Current status and new features of the Consensus Coding Sequence database

HuR controls glutaminase RNA metabolism

Glutaminase (GLS) is directly related to cell growth and tumor progression, making it a target for cancer treatment. The RNA-binding protein HuR (encoded by the ELAVL1 gene) influences mRNA stability and alternative splicing. Overexpression of ELAVL1 is common in several cancers, including breast cancer. Here we show that HuR regulates GLS mRNA alternative splicing and isoform translation/stability in breast cancer. Elevated ELAVL1 expression correlates with high levels of the glutaminase isoforms C (GAC) and kidney-type (KGA), which are associated with poor patient prognosis. Knocking down ELAVL1 reduces KGA and increases GAC levels, enhances glutamine anaplerosis into the TCA cycle, and drives cells towards glutamine dependence. Furthermore, we show that combining chemical inhibition of GLS with ELAVL1 silencing synergistically decreases breast cancer cell growth and invasion. These findings suggest that dual inhibition of GLS and HuR offers a therapeutic strategy for breast cancer treatment.

A newly identified gene Ahed plays essential roles in murine haematopoiesis

The development of haematopoiesis involves the coordinated action of numerous genes, some of which are implicated in haematological malignancies. However, the biological function of many genes remains elusive and unknown functional genes are likely to remain to be uncovered. Here, we report a previously uncharacterised gene in haematopoiesis, identified by screening mutant embryonic stem cells. The gene, 'attenuated haematopoietic development (Ahed)', encodes a nuclear protein. Conditional knockout (cKO) of Ahed results in anaemia from embryonic day 14.5 onward, leading to prenatal demise. Transplantation experiments demonstrate the incapacity of Ahed-deficient haematopoietic cells to reconstitute haematopoiesis in vivo. Employing a tamoxifen-inducible cKO model, we further reveal that Ahed deletion impairs the intrinsic capacity of haematopoietic cells in adult mice. Ahed deletion affects various pathways, and published databases present cancer patients with somatic mutations in Ahed. Collectively, our findings underscore the fundamental roles of Ahed in lifelong haematopoiesis, implicating its association with malignancies.

Recurring EPHB1 mutations in human cancers alter receptor signalling and compartmentalisation of colorectal cancer cells

BACKGROUND

Ephrin (EPH) receptors have been implicated in tumorigenesis and metastasis, but the functional understanding of mutations observed in human cancers is limited. We previously demonstrated reduced cell compartmentalisation for somatic EPHB1 mutations found in metastatic colorectal cancer cases. We therefore integrated pan-cancer and pan-EPH mutational data to prioritise recurrent EPHB1 mutations for functional studies to understand their contribution to cancer development and metastasis.

METHODS

Here, 79,151 somatic mutations in 9,898 samples of 33 different tumour types were analysed with a bioinformatic pipeline to find 3D-mutated cluster pairs and hotspot mutations in EPH receptors. From these, 15 recurring EPHB1 mutations were stably expressed in colorectal cancer followed by confocal microscopy based in vitro compartmentalisation assays and phospho-proteome analysis.

RESULTS

The 3D-protein structure-based bioinformatics analysis resulted in 63% EPHB1 mutants with compartmentalisation phenotypes vs 43% for hotspot mutations. Whereas the ligand-binding domain mutations C61Y, R90C, and R170W, the fibronectin domain mutation R351L, and the kinase domain mutation D762N displayed reduced to strongly compromised cell compartmentalisation, the kinase domain mutations R743W and G821R enhanced this phenotype. While mutants with reduced compartmentalisation also had reduced ligand induced receptor phosphorylation, the enhanced compartmentalisation was not linked to receptor phosphorylation level. Phosphoproteome mapping pinpointed the PI3K pathway and PIK3C2B phosphorylation in cells harbouring mutants with reduced compartmentalisation.

CONCLUSIONS

This is the first integrative study of pan-cancer EPH receptor mutations followed by in vitro validation, a robust way to identify cancer-causing mutations, uncovering EPHB1 mutation phenotypes and demonstrating the utility of protein structure-based mutation analysis in characterization of novel cancer genes. Video Abstract.

Constructing and interpreting a large-scale variant effect map for an ultrarare disease gene: Comprehensive prediction of the functional impact of PSAT1 genotypes

Reduced activity of the enzymes encoded by PHGDH, PSAT1, and PSPH causes a set of ultrarare, autosomal recessive diseases known as serine biosynthesis defects. These diseases present in a broad phenotypic spectrum: at the severe end is Neu-Laxova syndrome, in the intermediate range are infantile serine biosynthesis defects with severe neurological manifestations and growth deficiency, and at the mild end is childhood disease with intellectual disability. However, L-serine supplementation, especially if started early, can ameliorate and in some cases even prevent symptoms. Therefore, knowledge of pathogenic variants can improve clinical outcomes. Here, we use a yeast-based assay to individually measure the functional impact of 1,914 SNV-accessible amino acid substitutions in PSAT. Results of our assay agree well with clinical interpretations and protein structure-function relationships, supporting the inclusion of our data as functional evidence as part of the ACMG variant interpretation guidelines. We use existing ClinVar variants, disease alleles reported in the literature and variants present as homozygotes in the primAD database to define assay ranges that could aid clinical variant interpretation for up to 98% of the tested variants. In addition to measuring the functional impact of individual variants in yeast haploid cells, we also assay pairwise combinations of PSAT1 alleles that recapitulate human genotypes, including compound heterozygotes, in yeast diploids. Results from our diploid assay successfully distinguish the genotypes of affected individuals from those of healthy carriers and agree well with disease severity. Finally, we present a linear model that uses individual allele measurements to predict the biallelic function of ~1.8 million allele combinations corresponding to potential human genotypes. Taken together, our work provides an example of how large-scale functional assays in model systems can be powerfully applied to the study of ultrarare diseases.

Recovering false negatives in CRISPR fitness screens with JLOE

It is widely accepted that pooled library CRISPR knockout screens offer greater sensitivity and specificity than prior technologies in detecting genes whose disruption leads to fitness defects, a critical step in identifying candidate cancer targets. However, the assumption that CRISPR screens are saturating has been largely untested. Through integrated analysis of screen data in cancer cell lines generated by the Cancer Dependency Map, we show that a typical CRISPR screen has a ∼20% false negative rate, in addition to library-specific false negatives. Replicability falls sharply as gene expression decreases, while cancer subtype-specific genes within a tissue show distinct profiles compared to false negatives. Cumulative analyses across tissues improves our understanding of core essential genes and suggest only a small number of lineage-specific essential genes, enriched for transcription factors that define pathways of tissue differentiation. To recover false negatives, we introduce a method, Joint Log Odds of Essentiality (JLOE), which builds on our prior work with BAGEL to selectively rescue the false negatives without an increased false discovery rate.

Predicting the functional effect of compound heterozygous genotypes from large scale variant effect maps

Background

Pathogenic variants in PHGDH, PSAT1 , and PSPH cause a set of rare, autosomal recessive diseases known as serine biosynthesis defects. Serine biosynthesis defects present in a broad phenotypic spectrum that includes, at the severe end, Neu-Laxova syndrome, a lethal multiple congenital anomaly disease, intermediately in the form of infantile serine biosynthesis defects with severe neurological manifestations and growth deficiency, and at the mild end, as childhood disease with intellectual disability. However, because L-serine supplementation, especially if started early, can ameliorate and in some cases even prevent symptoms, knowledge of pathogenic variants is highly actionable.

