MEME

Search sequence databases for the best combined matches with these motifs using MAST.
Search sequence databases for all matches with these motifs using FIMO.
Submit these motifs to BLOCKS multiple alignment processor.

MEME - Motif discovery tool

MEME version 4.3.0 (Release date: Sat Sep 26 01:51:56 PDT 2009)

For further information on how to interpret these results or to get a copy of the MEME software please access http://meme.sdsc.edu.

This file may be used as input to the MAST algorithm for searching sequence databases for matches to groups of motifs. MAST is available for interactive use and downloading at http://meme.sdsc.edu.

REFERENCE

If you use this program in your research, please cite:

Timothy L. Bailey and Charles Elkan, "Fitting a mixture model by expectation maximization to discover motifs in biopolymers", Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology, pp. 28-36, AAAI Press, Menlo Park, California, 1994.

TRAINING SET

DATAFILE= memeout/meme.fasta
ALPHABET= ACDEFGHIKLMNPQRSTVWY
Sequence name	Weight	Length	Sequence name	Weight	Length
Bacillus_subtilis	1.0000	222	Helicobacter_pylori	1.0000	223
Haemophilus_parainfluenzae	1.0000	225	Oceanimonas	1.0000	204
Desulfovibrio_africanus	1.0000	213	Geobacter	1.0000	484
Taylorella_asinigenitalis	1.0000	213	Oxalobacter_formigenes	1.0000	203
Cyanobacterium	1.0000	338	Cyanothece	1.0000	339
Dysgonomonas_gadei	1.0000	212	Pelodictyon_phaeoclathratiforme	1.0000	207
Chloroflexus_aggregans	1.0000	221	Rubrobacter_xylanophilus	1.0000	208
Treponema	1.0000	216	Fusobacterium_mortiferum	1.0000	210
Sulfurihydrogenibium_yellowstonense	1.0000	204	Aminobacterium_colombiense	1.0000	207
Akkermansia_muciniphila	1.0000	204	Fibrobacter_succinogenes	1.0000	210
Saccharomyces_cerevisiae	1.0000	540	Clavispora_lusitaniae	1.0000	505
Aspergillus_terreus	1.0000	518	Coccidioides_immitis	1.0000	587
Sordaria_macrospora	1.0000	523	Cryptococcus_gattii	1.0000	537
Cucumis_sativus	1.0000	384	Arabidopsis_thaliana	1.0000	522
Physcomitrella_patens	1.0000	510	Volvox_carteri	1.0000	1251
Thalassiosira_pseudonana	1.0000	323	Phaeodactylum_tricornutum	1.0000	580
Perkinsus_marinus	1.0000	297	Xenopus(Silurana)	1.0000	321
Trichoplax_adhaerens	1.0000	214	Naegleria_gruberi	1.0000	497
Acanthamoeba_castellanii	1.0000	463	Candida_tropicalis	1.0000	482
Lodderomyces_elongisporus	1.0000	553	Selaginella_moellendorffii	1.0000	527

COMMAND LINE SUMMARY

This information can also be useful in the event you wish to report a
problem with the MEME software.

command: meme memeout/meme.fasta -mod zoops -nmotifs 3 -prior dirichlet -nostatus -protein -oc memeout/

model:	mod=	zoops	nmotifs=	3	evt=	inf
object function= E-value of product of p-values
width:	minw=	8	maxw=	50	minic=	0.00
width:	wg=	11	ws=	1	endgaps=	yes
nsites:	minsites=	2	maxsites=	40	wnsites=	0.8
theta:	prob=	1	spmap=	pam	spfuzz=	120
em:	prior=	dirichlet	b=	0.01	maxiter=	50
	distance=	1e-05
data:	n=	14897	N=	40
sample:	seed=	0	seqfrac=	1
Letter frequencies in dataset:
A 0.114 C 0.016 D 0.058 E 0.054 F 0.026 G 0.085 H 0.020 I 0.067 K 0.052 L 0.095 M 0.020 N 0.035 P 0.042 Q 0.036 R 0.049 S 0.061 T 0.055 V 0.085 W 0.006 Y 0.024
Background letter frequencies (from dataset with add-one prior applied): A 0.114 C 0.016 D 0.058 E 0.054 F 0.026 G 0.085 H 0.020 I 0.067 K 0.052 L 0.095 M 0.020 N 0.035 P 0.042 Q 0.036 R 0.049 S 0.061 T 0.055 V 0.085 W 0.006 Y 0.024

MOTIF 1 width = 33 sites = 35 llr = 2229 E-value = 3.0e-598

SEQUENCE LOGO

PNG LOGOS require CONVERT from ImageMagick; see MEME installation guide

Information Content
99.1 (bits)

Relative Entropy
91.9 (bits)

Download LOGO
Without SSC:[EPS][PNG]
With SSC:[EPS][PNG]

