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PubMed2024

Structure and Methyl-lysine Binding Selectivity of the HUSH Complex Subunit MPP8.

The Human Silencing Hub (HUSH) guards the genome from the pathogenic effects of retroelement expression. Composed of MPP8, TASOR, and Periphilin-1, HUSH recognizes actively transcribed retrotransposed sequences by the presence of long (>1.5-kb) nascent transcripts without introns. HUSH recruits effectors that alter chromatin structure, degrade transcripts, and deposit transcriptionally repressive epigenetic marks. Here, we report the crystal structure of the C-terminal domain (CTD) of MPP8 necessary for HUSH activity. The MPP8 CTD consists of five ankyrin repeats followed by a domain with structural homology to the PINIT domains of Siz/PIAS-family SUMO E3 ligases. AlphaFold3 modeling of the MPP8-TASOR complex predicts that a SPOC domain and a domain with a novel fold in TASOR form extended interaction interfaces with the MPP8 CTD. Point mutations at these interfaces resulted in loss of HUSH-dependent transcriptional repression in a cell-based reporter assay, validating the AlphaFold3 model. The MPP8 chromodomain, known to bind the repressive mark H3K9me3, bound with similar or higher affinity to sequences in the H3K9 methyltransferase subunits SETDB1, ATF7IP, G9a, and GLP. Hence, MPP8 promotes heterochromatinization by recruiting H3K9 methyltransferases. Our work identifies novel structural elements in MPP8 required for HUSH complex assembly and silencing, thereby fulfilling vital functions in controlling retrotransposons.

Humans↗
PubMed2026

Molecular characterization of vitellogenin and its receptor with CRISPR-based sgRNA validation in the legume pod borer, Maruca vitrata (Geyer) (Lepidoptera: Crambidae).

Maruca vitrata, the legume pod borer, causes yield losses of up to 80% in grain legumes. Increasing insecticide resistance and environmental concerns necessitate sustainable pest management alternatives. In the present study, the complete vitellogenin (Vg) coding sequence (CDS), a key reproductive gene involved in oogenesis and embryonic development, was cloned and molecularly characterised from M. vitrata. The assembled Vg CDS (∼5.3 kb) shared 99.04% sequence identity with the reported M. vitrata Vg sequence (MG799570.1). Phylogenetic analysis demonstrated close evolutionary association with related Lepidopteran species, while protein domain analysis identified three conserved domains, namely LPD_N, DUF1943, and VWD. Among these, the single exon-encoded LPD_N domain was selected as the target region for CRISPR/Cas9-mediated editing. Homology models of Vg and vitellogenin receptor (VgR) (Global Model Quality Estimation (GMQE): 0.58 and 0.51) showed a favourable interaction by protein-protein docking (score: -295.66). Three single-guide RNAs (sgRNAs) were designed, synthesised through in-vitro transcription, and evaluated using in vitro cleavage assays. sgRNA1 targeting the LPD_N domain and sgRNA2 targeting the signal peptide region exhibited efficient site-specific cleavage activity, whereas sgRNA3 failed to induce cleavage because of an unfavourable secondary structure that likely impaired Cas9-sgRNA complex formation. Overall, this study provides the first CRISPR-oriented functional characterisation and sgRNA validation of the M. vitrata Vg gene, together with structural characterisation of VgR and Vg-VgR interaction analysis, providing preliminary molecular resources for future CRISPR/Cas9 studies and supporting future embryo microinjection and heritable genome editing for sustainable management of M. vitrata.

CRISPR/Cas9↗
PubMed2006

Topological and functional discovery in a gene coexpression meta-network of gastric cancer.

Gastric cancer is a leading cause of global cancer mortality, but comparatively little is known about the cellular pathways regulating different aspects of the gastric cancer phenotype. To achieve a better understanding of gastric cancer at the levels of systems topology, functional modules, and constituent genes, we assembled and systematically analyzed a consensus gene coexpression meta-network of gastric cancer incorporating >300 tissue samples from four independent patient populations (the "gastrome"). We find that the gastrome exhibits a hierarchical scale-free architecture, with an internal structure comprising multiple deeply embedded modules associated with diverse cellular functions. Individual modules display distinct subtopologies, with some (cellular proliferation) being integrated within the primary network, and others (ribosomal biosynthesis) being relatively isolated. One module associated with intestinal differentiation exhibited a remarkably high degree of autonomy, raising the possibility that its specific topological features may contribute towards the frequent occurrence of intestinal metaplasia in gastric cancer. At the single-gene level, we discovered a novel conserved interaction between the PLA2G2A prognostic marker and the EphB2 receptor, and used tissue microarrays to validate the PLA2G2A/EphB2 association. Finally, because EphB2 is a known target of the Wnt signaling pathway, we tested and provide evidence that the Wnt pathway may also similarly regulate PLA2G2A. Many of these findings were not discernible by studying the single patient populations in isolation. Thus, besides enhancing our knowledge of gastric cancer, our results show the broad utility of applying meta-analytic approaches to genome-wide data for the purposes of biological discovery.

