Additional file 4: of Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing

Supplementary methods. SV calling processes for 69 SV detection algorithms used in this study. (PDF 430 kb

Additional file 2: of Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing

Figure S13. Effect of read length, read coverage, and insert size on recall and precision for various SV algorithms. (PDF 2174 kb

Additional file 3: of Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing

Table S5. Recall and precision of SV-calling results with the simulated data (Sim-A, Sim-MEI, Sim-NUMT, Sim-VEI). Table S6. Recall and precision of SV-calling results with the real data (NA12978 data1 or PacBio-data1). Table S7. Recall and precision of SV-calling results with the real data (NA12978 data2 or PacBio-data2). Table S8. Recall and precision of SV-calling results with the real data (NA12978 data3 or PacBio-data3). Table S9. Recall and precision of SV-calling results with the real data (NA12978 data4 or PacBio-HG002). Table S10. SV calling results (recall, precision, Mendelian inheritance error, mean, and standard error) obtained with the four (or three) NA12878 real datasets. (including the numerical data of Fig. 3 and Additional file 1: Figures S3–S5). Table S11. Recall and precision of SV-calling results with the HG00514 real data. Table S14. Root mean squared errors of breakpoints (BPs) and lengths of called SVs for SV detection algorithms. Table S16. Recall and precision of SVs commonly called between a pair of SV detection algorithms with the simulated and the NA12878 real datasets. Table S17. Mean precision and recall of overlapped calls for each algorithm and for each SV category. Table S18. Fold change of precision and recall of overlapped calls between algorithm pair for the four (or three) sets of NA12878 real data. (XLSX 1162 kb

Additional file 1: of Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing

Figures S1-S12, Figures S14-S23, and Tables S1-S4, S12, S13, S15, S19, S20. (PDF 1464 kb

Neutrophils Are Essential As A Source Of Il-17 In The Effector Phase Of Arthritis

<div><p>Objective</p><p>Th17 has been shown to have a pivotal role in the development of arthritis. However, the role of IL-17 in the T cell-independent effector phase has not fully been examined. We investigated whether IL-17 is involved in the effector phase of arthritis by using K/BxN serum-induced arthritis model.</p><p>Methods</p><p>K/BxN serum was transferred into IL-17 knockout (KO) mice, SCID mice and their control mice, and arthritis was evaluated over time. In order to clarify the source of IL-17 in the effector phase, neutrophils or CD4+ T cells collected from IL-17 KO or control mice were injected into IL-17 KO recipient mice together with K/BxN serum. To examine if neutrophils secrete IL-17 upon stimulation, neutrophils were stimulated with immune complex in vitro and IL-17 in the supernatant was measured by ELISA.</p><p>Results</p><p>K/BxN serum-induced arthritis was much less severe in IL-17 KO mice than in WT mice. Since K/BxN serum-transferred SCID mice developed severe arthritis with high serum IL-17 concentration, we speculated neutrophils are the responsible player as an IL-17 source. When wild type (WT) but not IL-17 KO neutrophils were co-injected with K/BxN serum into IL-17 KO mice, arthritis was exacerbated, whereas co-injection of WT CD4+ T cells had no effect. In vitro, stimulation of neutrophils with immune complexcaused IL-17 secretion.</p><p>Conclusions</p><p>Neutrophils are essential as a source of IL-17 in the effector phase of arthritis. The trigger of secreting IL-17 from neutrophils may be immune complex.</p></div

Serological and Progression Differences of Joint Destruction in the Wrist and the Feet in Rheumatoid Arthritis - A Cross-Sectional Cohort Study - Fig 2

<p>(A) Comparison of joint destruction of the wrist and the feet in the duration of the disease. Larsen grade of the feet was significantly higher than that of the wrist in the first subgroup (p<0.001). (B) Comparison of difference of the joint destruction between the wrist and the feet in Larsen grade. <i>P</i> < 0.001.</p

Serological and Progression Differences of Joint Destruction in the Wrist and the Feet in Rheumatoid Arthritis - A Cross-Sectional Cohort Study

<div><p>Objective</p><p>To investigate clinical and radiological differences between joint destruction in the wrist and the feet in patients with RA.</p><p>Methods</p><p>A cross-sectional clinical study was conducted in an RA cohort at a single institution. Clinical data included age, sex and duration of disease. Laboratory data included sero-positivity for anti-cyclic citrullinated peptide (CCP) antibody and RF. Radiological measurements included Larsen grades and the modified Sharp/van der Heijde method (SHS) for the hands/wrists and the feet. Statistical analyses were performed using the Kruskal—Wallis H-test, a dummy variable linear regression model and multivariate logistic regression analysis with 95% confidence interval and odds ratios.</p><p>Results</p><p>A total of 405 patients were enrolled, and 314 patients were analysed in this study. The duration of disease in the foot-dominant group was significantly less than that in the wrist-dominant group. When patients were subdivided by duration of disease, the Larsen grade of the feet was significantly higher than that of the wrist in the first quadrant subgroup, but this was reversed with increasing duration of disease. Anti-CCP status was a significant predictive factor for joint destruction in the wrist but not in the feet, while RF status was not predictive in either the wrist or the feet.</p><p>Conclusions</p><p>Joint destruction in the feet started earlier than in the wrist, but the latter progresses faster with increasing duration of disease. Anti-CCP status predicts joint destruction in the wrist better than in the feet.</p></div

HsInv0379 genotyping and frequency in different populations.

<p>Number of individuals genotyped by PCR across inversion breakpoints, tag SNPs in high linkage disequilibrium with the inversion, and sequence reads spanning inversion breakpoints (BreakSeq). The number of unrelated individuals genotyped is also given together with genotype counts and allelic frequencies for each analyzed population.</p

Analysis of the new fusion transcript in HsInv0379 breakpoint.

<p><b>A.</b> RNA-Seq reads mapped to an AC construct corresponding to BP1 (vertical red arrow) in an inverted chromosome reveal a fusion transcript present only in the four <i>Std</i>/<i>Inv</i> individuals (bottom) but not in the four <i>Std</i>/<i>Std</i> (top). Boxes highlight the new exon (yellow) and <i>ZNF257</i> first exon (green). The structure of the fusion transcript reconstructed by Cufflinks [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005495#pgen.1005495.ref038" target="_blank">38</a>] is shown below the RNA-Seq profiles. Small arrows indicate the approximate position of the primers used to validate the transcript. The coordinates of the new exon in the HG19 reference genome are also indicated. <b>B.</b> Analysis of fusion transcript expression by RT-PCR in several individuals. <b>C.</b> Quantification of the fusion transcript levels by qPCR in 15 <i>Std</i>/<i>Std</i>, 11 <i>Std</i>/<i>Inv</i>, and 1 <i>Inv/Inv</i> individuals.</p

Inversion features and genotyping strategies.

<p>Horizontal lines represent the standard (<i>Std</i>, top) and inverted (<i>Inv</i>, bottom) arrangements. Genes are depicted as grey arrows indicating direction of transcription with the disrupted gene shown in red. Blue vertical arrows mark the two inversion breakpoints (BP1 and BP2). The black bar below the <i>Std</i> chromosome indicates the sequence included in the analyzed fosmid containing BP1 in the inverted orientation. Primers used for PCR genotyping are shown in the corresponding breakpoint of each arrangement as small black arrows. The three tag SNP alleles are shown next to the corresponding chromosome. Sanger chromatograms show the sequence of inversion breakpoints in the <i>Inv</i> chromosome.</p