Genomic Efforts Research Articles

The landscape of structural variation in aye-ayes (Daubentonia madagascariensis).

Aye-ayes (Daubentonia madagascariensis) are one of the 25 most critically endangered primate species in the world. Endemic to Madagascar, their small and highly fragmented populations make them particularly vulnerable to both genetic disease and anthropogenic environmental changes. Over the past decade, conservation genomic efforts have largely focused on inferring and monitoring population structure based on single nucleotide variants to identify and protect critical areas of genetic diversity. However, the recent release of a highly contiguous genome assembly allows, for the first time, for the study of structural genomic variation (deletions, duplications, insertions, and inversions) which are likely to impact a substantial proportion of the species' genome. Based on whole-genome, short-read sequencing data from 14 individuals, >1,000 high-confidence autosomal structural variants were detected, affecting ~240 kb of the aye-aye genome. The majority of these variants (>85%) were deletions shorter than 200 bp, consistent with the notion that longer structural mutations are often associated with strongly deleterious fitness effects. For example, two deletions longer than 850 bp located within disease-linked genes were predicted to impose substantial fitness deficits owing to a resulting frameshift and gene fusion, respectively; whereas several other major effect variants outside of coding regions are likely to impact gene regulatory landscapes. Taken together, this first glimpse into the landscape of structural variation in aye-ayes will enable future opportunities to advance our understanding of the traits impacting the fitness of this endangered species, as well as allow for enhanced evolutionary comparisons across the full primate clade.

A Review on Balancing Genomic Selection Efforts for Allogamous Plant Breeding

Genomic selection (GS) represents a paradigm shift in allogamous plant breeding, leveraging genome-wide marker data to predict the genetic potential of breeding candidates with unprecedented accuracy. This comprehensive review explores the evolution, principles, and applications of GS, highlighting its transformative impact on breeding efficiency and crop improvement. GS uses dense SNP markers to capture the genetic architecture of complex traits, surpassing traditional marker-assisted selection in predictive power. The integration of GS in breeding programs for crops like maize and perennial ryegrass has demonstrated significant gains in traits such as yield, disease resistance, and stress tolerance. Despite its advantages, GS faces challenges including high genotyping costs, the need for large training populations, and the complexity of genetic architectures. Economic constraints and ethical concerns about genetic diversity and data access also pose barriers. Emerging technologies such as AI, machine learning, high-throughput phenotyping, and genome editing hold promise for enhancing GS's accuracy and efficiency. Future strategies should focus on optimizing resource allocation, integrating GS with conventional breeding methods, and fostering collaborative efforts for data sharing and capacity building. The long-term impact of GS is profound, potentially accelerating breeding cycles, enhancing genetic diversity, and developing climate-resilient crops. Collaborative initiatives and open-access genomic resources will be crucial in overcoming current limitations and ensuring that GS benefits global agriculture. As GS continues to evolve, it promises to drive sustainable agricultural practices and improve food security, meeting the challenges posed by climate change and a growing global population. This review underscores the critical role of GS in modern plant breeding and its potential to revolutionize crop improvement.

Genomic surveillance reveals low-level circulation of two subtypes of genogroup C coxsackievirus A10 in Nanchang, Jiangxi Province, China, 2015-2023.

In recent years, coxsackievirus (CV) A10 has been associated with increasing sporadic hand, foot, and mouth disease (HFMD) cases and outbreaks globally. In addition to mild symptoms such as pharyngitis and herpangina, CVA10-related complications or even fatality can occur. Currently, systematic phylogenetic studies of CVA10 are limited. In this study, we first explored the epidemiological and genetic characteristics of CVA10 in Nanchang, an inland southeastern city of China, based on the HFMD surveillance network from 2015-2023. Among 3429 enterovirus-positive cases, 110 (3.04%) were associated with CVA10, with a male-to-female ratio of 1.62. The median age of the CVA10 patients was 2.3 years (interquartile range, IQR 1.0-4.0), with 94.55% (104/110) of the patients aged less than 5 years. Phylogenetic analyses using the full-length VP1, 5'UTR, P1, P2, P3 sequences and near full-length genomes indicated that CVA10 strains (n = 57) isolated in Nanchang belonged to genogroup C; two strains identified in 2017 belonged to C1 subtypes clustered with strains from Vietnam, Madagascar, France and Spain; and the others belonged to C2 subtypes interdigitating with CVA10 isolates from mainland China, the United States and Australia. Through extensive analysis, we identified a rare F168Y mutation in epitope 4 of VP1 in a Madagascar strain of genogroup F and a Chinese strain of genogroup C. Based on Bayesian evolutionary analyses, the average nucleotide substitution rate for the VP1 gene of CV10 strains was 3.07×10-3 substitutions/site/year. The most recent common ancestor (tMRCA) of genogroup C was dated 1990.84, and the tMRCA of CVA10 strains from Nanchang was dated approximately 2003.16, similar to strains circulating in other regions of China, suggesting that the viruses were likely introduced and cryptically circulated in China before the establishment of the HFMD surveillance network. Recombination analysis indicated intertypic recombination of the Nanchang strain with the genogroup G strain in the 3D region. Given the shifting dominance of viral genotypes and frequent recombination events, the existing surveillance system needs to be regulated to enhance genomic surveillance efforts on a more diverse spectrum of genotypes in the future.