Methods

Recently, our laboratory established a yeast-based assay for human PSAT1 function. We have now applied it at scale to assay the functional impact of 1,914 SNV-accessible amino acid substitutions. In addition to assaying the functional impact of individual variants in yeast haploid cells, we can assay pairwise combinations of PSAT1 alleles that recapitulate human genotypes, including compound heterozygotes, in yeast diploids.

Results

Results of our assays of individual variants (in haploid yeast cells) agree well with clinical interpretations and protein structure-function relationships, supporting the use of our data as functional evidence under the ACMG interpretation guidelines. Results from our diploid assay successfully distinguish patient genotypes from those of healthy carriers and agree well with disease severity. Finally, we present a linear model that uses individual allele measurements (in haploid yeast cells) to accurately predict the biallelic function (in diploid yeast cells) of ~ 1.8 million allele combinations corresponding to potential human genotypes.

Conclusions

Taken together, our work provides an example of how large-scale functional assays in model systems can be powerfully applied to the study of a rare disease.

Identifying genes with conserved splicing structure and orthologous isoforms in human, mouse and dog

BACKGROUND

In eukaryote transcriptomes, a significant amount of transcript diversity comes from genes' capacity to generate different transcripts through alternative splicing. Identifying orthologous alternative transcripts across multiple species is of particular interest for genome annotators. However, there is no formal definition of transcript orthology based on the splicing structure conservation. Likewise there is no public dataset benchmark providing groups of orthologous transcripts sharing a conserved splicing structure.

RESULTS

We introduced a formal definition of splicing structure orthology and we predicted transcript orthologs in human, mouse and dog. Applying a selective strategy, we analyzed 2,167 genes and their 18,109 known transcripts and identified a set of 253 gene orthologs that shared a conserved splicing structure in all three species. We predicted 6,861 transcript CDSs (coding sequence), mainly for dog, an emergent model species. Each predicted transcript was an ortholog of a known transcript: both share the same CDS splicing structure. Evidence for the existence of the predicted CDSs was found in external data.

CONCLUSIONS

We generated a dataset of 253 gene triplets, structurally conserved and sharing all their CDSs in human, mouse and dog, which correspond to 879 triplets of spliced CDS orthologs. We have released the dataset both as an SQL database and as tabulated files. The data consists of the 879 CDS orthology groups with their detailed splicing structures, and the predicted CDSs, associated with their experimental evidence. The 6,861 predicted CDSs are provided in GTF files. Our data may contribute to compare highly conserved genes across three species, for comparative transcriptomics at the isoform level, or for benchmarking splice aligners and methods focusing on the identification of splicing orthologs. The data is available at https://data-access.cesgo.org/index.php/s/V97GXxOS66NqTkZ .

Exploration of databases and methods supporting drug repurposing: a comprehensive survey

Drug development involves a deep understanding of the mechanisms of action and possible side effects of each drug, and sometimes results in the identification of new and unexpected uses for drugs, termed as drug repurposing. Both in case of serendipitous observations and systematic mechanistic explorations, confirmation of new indications for a drug requires hypothesis building around relevant drug-related data, such as molecular targets involved, and patient and cellular responses. These datasets are available in public repositories, but apart from sifting through the sheer amount of data imposing computational bottleneck, a major challenge is the difficulty in selecting which databases to use from an increasingly large number of available databases. The database selection is made harder by the lack of an overview of the types of data offered in each database. In order to alleviate these problems and to guide the end user through the drug repurposing efforts, we provide here a survey of 102 of the most promising and drug-relevant databases reported to date. We summarize the target coverage and types of data available in each database and provide several examples of how multi-database exploration can facilitate drug repurposing.

Genome-wide transcriptome study using deep RNA sequencing for myocardial infarction and coronary artery calcification

Background

Coronary artery calcification (CAC) is a noninvasive measure of coronary atherosclerosis, the proximal pathophysiology underlying most cases of myocardial infarction (MI). We sought to identify expression signatures of early MI and subclinical atherosclerosis in the Framingham Heart Study (FHS). In this study, we conducted paired-end RNA sequencing on whole blood collected from 198 FHS participants (55 with a history of early MI, 72 with high CAC without prior MI, and 71 controls free of elevated CAC levels or history of MI). We applied DESeq2 to identify coding-genes and long intergenic noncoding RNAs (lincRNAs) differentially expressed in MI and high CAC, respectively, compared with the control.

Results

On average, 150 million paired-end reads were obtained for each sample. At the false discovery rate (FDR) < 0.1, we found 68 coding genes and 2 lincRNAs that were differentially expressed in early MI versus controls. Among them, 60 coding genes were detectable and thus tested in an independent RNA-Seq data of 807 individuals from the Rotterdam Study, and 8 genes were supported by p value and direction of the effect. Immune response, lipid metabolic process, and interferon regulatory factor were enriched in these 68 genes. By contrast, only 3 coding genes and 1 lincRNA were differentially expressed in high CAC versus controls. APOD, encoding a component of high-density lipoprotein, was significantly downregulated in both early MI (FDR = 0.007) and high CAC (FDR = 0.01) compared with controls.

Conclusions

We identified transcriptomic signatures of early MI that include differentially expressed protein-coding genes and lincRNAs, suggesting important roles for protein-coding genes and lincRNAs in the pathogenesis of MI.

LincRNA-immunity landscape analysis identifies EPIC1 as a regulator of tumor immune evasion and immunotherapy resistance

Through an integrative analysis of the lincRNA expression and tumor immune response in 9,626 tumor samples across 32 cancer types, we developed a lincRNA-based immune response (LIMER) score that can predict the immune cells infiltration and patient prognosis in multiple cancer types. Our analysis also identified tumor-specific lincRNAs, including EPIC1, that potentially regulate tumor immune response in multiple cancer types. Immunocompetent mouse models and in vitro co-culture assays demonstrated that EPIC1 induces tumor immune evasion and resistance to immunotherapy by suppressing tumor cell antigen presentation. Mechanistically, lincRNA EPIC1 interacts with the histone methyltransferase EZH2, leading to the epigenetic silencing of IFNGR1, TAP1/2, ERAP1/2, and MHC-I genes. Genetic and pharmacological inhibition of EZH2 abolish EPIC1's immune-related oncogenic effect and its suppression of interferon-γ signaling. The EPIC1-EZH2 axis emerges as a potential mechanism for tumor immune evasion that can serve as therapeutic targets for immunotherapy.

Identifying Discriminative Biological Function Features and Rules for Cancer-Related Long Non-coding RNAs

Cancer has been a major public health problem worldwide for many centuries. Cancer is a complex disease associated with accumulative genetic mutations, epigenetic aberrations, chromosomal instability, and expression alteration. Increasing lines of evidence suggest that many non-coding transcripts, which are termed as non-coding RNAs, have important regulatory roles in cancer. In particular, long non-coding RNAs (lncRNAs) play crucial roles in tumorigenesis. Cancer-related lncRNAs serve as oncogenic factors or tumor suppressors. Although many lncRNAs are identified as potential regulators in tumorigenesis by using traditional experimental methods, they are time consuming and expensive considering the tremendous amount of lncRNAs needed. Thus, effective and fast approaches to recognize tumor-related lncRNAs should be developed. The proposed approach should help us understand not only the mechanisms of lncRNAs that participate in tumorigenesis but also their satisfactory performance in distinguishing cancer-related lncRNAs. In this study, we utilized a decision tree (DT), a type of rule learning algorithm, to investigate cancer-related lncRNAs with functional annotation contents [gene ontology (GO) terms and KEGG pathways] of their co-expressed genes. Cancer-related and other lncRNAs encoded by the key enrichment features of GO and KEGG filtered by feature selection methods were used to build an informative DT, which further induced several decision rules. The rules provided not only a new tool for identifying cancer-related lncRNAs but also connected the lncRNAs and cancers with the combinations of GO terms. Results provided new directions for understanding cancer-related lncRNAs.

