/KI_Strunz_Bjorkstrom

Primary LanguageRGNU General Public License v3.0GPL-3.0

Continuous human uterine NK cell differentiation in response to endometrial regeneration and pregnancy

Benedikt Strunz1,‡, Jonna Bister1, Hanna Jönsson1, Iva Filipovic1, Ylva Crona-Guterstam1,2,3, Egle Kvedaraite1,4, Natalie Sleiers1, Bogdan Dumitrescu5, Mats Brännström6, Antonio Lentini7, Björn Reinius7, Martin Cornillet1, Tim Willinger1, Sebastian Gidlöf3,8, Russell S. Hamilton9,10, Martin A. Ivarsson1 & Niklas K. Björkström1,‡

1 Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
2Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
3 Department of Obstetrics and Gynecology, Karolinska University Hospital Huddinge, Stockholm, Sweden
4 Childhood Cancer Research Unit, Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm, Sweden
5 Department of Obstetrics and Gynecology, Mälarsjukhuset, Eskilstuna, Sweden
6 Department of Obstetrics and Gynecology, University of Gothenburg, Gothenburg, Swedenn
7 Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
8 Department of Obstetrics and Gynecology, Stockholm South General Hospital, Stockholm, Sweden
9 Centre for Trophoblast Research, University of Cambridge, Cambridge, UK
10 Department of Genetics, University of Cambridge, Cambridge, UK
Corresponding authors: benedikt.strunz@ki.se, niklas.bjorkstrom@ki.se

Publication

Strunz, B., Bister, J., Jönsson, H., Filipovic, I., Crona-Guterstam, Y., Kvedaraite, E., Sleiers, N., Dumitrescu, B., Brännström, M., Lentini, A., Reinius, B., Cornillet, M., Willinger, T., Gidlöf, S., Hamilton, R.S., Ivarsson, M.A., & Björkström, N.K. (2021) Continuous human uterine NK cell differentiation in response to endometrial regeneration and pregnancy. Science Immunology, 6, eabb7800 [Science Immunology] [DOI]

Abstract

On publication

Bulk RNA-Seq

RNA-seq data have been deposited in the ArrayExpress database at EMBL-EBI under accession number E-MTAB-8709

Sample Table

Sample Name Group
1_HU12_P11 CD39+KIR+
2_HU12_P9 CD39-KIR-
3_HU12_P10 CD39-KIR+
5_HU13_P11 CD39+KIR+
6_HU13_P9 CD39-KIR-
7_HU13_P10 CD39-KIR+
9_Hu05_P11 CD39+KIR+
10_Hu05_P9 CD39-KIR-
11_Hu05_P10 CD39-KIR+
14_Hu7_P12 CD39+KIR+
15_Hu7_P13 CD39-KIR+
16_Hu7_P9 CD39-KIR-

Data Processing

Raw sequencing files are run through quality control using FastQC (v0.11.5) and fastq_screen (v0.9.3). Low quality and adapter sequencing are trimmed with Trim Galore! (v0.6.4). Trimmed reads are aligned to the reference genome (GRCh38, ensEMBL) using STAR (v020201). Alignments are assessed using qualimap (v2.2) and featureCounts (v 1.5.0-p2). Gene quantification is performed with featureCounts (v 1.5.0-p2). Differential gene expression is performed with DESeq2 package (v1.22.2, R v3.5.3), including principle component analysis (PCA) to assess sample clustering, and multiple testing correction to produce false discovery rates. Finally all metrics from the RNA-Seq pipelines are summarised and reports produced using MultiQC (0.9.dev0).

Additional Processing Steps

Additional filtering steps were applied in order to focus on the high confidence DEGs. First, genes with exceeding inter-donor variation were excluded if the calculated CV2 (Anders & Huber 2010) surpassed a cut-off of CV2 >1.95 in the subset with highest read count. Next, genes with a mean expression of <10 reads were excluded and a FDR adjusted p-value <0.05 was used for determining significant DEGs.

Resources Used

Resource URL
GRCh38 Link
FastQC Link
Trim_galore Link
STAR DOI
HTSeq-counts DOI
Feature_counts DOI
Qualimap DOI
RSeQC DOI
ClusterFlow DOI
MultiQC DOI
Bulk RNA-Seq Pipeline

Pipeline run using ClusterFlow

#fastqc
#fastq_screen
#trim_galore
      #fastqc
      #star
        #qualimap_rnaseq
        #rseqc_infer_experiment
        #featureCounts
        #htseq_counts

FeatureCount gene count files are available in the FeatureCount directory

Script to reproduce paper figures (Bulk RNA-Seq only)

The R script used to generate the figures in the paper is RSH_KI_0001.QC.R available to download. Required R-packages are listed at the top of the file and must be installed prior to running the script.

