Faba bean (Vicia faba L.), a member of the Fabaceae family, is one of the important food legumes cultivated in cool temperate regions. It holds great importance for human consumption and livestock feed because of its high protein content, dietary fibre, and nutritional value. Major faba bean breeding challenges include its mixed breeding system, unknown wild progenitor, and genome size of ~13 Gb, which is the largest among diploid field crops. The key breeding objectives in faba bean include improved resistance to biotic and abiotic stress and enhanced seed quality traits. Major progress on reduction of vicine-convicine and seed coat tannins, the main anti-nutritional factors limiting faba bean seed usage, have been recently achieved through gene discovery. Genomic resources are relatively less advanced compared to other grain legume species, but significant improvements are underway due to a recent significant increase in research activities. A number of bi-parental populations have been constructed and mapped for targeted traits in the last decade. Faba bean now benefits from saturated synteny‐based genetic maps, along with next-generation sequencing and high-throughput genotyping technologies that are paving the way for marker-assisted selection. Developing a reference genome, and ultimately a pan-genome, will provide a foundational resource for molecular breeding. In this review, we cover the recent development and deployment of genomic tools for faba bean breeding.

Papillary thyroid carcinoma (PTC) has two main histologic variants: classical-PTC (CL-PTC) and follicular variant PTC (FV-PTC). Recently, due to its similar features to benign lesions, the encapsulated FV-PTC variant was reclassified as noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP). Nonetheless, specific molecular signatures are not yet available. It is well known that telomere-related genome instability is caused by inappropriate DNA repair of dysfunctional telomeres and that mechanisms involved in the damaged telomere repair processing may led to detrimental outcomes, altering the 3D nuclear telomere and genome organization in cancer cells. This pilot study aimed to evaluate whether a specific nuclear telomere architecture might characterize NIFTP, potentially distinguishing it from other PTC histologic variants. Our findings demonstrate that 3D telomere profiles of CL-PTC and FV-PTC were different from NIFTP and that NIFTP more closely resembles follicular thyroid adenoma (FTA). NIFTP has longer telomeres than CL-PTC and FV-PTC samples and telomere length overlaps in NIFTP and FTA. There was no association between BRAF expression and telomere length in all tested samples. Our data showing that 3D nuclear telomere organization is altered differently in thyroid cancer variants, suggest that this parameter might guide clinical management of NIFTP. Although further investigations in a larger cohort of patients are necessary to corroborate our observations, telomere-related genomic instability might be of value in the diagnosis of NIFTP and allow for a more appropriate selection of the correct treatment.

Estimation of breeding values through Best Linear Unbiased Prediction (BLUP) using pedigree-based kinship and Marker-Assisted Selection (MAS) are the two fundamental breeding methods used before and after the introduction of genetic markers, respectively. The emergence of high-density genome-wide markers has led to the development of two parallel series of approaches inspired by BLUP and MAS, which are collectively referred to as Genomic Selection (GS). The first series of GS methods alters pedigree-based BLUP by replacing pedigree-based kinship with marker-based kinship in a variety of ways, including weighting markers by their effects in genome-wide association study (GWAS), joining both pedigree and marker-based kinship together in a single-step BLUP, and substituting individuals with groups in a compressed BLUP. The second series of GS methods estimates the effects for all genetic markers simultaneously. For the second series methods, the marker effects are summed together regardless of their individual significance. Instead of fitting individuals as random effects like in the BLUP series, the second series fits markers as random effects. Differing assumptions regarding the underlying distribution of these marker effects have resulted in the development of many Bayesian-based GS methods. This review highlights critical concept developments for both of these series and explores ongoing GS developments in machine learning, multiple trait selection, and adaptation for hybrid breeding. Furthermore, considering the increasing use and variety of GS methods in plant breeding programs, this review addresses important concerns for future GS development and application, such as the use of GWAS-assisted GS, the long-term effectiveness of GS methods, and the valid assessment of prediction accuracy.

