Young tableau reconstruction via minors

The tableau reconstruction problem, posed by Monks (2009), asks the following. Starting with a standard Young tableau $T$, a 1-minor of $T$ is a tableau obtained by first deleting any cell of $T$, and then performing jeu de taquin slides to fill the resulting gap. This can be iterated to arrive at the set of $k$-minors of $T$. The problem is this: given $k$, what are the values of $n$ such that every tableau of size $n$ can be reconstructed from its set of $k$-minors? For $k=1$, the problem was recently solved by Cain and Lehtonen. In this paper, we solve the problem for $k=2$, proving the sharp lower bound $n \geq 8$. In the case of multisets of $k$-minors, we also give a lower bound for arbitrary $k$, as a first step toward a sharp bound in the general multiset case.Comment: 24 pages, 18 figure

No Evidence That Genetic Variation at the Klotho Locus Is Associated With Longevity in Caucasians from the Newcastle 85+ Study and the UK Biobank

Copyright © The Author(s) 2021. The demographics of Western populations are changing, with an increase in the proportion of older adults. There is evidence to suggest that genetic factors may influence the aging process: studying these may lead to interventions to help individuals live a longer and healthier life. Evidence from several groups indicates that Klotho (KL), a gene encoding a single-pass transmembrane protein that acts as an FGF23 co-receptor, may be associated with longevity and healthy aging. We aimed to explore this area further by comparing the genotype counts in 642 long-lived individuals from the Newcastle 85+ Study with 18 295 middle-aged Newcastle-based controls from the UK Biobank to test whether variants at the KL gene locus are over- or under-represented in older individuals. If KL is associated with longevity, then we would expect the genotype counts to differ between the 2 cohorts. We found that the rs2283368 CC genotype and the rs9536338 C allele, but not the KL-VS haplotype, were associated with reaching very old age. However, these associations did not replicate in the remainder of the UK Biobank cohort. Thus, our results do not reliably support the role of KL as a longevity factor.Calico LLC (South San Francisco, California, United States); HAA is the recipient of a PhD studentship from the College of Health, Medical and Life Sciences, Brunel University London

Rocketing restoration : enabling the upscaling of ecological restoration in the Anthropocene

In the 25 years during which the Society for Ecological Restoration (SER) has overseen the publication of Restoration Ecology, the field has witnessed conceptual and practical advances. These have become necessary due to the scale of environmental change wrought by the increasing global human population, and associated demands for food, fiber, energy, and water. As we look to the future, and attempt to fulfill global restoration commitments and meet sustainable development goals, there is a need to reverse land degradation and biodiversity loss through upscaling ecological restoration. Here, we argue that this upscaling requires an expanded vision for restoration that explicitly accounts for people and nature. This expansion can assess success in a future-focused way and as improvements relative to a degraded socio-ecological system. We suggest that upscaling requires addressing governance, legal and ethical challenges, investing in technological and educational capacity building, bolstering the practical science necessary for restoration, encouraging adoptable packages to ensure livelihoods of local stakeholders, and promoting investment opportunities for local actors and industry. Providing SER embraces this socio-ecological vision, it is ideally placed to aid the achievement of goals and remain globally relevant. SER needs to harness and coordinate three sources of potential energy (global political commitments, the green economy, and local community engagement) to rocket restoration into the Anthropocene. With principles that can embrace flexibility and context-dependency in minimum restoration standards, SER has the potential to guide socio-ecological restoration and help realize the ultimate goal of a sustainable Earth

A flexible integrative approach based on random forest improves prediction of transcription factor binding sites

Transcription factor binding sites (TFBSs) are DNA sequences of 6-15 base pairs. Interaction of these TFBSs with transcription factors (TFs) is largely responsible for most spatiotemporal gene expression patterns. Here, we evaluate to what extent sequence-based prediction of TFBSs can be improved by taking into account the positional dependencies of nucleotides (NPDs) and the nucleotide sequence-dependent structure of DNA. We make use of the random forest algorithm to flexibly exploit both types of information. Results in this study show that both the structural method and the NPD method can be valuable for the prediction of TFBSs. Moreover, their predictive values seem to be complementary, even to the widely used position weight matrix (PWM) method. This led us to combine all three methods. Results obtained for five eukaryotic TFs with different DNA-binding domains show that our method improves classification accuracy for all five eukaryotic TFs compared with other approaches. Additionally, we contrast the results of seven smaller prokaryotic sets with high-quality data and show that with the use of high-quality data we can significantly improve prediction performance. Models developed in this study can be of great use for gaining insight into the mechanisms of TF binding