NAME	START	P-VALUE	SITES
Saccharomyces_cerevisiae	64	1.73e-36	`VAEALEVQKI`	`CKKYNVPLIINDRIDVAMAIDADGVHVGQDDMP`	`IPMVRKLLGP`
Volvox_carteri	1095	1.82e-35	`AREAAAALKV`	`CRQYGVPLIINDRVDVALAVGADGVHVGQSDLP`	`TAVVRALIGP`
Clavispora_lusitaniae	62	1.06e-34	`IDRAKDVLKI`	`TRPRGVPLIINDRVDVALAVDADGVHVGQDDMP`	`ARIVRQLIGP`
Arabidopsis_thaliana	366	4.98e-33	`LEEAKACIDI`	`CRSHGVSLLINDRIDIALACDADGVHVGQSDMP`	`VDLVRSLLGP`
Cucumis_sativus	230	6.89e-33	`LEVAKSCIKI`	`CHAHGVPLLINDRIDIALACNADGVHVGQSDIP`	`AHEVRRLLGP`
Chloroflexus_aggregans	62	8.10e-33	`VAEAQVLREL`	`TRRTGVPLIVNDRLDVALAVDADGVHLGQDDMP`	`AALARRLIGP`
Lodderomyces_elongisporus	63	1.53e-32	`IKRAQQVHAL`	`TKPRGIPLIINDRVDVALAIDAEGVHVGQDDMP`	`ATSVRELIGP`
Acanthamoeba_castellanii	24	7.01e-32	`IEQASRIKSV`	`THRHGVPLIINDRLDVALAVGADGIHVGQDDMA`	`ATTARALLKQ`
Fibrobacter_succinogenes	59	1.09e-31	`MELAAAAHEV`	`TKRYNIPLIIDDRVDVALAIGAEGVHVGQTDMP`	`VKIARQLMGA`
Cyanothece	190	1.09e-31	`LEMAQKLCEL`	`CHQYDALFIVNDRVDIALAVNADGVHLGQQDIP`	`IALARRILGP`
Pelodictyon_phaeoclathratiforme	55	2.59e-31	`FSWAVEISKR`	`CHQYHALCIINDRVDIALASSADGVHLGQQDMP`	`ASTARKLLGK`
Oceanimonas	56	2.59e-31	`IERAEAVKAV`	`LQGTGVPLIINDRVDVALAVDADGVHLGQSDMP`	`ATHARRLLGP`
Aspergillus_terreus	60	4.53e-31	`IHTAKKLHQI`	`TTKYGVPLLINDRVDVALAVGAEGVHLGQDDMT`	`IEEAKRLLPK`
Selaginella_moellendorffii	364	6.86e-31	`IKIAEASLAI`	`GRKYGVPVLINDRVDVAVACNADGVHLGQTDMP`	`VRLARSILGP`
Naegleria_gruberi	47	1.03e-30	`LEQAKSLQKI`	`CRRHGVPFLIDDRVDLAVAIDADGVHVGQKDLP`	`PQYVRKLIGN`
Treponema	66	1.54e-30	`EKEALELQAL`	`CKKYKVPFIVNDNVELAKKIDADGVHVGQEDMN`	`ACKVRELLGP`
Sordaria_macrospora	63	2.29e-30	`IAMGKKLHAI`	`TKKYNVPLLINDRIDVALAVGCEGVHIGQDDME`	`LSTARRLLGP`
Aminobacterium_colombiense	60	5.66e-30	`LETALAMKRL`	`CYDYNVPLIINDRLDVALAAQADGVHLGQKDLP`	`LEAVRPFLPR`
Haemophilus_parainfluenzae	72	6.42e-30	`RALAIKCRDL`	`CRQYNVPFIVDDNVDLALEIEADGIHVGQSDTP`	`VKTIRARTHK`
Dysgonomonas_gadei	59	7.29e-30	`YNLAMKLKSI`	`LKSYNVPLIINDRLDIALACDAGGLHIGQSDMP`	`YSVARKLLGK`
Cyanobacterium	190	8.26e-30	`IKVARKLCEL`	`CHQYDALFIMNDRVDIALAINADGVHIGQEDIS`	`IKIAREIIGP`
Fusobacterium_mortiferum	62	1.06e-29	`VKEAREIREL`	`CRKNGVIFIVNDNVDIALLVDADGVHIGQEDMH`	`PDDVRKLIGD`
Coccidioides_immitis	101	2.81e-29	`IETASRLHTI`	`TKAHGVPLVINDRVDVALAVGAEGVHLGQDDMG`	`MAPNASQHYT`
Physcomitrella_patens	346	4.52e-29	`LQEAETSLKV`	`ARDYGIPLLINDRIDIAIACDADGVHLGQSDLP`	`VARARAILGP`
Desulfovibrio_africanus	60	1.02e-28	`LERAWRIKPI`	`CDAAGAPFIINDRVDVALAVGAAGVHLGRQDMP`	`YADARRLLGP`
Helicobacter_pylori	77	2.00e-28	`KQLALECQKL`	`CQKYGAPFIVNDEVQLALELKADGVHVGQEDMA`	`IEEVMTLCKK`
Cryptococcus_gattii	62	8.16e-28	`IEVARRTKAI`	`CDKYNVPVLINDRIDVHLAVGTAGIHVGQTDCP`	`IGLARSLVGP`
Perkinsus_marinus	34	1.19e-26	`YVKLAKETKK`	`LMPRHVPLIIDDRVDVCMASGADGVHVGDTDMS`	`VKDARSIIGP`
Oxalobacter_formigenes	54	2.27e-26	`LEQARALRDL`	`CRRYEKPFIINDYVDLCLELDTDGIHVGGMDVP`	`VKKVRAAVGP`
Bacillus_subtilis	68	3.90e-26	`IKFAEKAQAA`	`CREAGVPFIVNDDVELALNLKADGIHIGQEDAN`	`AKEVRAAIGD`
Akkermansia_muciniphila	59	5.08e-26	`YREALPIRDF`	`LASRGIPFIVNNRIDLALALEADGVHIGQRDLP`	`VPSVRAMIGP`
Geobacter	66	8.54e-26	`LELGQELKHL`	`CTEFQVEFIVNDDVELALALDADGVHLGQDDGD`	`PAAAREALGP`
Sulfurihydrogenibium_yellowstonense	56	1.10e-25	`LPISKDLKKL`	`CHKYDALFIVNDRLELTLKSDADGIHVGEEDVD`	`ISEIRKALKD`
Rubrobacter_xylanophilus	59	2.18e-24	`LPLARRLREV`	`CLRHGALFTVNDDIELARLSGAHGVHLGQEDEP`	`VARAREVLGP`
Trichoplax_adhaerens	60	7.41e-23	`LKIAYQCKEI`	`TSTYSIPLFINDNLAIAKKALADGVHLGQSDIL`	`LNNAREFLGN`

