Genome Biology最新文献

Background: Mouse models have allowed for the direct interrogation of genetic effects on molecular, physiological, and behavioral brain phenotypes. However, it is unknown to what extent neurological or psychiatric traits may be human- or primate-specific and therefore which components can be faithfully recapitulated in mouse models.

Results: We compare conservation of co-expression in 116 independent data sets derived from human, mouse, and non-human primate representing more than 15,000 total samples. We observe greater changes occurring on the human lineage than mouse, and substantial regional variation that highlights cerebral cortex as the most diverged region. Glia, notably microglia, astrocytes, and oligodendrocytes are the most divergent cell type, three times more on average than neurons. We show that cis-regulatory sequence divergence explains a significant fraction of co-expression divergence. Moreover, protein coding sequence constraint parallels co-expression conservation, such that genes with loss of function intolerance are enriched in neuronal, rather than glial modules. We identify dozens of human neuropsychiatric and neurodegenerative disease risk genes, such as COMT, PSEN-1, LRRK2, SHANK3, and SNCA, with highly divergent co-expression between mouse and human and show that 3D human brain organoids recapitulate in vivo co-expression modules representing several human cell types.

Conclusions: We identify robust co-expression modules reflecting whole-brain and regional patterns of gene expression. Compared with those that represent basic metabolic processes, cell-type-specific modules, most prominently glial modules, are the most divergent between species. These data and analyses serve as a foundational resource to guide human disease modeling and its interpretation.

Background: Whole-exome sequencing (WES) has been successful in identifying genes that cause familial Parkinson's disease (PD). However, until now this approach has not been deployed to study large cohorts of unrelated participants. To discover rare PD susceptibility variants, we performed WES in 1148 unrelated cases and 503 control participants. Candidate genes were subsequently validated for functions relevant to PD based on parallel RNA-interference (RNAi) screens in human cell culture and Drosophila and C. elegans models.

Results: Assuming autosomal recessive inheritance, we identify 27 genes that have homozygous or compound heterozygous loss-of-function variants in PD cases. Definitive replication and confirmation of these findings were hindered by potential heterogeneity and by the rarity of the implicated alleles. We therefore looked for potential genetic interactions with established PD mechanisms. Following RNAi-mediated knockdown, 15 of the genes modulated mitochondrial dynamics in human neuronal cultures and four candidates enhanced α-synuclein-induced neurodegeneration in Drosophila. Based on complementary analyses in independent human datasets, five functionally validated genes-GPATCH2L, UHRF1BP1L, PTPRH, ARSB, and VPS13C-also showed evidence consistent with genetic replication.

Conclusions: By integrating human genetic and functional evidence, we identify several PD susceptibility gene candidates for further investigation. Our approach highlights a powerful experimental strategy with broad applicability for future studies of disorders with complex genetic etiologies.

Background: Organophosphates are the most frequently and largely applied insecticide in the world due to their biodegradable nature. Gut microbes were shown to degrade organophosphates and cause intestinal dysfunction. The diabetogenic nature of organophosphates was recently reported but the underlying molecular mechanism is unclear. We aimed to understand the role of gut microbiota in organophosphate-induced hyperglycemia and to unravel the molecular mechanism behind this process.

Results: Here we demonstrate a high prevalence of diabetes among people directly exposed to organophosphates in rural India (n = 3080). Correlation and linear regression analysis reveal a strong association between plasma organophosphate residues and HbA1c but no association with acetylcholine esterase was noticed. Chronic treatment of mice with organophosphate for 180 days confirms the induction of glucose intolerance with no significant change in acetylcholine esterase. Further fecal transplantation and culture transplantation experiments confirm the involvement of gut microbiota in organophosphate-induced glucose intolerance. Intestinal metatranscriptomic and host metabolomic analyses reveal that gut microbial organophosphate degradation produces short chain fatty acids like acetic acid, which induces gluconeogenesis and thereby accounts for glucose intolerance. Plasma organophosphate residues are positively correlated with fecal esterase activity and acetate level of human diabetes.

Conclusion: Collectively, our results implicate gluconeogenesis as the key mechanism behind organophosphate-induced hyperglycemia, mediated by the organophosphate-degrading potential of gut microbiota. This study reveals the gut microbiome-mediated diabetogenic nature of organophosphates and hence that the usage of these insecticides should be reconsidered.

