Miniature transposable sequences are frequently mobilized in the bacterial plant pathogen Pseudomonas syringae pv. phaseolicola

Mobile genetic elements are widespread in Pseudomonas syringae, and often associate with virulence genes. Genome reannotation of the model bean pathogen P. syringae pv. phaseolicola 1448A identified seventeen types of insertion sequences and two miniature inverted-repeat transposable elements (MITEs) with a biased distribution, representing 2.8% of the chromosome, 25.8% of the 132-kb virulence plasmid and 2.7% of the 52-kb plasmid. Employing an entrapment vector containing sacB, we estimated that transposition frequency oscillated between 2.661025 and 1.161026, depending on the clone, although it was stable for each clone after consecutive transfers in culture media. Transposition frequency was similar for bacteria grown in rich or minimal media, and from cells recovered from compatible and incompatible plant hosts, indicating that growth conditions do not influence transposition in strain 1448A. Most of the entrapped insertions contained a full-length IS801 element, with the remaining insertions corresponding to sequences smaller than any transposable element identified in strain 1448A, and collectively identified as miniature sequences. From these, fragments of 229, 360 and 679-nt of the right end of IS801 ended in a consensus tetranucleotide and likely resulted from one-ended transposition of IS801. An average 0.7% of the insertions analyzed consisted of IS801 carrying a fragment of variable size from gene PSPPH_0008/PSPPH_0017, showing that IS801 can mobilize DNA in vivo. Retrospective analysis of complete plasmids and genomes of P. syringae suggests, however, that most fragments of IS801 are likely the result of reorganizations rather than one-ended transpositions, and that this element might preferentially contribute to genome flexibility by generating homologous regions of recombination. A further miniature sequence previously found to affect host range specificity and virulence, designated MITEPsy1 (100-nt), represented an average 2.4% of the total number of insertions entrapped in sacB, demonstrating for the first time the mobilization of a MITE in bacteria.

A genetic linkage map of an apple rootstock progeny anchored to the Malus genome sequence

An apple rootstock progeny raised from the cross between the very dwarfing ‘M.27’ and the more vigorous ‘M.116’ (‘M.M.106’ × ‘M.27’) was used for the construction of a linkage map comprising a total of 324 loci: 252 previously mapped SSRs, 71 newly characterised or previously unmapped SSR loci (including 36 amplified by 33 out of the 35 novel markers reported here), and the self-incompatibility locus. The map spanned the 17 linkage groups (LG) expected for apple covering a genetic distance of 1,229.5 cM, an estimated 91% of the Malus genome. Linkage groups were well populated and, although marker density ranged from 2.3 to 6.2 cM/SSR, just 15 gaps of more than 15 cM were observed. Moreover, only 17.5% of markers displayed segregation distortion and, unsurprisingly in a semi-compatible backcross, distortion was particularly pronounced surrounding the self-incompatibility locus (S) at the bottom of LG17. DNA sequences of 273 SSR markers and the S locus, representing a total of 314 loci in this investigation, were used to anchor to the ‘Golden Delicious’ genome sequence. More than 260 of these loci were located on the expected pseudo-chromosome on the ‘Golden Delicious’ genome or on its homeologous pseudo-chromosome. In total, 282.4 Mbp of sequence from 142 genome sequence scaffolds of the Malus genome were anchored to the ‘M.27’ × ‘M.116’ map, providing an interface between the marker data and the underlying genome sequence. This will be exploited for the identification of genes responsible for traits of agronomic importance such as dwarfing and water use efficiency.

