Differences in water release for the binding of EcoRI to specific and nonspecific DNA sequences.

The free energy difference between complexes of the restriction nuclease EcoRI with nonspecific DNA and with the enzyme's recognition sequence is linearly dependent on the water chemical potential of the solution, set using several very different solutes, ranging from glycine and glycerol to triethylene glycol and sucrose. This osmotic dependence indicates that the nonspecific complex sequesters some 110 waters more than the specific complex with the recognition sequence. The insensitivity of the difference in number of waters released to the solute identity further indicates that this water is sequestered in a space that is sterically inaccessible to solutes, most likely at the protein-DNA interface of the nonspecific complex. Calculations based on the structure of the specific complex suggest that the apposing DNA and protein surfaces in the nonspecific complex retain approximately a full hydration layer of water.

Multiple-complete-digest restriction fragment mapping: Generating sequence-ready maps for large-scale DNA sequencing

Multiple-complete-digest mapping is a DNA mapping technique based on complete-restriction-digest fingerprints of a set of clones that provides highly redundant coverage of the mapping target. The maps assembled from these fingerprints order both the clones and the restriction fragments. Maps are coordinated across three enzymes in the examples presented. Starting with yeast artificial chromosome contigs from the 7q31.3 and 7p14 regions of the human genome, we have produced cosmid-based maps spanning more than one million base pairs. Each yeast artificial chromosome is first subcloned into cosmids at a redundancy of ×15–30. Complete-digest fragments are electrophoresed on agarose gels, poststained, and imaged on a fluorescent scanner. Aberrant clones that are not representative of the underlying genome are rejected in the map construction process. Almost every restriction fragment is ordered, allowing selection of minimal tiling paths with clone-to-clone overlaps of only a few thousand base pairs. These maps demonstrate the practicality of applying the experimental and software-based steps in multiple-complete-digest mapping to a target of significant size and complexity. We present evidence that the maps are sufficiently accurate to validate both the clones selected for sequencing and the sequence assemblies obtained once these clones have been sequenced by a “shotgun” method.

Transposon Tc1-derived, sequence-tagged sites in Caenorhabditis elegans as markers for gene mapping

We present an approach to map large numbers of Tc1 transposon insertions in the genome of Caenorhabditis elegans. Strains have been described that contain up to 500 polymorphic Tc1 insertions. From these we have cloned and shotgun sequenced over 2000 Tc1 flanks, resulting in an estimated set of 400 or more distinct Tc1 insertion alleles. Alignment of these sequences revealed a weak Tc1 insertion site consensus sequence that was symmetric around the invariant TA target site and reads CAYATATRTG. The Tc1 flanking sequences were compared with 40 Mbp of a C. elegans genome sequence. We found 151 insertions within the sequenced area, a density of ≈1 Tc1 insertion in every 265 kb. As the rest of the C. elegans genome sequence is obtained, remaining Tc1 alleles will fall into place. These mapped Tc1 insertions can serve two functions: (i) insertions in or near genes can be used to isolate deletion derivatives that have that gene mutated; and (ii) they represent a dense collection of polymorphic sequence-tagged sites. We demonstrate a strategy to use these Tc1 sequence-tagged sites in fine-mapping mutations.

Mapping the σ70 subunit contact sites on Escherichia coli RNA polymerase with a σ70-conjugated chemical protease

