM-5, and blaSHV-7, was detected. Plasmid sequences were identified as carrying clinically important ARGs, evidencing IncX3 plasmids harboring blaKPC-2, blaNDM-5, or blaSHV-12 genes. Virulence genotyping underlined P. gergoviae as being a low-virulence species. In this regard, P. gergoviae is emerging as a new multidrug-resistant species belonging to the Enterobacteriaceae family. Therefore, continuous epidemiological genomic surveillance of P. gergoviae is required.

Species relationships within the genus Vitis based on molecular and morphological data.

The grape genus Vitis L. includes the domesticated V. vinifera, which is one of the most important fruit crop, and also close relatives recognized as valuable germplasm resources for improving cultivars. To resolve some standing problems in the species relationships within the Vitis genus we analyzed diversity in a set of 90 accessions comprising most of Vitis species and some putative hybrids. We discovered single nucleotide polymorphisms (SNPs) in SANGER sequences of twelve loci and genotyped accessions at a larger number of SNPs using a previously developed SNP array. Our phylogenic analyses consistently identified: three clades in North America, one in East Asia, and one in Europe corresponding to V. vinifera. Using heterozygosity measurement, haplotype reconstruction and chloroplast markers, we identified the hybrids existing within and between clades. The species relationships were better assessed after discarding these hybrids from analyses. We also studied the relationships between phylogeny and morphological traits and found that several traits significantly correlated with the phylogeny. The American clade that includes important species such as V. riparia and V. rupestris showed a major divergence with all other clades based on both DNA polymorphisms and morphological traits.

Similarity and diversity of genetic architecture for complex traits between East Asian and European populations

BackgroundGenome-wide association studies have detected a large number of single-nucleotide polymorphisms (SNPs) associated with complex traits in diverse ancestral groups. However, the trans-ethnic similarity and diversity of genetic architecture is not well understood currently.ResultsBy leveraging summary statistics of 37 traits from East Asian (Nmax=254,373) or European (Nmax=693,529) populations, we first evaluated the trans-ethnic genetic correlation (ρg) and found substantial evidence of shared genetic overlap underlying these traits between the two populations, with {widehat{rho }}_{g} ranging from 0.53 (se = 0.11) for adult-onset asthma to 0.98 (se = 0.17) for hemoglobin A1c. However, 88.9% of the genetic correlation estimates were significantly less than one, indicating potential heterogeneity in genetic effect across populations. We next identified common associated SNPs using the conjunction conditional false discovery rate method and observed 21.7% of trait-associated SNPs can be identified simultaneously in both populations. Among these shared associated SNPs, 20.8% showed heterogeneous influence on traits between the two ancestral populations. Moreover, we demonstrated that population-common associated SNPs often exhibited more consistent linkage disequilibrium and allele frequency pattern across ancestral groups compared to population-specific or null ones. We also revealed population-specific associated SNPs were much likely to undergo natural selection compared to population-common associated SNPs.ConclusionsOur study provides an in-depth understanding of similarity and diversity regarding genetic architecture for complex traits across diverse populations, and can assist in trans-ethnic association analysis, genetic risk prediction, and causal variant fine mapping.

Toll-Like Receptor 4 Gene Polymorphisms and Susceptibility to Schizophrenia: A Case-Control Study

ABSTRACT Schizophrenia is a common psychiatric disorder that exhibits a variety of symptoms. The exact etiology and pathogenesis are still doubtful. However, genetic and environmental factors seem to have a role. Years ago, the role of the immune system was focused on auto-antibodies, cytokines, different types of immune cells and immune genes. The Toll-like receptors (TLR) are a cornerstone of the innate immune system, particularly TLR4. TLR4 primarily recognises gram-negative lipopolysaccharides bacteria. This case-control study, for the first time to our knowledge, examined the role of TLR4 gene polymorphisms in 142 Egyptian schizophrenic patients and 175 healthy controls. Using polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP), four single nucleotide polymorphisms (SNPs) were investigated in the TLR4 gene rs11536889, rs10759931, rs1927911, and rs1927914. The Positive and Negative Syndrome Scale (PANSS) was used in diagnosis and assessment. A statistically significant association was observed between rs11536889, rs1927911 and rs1927914, but no association was found between rs10759931. There was no association between the different SNP genotypes and PANSS, except between rs1927914 and general psychopathologic symptoms. This study shows a strong association between TLR4 rs11356889 and rs1927911 minor alleles and schizophrenia. These findings could be additional evidence for the immune system’s role in schizophrenia development. However, more studies with a more significant sample number, TLR4 protein assessment, and a larger number of SNPs are recommended.

