Interaction between genetic regions responsible for the starch properties in non-glutinous rice varieties in Hokkaido, Japan.

Starch properties are the major determinants of grain quality and food characteristics in rice (Oryza sativa L.). Understanding the interactions between genetic regions responsible for starch properties will lead to the development of rice cultivars with desirable characteristics. This study investigated the genetic effect and interaction between qAC9.3, a low-amylose quantitative trait locus (QTL), and the genetic region around Starch branching enzyme IIb (SbeIIb). Both these factors are responsible for the starch properties of the Hokkaido breeding population. The amylose content, pasting temperature, and amylopectin chain-length distribution were compared using F5 lines derived from the cross between the lower amylose content and lower pasting temperature strain 'Hokkai332 (qAC9.3, SbeIIb)' and the higher amylose content and higher pasting temperature variety 'Kitagenki (-, SbeIIbsr )'. The qAC9.3 genotype exhibited low amylose content and reduced the hardness of boiled rice but increased the ratio of amylopectin long chains and did not alter the pasting temperature. In contrast, the SbeIIb genotype was associated with pasting temperature but did not affect the amylose content and hardness of boiled rice. It was suggested that appropriately selecting genotypes of these genetic regions and QTL would allow the fine-tuning of starch properties of cooked rice suitable for future demand.

Transient GI/MSP/1/N Queue.

A non-zero correlation between service times can be encountered in many real queueing systems. An attractive model for correlated service times is the Markovian service process, because it offers powerful fitting capabilities combined with analytical tractability. In this paper, a transient study of the queue length in a model with MSP services and a general distribution of interarrival times is performed. In particular, two theorems are proven: one on the queue length distribution at a particular time t, where t can be arbitrarily small or large, and another on the mean queue length at t. In addition to the theorems, multiple numerical examples are provided. They illustrate the development over time of the mean queue length and the standard deviation, along with the complete distribution, depending on the service correlation strength, initial system conditions, and the interarrival time variance.

DeltaMSI: artificial intelligence-based modeling of microsatellite instability scoring on next-generation sequencing data.

BACKGROUND: DNA mismatch repair deficiency (dMMR) testing is crucial for detection of microsatellite unstable (MSI) tumors. MSI is detected by aberrant indel length distributions of microsatellite markers, either by visual inspection of PCR-fragment length profiles or by automated bioinformatic scoring on next-generation sequencing (NGS) data. The former is time-consuming and low-throughput while the latter typically relies on simplified binary scoring of a single parameter of the indel distribution. The purpose of this study was to use machine learning to process the full complexity of indel distributions and integrate it into a robust script for screening of dMMR on small gene panel-based NGS data of clinical tumor samples without paired normal tissue. METHODS: Scikit-learn was used to train 7 models on normalized read depth data of 36 microsatellite loci in a cohort of 133 MMR proficient (pMMR) and 46 dMMR tumor samples, taking loss of MLH1/MSH2/PMS2/MSH6 protein expression as reference method. After selection of the optimal model and microsatellite panel the two top-performing models per locus (logistic regression and support vector machine) were integrated into a novel script (DeltaMSI) for combined prediction of MSI status on 28 marker loci at sample level. Diagnostic performance of DeltaMSI was compared to that of mSINGS, a widely used script for MSI detection on unpaired tumor samples. The robustness of DeltaMSI was evaluated on 1072 unselected, consecutive solid tumor samples in a real-world setting sequenced using capture chemistry, and 116 solid tumor samples sequenced by amplicon chemistry. Likelihood ratios were used to select result intervals with clinical validity. RESULTS: DeltaMSI achieved higher robustness at equal diagnostic power (AUC = 0.950; 95% CI 0.910-0.975) as compared to mSINGS (AUC = 0.876; 95% CI 0.823-0.918). Its sensitivity of 90% at 100% specificity indicated its clinical potential for high-throughput MSI screening in all tumor types. Clinical Trial Number/IRB B1172020000040, Ethical Committee, AZ Delta General Hospital.

Critical examination of the characterization techniques, and the evidence, for the existence of extra-long amylopectin chains.

