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Illumina Inc nextseq 500 platform
Schematic circular representation of complete genome sequences of KPC‐2‐producing A. hydrophila GSH8‐2. Short paired‐end whole‐genome sequencing was performed using an Illumina <t>NextSeq</t> 500 platform with a 300‐cycle NextSeq 500 Reagent Kit v2 (2 × 150‐mer). The complete genome sequences of the strains were determined using a PacBio Sequel sequencer for long‐read sequencing [Sequel SMRT Cell 1 M v2 (4/tray]; Sequel sequencing kit v2.1; insert size, approximately 10 kb). De novo assembly was performed using Canu version 1.4 (Koren et al ., 2017 ), minimap version 0.2‐r124 (Li, 2016 ), racon version 1.1.0 (Vaser et al ., 2017 ) and circulator version 1.5.3 (Hunt et al ., 2015 ). Error correction of tentative complete circular sequences was performed using Pilon version 1.18 with Illumina short reads (Walker et al ., 2014 ). Annotation was performed in Prokka version 1.11 (Seemann, 2014 ), InterPro v49.0 (Finn et al ., 2017 ) and NCBI‐BLASTP/BLASTX. Circular representations of complete genomic sequences were visualized using GView server (Petkau et al ., 2010 ). AMR genes were identified by homology searching against the ResFinder database (Zankari et al ., 2012 ). The class 1 integron was assigned in the INTEGRALL database ( http://integrall.bio.ua.pt/ ) (Moura et al ., 2009 ). Visualization of comparative plasmid ORFs organization was performed using Easyfig (Sullivan et al ., 2011 ). For representation of chromosomal DNA, from the inside: slot 1, GC skew; slot 2, GC content; slot 3, ORFs; slot 4, rRNA/tRNA; slots 5–7, BLASTatlas conserved gene analysis indicating three relative strains (see also Supporting Information Fig. S1 ); slot 8, prophage; slot 9, notable ARGs or ARG‐related genes (transposase, ARGs and reductases). In representations of circular plasmids, notable ORFs are highlighted as the indicated colour.
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1) Product Images from "Potential KPC‐2 carbapenemase reservoir of environmental Aeromonas hydrophila and Aeromonas caviae isolates from the effluent of an urban wastewater treatment plant in Japan"

Article Title: Potential KPC‐2 carbapenemase reservoir of environmental Aeromonas hydrophila and Aeromonas caviae isolates from the effluent of an urban wastewater treatment plant in Japan

Journal: Environmental Microbiology Reports

doi: 10.1111/1758-2229.12772

Schematic circular representation of complete genome sequences of KPC‐2‐producing A. hydrophila GSH8‐2. Short paired‐end whole‐genome sequencing was performed using an Illumina NextSeq 500 platform with a 300‐cycle NextSeq 500 Reagent Kit v2 (2 × 150‐mer). The complete genome sequences of the strains were determined using a PacBio Sequel sequencer for long‐read sequencing [Sequel SMRT Cell 1 M v2 (4/tray]; Sequel sequencing kit v2.1; insert size, approximately 10 kb). De novo assembly was performed using Canu version 1.4 (Koren et al ., 2017 ), minimap version 0.2‐r124 (Li, 2016 ), racon version 1.1.0 (Vaser et al ., 2017 ) and circulator version 1.5.3 (Hunt et al ., 2015 ). Error correction of tentative complete circular sequences was performed using Pilon version 1.18 with Illumina short reads (Walker et al ., 2014 ). Annotation was performed in Prokka version 1.11 (Seemann, 2014 ), InterPro v49.0 (Finn et al ., 2017 ) and NCBI‐BLASTP/BLASTX. Circular representations of complete genomic sequences were visualized using GView server (Petkau et al ., 2010 ). AMR genes were identified by homology searching against the ResFinder database (Zankari et al ., 2012 ). The class 1 integron was assigned in the INTEGRALL database ( http://integrall.bio.ua.pt/ ) (Moura et al ., 2009 ). Visualization of comparative plasmid ORFs organization was performed using Easyfig (Sullivan et al ., 2011 ). For representation of chromosomal DNA, from the inside: slot 1, GC skew; slot 2, GC content; slot 3, ORFs; slot 4, rRNA/tRNA; slots 5–7, BLASTatlas conserved gene analysis indicating three relative strains (see also Supporting Information Fig. S1 ); slot 8, prophage; slot 9, notable ARGs or ARG‐related genes (transposase, ARGs and reductases). In representations of circular plasmids, notable ORFs are highlighted as the indicated colour.
Figure Legend Snippet: Schematic circular representation of complete genome sequences of KPC‐2‐producing A. hydrophila GSH8‐2. Short paired‐end whole‐genome sequencing was performed using an Illumina NextSeq 500 platform with a 300‐cycle NextSeq 500 Reagent Kit v2 (2 × 150‐mer). The complete genome sequences of the strains were determined using a PacBio Sequel sequencer for long‐read sequencing [Sequel SMRT Cell 1 M v2 (4/tray]; Sequel sequencing kit v2.1; insert size, approximately 10 kb). De novo assembly was performed using Canu version 1.4 (Koren et al ., 2017 ), minimap version 0.2‐r124 (Li, 2016 ), racon version 1.1.0 (Vaser et al ., 2017 ) and circulator version 1.5.3 (Hunt et al ., 2015 ). Error correction of tentative complete circular sequences was performed using Pilon version 1.18 with Illumina short reads (Walker et al ., 2014 ). Annotation was performed in Prokka version 1.11 (Seemann, 2014 ), InterPro v49.0 (Finn et al ., 2017 ) and NCBI‐BLASTP/BLASTX. Circular representations of complete genomic sequences were visualized using GView server (Petkau et al ., 2010 ). AMR genes were identified by homology searching against the ResFinder database (Zankari et al ., 2012 ). The class 1 integron was assigned in the INTEGRALL database ( http://integrall.bio.ua.pt/ ) (Moura et al ., 2009 ). Visualization of comparative plasmid ORFs organization was performed using Easyfig (Sullivan et al ., 2011 ). For representation of chromosomal DNA, from the inside: slot 1, GC skew; slot 2, GC content; slot 3, ORFs; slot 4, rRNA/tRNA; slots 5–7, BLASTatlas conserved gene analysis indicating three relative strains (see also Supporting Information Fig. S1 ); slot 8, prophage; slot 9, notable ARGs or ARG‐related genes (transposase, ARGs and reductases). In representations of circular plasmids, notable ORFs are highlighted as the indicated colour.

