A comparison of software for analysis of rare and common short tandem repeat (STR) variation using human genome sequences from clinical and population-based samples.

Short tandem repeat (STR) variation is an often overlooked source of variation between genomes. STRs comprise about 3% of the human genome and are highly polymorphic. Some cause Mendelian disease, and others affect gene expression. Their contribution to common disease is not well-understood, but recent software tools designed to genotype STRs using short read sequencing data will help address this. Here, we compare software that genotypes common STRs and rarer STR expansions genome-wide, with the aim of applying them to population-scale genomes. By using the Genome-In-A-Bottle (GIAB) consortium and 1000 Genomes Project short-read sequencing data, we compare performance in terms of sequence length, depth, computing resources needed, genotyping accuracy and number of STRs genotyped. To ensure broad applicability of our findings, we also measure genotyping performance against a set of genomes from clinical samples with known STR expansions, and a set of STRs commonly used for forensic identification. We find that HipSTR, ExpansionHunter and GangSTR perform well in genotyping common STRs, including the CODIS 13 core STRs used for forensic analysis. GangSTR and ExpansionHunter outperform HipSTR for genotyping call rate and memory usage. ExpansionHunter denovo (EHdn), STRling and GangSTR outperformed STRetch for detecting expanded STRs, and EHdn and STRling used considerably less processor time compared to GangSTR. Analysis on shared genomic sequence data provided by the GIAB consortium allows future performance comparisons of new software approaches on a common set of data, facilitating comparisons and allowing researchers to choose the best software that fulfils their needs.

How useful are genomic data for predicting maladaptation to future climate?

Methods using genomic information to forecast potential population maladaptation to climate change or new environments are becoming increasingly common, yet the lack of model validation poses serious hurdles toward their incorporation into management and policy. Here, we compare the validation of maladaptation estimates derived from two methods-Gradient Forests (GFoffset) and the risk of non-adaptedness (RONA)-using exome capture pool-seq data from 35 to 39 populations across three conifer taxa: two Douglas-fir varieties and jack pine. We evaluate sensitivity of these algorithms to the source of input loci (markers selected from genotype-environment associations [GEA] or those selected at random). We validate these methods against 2- and 52-year growth and mortality measured in independent transplant experiments. Overall, we find that both methods often better predict transplant performance than climatic or geographic distances. We also find that GFoffset and RONA models are surprisingly not improved using GEA candidates. Even with promising validation results, variation in model projections to future climates makes it difficult to identify the most maladapted populations using either method. Our work advances understanding of the sensitivity and applicability of these approaches, and we discuss recommendations for their future use.

scAnnoX: an R package integrating multiple public tools for single-cell annotation.

Background: Single-cell annotation plays a crucial role in the analysis of single-cell genomics data. Despite the existence of numerous single-cell annotation algorithms, a comprehensive tool for integrating and comparing these algorithms is also lacking. Methods: This study meticulously investigated a plethora of widely adopted single-cell annotation algorithms. Ten single-cell annotation algorithms were selected based on the classification of either reference dataset-dependent or marker gene-dependent approaches. These algorithms included SingleR, Seurat, sciBet, scmap, CHETAH, scSorter, sc.type, cellID, scCATCH, and SCINA. Building upon these algorithms, we developed an R package named scAnnoX for the integration and comparative analysis of single-cell annotation algorithms. Results: The development of the scAnnoX software package provides a cohesive framework for annotating cells in scRNA-seq data, enabling researchers to more efficiently perform comparative analyses among the cell type annotations contained in scRNA-seq datasets. The integrated environment of scAnnoX streamlines the testing, evaluation, and comparison processes among various algorithms. Among the ten annotation tools evaluated, SingleR, Seurat, sciBet, and scSorter emerged as top-performing algorithms in terms of prediction accuracy, with SingleR and sciBet demonstrating particularly superior performance, offering guidance for users. Interested parties can access the scAnnoX package at https://github.com/XQ-hub/scAnnoX.

[Analysis of a patient with Retinitis pigmentosa due to a novel variant of IMPDH1 gene].