The LRRK2 Arg1628Pro variant is a risk factor for Parkinson's disease in the Chinese population

The c.G4883C variant in the leucine-rich repeat kinase 2 (LRRK2) gene (protein effect: Arg1628Pro) has been recently proposed as a second risk factor for sporadic Parkinson's disease in the Han Chinese population (after the Gly2385Arg variant). In this paper, we analyze the Arg1628Pro variant and the associated haplotype in a large sample of 1,337 Han subjects (834 patients and 543 controls) ascertained from a single referral center in Taiwan. In our sample, the Arg1628Pro allele was more frequent among patients (3.8%) than among controls (1.8%; p = 0.004, OR 2.13, 95% CI 1.29-3.52). Sixty heterozygous and two homozygous carriers of the Arg1628Pro variant were identified among the patients, of which only one was also a carrier of the LRRK2 Gly2385Arg variant. We also show that carriers of the Arg1628Pro variant share a common, extended haplotype, suggesting a founder effect. Parkinson's disease onset age was similar in patients who carried the Arg1628Pro variant and in those who did not carry it. Our data support the contention that the Arg1628Pro variant is a second risk factor for Parkinson's disease in the Han Chinese population. Adding the estimated effects of Arg1628Pro (population attributable risk [PAR] ∼4%) and Gly2385Arg variants (PAR ∼6%) yields a total PAR of ∼10%

Changes in the allocation of endogenous strigolactone improve plant biomass production on phosphate-poor soils.

Strigolactones (SLs) are carotenoid-derived phytohormones shaping plant architecture and inducing the symbiosis with endomycorrhizal fungi. In Petunia hybrida, SL transport within the plant and towards the rhizosphere is driven by the ABCG-class protein PDR1. PDR1 expression is regulated by phytohormones and by the soil phosphate abundance, and thus SL transport integrates plant development with nutrient conditions. We overexpressed PDR1 (PDR1 OE) to investigate whether increased endogenous SL transport is sufficient to improve plant nutrition and productivity. Phosphorus quantification and nondestructive X-ray computed tomography were applied. Morphological and gene expression changes were quantified at cellular and whole tissue levels via time-lapse microscopy and quantitative PCR. PDR1 OE significantly enhanced phosphate uptake and plant biomass production on phosphate-poor soils. PDR1 OE plants showed increased lateral root formation, extended root hair elongation, faster mycorrhization and reduced leaf senescence. PDR1 overexpression allowed considerable SL biosynthesis by releasing SL biosynthetic genes from an SL-dependent negative feedback. The increased endogenous SL transport/biosynthesis in PDR1 OE plants is a powerful tool to improve plant growth on phosphate-poor soils. We propose PDR1 as an as yet unexplored trait to be investigated for crop production. The overexpression of PDR1 is a valuable strategy to investigate SL functions and transport routes

Grammatical evolution decision trees for detecting gene-gene interactions

<p>Abstract</p> <p>Background</p> <p>A fundamental goal of human genetics is the discovery of polymorphisms that predict common, complex diseases. It is hypothesized that complex diseases are due to a myriad of factors including environmental exposures and complex genetic risk models, including gene-gene interactions. Such epistatic models present an important analytical challenge, requiring that methods perform not only statistical modeling, but also variable selection to generate testable genetic model hypotheses. This challenge is amplified by recent advances in genotyping technology, as the number of potential predictor variables is rapidly increasing.</p> <p>Methods</p> <p>Decision trees are a highly successful, easily interpretable data-mining method that are typically optimized with a hierarchical model building approach, which limits their potential to identify interacting effects. To overcome this limitation, we utilize evolutionary computation, specifically grammatical evolution, to build decision trees to detect and model gene-gene interactions. In the current study, we introduce the Grammatical Evolution Decision Trees (GEDT) method and software and evaluate this approach on simulated data representing gene-gene interaction models of a range of effect sizes. We compare the performance of the method to a traditional decision tree algorithm and a random search approach and demonstrate the improved performance of the method to detect purely epistatic interactions.</p> <p>Results</p> <p>The results of our simulations demonstrate that GEDT has high power to detect even very moderate genetic risk models. GEDT has high power to detect interactions with and without main effects.</p> <p>Conclusions</p> <p>GEDT, while still in its initial stages of development, is a promising new approach for identifying gene-gene interactions in genetic association studies.</p