Upon inbreeding, the architecture of the inbreeding load shifts as selection purges strongly deleterious recessive mutations and drift fixes many milder ones. Most small inbred populations show limited genetic variation while crosses between such populations commonly express pronounced heterosis, confirming fixation. In contrast, purging appears to be limited in that inbred populations often retain substantial inbreeding depression. In addition we have the enigma Darwin noted: purely selfing taxa are unknown. Because both purging and fixation reduce inbreeding depression and load, another mechanism must exist to sustain these. Background selection and the associations that develop among alleles in small inbred populations will shift the architecture of the load potentially creating blocks of recessive mutations linked in repulsion. This would generate pseudo-overdominance that could sustain these “PODs” and inbreeding load. Recombination and crosses between lineages could erode PODs. Crosses between populations fixed for different mutations would generate high pseudo-overdominance, enhancing heterosis and potentially POD formation. New recessive mutations arising within PODs would reinforce overdominance. PODs should generate clear genetic signatures including genomic hotspots of heterozygosity and linkage disequilibrium containing alleles at intermediate frequency generating segregating load. Results from several simulation and empirical studies match these predictions. Further simulations and comparative genomic analyses are needed to rigorously test whether PODs exist in sufficient strength and number to generate persistent inbreeding depression and load in inbred lineages.

Published transcriptomic data from surgically removed metastatic clear cell renal cell carcinoma (ccRCC) samples were re-analyzed from the Genomic Fabric Perspective that considers the transcriptome a multi-dimensional mathematical object, constrained by a dynamic set of expression correlations among genes. Every gene in the chest wall metastasis (MET), two primary tumors (PTA, PTB) and the surrounding normal tissue (NOR) of the right kidney was characterized by three independent measures: average expression level (AVE), relative expression variation (REV) and expression correlation (COR) with each other gene. AVE was used to determine the regulation of the genomic fabrics of ccRCC, apoptosis, chemokine and VEGF signaling pathways. REV quantified the alteration of the transcripts’ abundances control, while COR determined the remodeling of the transcriptomic networks of chemokine signaling and oxidative phosphorylation genes. The gene hierarchy was established in based on Gene Commanding Height and the Gene Master Regulators (GMR) TASOR (PTA), FAM27C (PTB) and ALG13 (MET) and DAPK3 (NOR) were identified in each profiled region. We predict that TASOR overexpression would block transcription in PTA but not in PTB, while slightly stimulating it in NOR. Silencing of ALG3 would slow-down the cell-cycle in all three cancer regions with practically no effect in NOR.

The humpback puffer, Tetraodon palembangensis, also known as Pao palembangensis, is a species of poisonous freshwater pufferfish mainly distributed in Southeast Asia (Thailand, Laos, Malaysia and Indonesia). Despite interesting biological features, such as its very inactive nature, tetrodotoxin production and body expansion mechanisms, molecular research on the humpback puffer is still rare because of the lack of a high-quality reference genome. Here, we reported a first chromosome-level genome assembly of an adult humpback puffer, of which the genome size is 362 Mb with ~1.78 Mb contig N50 and ~15.8 Mb scaffold N50s. Based on the genome, ~61.5Mb (18.11%) repeat sequences were also identified, and totally 19,925 genes were annotated, 99.20% of which could be predicted with function using protein-coding function databases. Finally, a phylogenetic tree was constructed with single-copy gene families from ten teleost fishes. The humpback puffer genome will be a valuable genomic resource to illustrate possible mechanisms of tetrodotoxin synthesis and tolerance, providing clues for future detailed studies of biological toxins.

Citizen Science has come up to perform analytics over the SARS-CoV-2 genome. Public GALAXY servers provide an automated platform for genomics analysis. Study includes design of GALAXY workflows for RNASEQ assembly and annotation as well as genomic variant discovery and perform analysis across four samples of SARS-CoV-2 infected humans obtained from the local population of Wuhan, China. It provides information about transcriptomics and genomic variants across the SARS-CoV-2 genome. Study can be extended to perform evolutionary and comparative study across each species of coronaviruses. Augmented and integrated study with cheminformatics and immunoinformatics will be a way forward for drug discovery and vaccine development.