Development and Validation of an RNA Sequencing Assay for Gene Fusion Detection in Formalin-Fixed, Paraffin-Embedded Tumors

RNA sequencing (RNA-seq) is a well-validated tool for detecting gene fusions in fresh-frozen tumors; however, RNA-seq is much more challenging to use with formalin-fixed, paraffin-embedded (FFPE) tumor samples. We evaluated the performance of RNA-seq to detect gene fusions in clinical FFPE tumor samples. Our assay identified all 15 spiked-in NTRK fusions from RNA reference material and six known fusions from five cancer cell lines. Limit of detection for the assay was assessed with a series of dilutions of RNA from the cell line H2228. These fusions can be detected when the dilution is down to 10%. Good intra-assay and interassay reproducibility was observed in three specimens. For clinical validation, the assay detected 10 of 12 fusions initially identified by a DNA panel (covering 23 gene fusions) in clinical specimens (83.3% sensitivity), whereas one fusion (MET fusion) was identified in another 34 fusion-negative tumor specimens as determined by the DNA panel (negative prediction value of 94.3%). This MET fusion was confirmed by RT-PCR and Sanger sequencing, which found that this is a false-negative result for the DNA panel. The assay also identified 26 extra fusions not covered by the DNA panel, 20 (76.9%) of which were validated by RT-PCR and Sanger sequencing. Therefore, this RNA assay has reasonable performance and could complement DNA-based next-generation sequencing assays.

Multiplex enCas12a screens detect functional buffering among paralogs otherwise masked in monogenic Cas9 knockout screens

BACKGROUND

Pooled library CRISPR/Cas9 knockout screening across hundreds of cell lines has identified genes whose disruption leads to fitness defects, a critical step in identifying candidate cancer targets. However, the number of essential genes detected from these monogenic knockout screens is low compared to the number of constitutively expressed genes in a cell.

RESULTS

Through a systematic analysis of screen data in cancer cell lines generated by the Cancer Dependency Map, we observe that half of all constitutively expressed genes are never detected in any CRISPR screen and that these never-essentials are highly enriched for paralogs. We investigated functional buffering among approximately 400 candidate paralog pairs using CRISPR/enCas12a dual-gene knockout screening in three cell lines. We observe 24 synthetic lethal paralog pairs that have escaped detection by monogenic knockout screens at stringent thresholds. Nineteen of 24 (79%) synthetic lethal interactions are present in at least two out of three cell lines and 14 of 24 (58%) are present in all three cell lines tested, including alternate subunits of stable protein complexes as well as functionally redundant enzymes.

CONCLUSIONS

Together, these observations strongly suggest that functionally redundant paralogs represent a targetable set of genetic dependencies that are systematically under-represented among cell-essential genes in monogenic CRISPR-based loss of function screens.

Whole-exome sequencing of a large Chinese azoospermia and severe oligospermia cohort identifies novel infertility causative variants and genes

Rare coding variants have been proven to be one of the significant factors contributing to spermatogenic failure in patients with non-obstructive azoospermia (NOA) and severe oligospermia (SO). To delineate the molecular characteristics of idiopathic NOA and SO, we performed whole-exome sequencing of 314 unrelated patients of Chinese Han origin and verified our findings by comparing to 400 fertile controls. We detected six pathogenic/likely pathogenic variants and four variants of unknown significance, in genes known to cause NOA/SO, and 9 of which had not been earlier reported. Additionally, we identified 20 novel NOA candidate genes affecting 25 patients. Among them, five (BRDT, CHD5, MCM9, MLH3 and ZFX) were considered as strong candidates based on the evidence obtained from murine functional studies and human single-cell (sc)RNA-sequencing data. These genetic findings provide insight into the aetiology of human NOA/SO and pave the way for further functional analysis and molecular diagnosis of male infertility.

Alternative Splicing of the SLCO1B1 Gene: An Exploratory Analysis of Isoform Diversity in Pediatric Liver

The hepatic influx transporter OATP1B1 (SLCO1B1) plays an important role in the disposition of endogenous substrates and drugs prescribed to children. Alternative splicing increases the diversity of protein products from > 90% of human genes and may be triggered by developmental signals. As concentrations of several endogenous OATP1B1 substrates change during growth and development, with this exploratory study we investigated age-dependent alternative splicing of SLCO1B1 mRNA in 97 postmortem livers (fetus-adolescents). Twenty-seven splice variants were detected; 10 were confirmed by additional bioinformatic analyses and verified by quantitative polymerase chain reaction, and selected for detailed analysis based on relative abundance, association with age, and overlap with an adjacent gene. Two splice variants code for reference OATP1B1 protein, and eight code for truncated proteins. The expression of eight isoforms was associated with age. We conclude that alternative splicing of SLCO1B1 occurs frequently in children; although the functional consequences remain unknown, the data raise the possibility of a regulatory role for alternative splicing in mediating developmental changes in drug disposition.

Formation of human long intergenic non-coding RNA genes, pseudogenes, and protein genes: Ancestral sequences are key players

Pathways leading to formation of non-coding RNA and protein genes are varied and complex. We report finding a conserved repeat sequence present in human and chimpanzee genomes that appears to have originated from a common primate ancestor. This sequence is repeatedly copied in human chromosome 22 (chr22) low copy repeats (LCR22) or segmental duplications and forms twenty-one different genes, which include the human long intergenic non-coding RNA (lincRNA) family FAM230, a newly discovered lincRNA gene family termed conserved long intergenic non-coding RNAs (clincRNA), pseudogene families, as well as the gamma-glutamyltransferase (GGT) protein gene family and the RNA pseudogenes that originate from GGT sequences. Of particular interest are the GGT5 and USP18 protein genes that appear to have formed from an homologous repeat sequence that also forms the clincRNA gene family. The data point to ancestral DNA sequences, conserved through evolution and duplicated in humans by chromosomal repeat sequences that may serve as functional genomic elements in the development of diverse genes.

Gene family information facilitates variant interpretation and identification of disease-associated genes in neurodevelopmental disorders

BACKGROUND

Classifying pathogenicity of missense variants represents a major challenge in clinical practice during the diagnoses of rare and genetic heterogeneous neurodevelopmental disorders (NDDs). While orthologous gene conservation is commonly employed in variant annotation, approximately 80% of known disease-associated genes belong to gene families. The use of gene family information for disease gene discovery and variant interpretation has not yet been investigated on a genome-wide scale. We empirically evaluate whether paralog-conserved or non-conserved sites in human gene families are important in NDDs.

METHODS

Gene family information was collected from Ensembl. Paralog-conserved sites were defined based on paralog sequence alignments; 10,068 NDD patients and 2078 controls were statistically evaluated for de novo variant burden in gene families.

