Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests

Background  

Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example Kruskal's algorithm. The efficiency of the algorithm makes it tractable for high-dimensional problems.     

Influences of sea level changes and volcanic eruptions on Holocene vegetation in Tonga

Here, we investigate Mid- to Late-Holocene vegetation changes in low-lying coastal areas in Tonga and how changing sea levels and recurrent volcanic eruptions have influenced vegetation dynamics on four islands of the Tongan archipelago (South Pacific). To investigate past vegetation and environmental change at Ngofe Marsh (‘Uta Vava’u), we examined palynomorphs (pollen and spores), charcoal (fire), and sediment characteristics (volcanic activity) from a 6.7-m-long sediment core. Radiocarbon dating indicated the sediments were deposited over the last 7700 years. We integrated the Ngofe Marsh data with similar previously published data from Avai’o’vuna Swamp on Pangaimotu Island, Lotofoa Swamp on Foa Island, and Finemui Swamp on Ha’afeva Island. Plant taxa were categorized as littoral, mangrove, rainforest, successional/ disturbance, and wetland groups, and linear models were used to examine relationships between vegetation, relative sea level change, and volcanic eruptions (tephra). We found that relative sea level change has impacted vegetation on three of the four islands investigated. Volcanic eruptions were not identified as a driver of vegetation change. Rainforest decline does not appear to be driven by sea level changes or volcanic eruptions. From all sites analyzed, vegetation at Finemui Swamp was most sensitive to changes in relative sea level. While vegetation on low-lying Pacific islands is sensitive to changing sea levels, island characteristics, such as area and elevation, are also likely to be important factors that mediate specific island responses to drivers of change.     

Pentose phosphate metabolism during dormancy breakage in Corylus avellana L.

Commercially obtained fruits of Corylus avellana exhibit the characteristic loss of dormancy of this seed following chilling under moist conditions. The activities of cytosolic and organellar enzymes of pentose phosphate pathway in cotyledonary tissue were assayed throughout stratification and over a similar period in damp vermiculite at 20° C. Glucose-6-phosphate dehydrogenase (G6PDH) and 6-phosphogluconic acid dehydrogenase (6PGDH) were both found in cytosolic extracts in all treatments; only 6PGDH was present in the organellar fraction.The enzyme activities monitored in seeds at 20° C remained relatively constant over the course of the investigation except in the case of cytosolic 6PGDH where it is suggested an inhibitor of the enzyme accumulated. This inhibitor was removed by the partial purification procedure. Increases in the activities of the enzymes occurred during stratification, the major increase coinciding exactly with dormancy breakage but prior to the initiation of germination. The marked increase in G6PDH and 6PGDH concurrent with the change in germination potential of the chilled seed may have considerable biochemical significance in breaking down the dormant state.Abbreviations G6P glucose-6-phosphate - G6PDH glucose-6 phosphate dehydrogenase - NADP nicotinamide adenine dinucleotide phosphate - 6 PGDH 6-phosphogluconic acid dehydrogenase - PPP pentose phosphate pathway     

Typha as a wetland food resource: evidence from the Tianluoshan site,Lower Yangtze Region,China

Vegetation History and Archaeobotany - Wetlands have been attractive environments for early communities worldwide. In China, wetlands offered natural ecological settings for the start of rice...     

Enlarging a training set for genomic selection by imputation of un-genotyped animals in populations of varying genetic architecture

Background

The most common application of imputation is to infer genotypes of a high-density panel of markers on animals that are genotyped for a low-density panel. However, the increase in accuracy of genomic predictions resulting from an increase in the number of markers tends to reach a plateau beyond a certain density. Another application of imputation is to increase the size of the training set with un-genotyped animals. This strategy can be particularly successful when a set of closely related individuals are genotyped.

Methods

Imputation on completely un-genotyped dams was performed using known genotypes from the sire of each dam, one offspring and the offspring’s sire. Two methods were applied based on either allele or haplotype frequencies to infer genotypes at ambiguous loci. Results of these methods and of two available software packages were compared. Quality of imputation under different population structures was assessed. The impact of using imputed dams to enlarge training sets on the accuracy of genomic predictions was evaluated for different populations, heritabilities and sizes of training sets.

Results

Imputation accuracy ranged from 0.52 to 0.93 depending on the population structure and the method used. The method that used allele frequencies performed better than the method based on haplotype frequencies. Accuracy of imputation was higher for populations with higher levels of linkage disequilibrium and with larger proportions of markers with more extreme allele frequencies. Inclusion of imputed dams in the training set increased the accuracy of genomic predictions. Gains in accuracy ranged from close to zero to 37.14%, depending on the simulated scenario. Generally, the larger the accuracy already obtained with the genotyped training set, the lower the increase in accuracy achieved by adding imputed dams.

Conclusions

Whenever a reference population resembling the family configuration considered here is available, imputation can be used to achieve an extra increase in accuracy of genomic predictions by enlarging the training set with completely un-genotyped dams. This strategy was shown to be particularly useful for populations with lower levels of linkage disequilibrium, for genomic selection on traits with low heritability, and for species or breeds for which the size of the reference population is limited.     

Bacterial colonization of Hydra hatchlings follows a robust temporal pattern

Animals are colonized by complex bacterial communities. The processes controlling community membership and influencing the establishment of the microbial ecosystem during development are poorly understood. Here we aimed to explore the assembly of bacterial communities in Hydra with the broader goal of elucidating the general rules that determine the temporal progression of bacterial colonization of animal epithelia. We profiled the microbial communities in polyps at various time points after hatching in four replicates. The composition and temporal patterns of the bacterial communities were strikingly similar in all replicates. Distinct features included high diversity of community profiles in the first week, a remarkable but transient adult-like profile 2 weeks after hatching, followed by progressive emergence of a stable adult-like pattern characterized by low species diversity and the preponderance of the Betaproteobacterium Curvibacter. Intriguingly, this process displayed important parallels to the assembly of human fecal communities after birth. In addition, a mathematical modeling approach was used to uncover the organizational principles of this colonization process, suggesting that both, local environmental or host-derived factor(s) modulating the colonization rate, as well as frequency-dependent interactions of individual bacterial community members are important aspects in the emergence of a stable bacterial community at the end of development.