General Information
ZFIN: Mapping Panel: An Integrated Map of the Zebrafish Genome

Meiotic Panel: An Integrated Map of the Zebrafish Genome (ZMAP)



       by Allen Day, Tom Conlin, and John H. Postlethwait
       Institute of Neuroscience, University of Oregon

        For the molecular cloning of genes originally identified by mutations, it is important to know all mapped markers residing near a mapped mutation.  Mapped coding sequences provide information on potential candidate loci and conserved chromosome segments, and mapped anonymous markers such as microsatellites provide highly polymorphic markers for fine structure mapping.
        To facilitate these strategies, we have produced a consolidated map containing all of the coding sequences currently positioned on the two large radiation hybrid (RH) mapping panels (the T51 panel, Kwok et al., 1998; Geisler et al., 1999; and the LN54 panel, Hukriede et al., 1999; Chevrette et al., 2000) and the doubled haploid (heat shock, HS) meiotic mapping panel (Kelly et al., 2000; Postlethwait et al., 2000; Woods et al., 2000).  We intercalated these sequences into the complete diploid meiotic map of microsatellites (MGH panel, Knapik et al., 1996; Shimoda et al., 1999).  The MGH microsatellite map was used as the standard because all of the other maps first constructed a framework map of microsatellites into which they have inserted the loci for coding sequences.

        The following strategy was used to intercalate the positions of coding sequences into the MGH map.  We assumed at the outset that, at least as a first approximation, the distances between closely linked markers would be approximately linearly related when any given map was compared to the MGH microsatellite map.  This assumption is an approximation, but for closely linked markers, the errors introduced by this assumption are likely to be small. 
        Data for the composite map were imported from data for the four panels stored in ZFIN.  For each locus on each map, two intervals were determined: the interval from the coding sequence to its nearest common microsatellite marker, and the interval from the coding sequence to its second-nearest microsatellite marker, with the condition that the two microsatellite markers were not closer to one another than the nearest microsatellite was to the coding sequence.  This reduced magnification of error from the reported microsatellite marker positions.  In cases where two qualifying microsatellite markers did not exist, we did not assign a position.  The ratio of the two intervals was then used to intercalate the coding sequence into the MGH microsatellite map.

        This integrated map is only as good as the original data sets from which the data were taken, with additional uncertainty introduced by the assumptions necessary to perform the intercalation procedure.  No independent attempt was made to verify the locations of markers, and so there are cases in which the same marker, or different markers from the same unigene cluster, appear in multiple locations.  In these conflicting cases, we display all locations and note them with asterisks following the marker names.
        In cases of conflicting map data, there is no reliable way, a priory, to decide which of several positions may be in error.  Sources of potential error include mosaic EST clones, errors in labeling samples or gel lanes, errors in the scoring of mapping gels, errors in the recording of data, and violation of the assumption of co-linear maps.  By examining all data in a common framework, however, it may be possible to determine which of several positions is in error.  For coding sequences with reported positions that cluster, a simple measure of variance will reveal which loci are most likely to be erroneous.
In the current ZMAP, all locations of loci were included.  For the purposes of providing candidate markers for mutations, it seems more prudent to err on the side of the inclusion of all data.  The cost of a marker appearing in an interval in which it does not belong is that a few false positives will be linked closely to one's mutant.  Simple experiments can quickly reveal loci that do not belong in a given interval, and we hope that you will contact us when you discover such a "mistake" in the map.  On the other hand, if we inappropriately exclude data that are correctly positioned, we will generate false negatives, and researchers will miss potential candidates.  This type of error is much more difficult to reveal.
        Thanks are due to ZFIN, Judy Sprague, Monte Westerfield, and NIH grants R01-RR10715 to JHP, P01-HD22486 to M. Westerfield and J. Postlethwait, and P40-RR12546 to the Zebrafish International Resource Center.


