Genome-wide analysis of single-nucleotide polymorphisms in human expressed sequences

Single-Nucleotide Polymorphisms (SNP) Mining and Their Effect on the Tridimensional Protein Structure Prediction in a Set of Immunity-Related Expressed Sequence Tags (EST) in Atlantic Salmon (Salmo salar)

Single-nucleotide polymorphisms (SNPs) are single genetic code variations considered one of the most common forms of nucleotide modifications. Such SNPs can be located in genes associated to immune response and, therefore, they may have direct implications over the phenotype of susceptibility to infections affecting the productive sector. In this study, a set of immune-related genes (cc motif chemokine 19 precursor [ccl19], integrin β2 (itβ2, also named cd18), glutathione transferase omega-1 [gsto-1], heat shock 70 KDa protein [hsp70], major histocompatibility complex class I [mhc-I]) were analyzed to identify SNPs by data mining. These genes were chosen based on their previously reported expression on infectious pancreatic necrosis virus (IPNV)-infected Atlantic salmon phenotype. The available EST sequences for these genes were obtained from the Unigene database. Twenty-eight SNPs were found in the genes evaluated and identified most of them as transition base changes. The effect of the SNPs located on the 5'-untranslated region (UTR) or 3'-UTR upon transcription factor binding sites and alternative splicing regulatory motifs was assessed and ranked with a low-medium predicted FASTSNP score risk. Synonymous SNPs were found on itβ2 (c.2275G > A), gsto-1 (c.558G > A), and hsp70 (c.1950C > T) with low FASTSNP predicted score risk. The difference in the relative synonymous codon usage (RSCU) value between the variant codons and the wild-type codon (ΔRSCU) showed one negative (hsp70 c.1950C > T) and two positive ΔRSCU values (itβ2 c.2275G > A; gsto-1 c.558G > A), suggesting that these synonymous SNPs (sSNPs) may be associated to differences in the local rate of elongation. Nonsynonymous SNPs (nsSNPs) in the gsto-1 translatable gene region were ranked, using SIFT and POLYPHEN web-tools, with the second highest (c.205A > G; c484T > C) and the highest (c.499T > C; c.769A > C) predicted score risk possible. Using homology modeling to predict the effect of these nonsynonymous SNPs, the most relevant nucleotide changes for gsto-1 were observed for the nsSNPs c.205A > G, c484T > C, and c.769A > C. Molecular dynamics was assessed to analyze if these GSTO-1 variants have significant differences in their conformational dynamics, suggesting these SNPs could have allosteric effects modulating its catalysis. Altogether, these results suggest that candidate SNPs identified may play a crucial potential role in the immune response of Atlantic salmon.

A hybridization-triggered DNAzyme cascade assay for enzyme-free amplified fluorescence detection of nucleic acids

An enzyme-free and ultrasensitive fluorescence assay for the detection of nucleic acids was successfully established by a hybridization-triggered DNAzyme cascade (HTDC).

A simple and ultrasensitive fluorescence assay for single-nucleotide polymorphism

In this report, a simple, label-free and highly efficient nucleic acid amplification technique is developed for ultrasensitive detection of single-nucleotide polymorphism (SNP). Briefly, a designed padlock probe is first circularized by a DNA ligase when it perfectly complements to a mutant gene. Then, the mutant gene functions as a primer to initiate branched rolling circle amplification reaction (BRCA), generating a large number of branched DNA strands and a lot of pyrophosphate molecules which is equivalent to the number of nucleotides consumed. With the addition of a terpyridine-Zn(II) complex, pyrophosphate molecules can be sensitively detected owing to the formation of a fluorescent terpyridine-Zn(II)-pyrophosphate complex. The fluorescence intensity is directly associated with the content of the mutant gene in a sample solution. On the other hand, the circulation of the padlock probe is prohibited when it hybridizes with the wild-type gene. In this assay, the accumulative nature of the BRCA process produces a detection limit of 0.1 pM and an excellent selectivity factor of 1000 toward SNP. As little as 0.1% mutant in the wild-type gene can be successfully detected. The simple procedure, high sensitivity, and high selectivity of this assay offer a potentially viable alternative for routine SNP analysis. Graphical abstract A simple and label-free fluorescence assay for SNP detection by coupling BRCA with selective fluorescence detection of pyrophosphate using the terpyridine-Zn(II) complex.

Comparing fixed sampling with minimizer sampling when using k-mer indexes to find maximal exact matches

Bioinformatics applications and pipelines increasingly use k-mer indexes to search for similar sequences. The major problem with k-mer indexes is that they require lots of memory. Sampling is often used to reduce index size and query time. Most applications use one of two major types of sampling: fixed sampling and minimizer sampling. It is well known that fixed sampling will produce a smaller index, typically by roughly a factor of two, whereas it is generally assumed that minimizer sampling will produce faster query times since query k-mers can also be sampled. However, no direct comparison of fixed and minimizer sampling has been performed to verify these assumptions. We systematically compare fixed and minimizer sampling using the human genome as our database. We use the resulting k-mer indexes for fixed sampling and minimizer sampling to find all maximal exact matches between our database, the human genome, and three separate query sets, the mouse genome, the chimp genome, and an NGS data set. We reach the following conclusions. First, using larger k-mers reduces query time for both fixed sampling and minimizer sampling at a cost of requiring more space. If we use the same k-mer size for both methods, fixed sampling requires typically half as much space whereas minimizer sampling processes queries only slightly faster. If we are allowed to use any k-mer size for each method, then we can choose a k-mer size such that fixed sampling both uses less space and processes queries faster than minimizer sampling. The reason is that although minimizer sampling is able to sample query k-mers, the number of shared k-mer occurrences that must be processed is much larger for minimizer sampling than fixed sampling. In conclusion, we argue that for any application where each shared k-mer occurrence must be processed, fixed sampling is the right sampling method.

