Although it is widely believed that early vertebrate evolution was shaped by ancient whole-genome duplications, the number, timing and mechanism of these events remain elusive. Here, we infer the history of vertebrates through genomic comparisons with a new chromosome-scale sequence of the invertebrate chordate amphioxus. We show how the karyotypes of amphioxus and diverse vertebrates are derived from 17 ancestral chordate linkage groups  by fusion, rearrangement and duplication. We resolve two distinct ancient duplications based on patterns of chromosomal conserved synteny. All extant vertebrates share the first duplication, which occurred in the mid/late Cambrian by autotetraploidization . In contrast, the second duplication is found only in jawed vertebrates and occurred in the mid–late Ordovician by allotetraploidization  from two now-extinct progenitors. This complex genomic history parallels the diversification of vertebrate lineages in the fossil record. Genomic comparisons with a new amphioxus chromosome-scale genome assembly reveal details of the early evolution of vertebrate genomes. This hypothesis received early support from the discovery of multiple vertebrate Hox clusters compared with one invertebrate cluster2 and the finding of numerous vertebrate gene families with members distributed across multiple chromosomes4. Further evidence came from the discovery of paralogous  blocks of linked genes on multiple chromosomes within the human genome8, culminating in the discovery of widespread quadruply conserved synteny of the human genome10. These studies support the so-called ‘2R’ scenario of two rounds of whole-genome duplication during vertebrate evolution.In the 1970s, Ohno14. Alternatives to the 2R hypothesis include the recent proposal of a single whole-genome duplication with “additional large paralogy regions being the product of rare segmental duplications occurring both before and after”, based on comparative analyses of the sea lamprey genome15. Others have suggested a series of large segmental duplications without any genome-wide events17, although this is a minority view. Contributing to this uncertainty are discrepancies in the inferred chromosomal organization of the proto-vertebrate ancestor. By analysing gene linkages within and among selected bony vertebrate genomes (Euteleostomi), some authors have suggested the existence of 10–13 proto-vertebrate  chromosomes20, although other studies21 have inferred 17 ancestral chromosomes.However, the number, timing and mechanism of these duplication events are still debated22, and provide a critical outgroup for analysing vertebrate-specific gene duplications10 and the evolution of vertebrate gene regulation23. To robustly infer the proto-vertebrate karyotype and the genomic changes that accompanied the invertebrate-to-vertebrate transition, we produced a chromosome-scale genome assembly of amphioxus (the Florida lancelet Branchiostoma floridae). We combined existing shotgun data10 with new in vitro24 and in vivo25 chromatin conformation capture sequences that enable megabase-scale scaffolds to be accurately linked together to reconstruct chromosomes25 30—the most complete chromosomal assembly of a marine invertebrate until amphioxus, albeit with only 80% of genes assigned to linkage groups—shows the remarkable stability of bilaterian chromosomes. Many amphioxus and scallop are in 1:1 correspondence, and others are related by the limited rearrangements described below  is derived from the 17 ancestral CLGs through a handful of large-scale rearrangements. Twelve amphioxus chromosomes  are in 1:1 correspondence with CLGs and are therefore direct descendants of these ancestral units, albeit with extensive internal gene order rearrangement  typically descend from single CLGs  are found in four descendent copies in bony vertebrate genomes Fig. ; the rem37, followed by more or less extensive mixing. By parsimony, we infer that the CLG fusions shared by paralogous α and β copies predate the genome-wide duplication that produced these α–β pairs, as shown in Fig. P < 10−10; Methods).Second, Fig. ). The genomic duplication that produced the 1–2 pairs therefore must have preceded the α–β duplication. We also infer from Fig. Third, each CLG generally participates in two α–β pairs of bony vertebrate segments , we expect that gene losses should be evenly distributed across  duplicated chromosomes—a symmetry enforced by persistent tetrasomic inheritance immediately following autotetraploidy45. In contrast, allotetraploidization (genome doubling accompanying interspecific hybridization) is an inherently asymmetrical process that brings together the genomes of two progenitors with distinct epigenetic landscapes, cytonuclear interactions and histories of transposable element activity. Allotetrapoids are therefore expected to show an asymmetrical distribution of gene losses, as observed in palaeo-allotetraploid plants42 and frogs41.Remarkably, we can infer the mechanisms of the temporally distinct 1–2 and α–β duplications by examining the chromosomal distribution of vertebrate orthologues relative to the unduplicated amphioxus genome. In the aftermath of a genome duplication, most duplicated genes are rapidly lost, so that paralogous segments retain a subset of the original gene complement10, including well-known genes such as those in the Hox, Wnt and Fox families; see Methods). Instead, we observe a strikingly asymmetrical pattern in which genes are more than twice as likely to be retained on α segments than on paralogous β segments . High-retention α copies retain >25% of ancestral CLG content relative to amphioxus  while paralogous low-retention β copies retain <25% . The mean difference between the retention fractions of α–β pairs is significantly higher than a null model in which retention is uniformly random across pairs of chromosomes  in the jawed vertebrate lineage  via allotetraploidization. Since Putnam et al.10 and Venkatesh et al.47 previously found extensive syntenic conservation between the genomes of the elephant shark and some bony vertebrates, we infer that the palaeo-allotetraploidy described here in bony vertebrates had already occurred before the last common gnathostome ancestor. A strong prediction of our model is thus that, when fully characterized, cartilaginous fish chromosomes will show the patterns of CLG fusion described in Fig. 3 or two rounds of autotetraploidization11. Several studies based on gene trees suggested that two duplications preceded the lamprey–jawed vertebrate split14, although an earlier analysis could not resolve the position of the first duplication (1R) relative to this split10.Our auto- then allotetraploidization model Fig.  differs 49). One of the ensuing autotetraploid lineages gave rise to lampreys, which lack CLG fusions that are found across bony vertebrates  to give the jawed vertebrate ancestor.The 1R event shared by all vertebrates is analogous to the autopolyploidizations described in salmonids, cyprinids (carps and their relatives) and sturgeons  has persisted for tens of millions of years49. Detailed analysis of Hox-bearing chromosomes by Lynch and Wagner50 suggests that they experienced two chromosomal crossovers early in vertebrate evolution. Interestingly, the Hox gene clusters are found on CLGB, with HoxA and HoxD found on α segments and HoxB and C on β segments. However, unlike most other CLGs, we cannot uniquely pair specific α and β copies based on chromosomal linkage in the absence of a pattern of paired fusion involving CLGB. This suggests that the ancestral Hox-bearing chromosomes  could have experiences a prolonged period of homeologous interaction and exchange, consistent with Lynch and Wagner’s finding.Although many vertebrate gene families do not follow a doubly bifurcating pattern, as expected in a simple 2R scenario10, several previous studies based only on comparisons among vertebrate genomes have variously inferred the existence of 10–13 ancestral vertebrate chromosomes20. Comparisons among vertebrate genomes without reference to an outgroup such as amphioxus are likely to miss the fusions that we have documented here, since anciently fused regions appear as single conserved syntenic blocks in comparisons among jawed vertebrates. Neglect of the complex history of fusions and mixing after duplication, and the reduced power to detect significant conserved synteny among paralogous regions with extensive gene loss . Finally, the original proposal10 of 17 CLGs has found renewed support from analysis of the reconstructed ancestral amniote karyotype14. However, we note that this study used the non-chromosomal draft assembly of the amphioxus genome10 for its outgroup, and so made the same assumptions as ref. 10.Although here we have described 17 CLGs by comparing the chromosomes of amphioxus and vertebrates, confirming ref. 10 are stable chromosomal units and that relicts of these units are readily detectable as either intact micro-chromosomes or large chromosomal segments in vertebrates, amphioxus, and even molluscs. Second, the jawed vertebrate lineage experienced two temporally and mechanistically distinct genome-wide duplications. The first—an autotetraploidization (1R)—preceded the divergence of lamprey and jawed vertebrate lineages51 ~490 million years ago (Ma). On the jawed vertebrate stem lineage, 1R was followed by a series of chromosomal fusions that preceded a second genome-wide duplication. On the lamprey lineage, 1R was followed by fewer and largely distinct fusions. Other studies53 have suggested that additional large-scale duplication events occurred in the lamprey lineage . Disentangling these additional duplications specific to either the lamprey or cyclostome lineages will require further study. Third, the observation of asymmetrical gene retention implies that the second whole-genome duplication in the jawed vertebrate lineage (2Rjv) was an allotetraploidization (whole-genome duplication after interspecific hybridization). This