Cluster Analysis↗
PubMed2002

GAZE: a generic framework for the integration of gene-prediction data by dynamic programming.

We describe a method (implemented in a program, GAZE) for assembling arbitrary evidence for individual gene components (features) into predictions of complete gene structures. Our system is generic in that both the features themselves, and the model of gene structure against which potential assemblies are validated and scored, are external to the system and supplied by the user. GAZE uses a dynamic programming algorithm to obtain the highest scoring gene structure according to the model and posterior probabilities that each input feature is part of a gene. A novel pruning strategy ensures that the algorithm has a run-time effectively linear in sequence length. To demonstrate the flexibility of our system in the incorporation of additional evidence into the gene prediction process, we show how it can be used to both represent nonstandard gene structures (in the form of trans-spliced genes in Caenorhabditis elegans), and make use of similarity information (in the form of Expressed Sequence Tag alignments), while requiring no change to the underlying software. GAZE is available at http://www.sanger.ac.uk/Software/analysis/GAZE.

Algorithms↗
PubMed2026

Stepwise Humanization of the Yeast TRAPP Core Enables Functional Analysis of TRAPP Variants.

The Transport Protein Particle (TRAPP) complex is a highly conserved multi-subunit tethering complex that plays a critical role in membrane trafficking. Mutations in TRAPP complex subunits have been implicated in a growing spectrum of rare genetic disorders, yet the molecular mechanisms underlying variant pathogenicity often remain unclear. Here, we developed a humanized yeast platform to enable systematic functional characterization of TRAPP complex variants of uncertain significance. Using a stepwise gene replacement strategy in Saccharomyces cerevisiae, we constructed a strain in which five yeast TRAPP core subunits were replaced with their human orthologues. The integration of human subunits was validated through quantitative RT-PCR and Western blotting. Growth assays revealed that partial humanization of the core complex recapitulates key functional aspects of TRAPP assembly and enables the functional investigation of variants of uncertain significance in vivo. Structural modeling and clash analysis provided insights into the impact of specific mutations on complex stability and subunit interactions. TRAPPC3 has not yet been definitively associated with human disease. Introduction of TRAPPC3 variants of uncertain clinical significance into the humanized strain resulted in pronounced growth defects and predicted structural clashes. This work demonstrates the power of humanized yeast as a model for elucidating potential genotype-phenotype relationships in TRAPPopathy disorders and provides a versatile platform to support variant interpretation, mechanistic studies, and potential therapeutic screening.

Saccharomyces cerevisiae↗
PubMed2006

High-throughput trapping of secretory pathway genes in mouse embryonic stem cells.

High-throughput gene trapping is a random approach for inducing insertional mutations across the mouse genome. This approach uses gene trap vectors that simultaneously inactivate and report the expression of the trapped gene at the insertion site, and provide a DNA tag for the rapid identification of the disrupted gene. Gene trapping has been used by both public and private institutions to produce libraries of embryonic stem (ES) cells harboring mutations in single genes. Presently, approximately 66% of the protein coding genes in the mouse genome have been disrupted by gene trap insertions. Among these, however, genes encoding signal peptides or transmembrane domains (secretory genes) are underrepresented because they are not susceptible to conventional trapping methods. Here, we describe a high-throughput gene trapping strategy that effectively targets secretory genes. We used this strategy to assemble a library of ES cells harboring mutations in 716 unique secretory genes, of which 61% were not trapped by conventional trapping, indicating that the two strategies are complementary. The trapped ES cell lines, which can be ordered from the International Gene Trap Consortium (http://www.genetrap.org), are freely available to the scientific community.

Animals↗
PubMed2026

Comparative in silico analysis of Apis mellifera immune responses to Varroa destructor and Tropilaelaps mercedesae: Common and mite-specific molecular signatures.