Background: Recent work has identified and mapped a range of posttranscriptional modifications in mRNA, including methylation of the N6 and N1 positions in adenine, pseudouridylation, and methylation of carbon 5 in cytosine (m5C). However, knowledge about the prevalence and transcriptome-wide distribution of m5C is still extremely limited; thus, studies in different cell types, tissues, and organisms are needed to gain insight into possible functions of this modification and implications for other regulatory processes.

Results: We have carried out an unbiased global analysis of m5C in total and nuclear poly(A) RNA of mouse embryonic stem cells and murine brain. We show that there are intriguing differences in these samples and cell compartments with respect to the degree of methylation, functional classification of methylated transcripts, and position bias within the transcript. Specifically, we observe a pronounced accumulation of m5C sites in the vicinity of the translational start codon, depletion in coding sequences, and mixed patterns of enrichment in the 3' UTR. Degree and pattern of methylation distinguish transcripts modified in both embryonic stem cells and brain from those methylated in either one of the samples. We also analyze potential correlations between m5C and micro RNA target sites, binding sites of RNA binding proteins, and N6-methyladenosine.

Conclusion: Our study presents the first comprehensive picture of cytosine methylation in the epitranscriptome of pluripotent and differentiated stages in the mouse. These data provide an invaluable resource for future studies of function and biological significance of m5C in mRNA in mammals.

Many genomic techniques have been developed to study gene essentiality genome-wide, such as CRISPR and shRNA screens. Our analyses of public CRISPR screens suggest protein interaction networks, when integrated with gene expression or histone marks, are highly predictive of gene essentiality. Meanwhile, the quality of CRISPR and shRNA screen results can be significantly enhanced through network neighbor information. We also found network neighbor information to be very informative on prioritizing ChIP-seq target genes and survival indicator genes from tumor profiling. Thus, our study provides a general method for gene essentiality analysis in functional genomic experiments ( http://nest.dfci.harvard.edu ).

The first genome sequence of the extinct European wild aurochs reveals the genetic foundation of native British and Irish landraces of cattle.See related Research article: www.dx.doi.org/10.1186/s13059-015-0790-2.

The chromatin interaction assays 5C and HiC have advanced our understanding of genomic spatial organization, but analysis approaches for these data are limited by usability and flexibility. The HiFive tool suite provides efficient data handling and a variety of normalization approaches for easy, fast analysis and method comparison. Integration of MPI-based parallelization allows scalability and rapid processing time. In addition to single-command analysis of an entire experiment from mapped reads to interaction values, HiFive has been integrated into the open-source, web-based platform Galaxy to connect users with computational resources and a graphical interface. HiFive is open-source software available from http://taylorlab.org/software/hifive/ .

Background: Pre-mRNA splicing occurs mainly co-transcriptionally, and both nucleosome density and histone modifications have been proposed to play a role in splice site recognition and regulation. However, the extent and mechanisms behind this interplay remain poorly understood.

Results: We use transcriptomic and epigenomic data generated by the ENCODE project to investigate the association between chromatin structure and alternative splicing. We find a strong and significant positive association between H3K9ac, H3K27ac, H3K4me3, epigenetic marks characteristic of active promoters, and exon inclusion in a small but well-defined class of exons, representing approximately 4 % of all regulated exons. These exons are systematically maintained at comparatively low levels of inclusion across cell types, but their inclusion is significantly enhanced in particular cell types when in physical proximity to active promoters.

Conclusion: Histone modifications and other chromatin features that activate transcription can be co-opted to participate in the regulation of the splicing of exons that are in physical proximity to promoter regions.

Mapping reads to a genome remains challenging, especially for non-model organisms with lower quality assemblies, or for organisms with higher mutation rates. While most research has focused on speeding up the mapping process, little attention has been paid to optimize the choice of mapper and parameters for a user's dataset. Here, we present Teaser, a software that assists in these choices through rapid automated benchmarking of different mappers and parameter settings for individualized data. Within minutes, Teaser completes a quantitative evaluation of an ensemble of mapping algorithms and parameters. We use Teaser to demonstrate how Bowtie2 can be optimized for different data.