OBJECTIVE: To explore the genetic basis for a patient with autosomal dominant retinitis pigmentosa (RP). METHODS: A male patient with RP treated at Gansu Provincial Maternal and Child Health Care Hospital in September 2019 was selected as the study subject. Clinical data was collected. Peripheral blood samples of the patient and his parents were subjected to whole exome sequencing (WES). Candidate variant was validated by Sanger sequencing and bioinformatic analysis. RESULTS: The patient, a 29-year-old male, developed night blindness, amblyopia, visual field defects and optic disc abnormalities since childhood. Gene sequencing revealed that he has harbored a heterozygous c.942G>C (p.Lys314Asn) variant of the IMPDH1 gene, which was inherited from his mother, whilst his father was of the wild type. Based on the guidelines from the American College of Medical Genetics and Genomics, the c.942G>C variant was predicted as likely pathogenic (PM1+PM2_Supporting+PP3+PP1). CONCLUSION: The c.942G>C (p.Lys314Asn) variant in the IMPDH1 gene probably underlay the RP in this patient.

Early detection of emerging viral variants through analysis of community structure of coordinated substitution networks.

The emergence of viral variants with altered phenotypes is a public health challenge underscoring the need for advanced evolutionary forecasting methods. Given extensive epistatic interactions within viral genomes and known viral evolutionary history, efficient genomic surveillance necessitates early detection of emerging viral haplotypes rather than commonly targeted single mutations. Haplotype inference, however, is a significantly more challenging problem precluding the use of traditional approaches. Here, using SARS-CoV-2 evolutionary dynamics as a case study, we show that emerging haplotypes with altered transmissibility can be linked to dense communities in coordinated substitution networks, which become discernible significantly earlier than the haplotypes become prevalent. From these insights, we develop a computational framework for inference of viral variants and validate it by successful early detection of known SARS-CoV-2 strains. Our methodology offers greater scalability than phylogenetic lineage tracing and can be applied to any rapidly evolving pathogen with adequate genomic surveillance data.

Clinically significant changes in genes and variants associated with epilepsy over time: implications for re-analysis.

Despite the significant advances in understanding the genetic architecture of epilepsy, many patients do not receive a molecular diagnosis after genomic testing. Re-analysing existing genomic data has emerged as a potent method to increase diagnostic yields-providing the benefits of genomic-enabled medicine to more individuals afflicted with a range of different conditions. The primary drivers for these new diagnoses are the discovery of novel gene-disease and variants-disease relationships; however, most decisions to trigger re-analysis are based on the passage of time rather than the accumulation of new knowledge. To explore how our understanding of a specific condition changes and how this impacts re-analysis of genomic data from epilepsy patients, we developed Vigelint. This approach combines the information from PanelApp and ClinVar to characterise how the clinically relevant genes and causative variants available to laboratories change over time, and this approach to five clinical-grade epilepsy panels. Applying the Vigelint pipeline to these panels revealed highly variable patterns in new, clinically relevant knowledge becoming publicly available. This variability indicates that a more dynamic approach to re-analysis may benefit the diagnosis and treatment of epilepsy patients. Moreover, this work suggests that Vigelint can provide empirical data to guide more nuanced, condition-specific approaches to re-analysis.

Oncologists' perceptions of tumor genomic profiling and barriers to communicating secondary hereditary risks to African American cancer patients.

BACKGROUND: Tumor genomic profiling (TGP) identifies targets for precision cancer treatments, but also secondary hereditary risks. Oncologists are poorly trained to communicate the results of TGP, especially among patients with lower health literacy, poorer genetics knowledge, and higher mistrust. African American (AA) patients are especially vulnerable to poor understanding due to significant cancer disparities and lower uptake of TGP. The goal of this research is to inform the development of an internet-based brief educational support for oncologists to prepare them to provide better decisional support related to TGP for their AA cancer patients. METHODS: This mixed-methods study used semi-structured interviews of oncologists to inform development of an online survey with a convenience sample of US-based oncologists (n = 50) to assess perceptions of the challenges of TGP and communicating results to AA patients. RESULTS: Most interviewed oncologists felt it was important to consider racial/cultural differences when communicating about hereditary risks. Cost, family dynamics, discrimination concerns, and medical mistrust were identified as particularly salient. Survey respondents' views related to AAs and perceptions of TGP were strongly associated with years since completing training, with recent graduates expressing stronger agreement with statements identifying barriers/disadvantages to TGP for AA patients. CONCLUSIONS: Oncologists who had more recently completed training expressed more negative perceptions of TGP and more perceived challenges in communicating about TGP with their AA patients. Focused training for oncologists that addresses barriers specific to AAs may be helpful in supporting improved communication about TGP and improved decisional support for AA patients with cancer considering TGP to evaluate their tumors.

