Number Of Single Nucleotide Polymorphisms Research Articles

Identification of the anti-mycobacterial functional properties of piperidinol derivatives.

Background and PurposeTuberculosis (TB) remains a major global health threat and is now the leading cause of death from a single infectious agent worldwide. The current TB drug regimen is inadequate, and new anti‐tubercular agents are urgently required to be able to successfully combat the increasing prevalence of drug‐resistant TB. The purpose of this study was to investigate a piperidinol compound derivative that is highly active against the Mycobacterium tuberculosis bacillus.Experimental ApproachThe antibacterial properties of the piperidinol compound and its corresponding bis‐Mannich base analogue were evaluated against M. smegmatis and Gram‐negative organisms. Cytotoxicity studies were undertaken in order to determine the selectivity index for these compounds. Spontaneous resistant mutants of M. smegmatis were generated against the piperidinol and corresponding bis‐Mannich base lead derivatives and whole genome sequencing employed to determine the genetic modifications that lead to selection pressure in the presence of these compounds.Key ResultsThe piperidinol and the bis‐Mannich base analogue were found to be selective for mycobacteria and rapidly kill this organism with a cytotoxicity selectivity index for mycobacteria of >30‐fold. Whole genome sequencing of M. smegmatis strains resistant to the lead compounds led to the identification of a number of single nucleotide polymorphisms indicating multiple targets.Conclusion and ImplicationsOur results indicate that the piperidinol moiety represents an attractive compound class in the pursuit of novel anti‐tubercular agents.Linked ArticlesThis article is part of a themed section on Drug Metabolism and Antibiotic Resistance in Micro‐organisms. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.14/issuetoc

Late Onset Alzheimer’s Disease Risk Variants in Cognitive Decline: The PATH Through Life Study

Recent genome wide association studies have identified a number of single nucleotide polymorphisms associated with late onset Alzheimer's disease (LOAD). We examined the associations of 24 LOAD risk loci, individually and collectively as a genetic risk score, with cognitive function. We used data from 1,626 non-demented older Australians of European ancestry who were examined up to four times over 12 years on tests assessing episodic memory, working memory, vocabulary, and information processing speed. Linear mixed models were generated to examine associations between genetic factors and cognitive performance. Twelve SNPs were significantly associated with baseline cognitive performance (ABCA7, MS4A4E, SORL1), linear rate of change (APOE, ABCA7, INPP5D, ZCWPW1, CELF1), or quadratic rate of change (APOE, CLU, EPHA1, HLA-DRB5, INPP5D, FERMT2). In addition, a weighted genetic risk score was associated with linear rate of change in episodic memory and information processing speed. Our results suggest that a minority of AD related SNPs may be associated with non-clinical cognitive decline. Further research is required to verify these results and to examine the effect of preclinical AD in genetic association studies of cognitive decline. The identification of LOAD risk loci associated with non-clinical cognitive performance may help in screening for individuals at greater risk of cognitive decline.

Comparative transcriptome analysis of berry-sizing effects of gibberellin (GA3) on seedless Vitis vinifera L.

Gibberellin (GA) is widely used to enlarge berries of seedless table grape and raisin varieties. The molecular mechanism underlying the berry-sizing effect of gibberelins is however poorly understood. We used a high-throughput deep sequencing technology to investigate the transcriptome and comparative expression profiles of berries from Vitis vinifera L. ‘Summer Black’ treated with GA3 with the aim of increasing the understanding of molecular mechanisms underlying the species’ expansion growth responses to exogenous GA3 hormone application. A total of 591 differentially expressed genes (DEGs) were detected including genes involved in fruit expansion and growth. There were four expansion genes, three cellulose synthase A catalytic subunit genes, four cellulose synthase-like protein genes and three xyloglucan endotransglucosylase genes. Differential expression of these genes could potentially explain the difference in the growth and sizes of fruits from control (CK) and GA3 treated (+GA) vines. In addition, the expression patterns of 14 DEGs were validated by qRT-PCR, and the outcomes agreed highly with the RNA-Seq results. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed to better understand the functions of these DEGs. We also identified a large number of single nucleotide polymorphism and insertion/deletion markers, which will be a rich resource for future marker development and breeding research in grape. The transcriptome analysis provides valuable information for furthering our understanding of the molecular mechanisms that regulate the fruit expansion growth, and adds to the growing foundation for future genetic and functional genomic studies in grape fruit.

