Genome Sequence Data Research Articles

Plastid phylogenomics and fossil evidence provide new insights into the evolutionary complexity of the ‘woody clade’ in Saxifragales

BackgroundThe “woody clade” in Saxifragales (WCS), encompassing four woody families (Altingiaceae, Cercidiphyllaceae, Daphniphyllaceae, and Hamamelidaceae), is a phylogenetically recalcitrant node in the angiosperm tree of life, as the interfamilial relationships of the WCS remain contentious. Based on a comprehensive sampling of WCS genera, this study aims to recover a robust maternal backbone phylogeny of the WCS by analyzing plastid genome (plastome) sequence data using Bayesian inference (BI), maximum likelihood (ML), and maximum parsimony (MP) methods, and to explore the possible causes of the phylogenetic recalcitrance with respect to deep relationships within the WCS, in combination with molecular and fossil evidence.ResultsAlthough the four WCS families were identically resolved as monophyletic, the MP analysis recovered different tree topologies for the relationships among Altingiaceae, Cercidiphyllaceae, and Daphniphyllaceae from the ML and BI phylogenies. The fossil-calibrated plastome phylogeny showed that the WCS underwent a rapid divergence of crown groups in the early Cretaceous (between 104.79 and 100.23 Ma), leading to the origin of the stem lineage ancestors of Altingiaceae, Cercidiphyllaceae, Daphniphyllaceae, and Hamamelidaceae within a very short time span (∼4.56 Ma). Compared with the tree topology recovered in a previous study based on nuclear genome data, cytonuclear discordance regarding the interfamilial relationships of the WCS was detected.ConclusionsMolecular and fossil evidence imply that the early divergence of the WCS might have experienced radiative diversification of crown groups, extensive extinctions at the genus and species levels around the Cretaceous/Paleocene boundary, and ancient hybridization. Such evolutionarily complex events may introduce biases in topological estimations within the WCS due to incomplete lineage sorting, cytonuclear discordance, and long-branch attraction, potentially impacting the accurate reconstruction of deep relationships.

The integration of whole‐genome resequencing and ecological niche modelling to conserve profiles of local adaptation

AbstractBackgroundEcological and genomic attributes of populations can provide two orthologous perspectives on the biological profiles associated with local adaptation. The ability of organisms to track suitable habitats (ecological adaptability) and of populations to shift allele frequencies (adaptive potential) are prerequisite for population sustainability.AimsMany contemporary populations are threatened by habitat loss (ecological vulnerability) and a lack of adaptive potential (evolutionary vulnerability). Technical advances provide new opportunities to address these challenges in biological conservation: Future habitat shifts can be predicted by ecological niche modelling and adaptive genetic diversity can be discerned using genome sequence data. Together, these two approaches illuminate the local adaptation profile and help identify the environmental and genomic conditions that should maximize evolutionary fitness.Materials and MethodsHere, we reviewed the primary literature to identify key studies that utilize both whole‐genome resequencing (WGR) and ecological niche modelling (ENM) in an effort to envisage future research directions that may benefit conservation efforts.ResultsWe identified ways to integrate different approaches, such as ENM‐informed adaptive genomics and adaptive genomics‐informed ENMs, that can be used to delineate and conserve local adaptation profiles.DiscussionIntegrative approaches can identify adaptive characteristics, vulnerable populations subject to environmental changes, and the patterns of local adaptation from geographic and genomic analyses. We discuss future research directions, limitations and their potential solutions with suggestions for collaborative workflows.ConclusionThe integration of WGR and ENM is promising with their continuous advancement. An integrative approach can be used to evaluate eco‐evolutionary attributes, at both organismal and molecular levels, that can be used to help conserve local adaptation profiles.

Lost in the Forest: Encoding categorical variables and the absent levels problem

AbstractLevels of a predictor variable that are absent when a classification tree is grown can not be subject to an explicit splitting rule. This is an issue if these absent levels are present in a new observation for prediction. To date, there remains no satisfactory solution for absent levels in random forest models. Unlike missing data, absent levels are fully observed and known. Ordinal encoding of predictors allows absent levels to be integrated and used for prediction. Using a case study on source attribution of Campylobacter species using whole genome sequencing (WGS) data as predictors, we examine how target-agnostic versus target-based encoding of predictor variables with absent levels affects the accuracy of random forest models. We show that a target-based encoding approach using class probabilities, with absent levels designated the highest rank, is systematically biased, and that this bias is resolved by encoding absent levels according to the a priori hypothesis of equal class probability. We present a novel method of ordinal encoding predictors via principal coordinates analysis (PCO) which capitalizes on the similarity between pairs of predictor levels. Absent levels are encoded according to their similarity to each of the other levels in the training data. We show that the PCO-encoding method performs at least as well as the target-based approach and is not biased.

