SIEVE: One-stop differential expression, variability, and skewness analyses using RNA-Seq data.

Motivation: RNA-Seq data analysis is commonly biased towards detecting differentially expressed genes and insufficiently conveys the complexity of gene expression changes between biological conditions. This bias arises because discrete models of RNA-Seq count data cannot fully characterize the mean, variance, and skewness of gene expression distribution using independent model parameters. A unified framework that simultaneously tests for differential expression, variability, and skewness is needed to realize the full potential of RNA-Seq data analysis in a systems biology context. Results: We present SIEVE, a statistical methodology that provides the desired unified framework. SIEVE embraces a compositional data analysis framework that transforms discrete RNA-Seq counts to a continuous form with a distribution that is well-fitted by a skew-normal distribution. Simulation results show that SIEVE controls the false discovery rate and probability of Type II error better than existing methods for differential expression analysis. Analysis of the Mayo RNA-Seq dataset for Alzheimer's disease using SIEVE reveals that a gene set with significant expression difference in mean, standard deviation and skewness between the control and the Alzheimer's disease group strongly predicts a subject's disease state. Furthermore, functional enrichment analysis shows that relying solely on differentially expressed genes detects only a segment of a much broader spectrum of biological aspects associated with Alzheimer's disease. The latter aspects can only be revealed using genes that show differential variability and skewness. Thus, SIEVE enables fresh perspectives for understanding the intricate changes in gene expression that occur in complex diseases. Availability: The SIEVE R package and source codes are available at https://github.com/Divo-Lee/SIEVE .

Diverse impacts of red palm olein, extra virgin coconut oil and extra virgin olive oil on cardiometabolic risk markers in individuals with central obesity: a randomised trial.

PURPOSE: Dietary fats with an abundance of phytonutrients have garnered public attention beyond fatty acids per se. This study was set to investigate the impact of consuming diets with red palm olein (RPOO), extra virgin coconut oil (EVCO) and extra virgin olive oil (EVOO, as a control) on cardiometabolic risk biomarkers and lipid profile. METHODS: We recruited a total of 156 individuals with central obesity, aged 25-45 years, with waist circumference ≥ 90 cm for men and ≥ 80 cm for women in a parallel single-blind 3-arm randomised controlled trial. The participants consumed isocaloric diets (~ 2400 kcal) enriched with respective test fats (RPOO, EVCO or EVOO) for a 12-week duration. RESULTS: The mean of the primary outcome plasma high sensitivity C-reactive protein was statistically similar between the three diets after a 12-week intervention. EVOO resulted in significantly lower mean LDL cholesterol compared with RPOO and EVCO, despite similar effects on LDL and HDL cholesterol subfractions. The RPOO diet group showed elevated mean [Formula: see text] and [Formula: see text]-carotenes levels compared with EVCO and EVOO diet groups (P < 0.05), corresponding with the rich carotenoid content in RPOO. CONCLUSION: The three oils, each of which has unique phytonutrient and fatty acid compositions, manifested statistically similar cardiometabolic effects in individuals with central obesity at risk of developing cardiovascular diseases with distinct circulating antioxidant properties. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov (NCT05791370).

clrDV: a differential variability test for RNA-Seq data based on the skew-normal distribution.

Background: Pathological conditions may result in certain genes having expression variance that differs markedly from that of the control. Finding such genes from gene expression data can provide invaluable candidates for therapeutic intervention. Under the dominant paradigm for modeling RNA-Seq gene counts using the negative binomial model, tests of differential variability are challenging to develop, owing to dependence of the variance on the mean. Methods: Here, we describe clrDV, a statistical method for detecting genes that show differential variability between two populations. We present the skew-normal distribution for modeling gene-wise null distribution of centered log-ratio transformation of compositional RNA-seq data. Results: Simulation results show that clrDV has false discovery rate and probability of Type II error that are on par with or superior to existing methodologies. In addition, its run time is faster than its closest competitors, and remains relatively constant for increasing sample size per group. Analysis of a large neurodegenerative disease RNA-Seq dataset using clrDV successfully recovers multiple gene candidates that have been reported to be associated with Alzheimer's disease.