It has been suggested that amylopectin can contain small but significant amounts of extra-long chains (ELCs), which could affect functional properties, and also would have implications for the mechanism of starch biosynthesis. However, current evidence for the existence of ELCs is ambiguous. The amylose/amylopectin separation and the characterization techniques used for the investigation of ELCs are reviewed, problems in those techniques are examined, and studies of ELCs of amylopectin are discussed. A model for the biosynthesis of amylopectin chains in terms of conventional biosynthesis enzymes, which provides an excellent fit to a large amount of experimental data, is used to provide a rigorous definition of ELCs. In addition, current investigations of ELCs, involving separation, is hindered by the lack of a method to quantitatively separate all the amylopectin from starch without any traces of residual amylose (which would have long chains). Unambiguous evidence for the existence of ELCs can be obtained using two-dimensional (2D) characterization, these dimensions being the degree of polymerization of a chain and the size of the whole molecule. Available 2D data indicate that there are no ELCs present in currently detectable quantities in native rice starches. However, concluding this more rigorously requires improvements in the resolution of current 2D methods.

Relative importance of branching enzyme isoforms in determining starch fine structure and physicochemical properties of indica rice.

KEY MESSAGE: Down-regulation of starch branching enzymes alters fine structure and starch properties, especially the B-type crystalline pattern and extremely high amylose content identified in the BEIIb-deficiency mutant in the indica rice. The relative importance of the starch branching enzymes in determining the molecular fine structure and starch functional properties were uncovered in this study. An indica rice, Guangluai 4 with high amylose content (AC) and high gelatinization temperature (GT) was used to generate the clustered regularly interspaced short palindromic repeats (CRISPR)/associated protein-9 (Cas9) knockout lines. Five mutant lines were identified including be1-1, be1-2, be2a-1, be2a-2 and be2b-1, and analysis of western blot showed the CRISPR/Cas9 system was successful in inducing mutations in the targeted genes. AC of be2b-1 (34.1%) was greater than that of wild type (WT) (27.4%) and other mutants. Mutations of either BEI or BEIIa did not alter the starch crystallite pattern (A-type). The BEIIb deficiency caused an opaque endosperm phenotype, changed the crystallite pattern from A- to B-type, and dramatically increased the degree of ordered structure, the relative proportion of amylose chains and intermediate to long amylopectin chains, average chain length of amylopectin molecules as well as GT. The BEIIa deficiency had no effect on the proportion of amylose chains, the length of amylopectin intermediate-long chains, conclusion temperature and enthalpy of gelatinization. Down-regulation of BEI increased the proportion of shortest amylopectin chains (fa) but decreased the proportion of long amylopectin chains (fb2 and fb3), leading to a lower GT. It is concluded that the relative importance in determining starch fine structures and functionality was in the order of BEIIb > BEI > BEIIa. Our results provide new information for utilizations of BE-deficient mutants in rice quality breeding.

Functional characterization of maltodextrin glucosidase for maltodextrin and glycogen metabolism in Vibrio vulnificus MO6-24/O.

Glycogen is important for transmission of V. vulnificus undergoing disparate environments of nutrient-rich host and nutrient-limited marine environment. The malZ gene of V. vulnificus encoding a maltodextrin glucosidase was cloned and over-expressed in E. coli to investigate its roles in glycogen/maltodextrin metabolism in the pathogen. The malZ gene encoded a protein with a predicted molecular mass of 70 kDa. The optimal pH and temperature of MalZ was 7.0 and 37 °C, respectively. MalZ hydrolyzed maltodextrin to glucose and maltose most efficiently, while hydrolyzed other substrates such as starch, maltose, ß-cyclomaltodextrin, and glycogen less efficiently. The activity was enhanced greatly by Mn2+. It also exhibited transglycosylation activity toward excessive maltotriose. The malZ knock-out mutant accumulated 2.3-5.6-fold less glycogen than the wild type when excessive maltodextrin or glucose was added to LB medium, while it accumulated more glycogen than the wild type (3.5-fold) in the presence of excessive maltose. Growth and glycogen accumulation of the mutant were retarded most significantly in the M63 minimal medium supplemented with 0.5% maltodextrin. Side chain length distributions of glycogen molecules were varied by the malZ mutation and types of the excessive carbon source. Based on the results, MalZ of V. vulnificus was likely to be involved in maltose/maltodextrin metabolism, thereby balancing synthesis of glycogen and energy generation in the cell. The bacterium seemed to have multiple and unique pathways for glycogen metabolism according to carbon sources.