Mutational signature-based identification of DNA repair deficient gastroesophageal adenocarcinomas for therapeutic targeting

Homologous recombination (HR) and nucleotide excision repair (NER) are the two most frequently disabled DNA repair pathways in cancer. HR-deficient breast, ovarian, pancreatic and prostate cancers respond well to platinum chemotherapy and PARP inhibitors. However, the frequency of HR deficiency in gastric and esophageal adenocarcinoma (GEA) still lacks diagnostic and functional validation. Using whole exome and genome sequencing data, we found that a significant subset of GEA, but very few colorectal adenocarcinomas, show evidence of HR deficiency by mutational signature analysis (HRD score). High HRD gastric cancer cell lines demonstrated functional HR deficiency by RAD51 foci assay and increased sensitivity to platinum chemotherapy and PARP inhibitors. Of clinical relevance, analysis of three different GEA patient cohorts demonstrated that platinum treated HR deficient cancers had better outcomes. A gastric cancer cell line with strong sensitivity to cisplatin showed HR proficiency but exhibited NER deficiency by two photoproduct repair assays. Single-cell RNA-sequencing revealed that, in addition to inducing apoptosis, cisplatin treatment triggered ferroptosis in a NER-deficient gastric cancer, validated by intracellular GSH assay. Overall, our study provides preclinical evidence that a subset of GEAs harbor genomic features of HR and NER deficiency and may therefore benefit from platinum chemotherapy and PARP inhibitors.

Improving the performance of supervised deep learning for regulatory genomics using phylogenetic augmentation.

Supervised deep learning is used to model the complex relationship between genomic sequence and regulatory function. Understanding how these models make predictions can provide biological insight into regulatory functions. Given the complexity of the sequence to regulatory function mapping (the cis-regulatory code), it has been suggested that the genome contains insufficient sequence variation to train models with suitable complexity. Data augmentation is a widely used approach to increase the data variation available for model training, however current data augmentation methods for genomic sequence data are limited. Inspired by the success of comparative genomics, we show that augmenting genomic sequences with evolutionarily related sequences from other species, which we term phylogenetic augmentation, improves the performance of deep learning models trained on regulatory genomic sequences to predict high-throughput functional assay measurements. Additionally, we show that phylogenetic augmentation can rescue model performance when the training set is down-sampled and permits deep learning on a real-world small dataset, demonstrating that this approach improves data efficiency. Overall, this data augmentation method represents a solution for improving model performance that is applicable to many supervised deep learning problems in genomics. The open-source GitHub repository agduncan94/phylogenetic_augmentation_paper includes the code for rerunning the analyses here and recreating the figures. Supplementary data are available at Bioinformatics online.

Abstract LB403: Suppression of antigen presentation in pediatric rhabdomyosarcoma

