Converting the values in all columns to a certain value in tibble/dplyr

I have a tibble object and I want to replace all of the columns except certain ones with a value (say NA or 0). I can able to do it without pipes %>% but how can I do it with %>%?

library(tibble)  
dtf <- tibble(id = c('12', '22', '33', '40'),
              x1 = c(0, 2, 3, 4),
              a2 = c(1, 0, 3, 0),
              c5 = c('a', 'b', 'c', 'd'))

# This raises an error:
dtf %>% select(-id) <- NA

Error in dtf %>% select(-id) <- NA : could not find function "%>%<-"

# This works:
dtf[, colnames(dtf) != 'id'] <- NA
dtf
# A tibble: 4 x 4
  id    x1    a2    c5   
  <chr> <lgl> <lgl> <lgl>
1 12    NA    NA    NA   
2 22    NA    NA    NA   
3 33    NA    NA    NA   
4 40    NA    NA    NA 

I believe I should use mutate() or mutate_all() but I couldn't figure out. One similar SO answer offered na_if() for NA values but I cannot make it work for this case.