The influence of genetic variation on gene expression

Genetic Analysis and Construction of a Fingerprint for Licensed Triadica sebifera Cultivars Using SSR Markers

Triadica sebifera is an important landscaping tree species because of its colorful autumn leaves. In recent years, some cultivars have been bred and licensed, but it can be difficult to identify them from their morphological traits due to their similar phenotypes. To explore the genetic relationships and construct a fingerprint of the cultivars, the licensed T. sebifera cultivars were analyzed using SSR markers. A total of 179 alleles were identified among the 21 cultivars at 16 SSR loci, and these alleles exhibited a high level of genetic diversity (He = 0.86). The genetic variations mainly occurred among cultivars based on an analysis of molecular variance (AMOVA). According to phylogenetic analysis, principal coordinate analysis (PCoA), and Bayesian clustering analysis, the genetic relationships were independent of geographic distances, which may be mainly due to transplantations between regions. Some cultivars with different leaf colors showed obvious genetic differentiation and may be preliminary candidates for cross-breeding. Finally, the fingerprint for the licensed cultivars was constructed with two SSR markers. The results of this study can provide technical support for the application and legal protection of licensed Triadica sebifera cultivars.

Increased DNA methylation contributes to the early ripening of pear fruits during domestication and improvement

BACKGROUND

DNA methylation is an essential epigenetic modification. However, its contribution to trait changes and diversity in the domestication of perennial fruit trees remains unknown.

RESULTS

Here, we investigate the variation in DNA methylation during pear domestication and improvement using whole-genome bisulfite sequencing in 41 pear accessions. Contrary to the significant decrease during rice domestication, we detect a global increase in DNA methylation during pear domestication and improvement. We find this specific increase in pear is significantly correlated with the downregulation of Demeter-like1 (DML1, encoding DNA demethylase) due to human selection. We identify a total of 5591 differentially methylated regions (DMRs). Methylation in the CG and CHG contexts undergoes co-evolution during pear domestication and improvement. DMRs have higher genetic diversity than selection sweep regions, especially in the introns. Approximately 97% of DMRs are not associated with any SNPs, and these DMRs are associated with starch and sucrose metabolism and phenylpropanoid biosynthesis. We also perform correlation analysis between DNA methylation and gene expression. We find genes close to the hypermethylated DMRs that are significantly associated with fruit ripening. We further verify the function of a hyper-DMR-associated gene, CAMTA2, and demonstrate that overexpression of CAMTA2 in tomato and pear callus inhibits fruit ripening.

CONCLUSIONS

Our study describes a specific pattern of DNA methylation in the domestication and improvement of a perennial pear tree and suggests that increased DNA methylation plays an essential role in the early ripening of pear fruits.

Search for chromosomal instability aiding variants reveal naturally occurring kinetochore gene variants that perturb chromosome segregation

Chromosomal instability (CIN) is a hallmark of cancers, and CIN-promoting mutations are not fully understood. Here, we report 141 chromosomal instability aiding variant (CIVa) candidates by assessing the prevalence of loss-of-function (LoF) variants in 135 chromosome segregation genes from over 150,000 humans. Unexpectedly, we observe both heterozygous and homozygous CIVa in Astrin and SKA3, two evolutionarily conserved kinetochore and microtubule-associated proteins essential for chromosome segregation. To stratify harmful versus harmless variants, we combine live-cell microscopy and controlled protein expression. We find the naturally occurring Astrin p.Q1012∗ variant is harmful as it fails to localize normally and induces chromosome misalignment and missegregation, in a dominant negative manner. In contrast, the Astrin p.L7Qfs∗21 variant generates a shorter isoform that localizes and functions normally, and the SKA3 p.Q70Kfs∗7 variant allows wild-type SKA complex localisation and function, revealing distinct resilience mechanisms that render these variants harmless. Thus, we present a scalable framework to predict and stratify naturally occurring CIVa, and provide insight into resilience mechanisms that compensate for naturally occurring CIVa.

Genome-wide expression QTL mapping reveals the highly dynamic regulatory landscape of a major wheat pathogen

BACKGROUND

In agricultural ecosystems, outbreaks of diseases are frequent and pose a significant threat to food security. A successful pathogen undergoes a complex and well-timed sequence of regulatory changes to avoid detection by the host immune system; hence, well-tuned gene regulation is essential for survival. However, the extent to which the regulatory polymorphisms in a pathogen population provide an adaptive advantage is poorly understood.

RESULTS

We used Zymoseptoria tritici, one of the most important pathogens of wheat, to generate a genome-wide map of regulatory polymorphism governing gene expression. We investigated genome-wide transcription levels of 146 strains grown under nutrient starvation and performed expression quantitative trait loci (eQTL) mapping. We identified cis-eQTLs for 65.3% of all genes and the majority of all eQTL loci are within 2kb upstream and downstream of the transcription start site (TSS). We also show that polymorphism in different gene elements contributes disproportionally to gene expression variation. Investigating regulatory polymorphism in gene categories, we found an enrichment of regulatory variants for genes predicted to be important for fungal pathogenesis but with comparatively low effect size, suggesting a separate layer of gene regulation involving epigenetics. We also show that previously reported trait-associated SNPs in pathogen populations are frequently cis-regulatory variants of neighboring genes with implications for the trait architecture.

CONCLUSIONS

Overall, our study provides extensive evidence that single populations segregate large-scale regulatory variation and are likely to fuel rapid adaptation to resistant hosts and environmental change.

A cohort-based study of host gene expression: tumor suppressor and innate immune/inflammatory pathways associated with the HIV reservoir size

The major barrier to an HIV cure is the HIV reservoir: latently-infected cells that persist despite effective antiretroviral therapy (ART). There have been few cohort-based studies evaluating host genomic or transcriptomic predictors of the HIV reservoir. We performed host RNA sequencing and HIV reservoir quantification (total DNA [tDNA], unspliced RNA [usRNA], intact DNA) from peripheral CD4+ T cells from 191 ART-suppressed people with HIV (PWH). After adjusting for nadir CD4+ count, timing of ART initiation, and genetic ancestry, we identified two host genes for which higher expression was significantly associated with smaller total DNA viral reservoir size, P3H3 and NBL1, both known tumor suppressor genes. We then identified 17 host genes for which lower expression was associated with higher residual transcription (HIV usRNA). These included novel associations with membrane channel (KCNJ2, GJB2), inflammasome (IL1A, CSF3, TNFAIP5, TNFAIP6, TNFAIP9, CXCL3, CXCL10), and innate immunity (TLR7) genes (FDR-adjusted q<0.05). Gene set enrichment analyses further identified significant associations of HIV usRNA with TLR4/microbial translocation (q = 0.006), IL-1/NRLP3 inflammasome (q = 0.008), and IL-10 (q = 0.037) signaling. Protein validation assays using ELISA and multiplex cytokine assays supported these observed inverse host gene correlations, with P3H3, IL-10, and TNF-α protein associations achieving statistical significance (p<0.05). Plasma IL-10 was also significantly inversely associated with HIV DNA (p = 0.016). HIV intact DNA was not associated with differential host gene expression, although this may have been due to a large number of undetectable values in our study. To our knowledge, this is the largest host transcriptomic study of the HIV reservoir. Our findings suggest that host gene expression may vary in response to the transcriptionally active reservoir and that changes in cellular proliferation genes may influence the size of the HIV reservoir. These findings add important data to the limited host genetic HIV reservoir studies to date.

The role and risks of selective adaptation in extreme coral habitats

The alarming rate of climate change demands new management strategies to protect coral reefs. Environments such as mangrove lagoons, characterized by extreme variations in multiple abiotic factors, are viewed as potential sources of stress-tolerant corals for strategies such as assisted evolution and coral propagation. However, biological trade-offs for adaptation to such extremes are poorly known. Here, we investigate the reef-building coral Porites lutea thriving in both mangrove and reef sites and show that stress-tolerance comes with compromises in genetic and energetic mechanisms and skeletal characteristics. We observe reduced genetic diversity and gene expression variability in mangrove corals, a disadvantage under future harsher selective pressure. We find reduced density, thickness and higher porosity in coral skeletons from mangroves, symptoms of metabolic energy redirection to stress response functions. These findings demonstrate the need for caution when utilizing stress-tolerant corals in human interventions, as current survival in extremes may compromise future competitive fitness.