Homozygosity for the WRN Helicase-Inactivating Variant, R834C, does not confer a Werner syndrome clinical phenotype

Loss-of-function mutations in the WRN helicase gene cause Werner syndrome- a progeroid syndrome with an elevated risk of cancer and other age-associated diseases. Large numbers of single nucleotide polymorphisms have been identified in WRN. We report here the organismal, cellular, and molecular phenotypes of variant rs3087425 (c. 2500C > T) that results in an arginine to cysteine substitution at residue 834 (R834C) and up to 90% reduction of WRN helicase activity. This variant is present at a high (5%) frequency in Mexico, where we identified 153 heterozygous and three homozygous individuals among 3,130 genotyped subjects. Family studies of probands identified ten additional TT homozygotes. Biochemical analysis of WRN protein purified from TT lymphoblast cell lines confirmed that the R834C substitution strongly and selectively reduces WRN helicase, but not exonuclease activity. Replication track analyses showed reduced replication fork progression in some homozygous cells following DNA replication stress. Among the thirteen TT homozygotes, we identified a previously unreported and statistically significant gender bias in favor of males (p = 0.0016), but none of the clinical findings associated with Werner syndrome. Our results indicate that WRN helicase activity alone is not rate-limiting for the development of clinical WS.

Assessing the numbers of SNPs needed to establish molecular IDs and characterize the genetic diversity of soybean cultivars derived from Tokachi nagaha

The development of a core set of SNP molecular markers that could be widely used in soybean genetic research would greatly facilitate research into the genetic diversity of soybean. We conducted an analysis of Tokachi nagaha and 137 of its descendant soybean cultivars using 4044 SNP markers with the goal of determining the appropriate number of single-nucleotide polymorphisms (SNPs) needed to construct unambiguous molecular IDs and characterize genetic diversity based on a genetic distance matrix correlation method. When the number of SNPs was held constant, the number of accession pairs that could be distinguished increased as the polymorphism informative content (PIC) value of the SNPs increased. A core panel of 20 selected SNPs from 11 linkage groups with a mean PIC value of 0.3703 and a range of 0.3640–0.3749 was able to identify almost all of the accession pairs in our study [9445 pairs (99.92%)]. The eight accession pairs that could not be identified with this core SNP set all originated from the same province and some of them had the same parental cultivars. The molecular IDs of the 138 accessions were constructed using the core 20 SNPs. It is known that both the number of SNPs and PIC values should be considered when SNPs are selected for use in the analysis of genetic diversity. In this study, when the PIC value was 0.3460, the correlation coefficient between the genetic distance matrices associated with a panel of 200 SNPs and the total population was >0.800, indicating satisfactory correlation. Our high-accuracy, high-resolution core SNP panel for germplasm fingerprinting and our findings about assessing genetic diversity will likely markedly improve the management and utilization efficiency of soybean germplasm resources.

Application of high-throughput sequencing to whole rabies viral genome characterisation and its use for phylogenetic re-evaluation of a raccoon strain incursion into the province of Ontario

