Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle

Many quantitative trait loci (QTLs) are in non-coding regions. Therefore, QTLs are assumed to affect gene regulation. Gene expression and RNA splicing are primary steps of transcription, so DNA variants changing gene expression (eVariants) or RNA splicing (sVariants) are expected to significantly affect phenotypes. We quantify the contribution of eVariants and sVariants detected from 16 tissues (n = 4,725) to 37 traits of ∼120,000 cattle (average magnitude of genetic correlation between traits = 0.13). Analyzed in Bayesian mixture models, averaged across 37 traits, cis and trans eVariants and sVariants detected from 16 tissues jointly explain 69.2% (SE = 0.5%) of heritability, 44% more than expected from the same number of random variants. This 69.2% includes an average of 24% from trans e-/sVariants (14% more than expected). Averaged across 56 lipidomic traits, multi-tissue cis and trans e-/sVariants also explain 71.5% (SE = 0.3%) of heritability, demonstrating the essential role of proximal and distal regulatory variants in shaping mammalian phenotypes.

BayesR3 enables fast MCMC blocked processing for largescale multi-trait genomic prediction and QTN mapping analysis

Bayesian methods, such as BayesR, for predicting the genetic value or risk of individuals from their genotypes, such as Single Nucleotide Polymorphisms (SNP), are often implemented using a Markov Chain Monte Carlo (MCMC) process. However, the generation of Markov chains is computationally slow. We introduce a form of blocked Gibbs sampling for estimating SNP effects from Markov chains that greatly reduces computational time by sampling each SNP effect iteratively n-times from conditional block posteriors. Subsequent iteration over all blocks m-times produces chains of length m × n. We use this strategy to solve large-scale genomic prediction and fine-mapping problems using the Bayesian MCMC mixed-effects genetic model, BayesR3. We validate the method using simulated data, followed by analysis of empirical dairy cattle data using high dimension milk mid infra-red spectra data as an example of “omics” data and show its use to increase the precision of mapping variants affecting milk, fat, and protein yields relative to a univariate analysis of milk, fat, and protein.

BayesR3 samples the polymorphisms affecting complex traits at reduced computational cost to predict the genetic value, breeding value, or individual risk of genotypes.

Empirical Evaluation of Inflorescences' Morphological Attributes for Yield Optimization of Medicinal Cannabis Cultivars

In recent decades with the reacknowledgment of the medicinal properties of Cannabis sativa L. (cannabis) plants, there is an increased demand for high performing cultivars that can deliver quality products for various applications. However, scientific knowledge that can facilitate the generation of advanced cannabis cultivars is scarce. In order to improve cannabis breeding and optimize cultivation techniques, the current study aimed to examine the morphological attributes of cannabis inflorescences using novel image analysis practices. The investigated plant population comprises 478 plants ascribed to 119 genotypes of high-THC or blended THC-CBD ratio that was cultivated under a controlled environment facility. Following harvest, all plants were manually processed and an image of the trimmed and refined inflorescences extracted from each plant was captured. Image analysis was then performed using in-house custom-made software which extracted 8 morphological features (such as size, shape and perimeter) for each of the 127,000 extracted inflorescences. Our findings suggest that environmental factors play an important role in the determination of inflorescences' morphology. Therefore, further studies that focus on genotype X environment interactions are required in order to generate inflorescences with desired characteristics. An examination of the intra-plant inflorescences weight distribution revealed that processing 75% of the plant's largest inflorescences will gain 90% of its overall yield weight. Therefore, for the optimization of post-harvest tasks, it is suggested to evaluate if the benefits from extracting and processing the plant's smaller inflorescences outweigh its operational costs. To advance selection efficacy for breeding purposes, a prediction equation for forecasting the plant's production biomass through width measurements of specific inflorescences, formed under the current experimental methodology, was generated. Thus, it is anticipated that findings from the current study will contribute to the field of medicinal cannabis by improving targeted breeding programs, advancing crop productivity and enhancing the efficacy of post-harvest procedures.

Genome-wide association studies dissect the G × E interaction for agronomic traits in a worldwide collection of safflowers (Carthamus tinctorius L.)

