The gene for trypsin inhibitor CMe is regulated in trans by the lys 3a locus in the endosperm of barley (Hordeum vulgare L.)

Summary A cDNA encoding trypsin inhibitor CMe from barley endosperm has been cloned and characterized. The longest open reading frame of the cloned cDNA codes for a typical signal peptide of 24 residues followed by a sequence which is identical to the known amino acid sequence of the inhibitor, except for an Ile/Leu substitution at position 59. Southern blot analysis of wheat-barley addition lines has shown that chromosome 3H of barley carries the gene for CMe. This protein is present at less than 2%–3% of the wild-type amount in the mature endosperm of the mutant Risø 1508 with respect to Bomi barley, from which it has been derived, and the corresponding steady state levels of the CMe mRNA are about I%. One or two copies of the CMe gene (synonym Itc1) per haploid genome have been estimated both in the wild type and in the mutant, and DNA restriction patterns are identical in both stocks, so neither a change in copy number nor a major rearrangement of the structural gene account for the markedly decreased expression. The mutation at the lys 3a locus in Risø 1508 has been previously mapped in chromosome 7 (synonym 5H). A single dose of the wild-type allele at this locus (Lys 3a) restores the expression of gene CMe (allele CMe-1) in chromosome 3H to normal levels.     

Isolation and promoter characterization of barley geneItr1 encoding trypsin inhibitor BTI-CMe: differential activity in wild-type and mutantlys3a endosperm

The geneItr1, encoding trypsin inhibitor BTI-CMe, has been obtained from a genomic library ofHordeum vulgare L. The gene has no introns and presents in its 5-upstream region 605 bp that are homologous to the long terminal repeats (LTR) of the copia-like retro-transposon Bare-1. Functional analysis of theItr1 promoter by transient expression in protoplasts derived from different barley tissues, has shown that in this system theItr1 promoter retains its endosperm specifity and thetrans-regulation mediated by theLys3a gene. The proximal promoter extending 343 bp upstream of the translation initiation ATG codon is sufficient to confer fullGUS expression and for endosperm specifity. In protoplasts derived from thelys3a mutant, Risø 1508,GUS activity was less than 5% of that obtained with the same constructs in the protoplasts of wild-type Bomi from which it derives. Gel retardation experiments, after incubation with proteins obtained from both types of endosperm nuclei, also show differential patterns. Possible reasons for these differences are discussed.Equal authours     

Control of galactosyl diglycerides in wheat endosperm by group 5 chromosomes

Lower levels of monogalactosyl diglyceride (MGDG) and digalactosyl diglyceride (DGDG) have been found in tetraploid wheats as compared with those in hexaploid wheats. The same difference has been found between hexaploid cultivars and tetraploid lines derived from them by D genome extraction. A lower level of MGDG and DGDG is also present in Triticum carthlicum (AABB) as compared with Aegilops squarrosa (DD) or with the synthetic T. spelta (AABBDD) obtained from them. Analysis of the appropriate nullitetrasomic and ditelosomic lines indicates that a gene or genes located in the short arm of chromosome 5D are responsible for the observed difference and that group 5 chromosomes can be ranked as to their influence on the MGDG and DGDG levels in the order 5B > 5D > 5A and 5D > 5B > 5A, respectively. These results further support our previous identification of DGDG as the lipid factor responsible for petroleum ether solubility of lipopurothionins. Since DGDG contributes to baking quality by improving the retention of fermentation gases, the present observations imply that the difference in bread-making quality between the two types of wheat is not due only to proteins contributed by the D genome.     

Extreme divergence of a novel wheat thionin generated by a mutational burst specifically affecting the mature protein domain of the precursor.

A new type of neutral thionin (type V), specifically expressed in developing wheat endosperm, has been found to be encoded by a set of single-copy genes located in the long arms of chromosomes 1A, 1B and 1D, within less than 10,000 base-pairs of those corresponding to the highly basic type-I thionins. Divergence between types I and V has occurred through a process of accelerated evolution that has affected the amino acid sequence of the mature thionin but not the precursor domains corresponding to the N-terminal signal peptide and the long C-terminal acidic peptide. This process involved a deletion and a non-synonymous nucleotide substitution rate equal to the synonymous rate in the thionin sequence.     

A (1-->6)-linked beta-mannopyrananan, pseudonigeran, and a (1-->4)-linked beta-xylan, isolated from the lichenised basidiomycete Dictyonema glabratum

Extraction of Dictyonema glabratum with hot 2% (w/v) aqueous KOH at 100 degrees C, followed by neutralisation and freeze-thawing, gave an insoluble glucan. The residue was further extracted by a similar process, but with hot 10% (w/v) aqueous KOH, furnishing a mixture of glucan, mannan and xylan. The mannan and xylan were obtained via precipitation of its copper complex with Fehling's solution, leaving the glucan in the supernatant. The insoluble complex was finally purified through gel permeation chromatography. Methylation analysis, one- and two-dimensional nuclear magnetic resonance examination showed the polysaccharides to be a (1-->3)-linked alpha-glucan (pseudonigeran) and a (1-->4)-linked beta-xylan, both not previously encountered in lichens, and a newly discovered (1-->6)-linked beta-mannan.     

Spatio‐temporal scaling of biodiversity and the species–time relationship in a stream fish assemblage

1. The increase of species richness with the area of the habitat sampled, that is the species–area relationship, and its temporal analogue, the species–time relationship (STR), are among the few general laws in ecology with strong conservation implications. However, these two scale‐dependent phenomena have rarely been considered together in biodiversity assessment, especially in freshwater systems. 2. We examined how the spatial scale of sampling influences STRs for a Central‐European stream fish assemblage (second‐order Bernecei stream, Hungary) using field survey data in two simulation‐based experiments. 3. In experiment one, we examined how increasing the number of channel units, such as riffles and pools (13 altogether), and the number of field surveys involved in the analyses (12 sampling occasions during 3 years), influence species richness. Complete nested curves were constructed to quantify how many species one observes in the community on average for a given number of sampling occasions at a given spatial scale. 4. In experiment two, we examined STRs for the Bernecei fish assemblage from a landscape perspective. Here, we evaluated a 10‐year reach level data set (2000–09) for the Bernecei stream and its recipient watercourse (third‐order Kemence stream) to complement results on experiment one and to explore the mechanisms behind the observed patterns in more detail. 5. Experiment one indicated the strong influence of the spatial scale of sampling on the accumulation of species richness, although time clearly had an additional effect. The simulation methodology advocated here helped to estimate the number of species in a diverse combination of spatial and temporal scale and, therefore, to determine how different scale combinations influence sampling sufficiency. 6. Experiment two revealed differences in STRs between the upstream (Bernecei) and downstream (Kemence) sites, with steeper curves for the downstream site. Equations of STR curves were within the range observed in other studies, predominantly from terrestrial systems. Assemblage composition data suggested that extinction–colonisation dynamics of rare, non‐resident (i.e. satellite) species influenced patterns in STRs. 7. Our results highlight that the determination of species richness can benefit from the joint consideration of spatial and temporal scales in biodiversity inventory surveys. Additionally, we reveal how our randomisation‐based methodology may help to quantify the scale dependency of diversity components (α, β, γ) in both space and time, which have critical importance in the applied context.