Raccoon rabies remains a serious public health problem throughout much of the eastern seaboard of North America due to the urban nature of the reservoir host and the many challenges inherent in multi-jurisdictional efforts to administer co-ordinated and comprehensive wildlife rabies control programmes. Better understanding of the mechanisms of spread of rabies virus can play a significant role in guiding such control efforts. To facilitate a detailed molecular epidemiological study of raccoon rabies virus movements across eastern North America, we developed a methodology to efficiently determine whole genome sequences of hundreds of viral samples. The workflow combines the generation of a limited number of overlapping amplicons covering the complete viral genome and use of high throughput sequencing technology. The value of this approach is demonstrated through a retrospective phylogenetic analysis of an outbreak of raccoon rabies which occurred in the province of Ontario between 1999 and 2005. As demonstrated by the number of single nucleotide polymorphisms detected, whole genome sequence data were far more effective than single gene sequences in discriminating between samples and this facilitated the generation of more robust and informative phylogenies that yielded insights into the spatio-temporal pattern of viral spread. With minor modification this approach could be applied to other rabies virus variants thereby facilitating greatly improved phylogenetic inference and thus better understanding of the spread of this serious zoonotic disease. Such information will inform the most appropriate strategies for rabies control in wildlife reservoirs.

Indel-seq: a fast-forward genetics approach for identification of trait-associated putative candidate genomic regions and its application in pigeonpea (Cajanus cajan).

Identification of candidate genomic regions associated with target traits using conventional mapping methods is challenging and time‐consuming. In recent years, a number of single nucleotide polymorphism (SNP)‐based mapping approaches have been developed and used for identification of candidate/putative genomic regions. However, in the majority of these studies, insertion–deletion (Indel) were largely ignored. For efficient use of Indels in mapping target traits, we propose Indel‐seq approach, which is a combination of whole‐genome resequencing (WGRS) and bulked segregant analysis (BSA) and relies on the Indel frequencies in extreme bulks. Deployment of Indel‐seq approach for identification of candidate genomic regions associated with fusarium wilt (FW) and sterility mosaic disease (SMD) resistance in pigeonpea has identified 16 Indels affecting 26 putative candidate genes. Of these 26 affected putative candidate genes, 24 genes showed effect in the upstream/downstream of the genic region and two genes showed effect in the genes. Validation of these 16 candidate Indels in other FW‐ and SMD‐resistant and FW‐ and SMD‐susceptible genotypes revealed a significant association of five Indels (three for FW and two for SMD resistance). Comparative analysis of Indel‐seq with other genetic mapping approaches highlighted the importance of the approach in identification of significant genomic regions associated with target traits. Therefore, the Indel‐seq approach can be used for quick and precise identification of candidate genomic regions for any target traits in any crop species.

Iterative sure independence screening EM-Bayesian LASSO algorithm for multi-locus genome-wide association studies.

Genome-wide association study (GWAS) entails examining a large number of single nucleotide polymorphisms (SNPs) in a limited sample with hundreds of individuals, implying a variable selection problem in the high dimensional dataset. Although many single-locus GWAS approaches under polygenic background and population structure controls have been widely used, some significant loci fail to be detected. In this study, we used an iterative modified-sure independence screening (ISIS) approach in reducing the number of SNPs to a moderate size. Expectation-Maximization (EM)-Bayesian least absolute shrinkage and selection operator (BLASSO) was used to estimate all the selected SNP effects for true quantitative trait nucleotide (QTN) detection. This method is referred to as ISIS EM-BLASSO algorithm. Monte Carlo simulation studies validated the new method, which has the highest empirical power in QTN detection and the highest accuracy in QTN effect estimation, and it is the fastest, as compared with efficient mixed-model association (EMMA), smoothly clipped absolute deviation (SCAD), fixed and random model circulating probability unification (FarmCPU), and multi-locus random-SNP-effect mixed linear model (mrMLM). To further demonstrate the new method, six flowering time traits in Arabidopsis thaliana were re-analyzed by four methods (New method, EMMA, FarmCPU, and mrMLM). As a result, the new method identified most previously reported genes. Therefore, the new method is a good alternative for multi-locus GWAS.

Collective Genetic Interaction Effects and the Role of Antigen-Presenting Cells in Autoimmune Diseases.