Parasitic mites Varroa destructor and Tropilaelaps mercedesae represent major threats to global honey bee (Apis mellifera) health and productivity, yet comparative molecular insights into host responses remain limited. To address this, we systematically compiled published studies (2015-2025) reporting genes associated with honey bee interactions with V. destructor (11 studies, 87 genes), T. mercedesae (4 studies, 35 genes), and hygienic behavior (6 studies, 44 genes). Gene identifiers were harmonized to the Amel_HAv3.1 genome assembly, yielding three non-redundant sets: 64 Varroa-associated, 34 Tropilaelaps-associated, and 44 hygienic behavior-associated genes. Venn analysis identified 10 overlapping genes (including A0A088A8D5, A0A088ADL8, ABAE_APIME, Def1, Def2, Gapdh, HYTA_APIME, Imd, LOC726783, and Vg), suggesting conserved defense mechanisms, while 41 and 24 genes were uniquely associated with Varroa and Tropilaelaps, respectively. Enrichment analyses revealed Varroa-responsive genes were enriched in immune processes, chitin catabolism, and signaling pathways (Toll/Imd, MAPK, Wnt). Tropilaelaps-associated genes were enriched for antibacterial defense and stress response, with Toll/Imd signaling as the sole significantly enriched pathway. Overlapping genes reinforced core innate immunity activation. Protein-protein interaction network centrality analysis identified key hub genes: Def1, HYTA_APIME, ABAE_APIME, PPO, Imd, PGRP-LC, Vg for Varroa; and ACPH1_APIME, MRJP1, Vg, LOC726783 for Tropilaelaps. Results demonstrate that, despite differences in mite biology, honey bees show a conserved immune response against both parasites, centered on antibacterial defense, humoral immunity, and activation of the Toll/Imd pathway. Although limited by the in-silico nature and research asymmetries reflecting Tropilaelaps' emergence, this curated resource establishes a comprehensive framework for elucidating shared and distinct molecular defense mechanisms. Ultimately, this approach prioritizes diagnostic markers and candidate genes for functional validation and breeding strategies to enhance colony resilience against mite‑driven disease globally.

Animals↗
PubMed2004

Hierarchical scaffolding with Bambus.

The output of a genome assembler generally comprises a collection of contiguous DNA sequences (contigs) whose relative placement along the genome is not defined. A procedure called scaffolding is commonly used to order and orient these contigs using paired read information. This ordering of contigs is an essential step when finishing and analyzing the data from a whole-genome shotgun project. Most recent assemblers include a scaffolding module; however, users have little control over the scaffolding algorithm or the information produced. We thus developed a general-purpose scaffolder, called Bambus, which affords users significant flexibility in controlling the scaffolding parameters. Bambus was used recently to scaffold the low-coverage draft dog genome data. Most significantly, Bambus enables the use of linking data other than that inferred from mate-pair information. For example, the sequence of a completed genome can be used to guide the scaffolding of a related organism. We present several applications of Bambus: support for finishing, comparative genomics, analysis of the haplotype structure of genomes, and scaffolding of a mammalian genome at low coverage. Bambus is available as an open-source package from our Web site.

Algorithms↗
PubMed2025

Identification of novel cytoskeleton protein involved in spermatogenic cells and sertoli cells of non-obstructive azoospermia based on microarray and bioinformatics analysis.