Cross transferability of finger millet SSR markers to little millet (Panicum sumatrense Roth. Ex Roem & Schult.)

Little millet is an important cereal known as a “nutra-grain' because of its numerous health benefits. Due to lack of genomic information, the present study analyzed the cross-transferability of finger millet SSR markers to little millet. SSR analysis using genomic DNA with 18 available markers in little millet revealed that 12 SSR markers had unique amplicons with the expected size, indicating 66.66 % cross-transferability. This indicates the conservation of the repetitive motifs AG, CTG, GTT, ACG, CGG, (GA)26, (TC)21, (CA)7N12 (GA)15, and (GA)7AA (GA)19 in both species. Genetic analysis with these transferable twelve SSR markers in 16 little millet genotypes revealed a total of 39 alleles with an average of 3.25 alleles per primer. The highest number of alleles (8) was found at GB-FM -53, while the lowest number of alleles (2) was found at GB-FM -67, GB-FM -87, GB-FM -98 and UGEP-101. Out of the total twelve amplified primers, four primers GB-FM -53, GB-FM -67, GB-FM -70 and UGEP-93 were found to be highly effective and best based on highest SSR primer index value, observed and effective number of alleles, Nei genetic diversity, Shannon information index and polymorphic information content. Finger millet SSR markers distinguished sixteen genotypes of little into two major clusters, where two genotypes, WV-151 and WV-152, were highly diverse. This study establishes the high cross-transferability of finger millet SSR markers to little millet facilitating genomic research and breeding efforts for genetically neglected little millet.

Extended genome-wide association study employing the African genome resources panel identifies novel susceptibility loci for Alzheimer's disease in individuals of African ancestry.

Despite a two-fold risk, individuals of African ancestry have been underrepresented in Alzheimer's disease (AD) genomics efforts. Genome-wide association studies (GWAS) of 2,903 AD cases and 6,265 controls of African ancestry. Within-dataset results were meta-analyzed, followed by functional genomics analyses. A novel AD-risk locus was identified in MPDZ on chromosome (chr) 9p23 (rs141610415, MAF=0.002, p=3.68×10-9). Two additional novel common and nine rare loci were identified with suggestive associations (P<9×10-7). Comparison of association and linkage disequilibrium (LD) patterns between datasets with higher and lower degrees of African ancestry showed differential association patterns at chr12q23.2 (ASCL1), suggesting that this association is modulated by regional origin of local African ancestry. These analyses identified novel AD-associated loci in individuals of African ancestry and suggest that degree of African ancestry modulates some associations. Increased sample sets covering as much African genetic diversity as possible will be critical to identify additional loci and deconvolute local genetic ancestry effects. Genetic ancestry significantly impacts risk of Alzheimer's Disease (AD). Although individuals of African ancestry are twice as likely to develop AD, they are vastly underrepresented in AD genomics studies. The Alzheimer's Disease Genetics Consortium has previously identified 16 common and rare genetic loci associated with AD in African American individuals. The current analyses significantly expand this effort by increasing the sample size and extending ancestral diversity by including populations from continental Africa. Single variant meta-analysis identified a novel genome-wide significant AD-risk locus in individuals of African ancestry at the MPDZ gene, and 11 additional novel loci with suggestive genome-wide significance at p<9×10-7. Comparison of African American datasets with samples of higher degree of African ancestry demonstrated differing patterns of association and linkage disequilibrium at one of these loci, suggesting that degree and/or geographic origin of African ancestry modulates the effect at this locus. These findings illustrate the importance of increasing number and ancestral diversity of African ancestry samples in AD genomics studies to fully disentangle the genetic architecture underlying AD, and yield more effective ancestry-informed genetic screening tools and therapeutic interventions.