Techniques Used: Sequencing, Genomic Sequencing, Plasmid Preparation

2) Product Images from "Identification of TNFAIP3 as relapse biomarker and potential therapeutic target for MOG antibody associated diseases"

Article Title: Identification of TNFAIP3 as relapse biomarker and potential therapeutic target for MOG antibody associated diseases

Journal: Scientific Reports

doi: 10.1038/s41598-020-69182-w

Gene expression analysis in PBMCs from MOG-AAD patients: Single cell RNA sequencing (inDrop) was performed on an untreated MOG-AAD patient#1 with 2 longitudinal samples, (1) Remission (MOG-AAD#1.2) and (2) Pre-relapse (MOG-AAD#1.3) as described in Materials and Methods. cDNA libraries were sequenced using the Illumina NextSeq 500 platform and analyzed following V3 Indrop criteria. After sequencing the raw BCL files were demultiplexed using bcl2fastq software by illumina ( https://support.illumina.com/sequencing/sequencing_software/bcl2fastq-conversion-software.html ). Reads obtained from bcl2fastq were further processed using the single-cell RNA-seq pipeline of the bcbio-nextgen ( https://bcbio-nextgen.readthedocs.io/en/latest/contents/pipelines.html#single-cell-rna-seq ) software suite. The scaled data was further clustered using Seurat and visualized using TSNE ( https://www.biorxiv.org/content/early/2018/11/02/460147 ). A Cluster analysis of a relapse and remission sample. B Differential expression of TNFAIP3 in the relapse and remission sample by single cell sequencing. Digital Gene Expression (DGE) sequencing was performed on an untreated MOG-AAD patient#1 with 3 longitudinal samples, (1) Rm (remission, MOG-AA#1.2), (2) PR (pre-relapse, MOG-AAD#1.3), and (3) R (relapse, MOG-AAD#1.4) as described in Materials and Methods. Raw BCL files generated through sequencing were further de-multiplexed using Picard ( https://github.com/broadinstitute/picard ) and the resulting FASTQ files where aligned to the human reference genome (GRCh38) using the STAR v2.4.2a 52 aligner. Further QC was done using the RNA-seQC 53 and transcript counts were produced using feature Counts function of the Subread package 54 . Data was normalized using the DESeq2 package 55 and the graphs were made using GraphPadPrism version 8.4.2 (464). C TNFAIP3 and NFκβ1 expression by DGE sequencing. NanoString Gene Expression Assay was performed on a MOG-AAD patient#2 with 3 longitudinal samples, (1) untreated R (relapse, MOG-AAD#2.1), (2) 8 months Rm/Ct (mycophenolate mofetil treated at remission, MOG-AAD#2.2), and (3) 11 months Rm/Ct (mycophenolate mofetil treated at remission, MOG-AAD#2.3) as described in Materials and Methods. Data were normalized and analyzed using nSolver software via the geometric mean of included housekeeping genes. The graphs were made using GraphPadPrism version 8.4.2 (464). D TNFAIP3 and TNF-α expression by NanoString Gene Expression Assay. qPCR was performed on CD4+ T cells from 7 MOG-AAD patients with longitudinal samples as described in Materials and Methods. It also included MOG-AAD patient#2 with 3 longitudinal samples as previously used for NanoString gene expression assay. The graphs were made using GraphPadPrism version 8.4.2 (464). E TNFAIP3 expression in MOG-AAD patient#2 by qPCR. F Grouped analysis of TNFAIP3 expression in relapse samples, remission samples and samples treated with corticosteroids by qPCR. Relapse n = 5, Remission n = 5, Steroid n = 4, Ordinary 1-way ANOVA; P = 0.0137.
Figure Legend Snippet: Gene expression analysis in PBMCs from MOG-AAD patients: Single cell RNA sequencing (inDrop) was performed on an untreated MOG-AAD patient#1 with 2 longitudinal samples, (1) Remission (MOG-AAD#1.2) and (2) Pre-relapse (MOG-AAD#1.3) as described in Materials and Methods. cDNA libraries were sequenced using the Illumina NextSeq 500 platform and analyzed following V3 Indrop criteria. After sequencing the raw BCL files were demultiplexed using bcl2fastq software by illumina ( https://support.illumina.com/sequencing/sequencing_software/bcl2fastq-conversion-software.html ). Reads obtained from bcl2fastq were further processed using the single-cell RNA-seq pipeline of the bcbio-nextgen ( https://bcbio-nextgen.readthedocs.io/en/latest/contents/pipelines.html#single-cell-rna-seq ) software suite. The scaled data was further clustered using Seurat and visualized using TSNE ( https://www.biorxiv.org/content/early/2018/11/02/460147 ). A Cluster analysis of a relapse and remission sample. B Differential expression of TNFAIP3 in the relapse and remission sample by single cell sequencing. Digital Gene Expression (DGE) sequencing was performed on an untreated MOG-AAD patient#1 with 3 longitudinal samples, (1) Rm (remission, MOG-AA#1.2), (2) PR (pre-relapse, MOG-AAD#1.3), and (3) R (relapse, MOG-AAD#1.4) as described in Materials and Methods. Raw BCL files generated through sequencing were further de-multiplexed using Picard ( https://github.com/broadinstitute/picard ) and the resulting FASTQ files where aligned to the human reference genome (GRCh38) using the STAR v2.4.2a 52 aligner. Further QC was done using the RNA-seQC 53 and transcript counts were produced using feature Counts function of the Subread package 54 . Data was normalized using the DESeq2 package 55 and the graphs were made using GraphPadPrism version 8.4.2 (464). C TNFAIP3 and NFκβ1 expression by DGE sequencing. NanoString Gene Expression Assay was performed on a MOG-AAD patient#2 with 3 longitudinal samples, (1) untreated R (relapse, MOG-AAD#2.1), (2) 8 months Rm/Ct (mycophenolate mofetil treated at remission, MOG-AAD#2.2), and (3) 11 months Rm/Ct (mycophenolate mofetil treated at remission, MOG-AAD#2.3) as described in Materials and Methods. Data were normalized and analyzed using nSolver software via the geometric mean of included housekeeping genes. The graphs were made using GraphPadPrism version 8.4.2 (464). D TNFAIP3 and TNF-α expression by NanoString Gene Expression Assay. qPCR was performed on CD4+ T cells from 7 MOG-AAD patients with longitudinal samples as described in Materials and Methods. It also included MOG-AAD patient#2 with 3 longitudinal samples as previously used for NanoString gene expression assay. The graphs were made using GraphPadPrism version 8.4.2 (464). E TNFAIP3 expression in MOG-AAD patient#2 by qPCR. F Grouped analysis of TNFAIP3 expression in relapse samples, remission samples and samples treated with corticosteroids by qPCR. Relapse n = 5, Remission n = 5, Steroid n = 4, Ordinary 1-way ANOVA; P = 0.0137.