               Chevrette M, Joly L, Tellis P, Knapik EW, Miles J, Fishman M, Ekker M (2000) Characterization of a zebrafish/mouse somatic cell hybrid panel.  Genomics. 64, 119-126.
               Geisler, R., Rauch, G.J., Baier, H., van Bebber, F., Brobeta, L., Dekens, M.P., Finger, K., Fricke, C., Gates, M.A., Geiger, H., Geiger-Rudolph, S., Gilmour, D., Glaser, S., Gnugge, L., Habeck, H., Hingst, K., Holley, S., Keenan, J., Kirn, A., Knaut, H., Lashkari, D., Maderspacher, F., Martyn, U., Neuhauss, S., Haffter P, et al. 1999. A radiation hybrid map of the zebrafish genome. Nat. Genet.  23:86-89.
               Hukriede, N., L. Joly, M. Tsang, J. Miles, P. Tellis, J. Epstein, W. Barbazuk, F. Li, B. Paw, J. Postlethwait, T. Hudson, L. Zon, J. McPherson, M. Chevrette, I. Dawid, S. Johnson, and M. Ekker (1999) Radiation hybrid mapping of the zebrafish genome. Proc. Natl. Acad. Sci.,USA 96:9745-9750.
               Kelly, P.D., F. Chu, I.G. Woods, P. Ngo-Hazelett, T. Cardozo, H. Huang, F. Kimm, L. Liao, Y.-L. Yan, Y. Zhou, S.L. Johnson, R. Abagyan, A.F. Schier, J.H. Postlethwait, and W.S. Talbot (2000) Genetic linkage mapping of zebrafish genes and ESTs. Genome Res. 10:558-567.
               Knapik, E. W., Goodman, A., Atkinson, O. S., Roberts, C. T., Shiozawa, M., Sim, C. U., Weksler-Zangen, S., Trolliet, M. R., Futrell, C., Innes, B. A., Koike, G., McLaughlin, M. G., Pierre, L., Simon, J. S., Vilallonga, E., Roy, M., Chiang, P. W., Fishman, M. C., Driever, W., and Jacob, H. J. (1996). A reference cross DNA panel for zebrafish (Danio rerio) anchored with simple sequence length polymorphisms. Development 123:451-460.
               Kwok, C., Korn, R.M., Davis, M.E., Burt, D.W., Critcher, R., M cCarthy, L., Paw, B.H., Zon, L.I., Goodfellow, P.N., and  Schmitt, K. 1998. Characterization of whole genome radiation hybrid mapping resources for non-mammalian vertebrates. Nucleic Acids Res. 26:3562 3566.
               Postlethwait, J.H., Woods, I.G., Ngo-Hazelett, P., Yan, Y.-L., Kelly, P.D., Chu, F., Huang, H., Hill Force, A., and Talbot, W.S. (2000) Zebrafish comparative genomics and the origins of vertebrate chromosomes. Genome Res. 10:1890-1902.
               Shimoda, N., Knapik, E.W., Ziniti, J., Sim, C., Yamada, E., Kaplan, S., Jackson, D., deSauvage, F., Jacob, H., and Fishman, M.C. (1999)  Zebrafish genetic map with 2000 microsatellite markers. Genomics. 58:219-232.
               Woods, I.G., Kelly, P.D., Chu, F., Ngo-Hazelett, P., Yan, Y.-L., Huang, H., Postlethwait, J.H., and Talbot, W.S. (2000) A comparative map of the zebrafish genome. Genome Res. 10:1903-1914.

Links to primary data:
T51 RH panel:

LN54 RH panel:

HS panel:

MGH microsatellite map:

Panel Producer: Postlethwait, John H. Most Recent Update: Oct 7, 2009
Panel type: Meiotic Number of meioses: 0
Current source of genetic material for mapping: Postlethwait, John H.

ZMAP panel: Statistics


    EST (total of 10048)
    SNP (total of 1709)
    SSLP (total of 7618)
    RAPD (total of 204)
    BAC_END (total of 3536)
    STS (total of 2131)
    PAC_END (total of 2)
    MUTANT (total of 2634)
    CDNA (total of 787)
    GENE (total of 6466)
Total of 35135 markers on panel

NOTE: There is too much data to display an entire chromosome
Please use Search ZMap to restrict the query.


