Effects of different types of low‐intensity management on plant‐pollinator interactions in Estonian grasslands

In the face of global pollinator decline, extensively managed grasslands play an important role in supporting stable pollinator communities. However, different types of extensive management may promote particular plant species and thus particular functional traits. As the functional traits of flowering plant species (e.g., flower size and shape) in a habitat help determine the identity and frequency of pollinator visitors, they can also influence the structures of plant−pollinator interaction networks (i.e., pollination networks). The aim of this study was to examine how the type of low‐intensity traditional management influences plant and pollinator composition, the structure of plant−pollinator interactions, and their mediation by floral and insect functional traits. Specifically, we compared mown wooded meadows to grazed alvar pastures in western Estonia. We found that both management types fostered equal diversity of plants and pollinators, and overlapping, though still distinct, plant and pollinator compositions. Wooded meadow pollination networks had significantly higher connectance and specialization, while alvar pasture networks achieved higher interaction diversity at a standardized sampling of interactions. Pollinators with small body sizes and short proboscis lengths were more specialized in their preference for particular plant species and the specialization of individual pollinators was higher in alvar pastures than in wooded meadows. All in all, the two management types promoted diverse plant and pollinator communities, which enabled the development of equally even and nested pollination networks. The same generalist plant and pollinator species were important for the pollination networks of both wooded meadows and alvar pastures; however, they were complemented by management‐specific species, which accounted for differences in network structure. Therefore, the implementation of both management types in the same landscape helps to maintain high species and interaction diversity.     

Identification of Single Nucleotide Polymorphisms Associated with Brown Rust Resistance, α-Amylase Activity and Pre-harvest Sprouting in Rye (<Emphasis Type="Italic">Secale cereale</Emphasis> L.)

Rye is a crop with relatively high resistance to biotic and abiotic stresses. However, the resistance to brown rust (Puccinia recondita f. sp. secalis) and pre-harvest sprouting are still not satisfactory. High α-amylase activity is also among the main disadvantages of this species. Therefore, effective tools, e.g. molecular markers, allowing precise and environmentally independent selection of favourable alleles are desirable. In the present study, two kinds of association mapping—genome-wide association mapping (GWAM) based on sequences of DArTSeq markers and candidate gene association mapping (CGAM) based on sequences of ScBx genes—were chosen for development of molecular markers fulfilling these criteria. The analysed population consisted of 149 diverse inbred lines (DILs). Altogether, 67 and 11 single nucleotide polymorphisms (SNPs) identified in, respectively, GWAM and CGAM, were significantly associated with the investigated traits: 2 SNPs with resistance to brown rust, 71 SNPs with resistance to pre-harvest sprouting and 5 SNPs with α-amylase activity in the grain. Fifteen SNPs were stable across all environments. The highest number (13) of environmentally stable SNPs was associated with pre-harvest sprouting resistance. The test employing the Kompetitive Allele Specific PCR method proved the versatility of four markers identified in both GWAM and CGAM.     

QTL mapping and comparative genome analysis of agronomic traits including grain yield in winter rye

Key message

Genetic diversity in elite rye germplasm as well as F _2:3 testcross design enables fast QTL mapping to approach genes controlling grain yield, grain weight, tiller number and heading date in rye hybrids.

Abstract

Winter rye (Secale cereale L.) is a multipurpose cereal crop closely related to wheat, which offers the opportunity for a sustainable production of food and feed and which continues to emerge as a renewable energy source for the production of bioethanol and biomethane. Rye contributes to increase agricultural crop species diversity particularly in Central and Eastern Europe. In contrast to other small grain cereals, knowledge on the genetic architecture of complex inherited, agronomic important traits is yet limited for the outbreeding rye. We have performed a QTL analysis based on a F_2:3 design and testcross performance of 258 experimental hybrids in multi-environmental field trials. A genetic linkage map covering 964.9 cM based on SSR, conserved-orthologous set (COS), and mixed-phase dominant DArT markers allowed to describe 22 QTL with significant effects for grain yield, heading date, tiller number, and thousand grain weight across seven environments. Using rye COS markers, orthologous segments for these traits have been identified in the rice genome, which carry cloned and functionally characterized rice genes. The initial genome scan described here together with the existing knowledge on candidate genes provides the basis for subsequent analyses of the genetic and molecular mechanisms underlying agronomic important traits in rye.

     

The General Growth Logistics of Cell Populations

An increment model based on thermodynamics lays bare that the cell size distributions of archaea, prokaryotes and eukaryotes are optimized and belong to the same universal class. Yet, when a cell absorbs mass or signals are processed, these conditions are disturbed. Relaxation re-installs ideal growth conditions via an exponential process with a rate that slows down with the cell size. In a growing ensemble, a distribution of relaxation modes comes in existence, exactly defined by the universal cell size distribution. The discovery of nano-mechanic acoustic activities in cells led us to assume that in a growing ensemble acoustic signals may contribute significantly to the transmission of essential information about growth-induced disturbances to all cells, initiating that way coordinated relaxation. The frequency increases with the cell number shortening the period between successive signals. The completion of rearrangements occurring at a constant rate is thus progressively impaired, until cellular growth stops, totally. Due to this phenomenon, the so-called "relaxation-frequency-dispersion" cell colonies should exhibit a maximum cell number. In populations with large cell numbers, subsystems, behaving similar-like colonies, should form network-like patterns. Based on these ideas, we formulate equations that describe the growth curves of all cell types, verifying that way the general nature of the growth logistics.     