Self-assembly of smooth muscle myosin filaments: adaptation of filament length by telokin and Mg·ATP.

The contractile apparatus of smooth muscle is malleable to accommodate stress and strain exerted on the muscle cell and to maintain optimal contractility. Structural lability of smooth muscle myosin filaments is believed to play an important role in the cell's malleability. However, the mechanism and regulation of myosin filament formation is still poorly understood. In the present in vitro study, using a static light scattering method, length distributions were obtained from suspensions of short myosin filaments (SFs) formed by rapid dilution or long ones (LFs) formed by slow dialysis. The distributions indicated the presence of dynamic equilibriums between soluble myosin and the SFs; i.e.: trimers, hexamers and mini filaments, covering the range up to 0.75 µm. The LFs were more stable, exhibiting favorable sizes at about 1.25, 2.4 and 4.5 µm. More distinct distributions were obtained from filaments adsorbed to a glass surface, by evanescent wave scattering and local electric field enhancement. Addition of telokin (TL) to the suspensions of unphosphorylated SFs resulted in widening of the soluble range, while in the case of the LFs this shift was larger, and accompanied by reduced contribution of the soluble myosin species. Such changes were largely absent in the case of phosphorylated myosin. In contrast, the presence of Mg·ATP resulted in elongation of the filaments and clear separation of filaments from soluble myosin species. Thus, TL and Mg·ATP appeared to modify the distribution of myosin filament lengths, i.e., increasing the lengths in preparing for phosphorylation, or reducing it to aid dephosphorylation.

Polymer type effect on PLGA-based microparticles preparation by solvent evaporation method with single emulsion system using focussed beam reflectance measurement.

AIM: This study aimed to investigate the effect of polymer type on solidification rate of PLGA polymeric microparticles and particle size/distribution of the emulsion droplets/hardened PLGA polymeric microparticles during solvent evaporation process using FBRM (Focussed Beam Reflectance Measurement). METHODS: PLGA polymeric microparticles were prepared by an O/W solvent evaporation method using various PLGA polymers, including PLGA Resomer® RG503H, RG502H and RG752H. The particle size mean, chord length distribution (CLD), and chord count of the emulsion droplets/hardened microparticles were monitored by FBRM. The morphology of polymeric microparticles were characterised by optical microscopy and scanning electron microscopy (SEM). RESULTS: The transformation of the emulsion droplets into solid microparticles occurred within the first 30 (± 1.04), 34 (± 1.15) and 37 (± 0.82) min and square weighted mean chord lengths are 64.08 (± 3.18), 52.36 (± 5.27) and 42.18 (± 4.61) µm when PLGA Resomer® RG503H, RG502H and RG752H were used respectively. Larger square weighted mean chord length of PLGA polymeric microparticles gave lower chord counts. PLGA RG752H microparticles gave smallest square weighted mean chord length and the chord counts was the highest. The CLDs measured by FBRM showed that a larger particle size mean gave longer CLD and a lower peak of particle number. SEM data revealed that the morphology of microparticles was influenced by type and physical properties of polymer. CONCLUSIONS: FBRM can be employed for online monitoring of the shift in the microparticle CLD and detect transformation of the emulsion droplets into solid microparticles during the solvent evaporation process. The microparticle CLD and transformation process were strongly influenced by polymer type.

Is liver glycogen fragility a possible drug target for diabetes?