Prospective cohort study of genomic newborn screening: BabyScreen+ pilot study protocol.

INTRODUCTION: Newborn bloodspot screening (NBS) is a highly successful public health programme that uses biochemical and other assays to screen for severe but treatable childhood-onset conditions. Introducing genomic sequencing into NBS programmes increases the range of detectable conditions but raises practical and ethical issues. Evidence from prospectively ascertained cohorts is required to guide policy and future implementation. This study aims to develop, implement and evaluate a genomic NBS (gNBS) pilot programme. METHODS AND ANALYSIS: The BabyScreen+ study will pilot gNBS in three phases. In the preimplementation phase, study materials, including education resources, decision support and data collection tools, will be designed. Focus groups and key informant interviews will also be undertaken to inform delivery of the study and future gNBS programmes. During the implementation phase, we will prospectively recruit birth parents in Victoria, Australia, to screen 1000 newborns for over 600 severe, treatable, childhood-onset conditions. Clinically accredited whole genome sequencing will be performed following standard NBS using the same sample. High chance results will be returned by genetic healthcare professionals, with follow-on genetic and other confirmatory testing and referral to specialist services as required. The postimplementation phase will evaluate the feasibility of gNBS as the primary aim, and assess ethical, implementation, psychosocial and health economic factors to inform future service delivery. ETHICS AND DISSEMINATION: This project received ethics approval from the Royal Children's Hospital Melbourne Research Ethics Committee: HREC/91500/RCHM-2023, HREC/90929/RCHM-2022 and HREC/91392/RCHM-2022. Findings will be disseminated to policy-makers, and through peer-reviewed journals and conferences.

From Base Pairs to City Squares: Comprehensive Precision Oncology for the Future.

SUMMARY: An increased understanding of the role of the social determinants of health in cancer prevention, cancer care, and outcomes can lead to their integration into genetics and genomics as well as informing interventions and clinical trials, creating a comprehensive precision oncology framework.

Isolation and identification of a novel phage targeting clinical multidrug-resistant Corynebacterium striatum isolates.

Introduction: Over the past decade, Corynebacterium striatum (C. striatum), an emerging multidrug-resistant (MDR) pathogen, has significantly challenged healthcare settings, especially those involving individuals with weakened immune systems. The rise of these superbugs necessitates innovative solutions. Methods: This study aimed to isolate and characterize bacteriophages targeting MDR-C. striatum. Utilizing 54 MDR-C. striatum isolates from a local hospital as target strains, samples were collected from restroom puddles for phage screening. Dot Plaque and Double-layer plate Assays were employed for screening. Results: A novel temperate bacteriophage, named CSP1, was identified through a series of procedures, including purification, genome extraction, sequencing, and one-step growth curves. CSP1 possesses a 39,752 base pair circular double-stranded DNA genome with HK97-like structural proteins and potential for site-specific recombination. It represents a new species within the unclassified Caudoviricetes class, as supported by transmission electron microscopy, genomic evolutionary analysis, and collinearity studies. Notably, CSP1 infected and lysed 21 clinical MDR-C. striatum isolates, demonstrating a wide host range. The phage remained stable in conditions ranging from -40 to 55°C, pH 4 to 12, and in 0.9% NaCl buffer, showing no cytotoxicity. Discussion: The identification of CSP1 as the first phage targeting clinical C. striatum strains opens new possibilities in bacteriophage therapy research, and the development of diagnostic and therapeutic tools against pathogenic bacteria.

Virus-induced host genomic remodeling dysregulates gene expression, triggering tumorigenesis.

Virus-induced genomic remodeling and altered gene expression contribute significantly to cancer development. Some oncogenic viruses such as Human papillomavirus (HPV) specifically trigger certain cancers by integrating into the host's DNA, disrupting gene regulation linked to cell growth and migration. The effect can be through direct integration of viral genomes into the host genome or through indirect modulation of host cell pathways/proteins by viral proteins. Viral proteins also disrupt key cellular processes like apoptosis and DNA repair by interacting with host molecules, affecting signaling pathways. These disruptions lead to mutation accumulation and tumorigenesis. This review focuses on recent studies exploring virus-mediated genomic structure, altered gene expression, and epigenetic modifications in tumorigenesis.

