r – Differences in the design models in DESeq2 and its interpretation

I am using DEseq2 and trying to understand the results obtained using different models.
I have the data design as

    sample genotype time
1   WT_S1       WT   T1
2   WT_S2       WT   T1
3   WT_S3       WT   T1
4   WT_S4       WT   T2
5   WT_S5       WT   T2
6   WT_S6       WT   T2
7   KO_S1       KO   T1
8   KO_S2       KO   T1
9   KO_S3       KO   T1
10  KO_S4       KO   T2
11  KO_S5       KO   T2
12  KO_S6       KO   T2

I have 3 models.

model1 : ~genotype

model2 : ~time

model3 : ~genotype + time

I get 200 genes as significant using model1 and another 198 genes as significant from model2. However when I use model3, I don’t have any significant genes. I would like to know what samples are being compared when using model 3.

ie, what samples are being compared in model3 when getting results using (obj3, name=”genotype_KO_vs_WT”)? How is it different from model1?

Also,what samples are being compared in model3 when getting results using results(obj2, name=”time_T2_vs_T1″) ? How is it different from model2?