Development of a high-throughput SNP array for sea cucumber (Apostichopus japonicus) and its application in genomic selection with MCP regularized deep neural networks

High-throughput single nucleotide polymorphism (SNP) genotyping assays are powerful tools for genetic studies and genomic breeding applications for many species. Though large numbers of SNPs have been identified in sea cucumber (Apostichopus japonicus), but, as yet, no high-throughput genotyping platform is available for this species. In this study, we designed and developed a high-throughput 24 K SNP genotyping array named HaishenSNP24K for A. japonicus, based on the multi-objective-local optimization (MOLO) algorithm and HD-Marker genotyping method. The SNP array exhibited a relatively high genotyping call rate (> 96%), genotyping accuracy (>95%) and exhibited highly polymorphic in sea cucumber populations. In addition, we also assessed its application in genomic selection (GS). Deep neural networks (DNN) that can capture the complicated interactions of genes have been proposed as a promising tool in GS for SNP-based genomic prediction of complex traits in animal breeding. To overcome the problem of over-fitting when using the HaishenSNP24K array as high-dimensional DNN input, we developed minmax concave penalty (MCP) regularization for sparse deep neural networks (DNN-MCP) that finds an optimal sparse structure of a DNN by minimizing the square error subject to the non-convex penalty MCP on the parameters (weights and biases). Compared to two linear models, namely RR-GBLUP and Bayes B, and the nonlinear model DNN, DNN-MCP has greatly improved the genomic prediction ability for three quantitative traits (e.g., wet weight, dry weight and survival time) in the sea cucumber population. To the best of our knowledge, this is the first work to develop a high-throughput SNP array for A. japonicus and a new model DNN-MCP for genomic prediction of complex traits in GS. The present results provide evidence that supports the HaishenSNP24K array with DNN-MCP will be valuable for genetic studies and molecular breeding in A. japonicus.

Contribution of 3D genome topological domains to genetic risk of cancers: a genome-wide computational study

BackgroundGenome-wide association studies have identified statistical associations between various diseases, including cancers, and a large number of single-nucleotide polymorphisms (SNPs). However, they provide no direct explanation of the mechanisms underlying the association. Based on the recent discovery that changes in three-dimensional genome organization may have functional consequences on gene regulation favoring diseases, we investigated systematically the genome-wide distribution of disease-associated SNPs with respect to a specific feature of 3D genome organization: topologically associating domains (TADs) and their borders.ResultsFor each of 449 diseases, we tested whether the associated SNPs are present in TAD borders more often than observed by chance, where chance (i.e., the null model in statistical terms) corresponds to the same number of pointwise loci drawn at random either in the entire genome, or in the entire set of disease-associated SNPs listed in the GWAS catalog. Our analysis shows that a fraction of diseases displays such a preferential localization of their risk loci. Moreover, cancers are relatively more frequent among these diseases, and this predominance is generally enhanced when considering only intergenic SNPs. The structure of SNP-based diseasome networks confirms that localization of risk loci in TAD borders differs between cancers and non-cancer diseases. Furthermore, different TAD border enrichments are observed in embryonic stem cells and differentiated cells, consistent with changes in topological domains along embryogenesis and delineating their contribution to disease risk.ConclusionsOur results suggest that, for certain diseases, part of the genetic risk lies in a local genetic variation affecting the genome partitioning in topologically insulated domains. Investigating this possible contribution to genetic risk is particularly relevant in cancers. This study thus opens a way of interpreting genome-wide association studies, by distinguishing two types of disease-associated SNPs: one with an effect on an individual gene, the other acting in interplay with 3D genome organization.

Genome-Wide Variation Analysis of Four Vegetable Soybean Cultivars Based on Re-Sequencing.

