Evaluating oligonucleotide properties for DNA microarray probe design

Identify potential miRNA-mRNA regulatory networks contributing to high-risk neuroblastoma

Neuroblastoma (NB) is a common tumor in children, usually in the retroperitoneum. After various treatments, low- and intermediate-risk patients have achieved good results, but the prognosis of high-risk patients is still very poor. Therefore, it is necessary to find new effective targets for the treatment of high-risk patients. In this study, comprehensive bioinformatics analysis was used to identify the differentially expressed genes (DEG and DEM) between high-risk patients and non-high-risk patients, and it was identified that ADRB2 may affect the survival status of high-risk patients due to miR -30a-5p regulation. The GSE49710, GSE73517, and GSE121513 datasets were downloaded from the Gene Expression Synthesis (GEO) database, and DEG and DEM were selected. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied to the selected DEGs. The STRING database and Cytoscape software were used to construct protein-protein interaction (PPI) networks and perform modular analysis of the DEGs. The TARGET data set containing information on overall survival days were used for the prognostic analysis of central genes. We identified a total of 255 DEGs from GSE49710 and GSE73517, and 193 DEMs from GSE121513. We identified the 5 most important central genes from the PPI network, performed a prognostic analysis in the target data set, and verified their expression using RT-qPCR to select the most important ADRB2 gene to predict miRNA. Integrating the differential miRNA predicted by miRDB and miRSystem and GSE121513 between the targeted miRNA and the prognosis, miR-30a-5p was finally identified as the targeted miRNA of ADRB2.

Analysis and identification of novel biomarkers involved in neuroblastoma via integrated bioinformatics

Neuroblastoma (NB) is the most common extracranial solid tumor in children. Under various treatments, some patients still have a poor prognosis. Hence, it is necessary to find new valid targets for NB therapy. In this study, a comprehensive bioinformatic analysis was used to identify differentially expressed genes (DEGs) between NB and control cells, and to select hub genes associated with NB. GSE66586 and GSE78061 datasets were downloaded from the Gene Expression Omnibus (GEO) database and DEGs were selected. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied to the selected DEGs. The STRING database and Cytoscape software were used to construct protein-protein interaction (PPI) networks and perform modular analysis of the DEGs. The R2 database was used for prognostic analysis. We identified a total of 238 DEGs from two microarray databases. GO enrichment analysis shows that these DEGs are mainly concentrated in the regulation of cell growth, cell migration, cell fate determination, and cell maturation. KEGG pathway analysis showed that these DEGs are mainly involved in focal adhesion, the TNF signaling pathway, cancer-related pathways, and signaling pathways regulating stem cell pluripotency. We identified the 15 most closely related DEGs from the PPI network, and performed R2 database prognostic analysis to select five hub genes - CTGF, EDN1, GATA2, LOX, and SERPINE1. This study distinguished hub genes and related signaling pathways that can potentially serve as diagnostic indicators and therapeutic biomarkers for NB, thereby improving understanding of the molecular mechanisms involved in NB.

Microbial community profiling of ammonia and nitrite oxidizing bacterial enrichments from brackishwater ecosystems for mitigating nitrogen species

Nitrogen species such as ammonia and nitrite are considered as major stressors in modern aquaculture practices. We developed enrichments of ammonia oxidising bacteria (AOB) and nitrite oxidising bacteria (NOB) for effective mitigation of nitrogenous wastes in the shrimp culture operations. The objective of this study was to understand the microbial community composition of AOB and NOB enrichments using the V3-V4 region of the 16S rDNA gene by Illumina MiSeq sequencing. The analysis revealed 2948 and 1069 OTUs at 97% similarity index and Shannon alpha diversity index of 7.64 and 4.85 for AOB and NOB enrichments, respectively. Comparative analysis showed that a total of 887 OTUs were common among AOB and NOB enrichments. The AOB and NOB enrichment were dominated by Eubacteria at 96% and 99.7% respectively. Proteobacterial phylum constituted 31.46% (AOB) and 39.75% (NOB) and dominated by α-Proteobacteria (20%) in AOB and γ-Proteobacteria (16%) in NOB. Among the species in AOB enrichment (2,948) two sequences were assigned to ammonia oxidising bacterial group belonging to Nitrosomonas, and Nitrosococcus genera and two belonged to archaeon group comprising Nitrosopumilus and Candidatus Nitrososphaeraea genera. The NOB enrichment was predominated by Nitrospiraceae and Thermodesulfovibrionaceae. Further, the data revealed the presence of heterotrophic bacteria contributing to the process of nitrification and form microcosm with the AOB and NOB. PICRUSt analysis predicted the presence of 24 different nitrogen cycling genes involved in nitrification, denitrification, ammonia and nitrogen transporter family, nitrate reduction and ammonia assimilation. The study confirms the presence of many lesser known nitrifying bacteria along with well characterised nitrifiers.