Machine learning analysis of wing venation patterns accurately identifies Sarcophagidae, Calliphoridae and Muscidae fly species.

In medical, veterinary and forensic entomology, the ease and affordability of image data acquisition have resulted in whole-image analysis becoming an invaluable approach for species identification. Krawtchouk moment invariants are a classical mathematical transformation that can extract local features from an image, thus allowing subtle species-specific biological variations to be accentuated for subsequent analyses. We extracted Krawtchouk moment invariant features from binarised wing images of 759 male fly specimens from the Calliphoridae, Sarcophagidae and Muscidae families (13 species and a species variant). Subsequently, we trained the Generalized, Unbiased, Interaction Detection and Estimation random forests classifier using linear discriminants derived from these features and inferred the species identity of specimens from the test samples. Fivefold cross-validation results show a 98.56 ± 0.38% (standard error) mean identification accuracy at the family level and a 91.04 ± 1.33% mean identification accuracy at the species level. The mean F1-score of 0.89 ± 0.02 reflects good balance of precision and recall properties of the model. The present study consolidates findings from previous small pilot studies of the usefulness of wing venation patterns for inferring species identities. Thus, the stage is set for the development of a mature data analytic ecosystem for routine computer image-based identification of fly species that are of medical, veterinary and forensic importance.

Size-age population structure of an endangered and anthropogenically introgressed northern Adriatic population of marble trout (Salmo marmoratus Cuv.): insights for its conservation and sustainable exploitation.

Salmonid species are main actors in the Italian socio-ecological landscape of inland fisheries. We present novel data on the size-age structure of one of the remnant Italian populations of the critically endangered marble trout Salmo marmoratus, which co-occurs with other stocked non-native salmonids in a large glacial river of the Lake Maggiore basin (Northern Italy-Southern Switzerland). Like other Italian native trout populations, the Toce River marble trout population is affected by anthropogenic introgression with the non-native brown trout S. trutta. Our sample includes 579 individuals, mainly collected in the Toce River main channel. We estimated the length-weight relationship, described the population size-age structure, estimated the age-specific growth trajectories, and fit an exponential mortality model. A subset of the sample was also used to measure numerical and biomass density. The estimated asymptotic maximum length is ~105 cm total length (TL). Mean length at first maturity is ~55 cm TL, and mean length at maximum yield per recruit is ~68 cm TL. Approximately 45-70% of the population are estimated to die annually, along with a fishing annual mortality of ~37%, with an exploitation ratio of ~0.5. The frequency distribution of length classes in a sample collected by angling shows that ~80% of the individuals that could be retained according to the current recreational fishing regulations likely never reproduced, and large fish disproportionally contributing to recruitment are fished and retained. We identify possible overfishing risks posed by present regulations, and propose updated harvest-slot length limits to mitigate such risks. More detailed and long-term datasets on this system are needed to more specifically inform the fishery management and monitor the effects of any change in the management strategy on the size-age structure of the marble trout population of the Toce River.

On the classification of simple and complex biological images using Krawtchouk moments and Generalized pseudo-Zernike moments: a case study with fly wing images and breast cancer mammograms.

