br Experimental design materials and methods Rad reference

Experimental design, materials and methods Rad51 reference sequences for each organism were downloaded from UniProt [5] (http://www.uniprot.org/). Rad51 UniProt sequence identifiers and the corresponding GenBank accession numbers for each of the represented species can be found in Table 1. Using these amino tegaserod sequences, a multiple sequence alignment was performed using MUSCLE (3.8) [6,7] (www.ebi.ac.uk/Tools/msa/muscle/). A percent identity matrix was prepared using data retrieved from Clustal2.1 [8] (www.ebi.ac.uk/). A neighbor-joining tree was assembled from the multiple sequence alignment data using the Jukes-Cantor genetic distance model and edited using Geneious 9.1.5 (www.geneious.com).
Acknowledgements This work was supported by the National Institutes of Health Grant R01GM098510 (MS).
Data The dataset of this article provides information on the Cyr61 and IL-8 expression in skin lesion in psoriasis patients (Figs. 1 and 2) and the change of the production of Cyr61 by specific siRNA in vitro and anti-Cyr61mAb in vivo (Figs. 3 and 4).
Experimental design, materials and methods
Funding sources This work was funded by National Natural Science Foundation of China (81473682, 81402618), Excellent Young Doctor Foundation of Shanghai Ninth People׳s Hospital (201608), Education Ministry Research Fund for the Doctoral Program (20130073110003), Science and Technology Commission of Shanghai Municipality (13JC1402300) and Shanghai Cultivate Outstanding Young Teachers in Colleges and Universities Scientific Research Fund (JDY09062).
Data The data shown in the article give information on the criteria of patients´ selection and the criteria for choosing genes to be studied as candidate biomarkers for these diseases in peripheral samples. The specific western-blot method for the analysis of MSR1 expression on protein extracted from PBMCs is provided. Table 1 provides a list of candidate genes to be validated as relevant biomarkers and Table 2 summarize the possible biomarkers that differentiate asthmatic and allergic phenotypes.
Experimental design, materials and methods
Funding sources This work was supported in part by research grants PI13/01730 co-supported by FEDER, CIBERES (ISCIII, 0013) and Biobank (PT13/0010/0012) from the Fund for Health Research (Spanish Ministry of Economy and Competitiveness). S. Baos was supported by CIBERES (ISCIII, 0013) and Conchita Rábago Foundation. D. Calzada by Conchita Rábago Foundation, Madrid, Spain. L. Cremades was supported by a contract from MINECO (PEJ-2014-A-31609, Sistema de Garantía Juvenil), cofinanced by European Social Fund (ESF) and Youth Employment Initiative (YEI).
Acknowledgements We are grateful to the funders of this work and to Oliver Shaw for English corrections.
Data The transcriptome sequencing from the spleen tissue of one-year-old (cis1) and three-year-old (cis3) grass carp was performed using Illumina paired-end sequencing technology. The dataset of this paper comprises ten data files that were generated from the KEGG annotation analysis and differential gene expression analysis of the transcriptome sequence above. The unigene expression levels are presented in File 1. The significantly differentially expressed unigenes between the cis1 and cis3 library are presented in File 2. The significant enrichment GO terms and KEGG pathways of DEGs are presented in Files 3 and 4, respectively. Information of the transcripts involved in the T-cell receptor signaling pathway, B-cell receptor signaling pathway, Toll-like receptor signaling pathway, antigen-processing and presentation, complement cascades, and chemokine signaling pathway are summarized on six files from Files 5 to 10, respectively.
Experimental design, materials and methods
Acknowledgements This work was supported by Grants from the National Natural Science Foundation of China (No. 31572356). We thank Majorbio (Shanghai, China) for help with bioinformatic analysis.