Autoimmune diseases occur when immune cells fail to develop or lose their tolerance toward self and destroy body’s own tissues. Both insufficient negative selection of self-reactive T cells and impaired development of regulatory T cells preventing effector cell activation are believed to contribute to autoimmunity. Genetic predispositions center around the major histocompatibility complex (MHC) class II loci involved in antigen presentation, the key determinant of CD4+ T cell activation. Recent studies suggested that variants in the MHC region also exhibit significant non-additive interaction effects. However, collective interactions involving large numbers of single nucleotide polymorphisms (SNPs) contributing to such effects are yet to be characterized. In addition, relatively little is known about the cell-type-specificity of such interactions in the context of cellular pathways. Here, we analyzed type 1 diabetes (T1D) and rheumatoid arthritis (RA) genome-wide association data sets via large-scale, high-performance computations and inferred collective interaction effects involving MHC SNPs using the discrete discriminant analysis. Despite considerable differences in the details of SNP interactions in T1D and RA data, the enrichment pattern of interacting pairs in reference epigenomes was remarkably similar: statistically significant interactions were epigenetically active in cell-type combinations connecting B cells to T cells and intestinal epithelial cells, with both helper and regulatory T cells showing strong disease-associated interactions with B cells. Our results provide direct genetic evidence pointing to the important roles B cells play as antigen-presenting cells toward CD4+ T cells in the context of central and peripheral tolerance. In addition, they are consistent with recent experimental studies suggesting that the repertoire of B cell-specific self-antigens in the thymus are critical to the effective control of corresponding autoimmune activation in peripheral tissues.

Effect of ageing and single nucleotide polymorphisms associated with the risk of aggressive prostate cancer in a New Zealand population.

Prostate cancer is one of the most significant male health concerns worldwide, and various researchers carrying out molecular diagnostics have indicated that genetic interactions with biological and behavioral factors play an important role in the overall risk and prognosis of this disease. Single nucleotide polymorphisms are increasingly becoming strong biomarker candidates to identify the susceptibility of individuals to prostate cancer. We carried out risk association of different stages of prostate cancer to a number of single nucleotide polymorphisms to identify the susceptible alleles in a New Zealand population and checked the interaction with environmental factors as well. We identified a number of single nucleotide polymorphisms to have associations specifically to the risk of prostate cancer and aggressiveness of the disease, and also certain single nucleotide polymorphisms to be vulnerable to the reported behavioral factors. We have addressed "special" environmental conditions prevalent in New Zealand, which can be used as a model for a bigger worldwide study.

Genomic differentiation between Asturiana de los Valles, Avileña-Negra Ibérica, Bruna dels Pirineus, Morucha, Pirenaica, Retinta and Rubia Gallega cattle breeds

The Spanish local beef cattle breeds have most likely common origin followed by a process of differentiation. This particular historical evolution has most probably left detectable signatures in the genome. The objective of this study was to identify genomic regions associated with differentiation processes in seven Spanish autochthonous populations (Asturiana de los Valles (AV), Avileña-Negra Ibérica (ANI), Bruna dels Pirineus (BP), Morucha (Mo), Pirenaica (Pi), Retinta (Re) and Rubia Gallega (RG)). The BovineHD 777K BeadChip was used on 342 individuals (AV, n=50; ANI, n=48; BP, n=50; Mo, n=50; Pi, n=48; Re, n=48; RG, n=48) chosen to be as unrelated as possible. We calculated the fixation index (FST) and performed a Bayesian analysis named SelEstim. The output of both procedures was very similar, although the Bayesian analysis provided a richer inference and allowed us to calculate significance thresholds by generating a pseudo-observed data set from the estimated posterior distributions. We identified a very large number of genomic regions, but when a very restrictive significance threshold was applied these regions were reduced to only 10. Among them, four regions can be highlighted because they comprised a large number of single nucleotide polymorphisms and showed extremely high signals (Kullback–Leiber divergence (KLD)>6). They are located in BTA 2 (5 575 950 to 10 152 228 base pairs (bp)), BTA 5 (17 596 734 to 18 850 702 bp), BTA 6 (37 853 912 to 39 441 548 bp) and BTA 18 (13 345 515 to 15 243 838 bp) and harbor, among others, the MSTN (Myostatin), KIT-LG (KIT Ligand), LAP3 (leucine aminopeptidase 3), NAPCG (non-SMC condensing I complex, subunit G), LCORL (ligand dependent nuclear receptor corepressor-like) and MC1R (Melanocortin 1 receptor) genes. Knowledge on these genomic regions allows to identify potential targets of recent selection and helps to define potential candidate genes associated with traits of interest, such as coat color, muscle development, fertility, growth, carcass and immunological response.