Tracking the prevalence and emergence of SARS-CoV-2 variants of concern using a regional genomic surveillance program.

In our manuscript, we describe the results of SARS-CoV-2 genomic surveillance from February 2021 to June 2022 at a metropolitan hospital in the United States. We demonstrate that consistent daily sampling is sufficient to track the regional prevalence and emergence of variants of concern (VOCs). Similar sampling efforts should be considered a viable option for local SARS-CoV-2 genomic surveillance at other regional laboratories. While the SARS-CoV-2 pandemic has evolved into a more endemic form, we still believe that additional real-world information about sampling, procedures, and data interpretation is valuable for ongoing as well as future genomic surveillance efforts. Our study should be of substantial interest to clinical virologists.

Topography of mutational signatures in non-small cell lung cancer: emerging concepts, clinical applications, and limitations.

The genome of a cell is continuously battered by a plethora of exogenous and endogenous processes that can lead to damaged DNA. Repair mechanisms correct this damage most of the time, but failure to do so leaves mutations. Mutations do not occur in random manner, but rather typically follow a more or less specific pattern due to known or imputed mutational processes. Mutational signature analysis is the process by which the predominant mutational process can be inferred for a cancer and can be used in several contexts to study both the genesis of cancer and its response to therapy. Recent pan-cancer genomic efforts such as "The Cancer Genome Atlas" have identified numerous mutational signatures that can be categorized into single base substitutions, doublet base substitutions, or small insertions/deletions. Understanding these mutational signatures as they occur in non-small lung cancer could improve efforts at prevention, predict treatment response to personalized treatments, and guide the development of therapies targeting tumor evolution. For non-small cell lung cancer, several mutational signatures have been identified that correlate with exposures such as tobacco smoking and radon and can also reflect endogenous processes such as aging, APOBEC activity, and loss of mismatch repair. Herein, we provide an overview of the current knowledge of mutational signatures in non-small lung cancer.

Abstract A023: Stratification of bladder cancer patients with the use of flow cytometry is increasing the diagnostic potential of molecular classifiers

Abstract Recent research suggests the potential categorization of bladder cancer (BLCa) patients into molecular subtypes to aid in the selection of appropriate treatment strategies, be it conventional, targeted, or a combination thereof. However, the practical implementation of molecular classifiers has faced obstacles due to the intricate nature of gene regulation, tumor heterogeneity, and challenges related to tumor sampling caused by substantial stromal infiltration and tumor multifocality. Hence, there is a pressing need for more straightforward marker-based methodologies to assist in genomic and transcriptomic subtyping efforts. Our study addressed this gap by establishing and validating a panel of antibodies for application in flow cytometry (FCM) to enhance the stratification of BLCa patients. We curated a set of 17 FCM markers capable of delineating four cell clusters (epithelial, immune, endothelial, and stromal) and defining tumor classification (basal and luminal), immune infiltration, and hot-target expression on BLCa tissue samples. This FCM panel was deployed on ex vivo tissue samples treated with chemotherapy and targeted therapy agents. Initially tested on a cohort of 10 BLCa tissue samples, our validation of the FCM panel revealed correlations between marker expression and clinical-pathological features, such as the presence of metastasis and heightened immune and stromal infiltration. Notably, samples exhibiting lower claudin-4 levels displayed increased immune infiltration, while those with metastases at diagnosis showcased elevated basal marker expression. The translational potential of the FCM panel was demonstrated in ex vivo experiments where tissue slices from six patients were subjected to chemotherapy and targeted therapy agents, leading to observable shifts in marker expression post-treatment, particularly pronounced with chemotherapy. Noteworthy effects included reductions in epithelial cells expressing FGFR3 and EGFR following targeted therapy with erdafitinib or lapatinib, alongside alterations in the basal/luminal cell ratio indicated by increased CD44, CD90, and CD239 marker expressions. Our findings underscore the value of FCM in categorizing BLCa patients based on specific marker expression, supplementing conventional histological analyses to enhance cancer diagnosis, guide personalized therapeutic approaches, and monitor treatment efficacy. Citation Format: Martina Radic, Federico La Manna, Martina Minoli, Panagiotis Chouvardas, George N. Thalmann, Roland Seiler-Blarer, Marianna Kruithof-de Julio, Bernhard Kiss. Stratification of bladder cancer patients with the use of flow cytometry is increasing the diagnostic potential of molecular classifiers [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr A023.