Dual-space disentangled-multimodal network (DDM-net) for glioma diagnosis and prognosis with incomplete pathology and genomic data.

Objective. Effective fusion of histology slides and molecular profiles from genomic data has shown great potential in the diagnosis and prognosis of gliomas. However, it remains challenging to explicitly utilize the consistent-complementary information among different modalities and create comprehensive representations of patients. Additionally, existing researches mainly focus on complete multi-modality data and usually fail to construct robust models for incomplete samples.Approach. In this paper, we propose adual-space disentangled-multimodal network (DDM-net)for glioma diagnosis and prognosis. DDM-net disentangles the latent features generated by two separate variational autoencoders (VAEs) into common and specific components through a dual-space disentangled approach, facilitating the construction of comprehensive representations of patients. More importantly, DDM-net imputes the unavailable modality in the latent feature space, making it robust to incomplete samples.Main results. We evaluated our approach on the TCGA-GBMLGG dataset for glioma grading and survival analysis tasks. Experimental results demonstrate that the proposed method achieves superior performance compared to state-of-the-art methods, with a competitive AUC of 0.952 and a C-index of 0.768.Significance. The proposed model may help the clinical understanding of gliomas and can serve as an effective fusion model with multimodal data. Additionally, it is capable of handling incomplete samples, making it less constrained by clinical limitations.

A chromosome-scale fishing cat reference genome for the evaluation of potential germline risk variants.

The fishing cat, Prionailurus viverrinus, faces a population decline, increasing the importance of maintaining healthy zoo populations. Unfortunately, zoo-managed individuals currently face a high prevalence of transitional cell carcinoma (TCC), a form of bladder cancer. To investigate the genetics of inherited diseases among captive fishing cats, we present a chromosome-scale assembly, generate the pedigree of the zoo-managed population, reaffirm the close genetic relationship with the Asian leopard cat (Prionailurus bengalensis), and identify 7.4 million single nucleotide variants (SNVs) and 23,432 structural variants (SVs) from whole genome sequencing (WGS) data of healthy and TCC cats. Only BRCA2 was found to have a high recurrent number of missense mutations in fishing cats diagnosed with TCC when compared to inherited human cancer risk variants. These new fishing cat genomic resources will aid conservation efforts to improve their genetic fitness and enhance the comparative study of feline genomes.

A chromosome-level genome assembly of the spider mite Tetranychus piercei McGregor.

Despite the rapid advances in sequencing technology, limited genomic resources are currently available for phytophagous spider mites, which include many important agricultural pests. One of these pests is Tetranychus piercei (McGregor), a serious banana pest in East Asia exhibiting remarkable tolerance to high temperature. In this study, we assembled a high-quality genome of T. piercei using a combination of PacBio long reads and Illumina short reads sequencing. With the assistance of chromatin conformation capture technology, 99.9% of the contigs were anchored into three pseudochromosomes with a total size of 86.02 Mb. Repetitive elements, accounting for 14.16% of this genome (12.20 Mb), are predominantly composed of long-terminal repeats (30.7%). By combining evidence of ab initio prediction, transcripts, and homologous proteins, we annotated 11,881 protein-coding genes. Both the genome and proteins have high BUSCO completeness scores (>94%). This high-quality genome, along with reliable annotation, provides a valuable resource for investigating the high-temperature tolerance of this species and exploring the genomic basis that underlies the host range evolution of spider mites.

The chromosomal-scale genome sequencing and assembly of Athetis lepigone.

Athetis lepigone is an emerging highly polyphagous insect pest reported to cause crop damage in several European and Asian countries. However, our understanding of its genetic adaptation mechanisms has been limited due to lack of high-quality genetic resources. In this study, we present a chromosomal-level genome of A. lepigone, representing the first species in the genus of Athetis. We employed PacBio long-read sequencing and Hi-C technologies to generate 612.49 Mb genome assembly which contains 42.43% repeat sequences with a scaffold N50 of 20.9 Mb. The contigs were successfully clustered into 31 chromosomal-size scaffolds with 37% GC content. BUSCO assessment revealed a genome completeness of 97.4% with 96.3 identified as core Arthropoda single copy orthologs. Among the 17,322 genes that were predicted, 15,965 genes were functionally annotated, representing a coverage of 92.17%. Furthermore, we revealed 106 P450, 37 GST, 27 UGT, and 74 COE gene families in the genome of A. lepigone. This genome provides a significant and invaluable genomic resource for further research across the entire genus of Athetis.