The association between rs1972820 and the risk of breast cancer in Isfahan population

A number of single nucleotide polymorphisms (SNPs) in ERBB4 gene have been linked to increase the risk of breast cancer. However, no study has been dedicated to analyze the significance of microRNA-related SNP rs1972820, located in ERBB4 3'-untranslated region (UTR), in breast tumors. Here, we investigated the frequency and association between rs1972820 and breast cancer. The rs1972820 genotypes in 182 samples were collected from 96 healthy people, and 86 breast cancer patients were determined using tetra-primer amplification refractory mutation system-polymerase chain reaction. The frequency of genotypes was analyzed to find the association between rs1972820 and breast cancer risk. Conditional logistic regression, odds ratios (ORs), the associated 95% confidence intervals (CIs), and Armitage's test were used in this study. In silico analysis suggested that rs1972820 located in the 3'UTR of ERBB4 gene affects the binding affinity of miR-3144-3p a potential oncomiRNA. Statistical analysis showed a significant association between SNP rs1972820 G allele and reduced breast cancer risk, odds ratio = 0.443 (95% CI: 0.196-0.998). rs1972820 SNP allele is significantly associated with the reduced risk of breast cancer and could be considered as a potential marker for breast cancer predisposition in population of Isfahan.

Genetic dissection of agronomically important traits in closely related temperate japonica rice cultivars.

Many quantitative trait loci (QTLs) for agronomically important traits such as grain yield, disease resistance, and stress tolerance of rice (Oryza sativa L.) have been detected by using segregating populations derived from crosses between indica and japonica subspecies or with wild relatives. However, the QTLs involved in the control of natural variation in agronomic traits among closely related cultivars are still unclear. Decoding the whole genome sequences of Nipponbare and other temperate japonica rice cultivars has accelerated the collection of a huge number of single nucleotide polymorphisms (SNPs). These SNPs are good resource for developing polymorphic DNA markers and for detecting QTLs distributed across all rice chromosomes. The temperate japonica rice cultivar Koshihikari has remained the top cultivar for about 40 years since 1979 in Japan. Unraveling the genetic factors in Koshihikari will provide important insights into improving agronomic traits in temperate japonica rice cultivars. Here we describe recent progress in our studies as an example of genetic analysis in closely related cultivars.

Plasmid Complement of Lactococcus lactis NCDO712 Reveals a Novel Pilus Gene Cluster.

Lactococcus lactis MG1363 is an important gram-positive model organism. It is a plasmid-free and phage-cured derivative of strain NCDO712. Plasmid-cured strains facilitate studies on molecular biological aspects, but many properties which make L. lactis an important organism in the dairy industry are plasmid encoded. We sequenced the total DNA of strain NCDO712 and, contrary to earlier reports, revealed that the strain carries 6 rather than 5 plasmids. A new 50-kb plasmid, designated pNZ712, encodes functional nisin immunity (nisCIP) and copper resistance (lcoRSABC). The copper resistance could be used as a marker for the conjugation of pNZ712 to L. lactis MG1614. A genome comparison with the plasmid cured daughter strain MG1363 showed that the number of single nucleotide polymorphisms that accumulated in the laboratory since the strains diverted more than 30 years ago is limited to 11 of which only 5 lead to amino acid changes. The 16-kb plasmid pSH74 was found to contain a novel 8-kb pilus gene cluster spaCB-spaA-srtC1-srtC2, which is predicted to encode a pilin tip protein SpaC, a pilus basal subunit SpaB, and a pilus backbone protein SpaA. The sortases SrtC1/SrtC2 are most likely involved in pilus polymerization while the chromosomally encoded SrtA could act to anchor the pilus to peptidoglycan in the cell wall. Overexpression of the pilus gene cluster from a multi-copy plasmid in L. lactis MG1363 resulted in cell chaining, aggregation, rapid sedimentation and increased conjugation efficiency of the cells. Electron microscopy showed that the over-expression of the pilus gene cluster leads to appendices on the cell surfaces. A deletion of the gene encoding the putative basal protein spaB, by truncating spaCB, led to more pilus-like structures on the cell surface, but cell aggregation and cell chaining were no longer observed. This is consistent with the prediction that spaB is involved in the anchoring of the pili to the cell.

