Identification of new ABA-and MEJA-activated sugarcane bZIP genes by data mining in the SUCEST database

Abstract Sugarcane is generally propagated by cuttings of the stalk containing one or more lateral buds, which will develop into a new plant. The transition from the dormant into the active stage constitutes a complex phenomenon characterized by changes in accumulation of phytohormones and several other physiological aspects. Abscisic acid (ABA) and methyl-jasmonate (MeJA) are major signaling molecules, which influence plant development and stress responses. These plant regulators modulate gene expression with the participation of many transcriptional factors. Basic leucine zipper proteins (bZIPs) form a large family of transcriptional factors involved in a variety of plant physiological processes, such as development and responses to stress. Query sequences consisting of fulllength protein sequence of each of the Arabidopsis bZIP families were utilized to screen the sugarcane EST database (SUCEST) and 86 sugarcane assembled sequences (SAS) coding for bZIPs were identified. cDNA arrays and RNA-gel blots were used to study the expression of these sugarcane bZIP genes during early plantlet development and in response to ABA and MeJA. Six bZIP genes were found to be differentially expressed during development. ABA and MeJA modulated the expression of eight sugarcane bZIP genes. Our findings provide novel insights into the expression of this large protein family of transcriptional factors in sugarcane

Predictability of evolutionary trajectories in fitness landscapes

Experimental studies on enzyme evolution show that only a small fraction of all possible mutation trajectories are accessible to evolution. However, these experiments deal with individual enzymes and explore a tiny part of the fitness landscape. We report an exhaustive analysis of fitness landscapes constructed with an off-lattice model of protein folding where fitness is equated with robustness to misfolding. This model mimics the essential features of the interactions between amino acids, is consistent with the key paradigms of protein folding and reproduces the universal distribution of evolutionary rates among orthologous proteins. We introduce mean path divergence as a quantitative measure of the degree to which the starting and ending points determine the path of evolution in fitness landscapes. Global measures of landscape roughness are good predictors of path divergence in all studied landscapes: the mean path divergence is greater in smooth landscapes than in rough ones. The model-derived and experimental landscapes are significantly smoother than random landscapes and resemble additive landscapes perturbed with moderate amounts of noise; thus, these landscapes are substantially robust to mutation. The model landscapes show a deficit of suboptimal peaks even compared with noisy additive landscapes with similar overall roughness. We suggest that smoothness and the substantial deficit of peaks in the fitness landscapes of protein evolution are fundamental consequences of the physics of protein folding.Comment: 14 pages, 7 figure

Development and external validation study of a melanoma risk prediction model incorporating clinically assessed naevi and solar lentigines

Background: Melanoma risk prediction models could be useful for matching preventive interventions to patients’ risk. Objectives: To develop and validate a model for incident first‐primary cutaneous melanoma using clinically assessed risk factors. Methods: We used unconditional logistic regression with backward selection from the Australian Melanoma Family Study (461 cases and 329 controls) in which age, sex and city of recruitment were kept in each step, and we externally validated it using the Leeds Melanoma Case–Control Study (960 cases and 513 controls). Candidate predictors included clinically assessed whole‐body naevi and solar lentigines, and self‐assessed pigmentation phenotype, sun exposure, family history and history of keratinocyte cancer. We evaluated the predictive strength and discrimination of the model risk factors using odds per age‐ and sex‐adjusted SD (OPERA) and the area under curve (AUC), and calibration using the Hosmer–Lemeshow test. Results: The final model included the number of naevi ≥ 2 mm in diameter on the whole body, solar lentigines on the upper back (a six‐level scale), hair colour at age 18 years and personal history of keratinocyte cancer. Naevi was the strongest risk factor; the OPERA was 3·51 [95% confidence interval (CI) 2·71–4·54] in the Australian study and 2·56 (95% CI 2·23–2·95) in the Leeds study. The AUC was 0·79 (95% CI 0·76–0·83) in the Australian study and 0·73 (95% CI 0·70–0·75) in the Leeds study. The Hosmer–Lemeshow test P‐value was 0·30 in the Australian study and < 0·001 in the Leeds study. Conclusions: This model had good discrimination and could be used by clinicians to stratify patients by melanoma risk for the targeting of preventive interventions. What's already known about this topic? Melanoma risk prediction models may be useful in prevention by tailoring interventions to personalized risk levels. For reasons of feasibility, time and cost many melanoma prediction models use self‐assessed risk factors. However, individuals tend to underestimate their naevus numbers. What does this study add? We present a melanoma risk prediction model, which includes clinically‐assessed whole‐body naevi and solar lentigines, and self‐assessed risk factors including pigmentation phenotype and history of keratinocyte cancer. This model performs well on discrimination, the model's ability to distinguish between individuals with and without melanoma, and may assist clinicians to stratify patients by melanoma risk for targeted preventive interventions

Variation of health-related quality of life assessed by caregivers and patients affected by severe childhood infections.

