The genomic evolutionary dynamics and global circulation patterns of respiratory syncytial virus.

Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infection in young children and the second leading cause of infant death worldwide. While global circulation has been extensively studied for respiratory viruses such as seasonal influenza, and more recently also in great detail for SARS-CoV-2, a lack of global multi-annual sampling of complete RSV genomes limits our understanding of RSV molecular epidemiology. Here, we capitalise on the genomic surveillance by the INFORM-RSV study and apply phylodynamic approaches to uncover how selection and neutral epidemiological processes shape RSV diversity. Using complete viral genome sequences, we show similar patterns of site-specific diversifying selection among RSVA and RSVB and recover the imprint of non-neutral epidemic processes on their genealogies. Using a phylogeographic approach, we provide evidence for air travel governing the global patterns of RSVA and RSVB spread, which results in a considerable degree of phylogenetic mixing across countries. Our findings highlight the potential of systematic global RSV genomic surveillance for transforming our understanding of global RSV spread.

Genomic wide association study and selective sweep analysis identify genes associated with improved yield under drought in Turkish winter wheat germplasm.

A panel comprising of 84 Turkish winter wheat landraces (LR) and 73 modern varieties (MV) was analyzed with genome wide association study (GWAS) to identify genes/genomic regions associated with increased yield under favorable and drought conditions. In addition, selective sweep analysis was conducted to detect signatures of selection in the winter wheat genome driving the differentiation between LR and MV, to gather an understanding of genomic regions linked to adaptation and yield improvement. The panel was genotyped with 25 K wheat SNP array and phenotyped for agronomic traits for two growing seasons (2018 and 2019) in Konya, Turkey. Year 2018 was treated as drought environment due to very low precipitation prior to heading whereas year 2019 was considered as a favorable season. GWAS conducted with SNPs and haplotype blocks using mixed linear model identified 18 genomic regions in the vicinities of known genes i.e., TaERF3-3A, TaERF3-3B, DEP1-5A, FRIZZY PANICLE-2D, TaSnRK23-1A, TaAGL6-A, TaARF12-2A, TaARF12-2B, WAPO1, TaSPL16-7D, TaTGW6-A1, KAT-2B, TaOGT1, TaSPL21-6B, TaSBEIb, trs1/WFZP-A, TaCwi-A1-2A and TaPIN1-7A associated with grain yield (GY) and yield related traits. Haplotype-based GWAS identified five haplotype blocks (H1A-42, H2A-71, H4A-48, H7B-123 and H7B-124), with the favorable haplotypes showing a yield increase of > 700 kg/ha in the drought season. SNP-based GWAS, detected only one larger effect genomic region on chromosome 7B, in common with haplotype-based GWAS. On an average, the percentage variation (PV) explained by haplotypes was 8.0% higher than PV explained by SNPs for all the investigated traits. Selective sweep analysis detected 39 signatures of selection between LR and MV of which 15 were within proximity of known functional genes controlling flowering (PRR-A1, PPR-D1, TaHd1-6B), GY and GY components (TaSus2-2B, TaGS2-B1, AG1-1A/WAG1-1A, DUO-A1, DUO-B1, AG2-3A/WAG2-3A, TaLAX1, TaSnRK210-4A, FBP, TaLAX1, TaPIL1 and AP3-1-7A/WPA3-7A) and 10 regions underlying various transcription factors and regulatory genes. The study outcomes contribute to utilization of LR in breeding winter wheat.

Clinical manifestations, antimicrobial resistance and genomic feature analysis of multidrug-resistant Elizabethkingia strains.