Techniques Used: Expressing, RNA Sequencing Assay, Sequencing, Software, Generated, Produced, Real-time Polymerase Chain Reaction

3) Product Images from "Chromosomal phase improves aneuploidy detection in non-invasive prenatal testing at low fetal DNA fractions"

Article Title: Chromosomal phase improves aneuploidy detection in non-invasive prenatal testing at low fetal DNA fractions

Journal: Scientific Reports

doi: 10.1038/s41598-022-14049-5

SNP-based targeted sequencing data with chromosomal phase. ( a ) Pedigree with parents and grandparents of the trisomy 18 fetus. MPSS data of DNA from saliva were available for the parents and microarray genotype data of DNA from saliva were available for the grandparents. Data from the SNP-based targeted sequencing and MPSS of maternal plasma using the Illumina Nextseq 500 platform were available at, respectively, 11 weeks and 15 weeks GA. ( b ) Schematic representation of the formation of a trisomic zygote through missegregation of chromosomes during maternal meiosis II. ( c ) Graphical representation of sequence data at loci heterozygous for the mother from the SNP-based targeted sequencing of maternal plasma at 11 weeks GA with a fetal DNA fraction estimated as f = 3.4%. Each green point corresponds to the fraction of the mother’s maternal allele reads at any of the 13,926 SNP loci that are consistent with heterozygous genotypes for the mother and were covered by more than 200 sequence fragments. The two black dotted lines represent the expected fractions of the mother’s maternal alleles in the case of a euploid fetus, and the three red dotted lines represent the expected fractions in the case of a fetus with trisomy of maternal origin. The blue line is a centered rolling mean across 200 consecutive heterozygous SNPs. The top bars represent the inferred inherited homologs of the fetus, with magenta, red, cyan, and blue colors representing, respectively, mother’s maternal, mother’s paternal, father’s maternal, and father’s paternal homologs. Chromosome 18, with three fetal homologs inferred, is highlighted in red. It is important to note that the algorithm to infer the inherited homolog segments takes also into account information about the homologs transmitted from the father of the fetus and allelic fractions at SNP loci consistent with homozygous genotype for the mother and which are not displayed in this figure and that the paternal homologs of the fetus further adds to the sampling noise at loci heterozygous for the mother.
Figure Legend Snippet: SNP-based targeted sequencing data with chromosomal phase. ( a ) Pedigree with parents and grandparents of the trisomy 18 fetus. MPSS data of DNA from saliva were available for the parents and microarray genotype data of DNA from saliva were available for the grandparents. Data from the SNP-based targeted sequencing and MPSS of maternal plasma using the Illumina Nextseq 500 platform were available at, respectively, 11 weeks and 15 weeks GA. ( b ) Schematic representation of the formation of a trisomic zygote through missegregation of chromosomes during maternal meiosis II. ( c ) Graphical representation of sequence data at loci heterozygous for the mother from the SNP-based targeted sequencing of maternal plasma at 11 weeks GA with a fetal DNA fraction estimated as f = 3.4%. Each green point corresponds to the fraction of the mother’s maternal allele reads at any of the 13,926 SNP loci that are consistent with heterozygous genotypes for the mother and were covered by more than 200 sequence fragments. The two black dotted lines represent the expected fractions of the mother’s maternal alleles in the case of a euploid fetus, and the three red dotted lines represent the expected fractions in the case of a fetus with trisomy of maternal origin. The blue line is a centered rolling mean across 200 consecutive heterozygous SNPs. The top bars represent the inferred inherited homologs of the fetus, with magenta, red, cyan, and blue colors representing, respectively, mother’s maternal, mother’s paternal, father’s maternal, and father’s paternal homologs. Chromosome 18, with three fetal homologs inferred, is highlighted in red. It is important to note that the algorithm to infer the inherited homolog segments takes also into account information about the homologs transmitted from the father of the fetus and allelic fractions at SNP loci consistent with homozygous genotype for the mother and which are not displayed in this figure and that the paternal homologs of the fetus further adds to the sampling noise at loci heterozygous for the mother.

Techniques Used: Targeted Sequencing, Microarray, Sequencing, Sampling

4) Product Images from "Single-nucleotide Differences and Cell Type Decide the Subcellular Localization of miRNA Isoforms (isomiRs), tRNA-derived Fragments (tRFs) and rRNA-derived Fragments (rRFs)"

Article Title: Single-nucleotide Differences and Cell Type Decide the Subcellular Localization of miRNA Isoforms (isomiRs), tRNA-derived Fragments (tRFs) and rRNA-derived Fragments (rRFs)

Journal: bioRxiv

doi: 10.1101/2022.08.22.503746

Overview of the Fraction-seq workflow 1. Three Triple Negative Breast Cancer (TNBC) cell lines BT-20, MDA-MB-231, and MDA-MB-468 were grown to ~200M cells and harvested. 2. From the same starting material, cells were separated into total, nuclear, cytoplasmic, mitochondrial, and mitoplast subcellular compartments. 3. The WES protein detection assay was used to analyze cell compartment markers in each cell fraction. 4. Short RNA-seq library preparation was carried out using NEBNext with 100 ng RNA from each sample followed by RNA sequencing using the Illumina NextSeq 500 platform at 75 cycles and an average depth of 30 million reads. 5. High quality short RNAs reads were mapped to isomiRs, tRFs, and rRFs and short RNAs between 18 and 50 nts and normalized to sequencing depth. Normalized reads with abundances greater than 10 RPM were further analyzed for the purpose of this study. 6. Northern blot analysis was used to confirm short RNAs identified by this study. Steps 1-5 were done using biological replicates (BT-20 – three replicates, MDA-MB-231 – three replicates, MDA-MB-468 4 replicates).
Figure Legend Snippet: Overview of the Fraction-seq workflow 1. Three Triple Negative Breast Cancer (TNBC) cell lines BT-20, MDA-MB-231, and MDA-MB-468 were grown to ~200M cells and harvested. 2. From the same starting material, cells were separated into total, nuclear, cytoplasmic, mitochondrial, and mitoplast subcellular compartments. 3. The WES protein detection assay was used to analyze cell compartment markers in each cell fraction. 4. Short RNA-seq library preparation was carried out using NEBNext with 100 ng RNA from each sample followed by RNA sequencing using the Illumina NextSeq 500 platform at 75 cycles and an average depth of 30 million reads. 5. High quality short RNAs reads were mapped to isomiRs, tRFs, and rRFs and short RNAs between 18 and 50 nts and normalized to sequencing depth. Normalized reads with abundances greater than 10 RPM were further analyzed for the purpose of this study. 6. Northern blot analysis was used to confirm short RNAs identified by this study. Steps 1-5 were done using biological replicates (BT-20 – three replicates, MDA-MB-231 – three replicates, MDA-MB-468 4 replicates).

Techniques Used: Multiple Displacement Amplification, Detection Assay, RNA Sequencing Assay, Sequencing, Northern Blot

5) Product Images from "Myeloid-to-mesenchymal NGF-p75 signaling coordinates skeletal cell migration during repair"

Article Title: Myeloid-to-mesenchymal NGF-p75 signaling coordinates skeletal cell migration during repair

Journal: bioRxiv

doi: 10.1101/2021.07.07.451468

Deletion of p75 in NMCCs inhibits cell migration and mineralization. Neonatal mouse calvarial cells (NMCCs) were isolated from p75 fl/fl mice and exposed to Adenoviral GFP (Ad-GFP) or Ad-Cre in vitro . (A) Ngfr expression by qRT-PCR among Ad-GFP- and Ad-Cre-treated cells after 72 hrs. (B) Cellular proliferation among Ad-GFP- and Ad-Cre-treated cells, by MTS assays at 72 h. (C) Apoptosis among Ad-GFP- and Ad-Cre-treated NMCCs by TUNEL assay. (D , E) Cellular migration assessed by (D) scratch wound healing assay at 14 h or (E) transwell assay at 4 h among Ad-GFP- and Ad-Cre-treated groups. Representative 100x images with percentage gap closure shown. (F) Osteogenic differentiation of Ad-GFP- and Ad-Cretreated NMCCs by Alizarin Red (AR) staining and quantification at 14 d. (G) Osteogenic gene expression among Ad-GFP- and Ad-Cre-treated NMCCs, including Runt-related transcription factor 2 ( Runx2 ), Osteocalcin ( Bglap ), and Collagen type 1 a1 ( Col1a1 ) at 7 d of differentiation. (H-L) Bulk total RNA sequencing (Illumina NextSeq 500 platform) among Ad-GFP- and Ad-Cre-treated NMCCs. (H) Differentially expressed genes (DEGs) of all 14,668 transcripts among Ad-Cre-treated NMCCs. Y-axis represents Log2 fold change (FC) for each gene. The number of upregulated DEGs (log2 FC ≥ 1, red dots) is 577, the number of downregulated DEGs (log2 fold change ≤ −1, green dots) is 399. (I) Principal component analysis among Ad-GFP- and Ad-Cretreated cells. (J) Unsupervised hierarchical clustering among Ad-GFP- and Ad-Cre-treated NMCCs. (K) DAVID functional GO analysis of biological processes enrichment among Ad- GFP- and Ad-Cre-treated NMCCs. (L) QIAGEN Ingenuity Pathway Analysis (IPA) identified representative pathways that were upregulated (Z-score > 0; red color) or downregulated (Z-score
Figure Legend Snippet: Deletion of p75 in NMCCs inhibits cell migration and mineralization. Neonatal mouse calvarial cells (NMCCs) were isolated from p75 fl/fl mice and exposed to Adenoviral GFP (Ad-GFP) or Ad-Cre in vitro . (A) Ngfr expression by qRT-PCR among Ad-GFP- and Ad-Cre-treated cells after 72 hrs. (B) Cellular proliferation among Ad-GFP- and Ad-Cre-treated cells, by MTS assays at 72 h. (C) Apoptosis among Ad-GFP- and Ad-Cre-treated NMCCs by TUNEL assay. (D , E) Cellular migration assessed by (D) scratch wound healing assay at 14 h or (E) transwell assay at 4 h among Ad-GFP- and Ad-Cre-treated groups. Representative 100x images with percentage gap closure shown. (F) Osteogenic differentiation of Ad-GFP- and Ad-Cretreated NMCCs by Alizarin Red (AR) staining and quantification at 14 d. (G) Osteogenic gene expression among Ad-GFP- and Ad-Cre-treated NMCCs, including Runt-related transcription factor 2 ( Runx2 ), Osteocalcin ( Bglap ), and Collagen type 1 a1 ( Col1a1 ) at 7 d of differentiation. (H-L) Bulk total RNA sequencing (Illumina NextSeq 500 platform) among Ad-GFP- and Ad-Cre-treated NMCCs. (H) Differentially expressed genes (DEGs) of all 14,668 transcripts among Ad-Cre-treated NMCCs. Y-axis represents Log2 fold change (FC) for each gene. The number of upregulated DEGs (log2 FC ≥ 1, red dots) is 577, the number of downregulated DEGs (log2 fold change ≤ −1, green dots) is 399. (I) Principal component analysis among Ad-GFP- and Ad-Cretreated cells. (J) Unsupervised hierarchical clustering among Ad-GFP- and Ad-Cre-treated NMCCs. (K) DAVID functional GO analysis of biological processes enrichment among Ad- GFP- and Ad-Cre-treated NMCCs. (L) QIAGEN Ingenuity Pathway Analysis (IPA) identified representative pathways that were upregulated (Z-score > 0; red color) or downregulated (Z-score

Techniques Used: Migration, Isolation, Mouse Assay, In Vitro, Expressing, Quantitative RT-PCR, TUNEL Assay, Wound Healing Assay, Transwell Assay, Staining, RNA Sequencing Assay, Functional Assay, Indirect Immunoperoxidase Assay

6) Product Images from "Chromosomal phase improves aneuploidy detection in non-invasive prenatal testing at low fetal DNA fractions"

Article Title: Chromosomal phase improves aneuploidy detection in non-invasive prenatal testing at low fetal DNA fractions