BACKGROUND: The agreement between self-reported and proxy measures of health status in ill children is not well established. This study aimed to quantify the variation in health-related quality of life (HRQOL) derived from young patients and their carers using different instruments. METHODS: A hospital-based cross-sectional survey was conducted between August 2010 and March 2011. Children with meningitis, bacteremia, pneumonia, acute otitis media, hearing loss, chronic lung disease, epilepsy, mild mental retardation, severe mental retardation, and mental retardation combined with epilepsy, aged between five to 14 years in seven tertiary hospitals were selected for participation in this study. The Health Utilities Index Mark 2 (HUI2), and Mark 3 (HUI3), and the EuroQoL Descriptive System (EQ-5D) and Visual Analogue Scale (EQ-VAS) were applied to both paediatric patients (self-assessment) and caregivers (proxy-assessment). RESULTS: The EQ-5D scores were lowest for acute conditions such as meningitis, bacteremia, and pneumonia, whereas the HUI3 scores were lowest for most chronic conditions such as hearing loss and severe mental retardation. Comparing patient and proxy scores (n = 74), the EQ-5D exhibited high correlation (r = 0.77) while in the HUI2 and HUI3 patient and caregiver scores were moderately correlated (r = 0.58 and 0.67 respectively). The mean difference between self and proxy-assessment using the HUI2, HUI3, EQ-5D and EQ-VAS scores were 0.03, 0.05, -0.03 and -0.02, respectively. In hearing-impaired and chronic lung patients the self-rated HRQOL differed significantly from their caregivers. CONCLUSIONS: The use of caregivers as proxies for measuring HRQOL in young patients affected by pneumococcal infection and its sequelae should be employed with caution. Given the high correlation between instruments, each of the HRQOL instruments appears acceptable apart from the EQ-VAS which exhibited low correlation with the others

Why Is the Correlation between Gene Importance and Gene Evolutionary Rate So Weak?

One of the few commonly believed principles of molecular evolution is that functionally more important genes (or DNA sequences) evolve more slowly than less important ones. This principle is widely used by molecular biologists in daily practice. However, recent genomic analysis of a diverse array of organisms found only weak, negative correlations between the evolutionary rate of a gene and its functional importance, typically measured under a single benign lab condition. A frequently suggested cause of the above finding is that gene importance determined in the lab differs from that in an organism's natural environment. Here, we test this hypothesis in yeast using gene importance values experimentally determined in 418 lab conditions or computationally predicted for 10,000 nutritional conditions. In no single condition or combination of conditions did we find a much stronger negative correlation, which is explainable by our subsequent finding that always-essential (enzyme) genes do not evolve significantly more slowly than sometimes-essential or always-nonessential ones. Furthermore, we verified that functional density, approximated by the fraction of amino acid sites within protein domains, is uncorrelated with gene importance. Thus, neither the lab-nature mismatch nor a potentially biased among-gene distribution of functional density explains the observed weakness of the correlation between gene importance and evolutionary rate. We conclude that the weakness is factual, rather than artifactual. In addition to being weakened by population genetic reasons, the correlation is likely to have been further weakened by the presence of multiple nontrivial rate determinants that are independent from gene importance. These findings notwithstanding, we show that the principle of slower evolution of more important genes does have some predictive power when genes with vastly different evolutionary rates are compared, explaining why the principle can be practically useful despite the weakness of the correlation

Discovery of the First Insect Nidovirus, a Missing Evolutionary Link in the Emergence of the Largest RNA Virus Genomes