second duplication preceded10 the divergence of bony and cartilaginous fish (~438–465 Ma)56. Our bounds on the timing of 1R and 2Rjv suggest that the extensive Ordovician diversification51 of early jawless and armoured fish (443–485 Ma) probably occurred during the period of diploidization after 1R, which was marked by chromosomal fusions and rearrangements that allowed new regulatory linkages to be explored. Hybridization of two related 1R descendants accompanied by genome duplication then established the lineage that subsequently gave rise to all living jawed vertebrates.Our analyses imply a novel scenario for vertebrate evolution and the events that shaped vertebrate genomes Fig. . First, To produce a chromosome-scale assembly of amphioxus, we (1) reassembled existing shotgun data and then (2) ordered and oriented the resulting assembly with in vitro and in vivo chromatin conformation capture data.57 to assemble the approximately tenfold redundant Sanger whole-genome shotgun sequence that was previously generated10 from a single diploid Florida lancelet (B. floridae). As in ref. 10, the two highly divergent haplotypes were assembled apart. For the present assembly, we resolved these diploid redundancies with HaploMerger2 (ref. 58) to produce a single reference haplotype for further analysis (Supplementary Note We used ARACHNE25) and in vivo (Hi-C) chromatin conformation capture libraries, as described in ref. 25 and Supplementary Note To achieve a chromosome-scale assembly of amphioxus, we obtained long-range linkages using in vitro  best BLASTp searches  as the synteny indicator vector of gene i that takes the value of 1 if the gene has its orthologue in chromosome a of the comparator, and 0 otherwise. To identify boundaries at which the conserved synteny changes, we computed the left and right windowed averages of the synteny indicator vector:We partitioned the amphioxus chromosomes into 17 CLGs using the data from Fig. i and i + 1. Using as comparators the vertebrates chicken, gar or frog, or the invertebrate scallop, and the window size W = 25, D shows spikes at discontinuous boundaries.The squared Euclidean norm of the difference D as intra-chromosomal boundaries in amphioxus between distinct patterns of conserved synteny. Consistent with the patterns seen in Fig. 10.We identified local peaks in 10. For the purposes of assessing the retention of gene duplicates after whole-genome duplication (see below), we counted only one gene family member per chromosome. With this counting, linked  gene duplications produced by local processes do not lead to increased retention values, but unlinked duplications plausibly created through chromosome or genome-scale events are counted.To allow for analysis of (unlinked) gene duplication in vertebrates relative to the chordate ancestor, we also constructed families of orthologous chordate genes through sequence-based clustering analyses, as described in ref. Visualization of the local CLG ancestry across vertebrate chromosomes Fig.  was base10 and later applied by Smith and Keinath13 in their comparison of lamprey linkage groups with jawed vertebrate chromosomes. The null hypothesis was that orthologous genes are randomly distributed across the two genomes, with a Bonferroni correction for the total number of pairwise tests. While Smith and Keinath13 used gene families defined by collecting high-scoring hits among lamprey and selected vertebrates, we used the 6,843 mutual best hits between amphioxus and each of the four bony vertebrates: spotted gar, chicken, frog and human. Mutual best hits provide a conservative set of orthologues. For mutual best-hit orthologues, the equivalent null distribution for the distribution of orthologues shared between chromosomes (or between windows within chromosomes) is hypergeometric  between CLGs and 50-gene windows; whereas plus signs indicate significance using 50-gene windows (P < 0.05), 100-gene windows (P < 0.01) and/or at the whole chromosome level (P < 0.05). Rows of Fig. Based on Figs. After genome duplications, unlinked duplicates may be lost. The retention fraction for a CLG on a vertebrate chromosome or chromosome segment is defined as the ratio of the number of CLG orthologues  found on that chromosome to the number of CLG-defining genes in amphioxus. Since a gene can be retained in multiple unlinked copies, the total retention of a CLG across all chromosomes of a vertebrate species can exceed one. As noted above, gene families are defined such that linked duplicates (arising by tandem duplication) are not counted towards the retention fraction; only unlinked duplicates are relevant for analysis of whole-genome duplications except in special circumstances of translocations that combine paralogous chromosomes from the same CLG on the same vertebrate chromosome. These translocations are identified by parsimony and comparison among vertebrate genomes, as described in the main text.To assess the significance of the difference between paired high- and low-retention classes, we compared the high and low means across the spotted gar and chicken against a null model in which retention rates in cells of Fig. Further information on research design is available in the Supplementary InformationSupplementary notes 1–7.Reporting SummarySupplementary TablesSupplementary Tables 1–7.


In our study we developed a set of statistical tools to systematically assess coverage of coding regions provided by several modern WES platforms, as well as PCR-free WGS. We identified a substantial problem in most previously published comparisons which did not account for mappability limitations of short reads. Using regression analysis and simple machine learning, as well as several novel metrics of coverage evenness, we analyzed the contribution from the major determinants of CDS coverage. Contrary to a common view, most of the observed bias in modern WES stems from mappability limitations of short reads and exome probe design rather than sequence composition. We also identified the ~ 500 kb region of human exome that could not be effectively characterized using short read technology and should receive special attention during variant analysis. Using our novel metrics of sequencing coverage, we identified main determinants of WES and WGS performance. Overall, our study points out avenues for improvement of enrichment-based methods and development of novel approaches that would maximize variant discovery at optimal cost.Advantages and diagnostic effectiveness of the two most widely used resequencing approaches, whole exome (WES) and whole genome (WGS) sequencing, are often debated. WES dominated large-scale resequencing projects because of lower cost and easier data storage and processing. Rapid development of 3 Practical use of NGS methods has dramatically increased with the development of targeted sequencing approaches, such as whole-exome sequencing (WES) or targeted sequencing of gene panels. WES emerged as an efficient alternative to whole-genome sequencing (WGS) due to both lower sequencing cost and simplification of variant analysis and data storage4. More than 80% of all variants reported in ClinVar, and more than 89% of variants reported to be pathogenic, come from the protein-coding part of the genome; this number increases to 99% when immediate CDS vicinity is included. Even allowing for the sampling bias, there is an overall agreement that most heritable diseases appear to be caused by alterations in the protein-coding regions of the genome. Given this, WES has dominated the projects characterizing human genome variation as well as clinical applications.Next-generation sequencing (NGS) is rapidly becoming an invaluable tool in human genetics research and clinical diagnostics5 could not statistically characterize many of the rare variants critical to diagnostics of Mendelian disease due to a limited sample size. In an attempt to get a representative picture of protein-coding variation in human population, 6,500 WES samples were sequenced during ESP6500 project6. When a much larger reference set of 60,706 WES experiments was compiled and uniformly processed by the Exome Aggregation Consortium (ExAC)7, it dramatically increased the accuracy of allelic frequency (AF) estimation in general population. This led to a surprising conclusion that up to 90% of variants reported as causative for Mendelian disease in ClinVar database are observed too often in healthy controls to directly cause disease7. The number of available WES experiments is rapidly increasing, and the latest Genome Aggregation Database (gnomAD) collection includes 123,136 WES experiments alongside with 15,496 WGS. Such impressive number of profiled individuals allows a much more thorough look at human coding genome variation, leading to many useful applications such as estimation of selective pressure across protein-coding regions8.The pioneering 1000 Genomes project11. A later study comprised most hybridization-based capture technologies available at the time12, and showed specific features of each of the four exome kits, including GC-content bias and differences in the distribution of coverage. Similar observations were made in one of the most recent comparative studies13. However, these and other earlier works on the topic included very limited number of samples, often with large variation of sequencing depth, which may have interfered with consistent platform comparison. Only one of the recent studies included larger amount of samples that allowed to identify tendencies in cross-sample coverage unevenness14.Several published studies have concentrated on comparing the performance of different exome capture technologies, or comparison between WES and WGS. With the emergence of commercial exome kits, three major manufacturers - Agilent, Illumina, and Nimblegen (Roche) - have become popular among users, representing the majority of all published WES studies. Early comparative studies have focused on comparison of target intervals of