Figure File Description
Figure 2 F
[PDF] [PNG]
A. PCA for top 500 most variable genes
Figure 2 G (left)
[PDF] [PNG]
Volcano plot for KIR+CD39+ Vs KIR-CD39-
Figure 2 G (right)
[PDF] [PNG]
Volcano plot for KIR+CD39+ Vs KIR+CD39-
Figure S2 A
[PDF] [PNG]
B. PCA Principle components explained
Figure S2 B
[PDF] [PNG]
Heatmap summarising differentially expressed genes from the three comparisons
Figure S2 C
[PDF] [PNG]
Volcano plot for KIR+CD39- Vs KIR-CD39-

Tables of differentially expressed genes (Bulk RNA-Seq only)

Normalised read counts [CSV]

Comparison Raw DEGs CV2 Filtered CV2 and MeanMax Filtered
Hu_CD39mKIRp_vs_Hu_CD39mKIRm [CSV] [CSV] [CSV]
Hu_CD39pKIRp_vs_Hu_CD39mKIRm [CSV] [CSV] [CSV]
Hu_CD39pKIRp_vs_Hu_CD39mKIRp [CSV] [CSV] [CSV]

Session Information

Details for the R version and packages used to create all figures

> sessionInfo()
R version 3.4.4 (2018-03-15)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS  10.14.6

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] eulerr_5.1.0               RColorBrewer_1.1-2         pheatmap_1.0.12            Cairo_1.5-10               ggforce_0.3.1             
 [6] biomaRt_2.34.2             DESeq2_1.18.1              SummarizedExperiment_1.8.1 DelayedArray_0.4.1         Biobase_2.38.0            
[11] GenomicRanges_1.30.3       GenomeInfoDb_1.14.0        IRanges_2.12.0             S4Vectors_0.16.0           BiocGenerics_0.24.0       
[16] reshape2_1.4.3             reshape_0.8.8              useful_1.2.6               matrixStats_0.55.0         Matrix_1.2-17             
[21] cowplot_0.9.4              ggrepel_0.8.1              ggplot2_3.2.1              dplyr_0.8.3                tidyr_1.0.0               

loaded via a namespace (and not attached):
 [1] bitops_1.0-6           bit64_0.9-7            progress_1.2.2         httr_1.4.1             tools_3.4.4            backports_1.1.4       
 [7] R6_2.4.0               rpart_4.1-15           Hmisc_4.2-0            DBI_1.0.0              lazyeval_0.2.2         colorspace_1.4-1      
[13] nnet_7.3-12            withr_2.1.2            tidyselect_0.2.5       gridExtra_2.3          prettyunits_1.0.2      curl_4.2              
[19] bit_1.1-14             compiler_3.4.4         htmlTable_1.13.2       labeling_0.3           scales_1.0.0           checkmate_1.9.4       
[25] genefilter_1.60.0      stringr_1.4.0          digest_0.6.21          foreign_0.8-72         XVector_0.18.0         base64enc_0.1-3       
[31] pkgconfig_2.0.3        htmltools_0.3.6        htmlwidgets_1.3        rlang_0.4.0            rstudioapi_0.10        RSQLite_2.1.2         
[37] farver_1.1.0           BiocParallel_1.12.0    acepack_1.4.1          RCurl_1.95-4.12        magrittr_1.5           GenomeInfoDbData_1.0.0
[43] Formula_1.2-3          Rcpp_1.0.2             munsell_0.5.0          lifecycle_0.1.0        stringi_1.4.3          yaml_2.2.0            
[49] MASS_7.3-51.4          zlibbioc_1.24.0        plyr_1.8.4             grid_3.4.4             blob_1.2.0             crayon_1.3.4          
[55] lattice_0.20-38        splines_3.4.4          annotate_1.56.2        hms_0.5.1              locfit_1.5-9.1         zeallot_0.1.0         
[61] knitr_1.25             pillar_1.4.2           geneplotter_1.56.0     XML_3.98-1.20          glue_1.3.1             latticeExtra_0.6-28   
[67] data.table_1.11.8      vctrs_0.2.0            tweenr_1.0.1           gtable_0.3.0           purrr_0.3.2            polyclip_1.10-0       
[73] assertthat_0.2.1       xfun_0.9               xtable_1.8-4           survival_2.44-1.1      tibble_2.1.3           AnnotationDbi_1.40.0  
[79] memoise_1.1.0          cluster_2.1.0

Links

Description URL
Publication [Science Immunology] [DOI]
Raw Data ArrayExpress EMBL-EBI E-MTAB-8709
Björkström Group Björkström group website
CTR Bioinformatics CTR-BFX

Contact

Contact Russell S. Hamilton (rsh46 -at- cam.ac.uk) for bioinformatics related queries