The effects of sampling on the efficiency and accuracy of k-mer indexes: Theoretical and empirical comparisons using the human genome

One of the most common ways to search a sequence database for sequences that are similar to a query sequence is to use a k-mer index such as BLAST. A big problem with k-mer indexes is the space required to store the lists of all occurrences of all k-mers in the database. One method for reducing the space needed, and also query time, is sampling where only some k-mer occurrences are stored. Most previous work uses hard sampling, in which enough k-mer occurrences are retained so that all similar sequences are guaranteed to be found. In contrast, we study soft sampling, which further reduces the number of stored k-mer occurrences at a cost of decreasing query accuracy. We focus on finding highly similar local alignments (HSLA) over nucleotide sequences, an operation that is fundamental to biological applications such as cDNA sequence mapping. For our comparison, we use the NCBI BLAST tool with the human genome and human ESTs. When identifying HSLAs, we find that soft sampling significantly reduces both index size and query time with relatively small losses in query accuracy. For the human genome and HSLAs of length at least 100 bp, soft sampling reduces index size 4-10 times more than hard sampling and processes queries 2.3-6.8 times faster, while still achieving retention rates of at least 96.6%. When we apply soft sampling to the problem of mapping ESTs against the genome, we map more than 98% of ESTs perfectly while reducing the index size by a factor of 4 and query time by 23.3%. These results demonstrate that soft sampling is a simple but effective strategy for performing efficient searches for HSLAs. We also provide a new model for sampling with BLAST that predicts empirical retention rates with reasonable accuracy by modeling two key problem factors.

Core–shell gold nanocubes for point mutation detection based on plasmon-enhanced fluorescence

A core–shell gold nanocube has been prepared for point mutation detection based on the PEF process.

The presence of a 5'-abasic lesion enhances discrimination of single nucleotide polymorphisms while inducing an isothermal ligase chain reaction

Lesion-induced DNA amplification (LIDA) has been employed in the detection of single nucleotide polymorphisms (SNPs). Due to the presence of the proximal abasic lesion, T4 DNA ligase exhibits greater intolerance to basepair mismatches when compared with mismatch ligation in the absence of the abasic lesion. Moreover the presence of the abasic group also results in an isothermal ligase chain reaction enabling SNP detection with great discrimination and sensitivity. Specifically, at forty minutes, the ratio of amplified product from the matched and mismatched initiated reactions are 7-12 depending on the mismatch. The ease of implementation of our method is demonstrated by real-time analysis of DNA amplification using a fluorescent plate reader.

A universal probe design for colorimetric detection of single-nucleotide variation with visible readout and high specificity

Single-nucleotide variation (SNV) is a crucial biomarker for drug resistance-related detection in cancer and bacterial infection. However, the unintended binding of DNA probes limits the specificity of SNV detection, and the need for redesigned sequences compromise the universality of SNV assay. Herein, we demonstrated a universal and low-cost assay for the colorimetric discrimination of drug-resistance related point mutation. By the use of a universal DNA probe and a split G-quadruplex, the signal could be recognized by naked eye at room temperature. The DNA probe was used as a signal reporter which not only improved the universality, but also enabled high specificity of probe hybridization. This assay was successfully applied in the detection of cancer-related SNV in the epidermal growth factor receptor (EGFR) gene, kirsten rat sarcoma viral oncogene homologue (KRAS), and tuberculosis drug-resistance related point mutation in RNA polymerase beta subunit gene (rpoB) with high specificity and visible readout. This method was simple, rapid, high-throughput and effective, which was suitable for point-of-care applications.

Entropy Beacon: A Hairpin-Free DNA Amplification Strategy for Efficient Detection of Nucleic Acids

Here, we propose an efficient strategy for enzyme- and hairpin-free nucleic acid detection called an entropy beacon (abbreviated as Ebeacon). Different from previously reported DNA hybridization/displacement-based strategies, Ebeacon is driven forward by increases in the entropy of the system, instead of free energy released from new base-pair formation. Ebeacon shows high sensitivity, with a detection limit of 5 pM target DNA in buffer and 50 pM in cellular homogenate. Ebeacon also benefits from the hairpin-free amplification strategy and zero-background, excellent thermostability from 20 °C to 50 °C, as well as good resistance to complex environments. In particular, based on the huge difference between the breathing rate of a single base pair and two adjacent base pairs, Ebeacon also shows high selectivity toward base mutations, such as substitution, insertion, and deletion and, therefore, is an efficient nucleic acid detection method, comparable to most reported enzyme-free strategies.

The Effect of Ancestry and Genetic Variation on Lung Function Predictions: What Is "Normal" Lung Function in Diverse Human Populations?

Lung function measures are an invaluable screening test for respiratory health and have been associated with the morbidity and mortality related to different airway disease as well as all-cause mortality. Currently, reference values for spirometric measurements are obtained using equations derived from individual ethnic or racial groups. The rapid expansion of more racially and ethnically diverse populations will challenge current race-based lung function reference equations. Recent international general population studies and ancestry-based genetic studies have found that ancestry and genetic variation are determinants of lung function and have suggested a role for genetic ancestry or gene variants in future lung function reference equations. In this review, we discuss the potential limitations of current lung function reference equations in a global society which is becoming more ethnically, racially, and, thus, genetically diverse. We also focus on how an individual's ancestral background or genetic profile could provide the basis for more accurate, personalized predictions of an individual's baseline lung function.