The past years saw the rise of genomic biobanks and mega-scale meta-analysis of genomic data that promise to reveal the genetic underpinnings of health and disease. However, the over-representation of Europeans in genomic studies not only limit the global understanding of disease risk and intervention efficacy, but also inhibit viable research into the genomic differences between carriers and patients. Whilst the community has agreed that more diverse samples are required, it is not enough to blindly increase diversity; the diversity must be quantified, compared, and annotated to lead to insight. Genetic annotations from separate biobanks need to be comparable, computable, operate without access to raw data due to privacy concerns. But they must be comparable, both for regular research and to allow international comparison in response to pandemics. Here, we evaluate the appropriateness of commonly used genomic tools used to depict population structure in a standardized and comparable manner. The end goal is to reduce the effects of confounding and learn from genuine variation in genetic effects on phenotypes across populations, which will improve the value of biobanks, locally and internationally, increase the accuracy of association analyses, and inform developmental efforts.

The holistic approach of One Health, which sees human, animal, plant, and environmental health as a unit, rather than discrete parts, requires not only interdisciplinary cooperation, but standardized methods for communicating and archiving data, enabling participants to easily share what they have learned and allow others to build upon their findings.Ongoing work by NCBI and the GenomeTrakr project illustrates how open data platforms can help meet the needs of federal and state regulators, public health laboratories, departments of agriculture, and universities. Here we describe how microbial pathogen surveillance can be transformed by having an open access database along with Best Practices for contributors to follow. First, we describe the open pathogen surveillance framework, hosted on the NCBI platform. We cover the current community standards for WGS quality, provide an SOP for assessing your own sequence quality and recommend QC thresholds for all submitters to follow. We then provide an overview of NCBI data submission along with step by step details. And finally, we provide curation guidance and an SOP for keeping your public data current within the database. These Best Practices can be models for other open data projects, thereby advancing the One Health goals of Findable, Accessible, Interoperable and Re-usable (FAIR) data.

New coronavirus (SARS-CoV-2) treatments and vaccines are under development to combat the COVID-19 disease. Several approaches are being used by scientists for investigation including 1) various small molecule approaches targeting RNA polymerase, 3C-like protease, and RNA endonuclease and 2) exploration of antibodies obtained from convalescent plasma from patients who have recovered from COVID-19. The coronavirus genome is highly prone to mutations that lead to genetic drift and escape from immune recognition; thus, it is imperative that sub-strains with different mutations are also accounted for during vaccine development. As the disease has grown to become a pandemic, new B-cell and T-cell epitopes predicted from SARS coronavirus have been reported. Using the epitope information along with variants of the virus, we have found several variants which might cause drifts. Among such variants, 23403A>G variant (p.D614G) in spike protein B-cell epitope is observed frequently in European countries such as the Netherlands, Switzerland and France.

Due to the rapid developments in aquaculture industry, Artemia franciscana, originally an American species, has been intentionally introduced to the Eurasia, Africa and Australia. In the present study, we used a partial sequence of the mitochondrial DNA Cytochrome Oxidase subunit I (mt-DNA COI) gene and genomic fingerprinting by Inter-Simple Sequence Repeats (ISSRs) to determine the genetic variability and population structure of Artemia populations (indigenous and introduced) from 14 different geographical locations in Western Asia. Based on the haplotype spanning network, Artemia urmiana has exhibited higher genetic variation than native parthenogenetic populations. Although A. urmiana represented a completely private haplotype distribution, no apparent genetic structure was recognized among the native parthenogenetic and invasive A. franciscana populations. Our ISSR findings have documented that despite invasive populations have lower variation than source population in Great Salt Lake (Utah, USA), they have significantly revealed higher genetic variability compare to the native populations in Western Asia. According to the ISSR results, the native populations were not fully differentiated by the PCoA analysis, but the exotic A. franciscana populations were geographically divided in four genetic groups. We believe that during the colonization, invasive populations have experienced substantial genetic divergences, under new ecological conditions in the non-indigenous regions.