Robust identification of regulatory variants (eQTLs) using a differential expression framework developed for RNA-sequencing

BACKGROUND

A gap currently exists between genetic variants and the underlying cell and tissue biology of a trait, and expression quantitative trait loci (eQTL) studies provide important information to help close that gap. However, two concerns that arise with eQTL analyses using RNA-sequencing data are normalization of data across samples and the data not following a normal distribution. Multiple pipelines have been suggested to address this. For instance, the most recent analysis of the human and farm Genotype-Tissue Expression (GTEx) project proposes using trimmed means of M-values (TMM) to normalize the data followed by an inverse normal transformation.

RESULTS

In this study, we reasoned that eQTL analysis could be carried out using the same framework used for differential gene expression (DGE), which uses a negative binomial model, a statistical test feasible for count data. Using the GTEx framework, we identified 35 significant eQTLs (P < 5 × 10^-8) following the ANOVA model and 39 significant eQTLs (P < 5 × 10^-8) following the additive model. Using a differential gene expression framework, we identified 930 and six significant eQTLs (P < 5 × 10^-8) following an analytical framework equivalent to the ANOVA and additive model, respectively. When we compared the two approaches, there was no overlap of significant eQTLs between the two frameworks. Because we defined specific contrasts, we identified trans eQTLs that more closely resembled what we expect from genetic variants showing complete dominance between alleles. Yet, these were not identified by the GTEx framework.

CONCLUSIONS

Our results show that transforming RNA-sequencing data to fit a normal distribution prior to eQTL analysis is not required when the DGE framework is employed. Our proposed approach detected biologically relevant variants that otherwise would not have been identified due to data transformation to fit a normal distribution.

Differences in expression of tumor suppressor, innate immune, inflammasome, and potassium/gap junction channel host genes significantly predict viral reservoir size during treated HIV infection

The major barrier to an HIV cure is the persistence of infected cells that evade host immune surveillance despite effective antiretroviral therapy (ART). Most prior host genetic HIV studies have focused on identifying DNA polymorphisms (e.g., CCR5Δ32 , MHC class I alleles) associated with viral load among untreated "elite controllers" (~1% of HIV+ individuals who are able to control virus without ART). However, there have been few studies evaluating host genetic predictors of viral control for the majority of people living with HIV (PLWH) on ART. We performed host RNA sequencing and HIV reservoir quantification (total DNA, unspliced RNA, intact DNA) from peripheral CD4+ T cells from 191 HIV+ ART-suppressed non-controllers. Multivariate models included covariates for timing of ART initiation, nadir CD4+ count, age, sex, and ancestry. Lower HIV total DNA (an estimate of the total reservoir) was associated with upregulation of tumor suppressor genes NBL1 (q=0.012) and P3H3 (q=0.012). Higher HIV unspliced RNA (an estimate of residual HIV transcription) was associated with downregulation of several host genes involving inflammasome ( IL1A, CSF3, TNFAIP5, TNFAIP6, TNFAIP9 , CXCL3, CXCL10 ) and innate immune ( TLR7 ) signaling, as well as novel associations with potassium ( KCNJ2 ) and gap junction ( GJB2 ) channels, all q<0.05. Gene set enrichment analyses identified significant associations with TLR4/microbial translocation (q=0.006), IL-1β/NRLP3 inflammasome (q=0.008), and IL-10 (q=0.037) signaling. HIV intact DNA (an estimate of the "replication-competent" reservoir) demonstrated trends with thrombin degradation ( PLGLB1 ) and glucose metabolism ( AGL ) genes, but data were (HIV intact DNA detected in only 42% of participants). Our findings demonstrate that among treated PLWH, that inflammation, innate immune responses, bacterial translocation, and tumor suppression/cell proliferation host signaling play a key role in the maintenance of the HIV reservoir during ART. Further data are needed to validate these findings, including functional genomic studies, and expanded epidemiologic studies in female, non-European cohorts.

Author Summary

Although lifelong HIV antiretroviral therapy (ART) suppresses virus, the major barrier to an HIV cure is the persistence of infected cells that evade host immune surveillance despite effective ART, "the HIV reservoir." HIV eradication strategies have focused on eliminating residual virus to allow for HIV remission, but HIV cure trials to date have thus far failed to show a clinically meaningful reduction in the HIV reservoir. There is an urgent need for a better understanding of the host-viral dynamics during ART suppression to identify potential novel therapeutic targets for HIV cure. This is the first epidemiologic host gene expression study to demonstrate a significant link between HIV reservoir size and several well-known immunologic pathways (e.g., IL-1β, TLR7, TNF-α signaling pathways), as well as novel associations with potassium and gap junction channels (Kir2.1, connexin 26). Further data are needed to validate these findings, including functional genomic studies and expanded epidemiologic studies in female, non-European cohorts.

Identification of transcriptional regulatory variants in pig duodenum, liver, and muscle tissues

BACKGROUND

In humans and livestock species, genome-wide association studies (GWAS) have been applied to study the association between variants distributed across the genome and a phenotype of interest. To discover genetic polymorphisms affecting the duodenum, liver, and muscle transcriptomes of 300 pigs from 3 different breeds (Duroc, Landrace, and Large White), we performed expression GWAS between 25,315,878 polymorphisms and the expression of 13,891 genes in duodenum, 12,748 genes in liver, and 11,617 genes in muscle.

RESULTS

More than 9.68 × 1011 association tests were performed, yielding 14,096,080 significantly associated variants, which were grouped in 26,414 expression quantitative trait locus (eQTL) regions. Over 56% of the variants were within 1 Mb of their associated gene. In addition to the 100-kb region upstream of the transcription start site, we identified the importance of the 100-kb region downstream of the 3'UTR for gene regulation, as most of the cis-regulatory variants were located within these 2 regions. We also observed 39,874 hotspot regulatory polymorphisms associated with the expression of 10 or more genes that could modify the protein structure or the expression of a regulator gene. In addition, 2 motifs (5'-GATCCNGYGTTGCYG-3' and a poly(A) sequence) were enriched across the 3 tissues within the neighboring sequences of the most significant single-nucleotide polymorphisms in each cis-eQTL region.

CONCLUSIONS

The 14 million significant associations obtained in this study are publicly available and have enabled the identification of expression-associated cis-, trans-, and hotspot regulatory variants within and across tissues, thus shedding light on the molecular mechanisms of regulatory variations that shape end-trait phenotypes.

The decreased expression of GW2 homologous genes contributed to the increased grain width and thousand‑grain weight in wheat-Dasypyrum villosum 6VS·6DL translocation lines

This study demonstrated that the aberrant transcription of DvGW2 contributed to the increased grain width and thousand-grain weight in wheat-Dasypyrum villosum T6VS·6DL translocation lines. Due to the high immunity to powdery mildew, Dasypyrum villosum 6VS has been one of the most successful applications of the wild relatives in modern wheat breeding. Along with the desired traits, side-effects could be brought when large alien chromosome fragments are introduced into wheat, but little is known about effects of 6VS on agronomic traits. Here, we found that T6VS·6DL translocation had significantly positive effects on grain weight, plant heightand spike length, and small negative effects on total spikelet number and spikelet compactness using recipient and wheat-D. villosum T6VS·6DL allohexaploid wheats, Wan7107 and Pm97033. Further analysis showed that the 6VS segment might exert direct genetic effect on grain width, then driving the increase of thousand-grain weight. Furthermore, comparative transcriptome analysis identified 2549 and 1282 differentially expressed genes (DEGs) and 2220 and 1496 specifically expressed genes (SEGs) at 6 days after pollination (DAP) grains and 15 DAP endosperms, respectively. Enrichment analysis indicated that the process of cell proliferation category was over-represented in the DEGs. Notably, two homologous genes, TaGW2-D1 and DvGW2, were identified as putative candidate genes associated with grain weight and yield. The expression analysis showed that DvGW2 had an aberrant expression in Pm97033, resulting in significantly lower total expression level of GW2 than Wan7107, which drives the increase of grain weight and width in Pm97033. Collectively, our data indicated that the compromised expression of DvGW2 is critical for increased grain width and weight in T6VS·6DL translocation lines.

