Can Nep1-like proteins form oligomers?

Nep1-like proteins (NLPs) are a novel family of microbial elicitors of plant necrosis that induce a hypersensitive-like response in dicot plants. The spatial structure and role of these proteins are yet unknown. In a paper published in BMC Plant Biology (2008; 8:50) we have proposed that the core region of Nep1-like proteins (NLPs) belong to the Cupin superfamily. Based on what is known about the Cupin superfamily, in this addendum to the paper we discuss how NLPs could form oligomers.Key words: quaternary structure, necrosis and ethylene inducing proteins, NLPs, MpNEP1, MpNEP2, NPP1, Moniliophthora perniciosa, Phytophthora parasiticaCupins may be organized as monomers, dimers, hexamers and octamers of β-barrel domains.¹ To the best of our knowledge trimers have not been detected yet. The interaction of two monomers building up a dimeric structure is basically performed by three types of interactions: hydrophobic interactions between β-strands in different subunits, salt bridges and hydrogen bonds between β-strands. In cupin dimers, the hydrophobic interactions occur between two βI strands in different subunits (Fig. 1A and B). This strand represents the central axis of rotation of the dimer as one residue in βI interacts with the corresponding residue in the other subunit (Fig. 1B). Therefore, all residues in βI must be hydrophobic, as one residue interacts with the other subunit and the next one in the sequence interacts with the interior of the protein. Charged residues in βI would disrupt such interactions. Most cupin dimers have strong hydrophobic residues such as tryptophan (W), phenylalanine (F) and methionine (M) pointing towards the own subunit (↓), while small hydrophobic residues such as leucine (L), isoleucine (I), and valine (V) point to the other subunit (↑). A particular case is leucine that interacts with other subunits, for instance, βI = liaW (positions 217–220 in Fig. 1B) and βI = LVsw of type I and II NLP consensuses, respectively. Therefore, the pattern of hydropathicity suggests that the side chain orientation is βI = l217 ↑ i218 ↓ a219 ↑ W220 ↓ d221 ↑. However we observe that just after βI there is a charged residue (aspartate D221) which would point outwards disrupting the dimer or at least making it less stable. It is interesting to observe that the requirement for a negatively charged residue at this last position is very high: 96% of all type I NLPs contains an aspartate (D) or glutamate (E) indicating an important role for it, maybe in avoiding dimerization of the NLPs. A second interesting hypothesis is as follows: several cupins are oxygenases, decarboxylases, etc. and use a negatively charged residue, such as aspartate or glutamate as proton donor.¹ Now, if the alternate pattern of side chains of the residues is βI = l217 ↓ i218 ↑ a219 ↓ W220 ↑ d221 ↓, instead of the previous one, then the aspartate or glutamate residue would point to the hydrophobic pocket and would be positioned to interact with the metal ion, as in cupins with enzymatic activity. However, there are no experimental evidences that the NLPs have enzymatic activity.Open in a separate windowFigure 1(A) Three-dimensional structure prediction for type I NLP consensus, (B) Interface between two βI strands in type I NLP consensus. From the left to the right: EF-coil with the conserved residue H162, βC and βH strands (superposed) with the conserved histidines H133 and H135 in βC, H193 and leucine L195 in