Ligation-rolling circle amplification combined with γ-cyclodextrin mediated stemless molecular beacon for sensitive and specific genotyping of single-nucleotide polymorphism

A novel approach for highly sensitive and selective genotyping of single-nucleotide polymorphism (SNP) has been developed based on ligation-rolling circle amplification (L-RCA) and stemless molecular beacon. In this approach, two tailored DNA probes were involved. The stemless molecular beacon, formed through the inclusion interactions of γ-cyclodextrin (γ-CD) and bis-pyrene labeled DNA fragment, was served as signal probe. In the absence of mutant target, the two pyrene molecules were bound in the γ-CD cavity to form an excimer and showed a strong fluorescence at 475 nm. It was here named γ-CD-P-MB. The padlock DNA probe was designed as recognition probe. Upon the recognition of a point mutation DNA targets, the padlock probe was ligated to generate a circular template. An RCA amplification was then initiated using the circular template in the presence of Phi29 polymerase and dNTPs. The L-RCA products, containing repetitive sequence units, subsequently hybridized with the γ-CD-P-MB. This made pyrene molecules away from γ-CD cavity and caused a decrease of excimer fluorescence. As a proof-of-concept, SNP typing of β-thalassemia gene at position -28 was investigated using this approach. The detection limit of mutated target was determined to be 40 fM. In addition, DNA ligase offered high fidelity in distinguishing the mismatched bases at the ligation site, resulting in positive detection of mutant target even when the ratio of the wildtype to the mutant is 999:1. Given these attractive characteristics, the developed approach might provide a great genotyping platform for pathogenic diagnosis and genetic analysis.

Pharmacogenetics: implications of race and ethnicity on defining genetic profiles for personalized medicine

Pharmacogenetics is being used to develop personalized therapies specific to subjects from different ethnic or racial groups. To date, pharmacogenetic studies have been primarily performed in trial cohorts consisting of non-Hispanic white subjects of European descent. A "bottleneck" or collapse of genetic diversity associated with the first human colonization of Europe during the Upper Paleolithic period, followed by the recent mixing of African, European, and Native American ancestries, has resulted in different ethnic groups with varying degrees of genetic diversity. Differences in genetic ancestry might introduce genetic variation, which has the potential to alter the therapeutic efficacy of commonly used asthma therapies, such as β2-adrenergic receptor agonists (β-agonists). Pharmacogenetic studies of admixed ethnic groups have been limited to small candidate gene association studies, of which the best example is the gene coding for the receptor target of β-agonist therapy, the β2-adrenergic receptor (ADRB2). Large consortium-based sequencing studies are using next-generation whole-genome sequencing to provide a diverse genome map of different admixed populations, which can be used for future pharmacogenetic studies. These studies will include candidate gene studies, genome-wide association studies, and whole-genome admixture-based approaches that account for ancestral genetic structure, complex haplotypes, gene-gene interactions, and rare variants to detect and replicate novel pharmacogenetic loci.

Versatile DNAzyme-based amplified biosensing platforms for nucleic acid, protein, and enzyme activity detection

DNAzymes have been widely applied as signal amplifiers for enzyme-free and highly sensitive detection of DNA. A few of them have also been employed for amplified detection of other biomolecules via a target-triggered assembly of split or mutated DNAzyme strategy. However, most of these designs adopt Mg(2+)-dependent DNAzyme as the catalytic unit, which suffered from low catalytic cleavage activity. Meanwhile, some DNAzymes with high catalytic activity are not suitable for these designs because the slight modification of the catalytic core might results in remarkably decreased or even no catalytic activity of these DNAzymes. On the basis of DNAzyme topological effect or the terminal protection of small-molecule-linked DNA, we developed two versatile sensing platforms for amplified detection of different biotargets. Since no modification is necessary for the catalytic core of the DNAzyme in these designs, they can employ any DNAzyme with high catalytic activity as amplified unit, which affords a high amplified efficiency for the sensing platform. A catalytic and molecular beacon design was further employed to realize the true enzymatic multiple turnover of DNAzyme. These designs together allow a high sensitivity for the biotargets, resulting in a detection limit of 20 pM, 0.2 U/mL, and 1 ng/mL for target DNA, DNA adenine methylation methyltransferase (Dam MTase), and streptavidin, respectively, much lower than previously reported biosensors. In addition, the proposed sensing strategy is versatile. By conjugating with various recognition units, it can be employed to detect a wide range of biotargets, varying from nucleic acids to proteins with high sensitivity.

Decoding the disease-associated proteins encoded in the human chromosome 4

Chromosome 4 is the fourth largest chromosome, containing approximately 191 megabases (~6.4% of the human genome) with 757 protein-coding genes. A number of marker genes for many diseases have been found in this chromosome, including genetic diseases (e.g., hepatocellular carcinoma) and biomedical research (cardiac system, aging, metabolic disorders, immune system, cancer and stem cell) related genes (e.g., oncogenes, growth factors). As a pilot study for the chromosome 4-centric human proteome project (Chr 4-HPP), we present here a systematic analysis of the disease association, protein isoforms, coding single nucleotide polymorphisms of these 757 protein-coding genes and their experimental evidence at the protein level. We also describe how the findings from the chromosome 4 project might be used to drive the biomarker discovery and validation study in disease-oriented projects, using the examples of secretomic and membrane proteomic approaches in cancer research. By integrating with cancer cell secretomes and several other existing databases in the public domain, we identified 141 chromosome 4-encoded proteins as cancer cell-secretable/shedable proteins. Additionally, we also identified 54 chromosome 4-encoded proteins that have been classified as cancer-associated proteins with successful selected or multiple reaction monitoring (SRM/MRM) assays developed. From literature annotation and topology analysis, 271 proteins were recognized as membrane proteins while 27.9% of the 757 proteins do not have any experimental evidence at the protein-level. In summary, the analysis revealed that the chromosome 4 is a rich resource for cancer-associated proteins for biomarker verification projects and for drug target discovery projects.

A novel SNP of the PNRC1 gene and its association with reproductive traits in Tsaiya ducks

Proline-rich nuclear receptor coactivator (PNRC)1 is a member of a new family of nuclear receptor coactivators capable of potentiating the transcriptional activity of nuclear receptors. The objective was to investigate the relationship between PNRC1 genotypes of single nucleotide polymorphism (SNP) and reproductive traits in ducks. Brown Tsaiya ducks (N = 305) from two lines, a control line with no selection and the selected line, were used. Polymerase chain reaction-single strand polymorphism and DNA sequencing were done to screen polymorphisms of the PNRC1 gene. A novel SNP (G98T) in 3'-untranslated region of the PNRC1 gene was identified and resulted in two genotypes, GG and GT. The frequencies of genotype GG and allele G were higher in both lines investigated. Regarding egg weight at first egg (EWFE), based on SNP trait association analysis, ducks with the GG genotype had a 4.48 g per egg greater egg weight at first egg when compared with ducks of the GT genotype in the control line (P < 0.05). In addition, this SNP was associated with the hatchability rate (HR) in the selected line; ducks with the GT genotype had a 6.70% higher hatchability rate than those with the GG genotype (P < 0.05). Therefore, we inferred that the PNRC1 gene could be a candidate locus or linked to a major gene that influenced egg weight-related and hatchability traits in Tsaiya ducks. Further investigations on additional duck populations with larger sample sizes are needed to confirm these results.