In image analysis, orthogonal moments are useful mathematical transformations for creating new features from digital images. Moreover, orthogonal moment invariants produce image features that are resistant to translation, rotation, and scaling operations. Here, we show the result of a case study in biological image analysis to help researchers judge the potential efficacy of image features derived from orthogonal moments in a machine learning context. In taxonomic classification of forensically important flies from the Sarcophagidae and the Calliphoridae family (n = 74), we found the GUIDE random forests model was able to completely classify samples from 15 different species correctly based on Krawtchouk moment invariant features generated from fly wing images, with zero out-of-bag error probability. For the more challenging problem of classifying breast masses based solely on digital mammograms from the CBIS-DDSM database (n = 1,151), we found that image features generated from the Generalized pseudo-Zernike moments and the Krawtchouk moments only enabled the GUIDE kernel model to achieve modest classification performance. However, using the predicted probability of malignancy from GUIDE as a feature together with five expert features resulted in a reasonably good model that has mean sensitivity of 85%, mean specificity of 61%, and mean accuracy of 70%. We conclude that orthogonal moments have high potential as informative image features in taxonomic classification problems where the patterns of biological variations are not overly complex. For more complicated and heterogeneous patterns of biological variations such as those present in medical images, relying on orthogonal moments alone to reach strong classification performance is unrealistic, but integrating prediction result using them with carefully selected expert features may still produce reasonably good prediction models.

Ocular surface disease in psoriatic patients in a developing country.

PURPOSE: To evaluate ocular surface changes among patients with psoriasis in Malaysia, a developing country in Southeast Asia. METHODS: An interdisciplinary case-control study (60 psoriasis patients and 40 control subjects) to look at the differences in ocular surface manifestations between patients with psoriasis and a group of age-, gender- and ethnicity-matched healthy controls. RESULTS: One hundred and twenty eyes of 60 patients with psoriasis and 80 eyes of 40 healthy controls without psoriasis were included in the study. Mild-to-moderate psoriasis was found in 42 patients (70%), while 18 patients (30%) had severe psoriasis. Psoriatic arthritis was found in 19 patients (32%). Of the 60 psoriatic patients, the prevalence of ocular involvement was 65% (39/60), in which 32% (19/60) had dry eyes, 27% (16/60) had lid margin abnormalities, 33% (20/60) had cataract, and one had history of anterior uveitis. Compared to controls, ocular surface of psoriatic patients showed more eyelid margin abnormalities, higher meibomian gland loss and lower tear film break-up time. The estimated odds ratio for dry eyes in the psoriasis group was 2.2 (95% CI: 0.8-6.9). CONCLUSION: Ocular surface disorders encompassing eyelid margin abnormalities, meibomian gland loss and tear dysfunction occur at an earlier and higher rate among psoriatic patients.

Random forests for predicting species identity of forensically important blow flies (Diptera: Calliphoridae) and flesh flies (Diptera: Sarcophagidae) using geometric morphometric data: Proof of concept.

Wing shape variation has been shown to be useful for delineating forensically important fly species in two Diptera families: Calliphoridae and Sarcophagidae. Compared to DNA-based identification, the cost of geometric morphometric data acquisition and analysis is relatively much lower because the tools required are basic, and stable softwares are available. However, to date, an explicit demonstration of using wing geometric morphometric data for species identity prediction in these two families remains lacking. Here, geometric morphometric data from 19 homologous landmarks on the left wing of males from seven species of Calliphoridae (n = 55), and eight species of Sarcophagidae (n = 40) were obtained and processed using Generalized Procrustes Analysis. Allometric effect was removed by regressing centroid size (in log10 ) against the Procrustes coordinates. Subsequently, principal component analysis of the allometry-adjusted Procrustes variables was done, with the first 15 principal components used to train a random forests model for species prediction. Using a real test sample consisting of 33 male fly specimens collected around a human corpse at a crime scene, the estimated percentage of concordance between species identities predicted using the random forests model and those inferred using DNA-based identification was about 80.6% (approximate 95% confidence interval = [68.9%, 92.2%]). In contrast, baseline concordance using naive majority class prediction was 36.4%. The results provide proof of concept that geometric morphometric data has good potential to complement morphological and DNA-based identification of blow flies and flesh flies in forensic work.

Linking the effects of helminth infection, diet and the gut microbiota with human whole-blood signatures.