Genome-wide association studies were conducted using a globally diverse safflower (Carthamus tinctorius L.) Genebank collection for grain yield (YP), days to flowering (DF), plant height (PH), 500 seed weight (SW), seed oil content (OL), and crude protein content (PR) in four environments (sites) that differed in water availability. Phenotypic variation was observed for all traits. YP exhibited low overall genetic correlations (rGoverall) across sites, while SW and OL had high rGoverall and high pairwise genetic correlations (rGij) across all pairwise sites. In total, 92 marker-trait associations (MTAs) were identified using three methods, single locus genome-wide association studies (GWAS) using a mixed linear model (MLM), the Bayesian multi-locus method (BayesR), and meta-GWAS. MTAs with large effects across all sites were detected for OL, SW, and PR, and MTAs specific for the different water stress sites were identified for all traits. Five MTAs were associated with multiple traits; 4 of 5 MTAs were variously associated with the three traits of SW, OL, and PR. This study provided insights into the phenotypic variability and genetic architecture of important safflower agronomic traits under different environments.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01295-8.

Circulating Cytokines Predict Immune-Related Toxicity in Melanoma Patients Receiving Anti-PD-1-Based Immunotherapy

PURPOSE

Combination PD-1 and CTLA-4 inhibitor therapy has dramatically improved the survival of patients with advanced melanoma but is also associated with significant immune-related toxicities. This study sought to identify circulating cytokine biomarkers of treatment response and immune-related toxicity.

EXPERIMENTAL DESIGN

The expression of 65 cytokines was profiled longitudinally in 98 patients with melanoma treated with PD-1 inhibitors, alone or in combination with anti-CTLA-4, and in an independent validation cohort of 49 patients treated with combination anti-PD-1 and anti-CTLA-4. Cytokine expression was correlated with RECIST response and immune-related toxicity, defined as toxicity that warranted permanent discontinuation of treatment and administration of high-dose steroids.

RESULTS

Eleven cytokines were significantly upregulated in patients with severe immune-related toxicities at baseline (PRE) and early during treatment (EDT). The expression of these 11 cytokines was integrated into a single toxicity score, the CYTOX (cytokine toxicity) score, and the predictive utility of this score was confirmed in the discovery and validation cohorts. The AUC for the CYTOX score in the validation cohort was 0.68 at PRE [95% confidence interval (CI), 0.51-0.84; P = 0.037] and 0.70 at EDT (95% CI, 0.55-0.85; P = 0.017) using ROC analysis.

CONCLUSIONS

The CYTOX score is predictive of severe immune-related toxicity in patients with melanoma treated with combination anti-CTLA-4 and anti-PD-1 immunotherapy. This score, which includes proinflammatory cytokines such as IL1a, IL2, and IFNα2, may help in the early management of severe, potentially life-threatening immune-related toxicity.See related commentary by Johnson and Balko, p. 1452.

Protein Multiplexed Immunoassay Analysis with R

Plasma samples from 177 control and type 2 diabetes patients collected at three Australian hospitals are screened for 14 analytes using six custom-made multiplex kits across 60 96-well plates. In total 354 samples were collected from the patients, representing one baseline and one end point sample from each patient. R methods and source code for analyzing the analyte fluorescence response obtained from these samples by Luminex Bio-Plex^® xMap multiplexed immunoassay technology are disclosed. Techniques and R procedures for reading Bio-Plex^® result files for statistical analysis and data visualization are also presented. The need for technical replicates and the number of technical replicates are addressed as well as plate layout design strategies. Multinomial regression is used to determine plate to sample covariate balance. Methods for matching clinical covariate information to Bio-Plex^® results and vice versa are given. As well as methods for measuring and inspecting the quality of the fluorescence responses are presented. Both fixed and mixed-effect approaches for immunoassay statistical differential analysis are presented and discussed. A random effect approach to outlier analysis and detection is also shown. The bioinformatics R methodology present here provides a foundation for rigorous and reproducible analysis of the fluorescence response obtained from multiplexed immunoassays.

Cytokine levels and associations with symptom severity in male and female children with autism spectrum disorder

Background

Autism spectrum disorders (ASDs) are complex, pervasive, and heterogeneous neurodevelopmental conditions with varying trajectories, significant male bias and largely unknown etiology. However, an understanding of the biological mechanisms driving pathophysiology is evolving. Immune system aberrations, as identified through cytokine profiles, are believed to have a role in ASD. Altered cytokine levels may facilitate identification of ASD subtypes as well as provide biological markers of response to effective treatments. Research exploring the relationship between cytokine profiles and ASD symptoms is, however, in its infancy. The objective of this study was to explore relationships between cytokine levels and the severity of ASD and other clinical traits.