Association of body mass index-related single nucleotide polymorphisms with psychiatric disease and memory performance in a Japanese population.

Obesity is a risk factor for psychiatric diseases. Recently, a number of single nucleotide polymorphisms (SNPs) have been shown to be related to body mass index (BMI). In this study, we investigated the association of BMI-related SNPs with psychiatric diseases and one of their endophenotypes, memory performance, in a Japanese population. The subjects were 1624 patients with one of three psychiatric diseases (799 patients with major depressive disorder, 594 with schizophrenia, and 231 with bipolar disorder) and 1189 healthy controls. Memory performance was assessed using the Wechsler Memory Scale - Revised (WMS-R). Genomic DNA was prepared from venous blood and used to genotype 23 BMI-related SNPs using the TaqMan 5'-exonuclease allelic discrimination assay. We then analysed the relationships between the SNPs and psychiatric disease and various subscales of the WMS-R. Three SNPs (rs11142387, rs12597579, and rs6548238) showed significant differences in the genotype or allele frequency between patients with any psychiatric diseases and controls. Furthermore, six SNPs (rs11142387, rs12597579, rs2815752, rs2074356, rs4776970, and rs2287019) showed significant differences in at least one subscale of the WMS-R depending on the genotypes of the healthy controls. Interestingly, rs11142387 near the Kruppel-like factor 9 (KLF9) was significantly associated with psychiatric disease and poor memory function. We identified three and six BMI-related SNPs associated with psychiatric disease and memory performance, respectively. In particular, carrying the A allele of rs11142387 near KLF9 was found to be associated with psychiatric disease and poor memory performance, which warrants further investigations.

The 1000 Genomes Project: Prediction of Known and Novel Blood Group Continental Distribution By Next Generation Sequencing