Helminth infection and dietary intake can affect the intestinal microbiota, as well as the immune system. Here we analyzed the relationship between fecal microbiota and blood profiles of indigenous Malaysians, referred to locally as Orang Asli, in comparison to urban participants from the capital city of Malaysia, Kuala Lumpur. We found that helminth infections had a larger effect on gut microbial composition than did dietary intake or blood profiles. Trichuris trichiura infection intensity also had the strongest association with blood transcriptional profiles. By characterizing paired longitudinal samples collected before and after deworming treatment, we determined that changes in serum zinc and iron levels among the Orang Asli were driven by changes in helminth infection status, independent of dietary metal intake. Serum zinc and iron levels were associated with changes in the abundance of several microbial taxa. Hence, there is considerable interplay between helminths, micronutrients and the microbiota on the regulation of immune responses in humans.

Enrichment of gut-derived Fusobacterium is associated with suboptimal immune recovery in HIV-infected individuals.

We explored the gut microbiota profile among HIV-infected individuals with diverse immune recovery profiles following long-term suppressive ART and investigated the relationship between the altered bacteria with markers of immune dysfunction. The microbiota profile of rectal swabs from 26 HIV-infected individuals and 20 HIV-uninfected controls were examined. Patients were classified as suboptimal responders, sIR (n = 10, CD4 T-cell <350 cells/ul) and optimal responders, oIR (n = 16, CD4 T-cell >500 cells/ul) after a minimum of 2 years on suppressive ART. Canonical correlation analysis(CCA) and multiple regression modelling were used to explore the association between fecal bacterial taxa abundance and immunological profiles in optimal and suboptimal responders. We found Fusobacterium was significantly enriched among the HIV-infected and the sIR group. CCA results showed that Fusobacterium abundance was negatively correlated with CD4 T-cell counts, but positively correlated with CD4 T-cell activation and CD4 Tregs. Multiple linear regression analysis adjusted for age, baseline CD4 T-cell count, antibiotic exposure and MSM status indicated that higher Fusobacterium relative abundance was independently associated with poorer CD4 T-cell recovery following ART. Enrichment of Fusobacterium was associated with reduced immune recovery and persistent immune dysfunction following ART. Modulating the abundance of this bacterial taxa in the gut may be a viable intervention to improve immune reconstitution in our setting.

Esophageal squamous cell carcinomas in a Malaysian cohort show a lack of association with human papillomavirus.

OBJECTIVE: With an age-standardized incidence rate of 2 per 100 000, esophageal cancer is not common among Malaysians, but they are nevertheless important due to its poor prognosis. The study is to clarify whether the human papillomavirus (HPV) is associated with esophageal cancer in Malaysians as there has been no report to date on this in Malaysians and other South East Asians. METHODS: Altogether 67 esophageal squamous cell carcinomas histologically diagnosed between 1 January 2004 and 31 December 2014 at the Department of Pathology, University of Malaya Medical Center, Malaysia were considered for HPV analysis using two commercially available methods, polymerase chain reaction with flow-through hybridization (21 HPV GenoArray Diagnostic Kit) and multiplex real-time polymerase chain reaction (Anyplex II HPV28 Detection). The DNA amplifiability of the formalin-fixed, paraffin-embedded tumor was checked by amplification of a 268 bp segment of the human ß-globin gene (GH20/PC04) prior to HPV detection. RESULTS: HPV detection was finally carried out in 51 patients. HPV16 was detected in the moderately differentiated, stage IV lower esophageal tumor of a 32-year-old Malaysian-born Chinese woman by both methods. Except for a predilection for Indians, the clinical characteristics of esophageal squamous cell carcinomas in this Malaysian cohort were generally similar to those of other populations. CONCLUSION: It appears that HPV is rare and an unlikely oncovirus in esophageal squamous cell carcinomas of Malaysians.

Dosage-dependent reduction of macular pigment optical density in female breast cancer patients receiving tamoxifen adjuvant therapy.