Methods

Multiplex assay techniques were used to measure levels of 27 cytokines in plasma samples from a cohort of 144 children diagnosed with ASD.

Results

Overall, results showed a significant negative association between platelet-derived growth factor (PDGF)-BB, and the severity of ASD symptoms. Furthermore, a significant interaction with sex suggested a different immune profile for females compared to males. ASD symptom severity was negatively associated with levels of 4 cytokines, IL-1β, IL-8, MIP-1β, and VEGF, in females, but not in males.

Conclusions

Results of the present study suggest that an altered cytokine response or profile is associated with the severity of ASD-related symptoms, with sex a potential modifier of this relationship. Further research in larger populations which recognizes the importance of sex comparisons and longitudinal assessments are now required to extend and further describe the role of the immune system in ASD.

Electronic supplementary material

The online version of this article (10.1186/s13229-017-0176-2) contains supplementary material, which is available to authorized users.

Linking structural features of protein complexes and biological function

Protein-protein interaction (PPI) establishes the central basis for complex cellular networks in a biological cell. Association of proteins with other proteins occurs at varying affinities, yet with a high degree of specificity. PPIs lead to diverse functionality such as catalysis, regulation, signaling, immunity, and inhibition, playing a crucial role in functional genomics. The molecular principle of such interactions is often elusive in nature. Therefore, a comprehensive analysis of known protein complexes from the Protein Data Bank (PDB) is essential for the characterization of structural interface features to determine structure-function relationship. Thus, we analyzed a nonredundant dataset of 278 heterodimer protein complexes, categorized into major functional classes, for distinguishing features. Interestingly, our analysis has identified five key features (interface area, interface polar residue abundance, hydrogen bonds, solvation free energy gain from interface formation, and binding energy) that are discriminatory among the functional classes using Kruskal-Wallis rank sum test. Significant correlations between these PPI interface features amongst functional categories are also documented. Salt bridges correlate with interface area in regulator-inhibitors (r = 0.75). These representative features have implications for the prediction of potential function of novel protein complexes. The results provide molecular insights for better understanding of PPIs and their relation to biological functions.

A novel multiplexed immunoassay identifies CEA, IL-8 and prolactin as prospective markers for Dukes' stages A-D colorectal cancers

Background

Current methods widely deployed for colorectal cancers (CRC) screening lack the necessary sensitivity and specificity required for population-based early disease detection. Cancer-specific protein biomarkers are thought to be produced either by the tumor itself or other tissues in response to the presence of cancers or associated conditions. Equally, known examples of cancer protein biomarkers (e.g., PSA, CA125, CA19-9, CEA, AFP) are frequently found in plasma at very low concentration (pg/mL-ng/mL). New sensitive and specific assays are therefore urgently required to detect the disease at an early stage when prognosis is good following surgical resection. This study was designed to meet the longstanding unmet clinical need for earlier CRC detection by measuring plasma candidate biomarkers of cancer onset and progression in a clinical stage-specific manner. EDTA plasma samples (1 μL) obtained from 75 patients with Dukes’ staged CRC or unaffected controls (age and sex matched with stringent inclusion/exclusion criteria) were assayed for expression of 92 human proteins employing the Proseek® Multiplex Oncology I proximity extension assay. An identical set of plasma samples were analyzed utilizing the Bio-Plex Pro™ human cytokine 27-plex immunoassay.

Results

Similar quantitative expression patterns for 13 plasma antigens common to both platforms endorsed the potential efficacy of Proseek as an immune-based multiplex assay for proteomic biomarker research. Proseek found that expression of Carcinoembryonic Antigen (CEA), IL-8 and prolactin are significantly correlated with CRC stage.

Conclusions

CEA, IL-8 and prolactin expression were found to identify between control (unaffected), non-malignant (Dukes’ A + B) and malignant (Dukes’ C + D) stages.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-015-9081-x) contains supplementary material, which is available to authorized users.