Sequence alignment and comparison through pairwise, multiple, global and local techniques are the main principles that underpin comparative genomics. However, most of the algorithms used are alignment-based which imposed some limitations on their use and application. In an attempt to provide an alignment-free alternative approaches, a methodology of comparative optinalysis and statistical mirroring was used and adopted to provide a suitable alternative for multiple genomic sequence comparison. In this article, methods comparison with MUSCLE, MUFFT, Clustal Omega, and T-Coffee was designed to assess the suitability and statistical power of statistical mirroring as an alternative method for multiple genomic sequences comparison using different sets of logically generated biological sequence datasets with different problems and computational complications. The results of the comparisons validate that statistical mirroring is a suitable alignment-free alternative approach for multiple genomic sequence comparison. The applied method (statistical mirroring) distinguishes itself over MUSCLE, MUFFT, Clustal Omega, and T-Coffee in specificity to a position-specific changes, specificity to a base-specific changes, cladogram and phylogenetic linearity, alignment independency, computational simplicity, and limit of input capacity.

Defects in pre-mRNA splicing are frequently a cause of Mendelian disease. Despite the advent of next-generation sequencing, allowing a deeper insight into a patient’s variant landscape, the ability to characterize variants causing splicing defects has not progressed with the same speed. To address this, recent years have seen a sharp spike in the number of splice prediction tools leveraging machine learning approaches, leaving clinical geneticists with a plethora of choices for in silico analysis. In this Review, some basic principles of machine learning are introduced in the context of genomics and splicing analysis. A critical comparative approach is then used to describe seven recent machine learning-based splice prediction tools, revealing highly diverse approaches and common caveats. We find that, although great progress has been made in producing specific and sensitive tools, there is still much scope for personalized approaches to prediction of variant impact on splicing. Such approaches may increase diagnostic yields and underpin improvements to patient care.

Cancer cell lines are widely used as in vitro models of tumorigenesis, facilitating fundamental discoveries in cancer biology and translational medicine. Currently, there are few options for glioblastoma (GBM) treatment and limited in vitro models with accurate genomic and transcriptomic characterization. Here, a detailed characterization of a new GBM cell line, namely AHOL1, was conducted in order to fully characterize its molecular composition based on its copy number alteration (CNA) and transcriptome profiling, followed by the validation of key elements associated with GBM tumorigenesis. Large numbers of CNAs and differentially expressed genes (DEGs) were identified. CNAs were distributed throughout the genome, including gains at Xq11.1-q28, Xp22.33-p11.1, Xq21.1-q21.33, 4p15.1-p14, 8q23.2-q23.3 and losses at Yq11.21-q12, Yp11.31-p11.2 and 12p13.31 positions. Nine druggable genes were identified, including HCRTR2, ETV1, PTPRD, PRKX, STS, RPS6KA6, ZFY, USP9Y and KDM5D. By integrating DEGs and CNAs, we identified 57 overlapping genes enriched in fourteen pathways. Altered expression of several cancer-related candidates found in the DEGs-CNA dataset was confirmed by RT-qPCR. Taken together, this first comprehensive genomic and transcriptomic landscape of AHOL1 provides unique resources for further studies and identifies several druggable targets that may be useful for therapeutics and biologic and molecular investigation of GBM.

Non-targeted effects (NTE) such as bystander effects or genomic instability have been known for many years but their significance for radiotherapy or medical diagnostic radiology are far from clear. Central to the issue are reported differences in response of normal and tumour tissues to signals from directly irradiated cells. This review will discuss possible mechanisms and implications of these different responses and will then discuss possible new therapeutic avenues suggested by the analysis. Finally, the importance of NTE for diagnostic radiology and nuclear medicine which stems from the dominance of NTE in the low dose region of the dose response curve will be presented. Areas such as second cancer induction and microenvironment plasticity will be discussed.

