Remote Sensing of Giant Reed with QuickBird Satellite Imagery

QuickBird high resolution (2.8 m) satellite imagery was evaluated for distinguishing giant reed ( Arundo donax L.) infestations along the Rio Grande in southwest Texas. (PDF has 5 pages.

Get Another Worker? Active Crowdlearning With Sequential Arrivals

Engineering and Applied Science

SPG20 protein spartin is recruited to midbodies by ESCRT-III protein Ist1 and participates in cytokinesis.

Hereditary spastic paraplegias (HSPs, SPG1-46) are inherited neurological disorders characterized by lower extremity spastic weakness. Loss-of-function SPG20 gene mutations cause an autosomal recessive HSP known as Troyer syndrome. The SPG20 protein spartin localizes to lipid droplets and endosomes, and it interacts with tail interacting protein 47 (TIP47) as well as the ubiquitin E3 ligases atrophin-1-interacting protein (AIP)4 and AIP5. Spartin harbors a domain contained within microtubule-interacting and trafficking molecules (MIT) at its N-terminus, and most proteins with MIT domains interact with specific ESCRT-III proteins. Using yeast two-hybrid and in vitro surface plasmon resonance assays, we demonstrate that the spartin MIT domain binds with micromolar affinity to the endosomal sorting complex required for transport (ESCRT)-III protein increased sodium tolerance (Ist)1 but not to ESCRT-III proteins charged multivesicular body proteins 1-7. Spartin colocalizes with Ist1 at the midbody, and depletion of Ist1 in cells by small interfering RNA significantly decreases the number of cells where spartin is present at midbodies. Depletion of spartin does not affect Ist1 localization to midbodies but markedly impairs cytokinesis. A structure-based amino acid substitution in the spartin MIT domain (F24D) blocks the spartin-Ist1 interaction. Spartin F24D does not localize to the midbody and acts in a dominant-negative manner to impair cytokinesis. These data suggest that Ist1 interaction is important for spartin recruitment to the midbody and that spartin participates in cytokinesis

Optimising the identification of causal variants across varying genetic architectures in crops

Association studies use statistical links between genetic markers and the phenotype variation across many individuals to identify genes controlling variation in the target phenotype. However, this approach, particularly conducted on a genome-wide scale (GWAS), has limited power to identify the genes responsible for variation in traits controlled by complex genetic architectures. In this study, we employ real-world genotype datasets from four crop species with distinct minor allele frequency distributions, population structures and linkage disequilibrium patterns. We demonstrate that different GWAS statistical approaches provide favourable trade-offs between power and accuracy for traits controlled by different types of genetic architectures. FarmCPU provides the most favourable outcomes for moderately complex traits while a Bayesian approach adopted from genomic prediction provides the most favourable outcomes for extremely complex traits. We assert that by estimating the complexity of genetic architectures for target traits and selecting an appropriate statistical approach for the degree of complexity detected, researchers can substantially improve the ability to dissect the genetic factors controlling complex traits such as flowering time, plant height and yield component