βH, W220 in βI and W118 in βB. The strands in the right subunit follow the same pattern but rotated.The second type of interaction is salt bridges between charged residues in different subunits. Analyzing all interacting side chains in the 1VJ2 protein (dimer), we verify that the charged side chains of N35 and E57 (numbers in original structure) are only 2.72 Å apart. In the NLPs, this corresponds to N108^36% (Q108^60%) at the border of βB and E138^98%. The negatively charged residue D125 helps to correct the orientation of the subunits in relation to each other avoiding any disorientation. The high conservation level of these residues suggests that NLPs are dimeric structures. However, as we will see next, only hydrophobic and charged interactions are not enough to build a dimer.Garcia et al. (2007)² have used small angle X-ray scattering (SAXS) to show that, in solution, at low concentrations (<2 mg/ml) the two copies of the NLPs of Moniliophthora perniciosa, MpNEP1 and MpNEP2, exist as dimers and monomers, respectively. The same technique showed that at higher concentrations, >5 mg/ml, both proteins exist as dimers, as is the case for PpNPP1.² They also reported, based on electrophoresis analysis, that PpNPP1 and MpNEP1 exist as oligomers and MpNEP2 as monomers.² However, experiments with the PpNPP1 in size exclusion chromatography using myoglobin as size standard suggest that PpNPP1 is a monomer.³ Figure 2 compares MpNEP1, MpNEP2 and PpNPP1, where the most relevant differences in sequence are marked with asterisks (*) and are possibly related to the differences in oligomeric properties between MpNEP1 and PpNPP1 with MpNEP2. These positions are methionine M27 and leucine L35, which occur only in MpNEP2, glycine G250, which occurs only in MpNEP2 and NEP1 (Fusarium oxysporum) and lysine K31, which occurs only MpNEP2, {"type":"entrez-protein","attrs":{"text":"BAB04114","term_id":"10173008"}}BAB04114 (Bacillus halodurans) and {"type":"entrez-protein","attrs":{"text":"AAU23136","term_id":"52003194"}}AAU23136 (Bacillus licheniformis). The other residues are aspartate D28, which occurs 9 times and alanine A37 which occurs 7 times of all investigated NLPs. Thus, the sequence mdHDkiakl at the start of the NLPs seems to explain the monomeric state of MpNEP2, although at higher concentrations they form dimers. Besides the weak hydrophobic interactions, dimeric cupins and bicupins (two β barrels in the same sequence building up a dimeric-like 4d-structure) are stable structures (see Fig. 1 in ref. ⁴). By aggregating the first β-strand in the start domain of one β-barrel to the ABIDG β-sheet of the other β-barrel, composing a big ABIDGY β-sheet (Y is the first β-strand). For instance, using the bicupin 1L3J (oxalate decarboxylase) as template, the low confidence level β-strand at position 26–33 (v in H29D30 avv) in type I NLPs corresponds to the first β-strand. Since this proceeds from both barrels they can build a stable structure (see Fig. 1 in ref. ⁴). The quaternary structure is related to the presence of interaction residues in the BID β-sheet of the cupin structure. These are present in the NLPs and would enable them to form dimers.Open in a separate windowFigure 2Alignment of type I NLP consensus, PpNPP1, MpNEP1 and MpNEP2. Solid line boxes are β-strands, double line boxes are α-helices. The sequence positions marked with asterisks (*) are possibly related to the differences in oligomeric properties between MpNEP1 and PpNPP1 with MpNEP2.     