CoMM-S4: A Collaborative Mixed Model Using Summary-Level eQTL and GWAS Datasets in Transcriptome-Wide Association Studies

Motivation: Genome-wide association studies (GWAS) have achieved remarkable success in identifying SNP-trait associations in the last decade. However, it is challenging to identify the mechanisms that connect the genetic variants with complex traits as the majority of GWAS associations are in non-coding regions. Methods that integrate genomic and transcriptomic data allow us to investigate how genetic variants may affect a trait through their effect on gene expression. These include CoMM and CoMM-S², likelihood-ratio-based methods that integrate GWAS and eQTL studies to assess expression-trait association. However, their reliance on individual-level eQTL data render them inapplicable when only summary-level eQTL results, such as those from large-scale eQTL analyses, are available. Result: We develop an efficient probabilistic model, CoMM-S⁴, to explore the expression-trait association using summary-level eQTL and GWAS datasets. Compared with CoMM-S², which uses individual-level eQTL data, CoMM-S⁴ requires only summary-level eQTL data. To test expression-trait association, an efficient variational Bayesian EM algorithm and a likelihood ratio test were constructed. We applied CoMM-S⁴ to both simulated and real data. The simulation results demonstrate that CoMM-S⁴ can perform as well as CoMM-S² and S-PrediXcan, and analyses using GWAS summary statistics from Biobank Japan and eQTL summary statistics from eQTLGen and GTEx suggest novel susceptibility loci for cardiovascular diseases and osteoporosis. Availability and implementation: The developed R package is available at https://github.com/gordonliu810822/CoMM.

Identification of human long noncoding RNAs associated with nonalcoholic fatty liver disease and metabolic homeostasis

A growing number of long noncoding RNAs (lncRNAs) have emerged as vital metabolic regulators. However, most human lncRNAs are nonconserved and highly tissue specific, vastly limiting our ability to identify human lncRNA metabolic regulators (hLMRs). In this study, we established a pipeline to identify putative hLMRs that are metabolically sensitive, disease relevant, and population applicable. We first progressively processed multilevel human transcriptome data to select liver lncRNAs that exhibit highly dynamic expression in the general population, show differential expression in a nonalcoholic fatty liver disease (NAFLD) population, and respond to dietary intervention in a small NAFLD cohort. We then experimentally demonstrated the responsiveness of selected hepatic lncRNAs to defined metabolic milieus in a liver-specific humanized mouse model. Furthermore, by extracting a concise list of protein-coding genes that are persistently correlated with lncRNAs in general and NAFLD populations, we predicted the specific function for each hLMR. Using gain- and loss-of-function approaches in humanized mice as well as ectopic expression in conventional mice, we validated the regulatory role of one nonconserved hLMR in cholesterol metabolism by coordinating with an RNA-binding protein, PTBP1, to modulate the transcription of cholesterol synthesis genes. Our work overcame the heterogeneity intrinsic to human data to enable the efficient identification and functional definition of disease-relevant human lncRNAs in metabolic homeostasis.

Reciprocal allopolyploid grasses (Festuca × Lolium) display stable patterns of genome dominance

Allopolyploidization entailing the merger of two distinct genomes in a single hybrid organism, is an important process in plant evolution and a valuable tool in breeding programs. Newly established hybrids often experience massive genomic perturbations, including karyotype reshuffling and gene expression modifications. These phenomena may be asymmetric with respect to the two progenitors, with one of the parental genomes being "dominant." Such "genome dominance" can manifest in several ways, including biased homoeolog gene expression and expression level dominance. Here we employed a k-mer-based approach to study gene expression in reciprocal Festuca pratensis Huds. × Lolium multiflorum Lam. allopolyploid grasses. Our study revealed significantly more genes where expression mimicked that of the Lolium parent compared with the Festuca parent. This genome dominance was heritable to successive generation and its direction was only slightly modified by environmental conditions and plant age. Our results suggest that Lolium genome dominance was at least partially caused by its more efficient trans-acting gene expression regulatory factors. Unraveling the mechanisms responsible for propagation of parent-specific traits in hybrid crops contributes to our understanding of allopolyploid genome evolution and opens a way to targeted breeding strategies.

Transcriptome Signatures Predict Phenotypic Variations of Candida auris

Health care facilities are facing serious threats by the recently emerging human fungal pathogen Candida auris owing to its pronounced antifungal multidrug resistance and poor diagnostic tools. Distinct C. auris clades evolved seemingly simultaneously at independent geographical locations and display both genetic and phenotypic diversity. Although comparative genomics and phenotypic profiling studies are increasing, we still lack mechanistic knowledge about the C. auris species diversification and clinical heterogeneity. Since gene expression variability impacts phenotypic plasticity, we aimed to characterize transcriptomic signatures of C. auris patient isolates with distinct antifungal susceptibility profiles in this study. First, we employed an antifungal susceptibility screening of clinical C. auris isolates to identify divergent intra-clade responses to antifungal treatments. Interestingly, comparative transcriptional profiling reveals large gene expression differences between clade I isolates and one clade II strain, irrespective of their antifungal susceptibilities. However, comparisons at the clade levels demonstrate that minor changes in gene expression suffice to drive divergent drug responses. Finally, we functionally validate transcriptional signatures reflecting phenotypic divergence of clinical isolates. Thus, our results suggest that large-scale transcriptional profiling allows for predicting phenotypic diversities of patient isolates, which may help choosing suitable antifungal therapies of multidrug-resistant C. auris.

Single-Nucleotide Polymorphisms in Oxidative Stress-Related Genes and the Risk of a Stroke in a Polish Population-A Preliminary Study

The present preliminary case-control study was undertaken to detect the potential association of six single nucleotide polymorphisms (SNPs) in oxidative stress-related genes: SOD2 (c.47T > C; rs4880), CAT (c.-89A > T; rs7943316), GPX4 (c.660T > A; rs713041), NOS1 (g.117803515C > T; rs1879417) and NOS2 (c.1823C > T; rs2297518 and c.-227G > C; rs10459953) and the occurrence of a stroke. The SNPs were determined using the TaqMan^® Allelic Discrimination Assay in 107 patients with strokes and 107 age- and sex-matched individuals who had not experienced cerebrovascular accidents. The T alleles of the rs4880 were positively correlated with a stroke (bootstrap OR 1.31; 1.07-1.59 95% CI). In the case of the rs713041, an association with the T allele was found (bootstrap OR 1.36; 1.12-1.67). In addition, the occurrence of a stroke was associated with the presence of the C allele of the rs1879417 (bootstrap OR 1.32; 1.09-1.61). We also found that the C/C genotype and C allele of the rs2297518 increased the risk of a stroke (bootstrap ORs 7.00; 4.34-11.29 and 4.96; 3.88-6.34, respectively). Moreover, the C allele of the rs10459953 was associated with an increased occurrence of this disease (bootstrap OR 1.31; 1.08-1.60). These results indicated that genetics variants in the SOD2, GPX4, NOS1 and NOS2 might be associated with susceptibility to strokes in the Polish population.

Variation under domestication in animal models: the case of the Mexican axolotl

BACKGROUND

Species adaptation to laboratory conditions is a special case of domestication that has modified model organisms phenotypically and genetically. The characterisation of these changes is crucial to understand how this variation can affect the outcome of biological experiments. Yet despite the wide use of laboratory animals in biological research, knowledge of the genetic diversity within and between different strains and populations of some animal models is still scarce. This is particularly the case of the Mexican axolotl, which has been bred in captivity since 1864.

RESULTS

Using gene expression data from nine different projects, nucleotide sequence variants were characterised, and distinctive genetic background of the experimental specimens was uncovered. This study provides a catalogue of thousands of nucleotide variants along predicted protein-coding genes, while identifying genome-wide differences between pigment phenotypes in laboratory populations.

CONCLUSIONS

Awareness of the genetic variation could guide a better experimental design while helping to develop molecular tools for monitoring genetic diversity and studying gene functions in laboratory axolotls. Overall, this study highlights the cross-taxa utility that transcriptomic data might have to assess the genetic variation of the experimental specimens, which might help to shorten the journey towards reproducible research.

eQTL mapping of the 12S globulin cruciferin gene PGCRURSE5 as a novel candidate associated with starch content in potato tubers

Tuber starch content (TSC) is a very important trait in potato (Solanum tuberosum L.). This study is the first to use expression quantitative trait loci (eQTL) mapping of transcript-derived markers for TSC in potato. Thirty-four differentially expressed genes were selected by comparing the RNA-seq data of contrasting bulked segregants. For the 11 candidate genes, we determined their relative expression levels across the segregating diploid potato population using RT-qPCR. We detected 36 eQTL as candidate genes distributed on all twelve potato chromosomes, and nine of them overlapped with QTL for TSC. Peaks for two eQTL, eAGPaseS-a and ePGRCRURSE5, were close to the corresponding loci of the large subunit of ADP-glucose pyrophosphorylase (AGPaseS-a) and the 12S globulin cruciferin gene (PGCRURSE5), respectively. The eQTL peaks for AGPaseS-a and PGRCRURSE5 explained 41.0 and 28.3% of the phenotypic variation at the transcript level. We showed the association of the DNA markers for AGPaseS-a and PGRCRURSE5 with QTL for TSC, and significant correlation between the expression level of PGRCRURSE5 and TSC. We did not observe a significant correlation between the expression level of AGPaseS-a and TSC. We concluded that the cruciferin gene PGRCRURSE5 is a novel candidate involved in the regulation of starch content in potato tubers.