various exome kits, and identified several important biases inherent to WES technology, such as coverage biases in regions with very high or low GC content15. Similarly to earlier studies10, it was found that WES achieves similar percentage of well-covered CDS bases only when the average coverage is 2–3 times higher, and with a substantial sequence bias. In several more recent studies, it was repeatedly stated that WGS provides more even and unbiased coverage of coding regions and generates more accurate variant calls17.It is often assumed that WGS offers more uniform coverage of CDS regions due to the nature of hybridization-based enrichment process used in WES. Such differences in coverage evenness increase the costs of effective per-base coverage in WES, questioning the overall benefit from using WES instead of WGS. Hence, the issue of WES/WGS comparison has been addressed by several studies that sought out optimal sequencing method to achieve maximum coverage of the protein-coding regions of the genome , while for MedExome and Nextera Rapid the dependence is much more pronounced (R2 = 0.360 and R2 = 0.815)  less than 10 and reads marked as PCR or optical duplicates; thus, such reads were removed when calculating coverage. All WES samples irrespective of the platform showed 50–70% efficiency of target enrichment and a similar distribution of sequencing depths across our WES dataset Fig. , corresp15) Fig. .Figure 1et al.20 (see Methods). Normalized coverage profiles and OE scores showed that both Illumina kits perform significantly worse than SureSelect and MedExome, while all exome platforms provided less even coverage than PCR-free WGS , with exception for SureSelect, that had mean coverage of ~120x Fig. . We thenWGS Fig. .To dissect potential sources of coverage bias we defined two possible components of coverage evenness: coverage distribution between different CDS regions , and uniformity of coverage within individual intervals . The latter type of coverage unevenness is inherent to WES platforms; hence, we first questioned whether it explains the difference between WES and WGS in the OE scores. Indeed, visual inspection of coverage profiles on individual CDS regions suggests that exome platforms highly vary in WIE Fig. . To moreTo more thoroughly characterize the capabilities and limitations of resequencing approaches, we have constructed a model to predict sequencing coverage of CDS regions that accounts for both between- and within-interval evenness (see Methods). Quite surprisingly, model-based prediction of the amount of bases covered at less that 10x at different mean coverages showed that all platforms, including WGS, have a certain amount of bases that are not covered at the required depth even at 200x average coverage Fig. . For comWe first evaluated the reproducibility of normalized coverage profiles for each technology. To this end, we estimated the correlation of per-interval normalized coverages across all samples for each technology. As seen from Fig. 13. We calculated normalized coverage at ~180,000 ClinVar variant sites divided into 10 deciles dependent on GC-content of 100 bp variant vicinity, and found that both Nextera Rapid and TruSeq Exome capture kits performed worse than the others in GC-rich regions and better in the AT-rich ones . We conservatively defined multimapping fraction (MF) as the proportion of sequencing coverage that results from reads with MQ = 0. We then calculated MF for each exome base-pair and for individual CDS regions, and analyzed the amount of bases or intervals with high MF . On avesis Fig. , Fig. 3dsis Fig. ; and thesis Fig. . In agresis Fig. . OverallFinally, we questioned whether a substantial proportion of CDS regions with low normalized coverage in WES samples is simply not targeted by the capture probes. We first evaluated the intersection of target regions of each WES kit and CDS intervals  (see Methods) with the bait design files for each WES technology, and calculated the fraction of poorly covered bases not overlapping target regions. Our analysis showed that for most platforms a large fraction of poorly covered bases falls into non-targeted regions of the exome Fig. . It is aIn order to compare the relative importance of different factors influencing CDS coverage, we fitted a linear regression model to predict normalized per-interval coverage depending on GC-content, interval length, multimapping fraction, and inclusion of the interval into the exome kit design. Analysis of the model showed that for SureSelect and Roche MedExome platforms multimapping fraction and inclusion are the most important predictors of normalized coverage, while GC-content is the major determinant of coverage for both Illumina kits. Importantly, the relative importance of GC-content was substantially decreased when using a linear classifier of poorly covered CDS regions  Fig. . Even mo22. Our analysis only accounts for chromosomal parts of the 1000 Genomes assembly , which is most often used for variant calling. Including alternative contigs  - a fatal neurological disorder with an early age of onset. Indeed, we found that for seven out of eight exons  inside SMA genes all coverage results solely from reads with zero mapping quality in both WES and WGS .We also statistically assessed the effect of mappability limitations on variant discovery. To this end we first calculated variant site density (VSD) (based on ExAC dataset) for each b37 CDS region and assessed the relationship between such variant site density and MF. We observed that regions with higher values of MF (~0.4 and higher) contain fewer variant sites per base-pair compared to the rest of the exome  and 751 ± 34 kb (for best WES) of CDS regions unreachable for sequencing technologies. The problem of low-mappability regions is known; for some of the genes with poor mappability, complex statistical methods have been proposed to determine genotype likelihoodsble Fig. , includiWGS Fig. .It is important to note that variant calling for WES samples should not be restricted to targeted intervals and should rather include targeted intervals, CDS regions, UTR sequences and bases flanking CDS to improve the power of variant discovery Fig. . Overallet al.23 suggested that WGS is more efficient than WES only by 2% of diagnosis rates on aggregate. Our observations suggest that WGS allows for more efficient coverage of only 1% of exome compared to best WES platforms, complementing the fact that only a small fraction of reported ClinVar pathogenic variants are not targeted by exome kits. Moderate rates of NGS-based diagnostics of monogenic diseases are likely explained by the lack of biological understanding of variant pathogenicity25. This, in turn, diminishes the role of technical WGS benefits, such as ability to identify numerous regulatory variants in intronic and intergenic regions. In many cases, annual re-analysis of undiagnosed samples using new biological data improves diagnosis rate26. Value of WGS will undoubtedly increase with better understanding of human genome regulation.A recent review by Wright rd generation methods become more widely adopted, one could envisage combinatorial methods that would benefit from long-read power of complex variant discovery, combined with high accuracy and cost efficiency of WES.Several lines of evidence indicate that modern WES remains an excellent alternative to WGS in research and clinical applications. Moreover, current WES technologies can be further improved in several ways: first, support for longer insert sizes would decrease the impact of both mappability and WIE; second, inclusion of all currently annotated CDS regions to make coverage more comprehensive; and third, better probe design and improvement of hybridization process would alleviate remaining unevenness resulting from GC-content or other sequence-based determinants. In fact, the most recent WES solutions  are reported to perform substantially better than NR or TS kits analyzed in this work, making WES samples approach WGS in terms of coverage distribution and eventually minimizing the diagnostic gap between WES and WGS approaches. When 3Peripheral venous blood samples were collected in EDTA from 167 patients with endocrine diseases, hereditary connective tissue disorders, orphan diseases and individuals from the control group. DNA was extracted with QIAsymphony automated station for the isolation of nucleic acids and proteins. The study was approved by the Review Board of Saint-Petersburg City Hospital No. 40  and Biobank of Center for Preventive Medicine , Moscow. All patients gave informed consent for blood sampling, research, processing of personal data and storage of biological materials before collecting the samples and processing the medical history data. The study was performed in accordance with the Declaration of Helsinki.After DNA extraction, we prepared whole exome libraries with Illumina Nextera Rapid Capture Exome (24 samples), Nimblegen (Roche) SeqCap EZ MedExome (43 samples), Illumina Truseq Exome (72 samples), and Agilent Sureselect XT2 V6 technologies (28 samples).1 µg of human DNA in 1x Low TE buffer (pH = 8.0) was used as a starting material and sheared on Diagenode BioRuptor UCD-200 DNA Fragmentation System to the average DNA fragment size of 170–180 bp. The shearing conditions were as follows: L-mode, 50 minutes of sonication cycles consisting of 30 s sonication and 30 s pause. Library preparation and exome capture were performed using SeqCap EZ MedExome Kit  following the SeqCap EZ Library SR User’s Guide, v5.1 without modification. DNA libraries were amplified using 7 PCR cycles, and 14 PCR cycles were performed for amplification of enriched libraries. Library quality was evaluated using QIAxcel DNA High Resolution Kit on QIAxcel Advanced System.Library preparation and exome capture were performed following the Nextera Rapid Capture Enrichment guide v. 15037436  without modifications. 