Genome Resequencing for Autotetraploid Rice and Its Closest Relatives Reveals Abundant Variation and High Potential in Rice Breeding.

Polyploid rice and its reverted diploid show rich phenotypic variation and strong heterosis, showing great breeding value. However, the genomic differences among tetraploids, counterpart common diploids, tetraploid-revertant diploids, and hybrid descendants are unclear. In this work, we bred a new excellent two-line hybrid rice variety, Y Liang You Duo Hui 14 (HTRM12), using Haitian tetraploid self-reverted diploid (HTRM2). Furthermore, we comparatively analyzed the important agronomic traits and genome-wide variations of those closest relatives, Haitian diploid (HT2), Haitian tetraploid (HT4), HTRM2, and HTRM12 in detail, based on multiple phenotypic investigations, genome resequencing, and bioinformatics analysis. The results of agronomic traits analysis and genome-wide variation analysis of single nucleotide polymorphism (SNP), insertion-deletion (InDel), and copy number variation (CNV) show that HT4 and HTRM2 had abundant phenotypic and genomic variations compared to HT2. HTRM2 can inherit important traits and variations from HT4. This implies that tetraploid self-reverted diploid has high potential in creating excellent breeding materials and in breeding breakthrough hybrid rice varieties. Our study verifies the feasibility that polyploid rice could be used as a mutation carrier for creating variations and provides genomic information, new breeding materials, and a new way of application for tetraploid rice breeding.

Evolution and strain diversity advance exploration of Candida albicans biology.

Fungi were some of the earliest organismal systems used to explore mutational processes and its phenotypic consequences on members of a species. Yeasts that cause significant human disease were quickly incorporated into these investigations to define the genetic and phenotypic drivers of virulence. Among Candida species, Candida albicans has emerged as a model for studying genomic processes of evolution because of its clinical relevance, relatively small genome, and ability to tolerate complex chromosomal changes. Here, we describe major recent findings that used evolution of strains from defined genetic backgrounds to delineate mutational and adaptative processes and include how nascent exploration into naturally occurring variation is contributing to these conceptual frameworks. Ultimately, efforts to discern adaptive mechanisms used by C. albicans will continue to divulge new biology and can better inform treatment regimens for the increasing prevalence of fungal disease.

Technological Development and Advances for Constructing and Analyzing Plant Pangenomes.

A pangenome captures the genomic diversity for a species, derived from a collection of genetic sequences of diverse populations. Advances in sequencing technologies have given rise to three primary methods for pangenome construction and analysis: de novo assembly and comparison, reference genome-based iterative assembly, and graph-based pangenome construction. Each method presents advantages and challenges in processing varying amounts and structures of DNA sequencing data. With the emergence of high-quality genome assemblies and advanced bioinformatic tools, the graph-based pangenome is emerging as an advanced reference for exploring the biological and functional implications of genetic variations.

Mitochondrial genome variation and intergenomic sequence transfers in Hevea species.

Among the Hevea species, rubber tree (Hevea brasiliensis) is the most important source of natural rubber. In previous studies, we sequenced the complete nuclear and chloroplast genomes of Hevea species, providing an invaluable resource for studying their phylogeny, disease resistance, and breeding. However, given that plant mitochondrial genomes are more complex and more difficult to assemble than that of the other organelles, little is known about their mitochondrial genome, which limits the comprehensive understanding of Hevea genomic evolution. In this study, we sequenced and assembled the mitochondrial genomes of four Hevea species. The four mitochondrial genomes had consistent GC contents, codon usages and AT skews. However, there were significant differences in the genome lengths and sequence repeats. Specifically, the circular mitochondrial genomes of the four Hevea species ranged from 935,732 to 1,402,206 bp, with 34-35 unique protein-coding genes, 35-38 tRNA genes, and 6-13 rRNA genes. In addition, there were 17,294-46,552 bp intergenomic transfer fragments between the chloroplast and mitochondrial genomes, consisting of eight intact genes (psaA, rrn16S, tRNA-Val, rrn5S, rrn4.5S, tRNA-Arg, tRNA-Asp, and tRNA-Asn), intergenic spacer regions and partial gene sequences. The evolutionary position of Hevea species, crucial for understanding its adaptive strategies and relation to other species, was verified by phylogenetic analysis based on the protein-coding genes in the mitochondrial genomes of 21 Malpighiales species. The findings from this study not only provide valuable insights into the structure and evolution of the Hevea mitochondrial genome but also lay the foundation for further molecular, evolutionary studies, and genomic breeding studies on rubber tree and other Hevea species, thereby potentially informing conservation and utilization strategies.