Motif 1 block diagrams

Name

Lowest
p-value

Motifs

Saccharomyces_cerevisiae

1.73e-36

Volvox_carteri

1.82e-35

Clavispora_lusitaniae

1.06e-34

Arabidopsis_thaliana

4.98e-33

Cucumis_sativus

6.89e-33

Chloroflexus_aggregans

8.10e-33

Lodderomyces_elongisporus

1.53e-32

Acanthamoeba_castellanii

7.01e-32

Fibrobacter_succinogenes

1.09e-31

Cyanothece

1.09e-31

Pelodictyon_phaeoclathratiforme

2.59e-31

Oceanimonas

2.59e-31

Aspergillus_terreus

4.53e-31

Selaginella_moellendorffii

6.86e-31

Naegleria_gruberi

1.03e-30

Treponema

1.54e-30

Sordaria_macrospora

2.29e-30

Aminobacterium_colombiense

5.66e-30

Haemophilus_parainfluenzae

6.42e-30

Dysgonomonas_gadei

7.29e-30

Cyanobacterium

8.26e-30

Fusobacterium_mortiferum

1.06e-29

Coccidioides_immitis

2.81e-29

Physcomitrella_patens

4.52e-29

Desulfovibrio_africanus

1.02e-28

Helicobacter_pylori

2.00e-28

Cryptococcus_gattii

8.16e-28

Perkinsus_marinus

1.19e-26

Oxalobacter_formigenes

2.27e-26

Bacillus_subtilis

3.90e-26

Akkermansia_muciniphila

5.08e-26

Geobacter

8.54e-26

Sulfurihydrogenibium_yellowstonense

1.10e-25

Rubrobacter_xylanophilus

2.18e-24

Trichoplax_adhaerens

7.41e-23

SCALE

\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|
1	25	50	75	100	125	150	175	200	225	250	275	300	325	350	375	400	425	450	475	500	525	550	575	600	625	650	675	700	725	750	775	800	825	850	875	900	925	950	975	1000	1025	1050	1075	1100	1125	1150	1175	1200	1225	1250

Motif 1 in BLOCKS format

to BLOCKS multiple alignment processor.

Motif 1 position-specific scoring matrix

Scan sequence databases for the best match in each sequence using MAST.

Motif 1 position-specific probability matrix

Scan sequence databases for all matches with this motif using FIMO.

Motif 1 regular-expression

[CT][RK]KY[GN][VA]P[LF][IL][IV]NDR[VI]D[VLI]ALA[VI][DG]ADGVH[VL]GQ[DSE]DMP

Time 19.32 secs.

MOTIF 2 width = 21 sites = 39 llr = 1311 E-value = 4.8e-290

SEQUENCE LOGO

Information Content
52.3 (bits)

Relative Entropy
48.5 (bits)

Download LOGO
Without SSC:[EPS][PNG]
With SSC:[EPS][PNG]