Abstract Background: Rhabdomyosarcoma (RMS) is an aggressive soft tissue sarcoma that is diagnosed based on the tumor cell's resemblance to embryonic or poorly differentiated skeletal muscle progenitors. Multiple immunotherapy clinical trials have found no evidence of immune reactivity against RMS, which has been attributed to the relatively low tumor mutation burden in these cancers. However, we made an unexpected observation that many patient RMS tumors had a near absence of MHC-I expression, a key requisite for anti-tumor CD8+ T lymphocytes and many immunotherapies. In this study, we explore the etiology of low antigen presentation in RMS and systematically evaluate therapeutic interventions that sensitize RMS to immunotherapy. Methods: Surface MHC-I expression was evaluated on pediatric tumor cell lines (n=65) from five major pediatric tumor types. RNA-seq, whole exome and genome sequencing data were analyzed from RMS tumors (total of n=247) and iPSC models of skeletal muscle development (PMID: 32011235). Epigentic drugs targeting DNA methylation (decitabine), EZH2 (tazemetostat), Class I/IV HDACs (mocetinostat), and LSD1 (GSK-LSD1) were used at sub-cytotoxic doses on RMS cell lines (n=10) and analyzed for surface MHC-I expression with flow cytometry and gene expression. T cell cytotoxicity assays were performed using engineered human T cells expressing an optimized TCR which recognizes an HLA*A2:01 restricted peptide from PRAME. Results: RMS cell line models exhibited a range of MHC-I expression with most having low or undetectable MHC-I expression, similar to that of a known MHC-I negative tumor type MYCN-amplified neuroblastoma. Exome sequencing of RMS tumors showed no evidence of loss-of-function alterations in essential antigen processing and presentation (APP) pathway genes. Gene expression profiling by RNAseq and western blotting, however, revealed an absence of core APP genes in many RMS tumors and cell lines. We uncovered that during a specific window of embryonic myogenesis, APP is suppressed and that RMS tumors mimicking this state of development show the deepest loss of APP. Multiple classes of epigenetic drugs were evaluated to rescue APP in RMS. Treatment of RMS using a DNA demethylating agent or HDAC inhibitor exhibited the strongest MHC-I restoration across RMS models with no changes observed using LSD1 or EZH2 inhibitors. As a proof-of-concept, we demonstrate that targeting the RMS antigen PRAME using TCR therapy is enhanced by the inclusion of epigenetic therapy. Conclusions and Significance: We revealed that epigenetic suppression of APP is a new hallmark of RMS and normal embryonic skeletal muscle development. Pharmacological reversal of APP pathway downregulation could be achieved using drugs targeting DNA methylation or class I/IV HDACs, and enhanced T cell cytotoxicity against RMS when used in combination. Overall, these findings may explain the historical lack of RMS responsiveness to immunotherapy and unlocks new immunotherapy strategies against RMS that rely on targeting MHC-I antigens. Citation Format: David Milewski, Hsien-Chao Chou, Vineela Gangalapudi, Meijie Tian, Yong Kim, Young Song, Jun Wei, Javed Khan. Suppression of antigen presentation in pediatric rhabdomyosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB403.

Radiogenomic biomarkers for immunotherapy in glioblastoma: a systematic review of magnetic resonance imaging studies

Abstract Background Immunotherapy is an effective “precision medicine” treatment for several cancers. Imaging signatures of the underlying genome (radiogenomics) in glioblastoma patients may serve as pre-operative biomarkers of the tumor-host immune apparatus. Validated biomarkers would have the potential to stratify patients during immunotherapy clinical trials, and if trials are beneficial, facilitate personalized neo-adjuvant treatment. The increased use of whole genome sequencing data, and the advances in bioinformatics and machine learning make such developments plausible. We performed a systematic review to determine the extent of development and validation of immune-related radiogenomic biomarkers for glioblastoma. Methods A systematic review was performed following PRISMA guidelines using the PubMed, Medline and Embase databases. Qualitative analysis was performed incorporating the QUADAS 2 tool and CLAIM checklist. PROSPERO registered: CRD42022340968. Extracted data was insufficiently homogenous to perform a meta-analysis. Results Nine studies, all retrospective, were included. Biomarkers extracted from MRI volumes of interest included apparent diffusion coefficient values, relative cerebral blood volume values, and image-derived features. These biomarkers correlated with genomic markers from tumor cells or immune cells or with patient survival. The majority of studies had a high risk of bias and applicability concerns regarding the index test performed. Conclusions Radiogenomic immune biomarkers have the potential to provide early treatment options to patients with glioblastoma. Targeted immunotherapy, stratified by these biomarkers, has the potential to allow individualised neo-adjuvant precision treatment options in clinical trials. However, there are no prospective studies validating these biomarkers, and interpretation is limited due to study bias with little evidence of generalizability.

Abstract LB014: The role of genetic alterations in metastatic development insights from a large-scale genomic database

