Molecular Biophysics and Biochemistry

Data reduction techniques are now a vital part of numerical analysis and principal component analysis is often used to identify important molecular features from a set of descriptors. We now take a different approach and apply data reduction techniques directly to protein structure. With this we can reduce the three-dimensional structural data into two-dimensions while preserving the correct relationships. With two-dimensional representations, structural comparisons between proteins are accelerated significantly. This means that protein-protein similarity comparisons are now feasible on a large scale. We show how the approach can help to predict the function of kinase structures according to the Hanks' classification based on their structural similarity to different kinase classes.

The transcriptome is the readout of the genome. Identifying common features in it across distant species can reveal fundamental principles. To this end, the ENCODE and modENCODE consortia have generated large amounts of matched RNA-sequencing data for human, worm and fly. Uniform processing and comprehensive annotation of these data allow comparison across metazoan phyla, extending beyond earlier within-phylum transcriptome comparisons and revealing ancient, conserved features. Specifically, we discover co-expression modules shared across animals, many of which are enriched in developmental genes. Moreover, we use expression patterns to align the stages in worm and fly development and find a novel pairing between worm embryo and fly pupae, in addition to the embryo-to-embryo and larvae-to-larvae pairings. Furthermore, we find that the extent of non-canonical, non-coding transcription is similar in each organism, per base pair. Finally, we find in all three organisms that the gene-ex...

The topology of the gene-regulatory network has been extensively analyzed. Now, given the large amount of available functional genomic data, it is possible to go beyond this and systematically study regulatory circuits in terms of logic elements. To this end, we present Loregic, a computational method integrating gene expression and regulatory network data, to characterize the cooperativity of regulatory factors. Loregic uses all 16 possible twoinput-one-output logic gates (e.g. AND or XOR) to describe triplets of two factors regulating a common target. We attempt to find the gate that best matches each triplet's observed gene expression pattern across many conditions. We make Loregic available as a generalpurpose tool (github.com/gersteinlab/loregic). We validate it with known yeast transcriptionfactor knockout experiments. Next, using human ENCODE ChIP-Seq and TCGA RNA-Seq data, we are able to demonstrate how Loregic characterizes complex circuits involving both proximally and distally regulating transcription factors (TFs) and also miRNAs. Furthermore, we show that MYC, a well-known oncogenic driving TF, can be modeled as acting independently from other TFs (e.g., using OR gates) but antagonistically with repressing miRNAs. Finally, we inter-relate Loregic's gate logic with other aspects of regulation, such as indirect binding via protein-protein interactions, feed-forward loop motifs and global regulatory hierarchy.

Background: Pseudogenes have long been considered as nonfunctional genomic sequences. However, recent evidence suggests that many of them might have some form of biological activity, and the possibility of functionality has increased interest in their accurate annotation and integration with functional genomics data.

SUMMARYH2A.Z is a H2A-type histone variant essential for many aspects of cell biology ranging from gene expression to genome stability. From deuterostomes, H2A.Z evolved into two paralogues H2A.Z.1 and H2A.Z.2 that differ by only three amino acids and are encoded by different genes (H2AFZ and H2AFV respectively). Despite the importance of this histone variant in development and cellular homeostasis, very little is known about the individual functions of each paralogue in mammals. Here we investigated the distinct roles of two paralogues in cell cycle regulation. Using a specific siRNA approach for each paralogue in human cells, we unveiled non-redundant functions for H2A.Z.1 and H2A.Z.2 in cell division: H2A.Z.1 regulates the expression of important cell cycle genes (including Myc and Ki-67) and its depletion leads to a G1 arrest, whereas H2A.Z.2 is essential for centromere integrity and function, thus playing a key role in chromosome segregation.

The 1000 Genomes Project Consortium* A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genomewide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants.

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies. The 1000 Genomes Project has already elucidated the properties and distribution of common and rare variation, provided insights into the processes that shape genetic diversity, and advanced understanding of disease biology 1,2. This resource provides a benchmark for surveys of human genetic variation and constitutes a key component for human genetic studies, by enabling array design 3,4 , genotype imputation 5 , cataloguing of variants in regions of interest, and filtering of likely neutral variants 6,7. In this final phase, individuals were sampled from 26 populations in Africa (AFR), East Asia (EAS), Europe (EUR), South Asia (SAS), and the Americas (AMR) (Fig. 1a; see Supplementary Table 1 for population descriptions and abbreviations). All individuals were sequenced using both whole-genome sequencing (mean depth = 7.4×) and targeted exome sequencing (mean depth = 65.7×). In addition, individuals and available first-degree relatives (generally, adult offspring) were genotyped using high-density SNP microarrays. This provided a cost-effective means to discover genetic variants and estimate individual genotypes and haplotypes 1,2 .