50 ng DNA was used as a starting material and 10 cycles of PCR were performed for pre-enrichment and post-enrichment PCR steps. Library quality was evaluated using QIAxcel DNA High Resolution Kit on QIAxcel Advanced System.300 ng of human DNA in 100 μl of 1x TE buffer (pH = 8.0) was used as a starting material and sheared on Diagenode BioRuptor UCD-200 DNA Fragmentation System to the average DNA fragment size of 200 bp. The shearing conditions were as follows: L-mode, 45 minutes of sonication cycles consisting of 30 seconds sonication and 30 seconds pause. Shearing results were evaluated using QIAxcel DNA High Resolution Kit on QIAxcel Advanced System. Several (1–10) additional sonication cycles were performed to reach the desired 200 bp DNA fragment size peak, when needed. 100 ng of sheared DNA was used as a starting material for library preparation. Library preparation and exome capture were performed using TruSeq Exome Library Prep Kit following the standard TruSeq Exome Library Prep Reference Guide (Illumina Document # 15059911 v01). Library quality was evaluated using QIAxcel DNA High Resolution Kit on QIAxcel Advanced System.2 µg of human DNA in 100 μl of 1x Low TE buffer (pH = 8.0) was used as a starting material and sheared on Diagenode BioRuptor UCD-200 DNA Fragmentation System to the average DNA fragment size of 150–200 bp. The shearing conditions were as follows: L-mode, 60 minutes of sonication cycles consisting of 30 seconds sonication and 30 seconds pause. Shearing results were evaluated using QIAxcel DNA High Resolution Kit on QIAxcel Advanced System. Library preparation and exome capture were performed following the SureSelectXT Target Enrichment System for Illumina Multiplexed Sequencing Protocol  for 3 µg of starting DNA. Library quality was evaluated using QIAxcel DNA High Resolution Kit on QIAxcel Advanced System.Illumina HiSeq 2500 and Illumina HiSeq. 4000 platforms were used for sequencing. Each exome library was sequenced using 101 bp (HiSeq 2500) or 150 bp (HiSeq 4000) paired-end reads. All WES samples satisfied the ExAC criterion of minimum 80% of CDS bases with 20x coverage.27. WGS libraries were prepared using TruSeq DNA PCR-Free LT Library Prep Kit  according to the manufacturer’s protocol. Additionally we used PCR-free WGS data of the Genome In A Bottle (GIAB) consortium28 (Chinese and Ashkenazi trios), as well as several samples publicly available at the NCBI Sequencing Read Archive (SRA) . For GIAB samples, we used pre-calculated Novoalign BAM files available at the GIAB FTP site (ftp://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/). For our own WGS samples and samples downloaded from SRA, we used bwa mem v0.7.1 for read alignment. All BAM files were narrowed down to the GENCODE v19 CDS regions using bedtools29. We further downsampled the 300x BAM file for GIAB sample HG001 to obtain 5 separate BAM files with 60x mean coverage or 10 BAM files with 30x mean coverage  and Genome Analysis ToolKit (according to the GATK Best Practices workflow32). Sample genotyping was done in a cohort calling mode using GATK HaplotypeCaller. Variant calling was restricted to either bait regions for each technology or the CDS regions (see Results). Variants were filtered using Variant Quality Score Recalibration . Annotation and subsequent filtration of variants was done using SnpEff and SnpSift tools followed by automated correction of reference minor alleles by RMA Hunter33. Hybrid selection metrics were calculated using CollectHsMetrics tool in the PicardTools package. Alignment data visualization was carried out in the Integrated Genomics Viewer (IGV)34.For all exome and genome samples, bioinformatic analysis of sequencing data was done using a pipeline based on bwa mem29. Reference GENCODE v19 genome annotation (http://gencodegenes.org/)35 was used for these estimations. Only chromosome located CDS regions of protein-coding genes were used in the analysis. We also used ClinVar database of variants implicated in human disease (build 2018-04-01) to assess coverage of important variant sites36.To analyze the proportion of CDS and UTR sequences covered by each technology’s declared design file, we used the bedtools packagehttps://github.com/bioinf/weswgs. We also calculated multimapping fraction (MF) for each sample and for each CDS region by subtracting mean coverage after filtering by mapping quality (MQ > 10) from mean coverage before such filtering.Modern best practices advise using GATK toolset for variant calling, which ignores reads with mapping quality (MQ) less than 10 and reads mapped as duplicate by Picard MarkDuplicates utility. Thus, all coverage calculations were done on BAM files with duplicate reads and reads with MQ < 10 removed. Exact coverage calculation pipeline is available at https://github.com/bioinf/weswgs). To collect normalized coverage profiles for each platform, BAM files were converted to a bedgraph format using bedtools. Next, the bedgraph file was intersected with the CDS regions according to GENCODE v19 genome annotation or the declared target regions for each technology. To calculate the coverage evenness and profiles of per-base normalized coverage we used the resulting bedgraph files to obtain fractions of bases having normalized coverage of at least N with N ranging from 0 to 3 with step 0.01. Overall evenness score was calculated as described20.To analyze the distribution of coverage across target regions, as well as between-interval evenness (BIE) and within-interval evenness , we used a combination of bedtools package and custom scripts in bash and Python , mean sequencing depth was calculated for each interval. These coverage values were then processed similarly to per-base coverages. Between-interval evenness (BIE) measure was calculated similarly to the OE from the profiles of normalized mean coverages of individual intervals.For calculation of the within-exon coverage distribution, all intervals having an average coverage of more than 10x in a sample were then divided into 100 bins of equal bp length. We then calculated normalized (divided by the mean coverage of a fragment) coverage in each bin. Then, mean coverage at each bin across all of the intervals was calculated for each sample. Within-interval evenness  was defined as the area under within-interval normalized coverage curve i is the bin number , and xi is the normalized coverage in this bin.where https://github.com/bioinf/weswgs). To calculate the mean coverage of variant sites depending on the GC-content of variant site neighborhood we selected 180452 known variants from the ClinVar database of clinically significant variants, and divided these variant sites into 10 equal groups depending on the GC-content  of the region 50 bp up- and downstream of the variant. We then calculated the read depth at all resulting variant sites using bedtools multicov.To calculate the allele ratio distribution and the distribution of total and low genotype quality (lowGQ) variants, we used the VCF file resulting from the cohort genotyping of samples, and scripts written in Python (available at M) of each individual CDS region in all samples sequenced with a particular technology, as well as the standard deviation (s) of this mean. We next predicted the amount of base-pairs with low (<10x) coverage . The resulting normalized coverage of each base-pair ij were used to calculate absolute read depth (Dij) at position j in interval i:Dij < 10) was then calculated for a range of exome average depths D = .We then calculating per-base normalized coverage by multiplication of Mi,, si) and the threshold value (0.1 or 0.2) using one-sample t-test with Holm-Bonferroni FDR correction.To obtain a list of intervals that systematically have poor sequencing coverage for each technology . Additionally, we selected a set of 10 samples for each technology and calculated the total length of intervals that have low (<0.1) normalized coverage in (a) any of the selected samples (“union”); and (b) all of the selected samples (“intersection”). We then calculated the intersection-to-union ratio (R) as the measure of coverage reproducibility:37. Model testing was performed using 5-fold cross validation, accuracy and kappa-statistic values were used to select the best model. For RF classification, a model with mtry = 2 was selected. Tuning was performed using the default number of trees in the ensemble. For all models, predictor importance was analyzed using the default measures for linear and RF models provided in the ‘caret’ package.To assess the relative importance of different variables for prediction of normalized per-interval coverage, we used several machine learning models for both regression and classification tasks. For regression, we fitted a simple linear model describing mean per-interval coverage depending on GC-content, interval length, multimapping fraction, and a binary variable indicating inclusion of the interval into the exome design. For linear classification, we trained a logistic regression-based classifier to predict a binary variable indicating a normalized coverage <0.1 using the same variables as predictors. Similar setup was used for random forest (RF) classifier. All machine learning-based analyses were done using the ‘caret’ package7 were used to make statistical assessment of variant density. Each exome interval was annotated with the number of ExAC variant sites that fall inside this interval using bedtools intersect. Next, variant counts were transformed to per-nucleotide variant site density, and the resulting dataset was used for sampling procedures.Exome Aggregation Consortium (ExAC) variant calls (v. 0.3.1)38 v3.2.1 and cowplot v1 packages. Scripts for data analysis and figures, as well as the processed data, can be found at https://github.com/bioinf/weswgs.All statistical analyses were carried out using R v3.6. All machine learning analyses were done using caret v6.0-84. All graphs were plotted using ggplot2Supplementary Figures S1-S10.Supplementary Table S1.Supplementary Table S2.Supplementary Table S3.