Abstract Metastasis remains a major challenge in cancer treatment, with somatic genetic alterations being a crucial feature in progression. This study harnesses the whole genome sequencing data in the Genomics England biobank (GEL), cataloging of somatic alterations in the context of cancer metastasis. Our research aims to uncover the genetic underpinnings that facilitate the spread of cancer from its primary site to secondary locations by analyzing clinicogenomic data from 3047 cancer patients with metastatic progression. In this study, we analyzed the complex relationship between somatic alterations and cancer progression to uncover significant interactions among these alterations in a broad distribution of common tumor types among well-established oncogenic and tumor suppressor genes. In our study, we employed a Bayesian network approach, enabling us to not only pinpoint crucial genetic contributors to metastasis but also to consider other clinical variables, including patient treatment, sex, age, tumor grade and cancer types. In our analysis, LILRB2 was found to directly increase metastatic risk in hematologic cancer, with prior evidence suggesting its potential as a therapeutic biomarker in colorectal cancer and adversely related to patient prognosis in lung cancer. Similarly, MYL1, initially linked to tumor metastasis and immune infiltration in head and neck squamous cell carcinoma, was also found to increase the risk of metastasis in renal cancer, while interacting with the transcription factor E2F4, marker of poor prognosis in hepatocellular carcinoma. Our study not only confirmed the numerous key somatic gene alterations significantly linked to metastatic behavior across various cancers, but also established their significant roles.Our work highlights the potential of leveraging extensive genomic databases such as GEL to enhance our understanding of cancer metastasis. GEL’s paired germline and somatic data allows us to not only identify mutations unique to cancer cells but also to uncover germline variants that are associated with an elevated risk of cancer and the presence of more aggressive tumor characteristics. By characterizing metastatic risk features, we can explore the opportunities to stratify high-risk patients in clinical trials, with similar effort has been applied to brain metastasis in lung adenocarcinoma. Although tumor heterogeneity poses a treatment challenge due to cell diversity, previous work has demonstrated value in targeting the metastatic potential. For instance, trastuzumab target HER2-positive breast cancers prone to metastasis, markedly improving patient outcomes. Similarly, vemurafenib effectively controls metastatic Melanoma progression by targeting specific mutations like BRAFV600E. Understanding the genetic basis of metastasis could help identify high risk patients and lead to personalized combination therapies addressing various tumor subpopulations. Future research based on these findings could lead to the development of personalized combination treatment strategies that improve patient outcomes. Citation Format: Songjun Xu, Danyang Yu, Shuwei Li, Christopher Moy, Julio Molineros. The role of genetic alterations in metastatic development insights from a large-scale genomic database [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB014.

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 7.4million 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.

Exploring the biotechnological potential of Acinetobacter soli ANG344B: A novel bacterium for 2-phenylethanol production

A bacterium, Acinetobacter soli ANG344B, isolated from river water, exhibited an exceptional capacity to produce 2-phenylethanol (2-PE) using L-phenylalanine (L-Phe) as a precursor—a capability typically observed in yeasts rather than bacteria. Bioreactor experiments were conducted to evaluate the production performance, using glucose as the carbon source for cellular growth and L-Phe as the precursor for 2-PE production. Remarkably, A. soli ANG344B achieved a 2-PE concentration of 2.35 ± 0.26 g/L in just 24.5 h of cultivation, exhibiting a global volumetric productivity of 0.10 ± 0.01 g/L.h and a production yield of 0.51 ± 0.01 g2-PE/gL-Phe, a result hitherto reported only for yeasts. These findings position A. soli ANG344B as a highly promising microorganism for 2-PE production.Whole-genome sequencing of A. soli strain ANG344 revealed a genome size of 3.52 Mb with a GC content of 42.7 %. Utilizing the Rapid Annotation using Subsystem Technology (RAST) server, 3418 coding genes were predicted, including genes coding for enzymes previously associated with the metabolic pathway of 2-PE production in other microorganisms, yet unreported in Acinetobacter species. Through gene mapping, 299 subsystems were identified, exhibiting 30 % subsystem coverage. The whole genome sequence data was submitted to NCBI GeneBank with the BioProject ID PRJNA982713. These draft genome data offer significant potential for exploiting the biotechnological capabilities of A. soli strain ANG344 and for conducting further comparative genomic studies.

On the effect heterogeneity of established disease susceptibility loci for Alzheimer's disease across different genetic ancestries.

Genome-wide association studies have identified numerous disease susceptibility loci (DSLs) for Alzheimer's disease (AD). However, only a limited number of studies have investigated the dependence of the genetic effect size of established DSLs on genetic ancestry. We utilized the whole genome sequencing data from the Alzheimer's Disease Sequencing Project (ADSP) including 35,569 participants. A total of 25,459 subjects in four distinct populations (African ancestry, non-Hispanic White, admixed Hispanic, and Asian) were analyzed. We found that nine DSLs showed significant heterogeneity across populations. Single nucleotide polymorphism (SNP) rs2075650 in translocase of outer mitochondrial membrane 40 (TOMM40) showed the largest heterogeneity (Cochran's Q=0.00, I2=90.08), followed by other SNPs in apolipoprotein C1 (APOC1) and apolipoprotein E (APOE). Two additional loci, signal-induced proliferation-associated 1 like 2 (SIPA1L2) and solute carrier 24 member 4 (SLC24A4), showed significant heterogeneity across populations. We observed substantial heterogeneity for the APOE-harboring 19q13.32 region with TOMM40/APOE/APOC1 genes. The largest risk effect was seen among African Americans, while Asians showed a surprisingly small risk effect.