It is now increasingly common for breast cancer patients to receive adjuvant tamoxifen therapy for a period of up to 10 years. As survival rate increases, managing tamoxifen ocular toxicities is important for patients' quality of life. Macular pigments in photoreceptor cells protect against free radical damage, which can cause macular degeneration. By reducing macular pigment concentration, tamoxifen may increase the risk of macular degeneration. Here, we compared macular pigment optical density (MPOD) and central macular thickness between breast cancer patients on tamoxifen adjuvant therapy (n = 70), and a control group (n = 72). Multiple regression analysis indicated that MPOD decreases with increasing tamoxifen dosage, up to a threshold of about 20 g, after which MPOD plateaus out. Mean MPOD in the treatment group (mean = 0.40) was significantly lower (p-value = 0.02) compared to the control group (mean = 0.47) for the left eye, and for the right eye (treatment mean = 0.39; control mean = 0.48; p-value = 0.009). No significant difference in mean central macular thickness was found between the treatment and the control group (p-values > 0.4). In the control group, MPOD and central macular thickness showed significant correlation (r∼0.30; p-values < 0.01) for both eyes. However, in the treatment group, loss of significant correlation was observed in the left eye (r = 0.21; p-value = 0.08). The present results show that MPOD decreases non-linearly as a function of tamoxifen dosage, and highlight the potential of tamoxifen to reduce macular pigment concentration through an unknown mechanism that does not depend on macular thinning solely.

DeSigN: connecting gene expression with therapeutics for drug repurposing and development.

BACKGROUND: The drug discovery and development pipeline is a long and arduous process that inevitably hampers rapid drug development. Therefore, strategies to improve the efficiency of drug development are urgently needed to enable effective drugs to enter the clinic. Precision medicine has demonstrated that genetic features of cancer cells can be used for predicting drug response, and emerging evidence suggest that gene-drug connections could be predicted more accurately by exploring the cumulative effects of many genes simultaneously. RESULTS: We developed DeSigN, a web-based tool for predicting drug efficacy against cancer cell lines using gene expression patterns. The algorithm correlates phenotype-specific gene signatures derived from differentially expressed genes with pre-defined gene expression profiles associated with drug response data (IC50) from 140 drugs. DeSigN successfully predicted the right drug sensitivity outcome in four published GEO studies. Additionally, it predicted bosutinib, a Src/Abl kinase inhibitor, as a sensitive inhibitor for oral squamous cell carcinoma (OSCC) cell lines. In vitro validation of bosutinib in OSCC cell lines demonstrated that indeed, these cell lines were sensitive to bosutinib with IC50 of 0.8-1.2 µM. As further confirmation, we demonstrated experimentally that bosutinib has anti-proliferative activity in OSCC cell lines, demonstrating that DeSigN was able to robustly predict drug that could be beneficial for tumour control. CONCLUSIONS: DeSigN is a robust method that is useful for the identification of candidate drugs using an input gene signature obtained from gene expression analysis. This user-friendly platform could be used to identify drugs with unanticipated efficacy against cancer cell lines of interest, and therefore could be used for the repurposing of drugs, thus improving the efficiency of drug development.

CORNAS: coverage-dependent RNA-Seq analysis of gene expression data without biological replicates.

BACKGROUND: In current statistical methods for calling differentially expressed genes in RNA-Seq experiments, the assumption is that an adjusted observed gene count represents an unknown true gene count. This adjustment usually consists of a normalization step to account for heterogeneous sample library sizes, and then the resulting normalized gene counts are used as input for parametric or non-parametric differential gene expression tests. A distribution of true gene counts, each with a different probability, can result in the same observed gene count. Importantly, sequencing coverage information is currently not explicitly incorporated into any of the statistical models used for RNA-Seq analysis. RESULTS: We developed a fast Bayesian method which uses the sequencing coverage information determined from the concentration of an RNA sample to estimate the posterior distribution of a true gene count. Our method has better or comparable performance compared to NOISeq and GFOLD, according to the results from simulations and experiments with real unreplicated data. We incorporated a previously unused sequencing coverage parameter into a procedure for differential gene expression analysis with RNA-Seq data. CONCLUSIONS: Our results suggest that our method can be used to overcome analytical bottlenecks in experiments with limited number of replicates and low sequencing coverage. The method is implemented in CORNAS (Coverage-dependent RNA-Seq), and is available at https://github.com/joel-lzb/CORNAS .

