Molecular ell, Volume 63 Supplemental Information Highly Sensitive and Robust Method for enome-wide hm Profiling of Rare ell Populations Dali Han, Xingyu Lu, lan H. Shih, Ji Nie, Qiancheng You, Meng Michelle Xu, ri M. Melnick, Ross L. Levine, and huan He
...6.8. ng ng ng ng cell cell hm-seal hm-seal D B E F hm-seal hm-seal cell cell ng ng ng ng Pearson's r % 8% 6% % % % hm-sealng ng cell Portion of tags in hm clusters Distinct reads (million) number of called hm peaks otal reads (million) hm-seal ng ng cell % 8% 6% % % % hm-seal ng ng cell 8 6 Portion of B-seq - validated peaks Figure S hm-seal nano-hm-seal μg rep μg rep ng rep ng rep ng rep ng rep cell rep cell rep Normalized hm reads B.. -k SS S k -k SS S k. H - - Distance to B-seq hm sites 3 Normalized hm reads...... hm low hm medium hm high Input - - Distance to oxrrbs hm Is nano-hm-seal rep nano-hm-seal rep Input Normalized hm reads
Figure S B 3 6 8 %m+hm MP MP MEP MEP hyper DMR 6 8 %m+hm hypo DMR hm MP hm MEP - - Distance to DMR Normalized hm reads - - Distance to DMR 9 8 7 6 3 6 3 MP MEP Normalized reads Normalized hm reads Normalized reads hm (log RPKM) -- Distance to DMR 7 -- Distance to DMR MP MP MEP MEP D hm LSK cells me3 H3K7 ac hm MP cells me3 H3K7 ac hm MP cells MEP cells me3 H3K7 ac hm me3 H3K7 ac ene expression E LSK hm (log RPKM) hm hm (log RPKM) (log RPKM) MP MP MEP (log RPKM) (log RPKM) me3 (log RPKM) H3K7c (log RPKM) -k SS S k -k SS S k -k SS S k -k SS S k 3 3 3 3 3 3 3 3 3 3 3
Figure S3 hm LSK MP MP MEP H3K7 me3 ac hm H3K7 me3 ac hm H3K7 me3 ac hm H3K7 me3 ac -.k.k -k k B hm -.k.k -k k LSK MP MP MEP MPP MP MP MEP -.k.k -k k me3 MPP MP MP MEP MPP MP MP MEP -.k.k -k k H3K7c MPP MP MP MEP I II III IV -k k -k k -k k cluster I cluster II cluster III cluster IV immune system development hemopoiesis leukocyte activation cell activation apoptotic mitochondrial changes nucleoside triphosphate metabolic histone modification peptidyl-lysine modification erythrocyte differentiation tetrapyrrole biosynthetic process leukocyte differentiation cell chemotaxis lymphocyte differentiation cell differentiation leukocyte migration carbohydrate derivative catabolic vacuole organization peptide hormone stimulus protein kinase negative regulation leukocyte activation 3 3 -lg(p-value) D -k k abnormal hematopoietic cell number abnormal immune system cell morphology abnormal leukocyte morphology abnormal adaptive immunity abnormal immune cell physiology decreased erythrocyte cell number reticulocytosis abnormal mean corpuscular volume hemolytic anemia abnormal erythroid progenitor cell morphology abnormal mononuclear cell differentiation abnormal myeloblast morphology/development abnormal lymphopoiesis abnormal B cell morphology abnormal cell differentiation -k k cluster I cluster II cluster III cluster IV abnormal mononuclear phagocyte morphology abnormal immune tolerance autoimmune response decreased cholesterol level abnormal acute inflammation 6 8 -lg(p-value)
Figure S L HS S HS MPP MP MP MF N Mono LP B D D8 NK MEP Ery EryB Log / NK cells Size: 7 () B cells Size: 87 8 Erythroid Progenitors Size: 66 6 Erythroid Size: 66 Lymphoid Progenitors Size: 66 ommon Size: 799 Myeloid Size: 673 Myeloid Progenitors Size: 866 Progenitors Size: 6337 Normalized hm reads 8 6 -% -% % % % % anyon F3 mpp W mpp Input B hm loss region hm gain region Motif Factor P-value Motif Factor P-value EV e-63 ER e-9 ata e-8 ata e-6 ES e- PU.-IRF e-7 SpiB e-6 PU. e-6 IRF e-96 ELF e-8 EWS:ER e- ata e-3 IRF e-6 IRF e-6 Fli e-3 BP e-8 EHF e- S e-7 S e- ES e-3
Supplementary Figure Legends Figure S. lobal comparison of conventional hm-seal and nano-hm-seal sequencing data Related to Figure ( and B) verage profiles () and heatmap (B) across gene regions ±, bp for nano-hm-seal libraries. Each row represents a gene, ordered by the mean value signals. Regular hm-seal libraries were generated from μg genomic DN and used as references. () enome-wide correlations (,bp tiling windows) of sequencing results obtained using conventional hm-seal and nano-hm-seal (with ng and ng DN as well as genomic DN isolated from, cells). (D) Fraction of reads located in hm high-density clusters for libraries constructed using different amounts of input DN. (E) Preseq library complexity curves for different libraries. (F) he number of high confident hm-enriched peaks (right axis) called from different libraries and the portion of peaks validated by B-seq hm sites (left axis). he hm-enriched peaks were considered as validated if B-seq detected hm sites reside in the area of bp surrounding the peak center. () he distribution of nano-hm-seal (ng) signals at hm sites detected by B-seq. hm sites were further divided into low ( - %), medium ( - %), high (% and above) subgroups (, sites were randomly selected for each subgroup) (H) he distribution of nano-hm-seal (ng) signals at 6 hm-containing Is detected by ox-rrbs method. Figure S. hm levels correlate with DN methylation and with histone marks in HS and progenitor cells Related to Figure () Boxplot to show the level of DN modification (m+hm) at hypo (upper) and hyper (lower) DMRs. (B-) he distribution of hm (B) and () signals at hypo (upper) and hyper (lower) DMRs. (D) Heatmap displaying the reads density distribution of hm and indicated histone modifications in all annotated genes ordered by decreasing expression in LSK, MP, MP cells and MEP cells. Each row represents a gene. Due to lack of LSK histone modification data in published datasets, LSK hm data was compared with histone modification data obtained from MPP cells. (E) Scatter plot displaying the correlation of hm with,, e3 and H3K7ac in LSK, MP, MP cells and MEP cells. Each dot represents a gene. Due to lack of LSK histone modification data in published dataset, LSK hm data was compared with histone modification data obtained from MPP cells. ll values are represented as log RPKM. he spearman rank correlation coefficient is shown (ρ) in each comparison.