Sequence characteristics define trade-offs between on-target and genome-wide off-target hybridization of oligoprobes

Off-target oligoprobe's interaction with partially complementary nucleotide sequences represents a problem for many bio-techniques. The goal of the study was to identify oligoprobe sequence characteristics that control the ratio between on-target and off-target hybridization. To understand the complex interplay between specific and genome-wide off-target (cross-hybridization) signals, we analyzed a database derived from genomic comparison hybridization experiments performed with an Affymetrix tiling array. The database included two types of probes with signals derived from (i) a combination of specific signal and cross-hybridization and (ii) genomic cross-hybridization only. All probes from the database were grouped into bins according to their sequence characteristics, where both hybridization signals were averaged separately. For selection of specific probes, we analyzed the following sequence characteristics: vulnerability to self-folding, nucleotide composition bias, numbers of G nucleotides and GGG-blocks, and occurrence of probe's k-mers in the human genome. Increases in bin ranges for these characteristics are simultaneously accompanied by a decrease in hybridization specificity-the ratio between specific and cross-hybridization signals. However, both averaged hybridization signals exhibit growing trends along with an increase of probes' binding energy, where the hybridization specific signal increases significantly faster in comparison to the cross-hybridization. The same trend is evident for the S function, which serves as a combined evaluation of probe binding energy and occurrence of probe's k-mers in the genome. Application of S allows extracting a larger number of specific probes, as compared to using only binding energy. Thus, we showed that high values of specific and cross-hybridization signals are not mutually exclusive for probes with high values of binding energy and S. In this study, the application of a new set of sequence characteristics allows detection of probes that are highly specific to their targets for array design and other bio-techniques that require selection of specific probes.

Optimization of signal-to-noise ratio for efficient microarray probe design

MOTIVATION

Target-specific hybridization depends on oligo-probe characteristics that improve hybridization specificity and minimize genome-wide cross-hybridization. Interplay between specific hybridization and genome-wide cross-hybridization has been insufficiently studied, despite its crucial role in efficient probe design and in data analysis.

RESULTS

In this study, we defined hybridization specificity as a ratio between oligo target-specific hybridization and oligo genome-wide cross-hybridization. A microarray database, derived from the Genomic Comparison Hybridization (GCH) experiment and performed using the Affymetrix platform, contains two different types of probes. The first type of oligo-probes does not have a specific target on the genome and their hybridization signals are derived from genome-wide cross-hybridization alone. The second type includes oligonucleotides that have a specific target on the genomic DNA and their signals are derived from specific and cross-hybridization components combined together in a total signal. A comparative analysis of hybridization specificity of oligo-probes, as well as their nucleotide sequences and thermodynamic features was performed on the database. The comparison has revealed that hybridization specificity was negatively affected by low stability of the fully-paired oligo-target duplex, stable probe self-folding, G-rich content, including GGG motifs, low sequence complexity and nucleotide composition symmetry.

CONCLUSION

Filtering out the probes with defined 'negative' characteristics significantly increases specific hybridization and dramatically decreasing genome-wide cross-hybridization. Selected oligo-probes have two times higher hybridization specificity on average, compared to the probes that were filtered from the analysis by applying suggested cutoff thresholds to the described parameters. A new approach for efficient oligo-probe design is described in our study.

CONTACT

shabalin@ncbi.nlm.nih.gov or olga.matveeva@gmail.com

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Natural Allelic Variations in Highly Polyploidy Saccharum Complex

Sugarcane (Saccharum spp.) is an important sugar and biofuel crop with high polyploid and complex genomes. The Saccharum complex, comprised of Saccharum genus and a few related genera, are important genetic resources for sugarcane breeding. A large amount of natural variation exists within the Saccharum complex. Though understanding their allelic variation has been challenging, it is critical to dissect allelic structure and to identify the alleles controlling important traits in sugarcane. To characterize natural variations in Saccharum complex, a target enrichment sequencing approach was used to assay 12 representative germplasm accessions. In total, 55,946 highly efficient probes were designed based on the sorghum genome and sugarcane unigene set targeting a total of 6 Mb of the sugarcane genome. A pipeline specifically tailored for polyploid sequence variants and genotype calling was established. BWA-mem and sorghum genome approved to be an acceptable aligner and reference for sugarcane target enrichment sequence analysis, respectively. Genetic variations including 1,166,066 non-redundant SNPs, 150,421 InDels, 919 gene copy number variations, and 1,257 gene presence/absence variations were detected. SNPs from three different callers (Samtools, Freebayes, and GATK) were compared and the validation rates were nearly 90%. Based on the SNP loci of each accession and their ploidy levels, 999,258 single dosage SNPs were identified and most loci were estimated as largely homozygotes. An average of 34,397 haplotype blocks for each accession was inferred. The highest divergence time among the Saccharum spp. was estimated as 1.2 million years ago (MYA). Saccharum spp. diverged from Erianthus and Sorghum approximately 5 and 6 MYA, respectively. The target enrichment sequencing approach provided an effective way to discover and catalog natural allelic variation in highly polyploid or heterozygous genomes.