Vegetable soybean is a type of value-added specialty soybean, served as a fresh vegetable or snack in China. Due to the difference from other types, it is important to understand the genetic structure and diversity of vegetable soybean for further utilization in breeding programs. The four vegetable cultivars, Taiwan-75, Zhexiandou No. 8, Zhexian No. 9 and Zhexian No. 10 are popular soybean varieties planted in Zhejiang province, and have large pods and intermediate maturity. The clustering showed a close relationship of these four cultivars in simple sequence repeat analysis. To reveal the genome variation of vegetable soybean, these four improved lines were analyzed by whole-genome re-sequencing. The average sequencing depth was 7X and the coverage ratio of each cultivar was at least more than 94%. Compared with the reference genome, a large number of single-nucleotide polymorphisms, insertion/deletions and structure variations were identified with different chromosome distributions. The average heterozygosity rate of the single-nucleotide polymorphisms was 11.99% of these four cultivars. According to the enrichment analysis, there were 23,371 genes identified with putative modifications, and a total of 282 genes were related to carbohydrate metabolic processes. These results provide useful information for genetic research and future breeding, which can facilitate the selection procedures in vegetable soybean breeding.

A Multi-Marker Test for Analyzing Paired Genetic Data in Transplantation.

Emerging evidence suggests that donor/recipient matching in non-HLA (human leukocyte antigen) regions of the genome may impact transplant outcomes and recognizing these matching effects may increase the power of transplant genetics studies. Most available matching scores account for either single-nucleotide polymorphism (SNP) matching only or sum these SNP matching scores across multiple gene-coding regions, which makes it challenging to interpret the association findings. We propose a multi-marker Joint Score Test (JST) to jointly test for association between recipient genotype SNP effects and a gene-based matching score with transplant outcomes. This method utilizes Eigen decomposition as a dimension reduction technique to potentially increase statistical power by decreasing the degrees of freedom for the test. In addition, JST allows for the matching effect and the recipient genotype effect to follow different biological mechanisms, which is not the case for other multi-marker methods. Extensive simulation studies show that JST is competitive when compared with existing methods, such as the sequence kernel association test (SKAT), especially under scenarios where associated SNPs are in low linkage disequilibrium with non-associated SNPs or in gene regions containing a large number of SNPs. Applying the method to paired donor/recipient genetic data from kidney transplant studies yields various gene regions that are potentially associated with incidence of acute rejection after transplant.

Development of a minimal KASP marker panel for distinguishing genotypes in apple collections.

Accurate identification of named accessions in germplasm collections is extremely important, especially for vegetatively propagated crops which are expensive to maintain. Thus, an inexpensive, reliable, and rapid genotyping method is essential because it avoids the need for laborious and time-consuming morphological comparisons. Single Nucleotide Polymorphism (SNP) marker panels containing large numbers of SNPs have been developed for many crop species, but such panels are much too large for basic cultivar identification. Here, we have identified a minimum set of SNP markers sufficient to distinguish apple cultivars held in the English and Welsh national collections providing a cheaper and automatable alternative to the markers currently used by the community. We show that SNP genotyping with a small set of well selected markers is equally efficient as microsatellites for the identification of apple cultivars and has the added advantage of automation and reduced cost when screening large numbers of samples.

Differential mitochondrial genome in patients with Rheumatoid Arthritis

Background Mitochondria play an important role in cell survival, function and lineage differentiation. Changes in mitochondrial DNA (mtDNA) may control mitochondrial functions and thus may impart an alternative cellular state thereby leading to a disease condition in the body. Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease wherein immune cells become self-reactive causing joint inflammation, swelling and pain in patients. The changes in mtDNA may alter cellular functions thereby directing the immune cells towards an inflammatory phenotype in RA. Therefore, it becomes pertinent to identify changes in mtDNA sequence in immune cells of RA patients to understand the pathogenesis and progression of RA. Methods mtDNA from peripheral blood mono-nuclear cells (PBMCs) of 23 RA patients and 17 healthy controls (HCs) were sequenced using next-generation sequencing (NGS). Further, single nucleotide polymorphisms (SNPs) and other variable changes in mtDNA hypervariable and coding regions, amino acid changes with a putative impact on disease, levels of heteroplasmy, copy number variations and haplogroup analysis in RA patients and HCs were analysed and compared to identify any association of mtDNA changes and RA disease. Results A total of 382 single nucleotide mtDNA variants were observed, 91 (23.82%) were present in hypervariable region and 291 (76.18%) in coding region of patients and HC. The variant 513 GCA > ACA, with G present in HVR-III, known to control the mitochondrial translation function, was significantly present in RA patients. The CYTB gene had larger number of SNPs in HC samples while RNR2 was more variable in RA patients. A non-synonymous heteroplasmy in ND1 gene was found at a single nucleotide position 3533 in an increased number of RA patients as compared to the controls. A significant increase in mtDNA duplication and a higher frequency of the haplogroup U was also characteristic of RA. Also, the presence of SNPs in mitochondrial tRNA genes at two positions 12308 A > G and 15924 A > G were found to be pathogenic. Conclusion We herein observed an altered mtDNA sequence in immune cells of RA patients and thus a possible role of mitochondrial genome in the development of RA. The observed nucleotide changes in mtDNA control region, RNR2 gene, increased heteroplasmy and mtDNA duplication in RA patients may alter sites for transcription factor binding thereby influencing mtDNA gene expression, as well as copy numbers thereby affecting the mitochondrial proteins and their functions. These changes in mtDNA could be one of the probable reasons among many leading to the progression of RA.