Novel genetic markers of the carbonic anhydrase II gene associated with egg production and reproduction traits in Tsaiya ducks

In our previous cDNA microarray study, we found that the carbonic anhydrase II (CA2) gene is one of the differentially expressed transcripts in the duck isthmus epithelium during egg formation period. The aim of this study was to identify the single-nucleotide polymorphisms (SNPs) in the CA2 gene of Tsaiya ducks. The relationship of SNP genotype with egg production and reproduction traits was also investigated. A total of 317 ducks from two lines, a control line with no selection and a selected line, were employed for testing. Three SNPs (C37T, A62G and A65G) in the 3'-untranslated region of the CA2 gene were found. SNP-trait association analysis showed that SNP C37T and A62G were associated with duck egg weight besides fertility. The ducks with the CT and AG genotypes had a 1.46 and 1.62 g/egg lower egg weight as compared with ducks with the CC and AA genotypes, respectively (p < 0.05). But the ducks with CT and AG genotypes had 5.20% and 4.22% higher fertility than those with CC and AA genotypes, respectively (p < 0.05). Diplotype constructed on these three SNPs was associated with duck fertility, and the diplotype H1H4 was dominant for duck fertility. These findings might provide the basis for balanced selection and may be used in marker-assisted selection to improve egg weight and fertility simultaneously in the Tsaiya ducks.

Fluorescence and visual detection of single nucleotide polymorphism using cationic conjugated polyelectrolyte

We report a simple assay for visual detection of single nucleotide polymorphisms (SNPs) with good sensitivity and selectivity. The selectivity is determined by Escherichia coli (E. coli) DNA ligase mediated circular formation upon recognition of the point mutation on DNA targets. Rolling cycle amplification (RCA) of the perfect-matched DNA target is then initiated using the in situ formed circular template in the presence of Phi29 enzyme. Due to amplification of the DNA target, the RCA product has a tandem-repeated sequence, which is significantly longer than that for the SNP strand. Direct addition of a cationic conjugated polymer of poly[9,9'-bis(6'-(N,N,N-trimethylammonium)hexyl)fluorene-co-9,9'-bis(2-(2-(2-(N,N,N-trimethylammonium)ethoxyl)-ethoxy)-ethyl)fluorene tetrabromide] containing 20 mol% 2,1,3-benzothiadiazole (PFBT(20)) into the RCA solution leads to blue-whitish fluorescent color for SNP strand and yellowish fluorescent color for amplified DNA, due to PFBT(20)/DNA complexation induced intrachain/interchain energy transfer. To further improve the contrast for visual detection, FAM-labeled peptide nucleic acid (PNA) was hybridized to each amplified sequence, which is followed by the addition of poly{2,7-[9,9-bis(6'-N,N,N-trimethylammoniumhexyl)]fluorene-co-2,5-difluoro-1,4-phenylene dibromide} (PFP). The PNA/DNA hybridization brings PFP and FAM-PNA into close proximity for energy transfer, and the solution fluorescent color appears green in the presence of target DNA with a detection limit of 1 nM, which is significantly improved as compared to that for most reported visual SNP assay.

RNASEQR--a streamlined and accurate RNA-seq sequence analysis program

Next-generation sequencing (NGS) technologies-based transcriptomic profiling method often called RNA-seq has been widely used to study global gene expression, alternative exon usage, new exon discovery, novel transcriptional isoforms and genomic sequence variations. However, this technique also poses many biological and informatics challenges to extracting meaningful biological information. The RNA-seq data analysis is built on the foundation of high quality initial genome localization and alignment information for RNA-seq sequences. Toward this goal, we have developed RNASEQR to accurately and effectively map millions of RNA-seq sequences. We have systematically compared RNASEQR with four of the most widely used tools using a simulated data set created from the Consensus CDS project and two experimental RNA-seq data sets generated from a human glioblastoma patient. Our results showed that RNASEQR yields more accurate estimates for gene expression, complete gene structures and new transcript isoforms, as well as more accurate detection of single nucleotide variants (SNVs). RNASEQR analyzes raw data from RNA-seq experiments effectively and outputs results in a manner that is compatible with a wide variety of specialized downstream analyses on desktop computers.

Strategies for genotyping

The identification of genomic loci linked to or associated with human disease has been greatly facilitated by the evolution of genotyping strategies and techniques. The success of these strategies continues to be based upon clear clinical assessment, accurate sample handling, and careful data management, but also increasingly upon experimental design. Technological advances in the field of genotyping have permitted increasingly complex and large population studies to be performed. An understanding of publicly available genetic variation databases, including an awareness of the limitations of these data, and an appreciation of the strategic approaches that should be used to exploit this information will provide tremendous insight for researchers are aiming to utilize this accessible technology. As genome-wide association studies (GWAS) and Next Generation (NextGen) sequencing become the mainstays of genetic analyses, it is important that their technical strengths and limitations, as well as their impact on study design, be understood before use in a linkage or genetic association study.