Liver glycogen α particles are molecularly fragile in diabetic mice, and readily form smaller ß particles, which degrade more rapidly to glucose. This effect is well associated with the loss of blood-glucose homeostasis in diabetes. The biological mechanism of such fragility is still unknown; therefore, there are perceived opportunities that could eventually lead to new means to manage type 2 diabetes. The hierarchical structures of glycogen particles are controlled by the underlying biosynthesis/degradation process that involves various enzymes, including, for example, glycogen synthase (GS) and glycogen-branching enzyme (GBE). Recent studies have shown that fragile glycogen α particles in diabetic mice have longer chains and a higher molecular density compared to wild-type mice, indicating an enhanced enzymatic activity ratio of GS to GBE in diabetes. Furthermore, it has been shown that with an improved blood glucose homeostasis, the glycogen fragility in diabetic mice can be restored by treatment with active ingredients from traditional Chinese medicine, yet the underlying mechanism is unknown. In this review, we summarize recent advances in understandings glycogen fragility from the perspectives of glycogen biosynthesis/degradation, glycogen hierarchical structures, and its relation to diabetes. Importantly, we for the first time set GS/GBE activity ratio as the therapeutic target for diabetes.

A detailed model and Monte Carlo simulation for predicting DIP genome length distribution in baculovirus infection of insect cells.

Baculoviruses have enormous potential for use as biopesticides to control insect pest populations without the adverse environmental effects posed by the widespread use of chemical pesticides. However, continuous baculovirus production is susceptible to DNA mutation and the subsequent production of defective interfering particles (DIPs). The amount of DIPs produced and their genome length distribution are of great interest not only for baculoviruses but for many other DNA and RNA viruses. In this study, we elucidate this aspect of virus replication using baculovirus as an example system and both experimental and modeling studies. The existing mathematical models for the virus replication process consider DIPs as a lumped quantity and do not consider the genome length distribution of the DIPs. In this study, a detailed population balance model for the cell-virus culture is presented, which predicts the genome length distribution of the DIP population along with their relative proportion. The model is simulated using the kinetic Monte Carlo algorithm, and the results agree well with the experimental results. Using this model, a practical strategy to maintain the DIP fraction to near to its maximum and minimum limits has been demonstrated.

Accurately estimating the length distributions of genomic micro-satellites by tumor purity deconvolution.

BACKGROUND: Genomic micro-satellites are the genomic regions that consist of short and repetitive DNA motifs. Estimating the length distribution and state of a micro-satellite region is an important computational step in cancer sequencing data pipelines, which is suggested to facilitate the downstream analysis and clinical decision supporting. Although several state-of-the-art approaches have been proposed to identify micro-satellite instability (MSI) events, they are limited in dealing with regions longer than one read length. Moreover, based on our best knowledge, all of these approaches imply a hypothesis that the tumor purity of the sequenced samples is sufficiently high, which is inconsistent with the reality, leading the inferred length distribution to dilute the data signal and introducing the false positive errors. RESULTS: In this article, we proposed a computational approach, named ELMSI, which detected MSI events based on the next generation sequencing technology. ELMSI can estimate the specific length distributions and states of micro-satellite regions from a mixed tumor sample paired with a control one. It first estimated the purity of the tumor sample based on the read counts of the filtered SNVs loci. Then, the algorithm identified the length distributions and the states of short micro-satellites by adding the Maximum Likelihood Estimation (MLE) step to the existing algorithm. After that, ELMSI continued to infer the length distributions of long micro-satellites by incorporating a simplified Expectation Maximization (EM) algorithm with central limit theorem, and then used statistical tests to output the states of these micro-satellites. Based on our experimental results, ELMSI was able to handle micro-satellites with lengths ranging from shorter than one read length to 10kbps. CONCLUSIONS: To verify the reliability of our algorithm, we first compared the ability of classifying the shorter micro-satellites from the mixed samples with the existing algorithm MSIsensor. Meanwhile, we varied the number of micro-satellite regions, the read length and the sequencing coverage to separately test the performance of ELMSI on estimating the longer ones from the mixed samples. ELMSI performed well on mixed samples, and thus ELMSI was of great value for improving the recognition effect of micro-satellite regions and supporting clinical decision supporting. The source codes have been uploaded and maintained at https://github.com/YixuanWang1120/ELMSI for academic use only.

Genetic and phenotypic associations between root architecture, arbuscular mycorrhizal fungi colonisation and low phosphate tolerance in strawberry (Fragaria × ananassa).