Journal: Scientific Reports

doi: 10.1038/s41598-022-14049-5

SNP-based targeted sequencing data with chromosomal phase. ( a ) Pedigree with parents and grandparents of the trisomy 18 fetus. MPSS data of DNA from saliva were available for the parents and microarray genotype data of DNA from saliva were available for the grandparents. Data from the SNP-based targeted sequencing and MPSS of maternal plasma using the Illumina Nextseq 500 platform were available at, respectively, 11 weeks and 15 weeks GA. ( b ) Schematic representation of the formation of a trisomic zygote through missegregation of chromosomes during maternal meiosis II. ( c ) Graphical representation of sequence data at loci heterozygous for the mother from the SNP-based targeted sequencing of maternal plasma at 11 weeks GA with a fetal DNA fraction estimated as f = 3.4%. Each green point corresponds to the fraction of the mother’s maternal allele reads at any of the 13,926 SNP loci that are consistent with heterozygous genotypes for the mother and were covered by more than 200 sequence fragments. The two black dotted lines represent the expected fractions of the mother’s maternal alleles in the case of a euploid fetus, and the three red dotted lines represent the expected fractions in the case of a fetus with trisomy of maternal origin. The blue line is a centered rolling mean across 200 consecutive heterozygous SNPs. The top bars represent the inferred inherited homologs of the fetus, with magenta, red, cyan, and blue colors representing, respectively, mother’s maternal, mother’s paternal, father’s maternal, and father’s paternal homologs. Chromosome 18, with three fetal homologs inferred, is highlighted in red. It is important to note that the algorithm to infer the inherited homolog segments takes also into account information about the homologs transmitted from the father of the fetus and allelic fractions at SNP loci consistent with homozygous genotype for the mother and which are not displayed in this figure and that the paternal homologs of the fetus further adds to the sampling noise at loci heterozygous for the mother.
Figure Legend Snippet: SNP-based targeted sequencing data with chromosomal phase. ( a ) Pedigree with parents and grandparents of the trisomy 18 fetus. MPSS data of DNA from saliva were available for the parents and microarray genotype data of DNA from saliva were available for the grandparents. Data from the SNP-based targeted sequencing and MPSS of maternal plasma using the Illumina Nextseq 500 platform were available at, respectively, 11 weeks and 15 weeks GA. ( b ) Schematic representation of the formation of a trisomic zygote through missegregation of chromosomes during maternal meiosis II. ( c ) Graphical representation of sequence data at loci heterozygous for the mother from the SNP-based targeted sequencing of maternal plasma at 11 weeks GA with a fetal DNA fraction estimated as f = 3.4%. Each green point corresponds to the fraction of the mother’s maternal allele reads at any of the 13,926 SNP loci that are consistent with heterozygous genotypes for the mother and were covered by more than 200 sequence fragments. The two black dotted lines represent the expected fractions of the mother’s maternal alleles in the case of a euploid fetus, and the three red dotted lines represent the expected fractions in the case of a fetus with trisomy of maternal origin. The blue line is a centered rolling mean across 200 consecutive heterozygous SNPs. The top bars represent the inferred inherited homologs of the fetus, with magenta, red, cyan, and blue colors representing, respectively, mother’s maternal, mother’s paternal, father’s maternal, and father’s paternal homologs. Chromosome 18, with three fetal homologs inferred, is highlighted in red. It is important to note that the algorithm to infer the inherited homolog segments takes also into account information about the homologs transmitted from the father of the fetus and allelic fractions at SNP loci consistent with homozygous genotype for the mother and which are not displayed in this figure and that the paternal homologs of the fetus further adds to the sampling noise at loci heterozygous for the mother.

Techniques Used: Targeted Sequencing, Microarray, Sequencing, Sampling

7) Product Images from "Identification of Key Genes and Pathways Associated with PIEZO1 in Bone-Related Disease Based on Bioinformatics"

Article Title: Identification of Key Genes and Pathways Associated with PIEZO1 in Bone-Related Disease Based on Bioinformatics

Journal: International Journal of Molecular Sciences

doi: 10.3390/ijms23095250

Gene expression profiles of GSE169261 ( A ), GSE139121 ( B ), GSE135282 ( C ), and GSE133069 ( D ) are visualized in volcano plots. DEGs are marked with red, and the criteria for a DEG are |log2FC| > 1.
Figure Legend Snippet: Gene expression profiles of GSE169261 ( A ), GSE139121 ( B ), GSE135282 ( C ), and GSE133069 ( D ) are visualized in volcano plots. DEGs are marked with red, and the criteria for a DEG are |log2FC| > 1.

Techniques Used: Expressing

Protein–protein interaction (PPI) analysis. PPI network for all the overlapping DEGs is constructed and followed by module analysis using the MCODE plugin on the Cytoscape (V.3.9.0) platform. Modules with a blue border are significant modules. The size of circles reflects the degree of connectivity.
Figure Legend Snippet: Protein–protein interaction (PPI) analysis. PPI network for all the overlapping DEGs is constructed and followed by module analysis using the MCODE plugin on the Cytoscape (V.3.9.0) platform. Modules with a blue border are significant modules. The size of circles reflects the degree of connectivity.

Techniques Used: Construct

8) Product Images from "Transcriptome of rhesus macaque (Macaca mulatta) exposed to total-body irradiation"

Article Title: Transcriptome of rhesus macaque (Macaca mulatta) exposed to total-body irradiation

Journal: Scientific Reports

doi: 10.1038/s41598-021-85669-6

Experimental and data analysis workflow. Longitudinally collected blood samples including: C (pre-irradiation), SD1 (day 1 post-irradiation), SD2 (day 2), SD3 (day 3), SD35 (day 35), SD60 (day 60) were collected from 7 NHPs for NextSeq 500 paired-end sequencing analyses and downstream bioinformatics analyses. Differential gene expression and functional pathway analysis were performed for gaining insight into radiation response in the survivors and non-survivors. Figure is created by the author using Microsoft PowerPoint ( https://www.microsoft.com/en-us/microsoft-365/powerpoint ).
Figure Legend Snippet: Experimental and data analysis workflow. Longitudinally collected blood samples including: C (pre-irradiation), SD1 (day 1 post-irradiation), SD2 (day 2), SD3 (day 3), SD35 (day 35), SD60 (day 60) were collected from 7 NHPs for NextSeq 500 paired-end sequencing analyses and downstream bioinformatics analyses. Differential gene expression and functional pathway analysis were performed for gaining insight into radiation response in the survivors and non-survivors. Figure is created by the author using Microsoft PowerPoint ( https://www.microsoft.com/en-us/microsoft-365/powerpoint ).