Error and error mitigation in low-coverage genome assemblies

The recent release of twenty-two new genome sequences has dramatically increased the data available for mammalian comparative genomics, but twenty of these new sequences are currently limited to ∼2× coverage. Here we examine the extent of sequencing error in these 2× assemblies, and its potential impact in downstream analyses. By comparing 2× assemblies with high-quality sequences from the ENCODE regions, we estimate the rate of sequencing error to be 1–4 errors per kilobase. While this error rate is fairly modest, sequencing error can still have surprising effects. For example, an apparent lineage-specific insertion in a coding region is more likely to reflect sequencing error than a true biological event, and the length distribution of coding indels is strongly distorted by error. We find that most errors are contributed by a small fraction of bases with low quality scores, in particular, by the ends of reads in regions of single-read coverage in the assembly. We explore several approaches for automatic sequencing error mitigation (SEM), making use of the localized nature of sequencing error, the fact that it is well predicted by quality scores, and information about errors that comes from comparisons across species. Our automatic methods for error mitigation cannot replace the need for additional sequencing, but they do allow substantial fractions of errors to be masked or eliminated at the cost of modest amounts of over-correction, and they can reduce the impact of error in downstream phylogenomic analyses. Our error-mitigated alignments are available for download.

Mining SNPs from EST sequences using filters and ensemble classifiers

Abundant single nucleotide polymorphisms (SNPs) provide the most complete information for genome-wide association studies. However, due to the bottleneck of manual discovery of putative SNPs and the inaccessibility of the original sequencing reads, it is essential to develop a more efficient and accurate computational method for automated SNP detection. We propose a novel computational method to rapidly find true SNPs in public-available EST (expressed sequence tag) databases; this method is implemented as SNPDigger. EST sequences are clustered and aligned. SNP candidates are then obtained according to a measure of redundant frequency. Several new informative biological features, such as the structural neighbor profiles and the physical position of the SNP, were extracted from EST sequences, and the effectiveness of these features was demonstrated. An ensemble classifier, which employs a carefully selected feature set, was included for the imbalanced training data. The sensitivity and specificity of our method both exceeded 80% for human genetic data in the cross validation. Our method enables detection of SNPs from the user's own EST dataset and can be used on species for which there is no genome data. Our tests showed that this method can effectively guide SNP discovery in ESTs and will be useful to avoid and save the cost of biological analyses.

RAFT-generated polyacrylamide-DNA block copolymers for single-nucleotide polymorphism genotyping by affinity capillary electrophoresis

Capillary electrophoretic separation of a mixture of 5'-fluorescein isothiocyanate-labeled single-stranded DNA (normal ssDNA) and its single-base-substituted one (mutant ssDNA) was achieved by using a RAFT-generated polyacrylamide-oligodeoxyribonucleotide block copolymer (PAAm-b-ODN) as an affinity polymeric probe. PAAm-b-ODN was synthesized through the Michael addition of thiol-terminated PAAm (PAAm-SH) to 5'-maleimide-modified ODN. PAAm-SH was derived from dithiobenzoate-terminated PAAm prepared via RAFT polymerization. The number-averaged molecular weight (M(n)) and the molecular weight distribution were determined by aqueous size exclusion chromatography. After a capillary tube was filled with the running buffer solution of PAAm-b-ODN, a mixture of normal and mutant ssDNA was subjected to electrophoresis and detected by a laser-induced fluorescent detector. Because the base sequence of PAAm-b-ODN was complementary to part of the mutant ssDNA, including a single-base substitution site, the electrophoretic migration of mutant ssDNA was retarded due to the formation of the equilibrium complex with PAAm-b-ODN. Increasing M(n) of the PAAm segment enhanced this retardation. On the other hand, normal ssDNA was unable to form the complex owing to a single-base mismatch, which was proved by melting curve measurements. The Lineweaver-Burk-type analysis of the mobility of mutant ssDNA revealed that the binding constants for the complexes with different PAAm-b-ODN probes were almost identical to each other. The analysis also demonstrated that the ratio of the hydrodynamic radius of the complex to that of the free mutant ssDNA increased with increasing M(n) of the affinity polymeric probe's PAAm segment. This means that the PAAm segment indirectly provides mutant ssDNA with an additional hydrodynamic friction force via the affinity interaction of the ODN segment. Optimization of the salt concentration of the running buffer and the capillary temperature improved the resolution of the separation. This affinity polymeric probe will be useful for developing a simple and highly reliable single-nucleotide polymorphism genotyping method.

Conserved recoding RNA editing of vertebrate C1q-related factor C1QL1

A-to-I RNA editing can lead to recoding of pre-mRNAs with profound functional consequences for the ensuing proteins. Here we show that complement component 1, q subcomponent-like 1 (C1QL1) undergoes RNA editing in vivo causing non-synonymous amino acid substitutions in human, mouse as well as zebrafish. The major editing site had previously been annotated as a single-nucleotide polymorphism in human, but our analysis reveals that post-transcriptional modification is the cause for the sequence variation. Remarkably, although editing of C1QL1 is conserved across vertebrate species, the predicted RNA secondary structure mediating editing involves different regions in zebrafish versus mammals.

Genome wide identification of recessive cancer genes by combinatorial mutation analysis

We devised a novel procedure to identify human cancer genes acting in a recessive manner. Our strategy was to combine the contributions of the different types of genetic alterations to loss of function: amino-acid substitutions, frame-shifts, gene deletions. We studied over 20,000 genes in 3 Gigabases of coding sequences and 700 array comparative genomic hybridizations. Recessive genes were scored according to nucleotide mismatches under positive selective pressure, frame-shifts and genomic deletions in cancer. Four different tests were combined together yielding a cancer recessive p-value for each studied gene. One hundred and fifty four candidate recessive cancer genes (p-value < 1.5 x 10(-7), FDR = 0.39) were identified. Strikingly, the prototypical cancer recessive genes TP53, PTEN and CDKN2A all ranked in the top 0.5% genes. The functions significantly affected by cancer mutations are exactly overlapping those of known cancer genes, with the critical exception for the absence of tyrosine kinases, as expected for a recessive gene-set.

