An Ancestral Recombination Graph for Diploid Populations with Skewed Offspring Distribution

A large offspring-number diploid biparental multilocus population model of Moran type is our object of study. At each time step, a pair of diploid individuals drawn uniformly at random contributes offspring to the population. The number of offspring can be large relative to the total population size. Similar “heavily skewed” reproduction mechanisms have been recently considered by various authors (cf. e.g., Eldon and Wakeley 2006, 2008) and reviewed by Hedgecock and Pudovkin (2011). Each diploid parental individual contributes exactly one chromosome to each diploid offspring, and hence ancestral lineages can coalesce only when in distinct individuals. A separation-of-timescales phenomenon is thus observed. A result of Möhle (1998) is extended to obtain convergence of the ancestral process to an ancestral recombination graph necessarily admitting simultaneous multiple mergers of ancestral lineages. The usual ancestral recombination graph is obtained as a special case of our model when the parents contribute only one offspring to the population each time. Due to diploidy and large offspring numbers, novel effects appear. For example, the marginal genealogy at each locus admits simultaneous multiple mergers in up to four groups, and different loci remain substantially correlated even as the recombination rate grows large. Thus, genealogies for loci far apart on the same chromosome remain correlated. Correlation in coalescence times for two loci is derived and shown to be a function of the coalescence parameters of our model. Extending the observations by Eldon and Wakeley (2008), predictions of linkage disequilibrium are shown to be functions of the reproduction parameters of our model, in addition to the recombination rate. Correlations in ratios of coalescence times between loci can be high, even when the recombination rate is high and sample size is large, in large offspring-number populations, as suggested by simulations, hinting at how to distinguish between different population models.     

Protein‐fold recognition using an improved single‐source K diverse shortest paths algorithm

Protein structure prediction, when construed as a fold recognition problem, is one of the most important applications of similarity search in bioinformatics. A new protein‐fold recognition method is reported which combines a single‐source K diverse shortest path (SSKDSP) algorithm with Enrichment of Network Topological Similarity (ENTS) algorithm to search a graphic feature space generated using sequence similarity and structural similarity metrics. A modified, more efficient SSKDSP algorithm is developed to improve the performance of graph searching. The new implementation of the SSKDSP algorithm empirically requires 82% less memory and 61% less time than the current implementation, allowing for the analysis of larger, denser graphs. Furthermore, the statistical significance of fold ranking generated from SSKDSP is assessed using ENTS. The reported ENTS‐SSKDSP algorithm outperforms original ENTS that uses random walk with restart for the graph search as well as other state‐of‐the‐art protein structure prediction algorithms HHSearch and Sparks‐X, as evaluated by a benchmark of 600 query proteins. The reported methods may easily be extended to other similarity search problems in bioinformatics and chemoinformatics. The SSKDSP software is available at http://compsci.hunter.cuny.edu/~leixie/sskdsp.html . Proteins 2016; 84:467–472. © 2016 Wiley Periodicals, Inc.     

Horticultural mineral oil influences Plum pox virus transmission by Myzus persicae

The residual activity of horticultural mineral oil (HMO) on the ability of green peach aphids, Myzus persicae (Sulzer), (GPA) to transmit Plum pox virus (PPV) to peach was measured by infection rates of detached leaves from plants sprayed with either HMO or water as a control that were inoculated using transfer of 25 viruliferous aphids per leaf at 0, 2, 4, 7, 9, 11 and 14 days after treatment (DAT). Persistent effects of HMO residue on the probing and feeding behaviours of GPA were also monitored with the electrical penetration graph (EPG) system. For glasshouse‐grown peach seedlings, the residual activity of HMO reduced PPV infection rates by more than 58% for up to 4 DAT following an initial reduction of approximately 81%. EPG recordings of GPA feeding behaviour showed that HMO significantly delayed first feeding probes and first intracellular punctures by more than 50 min without changing the ensuing stylet penetration behaviour. Applying HMO reduced virus infection rates for up to a week depending on the environmental conditions. EPG monitoring of aphid probing showed that HMO reduced the mean duration and mean number of potential drop (PD) phase feeding occurrences, compared with the water control. A reduction in the PD that has been shown to be related to the transmission of non‐persistently transmitted viruses may partly explain the reduction in PPV infection rates.     

Transforming the dilemma

How does natural selection lead to cooperation between competing individuals? The Prisoner's Dilemma captures the essence of this problem. Two players can either cooperate or defect. The payoff for mutual cooperation, R, is greater than the payoff for mutual defection, P. But a defector versus a cooperator receives the highest payoff, T, where as the cooperator obtains the lowest payoff, S. Hence, the Prisoner's Dilemma is defined by the payoff ranking T > R > P > S . In a well‐mixed population, defectors always have a higher expected payoff than cooperators, and therefore natural selection favors defectors. The evolution of cooperation requires specific mechanisms. Here we discuss five mechanisms for the evolution of cooperation: direct reciprocity, indirect reciprocity, kin selection, group selection, and network reciprocity (or graph selection). Each mechanism leads to a transformation of the Prisoner's Dilemma payoff matrix. From the transformed matrices, we derive the fundamental conditions for the evolution of cooperation. The transformed matrices can be used in standard frameworks of evolutionary dynamics such as the replicator equation or stochastic processes of game dynamics in finite populations.     