▪Background:The 1000 Genomes Project provides a database of over 80 million genomic variants found across 2504 individuals from 26 populations. A current priority of the genomics field is to design information systems to translate this knowledge into clinical significance and patient care. The applications and advantages of red blood cell (RBC) antigen prediction through genotyping are widely accepted in transfusion medicine. Current technologies address a limited number of single nucleotide polymorphisms (SNPs) in 12 blood group genes, and our background knowledge of RBC phenotype distribution is often limited to a few populations. We analyzed the 1000 Genomes database with 4 objectives: 1) determine allele distributions of 46 blood group-related genes across the 5 genotyped superpopulations: Africa, East Asia, Europe, South Asia and the Americas; 2) identify possible new blood group alleles and their geographic association; 3) determine the feasibility of blood group genotyping by NGS; and 4) establish a scaffold of chromosomal coordinates to interpret NGS output files into a predicted RBC phenotype.Results:From the initial list of 46 blood group-related genes, we eliminated the five genes with known rearrangements and focused only on regions that met the strict criteria for accessibility through short, paired-end NGS reads (77% of 80.4kb). We mapped over 800 known alleles in coding and non-coding regions, and documented the 80 variants that were both present in the 1000 Genomes database and met the strict accessibility criteria. Sixty-four of these 80 variants are not addressed by current RBC genotyping technology. All 80 variants, including the ACKR1 promoter silencing mutation, are located within exon pull-down boundaries. The average low-coverage sequencing depth was 18,424x, with exome-sequencing confirmation at 65.7x depth. Twenty-three alleles had at least one novel population distribution, such as documentation of the Kpaallele for the first time in Africa and South Asia. From a total of 30 novel blood group continental frequencies, 14 correspond to a newfound presence in South Asia.1000 Genomes identified a total of 926 missense mutations in blood group genes that met strict NGS mapping criteria, as well as multiple deletions. Two novel missense mutations in ERMAP and SLC14A1 are classified as likely antigenic, since they target the same amino acids responsible for the SCER- and Cr(a-) alleles. Six novel deletions involving the Lewis, H, Cromer, Indian and OK systems are also classified as likely-deleterious after careful analysis. For example, a novel in-frame 24bp deletion in SLC14A1 eliminates part of the intracytoplasmic tail, which is required for membrane localization and includes the 28G residue that defines JK*01W.03. Thus, this novel deletion is predicted to alter Kidd protein expression. The 8 novel alleles are distributed throughout the five superpopulations but are most frequently found in Africa. Four standard bioinformatics programs named SIFT, PolyPhen-2, Mutation Taster, and Mutation Assessor failed to detect half of the control known blood group alleles and thus are not adequate for the analysis of novel blood group variants in the transfusion medicine context.Conclusions:NGS can allow comprehensive, fast, and high-throughput RBC antigen prediction. All queried blood group alleles are amenable to targeted exome sequencing, and 77% of blood group coding sequences can be addressed with a short, paired-end NGS strategy. Based on 1000 Genomes, we created a database of the worldwide distribution of 80 known and 8 novel blood group variants, along with their chromosomal coordinates in the hg19 and GRCh38 assemblies. This database is the scaffold for the creation of a new transfusion medicine bioinformatics pipeline that will translate NGS .vcf output files into a predicted RBC phenotype. New algorithms that focus on exposed peptides and antigenicity are required for the analysis of novel variants identified by NGS in the immunohematology context. DisclosuresNo relevant conflicts of interest to declare.

A Review on Methods for Detecting SNP Interactions in High-Dimensional Genomic Data.

In this era of genome-wide association studies (GWAS), the quest for understanding the genetic architecture of complex diseases is rapidly increasing more than ever before. The development of high throughput genotyping and next generation sequencing technologies enables genetic epidemiological analysis of large scale data. These advances have led to the identification of a number of single nucleotide polymorphisms (SNPs) responsible for disease susceptibility. The interactions between SNPs associated with complex diseases are increasingly being explored in the current literature. These interaction studies are mathematically challenging and computationally complex. These challenges have been addressed by a number of data mining and machine learning approaches. This paper reviews the current methods and the related software packages to detect the SNP interactions that contribute to diseases. The issues that need to be considered when developing these models are addressed in this review. The paper also reviews the achievements in data simulation to evaluate the performance of these models. Further, it discusses the future of SNP interaction analysis.

A MAGIC population-based genome-wide association study reveals functional association of GhRBB1_A07 gene with superior fiber quality in cotton.

BackgroundCotton supplies a great majority of natural fiber for the global textile industry. The negative correlation between yield and fiber quality has hindered breeders’ ability to improve these traits simultaneously. A multi-parent advanced generation inter-cross (MAGIC) population developed through random-mating of multiple diverse parents has the ability to break this negative correlation. Genotyping-by-sequencing (GBS) is a method that can rapidly identify and genotype a large number of single nucleotide polymorphisms (SNP). Genotyping a MAGIC population using GBS technologies will enable us to identify marker-trait associations with high resolution.ResultsAn Upland cotton MAGIC population was developed through random-mating of 11 diverse cultivars for five generations. In this study, fiber quality data obtained from four environments and 6071 SNP markers generated via GBS and 223 microsatellite markers of 547 recombinant inbred lines (RILs) of the MAGIC population were used to conduct a genome wide association study (GWAS). By employing a mixed linear model, GWAS enabled us to identify markers significantly associated with fiber quantitative trait loci (QTL). We identified and validated one QTL cluster associated with four fiber quality traits [short fiber content (SFC), strength (STR), length (UHM) and uniformity (UI)] on chromosome A07. We further identified candidate genes related to fiber quality attributes in this region. Gene expression and amino acid substitution analysis suggested that a regeneration of bulb biogenesis 1 (GhRBB1_A07) gene is a candidate for superior fiber quality in Upland cotton. The DNA marker CFBid0004 designed from an 18 bp deletion in the coding sequence of GhRBB1_A07 in Acala Ultima is associated with the improved fiber quality in the MAGIC RILs and 105 additional commercial Upland cotton cultivars.ConclusionUsing GBS and a MAGIC population enabled more precise fiber QTL mapping in Upland cotton. The fiber QTL and associated markers identified in this study can be used to improve fiber quality through marker assisted selection or genomic selection in a cotton breeding program. Target manipulation of the GhRBB1_A07 gene through biotechnology or gene editing may potentially improve cotton fiber quality.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3249-2) contains supplementary material, which is available to authorized users.