Screening of human SNP database identifies recoding sites of A-to-I RNA editing

Single nucleotide polymorphisms (SNPs) are DNA sequence variations that can affect the expression or function of genes. As a result, they may lead to phenotypic differences between individuals, such as susceptibility to disease, response to medications, and disease progression. Millions of SNPs have been mapped within the human genome providing a rich resource for genetic variation studies. Adenosine-to-inosine RNA editing also leads to the production of RNA and protein sequence variants, but it acts on the level of primary gene transcripts. Sequence variations due to RNA editing may be misannotated as SNPs when relying solely on expressed sequence data instead of genomic material. In this study, we screened the human SNP database for potential cases of A-to-I RNA editing that cause amino acid changes in the encoded protein. Our search strategy applies five molecular features to score candidate sites. It identifies all previously known cases of editing present in the SNP database and successfully uncovers novel, bona fide targets of adenosine deamination editing. Our approach sets the stage for effective and comprehensive genome-wide screens for A-to-I editing targets.

Gene mapping in the wild with SNPs: guidelines and future directions

One of the biggest challenges facing evolutionary biologists is to identify and understand loci that explain fitness variation in natural populations. This review describes how genetic (linkage) mapping with single nucleotide polymorphism (SNP) markers can lead to great progress in this area. Strategies for SNP discovery and SNP genotyping are described and an overview of how to model SNP genotype information in mapping studies is presented. Finally, the opportunity afforded by new generation sequencing and typing technologies to map fitness genes by genome-wide association studies is discussed.

Detection of genome-wide polymorphisms in the AT-rich Plasmodium falciparum genome using a high-density microarray

Background

Genetic mapping is a powerful method to identify mutations that cause drug resistance and other phenotypic changes in the human malaria parasite Plasmodium falciparum. For efficient mapping of a target gene, it is often necessary to genotype a large number of polymorphic markers. Currently, a community effort is underway to collect single nucleotide polymorphisms (SNP) from the parasite genome. Here we evaluate polymorphism detection accuracy of a high-density 'tiling' microarray with 2.56 million probes by comparing single feature polymorphisms (SFP) calls from the microarray with known SNP among parasite isolates.

Results

We found that probe GC content, SNP position in a probe, probe coverage, and signal ratio cutoff values were important factors for accurate detection of SFP in the parasite genome. We established a set of SFP calling parameters that could predict mSFP (SFP called by multiple overlapping probes) with high accuracy (≥ 94%) and identified 121,087 mSFP genome-wide from five parasite isolates including 40,354 unique mSFP (excluding those from multi-gene families) and ~18,000 new mSFP, producing a genetic map with an average of one unique mSFP per 570 bp. Genomic copy number variation (CNV) among the parasites was also cataloged and compared.

Conclusion

A large number of mSFP were discovered from the P. falciparum genome using a high-density microarray, most of which were in clusters of highly polymorphic genes at chromosome ends. Our method for accurate mSFP detection and the mSFP identified will greatly facilitate large-scale studies of genome variation in the P. falciparum parasite and provide useful resources for mapping important parasite traits.

Solving the problem of Trans-Genomic Query with alignment tables

The trans-genomic query (TGQ) problem--enabling the free query of biological information, even across genomes--is a central challenge facing bioinformatics. Solutions to this problem can alter the nature of the field, moving it beyond the jungle of data integration and expanding the number and scope of questions that can be answered. An alignment table is a binary relationship on locations (sequence segments). An important special case of alignment tables are hit tables ? tables of pairs of highly similar segments produced by alignment tools like BLAST. However, alignment tables also include general binary relationships, and can represent any useful connection between sequence locations. They can be curated, and provide a high-quality queryable backbone of connections between biological information. Alignment tables thus can be a natural foundation for TGQ, as they permit a central part of the TGQ problem to be reduced to purely technical problems involving tables of locations.Key challenges in implementing alignment tables include efficient representation and indexing of sequence locations. We define a location datatype that can be incorporated naturally into common off-the-shelf database systems. We also describe an implementation of alignment tables in BLASTGRES, an extension of the open-source POSTGRESQL database system that provides indexing and operators on locations required for querying alignment tables. This paper also reviews several successful large-scale applications of alignment tables for Trans-Genomic Query. Tables with millions of alignments have been used in queries about alternative splicing, an area of genomic analysis concerning the way in which a single gene can yield multiple transcripts. Comparative genomics is a large potential application area for TGQ and alignment tables.

Affinity capillary electrophoretic DNA separation using PEG-oligodeoxyribonucleotide block copolymers: relationship between peak resolution and affinity strength

Capillary electrophoretic separation of chemically synthesized ssDNA and a single-base-substituted one (normal and mutant ssDNA, respectively) was demonstrated using a PEG-oligodeoxyribonucleotide block copolymer (PEG-b-ODN) as an affinity ligand. When the base sequence of PEG-b-ODN was designed to be complementary to part of normal ssDNA including the base-substituted site, the electrophoretic mobility of normal ssDNA significantly decreased whereas that of mutant ssDNA slightly changed. Resolution of the separation strongly depended on the ODN length of the copolymer, the capillary temperature, and the Mg2+ concentration in the running buffer, indicating that the retardation of migration of normal ssDNA was induced by the reversible hybridization with PEG-b-ODN. It was found that the dissociation constant (K(d)) of the duplex between normal ssDNA and the affinity probe ODN should be smaller than 10(-6) M to achieve the good peak separation. In addition, we calculated the mobility of the complex (mu(C)) between normal ssDNA and PEG-b-ODN using a two-state model. The base sequence of affinity probe ODN appropriate to achieve the sufficient resolution will be predicted on the basis of the mu(C) and K(d )values.