BACKGROUND: Elizabethkingia is emerging as an opportunistic pathogen in humans. The aim of this study was to investigate the clinical epidemiology, antimicrobial susceptibility, virulence factors, and genome features of Elizabethkingia spp. METHODS: Clinical data from 71 patients who were diagnosed with Elizabethkingia-induced pneumonia and bacteremia between August 2019 and September 2021 were analyzed. Whole-genome sequencing was performed on seven isolates, and the results were compared with a dataset of 83 available Elizabethkingia genomes. Genomic features, Kyoto Encyclopedia of Genes and Genomes (KEGG) results and clusters of orthologous groups (COGs) were analyzed. RESULTS: The mean age of the patients was 56.9 ± 20.7 years, and the in-hospital mortality rate was 29.6% (21/71). Elizabethkingia strains were obtained mainly from intensive care units (36.6%, 26/71) and emergency departments (32.4%, 23/71). The majority of the strains were isolated from respiratory tract specimens (85.9%, 61/71). All patients had a history of broad-spectrum antimicrobial exposure. Hospitalization for invasive mechanical ventilation or catheter insertion was found to be a risk factor for infection. The isolates displayed a high rate of resistance to cephalosporins and carbapenems, but all were susceptible to minocycline and colistin. Genomic analysis identified five ß-lactamase genes (blaGOB, blaBlaB, blaCME, blaOXA, and blaTEM) responsible for ß-lactam resistance and virulence genes involved in stress adaptation (ureB/G, katA/B, and clpP), adherence (groEL, tufA, and htpB) and immune modulation (gmd, tviB, cps4J, wbtIL, cap8E/D/G, and rfbC). Functional analysis of the COGs revealed that "metabolism" constituted the largest category within the core genome, while "information storage and processing" was predominant in both the accessory and unique genomes. The unique genes in our 7 strains were mostly enriched in KEGG pathways related to microRNAs in cancer, drug resistance (ß-lactam and vancomycin), ABC transporters, biological metabolism and biosynthesis, and nucleotide excision repair mechanisms. CONCLUSION: The Elizabethkingia genus exhibits multidrug resistance and carries carbapenemase genes. This study presents a comparative genomic analysis of Elizabethkingia, providing knowledge that facilitates a better understanding of this microorganism.

An integrated toolkit for human microglia functional genomics.

BACKGROUND: Microglia, the brain's resident immune cells, play vital roles in brain development, and disorders like Alzheimer's disease (AD). Human iPSC-derived microglia (iMG) provide a promising model to study these processes. However, existing iMG generation protocols face challenges, such as prolonged differentiation time, lack of detailed characterization, and limited gene function investigation via CRISPR-Cas9. METHODS: Our integrated toolkit for in-vitro microglia functional genomics optimizes iPSC differentiation into iMG through a streamlined two-step, 20-day process, producing iMG with a normal karyotype. We confirmed the iMG's authenticity and quality through single-cell RNA sequencing, chromatin accessibility profiles (ATAC-Seq), proteomics and functional tests. The toolkit also incorporates a drug-dependent CRISPR-ON/OFF system for temporally controlled gene expression. Further, we facilitate the use of multi-omic data by providing online searchable platform that compares new iMG profiles to human primary microglia: https://sherlab.shinyapps.io/IPSC-derived-Microglia/ . RESULTS: Our method generates iMG that closely align with human primary microglia in terms of transcriptomic, proteomic, and chromatin accessibility profiles. Functionally, these iMG exhibit Ca2 + transients, cytokine driven migration, immune responses to inflammatory signals, and active phagocytosis of CNS related substrates including synaptosomes, amyloid beta and myelin. Significantly, the toolkit facilitates repeated iMG harvesting, essential for large-scale experiments like CRISPR-Cas9 screens. The standalone ATAC-Seq profiles of our iMG closely resemble primary microglia, positioning them as ideal tools to study AD-associated single nucleotide variants (SNV) especially in the genome regulatory regions. CONCLUSIONS: Our advanced two-step protocol rapidly and efficiently produces authentic iMG. With features like the CRISPR-ON/OFF system and a comprehensive multi-omic data platform, our toolkit equips researchers for robust microglial functional genomic studies. By facilitating detailed SNV investigation and offering a sustainable cell harvest mechanism, the toolkit heralds significant progress in neurodegenerative disease drug research and therapeutic advancement.

Whole-genome assembly of a novel invertebrate herpesvirus from the gastropod Babylonia areolata.

Molluscan herpesviruses cause disease in species of major importance to aquaculture and are the only known herpesviruses to infect invertebrates, which lack an adaptive immune system. Understanding the evolution of malacoherpesviruses in relation to their hosts will likely require comparative genomic studies on multiple phylogenetic scales. Currently, only two malacoherpesvirus species have genomes that have been fully assembled, which limits the ability to perform comparative genomic studies on this family of viruses. In the present study, we fully assemble a herpesvirus from Illumina and Nanopore sequence data that were previously used to assemble the genome of the gastropod Babylonia areolata. We tentatively assign this novel herpesvirus to the genus Aurivirus within the family Malacoherpesviridae based on a phylogenetic analysis of DNA polymerase. While structurally similar to other malacoherpesvirus genomes, a synteny analysis of the novel herpesvirus with another Aurivirus species indicates that genomic rearrangements might be an important process in the evolution of this genus. We anticipate that future complete assemblies of malacoherpesviruses will be a valuable resource in comparative herpesvirus research.