BACKGROUND: Phosphate is an essential plant macronutrient required to achieve maximum crop yield. Roots are able to uptake soil phosphate from the immediate root area, thus creating a nutrient depletion zone. Many plants are able to exploit phosphate from beyond this root nutrient depletion zone through symbiotic association with Arbuscular Mycorrhizal Fungi (AMF). Here we characterise the relationship between root architecture, AMF association and low phosphate tolerance in strawberries. The contrasting root architecture in the parental strawberry cultivars 'Redgauntlet' and 'Hapil' was studied through a mapping population of 168 progeny. Low phosphate tolerance and AMF association was quantified for each genotype to allow assessment of the phenotypic and genotypic relationships between traits. RESULTS: A "phosphate scavenging" root phenotype where individuals exhibit a high proportion of surface lateral roots was associated with a reduction in root system size across genotypes. A genetic correlation between "root system size" traits was observed with a network of pleiotropic QTL found to represent five "root system size" traits. By contrast, average root diameter and the distribution of roots appeared to be under two discrete methods of genetic control. A total of 18 QTL were associated with plant traits, 4 of which were associated with solidity that explained 46% of the observed variation. Investigations into the relationship between AMF association and root architecture found that a higher root density was associated with greater AMF colonisation across genotypes. However, no phenotypic correlation or genotypic association was found between low phosphate tolerance and the propensity for AMF association, nor root architectural traits when plants are grown under optimal nutrient conditions. CONCLUSIONS: Understanding the genetic relationships underpinning phosphate capture can inform the breeding of strawberry varieties with better nutrient use efficiency. Solid root systems were associated with greater AMF colonisation. However, low P-tolerance was not phenotypically or genotypically associated with root architecture traits in strawberry plants. Furthermore, a trade-off was observed between root system size and root architecture type, highlighting the energetic costs associated with a "phosphate scavenging" root architecture.

Probing Atomic Distributions in Mono- and Bimetallic Nanoparticles by Supervised Machine Learning.

Properties of mono- and bimetallic metal nanoparticles (NPs) may depend strongly on their compositional, structural (or geometrical) attributes, and their atomic dynamics, all of which can be efficiently described by a partial radial distribution function (PRDF) of metal atoms. For NPs that are several nanometers in size, finite size effects may play a role in determining crystalline order, interatomic distances, and particle shape. Bimetallic NPs may also have different compositional distributions than bulk materials. These factors all render the determination of PRDFs challenging. Here extended X-ray absorption fine structure (EXAFS) spectroscopy, molecular dynamics simulations, and supervised machine learning (artificial neural-network) method are combined to extract PRDFs directly from experimental data. By applying this method to several systems of Pt and PdAu NPs, we demonstrate the finite size effects on the nearest neighbor distributions, bond dynamics, and alloying motifs in mono- and bimetallic particles and establish the generality of this approach.

Warmer and browner waters decrease fish biomass production.

Climate change studies have long focused on effects of increasing temperatures, often without considering other simultaneously occurring environmental changes, such as browning of waters. Resolving how the combination of warming and browning of aquatic ecosystems affects fish biomass production is essential for future ecosystem functioning, fisheries, and food security. In this study, we analyzed individual- and population-level fish data from 52 temperate and boreal lakes in Northern Europe, covering large gradients in water temperature and color (absorbance, 420 nm). We show that fish (Eurasian perch, Perca fluviatilis) biomass production decreased with both high water temperatures and brown water color, being lowest in warm and brown lakes. However, while both high temperature and brown water decreased fish biomass production, the mechanisms behind the decrease differed: temperature affected the fish biomass production mainly through a decrease in population standing stock biomass, and through shifts in size- and age-distributions toward a higher proportion of young and small individuals in warm lakes; brown water color, on the other hand, mainly influenced fish biomass production through negative effects on individual body growth and length-at-age. In addition to these findings, we observed that the effects of temperature and brown water color on individual-level processes varied over ontogeny. Body growth only responded positively to higher temperatures among young perch, and brown water color had a stronger negative effect on body growth of old than on young individuals. Thus, to better understand and predict future fish biomass production, it is necessary to integrate both individual- and population-level responses and to acknowledge within-species variation. Our results suggest that global climate change, leading to browner and warmer waters, may negatively affect fish biomass production, and this effect may be stronger than caused by increased temperature or water color alone.

Biomass Pretreatment and Enzymatic Hydrolysis Dynamics Analysis Based on Particle Size Imaging.