Endometriosis is a well-known risk factor for ovarian cancer. The genetic changes that characterise endometriosis are poorly understood; however, the mechanistic target of rapamycin (mTOR) pathway is involved. In this study, we investigated the expression of key mTOR components in endometriosis and the effects of rapalogues using an endometrioid ovarian carcinoma cell line (MdAH 2774) as an in vitro model. Gene expression of mTOR, dEPTOR, Rictor and Raptor was assessed by qPcR in 24 endometriosis patients and in silico in ovarian cancer patients. Furthermore, the effects of Rapamycin, Everolimus, deforolimus, Temsirolimus, Resveratrol, and BEZ235 (dactolisib, a dual kinase inhibitor) on mTOR signalling components was assessed. mTOR showed a significant increase in the expression in endometriosis and ovarian endometrioid adenocarcinoma patients compared to non-affected controls. dEPTOR, an inhibitor of mTOR, was downregulated in the advanced stages of ovarian cancer (III and IV) compared to earlier stages (I and II). Treatment of MdAH-2774 cells with the mTOR inhibitors resulted in the significant upregulation of dEPTOR mRNA, whereas treatment with rapamycin and BEZ-235 (100 nM) resulted in downregulation of the mTOR protein expression after 48 h of treatment. None of the treatments resulted in translocation of mTOR from cytoplasm to nucleus. Upregulation of dEPTOR is a positive prognostic marker in ovarian cancer and is increased in response to mTOR pathway inhibition suggesting that it functions as a tumour suppressor gene in endometrioid ovarian carcinoma. collectively, our data suggest the mTOR pathway as a potential connection between endometriosis and ovarian cancer and may be a potential target in the treatment of both conditions.

The accurate identification and description of the genes in the human and mouse genomes is a fundamental requirement for high quality analysis of data informing both genome biology and clinical genomics. Over the last 15 years, the GENCODE consortium has been producing reference quality gene annotations to provide this foundational resource. The GENCODE consortium includes both experimental and computational biology groups who work together to improve and extend the GENCODE gene annotation. Specifically, we generate primary data, create bioinformatics tools and provide analysis to support the work of expert manual gene annotators and automated gene annotation pipelines. In addition, manual and computational annotation workflows use any and all publicly available data and analysis, along with the research literature to identify and characterise gene loci to the highest standard. GENCODE gene annotations are accessible via the Ensembl and UCSC Genome Browsers, the Ensembl FTP site, En...

The most commonly employed mammalian model organism is the laboratory mouse. A wide variety of genetically diverse inbred mouse strains, representing distinct physiological states, disease susceptibilities, and biological mechanisms have been developed over the last century. We report full length draft de novo genome assemblies for 16 of the most widely used inbred strains and reveal for the first time extensive strain-specific haplotype variation. We identify and characterise 2,567 regions on the current Genome Reference Consortium mouse reference genome exhibiting the greatest sequence diversity between strains. These regions are enriched for genes involved in defence and immunity, and exhibit enrichment of transposable elements and signatures of recent retrotransposition events. Combinations of alleles and genes unique to an individual strain are commonly observed at these loci, reflecting distinct strain phenotypes. Several immune related loci, some in previously identified QTLs...

Background: Liquid biopsies offer a promising alternative to tissue samples, providing non-invasive diagnostic approaches or serial monitoring of disease evolution. However, certain challenges remain, and the full potential of liquid biopsies has yet to be reached. Here we report several methodological approaches to interrogate liquid biopsies using circulating tumour cell (CTC) enumeration and characterisation, transcriptomics, Raman spectroscopy, and copy number instability (CNI) scores using blood samples of lung cancer (LC) patients. Methods: We choose LC; since it still is the most common cause of cancer-related mortality worldwide, and therefore there is a need for development of new non-invasive diagnostic/prognostic technologies. Changes in gene expression were assessed using RNA-seq, and in CTCs using ImageStream, an imaging flow-cytometer. CNI scores, from paired tissue/ctDNA were also explored. Raman spectroscopy was used to provide chemical fingerprints of plasma samples...

In a 2018 paper posted to bioRxiv, Pertea et al. presented the CHESS database, a new catalog of human gene annotations that includes 1,178 new protein-coding predictions. These are based on evidence of transcription in human tissues and homology to earlier annotations in human and other mammals. Here, we reanalyze the evidence used by CHESS, and find that nearly all protein-coding predictions are false positives. We find that 86% overlap transposons marked by RepeatMasker that are known to frequently result in false positive protein-coding predictions. More than half are homologous to only nine Alu-derived primate sequences corresponding to an erroneous and previously withdrawn Pfam protein domain. The entire set shows poor evolutionary conservation and PhyloCSF protein-coding evolutionary signatures indistinguishable from noncoding RNAs, indicating lack of protein-coding constraint. Only four predictions are supported by mass spectrometry evidence, and even those matches are inconc...