Genetic Diversity Assessment in Plants from Reduced Representation Sequencing Data.

Genetic diversity refers to the variety of genetic traits within a population or a species. It is an essential aspect of both plant ecology and plant breeding because it contributes to the adaptability, survival, and resilience of populations in changing environments. This chapter outlines a pipeline for estimating genetic diversity statistics from reduced representation or whole genome sequencing data. The pipeline involves obtaining DNA sequence reads, mapping the corresponding reads to a reference genome, calling variants from the alignments, and generating an unbiased estimation of nucleotide diversity and divergence between populations. The pipeline is suitable for single-end Illumina reads and can be adjusted for paired-end reads. The resulting pipeline provides a comprehensive approach for aligning and analyzing sequencing data to estimate genetic diversity.

pyPGCF: A Python Software for Phylogenomic Analysis, Species Demarcation, Identification of Core, and Fingerprint Proteins of Bacterial Genomes That Are Important for Plants.

This computational protocol describes how to use pyPGCF, a python software package that runs in the linux environment, in order to analyze bacterial genomes and perform: (i) phylogenomic analysis, (ii) species demarcation, (iii) identification of the core proteins of a bacterial genus and its individual species, (iv) identification of species-specific fingerprint proteins that are found in all strains of a species and, at the same time, are absent from all other species of the genus, (v) functional annotation of the core and fingerprint proteins with eggNOG, and (vi) identification of secondary metabolite biosynthetic gene clusters (smBGCs) with antiSMASH. This software has already been implemented to analyze bacterial genera and species that are important for plants (e.g., Pseudomonas, Bacillus, Streptomyces). In addition, we provide a test dataset and example commands showing how to analyze 165 genomes from 55 species of the genus Bacillus. The main advantages of pyPGCF are that: (i) it uses adjustable orthology cut-offs, (ii) it identifies species-specific fingerprints, and (iii) its computational cost scales linearly with the number of genomes being analyzed. Therefore, pyPGCF is able to deal with a very large number of bacterial genomes, in reasonable timescales, using widely available levels of computing power.

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.

Subgenome-aware analyses reveal the genomic consequences of ancient allopolyploid hybridizations throughout the cotton family.

Malvaceae comprise some 4,225 species in 243 genera and nine subfamilies and include economically important species, such as cacao, cotton, durian, and jute, with cotton an important model system for studying the domestication of polyploids. Here, we use chromosome-level genome assemblies from representatives of five or six subfamilies (depending on the placement of Ochroma) to differentiate coexisting subgenomes and their evolution during the family's deep history. The results reveal that the allohexaploid Helicteroideae partially derive from an allotetraploid Sterculioideae and also form a component of the allodecaploid Bombacoideae and Malvoideae. The ancestral Malvaceae karyotype consists of 11 protochromosomes. Four subfamilies share a unique reciprocal chromosome translocation, and two other subfamilies share a chromosome fusion. DNA alignments of single-copy nuclear genes do not yield the same relationships as inferred from chromosome structural traits, probably because of genes originating from different ancestral subgenomes. These results illustrate how chromosome-structural data can unravel the evolutionary history of groups with ancient hybrid genomes.

The Diaspora Human Genomics Institute Launches the Together for Change Initiative: A Transformative, Historic Partnership to Ensure Health Equity in a Time of Unprecedented Technological Advancements.

Human subjects research and drug and device development currently base their findings largely on the genetic data of the non-Hispanic White population, excluding People of Color. This practice puts People of Color at a distinct and potentially deadly disadvantage in being treated for sickness, disability, and disease, as seen during the COVID-19 pandemic. Major disparities exist in all chronic health conditions, including cancer. Data show that less than 2% of genetic information being studied today originates from people of African ancestry. If genomic datasets do not adequately represent People of Color, new drugs and genetic therapies may not work as well as for people of European descent. Addressing the urgent concern that historically marginalized people may again be excluded from the next technological leap affecting human health and the benefits it will bring will requires a paradigm shift. Thus, on behalf of underserved and marginalized people, we developed the Together for CHANGE (T4C) initiative as a unique collaborative public-private partnership to address the concern. The comprehensive programs designed in the T4C initiative, governed by the Diaspora Human Genomics Institute founded by Meharry Medical College, will transform the landscape of education and health care and positively affect global Black communities for decades to come.