Parameters such as pretreatment method, enzyme type and concentration, determine the conversion efficiency of biomass' cellulose and hemicellulose to glucose and mainly xylose in biomass-based fuel production. Chemical quantification of these processes offers no information on the effect of enzymatic hydrolysis (EH) on particle morphology. We report on the development of a microscopy method for imaging pretreated biomass particles at different EH stages. The method was based on acquiring large field of view images, typically 20×10 mm2 containing thousands of particles. Morphology of particles with lengths between 2 µm and 5 mm could be visualized and analyzed. The particle length distribution of corn stover samples, pretreated with increasing amounts of sulfuric acid at different EH stages, was measured. Particle size was shown to be dependent on pretreatment severity and EH time. The methodology developed could offer an alternative method for characterization of EH of biomass for second generation biofuels and visualization of recalcitrant structures.

Engineering the Size Distributions of Ordered GaAs Nanowires on Silicon.

Reproducible integration of III-V semiconductors on silicon can open new path toward CMOS compatible optoelectronics and novel design schemes in next generation solar cells. Ordered arrays of nanowires could accomplish this task, provided they are obtained in high yield and uniformity. In this work, we provide understanding on the physical factors affecting size uniformity in ordered GaAs arrays grown on silicon. We show that the length and diameter distributions in the initial stage of growth are not much influenced by the Poissonian fluctuation-induced broadening, but rather are determined by the long incubation stage. We also show that the size distributions are consistent with the double exponential shapes typical for macroscopic nucleation with a large critical length after which the nanowires grow irreversibly. The size uniformity is dramatically improved by increasing the As4 flux, suggesting a new path for obtaining highly uniform arrays of GaAs nanowires on silicon.

Minimal tool set for a prokaryotic circadian clock.

BACKGROUND: Circadian clocks are found in organisms of almost all domains including photosynthetic Cyanobacteria, whereby large diversity exists within the protein components involved. In the model cyanobacterium Synechococcus elongatus PCC 7942 circadian rhythms are driven by a unique KaiABC protein clock, which is embedded in a network of input and output factors. Homologous proteins to the KaiABC clock have been observed in Bacteria and Archaea, where evidence for circadian behavior in these domains is accumulating. However, interaction and function of non-cyanobacterial Kai-proteins as well as homologous input and output components remain mainly unclear. RESULTS: Using a universal BLAST analyses, we identified putative KaiC-based timing systems in organisms outside as well as variations within Cyanobacteria. A systematic analyses of publicly available microarray data elucidated interesting variations in circadian gene expression between different cyanobacterial strains, which might be correlated to the diversity of genome encoded clock components. Based on statistical analyses of co-occurrences of the clock components homologous to Synechococcus elongatus PCC 7942, we propose putative networks of reduced and fully functional clock systems. Further, we studied KaiC sequence conservation to determine functionally important regions of diverged KaiC homologs. Biochemical characterization of exemplary cyanobacterial KaiC proteins as well as homologs from two thermophilic Archaea demonstrated that kinase activity is always present. However, a KaiA-mediated phosphorylation is only detectable in KaiC1 orthologs. CONCLUSION: Our analysis of 11,264 genomes clearly demonstrates that components of the Synechococcus elongatus PCC 7942 circadian clock are present in Bacteria and Archaea. However, all components are less abundant in other organisms than Cyanobacteria and KaiA, Pex, LdpA, and CdpA are only present in the latter. Thus, only reduced KaiBC-based or even simpler, solely KaiC-based timing systems might exist outside of the cyanobacterial phylum, which might be capable of driving diurnal oscillations.

Association mapping of starch chain length distribution and amylose content in pea (Pisum sativum L.) using carbohydrate metabolism candidate genes.