Germline APOBEC3B deletion is associated with breast cancer risk in an Asian multi-ethnic cohort and with immune cell presentation.

BACKGROUND: APOBEC3B is a cytosine deaminase implicated in immune response to viral infection, cancer predisposition and carcinogenesis. Germline APOBEC3B deletion is more common in East Asian women and confers a modest risk to breast cancer in both East Asian and Caucasian women. Analysis of tumour samples from women of European descent has shown that germline APOBEC3B deletion is associated with an increased propensity to develop somatic mutations and with an enrichment for immune response-related gene sets. However, this has not been examined in Asian tumour samples, where population differences in genetic and dietary factors may have an impact on the immune system. METHODS: In this study, we determined the prevalence of germline APOBEC3B deletion and its association with breast cancer risk in a cross-sectional hospital-based Asian multi-ethnic cohort of 1451 cases and 1442 controls from Malaysia. We compared gene expression profiles of breast cancers arising from APOBEC3B deletion carriers and non-carriers using microarray analyses. Finally, we characterised the overall abundance of tumour-infiltrating immune cells in breast cancers from TCGA and METABRIC using ESTIMATE and relative frequency of 22 immune cell subsets in breast cancers from METABRIC using CIBERSORT. RESULTS: The minor allelic frequency of APOBEC3B deletion was estimated to be 0.35, 0.42 and 0.16 in female populations of Chinese, Malay and Indian descent, respectively, and that germline APOBEC3B deletion was associated with breast cancer risk with odds ratios of 1.23 (95 % CI: [1.05, 1.44]) for one-copy deletion and 1.38 (95 % CI: [1.10, 1.74]) for two-copy deletion compared to women with no deletion. Germline APOBEC3B deletion was not associated with any clinicopathologic features or the expression of any APOBEC family members but was associated with immune response-related gene sets (FDR q values < 0.05). Analysis of breast cancers from METABRIC revealed breast cancers from APOBEC3B deletion carriers to have significantly higher abundance of tumour-infiltrating immune cells (P < 0.001). CONCLUSIONS: Taken together, our data suggests that tumour-infiltrating immune cells may be an important feature of breast cancers arising in women with APOBEC3B germline deletion, and that this may be of particular interest in Asian women where the germline deletion is more common.

Monogenean anchor morphometry: systematic value, phylogenetic signal, and evolution.

Background. Anchors are one of the important attachment appendages for monogenean parasites. Common descent and evolutionary processes have left their mark on anchor morphometry, in the form of patterns of shape and size variation useful for systematic and evolutionary studies. When combined with morphological and molecular data, analysis of anchor morphometry can potentially answer a wide range of biological questions. Materials and Methods. We used data from anchor morphometry, body size and morphology of 13 Ligophorus (Monogenea: Ancyrocephalidae) species infecting two marine mugilid (Teleostei: Mugilidae) fish hosts: Moolgarda buchanani (Bleeker) and Liza subviridis (Valenciennes) from Malaysia. Anchor shape and size data (n = 530) were generated using methods of geometric morphometrics. We used 28S rRNA, 18S rRNA, and ITS1 sequence data to infer a maximum likelihood phylogeny. We discriminated species using principal component and cluster analysis of shape data. Adams's K mult was used to detect phylogenetic signal in anchor shape. Phylogeny-correlated size and shape changes were investigated using continuous character mapping and directional statistics, respectively. We assessed morphological constraints in anchor morphometry using phylogenetic regression of anchor shape against body size and anchor size. Anchor morphological integration was studied using partial least squares method. The association between copulatory organ morphology and anchor shape and size in phylomorphospace was used to test the Rohde-Hobbs hypothesis. We created monogeneaGM, a new R package that integrates analyses of monogenean anchor geometric morphometric data with morphological and phylogenetic data. Results. We discriminated 12 of the 13 Ligophorus species using anchor shape data. Significant phylogenetic signal was detected in anchor shape. Thus, we discovered new morphological characters based on anchor shaft shape, the length between the inner root point and the outer root point, and the length between the inner root point and the dent point. The species on M. buchanani evolved larger, more robust anchors; those on L. subviridis evolved smaller, more delicate anchors. Anchor shape and size were significantly correlated, suggesting constraints in anchor evolution. Tight integration between the root and the point compartments within anchors confirms the anchor as a single, fully integrated module. The correlation between male copulatory organ morphology and size with anchor shape was consistent with predictions from the Rohde-Hobbs hypothesis. Conclusions. Monogenean anchors are tightly integrated structures, and their shape variation correlates strongly with phylogeny, thus underscoring their value for systematic and evolutionary biology studies. Our MonogeneaGM R package provides tools for researchers to mine biological insights from geometric morphometric data of speciose monogenean genera.