Variation in genome organization of the plant pathogenic fungus Colletotrichum lindemuthianum

The genome structure of Colletotrichum lindemuthianum in a set of diverse isolates was investigated using a combination of physical and molecular approaches. Flow cytometric measurement of genome size revealed significant variation between strains, with the smallest genome representing 59% of the largest. Southern-blot profiles of a cloned fungal telomere revealed a total chromosome number varying from 9 to 12. Chromosome separations using pulsed-field gel electrophoresis (PFGE) showed that these chromosomes belong to two distinct size classes: a variable number of small (< 2.5 Mb) polymorphic chromosomes and a set of unresolved chromosomes larger than 7 Mb. Two dispersed repeat elements were shown to cluster on distinct polymorphic minichromosomes. Single-copy flanking sequences from these repeat-containing clones specifically marked distinct small chromosomes. These markers were absent in some strains, indicating that part of the observed variability in genome organization may be explained by the presence or absence, in a given strain, of dispensable genomic regions and/or chromosomes.

A Brassica exon array for whole-transcript gene expression profiling

Affymetrix GeneChip (R) arrays are used widely to study transcriptional changes in response to developmental and environmental stimuli. GeneChip (R) arrays comprise multiple 25-mer oligonucleotide probes per gene and retain certain advantages over direct sequencing. For plants, there are several public GeneChip (R) arrays whose probes are localised primarily in 39 exons. Plant whole-transcript (WT) GeneChip (R) arrays are not yet publicly available, although WT resolution is needed to study complex crop genomes such as Brassica, which are typified by segmental duplications containing paralogous genes and/or allopolyploidy. Available sequence data were sampled from the Brassica A and C genomes, and 142,997 gene models identified. The assembled gene models were then used to establish a comprehensive public WT exon array for transcriptomics studies. The Affymetrix GeneChip (R) Brassica Exon 1.0 ST Array is a 5 mu M feature size array, containing 2.4 million 25-base oligonucleotide probes representing 135,201 gene models, with 15 probes per gene distributed among exons. Discrimination of the gene models was based on an E-value cut-off of 1E(-5), with <= 98 sequence identity. The 135 k Brassica Exon Array was validated by quantifying transcriptome differences between leaf and root tissue from a reference Brassica rapa line (R-o-18), and categorisation by Gene Ontologies (GO) based on gene orthology with Arabidopsis thaliana. Technical validation involved comparison of the exon array with a 60-mer array platform using the same starting RNA samples. The 135 k Brassica Exon Array is a robust platform. All data relating to the array design and probe identities are available in the public domain and are curated within the BrassEnsembl genome viewer at http://www.brassica.info/BrassEnsembl/index.html.

Tests of sunspot number sequences: 3. Effects of regression procedures on the calibration of historic sunspot data

We use sunspot group observations from the Royal Greenwich Observatory (RGO) to investigate the effects of intercalibrating data from observers with different visual acuities. The tests are made by counting the number of groups RB above a variable cut-off threshold of observed total whole-spot area (uncorrected for foreshortening) to simulate what a lower acuity observer would have seen. The synthesised annual means of RB are then re-scaled to the full observed RGO group number RA using a variety of regression techniques. It is found that a very high correlation between RA and RB (rAB > 0.98) does not prevent large errors in the intercalibration (for example sunspot maximum values can be over 30 % too large even for such levels of rAB). In generating the backbone sunspot number (RBB), Svalgaard and Schatten (2015, this issue) force regression fits to pass through the scatter plot origin which generates unreliable fits (the residuals do not form a normal distribution) and causes sunspot cycle amplitudes to be exaggerated in the intercalibrated data. It is demonstrated that the use of Quantile-Quantile (“Q  Q”) plots to test for a normal distribution is a useful indicator of erroneous and misleading regression fits. Ordinary least squares linear fits, not forced to pass through the origin, are sometimes reliable (although the optimum method used is shown to be different when matching peak and average sunspot group numbers). However, other fits are only reliable if non-linear regression is used. From these results it is entirely possible that the inflation of solar cycle amplitudes in the backbone group sunspot number as one goes back in time, relative to related solar-terrestrial parameters, is entirely caused by the use of inappropriate and non-robust regression techniques to calibrate the sunspot data.