Advancing human genotyping: The Infinium HTS iSelect Custom microarray panel (Rita) development study.

Single Nucleotide Polymorphisms (SNPs), as the most prevalent type of variation in the human genome, play a pivotal role in influencing human traits. They are extensively utilized in diverse fields such as population genetics, forensic science, and genetic medicine. This study focuses on the 'Rita' BeadChip, a custom SNP microarray panel developed using Illumina Infinium HTS technology. Designed for high-throughput genotyping, the panel facilitates the analysis of over 4000 markers efficiently and cost-effectively. After careful clustering performed on a set of 1000 samples, an evaluation of the Rita panel was undertaken, assessing its sensitivity, repeatability, reproducibility, precision, accuracy, and resistance to contamination. The panel's performance was evaluated in various scenarios, including sex estimation and parental relationship assessment, using GenomeStudio data analysis software. Findings show that over 95 % of the custom BeadChip assay markers were successful, with better performance of transitions over other mutations, and a considerably lower success rate for Y chromosome loci. An exceptional call rate exceeding 99 % was demonstrated for control samples, even with DNA input as low as 0.781 ng. Call rates above 80 % were still obtained with DNA quantities under 0.1 ng, indicating high sensitivity and suitability for forensic applications where DNA quantity is often limited. Repeatability, reproducibility, and precision studies revealed consistency of the panel's performance across different batches and operators, with no significant deviations in call rates or genotyping results. Accuracy assessments, involving comparison with multiple available genetic databases, including the 1000 Genome Project and HapMap, denoted over 99 % concordance, establishing the Rita panel's reliability in genotyping. The contamination study revealed insights into background noise and allowed the definition of thresholds for sample quality evaluation. Multiple metrics for differentiating between negative controls and true samples were highlighted, increasing the reliability of the obtained results. The sex estimation tool in GenomeStudio proved highly effective, correctly assigning sex in all samples with autosomal loci call rates above 97 %. The parental relationship assessment of family trios highlighted the utility of GenomeStudio in identifying genotyping errors or potential Mendelian inconsistencies, promoting the application of arrays such as Rita in kinship testing. Overall, this evaluation confirms the Rita microarray as a robust, high-throughput genotyping tool, underscoring its potential in genetic research and forensic applications. With its custom content and adaptable design, it not only meets current genotyping demands but also opens avenues for further research and application expansion in the field of genetic analysis.

MVAR: A Mouse Variation Registry.

The Mouse Variation Registry (MVAR) resource is a scalable registry of mouse single nucleotide variants and small indels and variant annotation. The resource accepts data in standard Variant Call Format (VCF) and assesses the uniqueness of the submitted variants via a canonicalization process. Novel variants are assigned a unique, persistent MVAR identifier; variants that are equivalent to an existing variant in the resource are associated with the existing identifier. Annotations for variant type, molecular consequence, impact, and genomic region in the context of specific transcripts and protein sequences are generated using Ensembl's Variant Effect Predictor (VEP) and Jannovar. Access to the data and annotations in MVAR are supported via an Application Programming Interface (API) and web application. Researchers can search the resource by gene symbol, genomic region, variant (expressed in Human Genome Variation Society syntax), refSNP identifiers, or MVAR identifiers. Tabular search results can be filtered by variant annotations (variant type, molecular consequence, impact, variant region) and viewed according to variant distribution across mouse strains. The registry currently comprises more than 99 million canonical single nucleotide variants for 581 strains of mice. MVAR is accessible from https://mvar.jax.org.