Getting the most out of RNA-seq data analysis.

Background. A common research goal in transcriptome projects is to find genes that are differentially expressed in different phenotype classes. Biologists might wish to validate such gene candidates experimentally, or use them for downstream systems biology analysis. Producing a coherent differential gene expression analysis from RNA-seq count data requires an understanding of how numerous sources of variation such as the replicate size, the hypothesized biological effect size, and the specific method for making differential expression calls interact. We believe an explicit demonstration of such interactions in real RNA-seq data sets is of practical interest to biologists. Results. Using two large public RNA-seq data sets-one representing strong, and another mild, biological effect size-we simulated different replicate size scenarios, and tested the performance of several commonly-used methods for calling differentially expressed genes in each of them. We found that, when biological effect size was mild, RNA-seq experiments should focus on experimental validation of differentially expressed gene candidates. Importantly, at least triplicates must be used, and the differentially expressed genes should be called using methods with high positive predictive value (PPV), such as NOISeq or GFOLD. In contrast, when biological effect size was strong, differentially expressed genes mined from unreplicated experiments using NOISeq, ASC and GFOLD had between 30 to 50% mean PPV, an increase of more than 30-fold compared to the cases of mild biological effect size. Among methods with good PPV performance, having triplicates or more substantially improved mean PPV to over 90% for GFOLD, 60% for DESeq2, 50% for NOISeq, and 30% for edgeR. At a replicate size of six, we found DESeq2 and edgeR to be reasonable methods for calling differentially expressed genes at systems level analysis, as their PPV and sensitivity trade-off were superior to the other methods'. Conclusion. When biological effect size is weak, systems level investigation is not possible using RNAseq data, and no meaningful result can be obtained in unreplicated experiments. Nonetheless, NOISeq or GFOLD may yield limited numbers of gene candidates with good validation potential, when triplicates or more are available. When biological effect size is strong, NOISeq and GFOLD are effective tools for detecting differentially expressed genes in unreplicated RNA-seq experiments for qPCR validation. When triplicates or more are available, GFOLD is a sharp tool for identifying high confidence differentially expressed genes for targeted qPCR validation; for downstream systems level analysis, combined results from DESeq2 and edgeR are useful.

Gross mismatch between thermal tolerances and environmental temperatures in a tropical freshwater snail: climate warming and evolutionary implications.

The relationship between acute thermal tolerance and habitat temperature in ectotherm animals informs about their thermal adaptation and is used to assess thermal safety margins and sensitivity to climate warming. We studied this relationship in an equatorial freshwater snail (Clea nigricans), belonging to a predominantly marine gastropod lineage (Neogastropoda, Buccinidae). We found that tolerance of heating and cooling exceeded average daily maximum and minimum temperatures, by roughly 20°C in each case. Because habitat temperature is generally assumed to be the main selective factor acting on the fundamental thermal niche, the discordance between thermal tolerance and environmental temperature implies trait conservation following 'in situ' environmental change, or following novel colonisation of a thermally less-variable habitat. Whereas heat tolerance could relate to an historical association with the thermally variable and extreme marine intertidal fringe zone, cold tolerance could associate with either an ancestral life at higher latitudes, or represent adaptation to cooler, higher-altitudinal, tropical lotic systems. The broad upper thermal safety margin (difference between heat tolerance and maximum environmental temperature) observed in this snail is grossly incompatible with the very narrow safety margins typically found in most terrestrial tropical ectotherms (insects and lizards), and hence with the emerging prediction that tropical ectotherms, are especially vulnerable to environmental warming. A more comprehensive understanding of climatic vulnerability of animal ectotherms thus requires greater consideration of taxonomic diversity, ecological transition and evolutionary history.

