install.packages("showtext") install.packages("ggsci") install.packages("devtools") library("devtools") install_github('fawda123/ggord') library("ggord") library("showtext") library("ggplot2") library("vegan") library("ggsci") library("RColorBrewer") BiocManager::install("futile.matrix") library("futile.matrix") font_add_google("Poppins", "Poppins") font_add_google("Roboto Mono", "Roboto Mono") showtext_auto() setwd("path") #db_RDA - variables explaining microbiome variation cov<-read.csv("coverage_quebec_order_transposase_qb_mg_edit.csv", header = T, row.names = 1) met<-read.csv("metadata_relative_abundance_edit2.csv",header=T, row.names = 1) met2<-read.csv("metadata_relative_abundance_edit.csv",header=T, row.names = 1) gen<-read.csv("coverage_quebec_order_transposase_change_values_sort.csv", header=T, row.names = 1) gen2<-gen[apply(gen[,-1], 1, function(x) !all(x==0)),] cov2<-cov[apply(cov[,-1], 1, function(x) !all(x==0)),] #1- Presence-absence table dist<-vegdist(gen2, method = "jaccard", binary=T) db_RDA<-capscale(dist~genotype+Site+pH+Temperature+mcy_genes+Years+Months, met) db_RDA2<-capscale(cov2~genotype+Site+pH+Temperature+mcy_genes+Years+Months, met2, dist = "bray", sqrt.dist= TRUE) ordiR2step(rda(cov2~1, data=met2), scope= formula(db_RDA2), direction= "forward", R2scope=TRUE, pstep=1000) ordiR2step(rda(gen2~1, data=met), scope= formula(db_RDA), direction= "forward", R2scope=TRUE, pstep=1000) db_RDA_sign<-capscale(dist~genotype+Years+Months, met) db_RDA_sign2<-capscale(cov2~genotype+Years+Months+Temperature, met2,dist = "bray", sqrt.dist= TRUE ) (R2adj <- RsquareAdj(db_RDA_sign)$adj.r.squared) (R2adj <- RsquareAdj(db_RDA_sign2)$adj.r.squared) anova.cca(db_RDA_sign, step=1000) anova.cca(db_RDA_sign, step=1000, by="axis") anova.cca(db_RDA_sign2, step=1000) anova.cca(db_RDA_sign2, step=1000, by="axis") beta.jac <- betadisper(dist, met$genotype, type='centroid') plot(beta.jac,hull = FALSE, ellipse = TRUE) beta.jac <- betadisper(dist, met$Site, type='centroid') beta.jac <- betadisper(dist, met$mcy_genes, type='centroid') OTU<-otu_table(gen2,taxa_are_rows = FALSE) meta = sample_data(met) genseq<-phyloseq(OTU,meta) distgen = phyloseq::distance(genseq, "jaccard", binary=TRUE) NMDS_test=metaMDS(distgen,k=2,trymax=1000) #pcoa=ordinate(genseq, "PCoA", distance=distgen) #2- Using a coverage table OTU2<-otu_table(cov2,taxa_are_rows = FALSE) meta2 = sample_data(met2) genseq2<-phyloseq(OTU2,meta2) distgen2 = sqrt(phyloseq::distance(genseq2, "bray")) NMDS_test2=metaMDS(distgen2,k=2,trymax=1000) #pcoa=ordinate(genseq, "PCoA", distance=distgen) n <- 20 qual_col_pals = brewer.pal.info[brewer.pal.info$category == 'qual',] col_vector = unlist(mapply(brewer.pal, qual_col_pals$maxcolors, rownames(qual_col_pals))) pie(rep(1,n), col=sample(col_vector, n)) plot_ordination(genseq2, NMDS_test2, color = "genotype") + theme_bw() + scale_colour_manual(values = col_vector) + geom_point(size = 2) + theme(axis.text.x = element_text(vjust=0.5, size=12), axis.text.y = element_text(vjust=0.5, size=12), axis.title.x = element_text(size = 15, face="bold", color="black"),axis.title.y = element_text(size=15,face="bold",color="black")) adonis(distgen2 ~ genotype, as(sample_data(genseq2), "data.frame")) adonis(distgen2 ~ mcy_genes, as(sample_data(genseq2), "data.frame")) adonis(distgen2 ~ Site, as(sample_data(genseq2), "data.frame")) adonis(distgen2 ~ Years, as(sample_data(genseq2), "data.frame")) adonis(distgen2 ~ Months, as(sample_data(genseq2), "data.frame")) adonis(distgen2 ~ pH, as(sample_data(genseq2), "data.frame")) adonis(distgen2 ~ Temperature, as(sample_data(genseq2), "data.frame")) betatax=betadisper(distgen2,data.frame(sample_data(genseq2))$genotype) p=permutest(betatax) p$tab betatax=betadisper(distgen2,data.frame(sample_data(genseq2))$Site) p=permutest(betatax) p$tab betatax=betadisper(distgen2,data.frame(sample_data(genseq2))$mcy_genes) p=permutest(betatax) p$tab betatax=betadisper(distgen2,data.frame(sample_data(genseq2))$Years) p=permutest(betatax) p$tab betatax=betadisper(distgen2,data.frame(sample_data(genseq2))$Months) p=permutest(betatax) p$tab betatax=betadisper(distgen2,data.frame(sample_data(genseq2))$Temperature) p=permutest(betatax) p$tab #Variables explaining Microcystis genotype variation Micro<-read.csv("coverage_filter_edit_transpose_edit_all_factors_remove_NA.csv", header=T, row.names = 1) db_RDA<-capscale(Micro[,12:25]~., Micro[,1:10],dist = "bray", sqrt.dist= TRUE) ordiR2step(rda(Micro[,12:25]~1, data=Micro[,1:10]), scope= formula(db_RDA), direction= "forward", R2scope=TRUE, pstep=1000) db_RDA_sign<-capscale(Micro[,12:25]~Years+Months, Micro[,1:10],dist = "bray", sqrt.dist= TRUE) (R2adj <- RsquareAdj(db_RDA_sign)$adj.r.squared) anova.cca(db_RDA_sign, step=1000) anova.cca(db_RDA_sign, step=1000, by="axis") OTU3<-otu_table(Micro[,12:25],taxa_are_rows = FALSE) meta3 = sample_data(Micro[,1:10]) genseq3<-phyloseq(OTU3,meta3) distgen3 = sqrt(phyloseq::distance(genseq3, "bray")) NMDS_test3=metaMDS(distgen3,k=2,trymax=1000) #pcoa=ordinate(genseq, "PCoA", distance=distgen) plot_ordination(genseq3, NMDS_test3, color = "Years") + theme_bw() + scale_colour_manual(values = col_vector) + geom_point(size = 2) + theme(axis.text.x = element_text(vjust=0.5, size=12), axis.text.y = element_text(vjust=0.5, size=12), axis.title.x = element_text(size = 15, face="bold", color="black"),axis.title.y = element_text(size=15,face="bold",color="black")) adonis(distgen3 ~ Years, as(sample_data(genseq3), "data.frame")) adonis(distgen3 ~ Months, as(sample_data(genseq3), "data.frame")) adonis(distgen3 ~ Period, as(sample_data(genseq3), "data.frame")) adonis(distgen3 ~ Site, as(sample_data(genseq3), "data.frame")) adonis(distgen3 ~ Total_Phosphorus_ug, as(sample_data(genseq3), "data.frame")) adonis(distgen3 ~ Total_Nitrogen_mg, as(sample_data(genseq3), "data.frame")) adonis(distgen3 ~ Cumulative_precipitation_t1_t7_mm, as(sample_data(genseq3), "data.frame")) adonis(distgen3 ~ Dissolved_P, as(sample_data(genseq3), "data.frame")) adonis(distgen3 ~ Dissolved_N, as(sample_data(genseq3), "data.frame")) adonis(distgen3 ~ Mean_temperature_t0_t7, as(sample_data(genseq3), "data.frame")) betatax=betadisper(distgen3,data.frame(sample_data(genseq3))$Years) p=permutest(betatax) p$tab betatax=betadisper(distgen3,data.frame(sample_data(genseq3))$Months) p=permutest(betatax) p$tab betatax=betadisper(distgen3,data.frame(sample_data(genseq3))$Period) p=permutest(betatax) p$tab #quantification phylosymbiosis OTU2<-otu_table(cov2,taxa_are_rows = FALSE) meta2 = sample_data(met2) genseq2<-phyloseq(OTU2,meta2) distgen2 = sqrt(phyloseq::distance(genseq2, "bray")) dist_micro<-read.csv("distance_microcystis_genotype_tree_sorted.csv",sep=",", row.names=1) dist_micro2<-as.matrix(dist_micro) dist_micro3<-arrange(sqrt(dist_micro2)) distgen3<-as.matrix(distgen2) distgen4<-arrange(distgen3) mantel(dist_micro3,distgen4, method = "spearman") proct<-protest(distgen4,dist_micro3)