An X Chromosome Transcriptome Wide Association Study Implicates ARMCX6 in Alzheimer's Disease.

The X chromosome is often omitted in disease association studies despite containing thousands of genes that may provide insight into well-known sex differences in the risk of Alzheimer's disease (AD). To model the expression of X chromosome genes and evaluate their impact on AD risk in a sex-stratified manner. Using elastic net, we evaluated multiple modeling strategies in a set of 175 whole blood samples and 126 brain cortex samples, with whole genome sequencing and RNA-seq data. SNPs (MAF > 0.05) within the cis-regulatory window were used to train tissue-specific models of each gene. We apply the best models in both tissues to sex-stratified summary statistics from a meta-analysis of Alzheimer's Disease Genetics Consortium (ADGC) studies to identify AD-related genes on the X chromosome. Across different model parameters, sample sex, and tissue types, we modeled the expression of 217 genes (95 genes in blood and 135 genes in brain cortex). The average model R2 was 0.12 (range from 0.03 to 0.34). We also compared sex-stratified and sex-combined models on the X chromosome. We further investigated genes that escaped X chromosome inactivation (XCI) to determine if their genetic regulation patterns were distinct. We found ten genes associated with AD at p < 0.05, with only ARMCX6 in female brain cortex (p=0.008) nearing the significance threshold after adjusting for multiple testing (α=0.002). We optimized the expression prediction of X chromosome genes, applied these models to sex-stratified AD GWAS summary statistics, and identified one putative AD risk gene, ARMCX6.

OASIS: An interpretable, finite-sample valid alternative to Pearson’s X2 for scientific discovery

Contingency tables, data represented as counts matrices, are ubiquitous across quantitative research and data-science applications. Existing statistical tests are insufficient however, as none are simultaneously computationally efficient and statistically valid for a finite number of observations. In this work, motivated by a recent application in reference-free genomic inference [K. Chaung et al., Cell 186, 5440-5456 (2023)], we develop Optimized Adaptive Statistic for Inferring Structure (OASIS), a family of statistical tests for contingency tables. OASIS constructs a test statistic which is linear in the normalized data matrix, providing closed-form P-value bounds through classical concentration inequalities. In the process, OASIS provides a decomposition of the table, lending interpretability to its rejection of the null. We derive the asymptotic distribution of the OASIS test statistic, showing that these finite-sample bounds correctly characterize the test statistic's P-value up to a variance term. Experiments on genomic sequencing data highlight the power and interpretability of OASIS. Using OASIS, we develop a method that can detect SARS-CoV-2 and Mycobacterium tuberculosis strains de novo, which existing approaches cannot achieve. We demonstrate in simulations that OASIS is robust to overdispersion, a common feature in genomic data like single-cell RNA sequencing, where under accepted noise models OASIS provides good control of the false discovery rate, while Pearson's [Formula: see text] consistently rejects the null. Additionally, we show in simulations that OASIS is more powerful than Pearson's [Formula: see text] in certain regimes, including for some important two group alternatives, which we corroborate with approximate power calculations.

The impact of telomere length on prostate cancer aggressiveness, genomic instability and health disparities

The telomere repetitive TTAGGG motif at the ends of chromosomes, serves to preserve genomic integrity and chromosomal stability. In turn, genomic instability is a hallmark of cancer—implicating telomere disturbance. Prostate cancer (PCa) shows significant ancestral disparities, with men of African ancestry at the greatest risk for aggressive disease and associated genomic instability. Yet, no study has explored the role of telomere length (TL) with respect to ancestrally driven PCa health disparities. Patient- and technically-matched tumour-blood whole genome sequencing data for 179 ancestrally defined treatment naïve PCa patients (117 African, 62 European), we assessed for TL (blood and tumour) associations. We found shortened tumour TL to be associated with aggressive PCa presentation and elevated genomic instabilities, including percentage of genome alteration and copy number gains, in men of African ancestry. For European patients, tumour TL showed significant associations with PCa driver genes PTEN, TP53, MSH2, SETBP1 and DDX11L1, while shorter blood TL (< 3200 base pairs) and tumour TL (< 2861 base pairs) were correlated with higher risk for biochemical recurrence. Concurring with previous studies linking TL to PCa diagnosis and/or prognosis, for the first time we correlated TL differences with patient ancestry with important implications for future treatments targeting telomere dysfunction.

