Priv014996.2


Basic Information
Transcription Factor Domain
Sequence Information
Similer Transcription Factors

Basic Information

Insect
Pedicia rivosa
Gene Symbol
egg
Assembly
GCA_963082725.1
Location
OY720154.1:42052793-42059180[+]

Transcription Factor Domain

TF Family
MBD
Domain
MBD domain
PFAM
PF01429
TF Group
Unclassified Structure
Description
The Methyl-CpG binding domain (MBD) binds to DNA that contains one or more symmetrically methylated CpGs [2]. DNA methylation in animals is associated with alterations in chromatin structure and silencing of gene expression. MBD has negligible non-specific affinity for DNA. In vitro foot-printing with MeCP2 showed the MBD can protect a 12 nucleotide region surrounding a methyl CpG pair [2]. MBDs are found in several Methyl-CpG binding proteins and also DNA demethylase [1].
Hmmscan Out
# of c-Evalue i-Evalue score bias hmm coord from hmm coord to ali coord from ali coord to env coord from env coord to acc
1 1 2.6e-15 7.2e-12 45.0 0.0 6 74 1269 1332 1265 1335 0.90

Sequence Information

Coding Sequence
ATGGGTCCTGTATTGACGACTACAGAAAAACGTGATACAATCAACACTAATATTAGATCAATACCCACAGTTCCTACTGAAAGCGAACCCCTTTCTAATGCTTCAAGAACTGACAATATAGAGGGCgataattatgaaaaagaaTCGGTTGTAAAAGCTCCAATAATTACCAAAGATTTGATCGGTATAGCGTCTCCCGATAATATAGTTTTGACGGAAAGAGTATATGATTCCGCACTAGAAGAGACTACTGTAAAAGATGGTTTAGATATTTCTACTGATGATATTATGATAATAGATGATTCTATAGAAGATATTAAAGTAATTCCGcgattaaatattaatttgaaagaaattaaaaaactagAAACTTCAACAGATACTTCATATAATGAGGATGTGATGATTATAGATGATCCTGATCCAATTTTAGAAGCTTTGACAAAAGAATCTACTTCTATAGATAATGTTTCTCCTTTAACTCCAATTTTGAAATCAAGtactgaaaataaaacaactgaTGATTCTGATGATATAATGATTATTGATGATATACCAGCAGAACccgaaattattaatttagctgatgacgatgatgatgaagaagaaaatattaatactaCAAAAATTGCAGATTATAAAGTTACAGAAATTAAGGTAGATACAGatgaaattatgaatattGATGAAATACTTGGTCCAATTCCAACAAATCCAGGAAGTCCAAATACAGCAAACCTTGAGCTTGATGTTTTAAGTAATGACCAAATGATTTTTGATAATGATGAACCAATGAAGCAAATAAATACAGTAAAAGAAATTGTACAAGAAAGAATTAGTGAAACTTATCAAACAGAAGTAGAAAAATCAGATGCTAAAATTCAATCTATAGGAAAAGATAAAGAATCCGTACAAATTGGTTTGGAAAAGGATGTGAATATGCCTGAAATTGATGTTACATGTAGAGAATCAGTTGATATAAGTGATGatgaagaatttattttgaaggAATCTGAGAAAAATGTAATAGAGGATCACAAAATTAGAGAGAAAACCATGACTGAAGACATTTCcgtagaaaaagaaaataataatttattagaaaatgaCAAAAGTTCAGagataataaaacaaaaaaataaaaatatagaaatcgAAACGGAGAAAAGTGATTTAATAGAATCTAAAAAAGATGGGGAATTAGATAATTTACCCACCAAAAATACTGAATCTGAATCAGCAATTCAAAATCTGTTATctttatataagaataaagaatGCAATCAGGATAAAGAATGTAATAAGGATAAAGAATGCAAATTAAATACAACCgaagaaacaattttattagaaagTTCAACAAATTTTCTGGATCAGGAAATCATAAAGCCGATTAAAGAATTATCGATGACAATTGAAGTAAAAGAAACTGAAAAAGatgaattaaatgataaatCCGAATctgaaaaagataaagaaaaaacacttTATGATTTTCCGGAAAATCTCACTTCCGAATGGATCAAACTGActaaagaaatggaaaaattggCTGATGAACCGAAAAAATTAGATGACAACATAGAAAAATTAACTGATGAAATCCAAAAATTATGTGATGAATCgacaaaattatttgatgatACACAACACGAAAGTAGAAAATTAATAGACAGATCTATGGAATATATGGAAACAGATGGTGATaataaagaacagaaaaagGCAATAGAagaactgaaaataaaatctataaaatatgatgaaaaaattaatattaatgaatCTGAACAGGGAAAAAGTAAtattacacaaaatattaatgataCAATATCAATTTCCGTTGATACAAGTGATGATTCTGACAACGAAAAATCTAATAAGGATATAAAGAAACTAgatgaaaaaatgttaaatcaaaacaaagaaataataagaacaaTTCAAAATACAGTAAATgctataaatgaaataataacaattgaTGATACTGATGataattcaaaaaatgtatcattactaagaaataaattaacagAAGTGACTAACGAACAAAATGTTGATGAgcagaaaattataaaacaactaACCGAGAATGtagttgaaaaagaaaaacaacgtGAATgcgttaattttgtttgtaaaaataaaagtagtGTTTTTCATTTGGCAccattatttgttttaagttattatggaattaaaaagaaaccaaaaaaattacaattcgTTTGTTCTGATTGTTTTGATCAAACTGTGGATCAATATGAGGAACTTTGTGGTGCGTTAGTTAATCACCAACCCTTACTACAACAAAATTTACCAAAACAAGCTGATTTAGTTGAAATATCAAGTagtgacgatgatgatgaagatcaTGACGAATCATTTAaagatacaaattttttatcattagaGGATATACAAgtattaaaagataatttagACGATATTTTACCTGAAACATTAAAACGTGTTTCAATTAATCAGCAAATGGAATGGAATACACAATTATTAACAGAATCatttaatcaaaatcaaaaaatttTAGAAGAATTGGAAGAAAGTGTTCGAGTATTACAAAAAGGAGCTGATCAAATGCATTTTACACTTTATAATATACAAGAAAGTTTCACAATTAAACGGTTACCTCCTGTTAATTTAGATTCTGATTGTATTGAACATACAGAACCATTTGAgTTTCCAGTTGAAGGTAAACTACAACGTCCACAAATAAATAGTGTAGATGATTATTTGGCAGCACACAAAACAAATGTATCATGGACTTCTTGTAAAGTGACTGAAATTATTGAAAGTGTAATATTACTCAGAGTTAATGGTAAAATAGTATTCAATTATAAAGTACAATTTTTAAGACAAAAAGGAATcgtaattaaaatgttaagtGGTAAAAATTTGGCATATGGAAATCCATCAATTGAACGTTATCCAATTGGTTGCAGGGTGATTGCATCATTTAATTCTGATAAGATTTCAGAGAAAAAGTTCAACAATTCTCAAGTGAATAGAACACATTATTTTCCGGGAATTGTTGCTGAGCCAATACAaccaaatacaaattttcgATATCTGATATTTTTTGATGATGGTTATACAAGTTATATAAGTCATGAAAATATACGTCTTGTTTGTGATTCATCAGCAAATGTATGGGAAGATGTATTAGAAGGTTCCAGAGAATTTATACATGAATATTTAATGGAAAGTGATCAACGTGCAATGGTACAAGTTAAAAAGGGACAACGTATTGTTACAGAATATAAAGGGATATGGTTACCAGCAAAAGTAACAGATATTGACTGTAGTTTAgtacaattatattttgaagAGGACAAACGTTATGAATGGATTTATCGTGGGTCAATGAGATTAGCACCATTATTTCGTgagaaacaaaattcaaaacttGCTACTGGAACACAATTACTTAAACGTAATGAACCATATATTGAATACATTACAATAACTGAAGATTTCCGCCCGAAACCACCTAAAGTTATACCTGAAGTGAAAGAACTCAACCCCCCAATAGCACCAAAAGAAATACCAAAAGCTATTCCAAACCGTGCTGTTGCAAAGAAAAGTACAGTCGTTAATCAAATTGTAAGGCCACAATTACCAATATCACTAAATCGGTCAACAATTGTTGTTGATGCAACGACCCAACCTGGAAAGATAACATATTTTACGGTTAAAAAACCTCGTGCACCATTACAATATCAAGTACACAATTGCAATCCTCGTTGCTTATATCAAGTTACAGATAATTTAACGCCATATAGTCCATTGGCGAAACCTTTATTATCAGGTTGGGAACGacaaattCCAACAACTCGTacatctaaaaaaaaagtgatcaTTTATAAAGGTCCATGTGGTAAACGTATGAGAAATATGCACGAATTACACCATTATCTTCGAGTTACAAAATCACCACTAAATGTTGaatgttttgattttgatgTACAAGTATATTGCCTAGCTGAATGGACAGTTGATAAACAATTCATAAGAAATcagGATTTATCCGATGGATTGGAAGAAATAGCAATATCATGTGTTAATTGTTTTGGTACCTCATTACCACCACCATGTATTTATTCAACGAAACGTGTGCCAACTGAGGGTGTGAACCTTAATTTAGATCAAAACTTTTTATGCGGCTGTGATTGTATTGATGATTGTTTGGATAAAACGAAATGCCAATGTTGGCAATTAACAATAGCTGgtgcaaaattaaaaaatgcaaatatACCAAATCATCAAATCGGTTATGAATTTAAACGTTTATTAGATCCTGTACCTACTGGTATATATGAATGCAATGCACGATGTAAATGCAATAGCCGTTGTATTAACCGTGTTGTCCAACATCCTCTTAATATAAAGTTACAAGTTTTTAAAACCAGAAATCGCGGATGGGGCTTGCGTACGATTAACGATATACCAAAAGGTGGTTTTATTTGCATATATGCGGGTCACTTATTAACTGAACAAAGGGCTAATGaaggTGGTGCAACAGATGGTGATGAATATTTTGCGGAATTGGATTATATTGAAGTGGTTGAACGTCTTAAAGAAGGTTATGAATCGGATATACCTGAGGAGGGTTTAGAAGATAGTAGCAGTGAGTCGGATAAAGAACAGCAAGCCAGCCTTGACCATAGTATGGATTCAGATACAGAATTTAAAGCAAATTTATCAGAACGTGCTCGTAAAACAATGAAAACTCGTTCAAGTACAAGAAAATTAACTACTGGACAAAAAAGTATTAATCagttatttaatgaaaaacaatcAACATCATCAAGTGATAAAAATGACgttgaaaaagataaaaataaatcaatggTGGTCGATGATTGCATTACAATATCAGATGATGAAGATGtAAGAGTGCCAGTAAATTTTATGCCGGATTCATCATTATTAGATTTGAATGATGATGAAGTACAATCTAAATATAAATCTGTGAGAAAAATGTATGGAAAAAATGAATACAGTTTTATAATGGACGCAAAGAAGACTGGAAATGTTGGACGTTATTTTAATCATTCATGTCAGCCAAATCTATTTGTTCAAAATGTATTTGTGGACACACATGATTTGCGTTTTCCATGGGTTGCGTTCTTTTCAAGTGAACCTATACGAGCAGGTACAGAATTAACATggaattataattatgatgTTGGTAGTGTTCCTGGGAAAGTGTTGTTTTGTGAATGTGGTGCTCTATCATGTCGCGGTCGTTTGCTATAA