RESULTS

We demonstrate that disease-associated missense variants are enriched at paralog-conserved sites across all disease groups and inheritance models tested. We developed a gene family de novo enrichment framework that identified 43 exome-wide enriched gene families including 98 de novo variant carrying genes in NDD patients of which 28 represent novel candidate genes for NDD which are brain expressed and under evolutionary constraint.

CONCLUSION

This study represents the first method to incorporate gene family information into a statistical framework to interpret variant data for NDDs and to discover new NDD-associated genes.

Complete Profiling of Methyl-CpG-Binding Domains for Combinations of Cytosine Modifications at CpG Dinucleotides Reveals Differential Read-out in Normal and Rett-Associated States

5-Methylcytosine (mC) exists in CpG dinucleotides of mammalian DNA and plays key roles in chromatin regulation during development and disease. As a main regulatory pathway, fully methylated CpG are recognized by methyl-CpG-binding domain (MBD) proteins that act in concert with chromatin remodelers, histone deacetylases and methyltransferases to trigger transcriptional downregulation. In turn, MBD mutations can alter CpG binding, and in case of the MBD protein MeCP2 can cause the neurological disorder Rett syndrome (RTT). An additional layer of complexity in CpG recognition is added by ten-eleven-translocation (TET) dioxygenases that oxidize mC to 5-hydroxymethyl-, 5-formyl- and 5-carboxylcytosine, giving rise to fifteen possible combinations of cytosine modifications in the two CpG strands. We report a comprehensive, comparative interaction analysis of the human MBD proteins MeCP2, MBD1, MBD2, MBD3, and MBD4 with all CpG combinations and observe individual preferences of each MBD for distinct combinations. In addition, we profile four MeCP2 RTT mutants and reveal that although interactions to methylated CpGs are similarly affected by the mutations, interactions to oxidized mC combinations are differentially affected. These findings argue for a complex interplay between local TET activity/processivity and CpG recognition by MBDs, with potential consequences for the transcriptional landscape in normal and RTT states.

Quality of whole genome sequencing from blood versus saliva derived DNA in cardiac patients

Background

Whole-genome sequencing (WGS) is becoming an increasingly important tool for detecting genomic variation. Blood derived DNA is the current standard for WGS for research or clinical purposes but may not always be feasible to acquire. The usability of DNA from saliva for WGS is not known. We compared the quality of WGS between blood versus saliva derived DNA.

Methods

WGS was performed in DNA from 531 blood and 502 saliva samples (including 5 paired samples) from participants enrolled in a heart disease biorepository. We compared the proportion of sequencing reads that mapped to non-human sources (microbiome), the sequencing coverage, and the yield and concordance of single nucleotide variant (SNV) and copy number variant (CNV) calls between blood and saliva genomes.

Results

Of 531 blood and 502 saliva samples, 46% saliva DNA failed quality control (QC) requirements for WGS compared to 6% QC failure for blood DNA. An average of 10.7% WGS reads in the saliva samples mapped to the human oral microbiome compared to 0.09% WGS reads in blood samples. However, these reads were readily excluded by excluding reads that did not map to the human reference genome. Sequencing coverage met or exceeded the target sequencing depth of 30x in all the blood samples and 4 of the 5 saliva samples; the fifth saliva sample had an average sequencing depth of 22.6x. Over 95% of SNVs identified in saliva were concordant with those identified in blood across the genome, within all gene coding regions, and within cardiovascular disease-related gene coding regions. Rare SNVs, defined as those with a minor allele frequency of less than 1% in the Genome Aggregation Database, had a lower concordance of 90% between blood and saliva genomes. CNVs had only 76% concordance between blood and saliva samples.

Conclusions

High quality saliva samples that meet stringent QC criteria can be used for WGS when blood-derived DNA is not available or is not suitable. Saliva DNA provides an acceptable yield of SNV calls but has a lower yield for CNV calls compared to blood DNA.

Epigenetic plasticity of enhancers in cancer

Enhancers are cis-acting elements with many sites bound by transcription factors and activate transcription over long distance. Histone modifications are critical for enhancer activity and utilized as hallmarks for the identification of putative enhancers. Monomethylation of histone H3 lysine 4 (H3K4me1) is the mark for enhancer priming; acetylation of histone H3 lysine 27 (H3K27ac) for active enhancers and trimethylation of histone H3 lysine 27 (H3K27me3) for silent enhancers. Recent studies from multiple groups have provided evidence that enhancer reprogramming, especially gain of enhancer activity, is closely related to tumorigenesis and cancer development. In this review, we will summarize the recent discoveries about enhancer regulation and the mechanisms of enhancer reprogramming in tumorigenesis, and discuss the potential application of enhancer manipulation in precision medicine.

A heterodimer of evolved designer-recombinases precisely excises a human genomic DNA locus

Site-specific recombinases (SSRs) such as the Cre/loxP system are useful genome engineering tools that can be repurposed by altering their DNA-binding specificity. However, SSRs that delete a natural sequence from the human genome have not been reported thus far. Here, we describe the generation of an SSR system that precisely excises a 1.4 kb fragment from the human genome. Through a streamlined process of substrate-linked directed evolution we generated two separate recombinases that, when expressed together, act as a heterodimer to delete a human genomic sequence from chromosome 7. Our data indicates that designer-recombinases can be generated in a manageable timeframe for precision genome editing. A large-scale bioinformatics analysis suggests that around 13% of all human protein-coding genes could be targetable by dual designer-recombinase induced genomic deletion (dDRiGD). We propose that heterospecific designer-recombinases, which work independently of the host DNA repair machinery, represent an efficient and safe alternative to nuclease-based genome editing technologies.

Evolutionary genomics analysis of human nucleus-encoded mitochondrial genes: implications for the roles of energy production and metabolic pathways in the pathogenesis and pathophysiology of demyelinating diseases

The myelin sheath is a plasma membrane extension that lines nerve fibers to protect, support and insulate neurons. The myelination of axons in vertebrates enables fast, saltatory impulse propagation, and this process relies on organelles, especially on mitochondria to supply energy. Approximately 99% of mitochondrial proteins are encoded in the nucleus. Since mitochondria play a central role in the energy production and metabolic pathways, which are essential for myelinogenesis, studying these nucleus-encoded genes (nMGs) may provide new insights into the roles of energy metabolism in demyelinating diseases. In this work, a multiomics-based approach was employed to 1) construct a 1,740 human nMG subset with mitochondrial localization evidence obtained from the Integrated Mitochondrial Protein Index (IMPI) and MitoCarta databases, 2) conduct an evolutionary genomics analysis across mouse, rat, monkey, chimp, and human models, 3) examine dysmyelination phenotype-related genes (nMG subset genes with oligodendrocyte- ​and myelin-related ​phenotypes, OMP-nMGs) in MGI mouse lines and human patients, 4) determine the expression discrepancy of OMP-nMGs in brain tissues of cuprizone-treated mice, multiple sclerosis patients, and normal controls, and 5) conduct literature data mining to explore OMP-nMG-associated disease impacts. By contrasting OMP-nMGs with other genes, OMP-nMGs were found to be more ubiquitously expressed (59.1% vs. 16.1%), disease-associated (67.3% vs. 20.2%), and evolutionarily conserved within the human populations. Our multiomics-based analysis identified 110 OMP-nMGs implicated in energy production and lipid and glycan biosynthesis in the pathogenesis and pathophysiology of demyelinating disorders. Future targeted characterization of OMP-nMGs in abnormal myelination conditions may allow the discovery of novel nMG mediated mechanisms underlying myelinogenesis and related diseases.