Characteristics of sugarcane white leaf phytoplasma transmission by the leafhopper Matsumuratettix hiroglyphicus

The leafhopper Matsumuratettix hiroglyphicus (Matsumura) (Hemiptera: Cicadellidae) is the most important vector of sugarcane white leaf (SCWL) phytoplasma that significantly affects the sugarcane crop in Asia. Here, we aimed to study the characteristics of SCWL phytoplasma transmission by M. hiroglyphicus. To this end, the stylet penetration activities performed during the acquisition access period (AAP) and inoculation access period (IAP) were investigated by the direct current electrical penetration graph technique and confirmed by quantitative polymerase chain reaction (qPCR). Additionally, the latent period (LP) of SCWL phytoplasma in the vector was determined by qPCR and localised by fluorescent in situ hybridisation. The results indicated that the acquisition of SCWL phytoplasma occurred during phloem ingestion (waveform D), whereas its inoculation was associated with salivation into the phloem sieve element (waveform C). The minimum AAP was 15 min and the minimum duration of phloem ingestion was 2.35 min. The minimum LP of SCWL phytoplasma in the vector was at least 14 days; then, SCWL phytoplasma moved to the salivary glands of the insect, enabling the transmission of the pathogen to the host plants. The minimum IAP for a successful transmission of SCWL phytoplasma to the host plants was 11–12 min, with a minimum duration of salivation into phloem of 1.35 min. The female vectors had higher SCWL phytoplasma copy numbers than the male vectors, and displayed faster AAP, IAP, and LP. Overall, our findings provide important information related to the feeding behaviour of M. hiroglyphicus and its effect on the transmission of SCWL phytoplasma.     

scGET: Predicting Cell Fate Transition During Early Embryonic Development by Single-cell Graph Entropy

During early embryonic development, cell fate commitment represents a critical transition or"tipping point"of embryonic differentiation, at which there is a drastic and qualitative shift of the cell populations. In this study, we presented a computational approach, scGET, to explore the gene–gene associations based on single-cell RNA sequencing (scRNA-seq) data for critical transition prediction. Specifically, by transforming the gene expression data to the local network entropy, the single-cell graph entropy (SGE) value quantitatively characterizes the stability and criticality of gene regu-latory networks among cell populations and thus can be employed to detect the critical signal of cell fate or lineage commitment at the single-cell level. Being applied to five scRNA-seq datasets of embryonic differentiation, scGET accurately predicts all the impending cell fate transitions. After identifying the"dark genes"that are non-differentially expressed genes but sensitive to the SGE value, the underlying signaling mechanisms were revealed, suggesting that the synergy of dark genes and their downstream targets may play a key role in various cell development processes. The application in all five datasets demonstrates the effectiveness of scGET in analyzing scRNA-seq data from a network perspective and its potential to track the dynamics of cell differentiation. The source code of scGET is accessible at https://github.com/zhongjiayuna/scGET_Project.     

Block structure and stability of the genetic code

It is known that different codons may be unified into larger groups related to the hierarchical structure, approximate hidden symmetries, and evolutionary origin of the universal genetic code. Using a simplified evolutionary motivated two-letter version of genetic code, the general principles of the most stable coding are discussed. By the complete enumeration in such a reduced code it is strictly proved that the maximum stability with respect to point mutations and shifts in the reading frame needs the fixation of the middle letters within codons in groups with different physico-chemical properties, thus, explaining a key feature of the universal genetic code. The translational stability of the genetic code is studied by the mapping of code onto de Bruijn graph providing both the compact visual representation of mutual relationships between different codons as well as between codons and protein coding DNA sequence and a powerful tool for the investigation of stability of protein coding. Then, the results are extended to four-letter codes. As is shown, the universal genetic code obeys mainly the principles of optimal coding. These results demonstrate the hierarchical character of optimization of universal genetic code with strictly optimal coding being evolved at the earliest stages of molecular evolution. Finally, the universal genetic code is compared with the other natural variants of genetic codes.     

Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions,local adaptation and geographic structure

Recent advances in sequencing allow population‐genomic data to be generated for virtually any species. However, approaches to analyse such data lag behind the ability to generate it, particularly in nonmodel species. Linkage disequilibrium (LD, the nonrandom association of alleles from different loci) is a highly sensitive indicator of many evolutionary phenomena including chromosomal inversions, local adaptation and geographical structure. Here, we present linkage disequilibrium network analysis (LDna), which accesses information on LD shared between multiple loci genomewide. In LD networks, vertices represent loci, and connections between vertices represent the LD between them. We analysed such networks in two test cases: a new restriction‐site‐associated DNA sequence (RAD‐seq) data set for Anopheles baimaii, a Southeast Asian malaria vector; and a well‐characterized single nucleotide polymorphism (SNP) data set from 21 three‐spined stickleback individuals. In each case, we readily identified five distinct LD network clusters (single‐outlier clusters, SOCs), each comprising many loci connected by high LD. In A. baimaii, further population‐genetic analyses supported the inference that each SOC corresponds to a large inversion, consistent with previous cytological studies. For sticklebacks, we inferred that each SOC was associated with a distinct evolutionary phenomenon: two chromosomal inversions, local adaptation, population‐demographic history and geographic structure. LDna is thus a useful exploratory tool, able to give a global overview of LD associated with diverse evolutionary phenomena and identify loci potentially involved. LDna does not require a linkage map or reference genome, so it is applicable to any population‐genomic data set, making it especially valuable for nonmodel species.     

Similarity Indices for Spatia I Ecological Data

We present a method for assessing similarity between species maps of presence and absence or abundance that emphasizes global features while ignoring minor local dissimilarities. The method arranges sites into small groups, or cliques, and allows controlled changes to be made within cliques to reduce the influence of local discrepancies. Resulting measures of similarity are visually more satisfactory than traditional indices. We show that the similarity indices are useful for model selection by comparing observed spatial patterns with those predicted by different fitted models. Examples are provided for spatial distributions of oribatid mites (Acari, Oribatei), woodlarks (Lullula arborea), and red deer (Cervus elaphus).