Figure S3. he distribution of hm and histone modifications at selected genomic regions Related to Figure () Heatmap displaying read densities of -seq, hm and histone modifications around the -seq signal-enriched peaks. -seq peaks were divided into four clusters by k-means clustering and ranked according to decreased signal values. Due to lack of LSK histone modification data in the published dataset, LSK -seq and hm data were compared with histone modification data obtained from MPP cells. (B) Heatmap displaying read densities of hm,,, me3 and H3K7c around DhMRs across differentiation stages. lusters were generated by k-means clustering of hm signals. Histone modification datasets were arranged to match the order of hm heatmap. (-D) Functional annotation of DhMRs in each cluster was performed using RE. he top over-represented categories belonging to ene Ontology biological process () and Mouse enome Informatics phenotype ontology (D) are shown. he x axis values correspond to the log-transformed binomial P-values. Figure S. he relationship between hm and functional regulatory elements in W or ML model mice Related to Figure and Figure 3 () he activity of lineage specific enhancers during hematopoiesis. Heatmap showing lineage-specific hematopoiesis enhancers with k-means cluster analysis of signals (K=9). he genomic location of hematopoietic enhancers and hip-seq dataset were obtained from a previously published study (Lara-stiaso et al., ). K-mean cluster analysis is performed by R package pheatmap. (B) op enriched known transcription factor binding motifs detected at DhMRs (left: hm loss; right: hm gain) in MPP cells. Motif information was obtained from the Homer motif database. () Normalized distribution profiles of hm in MPP cells across DN methylation canyon regions detected in hematopoietic stem cells. he genomic location of DN canyon was obtained from a previously published study (Jeong et al., ).
ables: Summary statistics for the nano-hm-seal sequencing experiments. Related to Figure Sample rawreads mappedreads mapratio UniqueReads UniqueRatio mes_ng_ 779389 7.96 876.69 mes_ng_ 7978 69896.96 8333.6 mes_ng_ 967 678.9 986.3 mes_ng_ 37 8676.9 869.8 mes_cell_ 37777 9876.9 7367. mes_cell_ 33867 3338.9 678. mes_ng_input 39 968.9 787.9 mes_ng_input 66 3639.67 7677.87 mes_cell_input 7699 6773.6 3769.86 hematopoiesis_cmp_ 6636 9679.9 96899.77 hematopoiesis_cmp_ 363 3767.9 77387.77 hematopoiesis_cmp_3 3669 89679.93 36.7 hematopoiesis_gmp_ 9 637768.9 77.7 hematopoiesis_gmp_ 683 6663.93 3.87 hematopoiesis_gmp_3 9978 33.93 9.9 hematopoiesis_lsk_ 78 69887.9 3669.8 hematopoiesis_lsk_ 669 6339.93 9763.83 hematopoiesis_lsk_3 39979 87963.9 8873.8 hematopoiesis_mep_ 873798 786.93 363. hematopoiesis_mep_ 86 8898.9 8636336.6 hematopoiesis_mep_3 67 87938.9 37. hematopoiesis_input 86986 3936.8 3896778.9 leukemia_f3 gmp 898 799.9 7.8 leukemia_f3 mpp 93699 8389.9 689.8 leukemia_f3 gmp 966.9 93.8 leukemia_f3 mpp 93338 86398.9 3699.8 leukemia_f3_3_gmp 63 97.9 33798.69 leukemia_f3_3_mpp 9898 8797.9 7.8 leukemia_w gmp 68 378.9 783.89 leukemia_w mpp 8698 78.9 78688.8 leukemia_w gmp 3867 3893.9 87.9 leukemia_w mpp 863368 997.96 7638.88 leukemia_w_3_gmp 868 98886.93 697.8 leukemia_w_3_mpp 3899 377.9 96.7 leukemia_w gmp 887 337.9 73877.8 leukemia_w mpp 989389 933.93 879333.88 leukemia_w gmp 767368 989.9 668.8 leukemia_w mpp 88 9783.9 9886.76 leukemia_f3_gmp_input 9877 86667.88 83936.98 leukemia_f3_mpp_input 688 3796.89 7369.7 leukemia_w_mpp_input 77 897.9 773778.98
References Jeong, M., Sun, D., Luo, M., Huang, Y., hallen,.., Rodriguez, B., Zhang, X., havez, L., Wang, H., Hannah, R., et al. (). Large conserved domains of low DN methylation maintained by Dnmt3a. Nature genetics 6, 7-3. Lara-stiaso, D., Weiner,., Lorenzo-Vivas, E., Zaretsky, I., Jaitin, D.., David, E., Keren-Shaul, H., Mildner,., Winter, D., Jung, S., et al. (). Immunogenetics. hromatin state dynamics during blood formation. Science 3, 93-99.