Identifying the molecular systems that influence cognitive resilience to Alzheimer's disease in genetically diverse mice

Individual differences in cognitive decline during normal aging and Alzheimer's disease (AD) are common, but the molecular mechanisms underlying these distinct outcomes are not fully understood. We utilized a combination of genetic, molecular, and behavioral data from a mouse population designed to model human variation in cognitive outcomes to search for the molecular mechanisms behind this population-wide variation. Specifically, we used a systems genetics approach to relate gene expression to cognitive outcomes during AD and normal aging. Statistical causal-inference Bayesian modeling was used to model systematic genetic perturbations matched with cognitive data that identified astrocyte and microglia molecular networks as drivers of cognitive resilience to AD. Using genetic mapping, we identified Fgf2 as a potential regulator of the astrocyte network associated with individual differences in short-term memory. We also identified several immune genes as regulators of a microglia network associated with individual differences in long-term memory, which was partly mediated by amyloid burden. Finally, significant overlap between mouse and two different human coexpression networks provided strong evidence of translational relevance for the genetically diverse AD-BXD panel as a model of late-onset AD. Together, this work identified two candidate molecular pathways enriched for microglia and astrocyte genes that serve as causal AD cognitive biomarkers, and provided a greater understanding of processes that modulate individual and population-wide differences in cognitive outcomes during AD.

Investigating population-scale allelic differential expression in wild populations of Oithona similis (Cyclopoida, Claus, 1866)

Acclimation allowed by variation in gene or allele expression in natural populations is increasingly understood as a decisive mechanism, as much as adaptation, for species evolution. However, for small eukaryotic organisms, as species from zooplankton, classical methods face numerous challenges. Here, we propose the concept of allelic differential expression at the population-scale (psADE) to investigate the variation in allele expression in natural populations. We developed a novel approach to detect psADE based on metagenomic and metatranscriptomic data from environmental samples. This approach was applied on the widespread marine copepod, Oithona similis, by combining samples collected during the Tara Oceans expedition (2009-2013) and de novo transcriptome assemblies. Among a total of 25,768 single nucleotide variants (SNVs) of O. similis, 572 (2.2%) were affected by psADE in at least one population (FDR < 0.05). The distribution of SNVs under psADE in different populations is significantly shaped by population genomic differentiation (Pearson r = 0.87, p = 5.6 × 10-30), supporting a partial genetic control of psADE. Moreover, a significant amount of SNVs (0.6%) were under both selection and psADE (p < .05), supporting the hypothesis that natural selection and psADE tends to impact common loci. Population-scale allelic differential expression offers new insights into the gene regulation control in populations and its link with natural selection.

Fast read alignment with incorporation of known genomic variants

Background

Many genetic variants have been reported from sequencing projects due to decreasing experimental costs. Compared to the current typical paradigm, read mapping incorporating existing variants can improve the performance of subsequent analysis. This method is supposed to map sequencing reads efficiently to a graphical index with a reference genome and known variation to increase alignment quality and variant calling accuracy. However, storing and indexing various types of variation require costly RAM space.

Methods

Aligning reads to a graph model-based index including the whole set of variants is ultimately an NP-hard problem in theory. Here, we propose a variation-aware read alignment algorithm (VARA), which generates the alignment between read and multiple genomic sequences simultaneously utilizing the schema of the Landau-Vishkin algorithm. VARA dynamically extracts regional variants to construct a pseudo tree-based structure on-the-fly for seed extension without loading the whole genome variation into memory space.

Results

We developed the novel high-throughput sequencing read aligner deBGA-VARA by integrating VARA into deBGA. The deBGA-VARA is benchmarked both on simulated reads and the NA12878 sequencing dataset. The experimental results demonstrate that read alignment incorporating genetic variation knowledge can achieve high sensitivity and accuracy.

Conclusions

Due to its efficiency, VARA provides a promising solution for further improvement of variant calling while maintaining small memory footprints. The deBGA-VARA is available at: https://github.com/hitbc/deBGA-VARA.

Emerging Roles for NLRC5 in Immune Diseases

Innate immunity activates the corresponding immune response relying on multiple pattern recognition receptors (PRRs) that includes pattern recognition receptors (PRRs), like NOD-like receptors (NLRs), RIG-I-like receptors (RLRs), and C-type lectin receptors (CLRs), which could accurately recognize invasive pathogens. In particular, NLRs belong to a large protein family of pattern recognition receptors in the cytoplasm, where they are highly correlated with activation of inflammatory response system followed by rapid clearance of invasive pathogens. Among the NLRs family, NLRC5, also known as NOD4 or NOD27, accounts for a large proportion and involves in immune responses far and wide. Notably, in the above response case of inflammation, the expression of NLRC5 remarkably increased in immune cells and immune-related tissues. However, the evidence for higher expression of NLRC5 in immune disease still remains controversial. It is noted that the growing evidence further accounts for the participation of NLRC5 in the innate immune response and inflammatory diseases. Moreover, NLRC5 has also been confirmed to exert a critical role in the control of regulatory diverse signaling pathways. Together with its broad participation in the occurrence and development of immune diseases, NLRC5 can be consequently treated as a potential therapeutic target. Nevertheless, the paucity of absolute understanding of intrinsic characteristics and underlying mechanisms of NLRC5 still make it hard to develop targeting drugs. Therefore, current summary about NLRC5 information is indispensable. Herein, current knowledge of NLRC5 is summarized, and research advances in terms of NLRC5 in characteristics, biological function, and regulatory mechanisms are reviewed.

Inheritance patterns of the transcriptome in hybrid chickens and their parents revealed by expression analysis

Although many phenotypic traits of chickens have been well documented, the genetic patterns of gene expression levels in chickens remain to be determined. In the present study, we crossed two chicken breeds, White Leghorn (WL) and Cornish (Cor), which have been selected for egg and meat production, respectively, for a few hundred years. We evaluated transcriptome abundance in the brain, muscle, and liver from the day-old progenies of pure-bred WL and Cor, and the hybrids of these two breeds, by RNA-Seq in order to determine the inheritance patterns of gene expression. Comparison among expression levels in the different groups revealed that most of the genes showed conserved expression patterns in all three examined tissues and that brain had the highest number of conserved genes, which indicates that conserved genes are predominantly important compared to others. On the basis of allelic expression analysis, in addition to the conserved genes, we identified the extensive presence of additive, dominant (Cor dominant and WL dominant), over-dominant, and under-dominant genes in all three tissues in hybrids. Our study is the first to provide an overview of inheritance patterns of the transcriptome in layers and broilers, and we also provide insights into the genetics of chickens at the gene expression level.

New considerations for hiPSC-based models of neuropsychiatric disorders

The development of human-induced pluripotent stem cells (hiPSCs) has made possible patient-specific modeling across the spectrum of human disease. Here, we discuss recent advances in psychiatric genomics and post-mortem studies that provide critical insights concerning cell-type composition and sample size that should be considered when designing hiPSC-based studies of complex genetic disease. We review recent hiPSC-based models of SZ, in light of our new understanding of critical power limitations in the design of hiPSC-based studies of complex genetic disorders. Three possible solutions are a movement towards genetically stratified cohorts of rare variant patients, application of CRISPR technologies to engineer isogenic neural cells to study the impact of common variants, and integration of advanced genetics and hiPSC-based datasets in future studies. Overall, we emphasize that to advance the reproducibility and relevance of hiPSC-based studies, stem cell biologists must contemplate statistical and biological considerations that are already well accepted in the field of genetics. We conclude with a discussion of the hypothesis of biological convergence of disease-through molecular, cellular, circuit, and patient level phenotypes-and how this might emerge through hiPSC-based studies.