Homogeneous and label-free fluorescence detection of single-nucleotide polymorphism using target-primed branched rolling circle amplification

We present a simple, sensitive, and cost-effective fluorescent assay of single-nucleotide polymorphism (SNP) with target-primed branched rolling circle amplification (TPBRCA). Designed padlock probe is circularized after perfect hybridization to mutant DNA. Then rolling circle amplification (RCA) reaction can be initiated from the mutant DNA that acts as primer and generates a long tandem single-stranded DNA (ssDNA) product. At the same time, the introduction of a reverse primer complementary to the target-primed RCA products leads to the branched RCA and eventually generates the various lengths of ssDNA and double-stranded DNA products, which are sensitively detected using SYBR Green I (SG) fluorescence dye. In contrast, the wild DNA contains a single mismatched base with the padlock probe and primes only a limited extension with the unligated padlock probe, generating weak background fluorescence with the addition of SG. Due to the excellent specificity and powerful amplification of TPBRCA reaction, the mutant DNA was distinctively differentiated from the wild DNA in a homogeneous and label-free manner. The assay is sensitive and specific enough to detect 5-amol (8.6-fM) mutant DNA strands. It was possible to accurately determine the mutant allele frequency as low as 1.0%.

DArT markers: diversity analyses and mapping in Sorghum bicolor

BACKGROUND

The sequential nature of gel-based marker systems entails low throughput and high costs per assay. Commonly used marker systems such as SSR and SNP are also dependent on sequence information. These limitations result in high cost per data point and significantly limit the capacity of breeding programs to obtain sufficient return on investment to justify the routine use of marker-assisted breeding for many traits and particularly quantitative traits. Diversity Arrays Technology (DArT) is a cost effective hybridisation-based marker technology that offers a high multiplexing level while being independent of sequence information. This technology offers sorghum breeding programs an alternative approach to whole-genome profiling. We report on the development, application, mapping and utility of DArT markers for sorghum germplasm.

RESULTS

A genotyping array was developed representing approximately 12,000 genomic clones using PstI+BanII complexity with a subset of clones obtained through the suppression subtractive hybridisation (SSH) method. The genotyping array was used to analyse a diverse set of sorghum genotypes and screening a Recombinant Inbred Lines (RIL) mapping population. Over 500 markers detected variation among 90 accessions used in a diversity analysis. Cluster analysis discriminated well between all 90 genotypes. To confirm that the sorghum DArT markers behave in a Mendelian manner, we constructed a genetic linkage map for a cross between R931945-2-2 and IS 8525 integrating DArT and other marker types. In total, 596 markers could be placed on the integrated linkage map, which spanned 1431.6 cM. The genetic linkage map had an average marker density of 1/2.39 cM, with an average DArT marker density of 1/3.9 cM.

CONCLUSION

We have successfully developed DArT markers for Sorghum bicolor and have demonstrated that DArT provides high quality markers that can be used for diversity analyses and to construct medium-density genetic linkage maps. The high number of DArT markers generated in a single assay not only provides a precise estimate of genetic relationships among genotypes, but also their even distribution over the genome offers real advantages for a range of molecular breeding and genomics applications.

DArT markers: diversity analyses and mapping in Sorghum bicolor

BACKGROUND

The sequential nature of gel-based marker systems entails low throughput and high costs per assay. Commonly used marker systems such as SSR and SNP are also dependent on sequence information. These limitations result in high cost per data point and significantly limit the capacity of breeding programs to obtain sufficient return on investment to justify the routine use of marker-assisted breeding for many traits and particularly quantitative traits. Diversity Arrays Technology (DArT) is a cost effective hybridisation-based marker technology that offers a high multiplexing level while being independent of sequence information. This technology offers sorghum breeding programs an alternative approach to whole-genome profiling. We report on the development, application, mapping and utility of DArT markers for sorghum germplasm.

RESULTS

A genotyping array was developed representing approximately 12,000 genomic clones using PstI+BanII complexity with a subset of clones obtained through the suppression subtractive hybridisation (SSH) method. The genotyping array was used to analyse a diverse set of sorghum genotypes and screening a Recombinant Inbred Lines (RIL) mapping population. Over 500 markers detected variation among 90 accessions used in a diversity analysis. Cluster analysis discriminated well between all 90 genotypes. To confirm that the sorghum DArT markers behave in a Mendelian manner, we constructed a genetic linkage map for a cross between R931945-2-2 and IS 8525 integrating DArT and other marker types. In total, 596 markers could be placed on the integrated linkage map, which spanned 1431.6 cM. The genetic linkage map had an average marker density of 1/2.39 cM, with an average DArT marker density of 1/3.9 cM.

CONCLUSION

We have successfully developed DArT markers for Sorghum bicolor and have demonstrated that DArT provides high quality markers that can be used for diversity analyses and to construct medium-density genetic linkage maps. The high number of DArT markers generated in a single assay not only provides a precise estimate of genetic relationships among genotypes, but also their even distribution over the genome offers real advantages for a range of molecular breeding and genomics applications.

An investigation of potential genetic determinants of propofol requirements and recovery from anaesthesia

BACKGROUND AND OBJECTIVE

The objectives of this study were, firstly, to characterize the inter-patient variability in the dose of propofol required to achieve a bispectral index <70 and 'time to eye opening' following propofol infusion and, secondly, to determine if the pharmacodynamic parameter 'time to achieve bispectral index <70' was influenced by genotype of the sex-linked drug receptor gene GABRE or if pharmacokinetic parameters such as clearance and 'time to eye opening' were influenced by the genotype of the metabolizing enzyme CYP2B6.

METHODS

One hundred and fifty patients received a standardized anaesthetic. Apparent systemic clearance values were estimated. Correlation was sought between carriers of different CYP2B6 and GABRE genotypes and apparent systemic clearance, 'time to achieve bispectral index <70' and 'time to eye opening'.

RESULTS

Propofol induction/emergence characteristics varied, with slow recovery times in a subset of males. Time to loss of verbal contact and time to bispectral index <70 varied 6.6- and 4.3-fold, respectively. At emergence, there was a 15.5- to 111-fold variability in the measured time intervals. Clearance varied from 9.1 to 55.8 mL min-1 kg-1. The CYP2B6 C1459T (R487C) genotype frequencies were TT 1%, TC 22% and CC 67%. The three major haplotypes of CYP2B6 (R487C, K262R and Q172H variants) were not significantly associated with time to eye opening or clearance. Clearance was similar in 487C carriers and 487RR genotypes. There was no statistically significant correlation between the four major haplotypes of GABRE variants investigated ([mRNA358]G/T, 20118C/T, 20326C/T and 20502 A/T) and the observed anaesthesia induction time.