NAME	START	P-VALUE	SITES
Physcomitrella_patens	406	3.34e-21	`CKTPEQAEKA`	`WKDGADYVGSGGVYPTNTKKD`	`NKTIGIEGLR`
Chloroflexus_aggregans	122	1.30e-20	`ASTLAEALQA`	`VQDGADYLGVGPIFATPTKPD`	`AAPPIGIDGL`
Bacillus_subtilis	127	3.04e-20	`AHTMSEVKQA`	`EEDGADYVGLGPIYPTETKKD`	`TRAVQGVSLI`
Arabidopsis_thaliana	426	4.58e-20	`CKTPEQAHQA`	`WKDGADYIGSGGVFPTNTKAN`	`NRTIGLDGLK`
Cucumis_sativus	290	4.58e-20	`CKTTEQAEQA`	`WIDGADYIGCGGVYPTNTKAN`	`NLTVGIDGLK`
Selaginella_moellendorffii	424	1.23e-19	`CKTVEQAVKA`	`YEDGADYIGCGGVYPTTTKKK`	`NKTIGLDGLR`
Rubrobacter_xylanophilus	119	1.23e-19	`AGGVEEARRA`	`VREGADYLGVGSVYPTPTKPD`	`AEVRGLGLIR`
Cyanothece	250	1.51e-18	`TTNPQEMEKA`	`IAEKADYIGVGPVYATPTKPD`	`KKAAGLDYVK`
Cyanobacterium	250	1.51e-18	`TTNPLEMEKA`	`IEEGADYIGVGPIYPTPNKPE`	`KETIQSDYLD`
Sordaria_macrospora	123	6.41e-18	`VSTIEEAMVA`	`CKGGADYLGIGTVYATPTKTN`	`TKNIIGAAGV`
Treponema	126	7.47e-18	`AQTVEEAILA`	`EKQGADYLGVGAVFPTGSKSD`	`AIDVPHETLK`
Lodderomyces_elongisporus	124	8.70e-18	`STPEEAQEVV`	`DQDVADYVGLGTVYATNTKKD`	`VTNPDGVGPI`
Fibrobacter_succinogenes	119	1.01e-17	`TKTVPQALEA`	`YEQGADYLGVGAIYPTTTKVV`	`TILTSVDTLK`
Aspergillus_terreus	120	1.17e-17	`ASSIDEAQKA`	`IAAGADYLGIGTMFATPTKTN`	`TKSIIGTAGT`
Cryptococcus_gattii	122	3.22e-17	`VGNVNEAKRA`	`IQQGADYVGIGAVWPTNSKDV`	`TKKNMLGPDG`
Acanthamoeba_castellanii	90	4.88e-17	`ATNEAQARAA`	`ELAGADYLGTSAVFPTDTKKD`	`GGAGYVIGLD`
Helicobacter_pylori	138	4.88e-17	`NTLEQALKAR`	`HLDGVAYLGVGPIFPTQSKKD`	`KQVVGVELLK`
Pelodictyon_phaeoclathratiforme	115	1.23e-16	`ASSPDEARLA`	`EQEGADYIGFGHIYPTASKVK`	`EFSPVGVEAL`
Clavispora_lusitaniae	123	2.32e-16	`GNEEETTEVC`	`EQKVADYVGLGTLYPTQTKDV`	`KNVCGPIGVR`
Taylorella_asinigenitalis	122	2.32e-16	`YNSIDMARDA`	`VKNGASYIAFGAMYPSPTKPN`	`AVKADTNLIK`
Perkinsus_marinus	95	2.97e-16	`YGRQEDAIAA`	`IRDGADYIATGAVYPTVTKPG`	`AVAQGLGQID`
Saccharomyces_cerevisiae	127	2.97e-16	`PSEVETLAKW`	`GPDMVDYIGVGTLFPTSTKKN`	`PKKSPMGPQG`
Fusobacterium_mortiferum	123	4.25e-16	`HSEKQGMEAY`	`KNPNVDYIGVGPIFPTTTKDT`	`TPVGLGYLEY`
Coccidioides_immitis	178	5.39e-16	`VSSVEEARIA`	`VEKRANYLGIGTVFATPTKTN`	`TKSIIGTAGV`
Geobacter	126	6.79e-16	`THSLTEALEA`	`QEAGADYVGFGALYPTDSKEV`	`EHIQGPEKLA`
Desulfovibrio_africanus	120	9.56e-16	`VHNMAELEEA`	`KATDADYFGLGPAFPTRTKPD`	`APAPWGMDEY`
Naegleria_gruberi	109	1.07e-15	`TFDQVDEALS`	`HNVRADYLGTNAIFPTLTKKD`	`AGQAVGLDGL`
Haemophilus_parainfluenzae	133	1.07e-15	`NRLDEAKIGE`	`ELSEIDYFGIGPIFPTQSKEN`	`PKPTLGMAFI`
Aminobacterium_colombiense	120	2.06e-15	`AHTVDQARIA`	`LKSGASYIGIGAAFPTGSKED`	`AHVVGLSRIR`
Trichoplax_adhaerens	120	3.46e-15	`VNNLSQLNNN`	`QNIFADYISLGPIFYTNTKLD`	`IEKPIGIEEI`
Dysgonomonas_gadei	119	4.69e-15	`VESIQDAIDA`	`NNLDVDYIGISPVFGTQTKTD`	`TAPALGLEGI`
Oceanimonas	116	6.31e-15	`VETEQQLFES`	`ESLPVDYLGLSAIFATPTKTD`	`LKRHWGIDGL`
Akkermansia_muciniphila	119	1.23e-14	`VSNKEQLRAV`	`DASLVDYLGMGPVFPTISKLN`	`APPVLGVEGF`
Volvox_carteri	1155	1.36e-13	`VKTPQQARDA`	`AAAGADYLGAGAVLPTGTKDT`	`DVIGLEGLGA`
Oxalobacter_formigenes	115	2.26e-13	`YGDLELARKA`	`TRDGASYVAFGGFYPSRVKKY`	`PVTTPQNIVS`
Sulfurihydrogenibium_yellowstonense	116	4.45e-13	`YGDVERAILM`	`ERLSATYVAFGSFYFSPTKPK`	`SKIVDKSVIT`
Xenopus(Silurana)	231	5.07e-13	`THGYAEMLRA`	`DIVAPSYIALGAVFPTTLKKM`	`ATQPQGVARL`
Phaeodactylum_tricornutum	489	5.07e-13	`THSYGELATA`	`LGVKPSYISLGPVFATSSKTV`	`QFDPQGLSLV`
Thalassiosira_pseudonana	214	6.14e-13	`VESASKSYQL`	`SPRGPDYLFVGTCYLTQSHPE`	`KSSADQLEGP`

Motif 2 block diagrams

Name

Lowest
p-value

Motifs

Physcomitrella_patens

3.34e-21

Chloroflexus_aggregans

1.30e-20

Bacillus_subtilis

3.04e-20

Arabidopsis_thaliana

4.58e-20

Cucumis_sativus

4.58e-20

Selaginella_moellendorffii

1.23e-19

Rubrobacter_xylanophilus

1.23e-19

Cyanothece

1.51e-18

Cyanobacterium

1.51e-18

Sordaria_macrospora

6.41e-18

Treponema

7.47e-18

Lodderomyces_elongisporus

8.70e-18

Fibrobacter_succinogenes

1.01e-17

Aspergillus_terreus

1.17e-17

Cryptococcus_gattii

3.22e-17

Acanthamoeba_castellanii

4.88e-17

Helicobacter_pylori

4.88e-17

Pelodictyon_phaeoclathratiforme

1.23e-16

Clavispora_lusitaniae

2.32e-16

Taylorella_asinigenitalis

2.32e-16

Perkinsus_marinus

2.97e-16

Saccharomyces_cerevisiae

2.97e-16

Fusobacterium_mortiferum

4.25e-16

Coccidioides_immitis

5.39e-16

Geobacter

6.79e-16

Desulfovibrio_africanus

9.56e-16

Naegleria_gruberi

1.07e-15

Haemophilus_parainfluenzae

1.07e-15

Aminobacterium_colombiense

2.06e-15

Trichoplax_adhaerens

3.46e-15

Dysgonomonas_gadei

4.69e-15

Oceanimonas

6.31e-15

Akkermansia_muciniphila

1.23e-14

Volvox_carteri

1.36e-13

Oxalobacter_formigenes

2.26e-13

Sulfurihydrogenibium_yellowstonense

4.45e-13

Xenopus(Silurana)

5.07e-13

Phaeodactylum_tricornutum

5.07e-13

Thalassiosira_pseudonana

6.14e-13

SCALE

\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|
1	25	50	75	100	125	150	175	200	225	250	275	300	325	350	375	400	425	450	475	500	525	550	575	600	625	650	675	700	725	750	775	800	825	850	875	900	925	950	975	1000	1025	1050	1075	1100	1125	1150	1175	1200	1225	1250

Motif 2 in BLOCKS format

to BLOCKS multiple alignment processor.