Gene expression variation and parental allele inheritance in a Xiphophorus interspecies hybridization model

Understanding the genetic mechanisms underlying segregation of phenotypic variation through successive generations is important for understanding physiological changes and disease risk. Tracing the etiology of variation in gene expression enables identification of genetic interactions, and may uncover molecular mechanisms leading to the phenotypic expression of a trait, especially when utilizing model organisms that have well-defined genetic lineages. There are a plethora of studies that describe relationships between gene expression and genotype, however, the idea that global variations in gene expression are also controlled by genotype remains novel. Despite the identification of loci that control gene expression variation, the global understanding of how genome constitution affects trait variability is unknown. To study this question, we utilized Xiphophorus fish of different, but tractable genetic backgrounds (inbred, F₁ interspecies hybrids, and backcross hybrid progeny), and measured each individual’s gene expression concurrent with the degrees of inter-individual expression variation. We found, (a) F₁ interspecies hybrids exhibited less variability than inbred animals, indicting gene expression variation is not affected by the fraction of heterozygous loci within an individual genome, and (b), that mixing genotypes in backcross populations led to higher levels of gene expression variability, supporting the idea that expression variability is caused by heterogeneity of genotypes of cis or trans loci. In conclusion, heterogeneity of genotype, introduced by inheritance of different alleles, accounts for the largest effects on global phenotypical variability.

Phenotypical variability is a multi-factorial phenomenon. Although it has been shown that inheriting certain gene is associated with lower phenotypical variability, how genome complexity affect phenotypical variability is still unclear. To study this question, we used inbred Xiphophorus fish, backcross interspecies hybrids, and F₁ interspecies hybrids between select Xiphophorus species to model genetic composition with minimum, medium, and maximum heterozygosity respectively, and measured their global gene expression variability. We found gene expression variation is not affected by the percentage of heterozygous loci in individual genome, but instead related to heterogeneity of genotype at local or remote loci.

Entamoeba histolytica: Quantitative Proteomics Analysis Reveals Putative Virulence-Associated Differentially Abundant Membrane Proteins

Entamoeba histolytica is a protozoan parasite that causes amebiasis and poses a significant health risk for populations in endemic areas. The molecular mechanisms involved in the pathogenesis and regulation of the parasite are not well characterized. We aimed to identify and quantify the differentially abundant membrane proteins by comparing the membrane proteins of virulent and avirulent variants of E. histolytica HM-1:IMSS, and to investigate the potential associations among the differentially abundant membrane proteins. We performed quantitative proteomics analysis using isobaric tags for relative and absolute quantitation labeling, in combination with two mass spectrometry instruments, that is, nano-liquid chromatography (nanoLC)-matrix-assisted laser desorption/ionization-mass spectrometry/mass spectrometry and nanoLC-electrospray ionization tandem mass spectrometry. Overall, 37 membrane proteins were found to be differentially abundant, whereby 19 and 18 membrane proteins of the virulent variant of E. histolytica increased and decreased in abundance, respectively. Proteins that were differentially abundant include Rho family GTPase, calreticulin, a 70-kDa heat shock protein, and hypothetical proteins. Analysis by Protein ANalysis THrough Evolutionary Relationships database revealed that the differentially abundant membrane proteins were mainly involved in catalytic activities (29.7%) and metabolic processes (32.4%). Differentially abundant membrane proteins that were found to be involved mainly in the catalytic activities and the metabolic processes were highlighted together with their putative roles in relation to the virulence. Further investigations should be performed to elucidate the roles of these proteins in E. histolytica pathogenesis.

A Robust Methodology for Assessing Differential Homeolog Contributions to the Transcriptomes of Allopolyploids

Polyploidy has played a pivotal and recurring role in angiosperm evolution. Allotetraploids arise from hybridization between species and possess duplicated gene copies (homeologs) that serve redundant roles immediately after polyploidization. Although polyploidization is a major contributor to plant evolution, it remains poorly understood. We describe an analytical approach for assessing homeolog-specific expression that begins with de novo assembly of parental transcriptomes and effectively (i) reduces redundancy in de novo assemblies, (ii) identifies putative orthologs, (iii) isolates common regions between orthologs, and (iv) assesses homeolog-specific expression using a robust Bayesian Poisson-Gamma model to account for sequence bias when mapping polyploid reads back to parental references. Using this novel methodology, we examine differential homeolog contributions to the transcriptome in the recently formed allopolyploids Tragopogon mirus and T. miscellus (Compositae). Notably, we assess a larger Tragopogon gene set than previous studies of this system. Using carefully identified orthologous regions and filtering biased orthologs, we find in both allopolyploids largely balanced expression with no strong parental bias. These new methods can be used to examine homeolog expression in any tetrapolyploid system without requiring a reference genome.

Realizing the significance of noncoding functionality in clinical genomics

Clinical genomics promises unprecedented precision in understanding the genetic basis of disease. Understanding the impact of variation across the genome is required to realize this potential. Currently, clinical genomics analyses focus on protein-coding genes. However, the noncoding genome is substantially larger than the protein-coding counterpart, and contains structural, regulatory, and transcribed information that needs to be incorporated into genome annotations if the full extent of the opportunity to use genomic information in healthcare is to be realized. This article reviews the challenges and opportunities in unlocking the clinical significance of coding and noncoding genomic information and translating its utility in practice.

Most of the DNA in the genome does not consist of genes that code for proteins, and understanding the function of these less examined parts of our genetic material is essential to fully understand human development and disease. Brian Gloss and Marcel Dinger at the Garvan Institute of Medical Research in Sydney, Australia, review the challenges and opportunities in unraveling the clinical significance of all parts of our DNA. Many regions of DNA that do not encode protein molecules perform crucial functions in regulating the activity and interactions of the protein-coding genes. Variations in these regions may significantly influence the risks and causes of disease. Studying all parts of the genome will be critical for ensuring that the powerful modern techniques of genetic analysis have maximal impact on healthcare.

Genetic regulation of disease risk and endometrial gene expression highlights potential target genes for endometriosis and polycystic ovarian syndrome

Gene expression varies markedly across the menstrual cycle and expression levels for many genes are under genetic control. We analyzed gene expression and mapped expression quantitative trait loci (eQTLs) in endometrial tissue samples from 229 women and then analyzed the overlap of endometrial eQTL signals with genomic regions associated with endometriosis and other reproductive traits. We observed a total of 45,923 cis-eQTLs for 417 unique genes and 2,968 trans-eQTLs affecting 82 unique genes. Two eQTLs were located in known risk regions for endometriosis including LINC00339 on chromosome 1 and VEZT on chromosome 12 and there was evidence for eQTLs that may be target genes in genomic regions associated with other reproductive diseases. Dynamic changes in expression of individual genes across cycle include alterations in both mean expression and transcriptional silencing. Significant effects of cycle stage on mean expression levels were observed for (2,427/15,262) probes with detectable expression in at least 90% of samples and for (2,877/9,626) probes expressed in some, but not all samples. Pathway analysis supports similar biological control of both altered expression levels and transcriptional silencing. Taken together, these data identify strong genetic effects on genes with diverse functions in human endometrium and provide a platform for better understanding genetic effects on endometrial-related pathologies.

CNVs are associated with genomic architecture in a songbird

Background

Understanding variation in genome structure is essential to understand phenotypic differences within populations and the evolutionary history of species. A promising form of this structural variation is copy number variation (CNV). CNVs can be generated by different recombination mechanisms, such as non-allelic homologous recombination, that rely on specific characteristics of the genome architecture. These structural variants can therefore be more abundant at particular genes ultimately leading to variation in phenotypes under selection. Detailed characterization of CNVs therefore can reveal evolutionary footprints of selection and provide insight in their contribution to phenotypic variation in wild populations.

Results

Here we use genotypic data from a long-term population of great tits (Parus major), a widely studied passerine bird in ecology and evolution, to detect CNVs and identify genomic features prevailing within these regions. We used allele intensities and frequencies from high-density SNP array data from 2,175 birds. We detected 41,029 CNVs concatenated into 8,008 distinct CNV regions (CNVRs). We successfully validated 93.75% of the CNVs tested by qPCR, which were sampled at different frequencies and sizes. A mother-daughter family structure allowed for the evaluation of the inheritance of a number of these CNVs. Thereby, only CNVs with 40 probes or more display segregation in accordance with Mendelian inheritance, suggesting a high rate of false negative calls for smaller CNVs. As CNVRs are a coarse-grained map of CNV loci, we also inferred the frequency of coincident CNV start and end breakpoints. We observed frequency-dependent enrichment of these breakpoints at homologous regions, CpG sites and AT-rich intervals. A gene ontology enrichment analyses showed that CNVs are enriched in genes underpinning neural, cardiac and ion transport pathways.