Earl Grey: A Fully Automated User-Friendly Transposable Element Annotation and Analysis Pipeline.

Transposable elements (TEs) are major components of eukaryotic genomes and are implicated in a range of evolutionary processes. Yet, TE annotation and characterization remain challenging, particularly for nonspecialists, since existing pipelines are typically complicated to install, run, and extract data from. Current methods of automated TE annotation are also subject to issues that reduce overall quality, particularly (i) fragmented and overlapping TE annotations, leading to erroneous estimates of TE count and coverage, and (ii) repeat models represented by short sections of total TE length, with poor capture of 5' and 3' ends. To address these issues, we present Earl Grey, a fully automated TE annotation pipeline designed for user-friendly curation and annotation of TEs in eukaryotic genome assemblies. Using nine simulated genomes and an annotation of Drosophila melanogaster, we show that Earl Grey outperforms current widely used TE annotation methodologies in ameliorating the issues mentioned above while scoring highly in benchmarking for TE annotation and classification and being robust across genomic contexts. Earl Grey provides a comprehensive and fully automated TE annotation toolkit that provides researchers with paper-ready summary figures and outputs in standard formats compatible with other bioinformatics tools. Earl Grey has a modular format, with great scope for the inclusion of additional modules focused on further quality control and tailored analyses in future releases.

A chromosomal-scale genome assembly of modern cultivated hybrid sugarcane provides insights into origination and evolution.

Sugarcane is a vital crop with significant economic and industrial value. However, the cultivated sugarcane's ultra-complex genome still needs to be resolved due to its high ploidy and extensive recombination between the two subgenomes. Here, we generate a chromosomal-scale, haplotype-resolved genome assembly for a hybrid sugarcane cultivar ZZ1. This assembly contains 10.4 Gb genomic sequences and 68,509 annotated genes with defined alleles in two sub-genomes distributed in 99 original and 15 recombined chromosomes. RNA-seq data analysis shows that sugar accumulation-associated gene families have been primarily expanded from the ZZSO subgenome. However, genes responding to pokkah boeng disease susceptibility have been derived dominantly from the ZZSS subgenome. The region harboring the possible smut resistance genes has expanded significantly. Among them, the expansion of WAK and FLS2 families is proposed to have occurred during the breeding of ZZ1. Our findings provide insights into the complex genome of hybrid sugarcane cultivars and pave the way for future genomics and molecular breeding studies in sugarcane.

Accuracy of Genomic prediction for fleece traits in Inner Mongolia Cashmere goats.

The fleece traits are important economic traits of goats. With the reduction of sequencing and genotyping cost and the improvement of related technologies, genomic selection for goats has become possible. The research collect pedigree, phenotype and genotype information of 2299 Inner Mongolia Cashmere goats (IMCGs) individuals. We estimate fixed effects, and compare the estimates of variance components, heritability and genomic predictive ability of fleece traits in IMCGs when using the pedigree based Best Linear Unbiased Prediction (ABLUP), Genomic BLUP (GBLUP) or single-step GBLUP (ssGBLUP). The fleece traits considered are cashmere production (CP), cashmere diameter (CD), cashmere length (CL) and fiber length (FL). It was found that year of production, sex, herd and individual ages had highly significant effects on the four fleece traits (P < 0.01). All of these factors should be considered when the genetic parameters of fleece traits in IMCGs are evaluated. The heritabilities of FL, CL, CP and CD with ABLUP, GBLUP and ssGBLUP methods were 0.26 ~ 0.31, 0.05 ~ 0.08, 0.15 ~ 0.20 and 0.22 ~ 0.28, respectively. Therefore, it can be inferred that the genetic progress of CL is relatively slow. The predictive ability of fleece traits in IMCGs with GBLUP (56.18% to 69.06%) and ssGBLUP methods (66.82% to 73.70%) was significantly higher than that of ABLUP (36.73% to 41.25%). For the ssGBLUP method is significantly (29% ~ 33%) higher than that with ABLUP, and which is slightly (4% ~ 14%) higher than that of GBLUP. The ssGBLUP will be as an superiors method for using genomic selection of fleece traits in Inner Mongolia Cashmere goats.