Project description:Single nucleotide polymorphisms (SNPs) are the most common type of genetic variation in gut microbial metagenome and host genome but they could not adequately represent the protein-level variants. Single amino-acid polymorphisms (SAP) derived from non-synonymous SNPs can cause functional changes of proteins and are important forces of adaption. However, SAP remain quite unexplored for human gut microbiome. Here, we present a comprehensive large-scale analysis of SAP in the gut ecosystem, introducing a rigorous computational pipeline for detecting such protein variation from 992 published human metaproteomes.
Project description:Background: Genome-wide detection of single feature polymorphisms (SFP) in swine using transcriptome profiling of day 25 placental RNA by contrasting probe intensities from either Meishan or an occidental composite breed with Affymetrix porcine microarrays is presented. A linear mixed model analysis was used to identify significant breed-by-probe interactions. Results: Gene specific linear mixed models were fit to each of the log2 transformed probe intensities on these arrays, using fixed effects for breed, probe, breed-by-probe interaction, and a random effect for array. After surveying the day 25 placental transcriptome, 789 probes with a q-value ⤠0.05 and |fold change| ⥠2 for the breed-by-probe interaction were identified as candidates containing SFP. To address the quality of the bioinformatics approach, universal pyrosequencing assays were designed from Affymetrix exemplar sequences to independently assess polymorphisms within a subset of probes. Of those probes sampled from high-, medium-, and low-ranking categories, 20 of 27 were confirmed by pyrosequencing to contain SFPs. In most cases, the 25-mer probe sequence printed on the microarray diverged from Meishan, not occidental crosses. This analysis was used to define a set of highly reliable predicted SFPs according to their probability scores. Conclusions: By this method we detected transition and transversion single nucleotide polymorphisms, as well as insertions/deletions. These results demonstrate that this approach can identify polymorphisms between two breeds and/or lines of any species for which a short oligonucleotide array is available, and can be used to rapidly develop markers for genetic mapping and association analysis in species where high density genotyping platforms are otherwise unavailable. SNPs and INDELS discovered by this approach have been publicly deposited in NCBIâs SNP repository dbSNP. This method is an attractive bioinformatics tool for uncovering breed-by-probe interactions, for rapidly identifying expressed SNPs, for investigating potential functional correlations between gene expression and breed polymorphisms, and is robust enough to be used on any Affymetrix gene expression platform. Keywords: Transcriptional profiling of Day 25 porcine placentas 6 samples: Breed (Meishan, Occidental) Placental Tissue, Day 25
Project description:Background: Genome-wide detection of single feature polymorphisms (SFP) in swine using transcriptome profiling of day 25 placental RNA by contrasting probe intensities from either Meishan or an occidental composite breed with Affymetrix porcine microarrays is presented. A linear mixed model analysis was used to identify significant breed-by-probe interactions. Results: Gene specific linear mixed models were fit to each of the log2 transformed probe intensities on these arrays, using fixed effects for breed, probe, breed-by-probe interaction, and a random effect for array. After surveying the day 25 placental transcriptome, 789 probes with a q-value ≤ 0.05 and |fold change| ≥ 2 for the breed-by-probe interaction were identified as candidates containing SFP. To address the quality of the bioinformatics approach, universal pyrosequencing assays were designed from Affymetrix exemplar sequences to independently assess polymorphisms within a subset of probes. Of those probes sampled from high-, medium-, and low-ranking categories, 20 of 27 were confirmed by pyrosequencing to contain SFPs. In most cases, the 25-mer probe sequence printed on the microarray diverged from Meishan, not occidental crosses. This analysis was used to define a set of highly reliable predicted SFPs according to their probability scores. Conclusions: By this method we detected transition and transversion single nucleotide polymorphisms, as well as insertions/deletions. These results demonstrate that this approach can identify polymorphisms between two breeds and/or lines of any species for which a short oligonucleotide array is available, and can be used to rapidly develop markers for genetic mapping and association analysis in species where high density genotyping platforms are otherwise unavailable. SNPs and INDELS discovered by this approach have been publicly deposited in NCBI’s SNP repository dbSNP. This method is an attractive bioinformatics tool for uncovering breed-by-probe interactions, for rapidly identifying expressed SNPs, for investigating potential functional correlations between gene expression and breed polymorphisms, and is robust enough to be used on any Affymetrix gene expression platform. Keywords: Transcriptional profiling of Day 25 porcine placentas
Project description:Nucleotide polymorphisms can potentially influence the hybridization of mRNA to 25-mer oligonucleotides. Because Affymetrix Rice Genome Array was designated mainly for Nipponbare genome of Oryza sativa, the expression level of other varieties could not be estimated correctly. We tried to apply new approaches to estimate expression level by discerning the probe-level differential hybridization.
Project description:Nucleotide polymorphisms can potentially influence the hybridization of mRNA to 25-mer oligonucleotides. Because Affymetrix Rice Genome Array was designated mainly for Nipponbare genome of Oryza sativa, the expression level of other varieties could not be estimated correctly. We tried to apply new approaches to estimate expression level by discerning the probe-level differential hybridization. Nipponbare and 93-11 replicates were analyzed.
Project description:Background: Bovine leukemia virus (BLV) microRNAs (miRNAs) contribute to viral latency and immune evasion. Naturally occurring single-nucleotide polymorphisms (SNPs) within the BLV miRNA cluster have been associated with persistent lymphocytosis in cattle, yet their functional impact remains unclear. Aims: This study aims to (1) evaluate how SNPs in BLV miRNAs affect miRNA biogenesis and mature miRNA levels; (2) determine whether specific SNPs alter miRNA–mRNA interactions and identify affected targets; and (3) characterize transcriptomic changes induced by reference versus SNP-bearing miRNAs. Methods: BLV miRNA loci were PCR-amplified and sequenced from 53 blood samples of infected cattle. Both reference and SNP-containing precursors were cloned into expression vectors and co-transfected with an miRNA-deficient BLV clone into HEK293T cells. Mature miRNA levels were quantified via stem-loop RT-qPCR. Computational target prediction (miRanda) validated changes in mRNA targeting. Gene-expression effects were assessed using Agilent microarrays, with selected findings confirmed by RT-qPCR and subjected to pathway enrichment analysis (IPA). Significance: This work will elucidate how BLV miRNA polymorphisms modify miRNA maturation and target recognition, reshape host gene networks, and contribute to viral persistence and immune modulation.