[Chinese expert consensus on the analytical validation of tumor comprehensive genomic profiling next generation sequencing testing (2024 edition)].

In hospital laboratories-developed testing is of great significance for the clinical testing products that has not been approved by the National Medical Product Administration and is urgently needed to meet clinical practice needs. With the development of cancer precision medicine in recent years, comprehensive genomic profiling (CGP) has become an important means and method for the detection of drug targets, precise molecular typing, and immunotherapy biomarkers in cancer patients. However, there is still a lack of unified understanding and consensus on clinical testing standards and application specifications for laboratory-developed testing in the hospitals. The Molecular Pathology Collaboration Group of the Cancer Experts Committee of the Chinese Anti-Cancer Association and the Molecular Pathology Group of the Pathology Branch of the Chinese Medical Association initiated the expert consensus on relevant specifications for analytical validation of CGP next-generation sequencing (NGS) testing in Chinese hospitals. Combined with domestic clinical practice, refer to domestic and foreign literatures, from the background of the laboratory-developed testing, analytical validation scenarios, evaluation indicators and variation ranges, sample types and quantities covered by analytical validation, clinical performance and drug efficacy determination, and site personnel for analytical validation, quality control, inter-laboratory quality evaluation and document management, etc. After the discussion by the expert group, 12 expert consensuses were formed to provide reference for the analytical validation and clinical application of tumor CGP NGS testing in Chinese hospitals, so as to promote the laboratory-developed testing applications in Chinese hospitals.

[Current status and prospects of genetic research on IgA nephropathy].

IgA nephropathy is the most common primary glomerulonephritis worldwide, and genetic factors may play an important role in its pathogenesis. Following candidate gene association analysis and genome-wide linkage study, genome-wide association studies (GWAS) have found multiple susceptibility genes related to the pathogenesis and clinical phenotype of IgA nephropathy. Meanwhile, structural variation and epigenetic changes are also closely related to IgA nephropathy. Genetic variants have been found to explain about 11% of its heritability. In the current era of genomic medicine, how to find more susceptible genes/loci, whole genome sequencing studies (WGS) provide clues to further understand the genetic variation of IgA nephropathy. How to find the cell type-specific susceptibility genes associated with IgA nephropathy, multi-omics studies will conduct comprehensive analysis via single-cell sequencing, expression quantitative trait locus (eQTL) and genomics to find the pathogenic genes and offer insights into the development of targeted drugs, which will be the trend and direction of future research.

[Analysis and precise intervention on pathogenic genes and mechanisms of lupus nephritis].

Lupus nephritis is the most common complication of systemic lupus erythematosus (SLE) and an important cause of end-stage kidney disease and death in patients with SLE. The pathogenesis of SLE is complex, with no effective treatment and poor long-term prognosis. The development of genomic medicine provides a new way to explore the disease-causing genes and pathogenesis of lupus nephritis. Here, the article introduces how to uncover the pathogenesis of lupus nephritis from the genome level and explore new strategies for diagnosis and treatment on this disease.

[Current Status and Issues of Companion Diagnostics in Cancer Genomic Medicine].

As of December 2023, there are 5 types of cancer gene panel tests covered by public insurance in Japan. Four of them partly feature companion diagnostics. When cancer gene panel test is used for the purpose of comprehensive gene profiling (CGP), a total of 56,000 points(44,000 points for the test administration fee and 12,000 points for the expert panel fee) can be claimed, whereas if the cancer gene panel test is used for the purpose of companion diagnostics, hospitals can claim only the reimbursement as a companion diagnostics, which fee is much cheaper than that of CGP. Therefore, cancer gene panel tests are rarely used as a companion diagnosis in daily clinical practice. Even when the test is performed as a CGP test, since its indication is limited to patients who have completed or are expected to complete standard chemotherapy, most biomarkers associated with approved drugs are already evaluated with stand-alone companion diagnostics at the time of CGP test application. On the other hand, there are some approved drugs, such as pembrolizumab for TMB-H or entrectinib or larotrectinib for NTRK fusion gene, for which there is no stand-alone companion diagnostics and the eligibility for these drugs cannot be judged without the results of CGP test. This paper discusses the current status and issues of companion diagnostics in cancer genomic medicine.

Genomic characterization of human respiratory syncytial virus circulating in Islamabad, Pakistan, during an outbreak in 2022-2023.