Achieving GWAS with homomorphic encryption

BackgroundOne way of investigating how genes affect human traits would be with a genome-wide association study (GWAS). Genetic markers, known as single-nucleotide polymorphism (SNP), are used in GWAS. This raises privacy and security concerns as these genetic markers can be used to identify individuals uniquely. This problem is further exacerbated by a large number of SNPs needed, which produce reliable results at a higher risk of compromising the privacy of participants.MethodsWe describe a method using homomorphic encryption (HE) to perform GWAS in a secure and private setting. This work is based on a proposed algorithm. Our solution mainly involves homomorphically encrypted matrix operations and suitable approximations that adapts the semi-parallel GWAS algorithm for HE. We leverage upon the complex space of the CKKS encryption scheme to increase the number of SNPs that can be packed within a ciphertext. We have also developed a cache module that manages ciphertexts, reducing the memory footprint.ResultsWe have implemented our solution over two HE open source libraries, HEAAN and SEAL. Our best implementation took 24.70 minutes for a dataset with 245 samples, over 4 covariates and 10643 SNPs.ConclusionsWe demonstrate that it is possible to achieve GWAS with homomorphic encryption with suitable approximations.

Novel Sulfolobus Fuselloviruses with Extensive Genomic Variations.

Fuselloviruses are among the most widespread and best-characterized archaeal viruses. They exhibit remarkable diversity, as the list of members of this family is rapidly growing. However, it has yet to be shown how a fuselloviral genome may undergo variation at the levels of both single nucleotides and sequence stretches. Here, we report the isolation and characterization of four novel spindle-shaped viruses, named Sulfolobus spindle-shaped viruses 19 to 22 (SSV19-22), from a hot spring in the Philippines. SSV19 is a member of the genus Alphafusellovirus, whereas SSV20-22 belong to the genus Betafusellovirus The genomes of SSV20-SSV22 are identical except for the presence of two large variable regions, as well as numerous sites of single-nucleotide polymorphisms (SNPs) unevenly distributed throughout the genomes and enriched in certain regions, including the gene encoding the putative end filament protein VP4. We show that coinfection of the host with SSV20 and SSV22 led to the formation of an SSV21-like virus, presumably through homologous recombination. In addition, large numbers of SNPs were identified in DNA sequences retrieved by PCR amplification targeting the SSV20-22 vp4 gene from the original enrichment culture, indicating the enormous diversity of SSV20-22-like viruses in the environment. The high variability of VP4 is consistent with its potential role in host recognition and binding by the virus.IMPORTANCE How a virus survives in the arms race with its host is an intriguing question. In this study, we isolated and characterized four novel fuselloviruses, named Sulfolobus spindle-shaped viruses 19 to 22 (SSV19-22). Interestingly, SSV20-22 differ primarily in two genomic regions and are apparently convertible through homologous recombination during coinfection. Moreover, sites of single-nucleotide polymorphism (SNP) were identified throughout the genomes of SSV20-22 and, notably, enriched in certain regions, including the gene encoding the putative end filament protein VP4, which is believed to be involved in host recognition and binding by the virus.

