Robust model rankings of forecasting performance

This paper investigates robust model rankings in out‐of‐sample, short‐horizon forecasting. We provide strong evidence that rolling window averaging consistently produces robust model rankings while improving the forecasting performance of both individual models and model averaging. The rolling window averaging outperforms the (ex post) “optimal” window forecasts in more than 50% of the times across all rolling windows.     

Cryptic and non-cryptic diversity in New Guinea ground snakes of the genus Stegonotus Duméril,Bibron and Duméril, 1854: a description of four new species (Squamata: Colubridae)

ABSTRACT

The island of New Guinea has been identified as biologically megadiverse but many taxa are still poorly known. This is especially the case for many of the island’s snakes, which by their very nature can be difficult to collect and study. Here we examine the phylogenetic and phylogeographic structure of a poorly studied snake genus, Stegonotus, focusing on the species of New Guinea; until now, Stegonotus has never been examined using modern phylogenetic methods. Using molecular data from 49 individuals representing eight of the ten described species, and including all New Guinea taxa, we estimate a multilocus phylogeny and examine population structure to help identify undescribed taxa. We use morphological data from the corresponding museum vouchered specimens (where available) and also examine additional specimens for taxa not included in the molecular data set to determine morphological differences among putative taxa. We find molecular evidence for four new species of Stegonotus, both morphologically obvious and cryptic, and describe them herein. The recognition of these four species indicates that Stegonotus diversity has been previously underestimated and also suggests that there are likely additional undescribed taxa within the genus. These four taxa increase the number of described species by 40% and further confirm New Guinea as the centre of diversity for the genus.

www.zoobank.org/urn:lsid:zoobank.org:pub:9E21390E-3FD4-40EB-9442-31BC92A76B4F     

Space use by two arboreal rodent species in a Neotropical cloud forest

Studying animal space use patterns can help increase our understating of ecological processes such as competition and community dynamics. To quantify space and habitat use in an isolated and patchy cloud forest community in Mexico, we evaluate the vertical stratification, home range and habitat selection of two arboreal rodents: Habromys schmidlyi and Reithrodontomys microdon. Using live-traps at ground level and different forest strata, we radio-equipped nine individuals of H. schmidlyi and seven of R. microdon, and evaluated fine-scale space use and broad-scale habitat selection between cloud forest and oak forest. We found an average home range of 0.24 ha for R. microdon males and 0.72 ha for females, with a preference for higher canopy in the cloud forest. For H. schmidlyi the home range was 0.83 ha for males and 0.29 ha for females, with a preference for the understory level in the cloud forest. Home range is three-dimensional for these rodents, so we estimate that on average, individuals of both species used eight trees in the time they were tracked. We characterised the vegetation at the trap sites, and used recursive partitioning to relate the presence of different plants with the probability of finding these two species and Peromyscus aztecus, a third rodent species also present in the area and considered in our analysis of habitat use. The highest probability of finding R. microdon (96%) was related to the presence of Brachythecium occidentale and Renauldia mexicana, while H. schmidlyi (95%) was found in close proximity to Fabronia ciliaris and Everniastrum. We highlight the importance of arboreal trapping in biodiversity assessments, and the role of arboreal rodents in maintaining tropical forest ecosystems. We suggest that these rodent species could avoid or reduce competition by using the vertical strata differentially, and that H. schmidlyi and R. microdon can be biological indicators for cloud forest management and conservation.     

Common loss-of-function variants of the epidermal barrier protein filaggrin are a major predisposing factor for atopic dermatitis

Atopic disease, including atopic dermatitis (eczema), allergy and asthma, has increased in frequency in recent decades and now affects approximately 20% of the population in the developed world. Twin and family studies have shown that predisposition to atopic disease is highly heritable. Although most genetic studies have focused on immunological mechanisms, a primary epithelial barrier defect has been anticipated. Filaggrin is a key protein that facilitates terminal differentiation of the epidermis and formation of the skin barrier. Here we show that two independent loss-of-function genetic variants (R510X and 2282del4) in the gene encoding filaggrin (FLG) are very strong predisposing factors for atopic dermatitis. These variants are carried by approximately 9% of people of European origin. These variants also show highly significant association with asthma occurring in the context of atopic dermatitis. This work establishes a key role for impaired skin barrier function in the development of atopic disease.     

Analysis of the human protein interactome and comparison with yeast, worm and fly interaction datasets

We present the first analysis of the human proteome with regard to interactions between proteins. We also compare the human interactome with the available interaction datasets from yeast (Saccharomyces cerevisiae), worm (Caenorhabditis elegans) and fly (Drosophila melanogaster). Of >70,000 binary interactions, only 42 were common to human, worm and fly, and only 16 were common to all four datasets. An additional 36 interactions were common to fly and worm but were not observed in humans, although a coimmunoprecipitation assay showed that 9 of the interactions do occur in humans. A re-examination of the connectivity of essential genes in yeast and humans indicated that the available data do not support the presumption that the number of interaction partners can accurately predict whether a gene is essential. Finally, we found that proteins encoded by genes mutated in inherited genetic disorders are likely to interact with proteins known to cause similar disorders, suggesting the existence of disease subnetworks. The human interaction map constructed from our analysis should facilitate an integrative systems biology approach to elucidating the cellular networks that contribute to health and disease states.     

Automating sequence-based detection and genotyping of SNPs from diploid samples

The detection of sequence variation, for which DNA sequencing has emerged as the most sensitive and automated approach, forms the basis of all genetic analysis. Here we describe and illustrate an algorithm that accurately detects and genotypes SNPs from fluorescence-based sequence data. Because the algorithm focuses particularly on detecting SNPs through the identification of heterozygous individuals, it is especially well suited to the detection of SNPs in diploid samples obtained after DNA amplification. It is substantially more accurate than existing approaches and, notably, provides a useful quantitative measure of its confidence in each potential SNP detected and in each genotype called. Calls assigned the highest confidence are sufficiently reliable to remove the need for manual review in several contexts. For example, for sequence data from 47-90 individuals sequenced on both the forward and reverse strands, the highest-confidence calls from our algorithm detected 93% of all SNPs and 100% of high-frequency SNPs, with no false positive SNPs identified and 99.9% genotyping accuracy. This algorithm is implemented in a software package, PolyPhred version 5.0, which is freely available for academic use.     

Truncating mutations in the Fanconi anemia J gene BRIP1 are low-penetrance breast cancer susceptibility alleles

We identified constitutional truncating mutations of the BRCA1-interacting helicase BRIP1 in 9/1,212 individuals with breast cancer from BRCA1/BRCA2 mutation-negative families but in only 2/2,081 controls (P = 0.0030), and we estimate that BRIP1 mutations confer a relative risk of breast cancer of 2.0 (95% confidence interval = 1.2-3.2, P = 0.012). Biallelic BRIP1 mutations were recently shown to cause Fanconi anemia complementation group J. Thus, inactivating truncating mutations of BRIP1, similar to those in BRCA2, cause Fanconi anemia in biallelic carriers and confer susceptibility to breast cancer in monoallelic carriers.