Conclusion

Great tit CNVs are present in almost half of the genes and prominent at repetitive-homologous and regulatory regions. Although overlapping genes under selection, the high number of false negatives make neutrality or association tests on CNVs detected here difficult. Therefore, CNVs should be further addressed in the light of their false negative rate and architecture to improve the comprehension of their association with phenotypes and evolutionary history.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4577-1) contains supplementary material, which is available to authorized users.

A Direct Test of Selection in Cell Populations Using the Diversity in Gene Expression within Tumors

Although intratumor diversity driven by selection has been the prevailing view in cancer biology, recent population genetic analyses have been unable to reject the neutral interpretation. As the power to reject neutrality in tumors is often low, it will be desirable to have an alternative means to test selection directly. Here, we utilize gene expression data as a surrogate for functional significance in intra- and intertumor comparisons. The expression divergence between samples known to be driven by selection (e.g., between tumor and normal tissues) is always higher than the divergence between normal samples, which should be close to the neutral level of divergence. In contrast, the expression differentiation between regions of the same tumor, being lower than the neutral divergence, is incompatible with the hypothesis of selectively driven divergence. To further test the hypothesis of neutral evolution, we select a hepatocellular carcinoma tumor that has large intratumor SNV and CNV (single nucleotide variation and copy number variation, respectively) diversity. This tumor enables us to calibrate the level of expression divergence against that of genetic divergence. We observe that intratumor divergence in gene expression profile lags far behind genetic divergence, indicating insufficient phenotypic differences for selection to operate. All these expression analyses corroborate that natural selection does not operate effectively within tumors, supporting recent interpretations of within-tumor diversity. As the expected level of genetic diversity, hence the potential for drug resistance, would be much higher under neutrality than under selection, the issue is of both theoretical and clinical significance.

Effects of short indels on protein structure and function in human genomes

Insertions and deletions (indels) represent the second most common type of genetic variations in human genomes. Indels can be deleterious and contribute to disease susceptibility as recent genome sequencing projects revealed a large number of indels in various cancer types. In this study, we investigated the possible effects of small coding indels on protein structure and function, and the baseline characteristics of indels in 2504 individuals of 26 populations from the 1000 Genomes Project. We found that each population has a distinct pattern in genes with small indels. Frameshift (FS) indels are enriched in olfactory receptor activity while non-frameshift (NFS) indels are enriched in transcription-related proteins. Structural analysis of NFS indels revealed that they predominantly adopt coil or disordered conformations, especially in proteins with transcription-related NFS indels. These results suggest that the annotated coding indels from the 1000 Genomes Project, while contributing to genetic variations and phenotypic diversity, generally do not affect the core protein structures and have no deleterious effect on essential biological processes. In addition, we found that a number of reference genome annotations might need to be updated due to the high prevalence of annotated homozygous indels in the general population.

Nine differentially expressed genes from a post mortem study and their association with suicidal status in a sample of suicide completers, attempters and controls

Several lines of evidence indicate that suicidal behaviour is partly heritable, with multiple genes implicated in its aetiology. We focused on nine genes (S100A13, EFEMP1, PCDHB5, PDGFRB, CDCA7L, SCN2B, PTPRR, MLC1 and ZFP36) which we previously detected as differentially expressed in the cortex of suicide victims compared to controls. We investigated 84 variants within these genes in 495 suicidal subjects (299 completers and 196 attempters) and 1513 controls (109 post-mortem and 1404 healthy). We evaluated associations with: 1) suicidal phenotype; 2) possible endophenotypes for suicidal behaviour. Overall positive results did not survive the correction threshold. However, we found a nominally different distribution of EFEMP1 genotypes, alleles and haplotypes between suicidal subjects and controls, results that were partially replicated when we separately considered the subgroup of suicide completers and post-mortem controls. A weaker association emerged also for PTPRR. Both EFEMP1 and PTPRR genes were also related to possible endophenotypes for suicidal behaviour such as anger, depression-anxiety and fatigue. Because of the large number of analyses performed and the low significance values further replication are mandatory. Nevertheless, neurotrophic gene variants, in particular EFEMP1 and PTPRR, may have a role in the pathogenesis of suicidal behaviour.

Deciphering the regulation of porcine genes influencing growth, fatness and yield-related traits through genetical genomics

Genetical genomics approaches aim at identifying quantitative trait loci for molecular traits, also known as intermediate phenotypes, such as gene expression, that could link variation in genetic information to physiological traits. In the current study, an expression GWAS has been carried out on an experimental Iberian × Landrace backcross in order to identify the genomic regions regulating the gene expression of those genes whose expression is correlated with growth, fat deposition, and premium cut yield measures in pig. The analyses were conducted exploiting Porcine 60K SNP BeadChip genotypes and Porcine Expression Microarray data hybridized on mRNA from Longissimus dorsi muscle. In order to focus the analysis on productive traits and reduce the number of analyses, only those probesets whose expression showed significant correlation with at least one of the seven phenotypes of interest were selected for the eGWAS. A total of 63 eQTL regions were identified with effects on 36 different transcripts. Those eQTLs overlapping with phenotypic QTLs on SSC4, SSC9, SSC13, and SSC17 chromosomes previously detected in the same animal material were further analyzed. Moreover, candidate genes and SNPs were analyzed. Among the most promising results, a long non-coding RNA, ALDBSSCG0000001928, was identified, whose expression is correlated with premium cut yield. Association analysis and in silico sequence domain annotation support TXNRD3 polymorphisms as candidate to regulate ALDBSSCG0000001928 expression, which can be involved in the transcriptional regulation of surrounding genes, affecting productive and meat quality traits.

Common variants in the PARL and PINK1 genes increase the risk to leprosy in Han Chinese from South China

Leprosy is a chronic infectious and neurological disease caused by Mycobacterium leprae, an unculturable pathogen with massive genomic decay and dependence on host metabolism. We hypothesized that mitochondrial genes PARL and PINK1 would confer risk to leprosy. Thirteen tag SNPs of PARL and PINK1 were analyzed in 3620 individuals with or without leprosy from China. We also sequenced the entire exons of PARL, PINK1 and PARK2 in 80 patients with a family history of leprosy by using the next generation sequencing technology (NGS). We found that PARL SNP rs12631031 conferred a risk to leprosy (P_adjusted = 0.019) and multibacillary leprosy (MB, P_adjusted = 0.020) at the allelic level. rs12631031 and rs7653061 in PARL were associated with leprosy and MB (dominant model, P_adjusted < 0.05) at the genotypic level. PINK1 SNP rs4704 was associated with leprosy at the genotypic level (P_adjusted = 0.004). We confirmed that common variants in PARL and PINK1 were associated with leprosy in patients underwent NGS. Furthermore, PARL and PINK1 could physically interact with each other and were involved in the highly connected network formed by reported leprosy susceptibility genes. Together, our results showed that PARL and PINK1 genetic variants are associated with leprosy.

Adrenal cortex expression quantitative trait loci in a German Holstein × Charolais cross

Background

The importance of the adrenal gland in regard to lactation and reproduction in cattle has been recognized early. Caused by interest in animal welfare and the impact of stress on economically important traits in farm animals the adrenal gland and its function within the stress response is of increasing interest. However, the molecular mechanisms and pathways involved in stress-related effects on economically important traits in farm animals are not fully understood. Gene expression is an important mechanism underlying complex traits, and genetic variants affecting the transcript abundance are thought to influence the manifestation of an expressed phenotype. We therefore investigated the genetic background of adrenocortical gene expression by applying an adaptive linear rank test to identify genome-wide expression quantitative trait loci (eQTL) for adrenal cortex transcripts in cattle.