Optimisation and evaluation of viral genomic sequencing of SARS-CoV-2 rapid diagnostic tests: a laboratory and cohort-based study

Sequencing of SARS-CoV-2 from rapid diagnostic tests (RDTs) can bolster viral genomic surveillance efforts; however, approaches to maximise and standardise pathogen genome recovery from RDTs remain underdeveloped. We aimed to systematically optimise the elution of genetic material from RDT components and to evaluate the efficacy of RDT sequencing for outbreak investigation. In this laboratory and cohort-based study we seeded RDTs with inactivated SARS-CoV-2 to optimise the elution of genomic material from RDT lateral flow strips. We measured the effect of changes in buffer type, time in buffer, and rotation on PCR cycle threshold (Ct) value. We recruited individuals older than 18 years residing in the greater Boston area, MA, USA, from July 18 to Nov 5, 2022, via email advertising to students and staff at Harvard University, MA, USA,and via broad social media advertising. All individuals recruited were within 5days of a positive diagnostic test for SARS-CoV-2; no other relevant exclusion criteria were applied. Each individual completed two RDTs and one PCR swab. On Dec 29, 2022, we also collected RDTs from a convenience sample of individuals who were positive for SARS-CoV-2 and associated with an outbreak at a senior housing facility in MA, USA. We extracted all returned PCR swabs and RDT components (ie, swab, strip, or buffer); samples with a Ct of less than 40 were subject to amplicon sequencing. We compared the efficacy of elution and sequencing across RDT brands and components and used RDT-derived sequences to infer transmission links within the outbreak at the senior housing facility. We conducted metagenomic sequencing of negative RDTs from symptomatic individuals living in the senior housing facility. Neither elution duration of greater than 10 min nor rotation during elution impacted viral titres. Elution in Buffer AVL (Ct=31·4) and Tris-EDTA Buffer (Ct=30·8) were equivalent (p=0·34); AVL outperformed elution in lysis buffer and 50% lysis buffer (Ct=40·0, p=0·0029 for both) as well as Universal Viral Transport Medium (Ct=36·7, p=0·079). Performance of RDT strips was poorer than that of matched PCR swabs (mean Ct difference 10·2 [SD 4·3], p<0·0001); however, RDT swabs performed similarly to PCR swabs (mean Ct difference 4·1 [5·2], p=0·055). No RDT brand significantly outperformed another. Across sample types, viral load predicted the viral genome assembly length. We assembled greater than 80% complete genomes from 12 of 17 RDT-derived swabs, three of 18 strips, and four of 11 residual buffers. We generated outbreak-associated SARS-CoV-2 genomes using both amplicon and metagenomic sequencing and identified multiple introductions of the virus that resulted in downstream transmission. RDT-derived swabs are a reasonable alternative to PCR swabs for viral genomic surveillance and outbreakinvestigation. RDT-derived lateral flow strips yield accurate, but significantly fewer, viral reads than matched PCR swabs. Metagenomic sequencing of negative RDTs can identify viruses that might underlie patient symptoms. The National Science Foundation, the Hertz Foundation, the National Institute of General Medical Sciences, Harvard Medical School, the Howard Hughes Medical Institute, the US Centers for Disease Control and Prevention, the Broad Institute and the National Institute of Allergy and Infectious Diseases.

Abstract 2446: Genomic landscape of longitudinally collected preinvasive airway lesions