The core enzyme of Escherichia coli RNA polymerase acquires essential promoter recognition and transcription initiation activities by binding one of several σ subunits. To characterize the proximity between σ70, the major σ for transcription of the growth-related genes, and the core enzyme subunits (α2ββ′), we analyzed the protein-cutting patterns produced by a set of covalently tethered FeEDTA probes [FeBABE: Fe (S)-1-(p-bromoacetamidobenzyl)EDTA]. The probes were positioned in or near conserved regions of σ70 by using seven mutants, each carrying a single cysteine residue at position 132, 376, 396, 422, 496, 517, or 581. Each FeBABE-conjugated σ70 was bound to the core enzyme, which led to cleavage of nearby sites on the β and β′ subunits (but not α). Unlike the results of random cleavage [Greiner, D. P., Hughes, K. A., Gunasekera, A. H. & Meares, C. F. (1996) Proc. Natl. Acad. Sci. USA 93, 71–75], the cut sites from different probe-modified σ70 proteins are clustered in distinct regions of the subunits. On the β subunit, cleavage is observed in two regions, one between residues 383 and 554, including the conserved C and Rif regions; and the other between 854 and 1022, including conserved region G, regions of ppGpp sensitivity, and one of the segments forming the catalytic center of RNA polymerase. On the β′ subunit, the cleavage was identified within the sequence 228–461, including β′ conserved regions C and D (which comprise part of the catalytic center).

Solution to Darwin's dilemma: Discovery of the missing Precambrian record of life

In 1859, in On the Origin of Species, Darwin broached what he regarded to be the most vexing problem facing his theory of evolution—the lack of a rich fossil record predating the rise of shelly invertebrates that marks the beginning of the Cambrian Period of geologic time (≈550 million years ago), an “inexplicable” absence that could be “truly urged as a valid argument” against his all embracing synthesis. For more than 100 years, the “missing Precambrian history of life” stood out as one of the greatest unsolved mysteries in natural science. But in recent decades, understanding of life's history has changed markedly as the documented fossil record has been extended seven-fold to some 3,500 million years ago, an age more than three-quarters that of the planet itself. This long-sought solution to Darwin's dilemma was set in motion by a small vanguard of workers who blazed the trail in the 1950s and 1960s, just as their course was charted by a few pioneering pathfinders of the previous century, a history of bold pronouncements, dashed dreams, search, and final discovery.

Fine mapping of colon tumor susceptibility (Scc) genes in the mouse, different from the genes known to be somatically mutated in colon cancer.

The predisposition to colon cancer is multigenetically controlled in animals and probably also in humans. We have analyzed the multigenic control of susceptibility to 1,2-dimethylhydrazine-induced colon tumors in mice by using a set of 20 homozygous CcS/Dem recombinant congenic strains, each of which contains a different random subset of approximately 12.5% of genes from the susceptible strain STS/A and 87.5% of genes from the relatively resistant strain BALB/cHeA. Some CcS/Dem strains received the alleles from the susceptible strain STS/A at one or more of the multiple colon tumor susceptibility loci and are susceptible, whereas others are resistant. Linkage analysis shows that these susceptibility genes are different from the mouse homologs of the genes known to be somatically mutated in human colon cancer (KRAS2, TP53, DCC, MCC, APC, MSH2, and probably also MLH1). Different subsets of genes control tumor numbers and size. Two colon cancer susceptibility genes, Scc1 and Scc2, map to mouse chromosome 2. The Scc1 locus has been mapped to a narrow region of 2.4 centimorgans (90% confidence interval).

A maximum likelihood algorithm for genome mapping of cytogenetic loci from meiotic configuration data.

Frequencies of meiotic configurations in cytogenetic stocks are dependent on chiasma frequencies in segments defined by centromeres, breakpoints, and telomeres. The expectation maximization algorithm is proposed as a general method to perform maximum likelihood estimations of the chiasma frequencies in the intervals between such locations. The estimates can be translated via mapping functions into genetic maps of cytogenetic landmarks. One set of observational data was analyzed to exemplify application of these methods, results of which were largely concordant with other comparable data. The method was also tested by Monte Carlo simulation of frequencies of meiotic configurations from a monotelodisomic translocation heterozygote, assuming six different sample sizes. The estimate averages were always close to the values given initially to the parameters. The maximum likelihood estimation procedures can be extended readily to other kinds of cytogenetic stocks and allow the pooling of diverse cytogenetic data to collectively estimate lengths of segments, arms, and chromosomes.