Improving Genetic Gain with Genomic Selection in Autotetraploid Potato

Potato ( L.) breeders consider a large number of traits during cultivar development and progress in conventional breeding can be slow. There is accumulating evidence that some of these traits, such as yield, are affected by a large number of genes with small individual effects. Recently, significant efforts have been applied to the development of genomic resources to improve potato breeding, culminating in a draft genome sequence and the identification of a large number of single nucleotide polymorphisms (SNPs). The availability of these genome-wide SNPs is a prerequisite for implementing genomic selection for improvement of polygenic traits such as yield. In this review, we investigate opportunities for the application of genomic selection to potato, including novel breeding program designs. We have considered a number of factors that will influence this process, including the autotetraploid and heterozygous genetic nature of potato, the rate of decay of linkage disequilibrium, the number of required markers, the design of a reference population, and trait heritability. Based on estimates of the effective population size derived from a potato breeding program, we have calculated the expected accuracy of genomic selection for four key traits of varying heritability and propose that it will be reasonably accurate. We compared the expected genetic gain from genomic selection with the expected gain from phenotypic and pedigree selection, and found that genetic gain can be substantially improved by using genomic selection.

Dimensionality of genomic information and performance of the Algorithm for Proven and Young for different livestock species.

BackgroundA genomic relationship matrix (GRM) can be inverted efficiently with the Algorithm for Proven and Young (APY) through recursion on a small number of core animals. The number of core animals is theoretically linked to effective population size (N e). In a simulation study, the optimal number of core animals was equal to the number of largest eigenvalues of GRM that explained 98% of its variation. The purpose of this study was to find the optimal number of core animals and estimate N e for different species.MethodsDatasets included phenotypes, pedigrees, and genotypes for populations of Holstein, Jersey, and Angus cattle, pigs, and broiler chickens. The number of genotyped animals varied from 15,000 for broiler chickens to 77,000 for Holsteins, and the number of single-nucleotide polymorphisms used for genomic prediction varied from 37,000 to 61,000. Eigenvalue decomposition of the GRM for each population determined numbers of largest eigenvalues corresponding to 90, 95, 98, and 99% of variation.ResultsThe number of eigenvalues corresponding to 90% (98%) of variation was 4527 (14,026) for Holstein, 3325 (11,500) for Jersey, 3654 (10,605) for Angus, 1239 (4103) for pig, and 1655 (4171) for broiler chicken. Each trait in each species was analyzed using the APY inverse of the GRM with randomly selected core animals, and their number was equal to the number of largest eigenvalues. Realized accuracies peaked with the number of core animals corresponding to 98% of variation for Holstein and Jersey and closer to 99% for other breed/species. N e was estimated based on comparisons of eigenvalue decomposition in a simulation study. Assuming a genome length of 30 Morgan, N e was equal to 149 for Holsteins, 101 for Jerseys, 113 for Angus, 32 for pigs, and 44 for broilers.ConclusionsEigenvalue profiles of GRM for common species are similar to those in simulation studies although they are affected by number of genotyped animals and genotyping quality. For all investigated species, the APY required less than 15,000 core animals. Realized accuracies were equal or greater with the APY inverse than with regular inversion. Eigenvalue analysis of GRM can provide a realistic estimate of N e.