The multiple sex chromosomes of platypus and echidna are not completely identical and several share homology with the avian Z

Background

Sex-determining systems have evolved independently in vertebrates. Placental mammals and marsupials have an XY system, birds have a ZW system. Reptiles and amphibians have different systems, including temperature-dependent sex determination, and XY and ZW systems that differ in origin from birds and placental mammals. Monotremes diverged early in mammalian evolution, just after the mammalian clade diverged from the sauropsid clade. Our previous studies showed that male platypus has five X and five Y chromosomes, no SRY, and DMRT1 on an X chromosome. In order to investigate monotreme sex chromosome evolution, we performed a comparative study of platypus and echidna by chromosome painting and comparative gene mapping.

Results

Chromosome painting reveals a meiotic chain of nine sex chromosomes in the male echidna and establishes their order in the chain. Two of those differ from those in the platypus, three of the platypus sex chromosomes differ from those of the echidna and the order of several chromosomes is rearranged. Comparative gene mapping shows that, in addition to bird autosome regions, regions of bird Z chromosomes are homologous to regions in four platypus X chromosomes, that is, X₁, X₂, X₃, X₅, and in chromosome Y₁.

Conclusion

Monotreme sex chromosomes are easiest to explain on the hypothesis that autosomes were added sequentially to the translocation chain, with the final additions after platypus and echidna divergence. Genome sequencing and contig anchoring show no homology yet between platypus and therian Xs; thus, monotremes have a unique XY sex chromosome system that shares some homology with the avian Z.     

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation

Background

Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction.

Methods

Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values.

Results

Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied.

Conclusions

These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.     

Prospects for estimating nucleotide divergence with RAPDs

The technique of random amplification of polymorphic DNA (RAPD), which is simply polymerase chain reaction (PCR) amplification of genomic DNA by a single short oligonucleotide primer, produces complex patterns of anonymous polymorphic DNA fragments. The information provided by these banding patterns has proved to be of great utility for mapping and for verification of identity of bacterial strains. Here we consider whether the degree of similarity of the banding patterns can be used to estimate nucleotide diversity and nucleotide divergence. With haploid data, fragments generated by RAPD-PCR can be treated in a fashion very similar to that for restriction-fragment data. Amplification of diploid samples, on the other hand, requires consideration of the fact that presence of a band is dominant to absence of the band. After describing a method for estimating nucleotide divergence on the basis of diploid samples, we summarize the restrictions and criteria that must be met when RAPD data are used for estimating population genetic parameters.      

Efficiency of population structures for mapping of Mendelian and imprinted quantitative trait loci in outbred pigs using variance component methods

In a simulation study different designs for a pure line pig population were compared for efficiency of mapping QTL using the variance component method. Phenotypes affected by a Mendelian QTL, a paternally expressed QTL, a maternally expressed QTL or by a QTL without an effect were simulated. In all alternative designs 960 progeny were phenotyped. Given the limited number of animals there is an optimum between the number of families and the family size. Estimation of Mendelian and parentally expressed QTL is more efficient in a design with large family sizes. Too small a number of sires should be avoided to minimize chances of sires to be non-segregating. When a large number of families is used, the number of haplotypes increases which reduces the accuracy of estimating the QTL effect and thereby reduces the power to show a significant QTL and to correctly position the QTL. Dense maps allow for smaller family size due to exploitation of LD-information. Given the different possible modes of inheritance of the QTL using 8 to16 boars, two litters per dam was optimal with respect to determining significance and correct location of the QTL for a data set consisting of 960 progeny. The variance component method combining linkage disequilibrium and linkage analysis seems to be an appropriate choice to analyze data sets which vary in marker density and which contain complex family structures.     

Microsatellite variation in Drosophila melanogaster and Drosophila simulans: a reciprocal test of the ascertainment bias hypothesis

Interspecific comparisons of microsatellite loci have repeatedly shown that the loci are longer and more variable in the species from which they are derived (the focal species) than are homologous loci in other (nonfocal) species. There is debate as to whether this is due to directional evolution or to an ascertainment bias during the cloning and locus selection processes. This study tests these hypotheses by performing a reciprocal study. Eighteen perfect dinucleotide microsatellite loci identified from a Drosophila simulans library screen and 18 previously identified in an identical Drosophila melanogaster library screen were used to survey natural populations of each species. No difference between focal and nonfocal species was observed for mean PCR fragment length. However, heterozygosity and number of alleles were significantly higher in the focal species than in the nonfocal species. The most common allele in the Zimbabwe population of both species was sequenced for 31 of the 36 loci. The length of the longest stretch of perfect repeat units is, on average, longer in the focal species than in the non-focal species. There is a positive correlation between the length of the longest stretch of perfect repeats and heterozygosity. The difference in heterozygosity can thus be explained by a reduction in the length of the longest stretch of perfect repeats in the nonfocal species. Furthermore, flanking-sequence length difference was noted between the two species at 58% of the loci sequenced. These data do not support the predictions of the directional-evolution hypothesis; however, consistent with the ascertainment bias hypothesis, the lower variability in nonfocal species is an artifact of the microsatellite cloning and isolation process. Our results also suggest that the magnitude of ascertainment bias for repeat unit length is a function of the microsatellite size distribution in the genomes of different species.