MiPepid: MicroPeptide identification tool using machine learning

Background

Micropeptides are small proteins with length < = 100 amino acids. Short open reading frames that could produces micropeptides were traditionally ignored due to technical difficulties, as few small peptides had been experimentally confirmed. In the past decade, a growing number of micropeptides have been shown to play significant roles in vital biological activities. Despite the increased amount of data, we still lack bioinformatics tools for specifically identifying micropeptides from DNA sequences. Indeed, most existing tools for classifying coding and noncoding ORFs were built on datasets in which “normal-sized” proteins were considered to be positives and short ORFs were generally considered to be noncoding. Since the functional and biophysical constraints on small peptides are likely to be different from those on “normal” proteins, methods for predicting short translated ORFs must be trained independently from those for longer proteins.

Results

In this study, we have developed MiPepid, a machine-learning tool specifically for the identification of micropeptides. We trained MiPepid using carefully cleaned data from existing databases and used logistic regression with 4-mer features. With only the sequence information of an ORF, MiPepid is able to predict whether it encodes a micropeptide with 96% accuracy on a blind dataset of high-confidence micropeptides, and to correctly classify newly discovered micropeptides not included in either the training or the blind test data. Compared with state-of-the-art coding potential prediction methods, MiPepid performs exceptionally well, as other methods incorrectly classify most bona fide micropeptides as noncoding. MiPepid is alignment-free and runs sufficiently fast for genome-scale analyses. It is easy to use and is available at https://github.com/MindAI/MiPepid.

Conclusions

MiPepid was developed to specifically predict micropeptides, a category of proteins with increasing significance, from DNA sequences. It shows evident advantages over existing coding potential prediction methods on micropeptide identification. It is ready to use and runs fast.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-3033-9) contains supplementary material, which is available to authorized users.

Consensus coding sequence (CCDS) database: a standardized set of human and mouse protein-coding regions supported by expert curation

The Consensus Coding Sequence (CCDS) project provides a dataset of protein-coding regions that are identically annotated on the human and mouse reference genome assembly in genome annotations produced independently by NCBI and the Ensembl group at EMBL-EBI. This dataset is the product of an international collaboration that includes NCBI, Ensembl, HUGO Gene Nomenclature Committee, Mouse Genome Informatics and University of California, Santa Cruz. Identically annotated coding regions, which are generated using an automated pipeline and pass multiple quality assurance checks, are assigned a stable and tracked identifier (CCDS ID). Additionally, coordinated manual review by expert curators from the CCDS collaboration helps in maintaining the integrity and high quality of the dataset. The CCDS data are available through an interactive web page (https://www.ncbi.nlm.nih.gov/CCDS/CcdsBrowse.cgi) and an FTP site (ftp://ftp.ncbi.nlm.nih.gov/pub/CCDS/). In this paper, we outline the ongoing work, growth and stability of the CCDS dataset and provide updates on new collaboration members and new features added to the CCDS user interface. We also present expert curation scenarios, with specific examples highlighting the importance of an accurate reference genome assembly and the crucial role played by input from the research community.

Deep sequencing across germline genome-wide association study signals relating to breast cancer events in women receiving aromatase inhibitors for adjuvant therapy of early breast cancer

OBJECTIVE

To identify additional genetic variants beyond those observed in a previous genome-wide association study (GWAS) in women treated on the MA.27 clinical trial in which women were randomized to 5 years of adjuvant therapy with anastrozole or exemestane.

PATIENTS AND METHODS

We performed a matched case-control study in 234 women who had a recurrence of breast cancer (cases) and 649 women who had not (controls). The analysis was restricted to White women with an estrogen receptor-positive breast cancer. Multiplex PCR-based targeted deep sequencing was performed of the MIR2052HG region on chromosome 8 between positions 75.4 and 75.7, a span of 300 kb, in an attempt to identify additional functional single nucleotide polymorphisms (SNPs).

RESULTS

A total of 4677 unique variants were identified that had not been identified in the previous GWAS. Clinical Annotation of Variants analysis revealed 10 variants, including eight SNPs and two insertion-deletion mutations with moderate or high impact. However, none of the common and variant regions was significant after adjustment for the most significant SNP (rs13260300) identified in our previous GWAS. We performed haplotype analysis that revealed two regions in which the haplotypes lost significance when adjusted for this prior GWAS SNP and one region with two significant haplotypes (P = 0.046 and 0.031) after adjusting for the GWAS SNP.

CONCLUSION

We were unable to identify common or rare variant regions that added value to the findings from our previous GWAS. We did find two haplotypes that were significant after adjusting for our top GWAS SNP but these were considered to be of marginal value.

Genetic characteristics of retinitis pigmentosa in 1204 Japanese patients

BACKGROUND

The genetic profile of retinitis pigmentosa (RP) in East Asian populations has not been well characterised. Therefore, we conducted a large-scale sequencing study to investigate the genes and variants causing RP in a Japanese population.

METHODS

A total of 1209 Japanese patients diagnosed with typical RP were enrolled. We performed deep resequencing of 83 known causative genes of RP using next-generation sequencing. We defined pathogenic variants as those that were putatively deleterious or registered as pathogenic in the Human Gene Mutation Database or ClinVar database and had a minor allele frequency in any ethnic population of ≤0.5% for recessive genes or ≤0.01% for dominant genes as determined using population-based databases.

RESULTS

We successfully sequenced 1204 patients with RP and determined 200 pathogenic variants in 38 genes as the cause of RP in 356 patients (29.6%). Variants in six genes (EYS, USH2A, RP1L1, RHO, RP1 and RPGR) caused RP in 65.4% (233/356) of those patients. Among autosomal recessive genes, two known founder variants in EYS [p.(Ser1653fs) and p.(Tyr2935*)] and four East Asian-specific variants [p.(Gly2752Arg) in USH2A, p.(Arg658*) in RP1L1, p.(Gly2186Glu) in EYS and p.(Ile535Asn) in PDE6B] and p.(Cys934Trp) in USH2A were found in ≥10 patients. Among autosomal dominant genes, four pathogenic variants [p.(Pro347Leu) in RHO, p.(Arg872fs) in RP1, p.(Arg41Trp) in CRX and p.(Gly381fs) in PRPF31] were found in ≥4 patients, while these variants were unreported or extremely rare in both East Asian and non-East Asian population-based databases.

CONCLUSIONS

East Asian-specific variants in causative genes were the major causes of RP in the Japanese population.

Identification of rare coding variants in TYK2 protective for rheumatoid arthritis in the Japanese population and their effects on cytokine signalling

OBJECTIVE

Although genome-wide association studies (GWAS) have identified approximately 100 loci for rheumatoid arthritis (RA), the disease mechanisms are not completely understood. We evaluated the pathogenesis of RA by focusing on rare coding variants.

METHODS

The coding regions of 98 candidate genes identified by GWAS were sequenced in 2294 patients with RA and 4461 controls in Japan. An association analysis was performed using cases and controls for variants, genes and domains of TYK2. Cytokine responses for two associated variants (R231W, rs201917359; and R703W, rs55882956) in TYK2 as well as a previously reported risk variant (P1004A, rs34536443) for multiple autoimmune diseases were evaluated by reporter assays.