Abstract Lung carcinoma in situ (CIS) lesions, as precursors to squamous cell carcinoma, exhibit microscopic uniformity while displaying diverse clinical trajectories. Half of these lesions progress to invasive cancer, while the remaining half either regress or remain indolent. Previous genomic profiling efforts have elucidated progression-specific genomic changes against a backdrop of inherent heterogeneity and notable chromosomal instability signatures. Here, we present a novel approach by analyzing longitudinally collected samples of preinvasive airway lesions, encompassing both progressive and indolent trajectories. Our findings reveal that genomic integrity and cell cycle dynamics constitute key distinctions between progressive and indolent lesions. Notably, a decrease in clonal diversity and an inverse correlation between TCRA-Tcell fraction and genomic instability are observed as lesions approach invasion. Somatic mutations in cancer driver genes BRAC2, CSMD3, and MUC16 are found significantly associated with lesion progression. Furthermore, progressive lesions exhibit a higher frequency of copy number changes compared to indolent lesions. Copy number loss in 1p, 3p, 9p, and 17p are found to be significantly associated with lesion progression. Phylogenetic analysis further confirms positive selection for copy number loss in these specific genomic regions, providing insights into the evolutionary trajectory of alterations in progressive lesions. The comprehensive understanding derived from these genomic analyses is anticipated to advance early detection strategies, mitigate overtreatment, and facilitate the development of preventative therapies targeting early clonal events in lung cancer. Citation Format: Ahmed Alhendi, Lukas Kalinke, Adam Pennycuick, Kate Davies, Pascal Durrenberger, Kate Gowers, Kristiana Grigoriadis, Nicholas McGranahan, Sam Janes. Genomic landscape of longitudinally collected preinvasive airway lesions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2446.

Genome-wide analysis of MADS-box transcription factor gene family in wild emmer wheat (Triticum turgidum subsp. dicoccoides).

The members of MADS-box gene family have important roles in regulating the growth and development of plants. MADS-box genes are highly regarded for their potential to enhance grain yield and quality under shifting global conditions. Wild emmer wheat (Triticum turgidum subsp. dicoccoides) is a progenitor of common wheat and harbors valuable traits for wheat improvement. Here, a total of 117 MADS-box genes were identified in the wild emmer wheat genome and classified to 90 MIKCC, 3 MIKC*, and 24 M-type. Furthermore, a phylogenetic analysis and expression profiling of the emmer wheat MADS-box gene family was presented. Although some MADS-box genes belonging to SOC1, SEP1, AGL17, and FLC groups have been expanded in wild emmer wheat, the number of MIKC-type MADS-box genes per subgenome is similar to that of rice and Arabidopsis. On the other hand, M-type genes of wild emmer wheat is less frequent than that of Arabidopsis. Gene expression patterns over different tissues and developmental stages agreed with the subfamily classification of MADS-box genes and was similar to common wheat and rice, indicating their conserved functionality. Some TdMADS-box genes are also differentially expressed under drought stress. The promoter region of each of the TdMADS-box genes harbored 6 to 48 responsive elements, mainly related to light, however hormone, drought, and low-temperature related cis-acting elements were also present. In conclusion, the results provide detailed information about the MADS-box genes of wild emmer wheat. The present work could be useful in the functional genomics efforts toward breeding for agronomically important traits in T. dicoccoides.

Genomic characterization of SARS-CoV-2 in Guinea, West Africa.

SARS-CoV-2 has claimed several million lives since its emergence in late 2019. The ongoing evolution of the virus has resulted in the periodic emergence of new viral variants with distinct fitness advantages, including enhanced transmission and immune escape. While several SARS-CoV-2 variants of concern trace their origins back to the African continent-including Beta, Eta, and Omicron-most countries in Africa remain under-sampled in global genomic surveillance efforts. In an effort to begin filling these knowledge gaps, we conducted retrospective viral genomic surveillance in Guinea from October 2020 to August 2021. We found that SARS-CoV-2 clades 20A, 20B, and 20C dominated throughout 2020 until the coincident emergence of the Alpha and Eta variants of concern in January 2021. The Alpha variant remained dominant throughout early 2021 until the arrival of the Delta variant in July. Surprisingly, despite the small sample size of our study, we also found the persistence of the early SARS-CoV-2 clade 19B as late as April 2021. Together, these data help fill in our understanding of the SARS-CoV-2 population dynamics in West Africa early in the COVID-19 pandemic.

Genetic Diversity and Population Structure of Jujube Cultivars in the United States Revealed by Single Nucleotide Polymorphism Markers

The nutritional and medicinal significance of jujube (Ziziphus jujuba) has led to persistent efforts in genomics to accelerate the utilization of its germplasm resources. However, the absence of accurate genetic identity of existing germplasm limits these studies. In the United States, different names were frequently given to the same jujube cultivars because the pedigrees of the imported germplasm are unclear. The present study selected a panel of 147 single nucleotide polymorphism (SNP) markers distributed across the jujube genome to examine genetic identity, genetic diversity, and population structure in 177 jujube cultivars sampled from different locations in the United States. SNP profile multilocus matching reported a total of 23 synonymous groups including 116 samples that were identical to at least one other sample. This led to the detection of 74 unique genotypes for subsequent diversity analysis. Model-based genetic structure analysis divided the distinctive genotypes into three major groups, with some admixtures among the groups. The genetic differentiation among these groups was further validated by analysis of molecular variance (Fst = 0.199, P value &lt; 0.001), principal coordinate analysis, and clustering analysis. Morphological traits were studied in some of the genetically identical commercial cultivar groups, (i.e., Li, Lang, and Jinsi). Results demonstrated significant morphological differences within genetically identical cultivars in the Jinsi group, indicating phenotypic variation resulting from mutations in these clones.