Spectral-domain optical coherence tomography evaluation of postoperative cystoid macular oedema following phacoemulsification with intraoperative complication.

BACKGROUND: To report the rate of cystoid macular oedema (CMO) as detected by spectral-domain optical coherence tomography (SD-OCT) after intraoperative complication during phacoemulsification. The secondary objectives include comparing mean macular thickness and best-corrected visual acuity (BCVA) between those who developed postoperative CMO against those who did not. METHODS: This is a prospective cohort study conducted in a tertiary hospital between July 2009 and June 2010. Serial SD-OCT and BCVA were performed at baseline, 1 week, 6 weeks and 16 weeks postoperatively. RESULTS: Single eyes from 47 subjects were analyzed; of these 16 (34%) eyes developed CMO. In the CMO group, mean macular thickness (±SD) increased sharply by 56 µm from 273 ± 24 µm at baseline to 329 ± 31 µm at 16 weeks; whereas in the non-CMO group, macular thickness showed a slight increase of 14 µm from 259 ± 21 µm to 272 ± 20 µm. In the CMO group, mean BCVA (in logarithm of minimum angle of resolution) improved modestly from 0.92 ± 0.66 to 0.66 ± 0.41 at week 16; while in the non-CMO group, mean BCVA improved markedly from 0.98 ± 0.59 to 0.21 ± 0.13. The two groups differed significantly in mean macular thickness (p < 0.001) and mean BCVA (p < 0.001) at 16 weeks. CONCLUSION: As detection rate of CMO is high, postoperative OCT monitoring for patients with intraoperative complications allows earlier diagnosis and treatment.

A phylogenomic approach to bacterial subspecies classification: proof of concept in Mycobacterium abscessus.

BACKGROUND: Mycobacterium abscessus is a rapidly growing mycobacterium that is often associated with human infections. The taxonomy of this species has undergone several revisions and is still being debated. In this study, we sequenced the genomes of 12 M. abscessus strains and used phylogenomic analysis to perform subspecies classification. RESULTS: A data mining approach was used to rank and select informative genes based on the relative entropy metric for the construction of a phylogenetic tree. The resulting tree topology was similar to that generated using the concatenation of five classical housekeeping genes: rpoB, hsp65, secA, recA and sodA. Additional support for the reliability of the subspecies classification came from the analysis of erm41 and ITS gene sequences, single nucleotide polymorphisms (SNPs)-based classification and strain clustering demonstrated by a variable number tandem repeat (VNTR) assay and a multilocus sequence analysis (MLSA). We subsequently found that the concatenation of a minimal set of three median-ranked genes: DNA polymerase III subunit alpha (polC), 4-hydroxy-2-ketovalerate aldolase (Hoa) and cell division protein FtsZ (ftsZ), is sufficient to recover the same tree topology. PCR assays designed specifically for these genes showed that all three genes could be amplified in the reference strain of M. abscessus ATCC 19977T. CONCLUSION: This study provides proof of concept that whole-genome sequence-based data mining approach can provide confirmatory evidence of the phylogenetic informativeness of existing markers, as well as lead to the discovery of a more economical and informative set of markers that produces similar subspecies classification in M. abscessus. The systematic procedure used in this study to choose the informative minimal set of gene markers can potentially be applied to species or subspecies classification of other bacteria.