RESULTS

A variant in TYK2 (R703W) showed a suggestive association (p=5.47×10^-8, OR=0.48). We observed more accumulation of rare coding variants in controls in TYK2 (p=3.94×10^-12, OR=0.56). The four-point-one, ezrin, radixin, moesin (FERM; 2.14×10^-3, OR=0.66) and pseudokinase domains (1.63×10^-8, OR=0.52) of TYK2 also showed enrichment of variants in controls. R231W in FERM domain especially reduced interleukin (IL)-6 and interferon (IFN)-γ signalling, whereas P1104A in kinase domain reduced IL-12, IL-23 and IFN-α signalling. R703W in pseudokinase domain reduced cytokine signals similarly to P1104A, but the effects were weaker than those of P1104A.

CONCLUSIONS

The FERM and pseudokinase domains in TYK2 were associated with the risk of RA in the Japanese population. Variants in TYK2 had different effects on cytokine signalling, suggesting that the regulation of selective cytokine signalling is a target for RA treatment.

A network of human functional gene interactions from knockout fitness screens in cancer cells

The function of human genes can be strongly inferred from their knockout fitness profiles across hundreds of CRISPR screens, illuminating the modular organization of the cell.

Genetic interactions mediate the emergence of phenotype from genotype. The systematic survey of genetic interactions in yeast showed that genes operating in the same biological process have highly correlated genetic interaction profiles, and this observation has been exploited to infer gene function in model organisms. Such assays of digenic perturbations in human cells are also highly informative, but are not scalable, even with CRISPR-mediated methods. As an alternative, we developed an indirect method of deriving functional interactions. We show that genes having correlated knockout fitness profiles across diverse, non-isogenic cell lines are analogous to genes having correlated genetic interaction profiles across isogenic query strains and similarly imply shared biological function. We constructed a network of genes with correlated fitness profiles across 276 high-quality CRISPR knockout screens in cancer cell lines into a “coessentiality network,” with up to 500-fold enrichment for co-functional gene pairs, enabling strong inference of gene function and highlighting the modular organization of the cell.

SmProt: a database of small proteins encoded by annotated coding and non-coding RNA loci

Small proteins is the general term for proteins with length shorter than 100 amino acids. Identification and functional studies of small proteins have advanced rapidly in recent years, and several studies have shown that small proteins play important roles in diverse functions including development, muscle contraction and DNA repair. Identification and characterization of previously unrecognized small proteins may contribute in important ways to cell biology and human health. Current databases are generally somewhat deficient in that they have either not collected small proteins systematically, or contain only predictions of small proteins in a limited number of tissues and species. Here, we present a specifically designed web-accessible database, small proteins database (SmProt, http://bioinfo.ibp.ac.cn/SmProt), which is a database documenting small proteins. The current release of SmProt incorporates 255 010 small proteins computationally or experimentally identified in 291 cell lines/tissues derived from eight popular species. The database provides a variety of data including basic information (sequence, location, gene name, organism, etc.) as well as specific information (experiment, function, disease type, etc.). To facilitate data extraction, SmProt supports multiple search options, including species, genome location, gene name and their aliases, cell lines/tissues, ORF type, gene type, PubMed ID and SmProt ID. SmProt also incorporates a service for the BLAST alignment search and provides a local UCSC Genome Browser. Additionally, SmProt defines a high-confidence set of small proteins and predicts the functions of the small proteins.

Overexpressed TTC3 Protein Tends to be Cleaved into Fragments and Form Aggregates in the Nucleus

Human tetratricopeptide repeat domain 3 (TTC3) is a gene on 21q22.2 within the Down syndrome critical region (DSCR). Earlier studies suggest that TTC3 may be an important regulator in individual development, especially in neural development. As an E3 ligase, TTC3 binds to phosphorylated Akt and silence its activity via proteasomal cascade. Several groups also reported the involvement of TTC3 in familial Alzheimer's disease recently. In addition, our previous work shows that TTC3 also regulates the degradation of DNA polymerase gamma and over-expressed TTC3 protein tends to form insoluble aggregates in cells. In this study, we focus on the solubility and intracellular localization of TTC3 protein. Over-expressed TTC3 tends to form insoluble aggregates over time. The proteasome inhibitor MG132 treatment resulted in more TTC3 aggregates in a short period of time. We fused the fluorescent protein to either terminus of the TTC3 protein and found that the intracellular localization of fluorescent signals are different between the N-terminal tagged and C-terminal tagged proteins. Western blotting revealed that the TTC3 protein is cleaved into fragments of different sizes at multiple sites. The N-terminal sub-fragments of TTC3 are prone to from nuclear aggregates and the TTC3 nuclear import is mediated by signals within the N-terminal 1 to 650 residues. Moreover, over-expressed TTC3 induced a considerable degree of cytotoxicity, and its N-terminal sub-fragments are more potent inhibitors of cell proliferation than full-length protein. Considering the prevalent proteostasis dysregulation in neurodegenerative diseases, these findings may relate to the pathology of such diseases.

CHESS: a new human gene catalog curated from thousands of large-scale RNA sequencing experiments reveals extensive transcriptional noise

We assembled the sequences from deep RNA sequencing experiments by the Genotype-Tissue Expression (GTEx) project, to create a new catalog of human genes and transcripts, called CHESS. The new database contains 42,611 genes, of which 20,352 are potentially protein-coding and 22,259 are noncoding, and a total of 323,258 transcripts. These include 224 novel protein-coding genes and 116,156 novel transcripts. We detected over 30 million additional transcripts at more than 650,000 genomic loci, nearly all of which are likely nonfunctional, revealing a heretofore unappreciated amount of transcriptional noise in human cells. The CHESS database is available at http://ccb.jhu.edu/chess .

Germline pathogenic variants of 11 breast cancer genes in 7,051 Japanese patients and 11,241 controls

Pathogenic variants in highly penetrant genes are useful for the diagnosis, therapy, and surveillance for hereditary breast cancer. Large-scale studies are needed to inform future testing and variant classification processes in Japanese. We performed a case-control association study for variants in coding regions of 11 hereditary breast cancer genes in 7051 unselected breast cancer patients and 11,241 female controls of Japanese ancestry. Here, we identify 244 germline pathogenic variants. Pathogenic variants are found in 5.7% of patients, ranging from 15% in women diagnosed <40 years to 3.2% in patients ≥80 years, with BRCA1/2, explaining two-thirds of pathogenic variants identified at all ages. BRCA1/2, PALB2, and TP53 are significant causative genes. Patients with pathogenic variants in BRCA1/2 or PTEN have significantly younger age at diagnosis. In conclusion, BRCA1/2, PALB2, and TP53 are the major hereditary breast cancer genes, irrespective of age at diagnosis, in Japanese women.

Data mining of the cancer-related lncRNAs GO terms and KEGG pathways by using mRMR method

LncRNAs plays an important role in the regulation of gene expression. Identification of cancer-related lncRNAs GO terms and KEGG pathways is great helpful for revealing cancer-related functional biological processes. Therefore, in this study, we proposed a computational method to identify novel cancer-related lncRNAs GO terms and KEGG pathways. By using existing lncRNA database and Max-relevance Min-redundancy (mRMR) method, GO terms and KEGG pathways were evaluated based on their importance on distinguishing cancer-related and non-cancer-related lncRNAs. Finally, GO terms and KEGG pathways with high importance were presented and analyzed. Our literature reviewing showed that the top 10 ranked GO terms and pathways were really related to interpretable tumorigenesis according to recent publications.