Techniques Used: Irradiation, Sequencing, Expressing, Functional Assay

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    Illumina Inc nextseq 500 platform
    Schematic circular representation of complete genome sequences of KPC‐2‐producing A. hydrophila GSH8‐2. Short paired‐end whole‐genome sequencing was performed using an Illumina <t>NextSeq</t> 500 platform with a 300‐cycle NextSeq 500 Reagent Kit v2 (2 × 150‐mer). The complete genome sequences of the strains were determined using a PacBio Sequel sequencer for long‐read sequencing [Sequel SMRT Cell 1 M v2 (4/tray]; Sequel sequencing kit v2.1; insert size, approximately 10 kb). De novo assembly was performed using Canu version 1.4 (Koren et al ., 2017 ), minimap version 0.2‐r124 (Li, 2016 ), racon version 1.1.0 (Vaser et al ., 2017 ) and circulator version 1.5.3 (Hunt et al ., 2015 ). Error correction of tentative complete circular sequences was performed using Pilon version 1.18 with Illumina short reads (Walker et al ., 2014 ). Annotation was performed in Prokka version 1.11 (Seemann, 2014 ), InterPro v49.0 (Finn et al ., 2017 ) and NCBI‐BLASTP/BLASTX. Circular representations of complete genomic sequences were visualized using GView server (Petkau et al ., 2010 ). AMR genes were identified by homology searching against the ResFinder database (Zankari et al ., 2012 ). The class 1 integron was assigned in the INTEGRALL database ( http://integrall.bio.ua.pt/ ) (Moura et al ., 2009 ). Visualization of comparative plasmid ORFs organization was performed using Easyfig (Sullivan et al ., 2011 ). For representation of chromosomal DNA, from the inside: slot 1, GC skew; slot 2, GC content; slot 3, ORFs; slot 4, rRNA/tRNA; slots 5–7, BLASTatlas conserved gene analysis indicating three relative strains (see also Supporting Information Fig. S1 ); slot 8, prophage; slot 9, notable ARGs or ARG‐related genes (transposase, ARGs and reductases). In representations of circular plasmids, notable ORFs are highlighted as the indicated colour.
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    86
    Illumina Inc rnaseq
    DELocal performance is not strongly dependent on the number of gene neighbours used in the analysis. Every gene is evaluated in relation to its neighbouring genes. In the absence of any “gold standard” for the number of neighbours, different numbers of nearest genes (within 1 Mb window) were used to identify the differentially expressed genes. The overall performances were measured using MCC. The performance of DELocal using <t>RNAseq</t> data was slightly better than with <t>microarray</t> data.
    Rnaseq, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Schematic circular representation of complete genome sequences of KPC‐2‐producing A. hydrophila GSH8‐2. Short paired‐end whole‐genome sequencing was performed using an Illumina NextSeq 500 platform with a 300‐cycle NextSeq 500 Reagent Kit v2 (2 × 150‐mer). The complete genome sequences of the strains were determined using a PacBio Sequel sequencer for long‐read sequencing [Sequel SMRT Cell 1 M v2 (4/tray]; Sequel sequencing kit v2.1; insert size, approximately 10 kb). De novo assembly was performed using Canu version 1.4 (Koren et al ., 2017 ), minimap version 0.2‐r124 (Li, 2016 ), racon version 1.1.0 (Vaser et al ., 2017 ) and circulator version 1.5.3 (Hunt et al ., 2015 ). Error correction of tentative complete circular sequences was performed using Pilon version 1.18 with Illumina short reads (Walker et al ., 2014 ). Annotation was performed in Prokka version 1.11 (Seemann, 2014 ), InterPro v49.0 (Finn et al ., 2017 ) and NCBI‐BLASTP/BLASTX. Circular representations of complete genomic sequences were visualized using GView server (Petkau et al ., 2010 ). AMR genes were identified by homology searching against the ResFinder database (Zankari et al ., 2012 ). The class 1 integron was assigned in the INTEGRALL database ( http://integrall.bio.ua.pt/ ) (Moura et al ., 2009 ). Visualization of comparative plasmid ORFs organization was performed using Easyfig (Sullivan et al ., 2011 ). For representation of chromosomal DNA, from the inside: slot 1, GC skew; slot 2, GC content; slot 3, ORFs; slot 4, rRNA/tRNA; slots 5–7, BLASTatlas conserved gene analysis indicating three relative strains (see also Supporting Information Fig. S1 ); slot 8, prophage; slot 9, notable ARGs or ARG‐related genes (transposase, ARGs and reductases). In representations of circular plasmids, notable ORFs are highlighted as the indicated colour.

    Journal: Environmental Microbiology Reports

    Article Title: Potential KPC‐2 carbapenemase reservoir of environmental Aeromonas hydrophila and Aeromonas caviae isolates from the effluent of an urban wastewater treatment plant in Japan

    doi: 10.1111/1758-2229.12772

    Figure Lengend Snippet: Schematic circular representation of complete genome sequences of KPC‐2‐producing A. hydrophila GSH8‐2. Short paired‐end whole‐genome sequencing was performed using an Illumina NextSeq 500 platform with a 300‐cycle NextSeq 500 Reagent Kit v2 (2 × 150‐mer). The complete genome sequences of the strains were determined using a PacBio Sequel sequencer for long‐read sequencing [Sequel SMRT Cell 1 M v2 (4/tray]; Sequel sequencing kit v2.1; insert size, approximately 10 kb). De novo assembly was performed using Canu version 1.4 (Koren et al ., 2017 ), minimap version 0.2‐r124 (Li, 2016 ), racon version 1.1.0 (Vaser et al ., 2017 ) and circulator version 1.5.3 (Hunt et al ., 2015 ). Error correction of tentative complete circular sequences was performed using Pilon version 1.18 with Illumina short reads (Walker et al ., 2014 ). Annotation was performed in Prokka version 1.11 (Seemann, 2014 ), InterPro v49.0 (Finn et al ., 2017 ) and NCBI‐BLASTP/BLASTX. Circular representations of complete genomic sequences were visualized using GView server (Petkau et al ., 2010 ). AMR genes were identified by homology searching against the ResFinder database (Zankari et al ., 2012 ). The class 1 integron was assigned in the INTEGRALL database ( http://integrall.bio.ua.pt/ ) (Moura et al ., 2009 ). Visualization of comparative plasmid ORFs organization was performed using Easyfig (Sullivan et al ., 2011 ). For representation of chromosomal DNA, from the inside: slot 1, GC skew; slot 2, GC content; slot 3, ORFs; slot 4, rRNA/tRNA; slots 5–7, BLASTatlas conserved gene analysis indicating three relative strains (see also Supporting Information Fig. S1 ); slot 8, prophage; slot 9, notable ARGs or ARG‐related genes (transposase, ARGs and reductases). In representations of circular plasmids, notable ORFs are highlighted as the indicated colour.

    Article Snippet: These isolates were then subjected to whole‐genome sequencing (WGS) as described previously (Sekizuka et al ., ), using an Illumina NextSeq 500 platform with a 300‐cycle NextSeq 500 Reagent Kit v2 (2 × 150‐mer).