Using a non-human primate model of the autoimmune neuroinflammatory disease multiple sclerosis (MS), we have unraveled the role of B cells in the making and breaking of immune tolerance against central nervous system myelin. It is discussed here that B cells prevent the activation of strongly pathogenic T cells present in the naïve repertoire, which are directed against the immunodominant myelin antigen MOG (myelin oligodendrocyte glycoprotein). Prevention occurs via destructive processing of a critical epitope (MOG34-56) through the lysosomal serine protease cathepsin G. This effective tolerance mechanism is abrogated when the B cells are infected with Epstein–Barr virus, a ubiquitous γ1-herpesvirus that entails the strongest non-genetic risk factor for MS. Callithrix jacchus), a small bodied Neotropical primate, we have explored how pathogenic T cells specific for the pathogenically relevant myelin antigen myelin oligodendrocyte glycoprotein (MOG)  while ignoring components from the host’s body (self antigens). The thymus has a central role in this process, as T cells competent to react against self are eliminated from the repertoire via negative selection, while T cells recognizing non-self antigens presented by the host’s major histocompatibility complex (MHC) molecules are allowed to enter the repertoire via positive selection Nossal . NeverthCallithrix jacchus) is a validated animal model of the human autoimmune neuroinflammatory disease MS   directed against the B lineage specific marker CD20 has a profound clinical effect in MS, the B cell has gained profound interest as a relevant target of therapy , developed an inflammatory demyelinating autoimmune disease that shows remarkable clinical and pathological similarities with MS  with a clonal variant of the clinically tested anti-CD20 mAb ofatumumab-suppressed clinical EAE development in marmosets sensitized against the full-length rhMOG protein  has narrow chymotrypsin-like specificity for some aromatic amino acids (Phe and Tyr), cathepsin G of humans (Ala189/Glu226) has a broader specificity range, including also Arg, Leu, His, Trp, Lys, and Met. The paper claims that cathepsin G of marmosets (Thr189/Ala226) has similar narrow chymotryptic activity as the mouse protease. Nevertheless, we observed that the degradation of the MOG34-56 peptide was abrogated when the Arg residues at positions 41 and 46 (underlined) were replaced by citrulline, despite the presence of at least three additional potential cleavage sites (bolded): GMEVGWYRPPFSRVVHLYRNGKD  represents the epitope of MHC-Ib/Caja-E-restricted CD8+ CD56+ T cells that accelerate EAE progression in the rhMOG/CFA model and forms the core pathogenic activity in the MOG34-56/IFA model  sequence  activity and the activation of autophagy  degraded, especially when autophagy was boosted with rapamycin  via which the peptide may bind to LC3, a docking molecule for specific sequestration of cargo in autophagomes (Birgisdottir et al. 46 residue may abrogate the autophagy escape route from cathepsin G exposure in phagolysomes, while conversion of this residue into citrulline abolishes cleavage and enables association of the peptide with autophagosomes ('t Hart et al. These considerations prompted a next set of experiments in which we tested proteolytic degradation of native and citrullinated MOG34-56 peptide in two preparations of human B cells, respectively, naïve B cells stimulated with CpG oligonucleotides that activate them via TLR9 or B lymphoblastoid cells infected with EBV (Morandi et al. 41 and Arg46 residues are essential contact points for binding of the epitope to the antigen receptor of encephalitogenic CD4+ T cells and that citrullination at these positions abrogates T cell recognition (Carrillo-Vico et al. 46 residue, while this modification may abrogate T cell recognition. We asked therefore whether there might be another pathogenic mechanism at work in the model.A study in the mouse EAE model revealed that the ArgTo test this possibility, we used a version of the peptide that could be visualized during and after the incubation with B cells via tagging a fluorochrome. This was achieved by coupling propargylglycine as a bioorthogonal handle to a slightly elongated variant of the MOG34-56 peptide, i.e., 31–55. Figure Despite decades of intensive research, scientists have only superficial understanding of the critical processes in MS pathogenesis. Valuable insights can be gained from immunotherapy studies and by investigating the biological underpinning of MS risk factors, as these are very likely connected to rate-limiting steps in the disease process. The recognition that infection with EBV substantially enhances the risk of developing MS in genetically prone individuals (Ascherio and Munger 46 by citrulline, which enables association of the EAE inducing MOG34-56 peptide with autophagosomes. We hypothesized that via this route, the vulnerable MOG40-48 epitope may be protected against fast endolysosomal degradation by cathepsin G and that its loading onto Caja-E molecules may be promoted (‘t Hart et al. Our research in the well-validated and translationally relevant marmoset EAE model revealed a central role of B cells in the control of autoimmunity against MOG, which seems to be exerted via destructive processing of the CD8 T cell epitope MOG40-48 by cathepsin G. This essentially tolerogenic mechanism is abolished when the B cells are infected with EBV. Analysis of the underlying mechanism revealed that the infection induces a post-translational modification in the epitope, i.e., replacement of ArgSummarizing, we posit an important tolerogenic function of cathepsin G in the marmoset EAE model, namely to prevent the B cell-mediated activation of hazardous T cells by destroying their MOG40-48 autoantigen epitope during processing. Infection of the B lymphocytes with EBV induces cellular mechanisms, citrullination and autophagy, which protect the epitope against fast degradation, thereby enabling presentation to T cells. It would be highly interesting to test whether this principle can be extended to other autoantigens critical in other autoimmune diseases.


Periodic paralyses are a group of disorders characterized by episodes of muscle paralyses. They are mainly divided as primary (hereditary) and secondary (acquired) periodic paralyses. Primary periodic paralyses occur as a result of mutations in genes encoding subunits of muscle membrane channel proteins such as sodium, calcium, and potassium channels, resulting in impairment of their properties. Primary periodic paralyses are further classified on the basis of affected ion channels and other associated complications. Some of these periodic paralyses are hyperkalemic periodic paralysis (Na-channel mutation), hypokalemic periodic paralysis (Na- or Ca-channel mutation), Andersen’s syndrome (K-channel mutation), etc. Periodic paralyses are a group of heterogeneous disorders characterized by flaccid paralysis and episodic attacks of muscle weakness. Periodic paralyses are mainly classified as primary and secondary periodic paralyses. Primary periodic paralyses are hereditary in which genes encoding channel protein subunits of skeletal muscle membrane are mutated, such as the muscular sodium, potassium or calcium channels, or the SCL4A1 protein . The objective of this study is to review the etiologies and pathogeneses of primary periodic paralyses and discuss other related aspects.Etiologies and pathogeneses of primary periodic paralysesPrimary periodic paralyses are caused due to mutations in genes encoding subunits of channel proteins of skeletal muscle membrane or endoplasmic reticulum like sodium, potassium, and calcium channels . FollowiSodium ChannelsThe muscle membrane sodium channels, extremely crucial for muscle membrane potentials, are composed of an α‐subunit and a β‐subunit . α‐SubunCalcium ChannelsThe human calcium channels CACNL1A3) are composed of five subunits  and play an important role in excitation-contraction coupling through its association with ryanodine receptors of the endoplasmic reticulum. They act as calcium release channels and regulate intracellular calcium levels in response to changes in membrane potential. A mutation in genes that encode muscle calcium channels causes hypokalemic periodic paralysis [A3 are coPotassium ChannelsThe potassium channels are composed of four subunits arranged as mono‐ or heteromers forming a central ion-conducting pore. These channels are found in skeletal muscles, heart, and brain and are responsible for the maintenance of resting membrane potential playing an important role in repolarization and hyperpolarization required in myoblast fusion. A mutation in the potassium channel gene located on chromosome 17 results in Andersen-Tawil syndrome, causing hyperexcitability followed by inexcitability of skeletal muscle membrane .Primary periodic paralyses are of various types differentiated on the basis of different gene mutations and channel proteins affected by these mutations. Several different types of primary periodic paralysis include hypokalemic, hyperkalemic, Anderson’s Syndrome, paramyotonia congenita, CMS, etc. .Hyperkalemic periodic paralysisHyperkalemic periodic paralysis is an autosomal dominant disease in which individuals suffer from paralytic episodes in limbs and high serum potassium levels (>5 mmol/L) . These ePathogenesisSeveral different mutations may be responsible for hyperkalemic periodic paralysis. The most common mutation occurs in skeletal muscle sodium channel gene SCN4A on chromosome 17. As a consequence, fast inactivation of sodium channels is either incomplete or slowed down abnormally enhancing sodium flow making muscle fibers more incline to depolarization. This prolonged depolarization is the reason why these individuals experience muscle weakness and myotonia. High extracellular potassium level causes mild depolarization of muscle fibers that keeps mutant sodium channels in the active state causing repetitive muscle action potentials which are perceived as myotonia. If the depolarization becomes more extensive, both normal and mutant sodium channels are held in a closed state stopping all the action potentials that leads to muscle paralysis and weakness [Hypokalemic periodic paralysisHypokalemic periodic paralysis, the most common periodic paralysis, is an autosomal dominant disorder characterized by episodes of flaccid muscle weakness lasting several hours to few days and low serum potassium level (<3.5 mmol/L) ,7. The fPathogenesisHypokalemic periodic paralysis occurs as a result of a mutation in the α‐subunit of the DHP‐receptor CACNA1S) gene on chromosome 1 or the α‐subunit of the sodium channel (SCN4A) gene on chromosome 17 [S gene onAndersen-Tawil syndromeAndersen-Tawil Syndrome  is an uncommon hereditary autosomal dominant disorder characterized by episodes of flaccid paralysis, with space of an hour to few days between each episode, along with complications like cardiac arrhythmias  and several physical deformations  . Other uPathogenesisAndersen’s syndrome occurs as a result of a mutation in gene KCNJ2 located on chromosome 17 encoding potassium channel Kir2.1 . The mutParamyotonia congenitaParamyotonia congenita is an autosomal dominant disorder characterized by persistent non-progressive myotonia and muscle weakness mainly in eyelids, neck, and upper limb muscles, which is induced by cold temperature and further worsened by exercise . These ePathogenesisParamyotonia congenita is caused by mutations in gene SCN4A located on chromosome 17 encoding skeletal muscle sodium channels. Voltage-sensitive part of domain IV is the most affected location; others including the cytoplasmic surface of transmembrane segments S2, S3, and S4. The most typical cause of paramytonia congenita is mutation segment S4 in which arginine is replaced by other amino acids nullifying its positive charge. These mutant channels are stabilized in an inactive state by low temperature, which explains the temperature sensitivity of the disease [Congenital myasthenic syndromeCMS is a heterogeneous hereditary disorder characterized by episodes of respiratory or bulbar paralysis and generalized muscle weakness. Other complications include facial weakness, ptosis, feeding difficulties, poor suck, and even arthrogryposis. Cardiac and smooth muscles are not affected. Complications start appearing at birth or soon after with varying severities .PathogenesisCMS is caused by mutations at several genes encoding proteins of the myoneural junction. These include several subunits of the acetylcholine receptor , the collagenic tail subunit of the acetylcholinesterase (COLQ), choline acetyltransferase (CHAT), rapsyn (RAPSN), or sodium channel .This review summarizes the causes of various types of primary periodic paralyses and shines light over their complications, inducing factors, and pathogenesis at the gene level. Yet, the mechanism of their pathophysiologies is not completely understood and is needed to be studied in greater detail in future studies to completely dissect the root causes of these disorders to help mask severe complications or completely eradicate the disease.