IBD risk loci are enriched in multigenic regulatory modules encompassing putative causative genes

GWAS have identified >200 risk loci for Inflammatory Bowel Disease (IBD). The majority of disease associations are known to be driven by regulatory variants. To identify the putative causative genes that are perturbed by these variants, we generate a large transcriptome data set (nine disease-relevant cell types) and identify 23,650 cis-eQTL. We show that these are determined by ∼9720 regulatory modules, of which ∼3000 operate in multiple tissues and ∼970 on multiple genes. We identify regulatory modules that drive the disease association for 63 of the 200 risk loci, and show that these are enriched in multigenic modules. Based on these analyses, we resequence 45 of the corresponding 100 candidate genes in 6600 Crohn disease (CD) cases and 5500 controls, and show with burden tests that they include likely causative genes. Our analyses indicate that ≥10-fold larger sample sizes will be required to demonstrate the causality of individual genes using this approach.

Whole-exome sequencing in 20,197 persons for rare variants in Alzheimer's disease

Objective

The genetic bases of Alzheimer's disease remain uncertain. An international effort to fully articulate genetic risks and protective factors is underway with the hope of identifying potential therapeutic targets and preventive strategies. The goal here was to identify and characterize the frequency and impact of rare and ultra-rare variants in Alzheimer's disease, using whole-exome sequencing in 20,197 individuals.

Methods

We used a gene-based collapsing analysis of loss-of-function ultra-rare variants in a case-control study design with data from the Washington Heights-Inwood Columbia Aging Project, the Alzheimer's Disease Sequencing Project and unrelated individuals from the Institute of Genomic Medicine at Columbia University.

Results

We identified 19 cases carrying extremely rare SORL1 loss-of-function variants among a collection of 6,965 cases and a single loss-of-function variant among 13,252 controls (P = 2.17 × 10^-8; OR: 36.2 [95% CI: 5.8-1493.0]). Age-at-onset was 7 years earlier for patients with SORL1 qualifying variant compared with noncarriers. No other gene attained a study-wide level of statistical significance, but multiple top-ranked genes, including GRID2IP,WDR76 and GRN, were among candidates for follow-up studies.

Interpretation

This study implicates ultra-rare, loss-of-function variants in SORL1 as a significant genetic risk factor for Alzheimer's disease and provides a comprehensive dataset comparing the burden of rare variation in nearly all human genes in Alzheimer's disease cases and controls. This is the first investigation to establish a genome-wide statistically significant association between multiple extremely rare loss-of-function variants in SORL1 and Alzheimer's disease in a large whole-exome study of unrelated cases and controls.

ADH1B: From alcoholism, natural selection, and cancer to the human phenome

The ADH1B (Alcohol Dehydrogenase 1B (class I), Beta Polypeptide) gene and its best-known functional alleles, Arg48His (rs1229984, ADH1B*2) and Arg370Cys (rs2066702, ADH1B*3), have been investigated in relation to many phenotypic traits; most frequently including alcohol metabolism and alcohol drinking behaviors, but also human evolution, liver function, cancer, and, recently, the comprehensive human phenome. To understand ADH1B functions and consequences, we provide here a bioinformatic analysis of its gene regulation and molecular functions, literature review of studies focused on this gene, and a discussion regarding future research perspectives. Certain ADH1B alleles have large effects on alcohol metabolism, and this relationship particularly encourages further investigations in relation to alcoholism and alcohol-associated cancer to understand better the mechanisms by which alcohol metabolism contributes to alcohol abuse and carcinogenesis. We also observed that ADH1B has complex mechanisms that regulate its expression across multiple human tissues, and these may be involved in cardiac and metabolic traits. Evolutionary data strongly suggest that the selection signatures at the ADH1B locus are primarily related to effects other than those on alcohol metabolism. This is also supported by the involvement of ADH1B in multiple molecular pathways and by the findings of our recent phenome-wide association study. Accordingly, future studies should also investigate other functions of ADH1B potentially relevant for the human phenome. © 2017 Wiley Periodicals, Inc.

Low-frequency coding variants in CETP and CFB are associated with susceptibility of exudative age-related macular degeneration in the Japanese population

Age-related macular degeneration (AMD) is a major cause of blindness in the elderly. Previous sequencing studies of AMD susceptibility genes have revealed the association of rare coding variants in CFH, CFI, C3 and C9 in European population; however, the impact of rare or low-frequency coding variants on AMD susceptibility in other populations is largely unknown. To identify the role of low-frequency coding variants on exudative AMD susceptibility in a Japanese population, we analysed the association of coding variants of 34 AMD candidate genes in the two-stage design by a multiplex PCR-based target sequencing method. We used a total of 2,886 (1st: 827, 2nd: 2,059) exudative AMD cases including typical AMD, polypoidal choroidal vasculopathy, and retinal angiomatous proliferation and 9,337 (1st: 3,247 2nd: 6,090) controls. Gene-based analysis found a significant association of low-frequency variants (minor allele frequency (MAF) < 0.05) in CETP, C2 and CFB. The association of CETP remained after conditioned with all known genome-wide association study (GWAS) associated variants. In addition, when we included only disruptive variants, enrichment of rare variants (MAF < 0.01) was also observed after conditioned with all GWAS associated variants (P = 1.03 × 10−6, odds ratio (OR) = 2.48). Haplotype and conditional analysis of the C2-CFB-SKIV2L locus showed a low-frequency variant (R74H) in CFB would be individually associated with AMD susceptibility independent of the GWAS associated SNP. These findings highlight the importance of target sequencing to reveal the impact of rare or low-frequency coding variants on disease susceptibility in different ethnic populations.

TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions

Transcription factors (TFs) are major trans-acting factors in transcriptional regulation. Therefore, elucidating TF-target interactions is a key step toward understanding the regulatory circuitry underlying complex traits such as human diseases. We previously published a reference TF-target interaction database for humans-TRRUST (Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining)-which was constructed using sentence-based text mining, followed by manual curation. Here, we present TRRUST v2 (www.grnpedia.org/trrust) with a significant improvement from the previous version, including a significantly increased size of the database consisting of 8444 regulatory interactions for 800 TFs in humans. More importantly, TRRUST v2 also contains a database for TF-target interactions in mice, including 6552 TF-target interactions for 828 mouse TFs. TRRUST v2 is also substantially more comprehensive and less biased than other TF-target interaction databases. We also improved the web interface, which now enables prioritization of key TFs for a physiological condition depicted by a set of user-input transcriptional responsive genes. With the significant expansion in the database size and inclusion of the new web tool for TF prioritization, we believe that TRRUST v2 will be a versatile database for the study of the transcriptional regulation involved in human diseases.

VarCards: an integrated genetic and clinical database for coding variants in the human genome

A growing number of genomic tools and databases were developed to facilitate the interpretation of genomic variants, particularly in coding regions. However, these tools are separately available in different online websites or databases, making it challenging for general clinicians, geneticists and biologists to obtain the first-hand information regarding some particular variants and genes of interest. Starting with coding regions and splice sties, we artificially generated all possible single nucleotide variants (n = 110 154 363) and cataloged all reported insertion and deletions (n = 1 223 370). We then annotated these variants with respect to functional consequences from more than 60 genomic data sources to develop a database, named VarCards (http://varcards.biols.ac.cn/), by which users can conveniently search, browse and annotate the variant- and gene-level implications of given variants, including the following information: (i) functional effects; (ii) functional consequences through different in silico algorithms; (iii) allele frequencies in different populations; (iv) disease- and phenotype-related knowledge; (v) general meaningful gene-level information; and (vi) drug-gene interactions. As a case study, we successfully employed VarCards in interpretation of de novo mutations in autism spectrum disorders. In conclusion, VarCards provides an intuitive interface of necessary information for researchers to prioritize candidate variations and genes.