Clinical and genetic analysis of essential hypertension with mitochondrial tRNAMet 4435A>G and YARS2 mutation.

To investigate the role of m.4435A>G and YARS2 c.572G>T (p.G191V) mutations in the development of essential hypertension. A hypertensive patient with m.4435A>G and YARS2 p.G191V mutations was identified from the mitochondrial genome and exon sequencing data previously collected. Clinical data were collected, and the molecular genetic study was conducted in the proband and his family members. Peripheral venous blood was collected, and immortalized lymphocyte lines were constructed. The mitochondrial tRNA, mitochondrial protein, ATP, mitochondrial membrane potential (MMP), and reactive oxygen species (ROS) in the constructed lymphocyte cell lines were detected. Mitochondrial genome sequencing results showed that all maternal members carried a highly conserved m.4435A>G mutation. The m.4435A>G mutation might affect the secondary structure and folding free energy of mitochondrial tRNA and change its stability, which would affect the anticodon ring structure. Compared with the control group, the cell lines carrying m.4435A>G and YARS2 p.G191V mutations had decreased mitochondrial tRNA homeostasis, partial mitochondrial protein expression, ATP production, and MMP levels, and increased ROS levels. The differences were statistically significant (P<0.05). The YARS2 p.G191V mutation aggravates the changes in mitochondrial translation and mitochondrial function caused by m.4435A>G by affecting the steady-state level of mitochondrial tRNA and further leads to cell dysfunction, indicating that YARS2 p.G191V and m.4435A>G mutations have a synergistic effect in this family and jointly participate in the occurrence and development of essential hypertension.

Rescue of Mycobacterium bovis DNA Obtained from Cultured Samples during Official Surveillance of Animal TB: Key Steps for Robust Whole Genome Sequence Data Generation.

Epidemiological surveillance of animal tuberculosis (TB) based on whole genome sequencing (WGS) of Mycobacterium bovis has recently gained track due to its high resolution to identify infection sources, characterize the pathogen population structure, and facilitate contact tracing. However, the workflow from bacterial isolation to sequence data analysis has several technical challenges that may severely impact the power to understand the epidemiological scenario and inform outbreak response. While trying to use archived DNA from cultured samples obtained during routine official surveillance of animal TB in Portugal, we struggled against three major challenges: the low amount of M. bovis DNA obtained from routinely processed animal samples; the lack of purity of M. bovis DNA, i.e., high levels of contamination with DNA from other organisms; and the co-occurrence of more than one M. bovis strain per sample (within-host mixed infection). The loss of isolated genomes generates missed links in transmission chain reconstruction, hampering the biological and epidemiological interpretation of data as a whole. Upon identification of these challenges, we implemented an integrated solution framework based on whole genome amplification and a dedicated computational pipeline to minimize their effects and recover as many genomes as possible. With the approaches described herein, we were able to recover 62 out of 100 samples that would have otherwise been lost. Based on these results, we discuss adjustments that should be made in official and research laboratories to facilitate the sequential implementation of bacteriological culture, PCR, downstream genomics, and computational-based methods. All of this in a time frame supporting data-driven intervention.

Mitochondrial and Nuclear DNA Variants in Amyotrophic Lateral Sclerosis: Enrichment in the Mitochondrial Control Region and Sirtuin Pathway Genes in Spinal Cord Tissue

Amyotrophic Lateral Sclerosis (ALS) is a progressive disease with prevalent mitochondrial dysfunctions affecting both upper and lower motor neurons in the motor cortex, brainstem, and spinal cord. Despite mitochondria having their own genome (mtDNA), in humans, most mitochondrial genes are encoded by the nuclear genome (nDNA). Our study aimed to simultaneously screen for nDNA and mtDNA genomes to assess for specific variant enrichment in ALS compared to control tissues. Here, we analysed whole exome (WES) and whole genome (WGS) sequencing data from spinal cord tissues, respectively, of 6 and 12 human donors. A total of 31,257 and 301,241 variants in nuclear-encoded mitochondrial genes were identified from WES and WGS, respectively, while mtDNA reads accounted for 73 and 332 variants. Despite technical differences, both datasets consistently revealed a specific enrichment of variants in the mitochondrial Control Region (CR) and in several of these genes directly associated with mitochondrial dynamics or with Sirtuin pathway genes within ALS tissues. Overall, our data support the hypothesis of a variant burden in specific genes, highlighting potential actionable targets for therapeutic interventions in ALS.