Results

A total of 10,986 adrenal cortex transcripts and 37,204 single nucleotide polymorphisms (SNPs) were analysed in 145 F2 cows of a Charolais × German Holstein cross. We identified 505 SNPs that were associated with the abundance of 129 transcripts, comprising 482 cis effects and 17 trans effects. These SNPs were located on all chromosomes but X, 16, 24 and 28. Associated genes are mainly involved in molecular and cellular functions comprising free radical scavenging, cellular compromise, cell morphology and lipid metabolism, including genes such as CYP27A1 and LHCGR that have been shown to affect economically important traits in cattle.

Conclusions

In this study we showed that adrenocortical eQTL affect the expression of genes known to contribute to the phenotypic manifestation in cattle. Furthermore, some of the identified genes and related molecular pathways were previously shown to contribute to the phenotypic variation of behaviour, temperament and growth at the onset of puberty in the same population investigated here. We conclude that eQTL analysis appears to be a useful approach providing insight into the molecular and genetic background of complex traits in cattle and will help to understand molecular networks involved.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-016-0442-x) contains supplementary material, which is available to authorized users.

Genome-Wide Gene/Genome Dosage Imbalance Regulates Gene Expressions in Synthetic Brassica napus and Derivatives (AC, AAC, CCA, CCAA)

Gene/genome dosage balance is an essential evolutionary mechanism for organisms to ensure a normal function, but the underlying causes of dosage-imbalance regulation remain poorly understood. Herein, the serial Brassica hybrids/polyploids (AC, AAC, CCA, CCAA) with different copies of A and C subgenomes from the same two parents of Brassica rapa and Brassica oleracea were synthesized to investigate the effects of genome dosages on gene expressions and interactions by using RNA-Seq. The expression changes of A- and C-subgenome genes were consistent with dosage alterations. Dosage-dependent and -independent genes were grouped according to the correlations between dosage variations and gene expressions. Expression levels of dosage-dependent genes were strongly correlated with dosage changes and mainly contributed to dosage effects, while those of dosage-independent genes gave weak correlations with dosage variations and mostly facilitated dosage compensation. More protein-protein interactions were detected for dosage-independent genes than dosage-dependent ones, as predicted by the dosage balance hypothesis. Dosage-dependent genes more likely impacted the expressions by trans effects, whereas dosage-independent genes preferred to play by cis effects. Furthermore, dosage-dependent genes were mainly associated with the basic biological processes to maintain the stability of the growth and development, while dosage-independent genes were more enriched in the stress response related processes to accelerate adaptation. The present comprehensive analysis of gene expression dependent/independent on dosage alterations in Brassica polyploids provided new insights into gene/genome dosage-imbalance regulation of gene expressions.

Aluminum, the genetic apparatus of the human CNS and Alzheimer's disease (AD)

The genomes of eukaryotes orchestrate their expression to ensure an effective, homeostatic and functional gene signaling program, and this includes fundamentally altered patterns of transcription during aging, development, differentiation and disease. These actions constitute an extremely complex and intricate process as genetic operations such as transcription involve the very rapid translocation and polymerization of ribonucleotides using RNA polymerases, accessory transcription protein complexes and other interrelated chromatin proteins and genetic factors. As both free ribonucleotides and polymerized single-stranded RNA chains, ribonucleotides are highly charged with phosphate, and this genetic system is extremely vulnerable to disruption by a large number of electrostatic forces, and primarily by cationic metals such as aluminum. Aluminum has been shown by independent researchers to be particularly genotoxic to the genetic apparatus, and it has become reasonably clear that aluminum disturbs genetic signaling programs in the CNS that bear a surprising resemblance to those observed in Alzheimer's disease (AD) brain. This paper will focus on a discussion of two molecular-genetic aspects of aluminum genotoxicity: (1) the observation that micro-RNA (miRNA)-mediated global gene expression patterns in aluminum-treated transgenic animal models of AD (Tg-AD) strongly resemble those found in AD; and (2) the concept of "human biochemical individuality" and the hypothesis that individuals with certain gene expression patterns may be especially sensitive and perhaps predisposed to aluminum genotoxicity.

General Assessment of Humoral Activity in Healthy Humans

The humoral immune system is network of biological molecules designed to maintain a healthy homeostatic equilibrium. Because antibodies are an abundant and highly specific effector of immunological action, they are also an important reservoir of previous host exposures. Antibodies may play a major role in early detection of host challenge. Unfortunately, few practical methods exist for interpreting the information stored in antibody variable regions. Immunosignatures use a microarray of thousands of random sequence peptides to interrogate antibodies in a broad and unbiased fashion. The pattern of binding between antibody and peptide is reproducible. Once the system has been trained on a disease cohort, blinded samples can be reliably predicted. Although immunosignatures of both chronic and infectious disease have been extensively tested, less has been done to demonstrate how healthy immunosignatures change over time or between individuals. Here, we report the results of a study of immunosignatures of healthy persons over brief (12 h sampled once per hour), intermediate (32 days sampled once per day), and long (5 years sampled once every year) time spans. Using this information, we were also able to detect intentional and unintentional immunological perturbations in the form of a vaccine and an infection, respectively. Our findings suggest that, even with the variability inherent in healthy immunosignatures, a single person's immunosignature will remain constant over time. Over this healthy signature, vaccines and infections create subsignatures that are common across multiple people, even subsuming healthy fluctuations. These findings have implications for disease monitoring and early diagnosis.

Variants in KCNJ11 and BAD do not predict response to ketogenic dietary therapies for epilepsy

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Common KCNJ11 and BAD variants were not associated with KDT response.

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There was no consistent effect of rare variants on KDT response.

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Larger cohorts may show associations from variants with effect size <3 or MAF < 0.05.

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Variants with small effect sizes are unlikely to be clinically relevant.

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Variants in other genes may influence response to KDT.

In the absence of specific metabolic disorders, predictors of response to ketogenic dietary therapies (KDT) are unknown. We aimed to determine whether variants in established candidate genes KCNJ11 and BAD influence response to KDT.

We sequenced KCNJ11 and BAD in individuals without previously-known glucose transporter type 1 deficiency syndrome or other metabolic disorders, who received KDT for epilepsy. Hospital records were used to obtain demographic and clinical data. Two response phenotypes were used: ≥50% seizure reduction and seizure-freedom at 3-month follow-up. Case/control association tests were conducted with KCNJ11 and BAD variants with minor allele frequency (MAF) > 0.01, using PLINK. Response to KDT in individuals with variants with MAF < 0.01 was evaluated.

303 Individuals had KCNJ11 and 246 individuals had BAD sequencing data and diet response data. Six SNPs in KCNJ11 and two in BAD had MAF > 0.01. Eight variants in KCNJ11 and seven in BAD (of which three were previously-unreported) had MAF < 0.01.

No significant results were obtained from association analyses, with either KDT response phenotype. P-values were similar when accounting for ethnicity using a stratified Cochran–Mantel–Haenszel test.

There did not seem to be a consistent effect of rare variants on response to KDT, although the cohort size was too small to assess significance.

Common variants in KCNJ11 and BAD do not predict response to KDT for epilepsy. We can exclude, with 80% power, association from variants with a MAF of >0.05 and effect size >3. A larger sample size is needed to detect associations from rare variants or those with smaller effect sizes.

RNA-Seq using two populations reveals genes and alleles controlling wood traits and growth in Eucalyptus nitens

Eucalyptus nitens is a perennial forest tree species grown mainly for kraft pulp production in many parts of the world. Kraft pulp yield (KPY) is a key determinant of plantation profitability and increasing the KPY of trees grown in plantations is a major breeding objective. To speed up the breeding process, molecular markers that can predict KPY are desirable. To achieve this goal, we carried out RNA-Seq studies on trees at extremes of KPY in two different trials to identify genes and alleles whose expression correlated with KPY. KPY is positively correlated with growth measured as diameter at breast height (DBH) in both trials. In total, six RNA bulks from two treatments were sequenced on an Illumina HiSeq platform. At 5% false discovery rate level, 3953 transcripts showed differential expression in the same direction in both trials; 2551 (65%) were down-regulated and 1402 (35%) were up-regulated in low KPY samples. The genes up-regulated in low KPY trees were largely involved in biotic and abiotic stress response reflecting the low growth among low KPY trees. Genes down-regulated in low KPY trees mainly belonged to gene categories involved in wood formation and growth. Differential allelic expression was observed in 2103 SNPs (in 1068 genes) and of these 640 SNPs (30%) occurred in 313 unique genes that were also differentially expressed. These SNPs may represent the cis-acting regulatory variants that influence total gene expression. In addition we also identified 196 genes which had Ka/Ks ratios greater than 1.5, suggesting that these genes are under positive selection. Candidate genes and alleles identified in this study will provide a valuable resource for future association studies aimed at identifying molecular markers for KPY and growth.