Pseudogenes are ideal markers of genome remodeling. In turn, the mouse is an ideal platform for studying them, particularly with the availability of developmental transcriptional data and the sequencing of 18 strains. Here, we present a comprehensive genome-wide annotation of the pseudogenes in the mouse reference genome and associated strains. We compiled this by combining manual curation of over 10,000 pseudogenes with results from automatic annotation pipelines. Also, by comparing the human and mouse, we annotated 165 unitary pseudogenes in mouse, and 303 unitaries in human. We make all our annotation available through mouse.pseudogene.org. The overall mouse pseudogene repertoire (in the reference and strains) is similar to human in terms of overall size, biotype distribution (~80% processed/~20% duplicated) and top family composition (with many GAPDH and ribosomal pseudogenes). However, notable differences arise in the pseudogene age distribution, with multiple retro-transpositi...

The radial spatial positioning of individual gene loci within interphase nuclei has been associated with up- and downregulation of their expression. In cancer, the genome organization may become disturbed due to chromosomal abnormalities, such as translocations or deletions, resulting in the repositioning of genes and alteration of gene expression with oncogenic consequences. In this study, we analyzed the nuclear repositioning of HLXB9 (also called MNX1), mapping at 7q36.3, in patients with hematological disorders carrying interstitial deletions of 7q of various extents, with a distal breakpoint in 7q36. We observed that HLXB9 remains at the nuclear periphery, or is repositioned towards the nuclear interior, depending upon the compositional properties of the chromosomal regions involved in the rearrangement. For instance, a proximal breakpoint leading the guanine-cytosine (GC)-poor band 7q21 near 7q36 would bring HLXB9 to the nuclear periphery, whereas breakpoints that join the GC-...

Pseudogenes are ideal markers of genome remodelling. In turn, the mouse is an ideal platform for studying them, particularly with the recent availability of strain-sequencing and transcriptional data. Here, combining both manual curation and automatic pipelines, we present a genome-wide annotation of the pseudogenes in the mouse reference genome and 18 inbred mouse strains (available via the mouse.pseudogene.org resource). We also annotate 165 unitary pseudogenes in mouse, and 303, in human. The overall pseudogene repertoire in mouse is similar to that in human in terms of size, biotype distribution, and family composition (e.g. with GAPDH and ribosomal proteins being the largest families). Notable differences arise in the pseudogene age distribution, with multiple retro-transpositional bursts in mouse evolutionary history and only one in human. Furthermore, in each strain about a fifth of all pseudogenes are unique, reflecting strain-specific evolution. Finally, we find that ~15% o...

Infection by the severe acute respiratory syndrome (SARS) coronavirus-2 (SARS-CoV-2) is the causative agent of a new disease (COVID-19). The risk of severe COVID-19 is increased by certain underlying comorbidities, including asthma, cancer, cardiovascular disease, hypertension, diabetes, and obesity. Notably, exposure to hormonally active chemicals called endocrine-disrupting chemicals (EDCs) can promote such cardio-metabolic diseases, endocrine-related cancers, and immune system dysregulation and thus, may also be linked to higher risk of severe COVID-19. Bisphenol A (BPA) is among the most common EDCs and exerts its effects via receptors which are widely distributed in human tissues, including nuclear oestrogen receptors (ERα and ERβ), membrane-bound oestrogen receptor (G protein-coupled receptor 30; GPR30), and human nuclear receptor oestrogen-related receptor gamma. As such, this paper focuses on the potential role of BPA in promoting comorbidities associated with severe COVID-1...

The human and mouse genomes contain instructions that specify RNAs and proteins and govern the timing, magnitude, and cellular context of their production. To better delineate these elements, phase III of the Encyclopedia of DNA Elements (ENCODE) Project has expanded analysis of the cell and tissue repertoires of RNA transcription, chromatin structure and modification, DNA methylation, chromatin looping, and occupancy by transcription factors and RNA-binding proteins. Here we summarize these efforts, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development. All data are available through the ENCODE data portal (https://www.encodeproject.org), including phase II ENCODE1 and Roadmap Epigenomics2 data. We have developed a registry of 926,535 human and 339,815 mouse candidate cis-regulatory elements, covering 7.9 and 3.4% of their respective genomes, by integrating selected datatypes associated with gene regulation, and cons...