Identification of ovarian cancer associated genes using an integrated approach in a Boolean framework

Background

Cancer is a complex disease where molecular mechanism remains elusive. A systems approach is needed to integrate diverse biological information for the prognosis and therapy risk assessment using mechanistic approach to understand gene interactions in pathways and networks and functional attributes to unravel the biological behaviour of tumors.

Results

We weighted the functional attributes based on various functional properties observed between cancerous and non-cancerous genes reported from literature. This weighing schema was then encoded in a Boolean logic framework to rank differentially expressed genes. We have identified 17 genes to be differentially expressed from a total of 11,173 genes, where ten genes are reported to be down-regulated via epigenetic inactivation and seven genes are up-regulated. Here, we report that the overexpressed genes IRAK1, CHEK1 and BUB1 may play an important role in ovarian cancer. We also show that these 17 genes can be used to form an ovarian cancer signature, to distinguish normal from ovarian cancer subjects and that the set of three genes, CHEK1, AR, and LYN, can be used to classify good and poor prognostic tumors.

Conclusion

We provided a workflow using a Boolean logic schema for the identification of differentially expressed genes by integrating diverse biological information. This integrated approach resulted in the identification of genes as potential biomarkers in ovarian cancer.

Analysis of in vitro secretion profiles from adipose-derived cell populations

Background

Adipose tissue is an attractive source of cells for therapeutic purposes because of the ease of harvest and the high frequency of mesenchymal stem cells (MSCs). Whilst it is clear that MSCs have significant therapeutic potential via their ability to secrete immuno-modulatory and trophic cytokines, the therapeutic use of mixed cell populations from the adipose stromal vascular fraction (SVF) is becoming increasingly common.

Methods

In this study we have measured a panel of 27 cytokines and growth factors secreted by various combinations of human adipose-derived cell populations. These were 1. co-culture of freshly isolated SVF with adipocytes, 2. freshly isolated SVF cultured alone, 3. freshly isolated adipocytes alone and 4. adherent adipose-derived mesenchymal stem cells (ADSCs) at passage 2. In addition, we produced an ‘in silico’ dataset by combining the individual secretion profiles obtained from culturing the SVF with that of the adipocytes. This was compared to the secretion profile of co-cultured SVF and adipocytes. Two-tailed t-tests were performed on the secretion profiles obtained from the SVF, adipocytes, ADSCs and the ‘in silico’ dataset and compared to the secretion profiles obtained from the co-culture of the SVF with adipocytes. A p-value of < 0.05 was considered statistically different. To assess the overall changes that may occur as a result of co-culture we compared the proteomes of SVF and SVF co-cultured with adipocytes using iTRAQ quantitative mass spectrometry.

Results

A co-culture of SVF and adipocytes results in a distinct secretion profile when compared to all other adipose-derived cell populations studied. This illustrates that cellular crosstalk during co-culture of the SVF with adipocytes modulates the production of cytokines by one or more cell types. No biologically relevant differences were detected in the proteomes of SVF cultured alone or co-cultured with adipocytes.

Conclusions

The use of mixed adipose cell populations does not appear to induce cellular stress and results in enhanced secretion profiles. Given the importance of secreted cytokines in cell therapy, the use of a mixed cell population such as the SVF with adipocytes may be considered as an alternative to MSCs or fresh SVF alone.

High throughput peptide mass fingerprinting and protein macroarray analysis using chemical printing strategies

We describe a chemical printer that uses piezoelectric pulsing for rapid, accurate, and non-contact microdispensing of fluid for proteomic analysis of immobilized protein macroarrays. We demonstrate protein digestion and peptide mass fingerprinting analysis of human plasma and platelet proteins direct from a membrane surface subsequent to defined microdispensing of trypsin and matrix solutions, hence bypassing multiple liquid-handling steps. Detection of low abundance, alkaline proteins from whole human platelet extracts has been highlighted. Membrane immobilization of protein permits archiving of samples pre-/post-analysis and provides a means for subanalysis using multiple chemistries. This study highlights the ability to increase sequence coverage for protein identification using multiple enzymes and to characterize N-glycosylation modifications using a combination of PNGase F and trypsin. We also demonstrate microdispensing of multiple serum samples in a quantitative microenzyme-linked immunosorbent assay format to rapidly screen protein macroarrays for pathogen-derived antigens. We anticipate the chemical printer will be a major component of proteomic platforms for high throughput protein identification and characterization with widespread applications in biomedical and diagnostic discovery.