BACKGROUND: Although starch consists of large macromolecules composed of glucose units linked by α-1,4-glycosidic linkages with α-1,6-glycosidic branchpoints, variation in starch structural and functional properties is found both within and between species. Interest in starch genetics is based on the importance of starch in food and industrial processes, with the potential of genetics to provide novel starches. The starch metabolic pathway is complex but has been characterized in diverse plant species, including pea. RESULTS: To understand how allelic variation in the pea starch metabolic pathway affects starch structure and percent amylose, partial sequences of 25 candidate genes were characterized for polymorphisms using a panel of 92 diverse pea lines. Variation in the percent amylose composition of extracted seed starch and (amylopectin) chain length distribution, one measure of starch structure, were characterized for these lines. Association mapping was undertaken to identify polymorphisms associated with the variation in starch chain length distribution and percent amylose, using a mixed linear model that incorporated population structure and kinship. Associations were found for polymorphisms in seven candidate genes plus Mendel's r locus (which conditions the round versus wrinkled seed phenotype). The genes with associated polymorphisms are involved in the substrate supply, chain elongation and branching stages of the pea carbohydrate and starch metabolic pathways. CONCLUSIONS: The association of polymorphisms in carbohydrate and starch metabolic genes with variation in amylopectin chain length distribution and percent amylose may help to guide manipulation of pea seed starch structural and functional properties through plant breeding.

Pathogenesis of Lafora Disease: Transition of Soluble Glycogen to Insoluble Polyglucosan.

Lafora disease (LD, OMIM #254780) is a rare, recessively inherited neurodegenerative disease with adolescent onset, resulting in progressive myoclonus epilepsy which is fatal usually within ten years of symptom onset. The disease is caused by loss-of-function mutations in either of the two genes EPM2A (laforin) or EPM2B (malin). It characteristically involves the accumulation of insoluble glycogen-derived particles, named Lafora bodies (LBs), which are considered neurotoxic and causative of the disease. The pathogenesis of LD is therefore centred on the question of how insoluble LBs emerge from soluble glycogen. Recent data clearly show that an abnormal glycogen chain length distribution, but neither hyperphosphorylation nor impairment of general autophagy, strictly correlates with glycogen accumulation and the presence of LBs. This review summarizes results obtained with patients, mouse models, and cell lines and consolidates apparent paradoxes in the LD literature. Based on the growing body of evidence, it proposes that LD is predominantly caused by an impairment in chain-length regulation affecting only a small proportion of the cellular glycogen. A better grasp of LD pathogenesis will further develop our understanding of glycogen metabolism and structure. It will also facilitate the development of clinical interventions that appropriately target the underlying cause of LD.

General continuous-time Markov model of sequence evolution via insertions/deletions: local alignment probability computation.

BACKGROUND: Insertions and deletions (indels) account for more nucleotide differences between two related DNA sequences than substitutions do, and thus it is imperative to develop a method to reliably calculate the occurrence probabilities of sequence alignments via evolutionary processes on an entire sequence. Previously, we presented a perturbative formulation that facilitates the ab initio calculation of alignment probabilities under a continuous-time Markov model, which describes the stochastic evolution of an entire sequence via indels with quite general rate parameters. And we demonstrated that, under some conditions, the ab initio probability of an alignment can be factorized into the product of an overall factor and contributions from regions (or local alignments) delimited by gapless columns. RESULTS: Here, using our formulation, we attempt to approximately calculate the probabilities of local alignments under space-homogeneous cases. First, for each of all types of local pairwise alignments (PWAs) and some typical types of local multiple sequence alignments (MSAs), we numerically computed the total contribution from all parsimonious indel histories and that from all next-parsimonious histories, and compared them. Second, for some common types of local PWAs, we derived two integral equation systems that can be numerically solved to give practically exact solutions. We compared the total parsimonious contribution with the practically exact solution for each such local PWA. Third, we developed an algorithm that calculates the first-approximate MSA probability by multiplying total parsimonious contributions from all local MSAs. Then we compared the first-approximate probability of each local MSA with its absolute frequency in the MSAs created via a genuine sequence evolution simulator, Dawg. In all these analyses, the total parsimonious contributions approximated the multiplication factors fairly well, as long as gap sizes and branch lengths are at most moderate. Examination of the accuracy of another indel probabilistic model in the light of our formulation indicated some modifications necessary for the model's accuracy improvement. CONCLUSIONS: At least under moderate conditions, the approximate methods can quite accurately calculate ab initio alignment probabilities under biologically more realistic models than before. Thus, our formulation will provide other indel probabilistic models with a sound reference point.