Current prenatal genetic evaluation showed a significantly increase in non-invasive screening and the reduction of invasive diagnostic procedures. To evaluate the diagnostic efficacy on detecting common aneuploidies, structural chromosomal rearrangements and pathogenic copy number variants (pCNV), we performed a retrospective analysis on a case series initially analyzed by aneuvysion fluorescence in situ hybridization (FISH) and karyotyping then followed by array comparative genomic hybridization (aCGH). Of the 386 cases retrieved from the past decade, common aneuploidies were detected in 137 cases (35.5%), other chromosomal structural rearrangements were detected in four cases (1%), and pCNV were detected in five cases (1.3%). The relative frequencies for common aneuploidies suggested a under detection of sex chromosome aneuploidies. Approximately 9.5% of cases with common aneuploidies showed a mosaic pattern. Inconsistent results between FISH and karyotyping were noted in cases with pseudo-mosaicism introduced by culture artifact or variable cellular proliferation from cells with mosaic karyotypic complements under in vitro cell culture. Based on findings from this case series, cell-based FISH and karyotyping should be performed to detect common aneuploidies, structural chromosomal abnormalities, and mosaic pattern. DNA-based aCGH and reflex FISH should be performed to detect and confirm genomic imbalances and pCNV. Practice points to ensure the diagnostic accuracy and efficacy were summarized.

Pasmo (Septoria linicola) is a fungal disease causing major losses in seed yield and quality, and stem fibre quality in flax. Pasmo resistance (PR) is quantitative and has low heritability. To improve PR breeding efficiency, the accuracy of genomic prediction (GP) was evaluated using a diverse worldwide core collection of 370 accessions. Four marker sets, including three defined by 500, 134, and 67 previously identified quantitative trait loci (QTL) and one of 52,347 PR-correlated genome-wide single nucleotide polymorphisms, were used to build ridge regression best linear unbiased prediction (RR-BLUP) models using pasmo severity (PS) data collected from field experiments performed during five consecutive years. With five-fold random cross-validation, GP accuracy as high as 0.92 was obtained from the models using the 500 QTL when the average PS was used as the training dataset. GP accuracy increased with training population size, reaching values >0.9 with training population size greater than 185. Linear regression of the observed PS with the number of positive-effect QTL in accessions provided an alternative GP approach with an accuracy of 0.86. The results demonstrate the GP models based on marker information from all identified QTL and the 5-year PS average is highly effective for PR prediction.

Heavy metals are compounds that can be hazardous and impair growth of living organisms. Bacteria have evolved the capability not only to cope with heavy metals but also to detoxify polluted environments. Three heavy metal-resistant strains of Mucilaginibacer rubeus and one of Mucilaginibacter kameinonensis were isolated from the gold/copper Zijin mining site, Longyan, Fujian, China. These strains were shown to exhibit high resistance to heavy metals with minimal inhibitory concentration reaching up to 3.5 mM Cu(II), 21 mM Zn(II), 1.2 mM Cd(II), and 10.0 mM As(III). Genomes of the four strains were sequenced by Illumina. Sequence analyses revealed the presence of a high abundance of heavy metal resistance (HMR) determinants. One of the strain, M. rubeus P2, carried genes encoding 6 putative P1B-1-ATPase, 5 putative P1B-3-ATPase and 4 putative Zn(II)/Cd(II) P1B-4 type ATPase, and 16 putative RND-type metal transporter systems. Moreover, the four genomes carry a high abundance of genes coding for putative metal binding chaperones. Analysis of the close vicinity of these HMR determinants uncovered the presence of clusters of genes potentially associated with mobile genetic elements. These loci include genes coding for tyrosine recombinases (integrases) and subunits of mating pore (type 4 secretion system) respectively allowing integration/excision and conjugative transfer of numerous genomic islands. Further in silico analyses revealed that their genetic organization and gene products resemble the Bacteroides integrative and conjugative element CTnDOT. These results highlight the pivotal role of genomic islands in the acquisition and dissemination of adaptive traits, allowing for rapid adaption of bacteria and colonization of hostile environments.

Genomic medicine is moving from research to the clinic. There is a lack of evidence about the impact of genomic medicine interventions on health outcomes. This is due in part to a lack of standardized outcome measures that can be used across different programs to evaluate the impact of interventions targeted to specific genetic conditions. The eMERGE Outcomes working group (OWG) developed measures to collect information on outcomes following the return of genomic results to participants for several genetic disorders. These outcomes were compared to outcome intervention pairs for genetic disorders developed independently by the ClinGen Actionability working group (AWG). In general, there was concordance between the defined outcomes between the two groups. The ClinGen outcomes tended to be higher level and the AWG scored outcomes represented a subset of outcomes referenced in the accompanying AWG evidence review. eMERGE OWG outcomes were more detailed and discrete, facilitating collection of relevant information from health records. This paper demonstrates that common outcomes for genomic medicine interventions can be identified. Further work is needed to standardize outcomes across genomic medicine implementation projects and make these publicly available to enhance dissemination and assist in making precision public health a reality.