In this study, conducted at the National Institute of Health, Islamabad, during an outbreak of human respiratory syncytial virus (hRSV) from December 2022 to January 2023, the first whole-genome sequences of hRSV isolates from Islamabad, Pakistan, were determined. Out of 10 positive samples, five were sequenced, revealing the presence of two genotypes: RSV-A (GA2.3.5, ON1 strain) and RSV-B (GB5.0.5.a, BA-10 strain). A rare non-synonymous substitution (E232G) in G the protein and N276S in the F protein were found in RSV-A. In RSV-B, the unique mutations K191R, Q209R, and I206M were found in the F protein. These mutations could potentially influence vaccine efficacy and viral pathogenicity. This research underscores the importance of genomic surveillance for understanding RSV diversity and guiding public health responses in Pakistan.

Toward Equitable Precision Oncology: Monitoring Racial and Ethnic Inclusion in Genomics and Clinical Trials.

PURPOSE: Ethnic diversity in cancer research is crucial as race/ethnicity influences cancer incidence, survival, drug response, molecular pathways, and epigenetic phenomena. In 2018, we began a project to examine racial/ethnic diversity in cancer research, with a commitment to review these disparities every 4 years. This report is our second assessment, detailing the present state of racial/ethnic diversity in cancer genomics and clinical trials. METHODS: To study racial/ethnic inclusion in cancer genomics, we extracted ethnic records from all data sets available at cBioPortal (n = 125,128 patients) and cancer-related genome-wide association studies (n = 28,011,282 patients) between 2018 and 2022. Concerning clinical trials, we selected studies related to breast cancer (n = 125,518 patients, 181 studies), lung cancer (n = 34,329 patients, 119 studies), and colorectal cancer (n = 40,808 patients, 105 studies). RESULTS: In cancer genomics (N = 28,136,410), 3% of individuals lack racial/ethnic registries; tumor samples were collected predominantly from White patients (89.14%), followed by Asian (7%), African American (0.55%), and Hispanic (0.21%) patients and other populations (0.1%). In clinical trials (N = 200,655), data on race/ethnicity are missing for 60.14% of the participants; for individuals whose race/ethnicity was recorded, most were characterized as White (28.33%), followed by Asian (7.64%), African (1.79), other ethnicities (1.37), and Hispanic (0.73). Racial/ethnic representation significantly deviates from global ethnic proportions (P ≤ .001) across all data sets, with White patients outnumbering other ethnic groups by a factor of approximately 4-6. CONCLUSION: Our second update on racial/ethnic representation in cancer research highlights the persistent overrepresentation of White populations in cancer genomics and a notable absence of racial/ethnic information across clinical trials. To ensure more equitable and effective precision oncology, future efforts should address the reasons behind the insufficient representation of ethnically diverse populations in cancer research.

Phylogenomics of Psammodynastes and Buhoma (Elapoidea: Serpentes), with the description of a new Asian snake family.

Asian mock vipers of the genus Psammodynastes and African forest snakes of the genus Buhoma are two genera belonging to the snake superfamily Elapoidea. The phylogenetic placements of Psammodynastes and Buhoma within Elapoidea has been extremely unstable which has resulted in their uncertain and debated taxonomy. We used ultraconserved elements and traditional nuclear and mitochondrial markers to infer the phylogenetic relationships of these two genera with other elapoids. Psammodynastes, for which a reference genome has been sequenced, were found, with strong branch support, to be a relatively early diverging split within Elapoidea that is sister to a clade consisting of Elapidae, Micrelapidae and Lamprophiidae. Hence, we allocate Psammodynastes to its own family, Psammodynastidae new family. However, the phylogenetic position of Buhoma could not be resolved with a high degree of confidence. Attempts to identify the possible sources of conflict in the rapid radiation of elapoid snakes suggest that both hybridisation/introgression during the rapid diversification, including possible ghost introgression, as well as incomplete lineage sorting likely have had a confounding role. The usual practice of combining mitochondrial loci with nuclear genomic data appears to mislead phylogeny reconstructions in rapid radiation scenarios, especially in the absence of genome scale data.

Genomic characterization and probiotic potential assessment of an exopolysaccharide-producing strain Pediococcus pentosaceus LL-07 isolated from fermented meat.