BACKGROUND: During mammalian spermatogenesis, the cytoskeleton system plays a significant role in morphological changes. Male infertility such as non-obstructive azoospermia (NOA) might be explained by studies of the cytoskeletal system during spermatogenesis. METHODS: The cytoskeleton, scaffold, and actin-binding genes were analyzed by microarray and bioinformatics (771 spermatogenic cellsgenes and 774 Sertoli cell genes). To validate these findings, we cross-referenced our results with data from a single-cell genomics database. RESULTS: In the microarray analyses of three human cases with different NOA spermatogenic cells, the expression of TBL3, MAGEA8, KRTAP3-2, KRT35, VCAN, MYO19, FBLN2, SH3RF1, ACTR3B, STRC, THBS4, and CTNND2 were upregulated, while expression of NTN1, ITGA1, GJB1, CAPZA1, SEPTIN8, and GOLGA6L6 were downregulated. There was an increase in KIRREL3, TTLL9, GJA1, ASB1, and RGPD5 expression in the Sertoli cells of three human cases with NOA, whereas expression of DES, EPB41L2, KCTD13, KLHL8, TRIOBP, ECM2, DVL3, ARMC10, KIF23, SNX4, KLHL12, PACSIN2, ANLN, WDR90, STMN1, CYTSA, and LTBP3 were downregulated. A combined analysis of Gene Ontology (GO) and STRING, were used to predict proteins' molecular interactions and then to recognize master pathways. Functional enrichment analysis showed that the biological process (BP) mitotic cytokinesis, cytoskeleton-dependent cytokinesis, and positive regulation of cell-substrate adhesion were significantly associated with differentially expressed genes (DEGs) in spermatogenic cells. Moleculare function (MF) of DEGs that were up/down regulated, it was found that tubulin bindings, gap junction channels, and tripeptide transmembrane transport were more significant in our analysis. An analysis of GO enrichment findings of Sertoli cells showed BP and MF to be common DEGs. Cell-cell junction assembly, cell-matrix adhesion, and regulation of SNARE complex assembly were significantly correlated with common DEGs for BP. In the study of MF, U3 snoRNA binding, and cadherin binding were significantly associated with common DEGs. CONCLUSION: Our analysis, leveraging single-cell data, substantiated our findings, demonstrating significant alterations in gene expression patterns.

Male↗
PubMed2006

Dissecting virulence pathways of Mycobacterium tuberculosis through protein-protein association.

The sudden increase in information derived from the completed Mycobacterium tuberculosis (Mtb) genome sequences has revealed the need for approaches capable of converting raw genome sequence data into functional information. To date, an experimental system for studying protein-protein association in mycobacteria is not available. We have developed a simple system, termed mycobacterial protein fragment complementation (M-PFC), that is based upon the functional reconstitution of two small murine dihydrofolate reductase domains independently fused to two interacting proteins. Using M-PFC, we have successfully demonstrated dimerization of yeast GCN4, interaction between Mtb KdpD and KdpE, and association between Esat-6 and Cfp-10. We established the association between the sensor kinase, DevS, and response regulator, DevR, thereby demonstrating the potential of M-PFC to study protein associations in the mycobacterial membrane. To validate our system, we screened an Mtb library for proteins that associate with the secreted antigen Cfp-10 and consistently identified Esat-6 in our screens. Additional proteins that specifically associate with Cfp-10 include Rv0686 and Rv2151c (FtsQ), a component and substrate, respectively, of the evolutionary conserved signal recognition pathway; and Rv3596c (ClpC1), an AAA-ATPase chaperone involved in protein translocation and quality control. Our results provide empirical evidence that directly links the Mtb specialized secretion pathway with the evolutionary conserved signal recognition and SecA/SecYEG pathways, suggesting they share secretory components. We anticipate that M-PFC will be a major contributor to the systematic assembly of mycobacterial protein interaction maps that will lead to the development of better strategies for the control of tuberculosis.

Bacterial Proteins↗
PubMed1998

Assembling genes from predicted exons in linear time with dynamic programming.

In a number of programs for gene structure prediction in higher eukaryotic genomic sequences, exon prediction is decoupled from gene assembly: a large pool of candidate exons is predicted and scored from features located in the query DNA sequence, and candidate genes are assembled from such a pool as sequences of nonoverlapping frame-compatible exons. Genes are scored as a function of the scores of the assembled exons, and the highest scoring candidate gene is assumed to be the most likely gene encoded by the query DNA sequence. Considering additive gene scoring functions, currently available algorithms to determine such a highest scoring candidate gene run in time proportional to the square of the number of predicted exons. Here, we present an algorithm whose running time grows only linearly with the size of the set of predicted exons. Polynomial algorithms rely on the fact that, while scanning the set of predicted exons, the highest scoring gene ending in a given exon can be obtained by appending the exon to the highest scoring among the highest scoring genes ending at each compatible preceding exon. The algorithm here relies on the simple fact that such highest scoring gene can be stored and updated. This requires scanning the set of predicted exons simultaneously by increasing acceptor and donor position. On the other hand, the algorithm described here does not assume an underlying gene structure model. Indeed, the definition of valid gene structures is externally defined in the so-called Gene Model. The Gene Model specifies simply which gene features are allowed immediately upstream which other gene features in valid gene structures. This allows for great flexibility in formulating the gene identification problem. In particular it allows for multiple-gene two-strand predictions and for considering gene features other than coding exons (such as promoter elements) in valid gene structures.