Genome-wide transcriptome study in wheat identified candidate genes related to processing quality, majority of them showing interaction (quality x development) and having temporal and spatial distributions

BACKGROUND

The cultivated bread wheat (Triticum aestivum L.) possesses unique flour quality, which can be processed into many end-use food products such as bread, pasta, chapatti (unleavened flat bread), biscuit, etc. The present wheat varieties require improvement in processing quality to meet the increasing demand of better quality food products. However, processing quality is very complex and controlled by many genes, which have not been completely explored. To identify the candidate genes whose expressions changed due to variation in processing quality and interaction (quality x development), genome-wide transcriptome studies were performed in two sets of diverse Indian wheat varieties differing for chapatti quality. It is also important to understand the temporal and spatial distributions of their expressions for designing tissue and growth specific functional genomics experiments.

RESULTS

Gene-specific two-way ANOVA analysis of expression of about 55 K transcripts in two diverse sets of Indian wheat varieties for chapatti quality at three seed developmental stages identified 236 differentially expressed probe sets (10-fold). Out of 236, 110 probe sets were identified for chapatti quality. Many processing quality related key genes such as glutenin and gliadins, puroindolines, grain softness protein, alpha and beta amylases, proteases, were identified, and many other candidate genes related to cellular and molecular functions were also identified. The ANOVA analysis revealed that the expression of 56 of 110 probe sets was involved in interaction (quality x development). Majority of the probe sets showed differential expression at early stage of seed development i.e. temporal expression. Meta-analysis revealed that the majority of the genes expressed in one or a few growth stages indicating spatial distribution of their expressions. The differential expressions of a few candidate genes such as pre-alpha/beta-gliadin and gamma gliadin were validated by RT-PCR. Therefore, this study identified several quality related key genes including many other genes, their interactions (quality x development) and temporal and spatial distributions.

CONCLUSIONS

The candidate genes identified for processing quality and information on temporal and spatial distributions of their expressions would be useful for designing wheat improvement programs for processing quality either by changing their expression or development of single nucleotide polymorphisms (SNPs) markers.

Additive, epistatic, and environmental effects through the lens of expression variability QTL in a twin cohort

The expression of a gene can vary across individuals in the general population, as well as between monozygotic twins. This variable expression is assumed to be due to the influence of both genetic and nongenetic factors. Yet little evidence supporting this assumption has been obtained from empirical data. In this study, we used expression data from a large twin cohort to investigate the influences of genetic and nongenetic factors on variable gene expression. We focused on a set of expression variability QTL (evQTL)--i.e., genetic loci associated with the variance, as opposed to the mean, of gene expression. We identified evQTL for 99, 56, and 79 genes in lymphoblastoid cell lines, skin, and fat, respectively. The differences in gene expression, measured by the relative mean difference (RMD), tended to be larger between pairs of dizygotic (DZ) twins than between pairs of monozygotic (MZ) twins, showing that genetic background influenced the expression variability. Furthermore, a more profound RMD was observed between pairs of MZ twins whose genotypes were associated with greater expression variability than the RMD found between pairs of MZ twins whose genotypes were associated with smaller expression variability. This suggests that nongenetic (e.g., environmental) factors contribute to the variable expression. Lastly, we demonstrated that the formation of evQTL is likely due to partial linkages between eQTL SNPs that are additively associated with the mean of gene expression; in most cases, no epistatic effect is involved. Our findings have implications for understanding divergent sources of gene expression variability.

Differential adaptation to multi-stressed conditions of wine fermentation revealed by variations in yeast regulatory networks

BACKGROUND

Variation of gene expression can lead to phenotypic variation and have therefore been assumed to contribute the diversity of wine yeast (Saccharomyces cerevisiae) properties. However, the molecular bases of this variation of gene expression are unknown. We addressed these questions by carrying out an integrated genetical-genomic study in fermentation conditions. We report here quantitative trait loci (QTL) mapping based on expression profiling in a segregating population generated by a cross between a derivative of the popular wine strain EC1118 and the laboratory strain S288c.

RESULTS

Most of the fermentation traits studied appeared to be under multi-allelic control. We mapped five phenotypic QTLs and 1465 expression QTLs. Several expression QTLs overlapped in hotspots. Among the linkages unraveled here, several were associated with metabolic processes essential for wine fermentation such as glucose sensing or nitrogen and vitamin metabolism. Variations affecting the regulation of drug detoxification and export (TPO1, PDR12 or QDR2) were linked to variation in four genes encoding transcription factors (PDR8, WAR1, YRR1 and HAP1). We demonstrated that the allelic variation of WAR1 and TPO1 affected sorbic and octanoic acid resistance, respectively. Moreover, analysis of the transcription factors phylogeny suggests they evolved with a specific adaptation of the strains to wine fermentation conditions. Unexpectedly, we found that the variation of fermentation rates was associated with a partial disomy of chromosome 16. This disomy resulted from the well known 8-16 translocation.

CONCLUSIONS

This large data set made it possible to decipher the effects of genetic variation on gene expression during fermentation and certain wine fermentation properties. Our findings shed a new light on the adaptation mechanisms required by yeast to cope with the multiple stresses generated by wine fermentation. In this context, the detoxification and export systems appear to be of particular importance, probably due to nitrogen starvation. Furthermore, we show that the well characterized 8-16 translocation located in SSU1, which is associated with sulfite resistance, can lead to a partial chromosomic amplification in the progeny of strains that carry it, greatly improving fermentation kinetics. This amplification has been detected among other wine yeasts.

Where genotype is not predictive of phenotype: towards an understanding of the molecular basis of reduced penetrance in human inherited disease

Some individuals with a particular disease-causing mutation or genotype fail to express most if not all features of the disease in question, a phenomenon that is known as 'reduced (or incomplete) penetrance'. Reduced penetrance is not uncommon; indeed, there are many known examples of 'disease-causing mutations' that fail to cause disease in at least a proportion of the individuals who carry them. Reduced penetrance may therefore explain not only why genetic diseases are occasionally transmitted through unaffected parents, but also why healthy individuals can harbour quite large numbers of potentially disadvantageous variants in their genomes without suffering any obvious ill effects. Reduced penetrance can be a function of the specific mutation(s) involved or of allele dosage. It may also result from differential allelic expression, copy number variation or the modulating influence of additional genetic variants in cis or in trans. The penetrance of some pathogenic genotypes is known to be age- and/or sex-dependent. Variable penetrance may also reflect the action of unlinked modifier genes, epigenetic changes or environmental factors. At least in some cases, complete penetrance appears to require the presence of one or more genetic variants at other loci. In this review, we summarize the evidence for reduced penetrance being a widespread phenomenon in human genetics and explore some of the molecular mechanisms that may help to explain this enigmatic characteristic of human inherited disease.

Bovine TB in livestock and wildlife: what's in the genes?

Bovine tuberculosis (BTB) is a chronic, infectious disease found in domestic livestock and wildlife. It is caused predominantly by Mycobacterium bovis, which forms part of the Mycobacterium tuberculosis complex. BTB has serious implications for the movement of animals and animal products, biodiversity, and public health and is of significant economic concern. The existence of wildlife maintenance hosts makes it extremely difficult to eradicate BTB, even when established control strategies are in place, creating the need for alternative methods for controlling this disease. There are multiple factors that influence the outcome of infection by a pathogen, one of which is the host's genome. The identification of genetic variants involved in the susceptibility to BTB would supply a new selection of potential drug targets as well as the possibility for the breeding of animals with greater disease resistance. In this review, we collate the results of the BTB heritability and association studies performed in cattle and wildlife, discuss considerations and other methodologies (such as gene expression work) to be taken into account when performing genetic studies, and make some recommendations for future work in this area.

Detection and impact of rare regulatory variants in human disease

Advances in genome sequencing are providing unprecedented resolution of rare and private variants. However, methods which assess the effect of these variants have relied predominantly on information within coding sequences. Assessing their impact in non-coding sequences remains a significant contemporary challenge. In this review, we highlight the role of regulatory variation as causative agents and modifiers of monogenic disorders. We further discuss how advances in functional genomics are now providing new opportunity to assess the impact of rare non-coding variants and their role in disease.