Protein Sequence
MGPVLTTTEKRDTINTNIRSIPTVPTESEPLSNASRTDNIEGDNYEKESVVKAPIITKDLIGIASPDNIVLTERVYDSALEETTVKDGLDISTDDIMIIDDSIEDIKVIPRLNINLKEIKKLETSTDTSYNEDVMIIDDPDPILEALTKESTSIDNVSPLTPILKSSTENKTTDDSDDIMIIDDIPAEPEIINLADDDDDEEENINTTKIADYKVTEIKVDTDEIMNIDEILGPIPTNPGSPNTANLELDVLSNDQMIFDNDEPMKQINTVKEIVQERISETYQTEVEKSDAKIQSIGKDKESVQIGLEKDVNMPEIDVTCRESVDISDDEEFILKESEKNVIEDHKIREKTMTEDISVEKENNNLLENDKSSEIIKQKNKNIEIETEKSDLIESKKDGELDNLPTKNTESESAIQNLLSLYKNKECNQDKECNKDKECKLNTTEETILLESSTNFLDQEIIKPIKELSMTIEVKETEKDELNDKSESEKDKEKTLYDFPENLTSEWIKLTKEMEKLADEPKKLDDNIEKLTDEIQKLCDESTKLFDDTQHESRKLIDRSMEYMETDGDNKEQKKAIEELKIKSIKYDEKININESEQGKSNITQNINDTISISVDTSDDSDNEKSNKDIKKLDEKMLNQNKEIIRTIQNTVNAINEIITIDDTDDNSKNVSLLRNKLTEVTNEQNVDEQKIIKQLTENVVEKEKQRECVNFVCKNKSSVFHLAPLFVLSYYGIKKKPKKLQFVCSDCFDQTVDQYEELCGALVNHQPLLQQNLPKQADLVEISSSDDDDEDHDESFKDTNFLSLEDIQVLKDNLDDILPETLKRVSINQQMEWNTQLLTESFNQNQKILEELEESVRVLQKGADQMHFTLYNIQESFTIKRLPPVNLDSDCIEHTEPFEFPVEGKLQRPQINSVDDYLAAHKTNVSWTSCKVTEIIESVILLRVNGKIVFNYKVQFLRQKGIVIKMLSGKNLAYGNPSIERYPIGCRVIASFNSDKISEKKFNNSQVNRTHYFPGIVAEPIQPNTNFRYLIFFDDGYTSYISHENIRLVCDSSANVWEDVLEGSREFIHEYLMESDQRAMVQVKKGQRIVTEYKGIWLPAKVTDIDCSLVQLYFEEDKRYEWIYRGSMRLAPLFREKQNSKLATGTQLLKRNEPYIEYITITEDFRPKPPKVIPEVKELNPPIAPKEIPKAIPNRAVAKKSTVVNQIVRPQLPISLNRSTIVVDATTQPGKITYFTVKKPRAPLQYQVHNCNPRCLYQVTDNLTPYSPLAKPLLSGWERQIPTTRTSKKKVIIYKGPCGKRMRNMHELHHYLRVTKSPLNVECFDFDVQVYCLAEWTVDKQFIRNQDLSDGLEEIAISCVNCFGTSLPPPCIYSTKRVPTEGVNLNLDQNFLCGCDCIDDCLDKTKCQCWQLTIAGAKLKNANIPNHQIGYEFKRLLDPVPTGIYECNARCKCNSRCINRVVQHPLNIKLQVFKTRNRGWGLRTINDIPKGGFICIYAGHLLTEQRANEGGATDGDEYFAELDYIEVVERLKEGYESDIPEEGLEDSSSESDKEQQASLDHSMDSDTEFKANLSERARKTMKTRSSTRKLTTGQKSINQLFNEKQSTSSSDKNDVEKDKNKSMVVDDCITISDDEDVRVPVNFMPDSSLLDLNDDEVQSKYKSVRKMYGKNEYSFIMDAKKTGNVGRYFNHSCQPNLFVQNVFVDTHDLRFPWVAFFSSEPIRAGTELTWNYNYDVGSVPGKVLFCECGALSCRGRLL

Similar Transcription Factors

Sequence clustering based on sequence similarity using MMseqs2

100% Identity
-
90% Identity
-
80% Identity
-