Click to see a list of all mapping panels.
ChromosomeMarkers on chromosome
1 SSLP(407) ; RAPD(14) ; STS(108) ; CDNA(37) ; EST(439) ; SNP(112) ; BAC_END(177) ; MUTANT(157) ; GENE(316) ; PAC_END(1)
2 GENE(348) ; STS(123) ; MUTANT(124) ; SSLP(318) ; CDNA(41) ; SNP(80) ; BAC_END(162) ; EST(529) ; RAPD(11)
3 SNP(56) ; SSLP(285) ; RAPD(6) ; STS(83) ; CDNA(49) ; BAC_END(134) ; EST(510) ; MUTANT(135) ; GENE(323)
4 GENE(163) ; MUTANT(51) ; EST(296) ; CDNA(19) ; STS(39) ; RAPD(2) ; BAC_END(78) ; SNP(46) ; SSLP(219)
5 SNP(89) ; SSLP(419) ; BAC_END(211) ; STS(154) ; MUTANT(98) ; PAC_END(1) ; EST(595) ; RAPD(7) ; GENE(414) ; CDNA(52)
6 RAPD(9) ; SNP(105) ; MUTANT(105) ; CDNA(41) ; GENE(250) ; EST(423) ; BAC_END(148) ; SSLP(343) ; STS(97)
7 BAC_END(210) ; STS(136) ; EST(506) ; RAPD(8) ; SNP(90) ; GENE(288) ; CDNA(45) ; MUTANT(210) ; SSLP(416)
8 STS(76) ; EST(421) ; SNP(72) ; MUTANT(95) ; CDNA(26) ; SSLP(311) ; RAPD(11) ; BAC_END(128) ; GENE(291)
9 EST(303) ; CDNA(33) ; GENE(215) ; STS(79) ; SNP(53) ; MUTANT(100) ; BAC_END(125) ; RAPD(13) ; SSLP(289)
10 MUTANT(92) ; STS(72) ; EST(326) ; SSLP(238) ; CDNA(37) ; GENE(210) ; RAPD(9) ; BAC_END(137) ; SNP(69)
11 EST(373) ; CDNA(24) ; SNP(76) ; BAC_END(133) ; MUTANT(99) ; STS(60) ; GENE(229) ; RAPD(9) ; SSLP(253)
12 GENE(235) ; SNP(53) ; MUTANT(84) ; STS(67) ; BAC_END(159) ; EST(358) ; CDNA(36) ; RAPD(1) ; SSLP(349)
13 SSLP(319) ; STS(123) ; GENE(301) ; MUTANT(136) ; SNP(39) ; CDNA(32) ; BAC_END(153) ; EST(437) ; RAPD(4)
14 STS(111) ; SSLP(353) ; SNP(53) ; RAPD(7) ; CDNA(36) ; EST(324) ; BAC_END(170) ; MUTANT(173) ; GENE(236)
15 CDNA(24) ; MUTANT(96) ; EST(359) ; RAPD(7) ; SNP(65) ; GENE(231) ; STS(75) ; BAC_END(132) ; SSLP(297)
16 GENE(297) ; RAPD(8) ; MUTANT(48) ; STS(69) ; CDNA(23) ; EST(484) ; BAC_END(141) ; SSLP(338) ; SNP(78)
17 SNP(57) ; BAC_END(133) ; GENE(205) ; STS(66) ; MUTANT(112) ; RAPD(6) ; SSLP(323) ; CDNA(19) ; EST(345)
18 EST(326) ; GENE(229) ; RAPD(8) ; CDNA(21) ; MUTANT(99) ; SNP(78) ; BAC_END(122) ; STS(54) ; SSLP(312)
19 SSLP(293) ; BAC_END(134) ; GENE(301) ; STS(82) ; EST(465) ; MUTANT(80) ; SNP(73) ; RAPD(10) ; CDNA(30)
20 GENE(250) ; CDNA(29) ; MUTANT(139) ; SNP(32) ; STS(97) ; SSLP(248) ; RAPD(20) ; BAC_END(114) ; EST(366)
21 STS(76) ; BAC_END(131) ; EST(405) ; SNP(92) ; MUTANT(88) ; GENE(212) ; RAPD(4) ; SSLP(286) ; CDNA(23)
22 STS(66) ; RAPD(8) ; MUTANT(71) ; EST(389) ; CDNA(29) ; SNP(73) ; SSLP(201) ; BAC_END(105) ; GENE(256)
23 SSLP(256) ; EST(478) ; CDNA(35) ; BAC_END(161) ; STS(111) ; MUTANT(82) ; GENE(302) ; RAPD(9) ; SNP(81)
24 EST(342) ; BAC_END(142) ; CDNA(23) ; RAPD(8) ; MUTANT(115) ; SNP(49) ; GENE(177) ; SSLP(293) ; STS(59)
25 SNP(38) ; STS(48) ; RAPD(5) ; CDNA(23) ; EST(249) ; BAC_END(96) ; GENE(187) ; MUTANT(45) ; SSLP(252)