    Techniques: Sequencing, Genomic Sequencing, Plasmid Preparation

    Gene expression analysis in PBMCs from MOG-AAD patients: Single cell RNA sequencing (inDrop) was performed on an untreated MOG-AAD patient#1 with 2 longitudinal samples, (1) Remission (MOG-AAD#1.2) and (2) Pre-relapse (MOG-AAD#1.3) as described in Materials and Methods. cDNA libraries were sequenced using the Illumina NextSeq 500 platform and analyzed following V3 Indrop criteria. After sequencing the raw BCL files were demultiplexed using bcl2fastq software by illumina ( https://support.illumina.com/sequencing/sequencing_software/bcl2fastq-conversion-software.html ). Reads obtained from bcl2fastq were further processed using the single-cell RNA-seq pipeline of the bcbio-nextgen ( https://bcbio-nextgen.readthedocs.io/en/latest/contents/pipelines.html#single-cell-rna-seq ) software suite. The scaled data was further clustered using Seurat and visualized using TSNE ( https://www.biorxiv.org/content/early/2018/11/02/460147 ). A Cluster analysis of a relapse and remission sample. B Differential expression of TNFAIP3 in the relapse and remission sample by single cell sequencing. Digital Gene Expression (DGE) sequencing was performed on an untreated MOG-AAD patient#1 with 3 longitudinal samples, (1) Rm (remission, MOG-AA#1.2), (2) PR (pre-relapse, MOG-AAD#1.3), and (3) R (relapse, MOG-AAD#1.4) as described in Materials and Methods. Raw BCL files generated through sequencing were further de-multiplexed using Picard ( https://github.com/broadinstitute/picard ) and the resulting FASTQ files where aligned to the human reference genome (GRCh38) using the STAR v2.4.2a 52 aligner. Further QC was done using the RNA-seQC 53 and transcript counts were produced using feature Counts function of the Subread package 54 . Data was normalized using the DESeq2 package 55 and the graphs were made using GraphPadPrism version 8.4.2 (464). C TNFAIP3 and NFκβ1 expression by DGE sequencing. NanoString Gene Expression Assay was performed on a MOG-AAD patient#2 with 3 longitudinal samples, (1) untreated R (relapse, MOG-AAD#2.1), (2) 8 months Rm/Ct (mycophenolate mofetil treated at remission, MOG-AAD#2.2), and (3) 11 months Rm/Ct (mycophenolate mofetil treated at remission, MOG-AAD#2.3) as described in Materials and Methods. Data were normalized and analyzed using nSolver software via the geometric mean of included housekeeping genes. The graphs were made using GraphPadPrism version 8.4.2 (464). D TNFAIP3 and TNF-α expression by NanoString Gene Expression Assay. qPCR was performed on CD4+ T cells from 7 MOG-AAD patients with longitudinal samples as described in Materials and Methods. It also included MOG-AAD patient#2 with 3 longitudinal samples as previously used for NanoString gene expression assay. The graphs were made using GraphPadPrism version 8.4.2 (464). E TNFAIP3 expression in MOG-AAD patient#2 by qPCR. F Grouped analysis of TNFAIP3 expression in relapse samples, remission samples and samples treated with corticosteroids by qPCR. Relapse n = 5, Remission n = 5, Steroid n = 4, Ordinary 1-way ANOVA; P = 0.0137.

    Journal: Scientific Reports

    Article Title: Identification of TNFAIP3 as relapse biomarker and potential therapeutic target for MOG antibody associated diseases

    doi: 10.1038/s41598-020-69182-w

    Figure Lengend Snippet: Gene expression analysis in PBMCs from MOG-AAD patients: Single cell RNA sequencing (inDrop) was performed on an untreated MOG-AAD patient#1 with 2 longitudinal samples, (1) Remission (MOG-AAD#1.2) and (2) Pre-relapse (MOG-AAD#1.3) as described in Materials and Methods. cDNA libraries were sequenced using the Illumina NextSeq 500 platform and analyzed following V3 Indrop criteria. After sequencing the raw BCL files were demultiplexed using bcl2fastq software by illumina ( https://support.illumina.com/sequencing/sequencing_software/bcl2fastq-conversion-software.html ). Reads obtained from bcl2fastq were further processed using the single-cell RNA-seq pipeline of the bcbio-nextgen ( https://bcbio-nextgen.readthedocs.io/en/latest/contents/pipelines.html#single-cell-rna-seq ) software suite. The scaled data was further clustered using Seurat and visualized using TSNE ( https://www.biorxiv.org/content/early/2018/11/02/460147 ). A Cluster analysis of a relapse and remission sample. B Differential expression of TNFAIP3 in the relapse and remission sample by single cell sequencing. Digital Gene Expression (DGE) sequencing was performed on an untreated MOG-AAD patient#1 with 3 longitudinal samples, (1) Rm (remission, MOG-AA#1.2), (2) PR (pre-relapse, MOG-AAD#1.3), and (3) R (relapse, MOG-AAD#1.4) as described in Materials and Methods. Raw BCL files generated through sequencing were further de-multiplexed using Picard ( https://github.com/broadinstitute/picard ) and the resulting FASTQ files where aligned to the human reference genome (GRCh38) using the STAR v2.4.2a 52 aligner. Further QC was done using the RNA-seQC 53 and transcript counts were produced using feature Counts function of the Subread package 54 . Data was normalized using the DESeq2 package 55 and the graphs were made using GraphPadPrism version 8.4.2 (464). C TNFAIP3 and NFκβ1 expression by DGE sequencing. NanoString Gene Expression Assay was performed on a MOG-AAD patient#2 with 3 longitudinal samples, (1) untreated R (relapse, MOG-AAD#2.1), (2) 8 months Rm/Ct (mycophenolate mofetil treated at remission, MOG-AAD#2.2), and (3) 11 months Rm/Ct (mycophenolate mofetil treated at remission, MOG-AAD#2.3) as described in Materials and Methods. Data were normalized and analyzed using nSolver software via the geometric mean of included housekeeping genes. The graphs were made using GraphPadPrism version 8.4.2 (464). D TNFAIP3 and TNF-α expression by NanoString Gene Expression Assay. qPCR was performed on CD4+ T cells from 7 MOG-AAD patients with longitudinal samples as described in Materials and Methods. It also included MOG-AAD patient#2 with 3 longitudinal samples as previously used for NanoString gene expression assay. The graphs were made using GraphPadPrism version 8.4.2 (464). E TNFAIP3 expression in MOG-AAD patient#2 by qPCR. F Grouped analysis of TNFAIP3 expression in relapse samples, remission samples and samples treated with corticosteroids by qPCR. Relapse n = 5, Remission n = 5, Steroid n = 4, Ordinary 1-way ANOVA; P = 0.0137.

    Article Snippet: 3,000 cells from a cell suspension comprising of CMCs from the 2 samples were isolated into droplets that contained lysis buffer. cDNA libraries were sequenced using the Illumina NextSeq 500 platform and analyzed following V3 Indrop criteria.