The time required to reach a correct diagnosis is one of the most important problems for rare disease (RD) patients. Diagnostic delay can be intolerably long, to the point that it is usually described as a “diagnostic odyssey” and, sometimes, a diagnosis might never occur. The International Rare Disease Research Consortium proposed, as ultimate goal for 2017-2027, to enable all people with a suspected RD to be diagnosed within one year if the disorder is known, and to enter a globally coordinated diagnostic and research pipeline for the unsolved cases. In-depth analysis of the genotype through next generation sequencing, together with a standardized in-depth phenotype description and sophisticated high-throughput approaches, have been applied as diagnostic tools to increase the chance of a timely and accurate diagnosis. This approach is very fruitful as, according to the Orphanet database, from 2010 to March 2017 more than 600 new RDs have been described and about 3600 genes linked to RDs have been identified. However, combination of -omics and phenotype data and international sharing of this information raise ethical concerns. Values to be assessed include not only patient autonomy but also family implications, beneficence, non-maleficence, justice, solidarity and reciprocity, which must be respected and promoted and, at the same time, balanced among each other. In this work we suggest that, to maximise patients involvement in the search for a diagnosis and identification of new causative genes, undiagnosed patients should have the possibility to: 1) actively participate in the description of their phenotype; 2) choose the level of visibility of their profile in matchmaking databases; 3) express their preferences regarding return of new findings, in particular which level of Variant of Unknown Significance (VUS) significance should be considered relevant to them. The quality of the relation between individual patients and physicians, and between the patient community and the scientific community is critically important for making the best use of available data and combining efforts in the search for matches with similar cases worldwide that will help to solve unsolved cases. The contribution of patients to collecting and coding data comprehensively is critical for efficient use of data downstream of data collection.

The mechanisms by which bacteriophage T4 converts the metabolism of its E. coli host to one dedicated to progeny phage production was the subject of decades of intense research in many labs from the 1950’s through the 1980’s. At this point, a wide range of phages are starting to be used therapeutically and in many other applications and also the range of available phage sequence data is skyrocketing. It is thus important to re-explore the extensive available data about the intricacies of the T4 infection process as summarized here, expand it to looking much more broadly at other genera of phages, and explore phage infections using newly-available modern techniques and a range of appropriate environmental conditions.

Crosstalk between the BMP and TGF-β signaling pathways regulates many complex developmental processes from the earliest stages of embryogenesis throughout adult life. In many situations, the two signaling pathways act reciprocally. For example, TGF-β signaling is generally pro-fibrotic whereas BMP signaling is anti-fibrotic and pro-calcific. Sex-specific differences occur in many diseases including cardiovascular pathologies. Differing ratios of fibrosis and calcification in stenotic valves suggests that BMP/TGF-β signaling may vary in men and women. In this review, we focus on the current understanding of the interplay between sex and BMP/TGF-β signaling and pose several unanswered questions.

For the majority of lipophilic compounds adipose tissue is traditionally considered as storage depot and only rarely as a target organ. Meanwhile, abnormalities in adipose tissue physiology induced by chemical exposures may contribute to the current epidemic of obesity and metabolic diseases. Polybrominated diphenyl ethers (PBDEs) is a group of lipophilic flame retardants found in majority of human samples in North America. Their ability to alter physiology of adipose tissue is unknown. We exposed pregnant mice to 0.2 mg/kg body weight/day of BDE-47 perinatally. Transcriptomic changes in gonadal adipose tissue were analyzed in male offspring using RNA-seq approach with subsequent bioinformatic analysis. Genes of coagulation and complement cascade, de novo lipogenesis, and xenobiotic metabolism were altered in expression in response to BDE-47 exposure. The affected molecular network included the following hubs: PPARα, HNF1A and HNF4. These findings suggest that adipose tissue should be considered a target tissue for BDE-47, in addition to its role as a storage depot. This study also builds a background for a targeted search of sensitive phenotypic endpoints of BDE-47 exposure, including lipid profile parameters and coagulation factors in circulation. Additional studies are needed to investigate the role of PBDEs as an obesogen.