Thermodynamic Post-Processing versus GC-Content Pre-Processing for DNA Codes Satisfying the Hamming Distance and Reverse-Complement Constraints

Stochastic, meta-heuristic and linear construction algorithms for the design of DNA strands satisfying Hamming distance and reverse-complement constraints often use a GC-content constraint to pre-process the DNA strands. Since GC-content is a poor predictor of DNA strand hybridization strength the strands can be filtered by post-processing using thermodynamic calculations. An alternative approach is considered here, where the algorithms are modified to remove consideration of GC-content and rely on post-processing alone to obtain large sets of DNA strands with satisfactory melting temperatures. The two approaches (pre-processing GC-content and post-processing melting temperatures) are compared and are shown to be complementary when large DNA sets are desired. In particular, the second approach can give significant improvements when linear constructions are used.

A Transcriptome-Targeting EcoChip for Assessing Functional Mycodiversity

A functional biodiversity microarray (EcoChip) prototype has been developed to facilitate the analysis of fungal communities in environmental samples with broad functional and phylogenetic coverage and to enable the incorporation of nucleic acid sequence data as they become available from large-scale (next generation) sequencing projects. A dual probe set (DPS) was designed to detect a) functional enzyme transcripts at conserved protein sites and b) phylogenetic barcoding transcripts at ITS regions present in precursor rRNA. Deviating from the concept of GeoChip-type microarrays, the presented EcoChip microarray phylogenetic information was obtained using a dedicated set of barcoding microarray probes, whereas functional gene expression was analyzed by conserved domain-specific probes. By unlinking these two target groups, the shortage of broad sequence information of functional enzyme-coding genes in environmental communities became less important. The novel EcoChip microarray could be successfully applied to identify specific degradation activities in environmental samples at considerably high phylogenetic resolution. Reproducible and unbiased microarray signals could be obtained with chemically labeled total RNA preparations, thus avoiding the use of enzymatic labeling steps. ITS precursor rRNA was detected for the first time in a microarray experiment, which confirms the applicability of the EcoChip concept to selectively quantify the transcriptionally active part of fungal communities at high phylogenetic resolution. In addition, the chosen microarray platform facilitates the conducting of experiments with high sample throughput in almost any molecular biology laboratory.

Targeted analysis of nucleotide and copy number variation by exon capture in allotetraploid wheat genome

Background

The ability of grass species to adapt to various habitats is attributed to the dynamic nature of their genomes, which have been shaped by multiple rounds of ancient and recent polyploidization. To gain a better understanding of the nature and extent of variation in functionally relevant regions of a polyploid genome, we developed a sequence capture assay to compare exonic sequences of allotetraploid wheat accessions.

Results

A sequence capture assay was designed for the targeted re-sequencing of 3.5 Mb exon regions that surveyed a total of 3,497 genes from allotetraploid wheat. These data were used to describe SNPs, copy number variation and homoeologous sequence divergence in coding regions. A procedure for variant discovery in the polyploid genome was developed and experimentally validated. About 1% and 24% of discovered SNPs were loss-of-function and non-synonymous mutations, respectively. Under-representation of replacement mutations was identified in several groups of genes involved in translation and metabolism. Gene duplications were predominant in a cultivated wheat accession, while more gene deletions than duplications were identified in wild wheat.

Conclusions

We demonstrate that, even though the level of sequence similarity between targeted polyploid genomes and capture baits can bias enrichment efficiency, exon capture is a powerful approach for variant discovery in polyploids. Our results suggest that allopolyploid wheat can accumulate new variation in coding regions at a high rate. This process has the potential to broaden functional diversity and generate new phenotypic variation that eventually can play a critical role in the origin of new adaptations and important agronomic traits.

Targeted analysis of nucleotide and copy number variation by exon capture in allotetraploid wheat genome

BACKGROUND

The ability of grass species to adapt to various habitats is attributed to the dynamic nature of their genomes, which have been shaped by multiple rounds of ancient and recent polyploidization. To gain a better understanding of the nature and extent of variation in functionally relevant regions of a polyploid genome, we developed a sequence capture assay to compare exonic sequences of allotetraploid wheat accessions.

RESULTS

A sequence capture assay was designed for the targeted re-sequencing of 3.5 Mb exon regions that surveyed a total of 3,497 genes from allotetraploid wheat. These data were used to describe SNPs, copy number variation and homoeologous sequence divergence in coding regions. A procedure for variant discovery in the polyploid genome was developed and experimentally validated. About 1% and 24% of discovered SNPs were loss-of-function and non-synonymous mutations, respectively. Under-representation of replacement mutations was identified in several groups of genes involved in translation and metabolism. Gene duplications were predominant in a cultivated wheat accession, while more gene deletions than duplications were identified in wild wheat.

CONCLUSIONS

We demonstrate that, even though the level of sequence similarity between targeted polyploid genomes and capture baits can bias enrichment efficiency, exon capture is a powerful approach for variant discovery in polyploids. Our results suggest that allopolyploid wheat can accumulate new variation in coding regions at a high rate. This process has the potential to broaden functional diversity and generate new phenotypic variation that eventually can play a critical role in the origin of new adaptations and important agronomic traits.