Enhancing virus multiplication could assist in the rapid production of vaccines against viral diseases. Cold atmospheric plasma (CAP), a physical approach relying on reactive oxygen species to achieve the desirable cellular outcome, was shown to be effective in enhancing virus propagation, where bovine rhinotrachieitis virus and Madin-Darby Bovine Kidney cells were used as the modeling virus and cell line, respectively. CAP was shown to create synergies with virus infection in arresting host cells at the G2/M stage, decreasing cell membrane potential, increasing intracellular calcium level, and inducing selective autophagy. In addition, CAP was demonstrated to suppress virus-triggered immunogenic signaling as evaluated by IRF7 expression. We presented evidences on CAP-triggered maximization of host resources toward virus multiplication that is advantageous for viral vaccine production, and opened a novel regime for applying CAP in the sector of medical care and health. Vaccine has long been considered as an effective approach for viral disease prevention and control, especially during an epidemic outbreak such as Coronavirus Disease 2019 (COVID-19) that is caused by Syndrome Coronavirus 2 (SARS-CoV-2) and currently threatening global health . Thus, it was possible that IBRV entry modified cell surface and thus reduced H2O2 entry, and the other components of CAP-triggered cellular signaling that led to reduced IRF3/7 expression. Though enhanced CAP efficacy as a result of quenching H2O2 provides certain experimental evidence, this hypothesis is, however, subjected to rigorous experimental tests before being considered true.Compromised immunogenic signaling protects virus-infected cells against immune cell recognition and thus is favorable for virus propagation. We found that CAP reduced the enhanced level of IRF3/7 on IBRV infection while increasing IRF3/7 in normal cells . On the e I IFNs . Interesenhanced . Thus, tt oxygen . In addiThough these events are all associated with the oxidative nature of CAP, no CAP component could replace CAP in boosting virus titer, as CAP components may interact with each other and with cell surface to initiate an avalanche of cell signaling that could not be simplified as just oxidation.We demonstrated in this paper that CAP could halt the cell cycle at the G2/M stage and trigger selective autophagy to maximize cell resources for virus multiplication, and suppress immunogenic signaling as represented by IRF3/7 expression to maintain an environment favorable for host survival. Thus, CAP represents a potential tool for enhancing vaccine production against viral diseases that deserves intensive efforts to explore mechanisms driving its synergies with virus infection.Click here for additional data file.


Objective: This study was aimed at investigating the regulation of mitochondrial function by histone deacetylase 6 (HDAC6) and the role of HDAC6 in the development and progression of sepsis.Results: HDAC6 downregulated PHB1 and subsequently promoted the development of CLP-induced sepsis. Inhibition of HDAC6 significantly attenuated CLP-induced sepsis through inhibition of mitochondrial dysfunction and reduced oxidant production, thus protecting the rats from oxidative injury.Conclusions: In this sepsis model, HDAC6 inhibits the expression and function of PHB1 and alters the function of the mitochondrial respiratory chain mediated by PHB1, thus enhancing the production of oxidants and increasing oxidative stress and thereby leading to severe oxidative injury in multiple organs.Methods: The expression of HDAC6 and prohibitin 1 (PHB1) in humans and in a rat model of sepsis was measured by quantitative reverse-transcription PCR and western blotting. Sepsis induction by cecal ligation and puncture (CLP) was confirmed by histological analysis. Concentrations of different sepsis markers were measured by an enzyme-linked immunosorbent assay, and mitochondrial function was assessed via the mitochondrial respiratory control rate. Sepsis is a systemic inflammatory response syndrome caused by infection and is considered to be the major cause of death among patients in intensive care units owing to its relatively high morbidity and mortality rate –3. It caOxidative stress, caused by inflammatory responses, is a known consequence of sepsis , 7, and HDAC6 is a member of the cytoplasmic class IIb histone deacetylase (HDAC) family. It deacetylates nonhistone proteins , includiPHB1 is located in chromosomal region 17q21, and encodes a 30 kDa protein that associates with prohibitin 2 (PHB2) to form 16–20-mer ringlike structures that perform chaperone or scaffolding activities within the mitochondria  expression) as compared to that in uninfected control cells  to treat the rats with CLP-induced sepsis, and then evaluated possible signs of tissue pathology. Tri A treatment significantly alleviated sepsis-associated lung injury in rats with CLP-induced sepsis in comparison with that in untreated septic rats , hydrogen peroxide (H2O2), and hydroxyl radicals (OH·) are generated in low amounts. As a mitochondrial protein, PHB1 plays an important role in cell proliferation, apoptosis, gene transcription  − ΔCt[Target gene]).As described previously , total Rg for 30 min at 4°C. The samples were then boiled in sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) loading buffer for 10 min and subjected to SDS-PAGE in a 10% gel, before transfer onto nitrocellulose membranes . The membranes were probed with primary antibodies overnight at 4°C and then with horseradish peroxidase–conjugated secondary antibodies. Bands were visualized by means of an Enhanced Chemiluminescence Substrate .As described elsewhere , cell anPlasma levels of creatinine and BUN were measured using a commercial assay kit  according to the manufacturer’s instructions. ALT and AST activities were measured on a Hitachi 7600-020 Automatic Analyzer .MDA levels and SOD activity were determined by means of the Thiobarbituric Acid Assay Kit  and a Xanthine and Xanthine Oxidase Reaction System , respectively, according to the manufacturers’ protocols. Absorbance was read at 532 nm (MDA) and 450 nm (SOD) on a microplate reader . The results were calculated according to the manufacturer’s instructions and were normalized to total protein concentration.TM Assay Kit  according to the manufacturer’s instructions.Serum levels of ROS were determined with the ROS-Glo0). VO2max was measured after the addition of 2.5 mM ADP, and Voligo was measured following the addition of 1 μg/mL oligomycin. O2 flux was calculated from the negative time derivative of the oxygen concentration signal using DatLab 4 software . Respiration results were normalized to fiber weight to adjust for potential differences in the mitochondrial content.Mitochondrial respiratory rate was measured in saponin-permeabilized cardiac fibers by high-resolution respirometry as described previously . Brieflyt test (two-tailed) and one-way analysis of variance (ANOVA) were conducted to compare various experimental groups. When more than two groups were included in an analysis, Bonferroni’s correction of the significance level was applied. Correlations among the expressions of HDAC6 and PHB1 and the mitochondrial respiratory control rate were assessed via Spearman’s correlation coefficients. Data with a p value less than 0.05 were considered statistically significant.All results were expressed as the mean ± standard error of the mean (SEM). The analyses were performed using GraphPad Prism . The Student All procedures in the experiments involving human participants and animals were conducted in accordance with the ethical standards of The China-Japan Friendship Hospital. Informed consent to participate in the study was obtained from all the participants.