Kinetics of growth and leukotoxin production by <Emphasis Type="Italic">Mannheimia haemolytica</Emphasis> in continuous culture

The growth and product formation kinetics of the bovine pathogen Mannheimia (Pasteurella) haemolytica strain OVI-1 in continuous culture were investigated. The leukotoxin (LKT) concentration and yield on biomass could substantially be enhanced by supplementation of a carbon-limited medium with an amino acid mixture or a mixture of cysteine and glutamine. Acetic acid was a major product, increasing to 1.66 g l(-1) in carbon-limited chemostat culture at intermediate dilution rates and accounting for more than 80% of the glucose carbon, whereas in amino acid-limited cultures high acetic acid concentrations were produced at low dilution rates, suggesting a carbon-overflow metabolism. The maintenance coefficients of carbon-limited and carbon-sufficient cultures were 0.07 and 0.88 mmol glucose g(-1) h(-1), respectively. LKT production was partially growth-associated and the LKT concentration was maximised to 0.15 g l(-1) and acetic acid production minimised by using a carbon-limited medium and a low dilution rate.     

Precision-mapping and statistical validation of quantitative trait loci by machine learning

Background

DNA sequence diversity within the human genome may be more greatly affected by copy number variations (CNVs) than single nucleotide polymorphisms (SNPs). Although the importance of CNVs in genome wide association studies (GWAS) is becoming widely accepted, the optimal methods for identifying these variants are still under evaluation. We have previously reported a comprehensive view of CNVs in the HapMap DNA collection using high density 500 K EA (Early Access) SNP genotyping arrays which revealed greater than 1,000 CNVs ranging in size from 1 kb to over 3 Mb. Although the arrays used most commonly for GWAS predominantly interrogate SNPs, CNV identification and detection does not necessarily require the use of DNA probes centered on polymorphic nucleotides and may even be hindered by the dependence on a successful SNP genotyping assay.

Results

In this study, we have designed and evaluated a high density array predicated on the use of non-polymorphic oligonucleotide probes for CNV detection. This approach effectively uncouples copy number detection from SNP genotyping and thus has the potential to significantly improve probe coverage for genome-wide CNV identification. This array, in conjunction with PCR-based, complexity-reduced DNA target, queries over 1.3 M independent NspI restriction enzyme fragments in the 200 bp to 1100 bp size range, which is a several fold increase in marker density as compared to the 500 K EA array. In addition, a novel algorithm was developed and validated to extract CNV regions and boundaries.

Conclusion

Using a well-characterized pair of DNA samples, close to 200 CNVs were identified, of which nearly 50% appear novel yet were independently validated using quantitative PCR. The results indicate that non-polymorphic probes provide a robust approach for CNV identification, and the increasing precision of CNV boundary delineation should allow a more complete analysis of their genomic organization.     

Detecting the degree of establishment of a non-indigenous species in coastal ecosystems: sea bass <Emphasis Type="Italic">Dicentrarchus labrax</Emphasis> escapes from sea cages in Canary Islands (Northeastern Central Atlantic)

This article gives an insight into the degree of establishment and potential impact of escaped sea bass in shallow coastal habitats of Tenerife. We studied spatial distribution, abundance, size frequency and use of habitat by visual census. Stomach contents and gonadal maturity of escaped sea bass were analysed. Results show that abundance of escaped sea bass is related to distance from to the nearest fish farm and to the habitat complexity. The most frequent size found in the wild corresponds to that of first marketing size. Stomach contents indicate that escaped sea bass were able to exploit natural resources, especially fish. The presence of a female with mature gonads indicates that conditions for successful maturation exist. However, further studies are needed to ensure whether or not escaped sea bass are able to establish self-reproducing populations. Thus, we can conclude that sea bass seem to be already established in shallow coastal habitats of Tenerife, but the population may depend mainly on escapees. As a result of being an opportunistic piscivore, sea bass could be predating on and competing with other native species that are economically important. These results are useful to develop a risk assessment based on quantitative data to predict negative effects. Moreover, management policies such as communication of massive escapes or mitigation measures are needed to prevent future impact on the marine environment. Handling editor: P. Viaroli     

Determining subpopulation methylation profiles from bisulfite sequencing data of heterogeneous samples using DXM

Epigenetic changes, such as aberrant DNA methylation, contribute to cancer clonal expansion and disease progression. However, identifying subpopulation-level changes in a heterogeneous sample remains challenging. Thus, we have developed a computational approach, DXM, to deconvolve the methylation profiles of major allelic subpopulations from the bisulfite sequencing data of a heterogeneous sample. DXM does not require prior knowledge of the number of subpopulations or types of cells to expect. We benchmark DXM’s performance and demonstrate improvement over existing methods. We further experimentally validate DXM predicted allelic subpopulation-methylation profiles in four Diffuse Large B-Cell Lymphomas (DLBCLs). Lastly, as proof-of-concept, we apply DXM to a cohort of 31 DLBCLs and relate allelic subpopulation methylation profiles to relapse. We thus demonstrate that DXM can robustly find allelic subpopulation methylation profiles that may contribute to disease progression using bisulfite sequencing data of any heterogeneous sample.