Motif 2 position-specific scoring matrix

Scan sequence databases for the best match in each sequence using MAST.

Motif 2 position-specific probability matrix

Scan sequence databases for all matches with this motif using FIMO.

Motif 2 regular-expression

ExDGADY[ILV]G[VL]G[AP][VI][FY][PA]TP[TS]K[KP][DN]

Time 35.69 secs.

MOTIF 3 width = 29 sites = 34 llr = 1404 E-value = 3.0e-276

SEQUENCE LOGO

Information Content
68.5 (bits)

Relative Entropy
59.6 (bits)

Download LOGO
Without SSC:[EPS][PNG]
With SSC:[EPS][PNG]

NAME	START	P-VALUE	SITES
Coccidioides_immitis	66	1.02e-25	`SAHYKGDLCT`	`VVEQAIQGGVTIVQYRDKHADTGVLIETA`	`SRLHTITKAH`
Selaginella_moellendorffii	329	7.21e-25	`NKRWDRSTPA`	`AVEQAIQGGATIIQIREKEAETLEFIKIA`	`EASLAIGRKY`
Dysgonomonas_gadei	24	7.21e-25	`SLSLGRPLET`	`VVEEAVRGGVTMVQLREKDASTLDFYNLA`	`MKLKSILKSY`
Clavispora_lusitaniae	27	3.12e-24	`MIPESSSFLS`	`QVQQAVENGVTIVQLREKNISTRDFIDRA`	`KDVLKITRPR`
Lodderomyces_elongisporus	28	3.73e-24	`MIPESKTFLG`	`QIEEAVNNGVTIVQLREKKLSTREFIKRA`	`QQVHALTKPR`
Desulfovibrio_africanus	25	1.06e-23	`VGCMGRDLAW`	`VVAEALAGGVTMVQLREKQATTREFLERA`	`WRIKPICDAA`
Arabidopsis_thaliana	331	1.25e-23	`NKKWNRSIVD`	`ALKAAIEGGATIIQLREKEAETREFLEEA`	`KACIDICRSH`
Fibrobacter_succinogenes	24	1.76e-23	`TSVPADRFLP`	`TVEAACKGGATLIQLREKNRSTREYMELA`	`AAAHEVTKRY`
Aspergillus_terreus	25	2.89e-23	`PILKGRDLCA`	`VVEEALKGGVTVVQYRDKKSDTGDQIHTA`	`KKLHQITTKY`
Cryptococcus_gattii	27	8.88e-23	`LLPPGKDYYE`	`SLEESLQGGVTLVQVREKDADTGEFIEVA`	`RRTKAICDKY`
Physcomitrella_patens	311	1.21e-22	`NKTWGRSTSE`	`AVRAAIEGGATIVQIRSKEADTGEFLQEA`	`ETSLKVARDY`
Chloroflexus_aggregans	27	4.09e-22	`GLSRGRSHVA`	`VIEAAITGGATVVQYREKHAPTRQMVAEA`	`QVLRELTRRT`
Cucumis_sativus	195	7.36e-22	`NERWDRSITD`	`AVKDAVEGGATIVQIREKDAKTRDFLEVA`	`KSCIKICHAH`
Sordaria_macrospora	28	1.14e-20	`AILGDRDLYE`	`VVEASVRGGTTIVQLRDKTSDTGDMIAMG`	`KKLHAITKKY`
Oceanimonas	21	2.16e-20	`DRQPIDTLQT`	`VVREAVAGGVTLVQVREKHGDVRAFIERA`	`EAVKAVLQGT`
Fusobacterium_mortiferum	27	2.45e-20	`NFSNGRSNYF`	`CVEEMIKGGIKIVQYRAKTKDTREKVKEA`	`REIRELCRKN`
Saccharomyces_cerevisiae	29	5.81e-20	`MLPPGTTLCS`	`QVEAGLKNGVTLVQIREKDIETKNFVAEA`	`LEVQKICKKY`
Cyanobacterium	155	1.49e-19	`ITSPIKNLFS`	`VVESSLKGGLQILQYREKNISDSSYIKVA`	`RKLCELCHQY`
Trichoplax_adhaerens	25	1.88e-19	`KQISDIEFLD`	`IIEKSIIGGVTSVQLREKNLEDDEFLKIA`	`YQCKEITSTY`
Aminobacterium_colombiense	25	2.36e-19	`QIGAPRTLLE`	`QTEEVLKGGATVIQLRDKQSGGRELLETA`	`LAMKRLCYDY`
Volvox_carteri	1060	3.31e-19	`NKKCNRTLLE`	`AVTLAVRGGATIIQLREKDTDGGDFAREA`	`AAALKVCRQY`
Cyanothece	155	3.31e-19	`VTSSRENFLK`	`IVESALQGGLTLLQYREKKIDDIVRLEMA`	`QKLCELCHQY`
Rubrobacter_xylanophilus	24	5.72e-19	`VTDPRDDLEE`	`RVEAALRGGVDIVQLREKRASREEVLPLA`	`RRLREVCLRH`
Oxalobacter_formigenes	19	1.09e-18	`DWDDTAKMVE`	`VTEKALTGGAQIVQYRHKTAGPELLLEQA`	`RALRDLCRRY`
Sulfurihydrogenibium_yellowstonense	21	1.20e-18	`KLTPYDKIFD`	`MVEQALKGGAKLVQLRDKNNSDDFLLPIS`	`KDLKKLCHKY`
Perkinsus_marinus	0	2.02e-18		`MVASAVAGGATCVQLRLKDVSTGDYVKLA`	`KETKKLMPRH`
Treponema	31	1.38e-17	`HWTGEKTLYQ`	`QTEEAILGGTTFLQIREKELNEADFEKEA`	`LELQALCKKY`
Akkermansia_muciniphila	24	4.70e-17	`ASKCRLSLLE`	`TVRKAADGGVTIVQYRSTNPDAGTCYREA`	`LPIRDFLASR`
Pelodictyon_phaeoclathratiforme	20	6.03e-17	`ITDEALCPVT`	`LAEQALKGGAAMIQLRHKTASGSQLFSWA`	`VEISKRCHQY`
Bacillus_subtilis	30	6.03e-17	`SNNTKADPVT`	`VVQKALKGGATLYQFREKGGDALTGEARI`	`KFAEKAQAAC`
Haemophilus_parainfluenzae	32	1.98e-16	`GDNLADNLLS`	`VLRQALEGGITCFQFRDKGKFSLENSPTE`	`QRALAIKCRD`
Naegleria_gruberi	8	5.16e-16	`MGKRSLEE`	`TVEQSIEGGSSIIQYREKRYPQQLTTRQM`	`LEQAKSLQKI`
Geobacter	31	1.51e-14	`TDQAERLVHR`	`VREALSSGGVAVLQYRDKVRAYEERLELG`	`QELKHLCTEF`
Helicobacter_pylori	38	3.65e-13	`KNDRINALLD`	`ALELALQSKITAFQFRQKGDLALQDPIEI`	`KQLALECQKL`