De novo viral protein synthesis following entry into host cells is essential for viral replication. As a consequence, viruses have evolved mechanisms to engage the host translational machinery while at the same time avoiding or counteracting host defenses that act to repress translation. Mammalian orthoreoviruses are dsRNA-containing viruses whose mRNAs were used as models for early investigations into the mechanisms that underpin the recognition and engagement of eukaryotic mRNAs by host cell ribosomes. However, there remain many unanswered questions and paradoxes regarding translation of reoviral mRNAs in the context of infection. This review summarizes the current state of knowledge about reovirus translation, identifies key unanswered questions, and proposes possible pathways toward a better understanding of reovirus translation. Viruses must use the host translation machinery to synthesize viral proteins. Early in infection viral mRNA transcripts must compete with a large excess of host transcripts for access to the translation machinery. Defective viral translation will severely impact viral replication. Eukaryotic translation is a complex and sophisticated cellular process which includes four phases: initiation, elongation, termination, and recycling ,2. The ts1 mRNA encodes two proteins: the attachment protein, σ1, and a second nonstructural protein called σ1s, which is synthesized from an alternative reading frame by “leaky scanning” and initiation on a downstream methionine [m3 mRNA encodes the viral nonstructural protein μNS. It is believed that an N-terminally deleted form of μNS called μNSC is synthesized by alternative initiation at a downstream methionine. However, this has not been experimentally confirmed for mammalian orthoreoviruses.Mammalian orthoreoviruses (reoviruses) are nonenveloped and carry a segmented double-stranded (ds)RNA genome within an icosahedral core particle. A second outer-capsid layer that functions to mediate virus entry surrounds the core . Core pathionine ,13,14,15This review focuses on what is currently known about translation of reovirus mRNA. Our goals are to identify outstanding questions and to highlight the implications of recent findings regarding the compartmentalization of translation in reovirus-infected cells.Reovirus mRNAs are synthesized by viral RNA-dependent RNA polymerases (λ3 protein) within viral core particles using the negative-sense strand of each dsRNA gene segment as a template. The viral mRNAs are capped at their 5′ ends by guanylyl- and methyl-transferase enzymes to form a eukaryotic cap 1 structure as they are extruded into the cytoplasm ,17,18. Ts3 mRNA, stabilizes viral RNAs [Polyadenylation of the 3′ end stabilizes mRNAs and protects them from degradation by the cellular mRNA decay machinery, which targets mRNAs without a 3′-poly(A) tail for decapping and degradation by 5′ and 3′ exonucleases . Lackingral RNAs . σNS intral RNAs ,26.Canonical eukaryotic mRNAs are circularized during translation by the poly(A)-binding protein (PABP) which binds to both the 3′ poly(A) and the eIF4F complex. Circularization of mRNA during translation enhances translation . For rotStudies in the 1970s of the structure of reovirus mRNA 5′ termini and their binding by ribosomes contributed to our current understanding of eukaryotic cap-dependent translation and ribosomal scanning ,35,36,37s1 reovirus mRNA has a 5′ UTR that is 12 nucleotides long. In order to place the initiating methionine tRNA at the P-site would require that the footprint of the ribosome overhang the cap structure. If the canonical eIF4F initiation complex were associated with the cap, this would also provide a steric hindrance to proper initiation at the start codon and joining of the 60S large ribosomal subunit. Further work to identify the specific initiation factors associated with reovirus mRNAs, particularly those with short 5′ UTRs, may help to uncover the mechanisms behind translational initiation.The 5′ and 3′ untranslated regions (UTRs) of reovirus mRNAs are short. The 5′ UTRs vary between 12 and 32 nucleotides in length, and the 3′ UTRs vary between 35 and 83 nt in length . A ribosNewly synthesized reovirus mRNAs are deposited into the cytoplasm absent any of the RNA-binding proteins that normally associate with cellular mRNAs . Naked mStress granules (SGs) are dynamic structures that contain messenger ribonucleoprotein (mRNP) complexes and a variety of other proteins including RNA-binding proteins. SGs are liquid–liquid phase-separation structures that form rapidly in response to stress-activated signal-pathway-mediated stalling of translational initiation and that dissipate upon removal of the stress . Virus iSGs sequester stalled ribosomal complexes that lacked a ternary complex. SGs can stabilize certain mRNAs that collect within them until the stress can be resolved or target others for degradation within processing bodies ,51. In aReovirus infection induces SG formation as early as 2 h after infection, with peak SG numbers seen approximately 6 h after infection. However, as the infection progresses SGs disappear, and the infected cells become refractory to further induction of SGs ,54. The Viral core particles localize to SGs soon after they enter the cytoplasm . Unlike Intriguingly, inducing SG formation in cells by treatment with sodium arsenite 30 min prior to infection benefits subsequent reovirus replication . Sodium The ISR is a cellular signaling pathway that activates transcription of a set of genes responsible for ameliorating and adapting to the initiating stress. The ISR signaling begins with phosphorylation of eIF2α and inhibition of translational initiation. Counterintuitively, a subset of mRNAs are translated preferentially when eIF2α is phosphorylated. This subset includes key transcription factors  that act to up-regulate genes that function to allow cells to adapt to and ameliorate the underlying stress. The mRNAs of ISR genes often have short upstream open reading frames (uORFs) in their 5′ untranslated regions that act to inhibit translation under normal concentrations of ternary complex. However, when translation initiation is inhibited and the concentrations of ternary complex become limiting, ribosomes scan past the uORFs and initiate at the canonical start codon of these mRNAs leading to synthesis of ISR proteins . Reovirus infection activates and appears to benefit from phosphorylation of eIF2α and activation of the ISR . Unlike Later in reovirus infection, SGs disassemble, despite the presence of high levels of phosphorylated eIF2α . Viral gViral factories form in the cytoplasm of reovirus-infected host cells that can be seen by immunofluorescence microscopy as early as 4 h postinfection ,76,77,78Reovirus VFs are dynamic structures that show liquid–liquid phase-separated properties ,91. At 2Early thin-section electron microscopy studies reported that ribosomes were absent from reovirus VFs leading to the belief that the translation of reovirus mRNAs occurred outside of VFs ,87. HoweMembranes are embedded within reovirus VFs. Studies using transmission electron microscopy, three-dimensional image reconstructions and immunofluorescence confocal microscopy detect ribosome-encrusted and other cellular-membrane fragments within VFs ,89,90. TRibosomes within cells can be free in the cytoplasm or associated with the ER. During viral infection, mRNA dissociates from free polyribosomes and cellular translation by ER-associated ribosomes are suppressed. However, ribosome loading on ER-bound mRNA is substantially higher than in the cytosol , and ER-By having viral translation occur within or in close proximity to VFs, viral transcription and translation can be coupled, and the requirement for viral mRNA and viral protein trafficking within cells is eliminated. The viral single-stranded RNA-binding protein σNS is concentrated at the margins of VFs and likely plays a role in retaining viral mRNAs within VFs ,75. ReteViral double-stranded RNA (dsRNA) is a pathogen-associated molecular pattern (PAMP) that is recognized by host pattern-recognition receptors (PRRs), which activate downstream signaling pathways leading to interferon (IFN) production and induction of antiviral effectors . By compThe two best characterized dsRNA-triggered antiviral pathways are the dsRNA-dependent protein-kinase (PKR) pathway and 2′–5′-oligoadenylate synthetase (OAS)/RNase L pathway . PKR is Infection with the most reovirus strains induces host translational shutoff; the Type 2 Jones (T2J) strain or strains clone 8 (c8), clone 87 (c87), and clone 93 (c93) causes dramatic host translational shutoff at high multiplicity . In contAlthough it is believed that PKR or RNase L are antiviral factors that are antagonized by the reovirus σ3 protein, it remains controversial to what extent PKR or RNase L exert an antiviral effect during infection. Evidence indicating that phosphorylated PKR has an antiviral effect on reovirus replication comes from experiments investigating the molecular basis for the oncolytic effects of reoviruses on transformed fibroblasts. NIH-3T3 cells are resistant to reovirus infection but become susceptible when transformed with activated Sos or Ras . The autBoth PKR and RNase L participate in the formation of cytoplasmic RNP granules in response to virus infection. Many viruses induce the formation of SGs ,124. UpoReovirus proteins σNS and σ3 associate with ribosomes or polysomes ,129,130.The association of σ3 with ribosomes/ polysomes and its functional significance remains unclear. Late in the infection, some reports have described the synthesis of reovirus mRNAs that are uncapped yet are efficiently translated. Entering core particles synthesize capped viral mRNAs, but newly assembled “secondary” core particles purified from infected cells transcribe noncapped viral mRNAs . It is hIt has been proposed that σ3 may act as a translation-initiation factor that binds to ribosomes to stimulate late uncapped viral translation. When expressed ectopically, σ3 predominantly localizes to the nucleus . SimilarReovirus protein synthesis takes place in the cytoplasm and depends exclusively on the host translational machinery. Therefore, reovirus has developed strategies to promote efficient viral translation in a competitive cellular environment. It seems likely that translation of reovirus mRNAs is spatiotemporally regulated . Evidenc○What types of RNP granules or RNP granules combinations are formed at early stages after infection, and what function do RNP granules have during viral infection?○Are early viral mRNAs translated within RNP granules?○What is the mechanism by which reoviruses disrupt SGs/RNP granules?○How does σ3 regulate reovirus translation? ○What is the functional significance of the nuclear localization of σ3? ○Are uncapped viral mRNAs synthesized late in infection, and if so, how does σ3 promote their translation?○How does the activation of the ISR and PKR or RNase L benefit viral replication?Our growing understanding of reovirus translation leaves many questions as yet unanswered. Some important questions to be addressed in future studies are as follows:


Small open reading frames (smORF/sORFs) that encode short protein sequences are often overlooked during the standard gene prediction process thus leading to many sORFs being left undiscovered and/or misannotated. For many genomes, a second round of sORF targeted gene prediction can complement the existing annotation. In this study, we specifically targeted the identification of ORFs encoding for 80 amino acid residues or less from 31 fungal genomes. We then compared the predicted sORFs and analysed those that are highly conserved among the genomes.A first set of sORFs was identified from existing annotations that fitted the maximum of 80 residues criterion. A second set was predicted using parameters that specifically searched for ORF candidates of 80 codons or less in the exonic, intronic and intergenic sequences of the subject genomes. A total of 1986 conserved sORFs were predicted and characterized.It is evident that numerous open reading frames that could potentially encode for polypeptides consisting of 80 amino acid residues or less are overlooked during standard gene prediction and annotation. From our results, additional targeted reannotation of genomes is clearly able to complement standard genome annotation to identify sORFs. Due to the lack of, and limitations with experimental validation, we propose that a simple conservation analysis can provide an acceptable means of ensuring that the predicted sORFs are sufficiently clear of gene prediction artefacts.The online version of this article (10.1186/s12859-018-2550-2) contains supplementary material, which is available to authorized users. Saccharomyces cerevisiae were published [Small open reading frames (smORF) are sequences that potentially encode for proteins but are shorter than other more commonly translated genomic DNA sequences . Such prublished , 3. In aBacillus subtilis is known to inhibit sporulation by preventing the activation of a required transcription factor [Drosophila melanogaster, are known to be important for leg development [Homo sapiens, the humanin (24 amino acids) protein is involved in mitochondria-nuclear retrograde signalling that controls apoptosis [Despite the term sORF turning up only in more recent literature, the existence of genes that code for proteins of 150 residues and less have been known for more than three decades. Functional sORFs have been identified in a wide range of organisms from prokaryotes to humans. The Sda protein 46 residues) found in  residueselopment . The Cg-elopment . In Homopoptosis , 10. Pospoptosis .Escherichia coli (15–20 amino acids) [- Saccharomyces cerevisiae (less than 100 amino acids) [Arabidopsis thaliana (100–150 amino aicds) [Bradyrhizobium japonicum (less than 80 amino acids) [Drosophila (less than 100 amino acids) [As genome sequencing capabilities steadily progressed from the late 90s, through the 2000s to the present, many studies have identified and annotated sORFs directly from genome sequence data . Variouso acids) ; in yeaso acids) , 14; in o acids) ; in inseo acids) ; in mouso acids)  and in ho acids) . More reS. cerevisiae had defined 100 residues and 150 residues as the minimum number to be encoded by an ORF thus in a way setting a parameter value for future gene predictions and annotation work [Nevertheless, it has also been shown that many ORFs with lengths of 100 or less amino acids may have been missed during gene prediction from whole genome sequences because the gene prediction tools are tuned to ignore small genes perceived to be ‘junk’ or non-protein coding . For exaion work , 3. Perhion work .In this work, we have identified potential sORFs from fungal genomes by specifically repeating the gene prediction and annotation processes based on a residue length cutoff of 80 amino acids or less and specified the range of sORFs length distribution among homologs to avoid false positives. The cutoff of 80 residues was chosen as a simplistic means of selecting ORFs that were most likely to have been overlooked by previous gene predictions. The identification of 1986 putative predicted sORFs involved a large sequence dataset extracted from 31 fungal genome sequences with a total of 210,928 ORFs from existing gene prediction and annotation. The predicted sORFs were then compared to identify highly conserved examples within the fungal genomes dataset by adopting the assumption that such highly conserved sequences may code for common or even essential functions and are thus unlikely to be artefacts or randomly matched examples. This can potentially be a quick and inexpensive means of identifying subsets of sORFs that are classified as hypothetical proteins for experimental characterization.The fungal genomes selected were required to have associated annotations for predicted genes thus limiting our dataset to only 31 genomes at the time the work was initiated. These annotations were utilized to identify 5255 sORFs genes that had already been identified in the original annotation to encode for a maximum of 80 amino acid residues. The ORF prediction process was then repeated for all 31 fungal genomes using the computer programs getorf , 23 and CD-HIT  clusteriThe clustering based on 70% similarity of the 47,842 potential sORFs resulted in a total of 1986 putative sORFs that are conserved within at least two fungal species   pathway. There are two sORFs (C. dubliniensis-sf4096_1 and P. pastoris-sf9282_1) from the computational reannotation that were clustered together with conserved alignments, and thus indicating they may have the same function , nucleus (57), endoplasmic reticulum (13), integral component of membrane (33) and Ssh1 translocon complex (22). Under the molecular function classification - the predicted sORFs were assigned to functions associated to mating pheromone activity (11), DNA and RNA binding (41), ribosome (145), cytochrome (7), protein binding (31), zinc ion binding (22), hydrogen ion transmembrane transporter activity (39), metal ion binding (16), protein heterodimerization activity (1), oxidoreductase activity (1), ATP binding (1), GTP binding (1) and ligase activity (1). For biological process GO classification, the 115 predicted sORFs in this group were classified into ribosome biogenesis (26), carbohydrate metabolic process (2), mitochondrial electron transport (4), DNA repair (1), mRNA export from nucleus (4), translation (10), protein N-linked glycosylation (1), protein targeting and targeting (3), copper ion transport (5), nucleocytoplasmic transport (14), response to stress (2), protein secretion (3), protein import into mitochondrial matrix (7), mitochondrial respiratory chain complex IV assembly (14), regulation of catalytic activity (8), transmembrane transport (1), vacuolar proton-transporting V-type ATPase complex assembly (5) and mitochondrial outer membrane translocase complex assembly (1).Based on the cellular component classification, the secreted sORFs are associated with roles in communication, differentiation and establishing clonal behaviour. The secreted sORFs predicted that was associated to mating pheromone activity were 34–35 amino acids in length. There are 51 predicted sORFs that were associated with functions as membrane features or even in modulating cell membrane thickness or fluidity to respond to changing environmental conditions. One such example is the predicted sORF encoding 52 residues that is associated with plasma membrane proteolipid 3 (Pmp3p), which is part of the phosphoinositide-regulated stress sensor that has a role in the modulation of plasma membrane potential and in the regulation of intracellular ion homeostasis .The methods that we have developed from available and proven tools are expected to be easily deployable to other genomes as and when they become available with minimal modifications. Recently, a psychrophilic yeast genome had been reported  that hasThe results of our work reveal that a high number of potential sORFs could be overlooked by the standard gene prediction workflow. We therefore recommend that the standard genome annotation process be complemented by analyses that specifically target the annotation of sORFs , 40, andhttps://github.com/firdausraih/sORFs-fungal-genomes  format using a Perl script. The intergenic regions were extracted from both the forward and reverse strands.The intronic and coding regions for the genomes were identified using Artemis  [https:/Gene predictions that specifically targeted the identification of sORFs were done by using sORFfinder-getorf approaches that combined two programs: getorf and sORFfinder. The prediction of the sORFs were carried out for each scaffold and/or chromosome. The sORFs predictions using getorf from the EMBOSS package , 42 wereThe predicted sORFs from getorf and sORFfinder search outputs for each fungi genome were combined and clustered using CD-HIT-EST , 43 and The pre-annotated sORFs and those that were predicted as potential sORFs were then combined and clustered using CD-HIT at 70% identity to remove clusters that contained only a single sequence. For each cluster, sORFs that have homologs in at least two different species in one cluster were considered as potentially conserved sORFs. All conserved sORFs were identified their Kozak sequences using CPC2 .Identification of conserved sORFs in the clusters were carried out using the MUSCLE  sequenceThe predicted sORFs were annotated using blast, interpro and classified using BLAST2GO into the three main Gene Ontology classes of molecular function, biological processes and cellular component –51.Additional file 1:A listing of 1986 putative conserved sORFs predicted. This file contains a list of 1986 putative conserved sORFs predicted from all fungal genomes that can be viewed using Microsoft excel or text viewer. (TXT 151 kb)Additional file 2:List of predicted sORFs with homologs. This file contains a list of sORFs predicted from all fungal genomes with their homologs that can be viewed using Microsoft excel or a text viewer. (TXT 118 kb)Additional file 3:Pseudocode for sORFs workflow. This file contains a pseudocode for finding sORFs workflow using Linux environment using BASH, PYTHON and the Perl programming language. (ZIP 8 kb)