Automatic poisson peak harvesting for high throughput protein identification

High throughput identification of proteins by peptide mass fingerprinting requires an efficient means of picking peaks from mass spectra. Here, we report the development of a peak harvester to automatically pick monoisotopic peaks from spectra generated on matrix-assisted laser desorption/ionisation time of flight (MALDI-TOF) mass spectrometers. The peak harvester uses advanced mathematical morphology and watershed algorithms to first process spectra to stick representations. Subsequently, Poisson modelling is applied to determine which peak in an isotopically resolved group represents the monoisotopic mass of a peptide. We illustrate the features of the peak harvester with mass spectra of standard peptides, digests of gel-separated bovine serum albumin, and with Escherictia coli proteins prepared by two-dimensional polyacrylamide gel electrophoresis. In all cases, the peak harvester proved effective in its ability to pick similar monoisotopic peaks as an experienced human operator, and also proved effective in the identification of monoisotopic masses in cases where isotopic distributions of peptides were overlapping. The peak harvester can be operated in an interactive mode, or can be completely automated and linked through to peptide mass fingerprinting protein identification tools to achieve high throughput automated protein identification.

On the use of local statistical properties in focusing microscopy images

Techniques to extract focus properties of microscopy images are many and varied. Many of them, however, rely on the summation of local statistical properties. Presented here is an examination of conventional focus determination algorithms, and a new method based on planar histograms of these local statistical properties. It is shown that this new method provides finer discernment of the focus properties of an image, and provides a means to extend the focus of an optical microscopy system.

Optical flow analysis of the ventral cellular layer of the migrating Dictyostelium discoideum slug

A digital image analysis system for extracting motion information from time-varying digital light microscopy images is presented. This system is then used to map out the movement profile of the surface layer of cells in contact with the substratum through the extracellular matrix (ECM) of the migrating Dictyostelium discoideum slug. From digital high magnification light microscopy images, the morphology of moving cells within the tail region of a young migrating wild-type WS380B slug is described, and compared with the morphology of streaming D. discoideum cells. It is shown that: (i) when the migrating tip of the slug touches the agar substrate, cells in the anterior ventral surface layer of the tip region slow dramatically; (ii) overall cell movement in the ventral surface layer of the migrating D. discoideum slug is slower than the movement of the slug as a whole; and (iii) in less than 10% of cases a wave of movement (groups of cells synchronously slowing down and then accelerating forward) propagates down the slug axis at approx. 1.2 microns s-1. The time interval between waves may be related to the time interval between tip-to-substratum contact that is periodically re-established during normal WS380B slug migration after each aerial projection of the tip.

Length regulation in the Dictyostelium discoideum slug is a late event

Time-lapse video light microscopy was used to study the emergence and maturation of the migratory slug from a D. discoideum aggregate. The anterior part, the tip of this simple multicellular organism, establishes migration prior to the definition of the rear, and hence the length of the slug. It was found that newly formed slugs of wild-type strain WS380B can reach lengths greater than 1 cm, yet mature slugs of this strain are rarely longer than 2-3 mumm. Often the tip extended out of the aggregation mound upon an arching pillar of cells. After the tip first touched the substratum, it commenced migration with a rapid succession of movement steps. Here we show that at the initiation of migration, a differential rate of cell movement along the developing slug axis results in a series of complicated changes, before the stable and mature shape of the slug is formed. Our results lead to new conclusions about D. discoideum slug formation and shape maintenance. Evidence is presented for regulation of slug length.

Movement of the Dictyostelium discoideum slug: models, musings, and images

The last 5 years have resulted in many advances in knowledge of the cytoskeleton and motility of individual cells. Here the problem of multicellular movement is addressed. The Dictyostelium discoideum slug is examined, and models for how approximately 100,000 cells become coordinated to move are briefly reviewed. Experiments that contributed to model building as well as those used to test models are considered. Four levels of experimentation are considered: (1) the extracellular matrix (ECM) is examined as a component of the system; (2) information obtained by examining the organisation of slug cells through sectioning is presented; (3) time, the 4th dimension, is considered, and approaches to studying the dynamics of cell interactions from the point of view of movement are outlined, and (4) cell adhesion molecules are addressed.