Mutations overlying the miR172 target site of TOE-type genes are prime candidate variants for the double-flower trait in mei

Mutations affecting flower shape in many plants have been favored by human selection, and various fruit trees are also grown for ornamental purposes. Mei (Prunus mume) is a dual purpose tree originated in China well known in the Western world for its generous early blooms, often bearing double flowers. Building on the knowledge of its genomic location, a candidate gene approach was used to identify a 49 bp deletion encompassing the miR172 target site of the euAP2 gene pmTOE (PmuVar_Ch1_3490) as a prime variant linked to flower doubleness. Searching within a large dataset of genome sequencing data from Eastern germplasm collections demonstrated a tight variant-trait association, further confirmed in a panel of commercial and non-commercial varieties available in Italy. Moreover, two SNP mutations in the miR172 target site of pmPET (PmuVar_Ch1_1333) were identified in some double flower accessions. The mei orthologue of PETALOSA genes already found responsible for the phenotype in other plants suggests that independent variants may have been selected throughout mei domestication history.

Auto-phylo v2 and auto-phylo-pipeliner: building advanced, flexible, and reusable pipelines for phylogenetic inferences, estimation of variability levels and identification of positively selected amino acid sites.

The vast amount of genome sequence data that is available, and that is predicted to drastically increase in the near future, can only be efficiently dealt with by building automated pipelines. Indeed, the Earth Biogenome Project will produce high-quality reference genome sequences for all 1.8 million named living eukaryote species, providing unprecedented insight into the evolution of genes and gene families, and thus on biological issues. Here, new modules for gene annotation, further BLAST search algorithms, further multiple sequence alignment methods, the adding of reference sequences, further tree rooting methods, the estimation of rates of synonymous and nonsynonymous substitutions, and the identification of positively selected amino acid sites, have been added to auto-phylo (version 2), a recently developed software to address biological problems using phylogenetic inferences. Additionally, we present auto-phylo-pipeliner, a graphical user interface application that further facilitates the creation and running of auto-phylo pipelines. Inferences on S-RNase specificity, are critical for both cross-based breeding and for the establishment of pollination requirements. Therefore, as a test case, we develop an auto-phylo pipeline to identify amino acid sites under positive selection, that are, in principle, those determining S-RNase specificity, starting from both non-annotated Prunus genomes and sequences available in public databases.

Polygenic risk associated with Alzheimer's disease and other traits influences genes involved in T cell signaling and activation.

T cells, known for their ability to respond to an enormous variety of pathogens and other insults, are increasingly recognized as important mediators of pathology in neurodegeneration and other diseases. T cell gene expression phenotypes can be regulated by disease-associated genetic variants. Many complex diseases are better represented by polygenic risk than by individual variants. We first compute a polygenic risk score (PRS) for Alzheimer's disease (AD) using genomic sequencing data from a cohort of Alzheimer's disease (AD) patients and age-matched controls, and validate the AD PRS against clinical metrics in our cohort. We then calculate the PRS for several autoimmune disease, neurological disorder, and immune function traits, and correlate these PRSs with T cell gene expression data from our cohort. We compare PRS-associated genes across traits and four T cell subtypes. Several genes and biological pathways associated with the PRS for these traits relate to key T cell functions. The PRS-associated gene signature generally correlates positively for traits within a particular category (autoimmune disease, neurological disease, immune function) with the exception of stroke. The trait-associated gene expression signature for autoimmune disease traits was polarized towards CD4+ T cell subtypes. Our findings show that polygenic risk for complex disease and immune function traits can have varying effects on T cell gene expression trends. Several PRS-associated genes are potential candidates for therapeutic modulation in T cells, and could be tested in in vitro applications using cells from patients bearing high or low polygenic risk for AD or other conditions.