DMAP – Graphical representation of physical and genetic map correlation

Next-generation sequencing approaches coupled with appropriate assembly software can provide draft genome sequences of complex organisms as a series of unordered contigs in a timely and cost effective manner. Likewise, high throughput mapping technologies such as DArT and SNP platforms can provide a high density of sequence-anchored markers with which high resolution genetic maps can be constructed. Visualising and interpreting these data requires a new generation of tools as the volume of data leads to considerable redundancy and information overload in graphical representation. DMAP provides a highly configurable visual representation of physical and genetic map correlation, reducing data representation to an aesthetically acceptable degree. It also calculates an optimal orientation for the ordered sequence contigs, highlighting markers that are anomalous and contigs which may be in erroneous positions. Output is as PDF, allowing subsequent refinement prior to print publication and vector based representation for online supplementary figures. The perl scripts have few dependencies and code is freely available under a creative commons license (CC-BY) from the author’s GitHub repository at http://github.com/davidmam/DMAP.git.

Microsatellite discovery from BAC end sequences and genetic mapping to anchor the soybean physical and genetic maps

Whole-genome sequencing of the soybean ( Glycine max (L.) Merr. ‘Williams 82’) has made it important to integrate its physical and genetic maps. To facilitate this integration of maps, we screened 3290 microsatellites (SSRs) identified from BAC end sequences of clones comprising the ‘Williams 82’ physical map. SSRs were screened against 3 mapping populations. We found the AAT and ACT motifs produced the greatest frequency of length polymorphisms, ranging from 17.2% to 32.3% and from 11.8% to 33.3%, respectively. Other useful motifs include the dinucleotide repeats AG, AT, and AG, with frequency of length polymorphisms ranging from 11.2% to 18.4% (AT), 12.4% to 20.6% (AG), and 11.3% to 16.4% (GT). Repeat lengths less than 16 bp were generally less useful than repeat lengths of 40–60 bp. Two hundred and sixty-five SSRs were genetically mapped in at least one population. Of the 265 mapped SSRs, 60 came from BAC singletons not yet placed into contigs of the physical map. One hundred and ten originated in BACs located in contigs for which no genetic map location was previously known. Ninety-five SSRs came from BACs within contigs for which one or more other BACs had already been mapped. For these fingerprinted contigs (FPC) a high percentage of the mapped markers showed inconsistent map locations. A strategy is introduced by which physical and genetic map inconsistencies can be resolved using the preliminary 4× assembly of the whole genome sequence of soybean.

Physical and genetic map of the Spiroplasma kunkelii CR2-3x chromosome

Spiroplasma kunkelii (class Mollicutes) is the characteristically helical, wall-less bacterium that causes corn stunt disease. A combination of restriction enzyme analysis, pulsed-field gel electrophoresis (PFGE), and Southern hybridization analysis was used to construct a physical and genetic map of the S. kunkelii CR2-3x chromosome. The order of restriction fragments on the map was determined by analyses of reciprocal endonuclease double digests employing I-CeuI, AscI, ApaI, EagI, SmaI, BssHII, BglI, and SalI; adjacent fragments were identified on two-dimensional pulsed-field electrophoresis gels. The size of the chromosome was estimated at 1550 kb. Oligonucleotide pairs were designed to prime the amplification of 26 S. kunkelii gene sequences in the polymerase chain reaction (PCR). Using PCR amplicons as probes, the locations of 27 S. kunkelii putative single-copy genes were positioned on the map by Southern hybridization analyses of chromosomal fragments separated in PFGE. The nucleotide sequence of the single ribosomal RNA operon was determined and its location mapped to a chromosomal segment bearing recognition sites for SalI, SmaI, EagI, and I-CeuI.Key words: Spiroplasma kunkelii CR2-3x, corn stunt spiroplasma, mollicutes, genome mapping, two-dimensional pulsed-field gel electrophoresis.