CONCLUSIONS

Great inter-patient variability exists in the dose of propofol required to achieve bispectral index <70, apparent systemic propofol clearance and time to eye opening. Common haplotypic differences at the CYP2B6 and GABRE genes do not appear to account for the majority of the observed inter-patient variability.

SNP detection exploiting multiple sources of redundancy in large EST collections improves validation rates

MOTIVATION

Single nucleotide polymorphism (SNP) detection exploiting redundancy in expressed sequence tag (EST) collections that arises from the presence of transcripts of the same gene from different individuals has been used to generate large collections of SNPs for many species. A second source of redundancy, namely that EST collections can contain multiple transcripts of the same gene from the same individual, can be exploited to distinguish true SNPs from sequencing error. In this article, we demonstrate with Atlantic salmon and pig EST collections that splitting the EST collection in two, detecting SNPs in both subsets, then accepting only cross-validated SNPs increases validation rates.

RESULTS

In the pig data set, 676 cross-validated putative SNPs were detected in a collection of 160,689 ESTs. When validating a subset of these by genotyping on MassARRAY 85.1% of SNPs were polymorphic in successful assays. In the salmon data set, 856 cross-validated putative SNPs were detected in a collection of 243,674 ESTs. Validation by genotyping showed that 81.0% of the cross-validated putative SNPs were polymorphic in successful assays.

AVAILABILITY

Cross-validated SNPs are available at dbSNP (http://www.ncbi.nlm.nih.gov/projects/SNP/), ss69371838-ss69372575 for the salmon SNPs and ss69372587-ss69373226 for the pig SNPs.

EMMA: an efficient massive mapping algorithm using improved approximate mapping filtering

Efficient massive mapping algorithm (EMMA), an algorithm on efficiently mapping massive cDNAs onto genomic sequences, has recently been developed. The process of mapping massive cDNAs onto genomic sequences has been improved using more approximate mapping filtering based on an enhanced suffix array coupled with a pruned fast hash table, algorithms of block alignment extensions, and k-longest paths. When compared with the classical BLAT software in this field, the computing of EMMA ranges from two to forty-one times faster under similar prediction precisions.

SNP-PHAGE--High throughput SNP discovery pipeline

Background

Single nucleotide polymorphisms (SNPs) as defined here are single base sequence changes or short insertion/deletions between or within individuals of a given species. As a result of their abundance and the availability of high throughput analysis technologies SNP markers have begun to replace other traditional markers such as restriction fragment length polymorphisms (RFLPs), amplified fragment length polymorphisms (AFLPs) and simple sequence repeats (SSRs or microsatellite) markers for fine mapping and association studies in several species. For SNP discovery from chromatogram data, several bioinformatics programs have to be combined to generate an analysis pipeline. Results have to be stored in a relational database to facilitate interrogation through queries or to generate data for further analyses such as determination of linkage disequilibrium and identification of common haplotypes. Although these tasks are routinely performed by several groups, an integrated open source SNP discovery pipeline that can be easily adapted by new groups interested in SNP marker development is currently unavailable.

Results

We developed SNP-PHAGE (SNP discovery Pipeline with additional features for identification of common haplotypes within a sequence tagged site (Haplotype Analysis) and GenBank (-dbSNP) submissions. This tool was applied for analyzing sequence traces from diverse soybean genotypes to discover over 10,000 SNPs. This package was developed on UNIX/Linux platform, written in Perl and uses a MySQL database. Scripts to generate a user-friendly web interface are also provided with common queries for preliminary data analysis. A machine learning tool developed by this group for increasing the efficiency of SNP discovery is integrated as a part of this package as an optional feature. The SNP-PHAGE package is being made available open source at .

Conclusion

SNP-PHAGE provides a bioinformatics solution for high throughput SNP discovery, identification of common haplotypes within an amplicon, and GenBank (dbSNP) submissions. SNP selection and visualization are aided through a user-friendly web interface. This tool is useful for analyzing sequence tagged sites (STSs) of genomic sequences, and this software can serve as a starting point for groups interested in developing SNP markers.

Inference of population genetic parameters in metagenomics: a clean look at messy data

Metagenomic projects generate short, overlapping fragments of DNA sequence, each deriving from a different individual. We report a new method for inferring the scaled mutation rate, theta = 2Neu, and the scaled exponential growth rate, R = Ner, from the site-frequency spectrum of these data while accounting for sequencing error via Phred quality scores. After obtaining maximum likelihood parameter estimates for theta and R, we calculate empirical Bayes quality scores reflecting the posterior probability that each apparently polymorphic site is truly polymorphic; these scores can then be used for other applications such as SNP discovery. For realistic parameter ranges, analytic and simulation results show our estimates to be essentially unbiased with tight confidence intervals. In contrast, choosing an arbitrary quality score cutoff (e.g., trimming reads) and ignoring further quality information during inference yields biased estimates with greater variance. We illustrate the use of our technique on a new project analyzing activated sludge from a lab-scale bioreactor seeded by a wastewater treatment plant.

Monomorphism of human cytochrome c

Cytochrome c (Cyt c) has key roles in both mitochondrial electron transfer and apoptosis onset and is therefore likely undergoing a strong selective pressure against amino acid variation. Nevertheless, a phylogenetically fast amino acid replacement rate in the Cyt c of species of the anthropoid primate lineage was recently reported. We therefore looked for the presence of nonsynonymous single nucleotide polymorphisms (nsSNPs) in the human Cyt c (HGNC approved gene symbol: CYCS), which, given its cellular constraints, could have important functional consequences, and found a large number of putative nsSNPs reported in the dbSNP database. We then subjected these putative SNPs to experimental validation by sequencing the Cyt c gene in a panel of 95 individuals assumed as a standard reference of the human population diversity. Surprisingly, none of the putative SNPs survived experimental validation. We conclude that non-rare allelic variants of the Cyt c protein are absent in the human populations analyzed in this study.