The Use of SNP Genotyping for QTL/ Candidate Gene Discovery in Plants

Many plant species have been sequenced, which has enabled the identification of genetic variation such as novel single-nucleotide polymorphisms (SNPs). SNP-based genotyping technologies have been developed over the last decade and play important roles in detecting SNPs in a cost and time effective manner, thereby facilitating plant genetic and genomic studies. The availability of genome and genetics resources and increase in sequencing data has led to SNPs discovery and array development using various approaches in many plant species. The development of SNP arrays for genotyping requires three steps: identification of a large number of SNPs, validation, and final selection. The discovery of SNPs and array development at various densities have been successfully developed and utilized in many diploid and polyploid plant species. SNP genotyping arrays have been useful for many applications such as cloning, association mapping, analyses of species diversity, evolution, genomic selection, and comparative genomics. The assaying of large segregating or mutant populations with an SNP array allows the accurate, efficient, and rapid determination of the genotypes of many individuals and genetic variations. Genotyping assays are an efficient way of generating a vast amount of genotypic data in crop species to produce highly informative SNPs for marker-assisted selection in breeding programs as well as functional genomic studies. This review highlights the SNP genotyping in the application of identification of SNPs in the discovery of quantitative trait locus (QTL) or candidate genes for important crop traits and dissection of other complex traits.

SMaSH: Sample matching using SNPs in humans

BackgroundInadvertent sample swaps are a real threat to data quality in any medium to large scale omics studies. While matches between samples from the same individual can in principle be identified from a few well characterized single nucleotide polymorphisms (SNPs), omics data types often only provide low to moderate coverage, thus requiring integration of evidence from a large number of SNPs to determine if two samples derive from the same individual or not.MethodsWe select about six thousand SNPs in the human genome and develop a Bayesian framework that is able to robustly identify sample matches between next generation sequencing data sets.ResultsWe validate our approach on a variety of data sets. Most importantly, we show that our approach can establish identity between different omics data types such as Exome, RNA-Seq, and MethylCap-Seq. We demonstrate how identity detection degrades with sample quality and read coverage, but show that twenty million reads of a fairly low quality RNA-Seq sample are still sufficient for reliable sample identification.ConclusionOur tool, SMASH, is able to identify sample mismatches in next generation sequencing data sets between different sequencing modalities and for low quality sequencing data.

397 Uncovering causative, noncoding genetic variants in cutaneous diseases

Noncoding regions of the human genome are frequently and strongly linked with genetically complex human diseases by genome wide association studies (GWAS). These regions are thought to harbor single nucleotide polymorphisms (SNPs) with gene regulatory (enhancer or repressor) activity that modulate expression of disease mediating genes. Given the large number of SNPs in a linked genomic region, identification of causative variants has been hampered by a lack of methods to rapidly measure the gene regulatory function of numerous SNPs at once. Here we apply a combination of epigenomic filtering and a massively parallel reporter assay (MPRA) to identify causative, noncoding SNPs underlying several cutaneous diseases. Integrating published GWAS data from 8 polygenic skin diseases, including cutaneous cancers and inflammatory diseases with epigenetic profiling of human primary keratinocytes (ATAC-Seq and ChIP-Seq) identified numerous candidate disease-linked SNPs in regions of transcriptionally active chromatin. To functionally characterize the filtered SNPs, we measured allele-specific gene regulatory activity using MPRA – a multiplexed, next-gen sequencing method based on the canonical luciferase-based reporter assay. We performed MPRA with 516 SNP pairs using primary human keratinocytes in distinct states of differentiation and identified disease-linked SNPs with allele- and differentiation state-specific gene regulatory activity. We further linked active SNPs to putative disease-mediating target genes using the GTEx eQTL database and chromatin looping analysis (Hi-ChIP) in primary human keratinocytes. Our results not only help further mechanistic studies for understanding the basis of cutaneous disorders, but also provide a framework for identifying causative, noncoding SNPs in complex genetic diseases.