Motif 3 block diagrams

Name

Lowest
p-value

Motifs

Coccidioides_immitis

1.02e-25

Selaginella_moellendorffii

7.21e-25

Dysgonomonas_gadei

7.21e-25

Clavispora_lusitaniae

3.12e-24

Lodderomyces_elongisporus

3.73e-24

Desulfovibrio_africanus

1.06e-23

Arabidopsis_thaliana

1.25e-23

Fibrobacter_succinogenes

1.76e-23

Aspergillus_terreus

2.89e-23

Cryptococcus_gattii

8.88e-23

Physcomitrella_patens

1.21e-22

Chloroflexus_aggregans

4.09e-22

Cucumis_sativus

7.36e-22

Sordaria_macrospora

1.14e-20

Oceanimonas

2.16e-20

Fusobacterium_mortiferum

2.45e-20

Saccharomyces_cerevisiae

5.81e-20

Cyanobacterium

1.49e-19

Trichoplax_adhaerens

1.88e-19

Aminobacterium_colombiense

2.36e-19

Volvox_carteri

3.31e-19

Cyanothece

3.31e-19

Rubrobacter_xylanophilus

5.72e-19

Oxalobacter_formigenes

1.09e-18

Sulfurihydrogenibium_yellowstonense

1.20e-18

Perkinsus_marinus

2.02e-18

Treponema

1.38e-17

Akkermansia_muciniphila

4.70e-17

Pelodictyon_phaeoclathratiforme

6.03e-17

Bacillus_subtilis

6.03e-17

Haemophilus_parainfluenzae

1.98e-16

Naegleria_gruberi

5.16e-16

Geobacter

1.51e-14

Helicobacter_pylori

3.65e-13

SCALE

\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|
1	25	50	75	100	125	150	175	200	225	250	275	300	325	350	375	400	425	450	475	500	525	550	575	600	625	650	675	700	725	750	775	800	825	850	875	900	925	950	975	1000	1025	1050	1075	1100	1125	1150	1175	1200	1225	1250

Motif 3 in BLOCKS format

to BLOCKS multiple alignment processor.

Motif 3 position-specific scoring matrix

Scan sequence databases for the best match in each sequence using MAST.

Motif 3 position-specific probability matrix

Scan sequence databases for all matches with this motif using FIMO.

Motif 3 regular-expression

VVE[EAQ]A[LIV]KGG[AV]T[IL][VI]Q[LY]R[ED]KxA[DS]T[RG][ED]F[LI][EK]EA

Time 50.37 secs.

SUMMARY OF MOTIFS

Combined block diagrams: non-overlapping sites with p-value < 0.0001

Name

Combined
p-value

Motifs

Bacillus_subtilis

4.22e-51

Helicobacter_pylori

1.79e-46

Haemophilus_parainfluenzae

8.03e-50

Oceanimonas

1.76e-54

Desulfovibrio_africanus

6.27e-56

Geobacter

4.79e-43

Taylorella_asinigenitalis

1.05e-24

Oxalobacter_formigenes

2.02e-46

Cyanobacterium

5.14e-55

Cyanothece

1.60e-56

Dysgonomonas_gadei

1.56e-57

Pelodictyon_phaeoclathratiforme

9.50e-53

Chloroflexus_aggregans

3.74e-63

Rubrobacter_xylanophilus

7.19e-51

Treponema

9.41e-54

Fusobacterium_mortiferum

5.99e-54

Sulfurihydrogenibium_yellowstonense

2.09e-45

Aminobacterium_colombiense

1.35e-52

Akkermansia_muciniphila

1.05e-45

Fibrobacter_succinogenes

1.31e-60

Saccharomyces_cerevisiae

4.21e-59

Clavispora_lusitaniae

9.56e-62

Aspergillus_terreus

1.87e-58

Coccidioides_immitis

2.69e-57

Sordaria_macrospora

1.90e-55

Cryptococcus_gattii

2.76e-54

Cucumis_sativus

1.20e-61

Arabidopsis_thaliana

4.13e-63

Physcomitrella_patens

2.19e-59

Volvox_carteri

1.31e-53

Thalassiosira_pseudonana

2.37e-12

Phaeodactylum_tricornutum

6.34e-17

Perkinsus_marinus

1.02e-48

Xenopus(Silurana)