DNA repair helps in maintaining the proper and healthy functioning for the cells in the human body. Failure in DNA repair process can lead to aberrations as well as tumorous stages. There are various types of damages that a DNA can go through, one of which is the DNA double strand breaks (DSB) that can be repaired via homologous recombination (HR). RAD51 plays a central role in HR and has been implicated as a negative/poor prognostic marker for colorectal adenocarcinoma, with high expression in colorectal cancer. Mechanistically, RAD51AP1 facilitates RAD51 during the repairing process by binding with RAD51 via two DNA binding sites, thus helping in the D-loop formation in the HR process. Often, in biology, we are faced with the problem of exploring relevant unknown biological hypotheses in the form of myriads of combination of factors that might be affecting the pathway under certain conditions. For example, RAD51AP1-XRCC2 is one such 2^nd order combination whose relation needs to be tested under the influence recently developed Porcupine-WNT inhibitor ETC-1922159. The x-ray repair cross complementing XRCC family is known to work as a mediator or stabilizer for RAD51 during the HR process. The inhibitor is known to suppress Porcupine and thus inhibit a range of oncogenes known to be directly or indirectly affected by the Wnts. In a recent unpublished work in bioRxiv, we had the opportunity to rank these unknown biological hypotheses for down regulated genes at 2^nd order level after the drug was administered. The in silico observations showed that the combination of RAD51AP1-XRCC2 was assigned a relatively lower rank, thus validating the pipeline's efficacy with the confirmed wet lab experiment that indicate that both RAD51AP1 and XRCC2 were down regulated after treatment in cancer cells. Here, we take one step further by in silico analysis of the 3^rd order combinations of RAD51-X-X & RAD51AP1-X-X (X can be known or unknown factor), from a range of 100 randomly picked down regulated genes after ETC-1922159 treatment. The pipeline uses the density based HSIC (Hibert Schmidth Information Criterion) sensitivity index with an rbf (radial basis function) kernel, which is known to be highly effective in sensitivity analysis. Various unknown/unexplored/untested RAD51/RAD51AP1 related 3^rd order biological hypotheses emerge some of which are confirmed in wet lab, while others need to be tested.

A novel binary toxin-positive non-027, non-078 Clostridium difficile strain designated LC693 whose sequence type was ST201 was isolated from the fecal sample of a patient with severe diarrhea in China. To understand the pathogenesis basis of C. difficile ST201, this recently recovered isolate LC693 was then chosen for whole genome sequencing. The project finally generated an estimated genome size of approximately 4.07 Mbp. The genome sequence was then analyzed together with the other two ST201 strains VL-0104 and VL-0391 and compared to the epidemic 027/ST1 and 078/ST11 strains. Phylogenetic analysis demonstrated that the ST201 strains belonged to clade 3. Genome size of the three ST201 strains ranged from 4.07 Mb~4.16 Mb, with an average GC content between 28.5%~28.9%. The ST201 genomes contained more than 40 antibiotic resistance genes and 15 of them were predicted to be associated with vancomycin-resistance, suggesting that they may have a strong antibiotic resistance. The ST201 strains contained a typical clade 3 specific PaLoc with a Tn6218 element inserted, and those genes harbored on their PaLoc that participated in the toxin expression and regulation were highly homologues to the epidemic 027 and 078 strains, with the exception of tcdC. A truncated TcdC was found in the ST201 strains, which is suggestive to have a contribution to the toxin production of the ST201 strains. In addition, the ST201 strains contained intact binary toxin coding and regulation genes, which is also proposed to contribute to the virulence. Genome comparison of the ST201 strains with the epidemic 027 and 078 strain identified 641 genes specific for the C. difficile ST201, and a number of them were predicted as fitness and virulence associated genes. The identification of those genes also contributes to the pathogenesis of the ST201 strain. To our knowledge, this is the first study that the genome sequence of C. difficile ST201 was discussed in detail, and the present study would have a contribution to understanding the pathogenesis basis of C. difficile ST201.