Nidoviruses with large genomes (26.3–31.7 kb; ‘large nidoviruses’), including Coronaviridae and Roniviridae, are the most complex positive-sense single-stranded RNA (ssRNA+) viruses. Based on genome size, they are far separated from all other ssRNA+ viruses (below 19.6 kb), including the distantly related Arteriviridae (12.7–15.7 kb; ‘small nidoviruses’). Exceptionally for ssRNA+ viruses, large nidoviruses encode a 3′-5′exoribonuclease (ExoN) that was implicated in controlling RNA replication fidelity. Its acquisition may have given rise to the ancestor of large nidoviruses, a hypothesis for which we here provide evolutionary support using comparative genomics involving the newly discovered first insect-borne nidovirus. This Nam Dinh virus (NDiV), named after a Vietnamese province, was isolated from mosquitoes and is yet to be linked to any pathology. The genome of this enveloped 60–80 nm virus is 20,192 nt and has a nidovirus-like polycistronic organization including two large, partially overlapping open reading frames (ORF) 1a and 1b followed by several smaller 3′-proximal ORFs. Peptide sequencing assigned three virion proteins to ORFs 2a, 2b, and 3, which are expressed from two 3′-coterminal subgenomic RNAs. The NDiV ORF1a/ORF1b frameshifting signal and various replicative proteins were tentatively mapped to canonical positions in the nidovirus genome. They include six nidovirus-wide conserved replicase domains, as well as the ExoN and 2′-O-methyltransferase that are specific to large nidoviruses. NDiV ORF1b also encodes a putative N7-methyltransferase, identified in a subset of large nidoviruses, but not the uridylate-specific endonuclease that – in deviation from the current paradigm - is present exclusively in the currently known vertebrate nidoviruses. Rooted phylogenetic inference by Bayesian and Maximum Likelihood methods indicates that NDiV clusters with roniviruses and that its branch diverged from large nidoviruses early after they split from small nidoviruses. Together these characteristics identify NDiV as the prototype of a new nidovirus family and a missing link in the transition from small to large nidoviruses

Structure and Age Jointly Influence Rates of Protein Evolution

What factors determine a protein's rate of evolution are actively debated. Especially unclear is the relative role of intrinsic factors of present-day proteins versus historical factors such as protein age. Here we study the interplay of structural properties and evolutionary age, as determinants of protein evolutionary rate. We use a large set of one-to-one orthologs between human and mouse proteins, with mapped PDB structures. We report that previously observed structural correlations also hold within each age group – including relationships between solvent accessibility, designabililty, and evolutionary rates. However, age also plays a crucial role: age modulates the relationship between solvent accessibility and rate. Additionally, younger proteins, despite being less designable, tend to evolve faster than older proteins. We show that previously reported relationships between age and rate cannot be explained by structural biases among age groups. Finally, we introduce a knowledge-based potential function to study the stability of proteins through large-scale computation. We find that older proteins are more stable for their native structure, and more robust to mutations, than younger ones. Our results underscore that several determinants, both intrinsic and historical, can interact to determine rates of protein evolution

Population Genetics of Franciscana Dolphins (Pontoporia blainvillei): Introducing a New Population from the Southern Edge of Their Distribution