8.37e-19

Trichoplax_adhaerens

2.01e-45

Naegleria_gruberi

4.35e-49

Acanthamoeba_castellanii

1.55e-40

Lodderomyces_elongisporus

7.98e-61

Selaginella_moellendorffii

8.68e-62

SCALE

\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|	\|
1	25	50	75	100	125	150	175	200	225	250	275	300	325	350	375	400	425	450	475	500	525	550	575	600	625	650	675	700	725	750	775	800	825	850	875	900	925	950	975	1000	1025	1050	1075	1100	1125	1150	1175	1200	1225	1250

Motif summary in machine readable format.

Stopped because Stopped because nmotifs = 3 reached..

CPU: kodomo.fbb.msu.ru

EXPLANATION OF MEME RESULTS

The MEME results consist of:

The version of MEME and the date it was released.
The reference to cite if you use MEME in your research.
A description of the sequences you submitted (the "training set") showing the name, "weight" and length of each sequence.
The command line summary detailing the parameters with which you ran MEME.
Information on each of the motifs MEME discovered, including:
1. A summary line showing the width, number of occurrences, log likelihood ratio and statistical significance of the motif.
2. A sequence LOGO.
3. The information content of the motif.
4. The relative entropy of the motif.
5. Downloadable LOGO files suitable for publication.
6. The occurrences of the motif sorted by p-value and aligned with each other.
7. Block diagrams of the occurrences of the motif within each sequence in the training set.
8. The motif in BLOCKS or FASTA format.
9. A position-specific scoring matrix (PSSM) for use by the MAST database search program.
10. The position specific probability matrix (PSPM) describing the motif.
11. A regular expression describing the motif.
A summary of motifs showing an optimized (non-overlapping) tiling of all of the motifs onto each of the sequences in the training set.
The reason why MEME stopped and the name of the CPU on which it ran.
This explanation of how to interpret MEME results.

MOTIFS

For each motif that it discovers in the training set, MEME prints the following information:

Summary Line
This line gives the width ('width'), number of occurrences in the training set ('sites'), log likelihood ratio ('llr') and 'E-value' of the motif. Each motif describes a pattern of a fixed width--no gaps are allowed in MEME motifs. MEME numbers the motifs consecutively from one as it finds them. MEME usually finds the most statistically significant (low E-value) motifs first. The statistical significance of a motif is based on its log likelihood ratio, its width and number of occurrences, the background letter frequencies (given in the command line summary ), and the size of the training set. The E-value is an estimate of the expected number of motifs with the given log likelihood ratio (or higher), and with the same width and number of occurrences, that one would find in a similarly sized set of random sequences. (In random sequences each position is independent with letters chosen according to the background letter frequencies.) The log likelihood ratio is the logarithm of the ratio of the probability of the occurrences of the motif given the motif model (likelihood given the motif) versus their probability given the background model (likelihood given the null model). (Normally the background model is a 0-order Markov model using the background letter frequencies, but higher order Markov models may be specified via the -bfile option to MEME.) Clicking on the buttons to the left of the motif summary line takes you to the previous motif (P) or next motif (N).

Sequence LOGO

MEME motifs are represented by position-specific probability matrices that specify the probability of each possible letter appearing at each possible position in an occurrence of the motif. These are displayed as "sequence LOGOS", containing stacks of letters at each position in the motif. The total height of the stack is the "information content" of that position in the motif in bits. The height of the individual letters in a stack is the probability of the letter at that position multiplied by the total information content of the stack.

Note: The MEME LOGO differs from those produced by the Weblogo program because a small-sample correction is NOT applied. However, MEME LOGOs in PNG and encapsulated postscript (EPS) formats with small-sample correction (SSC) are available by clicking on one of the links named "With SSC" (EPS or PNG) under Download LOGO. The MEME LOGOs without small sample correction are similarly available. Error bars are included in the LOGOs with small-sample correction.

The information content of each motif position is computed as described in the paper by Schneider and Stephens, "Sequence Logos: A New Way to Display Consensus Sequences" but the small-sample correction, e(n), is set to zero for the LOGO displayed in the MEME output. The corrected information content of position i is given by

           R(i) for amino acids   = log2(20) - (H(i) + e(n))   (1a) 
           R(i) for nucleic acids =    2    - (H(i) + e(n))    (1b)

where H(i) is the entropy of position i,

           H(l) = - (Sum f(a,i) * log2[ f(a,i) ]).             (2)

Here, f(a,i) is the frequency of base or amino acid a at position i, and e(n) is the small-sample correction for an alignment of n letters. The height of letter a in column i is given by

           height = f(a,i) * R(i)                              (3)

The approximation for the small-sample correction, e(n), is given by:

           e(n) = (s-1) / (2 * ln(2) * n),                     (4)

where s is 4 for nucleotides, 20 for amino acids, and n is the number of sequences in the alignment.

The letters in the logos are colored as follows. For DNA sequences, the letter categories contain one letter each. For proteins, the categories are based on the biochemical properties of the various amino acids. The categories and their colors are:

NUCLEIC ACIDS	COLOR
A	RED
C	BLUE
G	ORANGE
T	GREEN

AMINO ACIDS	COLOR	PROPERTIES
A, C, F, I, L, V, W and M	BLUE	Most hydrophobic[Kyte and Doolittle, 1982]
NQST	GREEN	Polar, non-charged, non-aliphatic residues
DE	MAGENTA	Acidic
KR	RED	Positively charged
H	PINK
G	ORANGE
P	YELLOW
Y	TURQUOISE

J. Kyte and R. Doolittle, 1982. "A Simple Method for Displaying the Hydropathic Character of a Protein", J. Mol Biol. 157, 105-132.