Intrinsically Disordered Proteome of Human Membrane-Less Organelles

It is recognized now that various proteinaceous membrane-less organelles (PMLOs) are commonly found in cytoplasm, nucleus, and mitochondria of various eukaryotic cells (as well as in the chloroplasts of plant cells). Being different from the "traditional" membrane-encapsulated organelles, such as chloroplasts, endoplasmic reticulum, Golgi apparatus, lysosomes, mitochondria, nucleus, and vacuoles, PMLOs solve the cellular need to facilitate and regulate molecular interactions via reversible and controllable isolation of target molecules in specialized compartments. PMLOs possess liquid-like behavior and are believed to be formed as a result of biological liquid-liquid phase transitions (LLPTs, also known as liquid-liquid phase separation), where an intricate interplay between RNA and intrinsically disordered proteins (IDPs) or hybrid proteins containing ordered domains and intrinsically disordered protein regions (IDPRs) may play an important role. This review analyzes the prevalence of intrinsic disorder in proteins associated with various PMLOs found in human cells and considers some of the functional roles of IDPs/IDPRs in biogenesis of these organelles.

Sensitivity of whole exome sequencing in detecting infantile- and late-onset Pompe disease

Pompe disease is a metabolic myopathy with a wide spectrum of clinical presentation. The gold-standard diagnostic test is acid alpha-glucosidase assay on skin fibroblasts, muscle or blood. Identification of two GAA pathogenic variants in-trans is confirmatory. Optimal effectiveness of enzyme replacement therapy hinges on early diagnosis, which is challenging in late-onset form of the disease due to non-specific presentation. Next-generation sequencing-based panels effectively facilitate diagnosis, but the sensitivity of whole-exome sequencing (WES) in detecting pathogenic GAA variants remains unknown. We analyzed WES data from 93 patients with confirmed Pompe disease and GAA genotypes based on PCR/Sanger sequencing. After ensuring that the common intronic variant c.-32-13T>G is not filtered out, whole-exome sequencing identified both GAA pathogenic variants in 77/93 (83%) patients. However, one variant was missed in 14/93 (15%), and both variants were missed in 2/93 (2%). One complex indel leading to a severe phenotype was incorrectly called a nonsynonymous substitution c.-32-13T>C due to misalignment. These results demonstrate that WES may fail to diagnose Pompe disease. Clinicians need to be aware of limitations of WES, and consider tests specific to Pompe disease when WES does not provide a diagnosis in patients with proximal myopathy, progressive respiratory failure or other subtle symptoms.

WDR26 Haploinsufficiency Causes a Recognizable Syndrome of Intellectual Disability, Seizures, Abnormal Gait, and Distinctive Facial Features

We report 15 individuals with de novo pathogenic variants in WDR26. Eleven of the individuals carry loss-of-function mutations, and four harbor missense substitutions. These 15 individuals comprise ten females and five males, and all have intellectual disability with delayed speech, a history of febrile and/or non-febrile seizures, and a wide-based, spastic, and/or stiff-legged gait. These subjects share a set of common facial features that include a prominent maxilla and upper lip that readily reveal the upper gingiva, widely spaced teeth, and a broad nasal tip. Together, these features comprise a recognizable facial phenotype. We compared these features with those of chromosome 1q41q42 microdeletion syndrome, which typically contains WDR26, and noted that clinical features are consistent between the two subsets, suggesting that haploinsufficiency of WDR26 contributes to the pathology of 1q41q42 microdeletion syndrome. Consistent with this, WDR26 loss-of-function single-nucleotide mutations identified in these subjects lead to nonsense-mediated decay with subsequent reduction of RNA expression and protein levels. We derived a structural model of WDR26 and note that missense variants identified in these individuals localize to highly conserved residues of this WD-40-repeat-containing protein. Given that WDR26 mutations have been identified in ∼1 in 2,000 of subjects in our clinical cohorts and that WDR26 might be poorly annotated in exome variant-interpretation pipelines, we would anticipate that this disorder could be more common than currently appreciated.

Mouse Genome Informatics (MGI) Resource: Genetic, Genomic, and Biological Knowledgebase for the Laboratory Mouse

The Mouse Genome Informatics (MGI) Resource supports basic, translational, and computational research by providing high-quality, integrated data on the genetics, genomics, and biology of the laboratory mouse. MGI serves a strategic role for the scientific community in facilitating biomedical, experimental, and computational studies investigating the genetics and processes of diseases and enabling the development and testing of new disease models and therapeutic interventions. This review describes the nexus of the body of growing genetic and biological data and the advances in computer technology in the late 1980s, including the World Wide Web, that together launched the beginnings of MGI. MGI develops and maintains a gold-standard resource that reflects the current state of knowledge, provides semantic and contextual data integration that fosters hypothesis testing, continually develops new and improved tools for searching and analysis, and partners with the scientific community to assure research data needs are met. Here we describe one slice of MGI relating to the development of community-wide large-scale mutagenesis and phenotyping projects and introduce ways to access and use these MGI data. References and links to additional MGI aspects are provided.

A Computational Methodology to Overcome the Challenges Associated With the Search for Specific Enzyme Targets to Develop Drugs Against Leishmania major

We present an approach for detecting enzymes that are specific of Leishmania major compared with Homo sapiens and provide targets that may assist research in drug development. This approach is based on traditional techniques of sequence homology comparison by similarity search and Markov modeling; it integrates the characterization of enzymatic functionality, secondary and tertiary protein structures, protein domain architecture, and metabolic environment. From 67 enzymes represented by 42 enzymatic activities classified by AnEnPi (Analogous Enzymes Pipeline) as specific for L major compared with H sapiens, only 40 (23 Enzyme Commission [EC] numbers) could actually be considered as strictly specific of L major and 27 enzymes (19 EC numbers) were disregarded for having ambiguous homologies or analogies with H sapiens. Among the 40 strictly specific enzymes, we identified sterol 24-C-methyltransferase, pyruvate phosphate dikinase, trypanothione synthetase, and RNA-editing ligase as 4 essential enzymes for L major that may serve as targets for drug development.

Genome annotation for clinical genomic diagnostics: strengths and weaknesses

The Human Genome Project and advances in DNA sequencing technologies have revolutionized the identification of genetic disorders through the use of clinical exome sequencing. However, in a considerable number of patients, the genetic basis remains unclear. As clinicians begin to consider whole-genome sequencing, an understanding of the processes and tools involved and the factors to consider in the annotation of the structure and function of genomic elements that might influence variant identification is crucial. Here, we discuss and illustrate the strengths and weaknesses of approaches for the annotation and classification of important elements of protein-coding genes, other genomic elements such as pseudogenes and the non-coding genome, comparative-genomic approaches for inferring gene function, and new technologies for aiding genome annotation, as a practical guide for clinicians when considering pathogenic sequence variation. Complete and accurate annotation of structure and function of genome features has the potential to reduce both false-negative (from missing annotation) and false-positive (from incorrect annotation) errors in causal variant identification in exome and genome sequences. Re-analysis of unsolved cases will be necessary as newer technology improves genome annotation, potentially improving the rate of diagnosis.