Dispersion patterns of SARS-CoV-2 variants Gamma, Lambda and Mu in Latin America and the Caribbean

Latin America and Caribbean (LAC) regions were an important epicenter of the COVID-19 pandemic and SARS-CoV-2 evolution. Through the COVID-19 Genomic Surveillance Regional Network (COVIGEN), LAC countries produced an important number of genomic sequencing data that made possible an enhanced SARS-CoV-2 genomic surveillance capacity in the Americas, paving the way for characterization of emerging variants and helping to guide the public health response. In this study we analyzed approximately 300,000 SARS-CoV-2 sequences generated between February 2020 and March 2022 by multiple genomic surveillance efforts in LAC and reconstructed the diffusion patterns of the main variants of concern (VOCs) and of interest (VOIs) possibly originated in the Region. Our phylogenetic analysis revealed that the spread of variants Gamma, Lambda and Mu reflects human mobility patterns due to variations of international air passenger transportation and gradual lifting of social distance measures previously implemented in countries. Our results highlight the potential of genetic data to reconstruct viral spread and unveil preferential routes of viral migrations that are shaped by human mobility patterns.

Plant genomic resources at National Genomics Data Center: assisting in data-driven breeding applications.

The online version contains supplementary material available at 10.1007/s42994-023-00134-4.

Beyond the factor indeterminacy problem using genome-wide association data.

Latent factors, such as general intelligence, depression and risk tolerance, are invoked in nearly all social science research where a construct is measured via aggregation of symptoms, question responses or other measurements. Because latent factors cannot be directly observed, they are inferred by fitting a specific model to empirical patterns of correlations among measured variables. A long-standing critique of latent factor theories is that the correlations used to infer latent factors can be produced by alternative data-generating mechanisms that do not include latent factors. This is referred to as the factor indeterminacy problem. Researchers have recently begun to overcome this problem by using information on the associations between individual genetic variants and measured variables. We review historical work on the factor indeterminacy problem and describe recent efforts in genomics to rigorously test the validity of latent factors, advancing the understanding of behavioural science constructs.

Human Genetics of Defects of Situs.

Defects of situs are associated with complex sets of congenital heart defects in which the normal concordance of asymmetric thoracic and abdominal organs is disturbed. The cellular and molecular mechanisms underlying the formation of the embryonic left-right axis have been investigated extensively in the past decade. This has led to the identification of mutations in at least 33 different genes in humans with heterotaxy and situs defects. Those mutations affect a broad range of molecular components, from transcription factors, signaling molecules, and chromatin modifiers to ciliary proteins. A substantial overlap of these genes is observed with genes associated with other congenital heart diseases such as tetralogy of Fallot and double-outlet right ventricle, d-transposition of the great arteries, and atrioventricular septal defects. In this chapter, we present the broad genetic heterogeneity of situs defects including recent human genomics efforts.

The Exceptionally Large Genomes of the Fabeae Tribe: Comparative Genomics and Applications in Abiotic and Biotic Stress Studies

The Fabeae tribe comprises five legume genera, which include some of the most ancient and important crops, like peas, lentils, and faba beans. Biotic and environmental stresses are major threats to the stable and high productivity of Fabeae crops. The use of omics resources can provide breeders with the tools needed to develop new crop varieties in a more efficient and sustainable way. However, the genomic efforts on Fabeae crops have lagged behind compared to other legume species, mainly due to their large genome size and repeat content. The first annotated chromosome-level reference genome assembly in Fabeae was published for pea (Pisum sativum cv. Caméor) in 2019. Since then, many efforts have been made to sequence the genome of other species from this tribe. Currently, 17 genomes of Fabeae species are available for the scientific community; five of them are at the chromosome level. Fundamental knowledge and molecular tools for breeding have been boosted on the legume resistance/tolerance against biotic and abiotic stresses by the availability of some of these recent reference genomes, especially the pea cv. Caméor genome. This review provides a comparison of the Fabeae tribe genomes available and an overview of recent accomplishments in their application in abiotic and biotic stress research.