Algorithms↗
PubMed2004

Tertiary structure predictions on a comprehensive benchmark of medium to large size proteins.

We evaluate tertiary structure predictions on medium to large size proteins by TASSER, a new algorithm that assembles protein structures through rearranging the rigid fragments from threading templates guided by a reduced Calpha and side-chain based potential consistent with threading based tertiary restraints. Predictions were generated for 745 proteins 201-300 residues in length that cover the Protein Data Bank (PDB) at the level of 35% sequence identity. With homologous proteins excluded, in 365 cases, the templates identified by our threading program, PROSPECTOR_3, have a root-mean-square deviation (RMSD) to native < 6.5 angstroms, with >70% alignment coverage. After TASSER assembly, in 408 cases the best of the top five full-length models has a RMSD < 6.5 angstroms. Among the 745 targets are 18 membrane proteins, with one-third having a predicted RMSD < 5.5 A. For all representative proteins less than or equal to 300 residues that have corresponding multiple NMR structures in the Protein Data Bank, approximately 20% of the models generated by TASSER are closer to the NMR structure centroid than the farthest individual NMR model. These results suggest that reasonable structure predictions for nonhomologous large size proteins can be automatically generated on a proteomic scale, and the application of this approach to structural as well as functional genomics represent promising applications of TASSER.

Algorithms↗
PubMed2006

An automated method for rapid identification of putative gene family members in plants.

BACKGROUND: Gene duplication events have played a significant role in genome evolution, particularly in plants. Exhaustive searches for all members of a known gene family as well as the identification of new gene families has become increasingly important. Subfunctionalization via changes in regulatory sequences following duplication (adaptive selection) appears to be a common mechanism of evolution in plants and can be accompanied by purifying selection on the coding region. Such negative selection can be detected by a bias toward synonymous over nonsynonymous substitutions. However, the process of identifying this bias requires many steps usually employing several different software programs. We have simplified the process and significantly shortened the time required by condensing many steps into a few scripts or programs to rapidly identify putative gene family members beginning with a single query sequence. RESULTS: In this report we 1) describe the software tools (SimESTs, PCAT, and SCAT) developed to automate the gene family identification, 2) demonstrate the validity of the method by correctly identifying 3 of 4 PAL gene family members from Arabidopsis using EST data alone, 3) identify 2 to 6 CAD gene family members from Glycine max (previously unidentified), and 4) identify 2 members of a putative Glycine max gene family previously unidentified in any plant species. CONCLUSION: Gene families in plants, particularly that subset where purifying selection has occurred in the coding region, can be identified quickly and easily by integrating our software tools and commonly available contig assembly and ORF identification programs.

Arabidopsis↗
PubMed2004

A novel, high-performance random array platform for quantitative gene expression profiling.

We have developed a new microarray technology for quantitative gene-expression profiling on the basis of randomly assembled arrays of beads. Each bead carries a gene-specific probe sequence. There are multiple copies of each sequence-specific bead in an array, which contributes to measurement precision and reliability. We optimized the system for specific and sensitive analysis of mammalian RNA, and using RNA controls of defined concentration, obtained the following estimates of system performance: specificity of 1:250,000 in mammalian poly(A(+)) mRNA; limit of detection 0.13 pM; dynamic range 3.2 logs; and sufficient precision to detect 1.3-fold differences with 95% confidence within the dynamic range. Measurements of expression differences between human brain and liver were validated by concordance with quantitative real-time PCR (R(2) = 0.98 for log-transformed ratios, and slope of the best-fit line = 1.04, for 20 genes). Quantitative performance was further verified using a mouse B- and T-cell model system. We found published reports of B- or T-cell-specific expression for 42 of 59 genes that showed the greatest differential expression between B- and T-cells in our system. All of the literature observations were concordant with our results. Our experiments were carried out on a 96-array matrix system that requires only 100 ng of input RNA and uses standard microtiter plates to process samples in parallel. Our technology has advantages for analyzing multiple samples, is scalable to all known genes in a genome, and is flexible, allowing the use of standard or custom probes in an array.

Animals↗
PubMed2006

Prediction of active nodes in the transcriptional network of neural tube patterning.