Note: the "text" output format of MEME preserves the historical MEME format where LOGOS are replaced by a simplified probability matrix, a relative entropy plot, and a multi-level consensus sequence.

Information Content
This is the information content of the motif in bits. It is equal to the sum of the uncorrected information content, R(), in the columns of the LOGO. This is equal relative entropy of the motif relative to a uniform background frequency model.
Relative Entropy
This is the relative entropy of the motif, computed in bits and relative to the background letter frequencies given in the command line summary. It is equal to the log-likelihood ratio (llr) divided by the number of occurrences (sites) of the motif times 1/ln(2),
```
               re = llr / (sites * ln(2)).
	    
```
Occurrences of the Motif
MEME displays the occurrences (sites) of the motif in the training set. The sites are shown aligned with each other, and the ten sequence positions preceding and following each site are also shown. Each site is identified by the name of the sequence where it occurs, the strand (if both strands of DNA sequences are being used), and the position in the sequence where the site begins. When the DNA strand is specified, '+' means the sequence in the training set, and '-' means the reverse complement of the training set sequence. (For '-' strands, the 'start' position is actually the position on the positive strand where the site ends.) The sites are listed in order of increasing statistical significance (p-value). The p-value of a site is computed from the the match score of the site with the position specific scoring matrix for the motif. The p-value gives the probability of a random string (generated from the background letter frequencies) having the same match score or higher. (This is referred to as the position p-value by the MAST algorithm.)
Block Diagrams of Motif Occurrences
The occurrences of the motif in the training set sequences are shown with MAST-style block diagrams. One diagram is printed for each sequence showing all the occurrences of the motif in that sequence. The sequences are sorted by the lowest p-value among all occurrences of the motif in a given sequence. (The p-value of an occurrence is the probability of a single random subsequence the length of the motif, generated according to the 0-order background model, having a score at least as high as the score of the occurrence.) When the DNA strand is specified, '+' means the motif appears from left to right on the sequence, and '-' means the motif appears from right to left on the complementary strand. A sequence position scale is shown at the end of each table of block diagrams. Very long sequences are shown with thick lines connecting the motifs and are not drawn to scale.
Motif in BLOCKS format or FASTA format>
For use with BLOCKS tools, MEME prints the occurrences of the motif in BLOCKS format.
You can convert these blocks to PSSMs (position-specific scoring matrices), LOGOS (color representations of the motifs), phylogeny trees and search them against a database of other blocks by pasting everything from the "BL" line to the "//" line (inclusive) into the Multiple Alignment Processor.
If you include the -print_fasta switch on the command line, MEME prints the motif sites in FASTA format instead of BLOCKS format.
Position-Specific Scoring Matrix
The position-specific scoring matrix corresponding to the motif is printed for use by database search programs such as MAST. This matrix is a log-odds matrix calculated by taking 100 times the log (base 2) of the ratio p/f at each position in the motif where p is the probability of a particular letter at that position in the motif, and f is the background frequency of the letter (given in the command line summary section.) This is the same matrix that is used above in computing the p-values of the occurrences of the motif in the Occurrences of the Motif and Block Diagrams of Motif Occurrences sections. The scoring matrix is printed "sideways"--columns correspond to the letters in the alphabet (in the same order as shown in the simplified motif) and rows corresponding to the positions of the motif, position one first. The scoring matrix is preceded by a line starting with "log-odds matrix:" and containing the length of the alphabet, width of the motif, number of characters in the training set, the scoring threshold (obsolete) and the motif E-value.
Note: The probability p used to compute the PSSM is not exactly the same as the corresponding value in the Position Specific Probability Matrix (PSPM). The values of p used to compute the PSSM take into account the motif prior, whereas the values in the PSPM are just the observed frequencies of letters in the motif sites.
Position-Specific Probability Matrix
The motif itself is a position-specific probability matrix giving, for each position in the pattern, the observed frequency ("probability") of each possible letter. The probability matrix is printed "sideways"--columns correspond to the letters in the alphabet (in the same order as shown in the simplified motif) and rows corresponding to the positions of the motif, position one first. The motif is preceded by a line starting with "letter-probability matrix:" and containing the length of the alphabet, width of the motif, number of occurrences of the motif, and the E-value of the motif.
Note: Earlier versions of MEME gave the posterior probabilities--the probability after applying a prior on letter frequencies--rather than the observed frequencies. These versions of MEME also gave the number of possible positions for the motif rather than the actual number of occurrences. The output from these earlier versions of MEME can be distinguished by "n=" rather than "nsites=" in the line preceding the matrix.
Regular Expression
This is a regular expression (RE) describing the motif. In each column, all letters with observed frequencies greater than 0.2 are shown; less-frequent letters are not included in the RE. MEME regular expressions are interpreted as follows: single letters match that letter; groups of letters in square brackets match any of the letters in the group. Regular expressions can be used for searching for the motif in sequences (using, for example, PatMatch ) but the search accuracy will usually be better with the PSSM (using, for example MAST.)
Motif Summary Tiling
The motif summary tiling is done using the same algorithm as used by MAST. The motif occurrences shown in the motif summary may not be exactly the same as those reported in each motif section because only motifs with a position p-value of 0.0001 that don't overlap other, more significant motif occurrences are shown. The format of the machine readable motif-summary is:
```
        [sequence_name combined_p-value number_of_motif_occurrences [motif_number start_of_motif position_p-value]+]+
        
```
See the documentation for MAST output for the definition of position and combined p-values.