Identification of QTLs for Blast, Bacterial Blight, and Planthopper Resistance Using SNP-Based Linkage Maps from Two Recombinant Inbred Rice Lines

Rice is the most significant global food security. Several biotic factors limit rice production, breeding biotic-resistant rice has, therefore, become an increasingly important goal. Two elite rice lines, IR71033-121-15 (IR71033) and IR57514-PMI-5-B-1-2 (IR57514), provide potential genes for biotic stress resistance traits. In this study, genotyping by sequencing (GBS) for single nucleotide polymorphism (SNP)-based linkage map construction was used to detect quantitative trait loci (QTLs) for blast (BL), bacterial blight (BB), whitebacked planthopper (WBPH), and brown planthopper (BPH) resistance. IR71033 was derived from Oryza minuta and carried BL, BB, WBPH, and BPH resistance QTLs. IR57514 is a well-adapted rainfed lowland line that carries BL and BB resistance QTLs. Two sets of recombinant inbred line (RIL) populations derived from crosses of KDML105 × IR71033 and KDML105 × IR57514 were used to dissect the genetic basis of disease and insect pest resistance. The RIL populations were evaluated for BL, BB, WBPH, and BPH resistance from 2016 to 2018 at four rice research centers in Thailand. From these, we identified a large number of SNPs through GBS and constructed high-resolution linkage maps. By combining phenotypic evaluation with the GBS data, a total of 24 QTLs on four chromosomes were detected that confered pest resistance and explained 7.3% - 61.4% of the phenotypic variance. These findings should facilitate identifying novel resistance genes and applying marker-assisted selection for resistance to the four major rice pests investigated here. These strategies will improve the resilience and reliability of rice varieties adapted to the low-yielding environment of rainfed lowland areas worldwide.

HSP90 as a global genetic modifier for male genital morphology inDrosophila melanogaster

The molecular chaperone protein HSP90 has been proposed to modulate genotype-phenotype relationship in a broad range of organisms. We explore the proposed genetic modifier effect of HSP90 through a genomewide analysis. Here, we show that HSP90 functions as a genetic modifier of genital morphology in Drosophila melanogaster. We identified a large number of single-nucleotide polymorphisms (SNPs) with an HSP90-dependent effect by using genome wide association analysis. We classified the SNPs into the ones under capacitance effect (smaller allelic effect under HSP90 inhibition) or the ones under potentiation effect (larger allelic effect under HSP90 inhibition). Although the majority of SNPs are under capacitance, there are a large number of SNPs under potentiation. This observation provides support for a model in which Hsp90 is not described exclusively as a "genetic capacitor," but is described more broadly as a "genetic modifier." Because the majority of the candidate genes estimated from SNPs with an HSP90-dependent effect in the current study has never been reported to interact with HSP90 directly, the global genetic modifier effect of HSP90 may be exhibited through epistatic interactions in gene regulatory networks.

PRS-on-Spark (PRSoS): a novel, efficient and flexible approach for generating polygenic risk scores

BackgroundPolygenic risk scores (PRS) describe the genomic contribution to complex phenotypes and consistently account for a larger proportion of variance in outcome than single nucleotide polymorphisms (SNPs) alone. However, there is little consensus on the optimal data input for generating PRS, and existing approaches largely preclude the use of imputed posterior probabilities and strand-ambiguous SNPs i.e., A/T or C/G polymorphisms. Our ability to predict complex traits that arise from the additive effects of a large number of SNPs would likely benefit from a more inclusive approach.ResultsWe developed PRS-on-Spark (PRSoS), a software implemented in Apache Spark and Python that accommodates different data inputs and strand-ambiguous SNPs to calculate PRS. We compared performance between PRSoS and an existing software (PRSice v1.25) for generating PRS for major depressive disorder using a community cohort (N = 264). We found PRSoS to perform faster than PRSice v1.25 when PRS were generated for a large number of SNPs (~ 17 million SNPs; t = 42.865, p = 5.43E-04). We also show that the use of imputed posterior probabilities and the inclusion of strand-ambiguous SNPs increase the proportion of variance explained by a PRS for major depressive disorder (from 4.3% to 4.8%).ConclusionsPRSoS provides the user with the ability to generate PRS using an inclusive and efficient approach that considers a larger number of SNPs than conventional approaches. We show that a PRS for major depressive disorder that includes strand-ambiguous SNPs, calculated using PRSoS, accounts for the largest proportion of variance in symptoms of depression in a community cohort, demonstrating the utility of this approach. The availability of this software will help users develop more informative PRS for a variety of complex phenotypes.

Abstract PL04-02: Pharmacogenomics of chemotherapeutic-induced toxicities: Challenges and opportunities

Abstract PL04-02: Pharmacogenomics of chemotherapeutic-induced toxicities: Challenges and opportunities