A transcriptional network governs patterning in the developing spinal cord. As the developmental program runs, the levels of sequence-specific DNA-binding transcription factors (SSTFs) in each progenitor cell type change to ultimately define a set of postmitotic populations with combinatorial codes of expressed SSTFs. A network description of the neural tube (NT) transcriptional patterning process will require definition of nodes (SSTFs and target enhancers) and edges (interactions between nodes). There are 1,600 SSTF nodes in a given mammalian genome. To limit the complexity of a network description, it will be useful to discriminate between active and passive SSTF nodes. We define active SSTF nodes as those that are differentially expressed within the system. Our system, the developing NT, was partitioned into two pools of genetically defined populations by using flow sorting. Microarray comparisons across the partition led to an estimate of 500-700 active SSTF nodes in the transcriptional network of the developing NT. These included most of the 66 known SSTFs assembled from review articles and recent reports on NT patterning. Empirical cutoffs based on the performance of knowns were used to identify 188 further active SSTFs nodes that performed similarly. The general utility and limitations of the population-partitioning paradigm are discussed.

Animals↗
PubMed2003

Design and assessment of a fast algorithm for identifying specific probes for human and mouse genes.

MOTIVATION: Mammalian genomes are highly complex. To identify the unique sequences of each gene in a mammalian gene database containing tens of thousands of DNA sequences is a computation intensive task. With the advent of parallel genetic analysis methods such as microarrays and the availability of more and more whole genome sequences of organisms, an algorithm allowing speedy identification of the unique gene probes for functional studies of individual genes will be a very useful tool. RESULTS: We have developed a fast algorithm as well as a software program based on the algorithm for identifying gene specific probes of complex organisms. The algorithm was applied to the assemblies of gene sequences and was highly efficient for large databases such as the TIGR human THC and mouse TC databases. The results were assessed with the BLAST sequence alignment software. Two probe data sets have been compiled to contain specific probes for around 100 000 putative human gene transcripts and 70 000 putative mouse gene transcripts. AVAILABILITY: The gene specific probes for the putative human and mouse genes referenced in the TIGR gene indices are available at: ftp://genestamp.ibms.sinica.edu.tw/pub/SpecificP/. The software program and the source codes are available upon request.

Algorithms↗
PubMed2006

Accurate phylogenetic classification of variable-length DNA fragments.

Metagenome studies have retrieved vast amounts of sequence data from a variety of environments leading to new discoveries and insights into the uncultured microbial world. Except for very simple communities, the encountered diversity has made fragment assembly and the subsequent analysis a challenging problem. A taxonomic characterization of metagenomic fragments is required for a deeper understanding of shotgun-sequenced microbial communities, but success has mostly been limited to sequences containing phylogenetic marker genes. Here we present PhyloPythia, a composition-based classifier that combines higher-level generic clades from a set of 340 completed genomes with sample-derived population models. Extensive analyses on synthetic and real metagenome data sets showed that PhyloPythia allows the accurate classification of most sequence fragments across all considered taxonomic ranks, even for unknown organisms. The method requires no more than 100 kb of training sequence for the creation of accurate models of sample-specific populations and can assign fragments >or=1 kb with high specificity.

Animals↗
PubMed2004

Integrated and sequence-ordered BAC- and YAC-based physical maps for the rat genome.

As part of the effort to sequence the genome of Rattus norvegicus, we constructed a physical map comprised of fingerprinted bacterial artificial chromosome (BAC) clones from the CHORI-230 BAC library. These BAC clones provide approximately 13-fold redundant coverage of the genome and have been assembled into 376 fingerprint contigs. A yeast artificial chromosome (YAC) map was also constructed and aligned with the BAC map via fingerprinted BAC and P1 artificial chromosome clones (PACs) sharing interspersed repetitive sequence markers with the YAC-based physical map. We have annotated 95% of the fingerprint map clones in contigs with coordinates on the version 3.1 rat genome sequence assembly, using BAC-end sequences and in silico mapping methods. These coordinates have allowed anchoring 358 of the 376 fingerprint map contigs onto the sequence assembly. Of these, 324 contigs are anchored to rat genome sequences localized to chromosomes, and 34 contigs are anchored to unlocalized portions of the rat sequence assembly. The remaining 18 contigs, containing 54 clones, still require placement. The fingerprint map is a high-resolution integrative data resource that provides genome-ordered associations among BAC, YAC, and PAC clones and the assembled sequence of the rat genome.

Animals↗