Streptococcus ruminantium-associated sheep mastitis outbreak detected in Italy is distinct from bovine isolates

Streptococcus ruminantium is the causative agent of several bovine and ovine diseases, however reports are uncommon and application of whole genome sequencing to identify is rare. We report for the first time, a severe ovine mastitis outbreak caused by S. ruminantium in Italy, 2022. S. ruminantium was isolated from 12 adult lactating ewes with diffuse nodules in the mammary parenchyma and predominantly serous and clotted milk. All outbreak isolates, along with five additional historical Italian isolates (between 2011 and 2017), were genomically characterised and then analysed in the context of all publicly available S. ruminantium genomes. Antimicrobial susceptibility testing was performed to determine the MICs of 16 antibiotics. The results showed that all isolates were susceptible to all antimicrobials tested except kanamycin. Single Nucleotide Variant analysis confirmed this as a clonal outbreak across 10 sheep (≤ 15 SNVs), while the two others were colonised by more distantly related clones (≤ 53 pairwise SNVs), indicating the presence of multiple infecting lineages. The five historical S. ruminantium isolates were comprised of genetically-distant singletons (between 1259 and 5430 pairwise SNVs to 2022 outbreak isolates). Ovine isolates were found to be genetically distinct to bovine isolates, forming monophyletic groups. Bovine isolates were similarly made up of singleton clones in all but two isolates. Taken together, our genomic analysis using all globally available genomes is consistent with general opportunistic pathogenesis of S. ruminantium. We encourage future genomic surveillance efforts to facilitate outbreak detection, as well as improve our understanding of this poorly-understood, multi-host, zoonotic pathogen.

2299. Genomic Epidemiology of SARS-CoV-2 in Metropolitan Detroit

Abstract Background The COVID-19 pandemic, resulting from the rapidly evolving SARS-CoV-2 virus, has drastically impacted health systems and economies worldwide. Genomic sequencing is critical for the surveillance of SARS-CoV-2 to monitor the rapidly evolving virus and identify new strains. Methods 583 isolates from Henry Ford Health were retrospectively profiled across 3 years (117 isolates in 2020; 39 in 2021; 427 in 2022). DNA was extracted using Kingfisher viral isolation kit; RT-PCR screening was used to identify isolates with cycle threshold &amp;lt; 32 for whole genome sequencing (WGS). Libraries were generated using QIAseq DIRECT SARS-CoV-2 Kit, followed by Illumina sequencing (MiSeq or NovaSeq 6000; 300 cycles). Lineage analysis of the SARS-CoV-2 consensus genome sequences generated from samtools variant analysis pipeline was determined using Nextclade and Pangolin software. Results Sequences were classified into 11 unique clades across 108 lineages by Nextclade and Pangolin, respectively. Almost three-fourths of the sequenced isolates were from 2022. 117 (20%) genomes were from the early pandemic (2020) and were clustered into 8 clades: 19A, 19B, 20A, 20B, 20C, 21 J (Delta) and 21L (Omicron). Most of the 2022 genomes (72%) were in clade 20C from lineage B.1, identified during the outbreak in Europe. 15 (13%) genomes had clade 19A (lineage B) and 1 had 19B (lineage A.3), identified early in the pandemic in Wuhan, China. Of the 39 (7%) genomes from 2021, the majority (82%) clustered into clade Delta 21J that originated in India. Only 2 (5%) of the genomes from 2021 had Alpha variant of concern (21I) from the lineage B1.1.7, which were suspected to be more transmissible. Of the 427 (73%) genomes from 2022, 393 (92%) had variants within Omicron variant of concern (21L), with 79 different lineages; 1 was Omicron variant 21K from the lineage BA1.1. Other clades observed in the 2022 batch were 19A (6%), 20A (0.2%), 20B (0.2%), 20C (0.2%) and 21M (1%). Conclusion Our genomic surveillance data suggest that SARS-CoV-2 infections at the local level mirrored global outbreaks. This underscores the importance of robust genomic surveillance efforts to inform public health planning and practice. Disclosures Marcus Zervos, MD, Contrafect: Advisor/Consultant|GSK: Grant/Research Support|Johnson and Johnson: Grant/Research Support|Pfizer: Grant/Research Support