Due to anthropogenic factors, the franciscana dolphin, Pontoporia blainvillei, is the most threatened small cetacean on the Atlantic coast of South America. Four Franciscana Management Areas have been proposed: Espiritu Santo to Rio de Janeiro (FMA I), São Paulo to Santa Catarina (FMA II), Rio Grande do Sul to Uruguay (FMA III), and Argentina (FMA IV). Further genetic studies distinguished additional populations within these FMAs. We analyzed the population structure, phylogeography, and demographic history in the southernmost portion of the species range. From the analysis of mitochondrial DNA control region sequences, 5 novel haplotypes were found, totalizing 60 haplotypes for the entire distribution range. The haplotype network did not show an apparent phylogeographical signal for the southern FMAs. Two populations were identified: Monte Hermoso (MH) and Necochea (NC)+Claromecó (CL)+Río Negro (RN). The low levels of genetic variability, the relative constant size over time, and the low levels of gene flow may indicate that MH has been colonized by a few maternal lineages and became isolated from geographically close populations. The apparent increase in NC+CL+RN size would be consistent with the higher genetic variability found, since genetic diversity is generally higher in older and expanding populations. Additionally, RN may have experienced a recent split from CL and NC; current high levels of gene flow may be occurring between the latter ones. FMA IV would comprise four franciscana dolphin populations: Samborombón West+Samborombón South, Cabo San Antonio+Buenos Aires East, NC+CL+Buenos Aires Southwest+RN and MH. Results achieved in this study need to be taken into account in order to ensure the long-term survival of the species.Fil: Gariboldi, María Constanza. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Maimónides. Área de Investigaciones Biomédicas y Biotecnológicas. Centro de Estudios Biomédicos, Biotecnológicos, Ambientales y de Diagnóstico; ArgentinaFil: Tunez, Juan Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Luján; ArgentinaFil: Dejean, Cristina Beatriz. Universidad Maimónides. Área de Investigaciones Biomédicas y Biotecnológicas. Centro de Estudios Biomédicos, Biotecnológicos, Ambientales y de Diagnóstico; Argentina. Universidad de Buenos Aires. Facultad de Filosofía y Letras. Instituto de Ciencias Antropológicas. Sección Antropología Biológica; ArgentinaFil: Failla, Mauricio. Fundación Cethus; ArgentinaFil: Vitullo, Alfredo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Maimónides. Área de Investigaciones Biomédicas y Biotecnológicas. Centro de Estudios Biomédicos, Biotecnológicos, Ambientales y de Diagnóstico; ArgentinaFil: Negri, Maria Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales ; ArgentinaFil: Cappozzo, Humberto Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Maimónides. Área de Investigaciones Biomédicas y Biotecnológicas. Centro de Estudios Biomédicos, Biotecnológicos, Ambientales y de Diagnóstico; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales ; Argentin

Integrated Assessment of Genomic Correlates of Protein Evolutionary Rate

Rates of evolution differ widely among proteins, but the causes and consequences of such differences remain under debate. With the advent of high-throughput functional genomics, it is now possible to rigorously assess the genomic correlates of protein evolutionary rate. However, dissecting the correlations among evolutionary rate and these genomic features remains a major challenge. Here, we use an integrated probabilistic modeling approach to study genomic correlates of protein evolutionary rate in Saccharomyces cerevisiae. We measure and rank degrees of association between (i) an approximate measure of protein evolutionary rate with high genome coverage, and (ii) a diverse list of protein properties (sequence, structural, functional, network, and phenotypic). We observe, among many statistically significant correlations, that slowly evolving proteins tend to be regulated by more transcription factors, deficient in predicted structural disorder, involved in characteristic biological functions (such as translation), biased in amino acid composition, and are generally more abundant, more essential, and enriched for interaction partners. Many of these results are in agreement with recent studies. In addition, we assess information contribution of different subsets of these protein properties in the task of predicting slowly evolving proteins. We employ a logistic regression model on binned data that is able to account for intercorrelation, non-linearity, and heterogeneity within features. Our model considers features both individually and in natural ensembles (“meta-features”) in order to assess joint information contribution and degree of contribution independence. Meta-features based on protein abundance and amino acid composition make strong, partially independent contributions to the task of predicting slowly evolving proteins; other meta-features make additional minor contributions. The combination of all meta-features yields predictions comparable to those based on paired species comparisons, and approaching the predictive limit of optimal lineage-insensitive features. Our integrated assessment framework can be readily extended to other correlational analyses at the genome scale

Ancient Ancestry of KFDV and AHFV Revealed by Complete Genome Analyses of Viruses Isolated from Ticks and Mammalian Hosts

Alkhurma hemorrhagic fever (AHF) and Kyasanur Forest disease (KFD) viruses both cause serious and sometimes fatal human disease in their respective ranges, Saudi Arabia and India. AHFV was first identified in the mid-1990s and due to its strong genetic similarity to KFDV it has since been considered the result of a recent introduction of KFDV into Saudi Arabia. To gain a better understanding of the evolutionary history of AHFV and KFDV, we sequenced the full-length genomes of 3 KFDV and 16 AHFV. Sequence analyses show a greater genetic diversity within AHFV than previously thought, particularly within the tick population. The phylogeny constructed with these 19 full-length sequences and two AHFV sequences from GenBank indicates AHFV diverged from KFDV almost 700 years ago. Given the presence of competent tick vectors in the regions between and surrounding Saudi Arabia and India and the recent identification of AHFV in Egypt, these results suggest a broader geographic range of AHFV and KFDV, and raise the possibility of other AHFV/KFDV–like viruses circulating in these regions