K-SPMM: a database of murine spermatogenic promoters modules & motifs

BACKGROUND: Understanding the regulatory processes that coordinate the cascade of gene expression leading to male gamete development has proven challenging. Research has been hindered in part by an incomplete picture of the regulatory elements that are both characteristic of and distinctive to the broad population of spermatogenically expressed genes. DESCRIPTION: K-SPMM, a database of murine Spermatogenic Promoters Modules and Motifs, has been developed as a web-based resource for the comparative analysis of promoter regions and their constituent elements in developing male germ cells. The system contains data on 7,551 genes and 11,715 putative promoter regions in Sertoli cells, spermatogonia, spermatocytes and spermatids. K-SPMM provides a detailed portrait of promoter site components, ranging from broad distributions of transcription factor binding sites to graphical illustrations of dimeric modules with respect to individual transcription start sites. Binding sites are identified through their similarities to position weight matrices catalogued in either the JASPAR or the TRANSFAC transcription factor archives. A flexible search function allows sub-populations of promoters to be identified on the basis of their presence in any of the four cell-types, their association with a list of genes or their component transcription-factor families. CONCLUSION: This system can now be used independently or in conjunction with other databases of gene expression as a powerful aid to research networks of co-regulation. We illustrate this with respect to the spermiogenically active protamine locus in which binding sites are predicted that align well with biologically foot-printed protein binding domains. AVAILABILITY

Conserving, Distributing and Managing Genetically Modified Mouse Lines by Sperm Cryopreservation

Sperm from C57BL/6 mice are difficult to cryopreserve and recover. Yet, the majority of genetically modified (GM) lines are maintained on this genetic background.Reported here is the development of an easily implemented method that consistently yields fertilization rates of 70+/-5% with this strain. This six-fold increase is achieved by collecting sperm from the vas deferens and epididymis into a cryoprotective medium of 18% raffinose (w/v), 3% skim milk (w/v) and 477 microM monothioglycerol. The sperm suspension is loaded into 0.25 mL French straws and cooled at 37+/-1 degrees C/min before being plunged and then stored in LN(2). Subsequent to storage, the sperm are warmed at 2,232+/-162 degrees C/min and incubated in in vitro fertilization media for an hour prior to the addition of oocyte cumulus masses from superovulated females. Sperm from 735 GM mouse lines on 12 common genetic backgrounds including C57BL/6J, BALB/cJ, 129S1/SvImJ, FVB/NJ and NOD/ShiLtJ were cryopreserved and recovered. C57BL/6J and BALB/cByJ fertilization rates, using frozen sperm, were slightly reduced compared to rates involving fresh sperm; fertilization rates using fresh or frozen sperm were equivalent in all other lines. Developmental capacity of embryos produced using cryopreserved sperm was equivalent, or superior to, cryopreserved IVF-derived embryos.Combined, these results demonstrate the broad applicability of our approach as an economical and efficient option for archiving and distributing mice

HMMerThread: Detecting Remote, Functional Conserved Domains in Entire Genomes by Combining Relaxed Sequence-Database Searches with Fold Recognition

Conserved domains in proteins are one of the major sources of functional information for experimental design and genome-level annotation. Though search tools for conserved domain databases such as Hidden Markov Models (HMMs) are sensitive in detecting conserved domains in proteins when they share sufficient sequence similarity, they tend to miss more divergent family members, as they lack a reliable statistical framework for the detection of low sequence similarity. We have developed a greatly improved HMMerThread algorithm that can detect remotely conserved domains in highly divergent sequences. HMMerThread combines relaxed conserved domain searches with fold recognition to eliminate false positive, sequence-based identifications. With an accuracy of 90%, our software is able to automatically predict highly divergent members of conserved domain families with an associated 3-dimensional structure. We give additional confidence to our predictions by validation across species. We have run HMMerThread searches on eight proteomes including human and present a rich resource of remotely conserved domains, which adds significantly to the functional annotation of entire proteomes. We find ∼4500 cross-species validated, remotely conserved domain predictions in the human proteome alone. As an example, we find a DNA-binding domain in the C-terminal part of the A-kinase anchor protein 10 (AKAP10), a PKA adaptor that has been implicated in cardiac arrhythmias and premature cardiac death, which upon stress likely translocates from mitochondria to the nucleus/nucleolus. Based on our prediction, we propose that with this HLH-domain, AKAP10 is involved in the transcriptional control of stress response. Further remotely conserved domains we discuss are examples from areas such as sporulation, chromosome segregation and signalling during immune response. The HMMerThread algorithm is able to automatically detect the presence of remotely conserved domains in proteins based on weak sequence similarity. Our predictions open up new avenues for biological and medical studies. Genome-wide HMMerThread domains are available at http://vm1-hmmerthread.age.mpg.de