    Techniques: Expressing, RNA Sequencing Assay, Sequencing, Software, Generated, Produced, Real-time Polymerase Chain Reaction

    SNP-based targeted sequencing data with chromosomal phase. ( a ) Pedigree with parents and grandparents of the trisomy 18 fetus. MPSS data of DNA from saliva were available for the parents and microarray genotype data of DNA from saliva were available for the grandparents. Data from the SNP-based targeted sequencing and MPSS of maternal plasma using the Illumina Nextseq 500 platform were available at, respectively, 11 weeks and 15 weeks GA. ( b ) Schematic representation of the formation of a trisomic zygote through missegregation of chromosomes during maternal meiosis II. ( c ) Graphical representation of sequence data at loci heterozygous for the mother from the SNP-based targeted sequencing of maternal plasma at 11 weeks GA with a fetal DNA fraction estimated as f = 3.4%. Each green point corresponds to the fraction of the mother’s maternal allele reads at any of the 13,926 SNP loci that are consistent with heterozygous genotypes for the mother and were covered by more than 200 sequence fragments. The two black dotted lines represent the expected fractions of the mother’s maternal alleles in the case of a euploid fetus, and the three red dotted lines represent the expected fractions in the case of a fetus with trisomy of maternal origin. The blue line is a centered rolling mean across 200 consecutive heterozygous SNPs. The top bars represent the inferred inherited homologs of the fetus, with magenta, red, cyan, and blue colors representing, respectively, mother’s maternal, mother’s paternal, father’s maternal, and father’s paternal homologs. Chromosome 18, with three fetal homologs inferred, is highlighted in red. It is important to note that the algorithm to infer the inherited homolog segments takes also into account information about the homologs transmitted from the father of the fetus and allelic fractions at SNP loci consistent with homozygous genotype for the mother and which are not displayed in this figure and that the paternal homologs of the fetus further adds to the sampling noise at loci heterozygous for the mother.

    Journal: Scientific Reports

    Article Title: Chromosomal phase improves aneuploidy detection in non-invasive prenatal testing at low fetal DNA fractions

    doi: 10.1038/s41598-022-14049-5

    Figure Lengend Snippet: SNP-based targeted sequencing data with chromosomal phase. ( a ) Pedigree with parents and grandparents of the trisomy 18 fetus. MPSS data of DNA from saliva were available for the parents and microarray genotype data of DNA from saliva were available for the grandparents. Data from the SNP-based targeted sequencing and MPSS of maternal plasma using the Illumina Nextseq 500 platform were available at, respectively, 11 weeks and 15 weeks GA. ( b ) Schematic representation of the formation of a trisomic zygote through missegregation of chromosomes during maternal meiosis II. ( c ) Graphical representation of sequence data at loci heterozygous for the mother from the SNP-based targeted sequencing of maternal plasma at 11 weeks GA with a fetal DNA fraction estimated as f = 3.4%. Each green point corresponds to the fraction of the mother’s maternal allele reads at any of the 13,926 SNP loci that are consistent with heterozygous genotypes for the mother and were covered by more than 200 sequence fragments. The two black dotted lines represent the expected fractions of the mother’s maternal alleles in the case of a euploid fetus, and the three red dotted lines represent the expected fractions in the case of a fetus with trisomy of maternal origin. The blue line is a centered rolling mean across 200 consecutive heterozygous SNPs. The top bars represent the inferred inherited homologs of the fetus, with magenta, red, cyan, and blue colors representing, respectively, mother’s maternal, mother’s paternal, father’s maternal, and father’s paternal homologs. Chromosome 18, with three fetal homologs inferred, is highlighted in red. It is important to note that the algorithm to infer the inherited homolog segments takes also into account information about the homologs transmitted from the father of the fetus and allelic fractions at SNP loci consistent with homozygous genotype for the mother and which are not displayed in this figure and that the paternal homologs of the fetus further adds to the sampling noise at loci heterozygous for the mother.

    Article Snippet: Libraries were run on the Illumina NextSeq 500 platform with a high output, 300 cycle kit, with 159 base pairs paired-end sequence reads, to maximize the odds of overlapping an informative polymorphic locus.

    Techniques: Targeted Sequencing, Microarray, Sequencing, Sampling

    DELocal performance is not strongly dependent on the number of gene neighbours used in the analysis. Every gene is evaluated in relation to its neighbouring genes. In the absence of any “gold standard” for the number of neighbours, different numbers of nearest genes (within 1 Mb window) were used to identify the differentially expressed genes. The overall performances were measured using MCC. The performance of DELocal using RNAseq data was slightly better than with microarray data.

    Journal: PLoS Computational Biology

    Article Title: Chromosomal neighbourhoods allow identification of organ specific changes in gene expression

    doi: 10.1371/journal.pcbi.1008947

    Figure Lengend Snippet: DELocal performance is not strongly dependent on the number of gene neighbours used in the analysis. Every gene is evaluated in relation to its neighbouring genes. In the absence of any “gold standard” for the number of neighbours, different numbers of nearest genes (within 1 Mb window) were used to identify the differentially expressed genes. The overall performances were measured using MCC. The performance of DELocal using RNAseq data was slightly better than with microarray data.

    Article Snippet: Gene expression was measured both in microarray (platform: GPL6096, Affymetrix Mouse Exon Array 1.0) and RNAseq (platforms GPL19057, Illumina NextSeq 500).

    Techniques: Microarray

    Comparison of DELocal with earlier methods to identify differential expression. Evaluation matrices show that, except for recall (sensitivity), DELocal equals or outperforms earlier methods. However due to large number of true negatives, the significance scores of precision, F1 and MCC remained negligible. The evaluation matrices are explained in Materials and Methods section. The analysis was done using RNAseq data. For microarray data see S5 Fig .

    Journal: PLoS Computational Biology

    Article Title: Chromosomal neighbourhoods allow identification of organ specific changes in gene expression

    doi: 10.1371/journal.pcbi.1008947

    Figure Lengend Snippet: Comparison of DELocal with earlier methods to identify differential expression. Evaluation matrices show that, except for recall (sensitivity), DELocal equals or outperforms earlier methods. However due to large number of true negatives, the significance scores of precision, F1 and MCC remained negligible. The evaluation matrices are explained in Materials and Methods section. The analysis was done using RNAseq data. For microarray data see S5 Fig .

    Article Snippet: Gene expression was measured both in microarray (platform: GPL6096, Affymetrix Mouse Exon Array 1.0) and RNAseq (platforms GPL19057, Illumina NextSeq 500).

    Techniques: Expressing, Microarray

    Compared to other methods, DELocal is at least as powerful in detecting differentially expressed genes. Receiver operating characteristic (ROC) curves and areas under the curves (within the parenthesis) show that DELocal outperforms other methods on both microarray and RNAseq data.

    Journal: PLoS Computational Biology

    Article Title: Chromosomal neighbourhoods allow identification of organ specific changes in gene expression

    doi: 10.1371/journal.pcbi.1008947

    Figure Lengend Snippet: Compared to other methods, DELocal is at least as powerful in detecting differentially expressed genes. Receiver operating characteristic (ROC) curves and areas under the curves (within the parenthesis) show that DELocal outperforms other methods on both microarray and RNAseq data.

    Article Snippet: Gene expression was measured both in microarray (platform: GPL6096, Affymetrix Mouse Exon Array 1.0) and RNAseq (platforms GPL19057, Illumina NextSeq 500).

    Techniques: Microarray