The ZNF800 gene is between 127373344bp and 127391557bp on the reverse strand of Chromosome 7, locus 7q31.33, spanning a total of 18214 base pairs.
ZNF800 contains 6 functioning C2H2 zinc finger protein domains, a number of SNP's, and multiple experimentally-shown phosphorylation[2][3][4] and SUMOylation sites.
[5][6][7][8][9] ZNF800 is in the neighborhood of PAX4,[10] which plays an important role in the differentiation and development of pancreatic islet beta cells.
ZNF800 is ubiquitously expressed in at least 27 different tissues, with the largest amounts in bone marrow, testis, and lymph nodes.
Several different tools were used on ExPASy Proteomics to analyze ZNF800 for likely protein modification sites, unique composition, and localization.
The likely sites of Phosphorilation, O-Glycosilation, Sumoylation, and O-ß-GlcNAc attachment are detailed below: (N/A when applied to whole protein) pat4: RKPK (4) at 473 pat4: RRKR (5) at 529 pat7: none bipartite: RRGVRRHIRKVHKKKME at 242 bipartite: KRDVIRHITVVHKKSSR at 531 content of basic residues: 17.8% NLS Score: 1.27 RRGVRRHIRKVH at 232
When multiple sequence alignments were made, the zinc finger binding domains were the areas with the most conservation.
Based on the found E values of the protein with its orthologs in the aforementioned categories using NCBI Blast,[23] ZNF800 is at least 930 Millions of years old.
At first it was hypothesized that ZNF800 has an Ortholog in fungus, dating back to 1150 Millions of years ago, however, a BLAT[10] search of the fungus sequence in the human domain gave no results, which lead to the conclusion that these sequences are not similar enough to prove they are truly related.
The most common transcription factors with high probability (>0.84) of binding ZNF800 promoter are shown in the figure.
There are 4 existing patents mention ZNF800 in lists of 100s-1000s, which address concepts such as “prostate cancer progression”, “progression risk of glaucoma”, “method for inducing pluripotency in human somatic cells”, and “modifying transcriptional regulatory networks in stem cells”.