BACKGROUND: The genomic information available for Pediococcus pentosaceus is primarily derived from fermented fruits and vegetables, with less information available from fermented meat. P. pentosaceus LL-07, a strain isolated from fermented meat, has the capability of producing exopolysaccharides (EPS). To assess the probiotic attributes of P. pentosaceus LL-07, we conducted whole-genome sequencing (WGS) using the PacBio SequelIIe and Illumina MiSeq platforms, followed by in vitro experiments to explore its probiotic potential. RESULTS: The genome size of P. pentosaceus LL-07 is 1,782,685 bp, comprising a circular chromosome and a circular plasmid. Our investigation revealed the absence of a CRISPR/Cas system. Sugar fermentation experiments demonstrated the characteristics of carbohydrate metabolism. P. pentosaceus LL-07 contains an EPS synthesis gene cluster consisting of 13 genes, which is different from the currently known gene cluster structure. NO genes associated with hemolysis or toxin synthesis were detected. Additionally, eighty-six genes related to antibiotic resistance were identified but not present in the prophage, transposon or plasmid. In vitro experiments demonstrated that P. pentosaceus LL-07 was comparable to the reference strain P. pentosaceus ATCC25745 in terms of tolerance to artificial digestive juice and bile, autoaggregation and antioxidation, and provided corresponding genomic evidence. CONCLUSION: This study confirmed the safety and probiotic properties of P. pentosaceus LL-07 via complete genome and phenotype analysis, supporting its characterization as a potential probiotic candidate.

OrthoRefine: automated enhancement of prior ortholog identification via synteny.

BACKGROUND: Identifying orthologs continues to be an early and imperative step in genome analysis but remains a challenging problem. While synteny (conservation of gene order) has previously been used independently and in combination with other methods to identify orthologs, applying synteny in ortholog identification has yet to be automated in a user-friendly manner. This desire for automation and ease-of-use led us to develop OrthoRefine, a standalone program that uses synteny to refine ortholog identification. RESULTS: We developed OrthoRefine to improve the detection of orthologous genes by implementing a look-around window approach to detect synteny. We tested OrthoRefine in tandem with OrthoFinder, one of the most used software for identification of orthologs in recent years. We evaluated improvements provided by OrthoRefine in several bacterial and a eukaryotic dataset. OrthoRefine efficiently eliminates paralogs from orthologous groups detected by OrthoFinder. Using synteny increased specificity and functional ortholog identification; additionally, analysis of BLAST e-value, phylogenetics, and operon occurrence further supported using synteny for ortholog identification. A comparison of several window sizes suggested that smaller window sizes (eight genes) were generally the most suitable for identifying orthologs via synteny. However, larger windows (30 genes) performed better in datasets containing less closely related genomes. A typical run of OrthoRefine with ~ 10 bacterial genomes can be completed in a few minutes on a regular desktop PC. CONCLUSION: OrthoRefine is a simple-to-use, standalone tool that automates the application of synteny to improve ortholog detection. OrthoRefine is particularly efficient in eliminating paralogs from orthologous groups delineated by standard methods.

Genome composition and GC content influence loci distribution in reduced representation genomic studies.

BACKGROUND: Genomic architecture is a key evolutionary trait for living organisms. Due to multiple complex adaptive and neutral forces which impose evolutionary pressures on genomes, there is a huge variability of genomic features. However, their variability and the extent to which genomic content determines the distribution of recovered loci in reduced representation sequencing studies is largely unexplored. RESULTS: Here, by using 80 genome assemblies, we observed that whereas plants primarily increase their genome size by expanding their intergenic regions, animals expand both intergenic and intronic regions, although the expansion patterns differ between deuterostomes and protostomes. Loci mapping in introns, exons, and intergenic categories obtained by in silico digestion using 2b-enzymes are positively correlated with the percentage of these regions in the corresponding genomes, suggesting that loci distribution mostly mirrors genomic architecture of the selected taxon. However, exonic regions showed a significant enrichment of loci in all groups regardless of the used enzyme. Moreover, when using selective adaptors to obtain a secondarily reduced loci dataset, the percentage and distribution of retained loci also varied. Adaptors with G/C terminals recovered a lower percentage of selected loci, with a further enrichment of exonic regions, while adaptors with A/T terminals retained a higher percentage of loci and slightly selected more intronic regions than expected. CONCLUSIONS: Our results highlight how genome composition, genome GC content, RAD enzyme choice and use of base-selective adaptors influence reduced genome representation techniques. This is important to acknowledge in population and conservation genomic studies, as it determines the abundance and distribution of loci.