Subtelomeres: hotspots of genome variation.

Eukaryotic cells contain multiple types of duplicated sequences. Typical examples are tandem repeat sequences including telomeres, centromeres, rDNA genes and transposable elements. Most of these sequences are unstable; thus, their copy numbers or sequences change rapidly in the course of evolution. In this review, I will describe roles of subtelomere regions, which are located adjacent to telomeres at chromosome ends, and recent discoveries about their sequence variation.

Plant genome resequencing and population genomics: Current status and future prospects.

Advances in DNA sequencing technology have sparked a genomics revolution, driving breakthroughs in plant genetics and crop breeding. Recently, the focus has shifted from cataloging genetic diversity in plants to exploring their functional significance and delivering beneficial alleles for crop improvement. This transformation has been facilitated by the increasing adoption of whole-genome resequencing. In this review, we summarize the current progress of population-based genome resequencing studies and how these studies affect crop breeding. A total of 187 land plants from 163 countries have been resequenced, comprising 54 413 accessions. As part of resequencing efforts 367 traits have been surveyed and 86 genome-wide association studies have been conducted. Economically important crops, particularly cereals, vegetables, and legumes, have dominated the resequencing efforts, leaving a gap in 49 orders, including Lycopodiales, Liliales, Acorales, Austrobaileyales, and Commelinales. The resequenced germplasm is distributed across diverse geographic locations, providing a global perspective on plant genomics. We highlight genes that have been selected during domestication, or associated with agronomic traits, and form a repository of candidate genes for future research and application. Despite the opportunities for cross-species comparative genomics, many population genomic datasets are not accessible, impeding secondary analyses. We call for a more open and collaborative approach to population genomics that promotes data sharing and encourages contribution-based credit policy. The number of plant genome resequencing studies will continue to rise with the decreasing DNA sequencing costs, coupled with advances in analysis and computational technologies. This expansion, in terms of both scale and quality, holds promise for deeper insights into plant trait genetics and breeding design.

Identifying Genomic Signatures of Positive Selection to Predict Protective Genomic Loci in the Cohort of Lithuanian Clean-Up Workers of the Chornobyl Nuclear Disaster.

Some people resist or recover from health challenges better than others. We studied Lithuanian clean-up workers of the Chornobyl nuclear disaster (LCWC) who worked in the harshest conditions and, despite high ionising radiation doses as well as other factors, continue ageing relatively healthily. Thus, we hypothesised that there might be individual features encoded by the genome which act protectively for better adaptiveness and health that depend on unique positive selection signatures. Whole-genome sequencing was performed for 40 LCWC and a control group composed of 25 men from the general Lithuanian population (LTU). Selective sweep analysis was performed to identify genomic regions which may be under recent positive selection and determine better adaptiveness. Twenty-two autosomal loci with the highest positive selection signature values were identified. Most important, unique loci under positive selection have been identified in the genomes of the LCWC, which may influence the survival and adaptive qualities to extreme conditions, and the disaster itself. Characterising these loci provide a better understanding of the interaction between ongoing microevolutionary processes, multifactorial traits, and diseases. Studying unique groups of disease-resistant individuals could help create new insights for better, more individualised, disease diagnostics and prevention strategies.

Whole genome sequencing reveals population diversity and variation in HIV-1 specific host genes.

HIV infection continues to be a major global public health issue. The population heterogeneity in susceptibility or resistance to HIV-1 and progression upon infection is attributable to, among other factors, host genetic variation. Therefore, identifying population-specific variation and genetic modifiers of HIV infectivity can catapult the invention of effective strategies against HIV-1 in African populations. Here, we investigated whole genome sequences of 390 unrelated HIV-positive and -negative individuals from Botswana. We report 27.7 million single nucleotide variations (SNVs) in the complete genomes of Botswana nationals, of which 2.8 million were missing in public databases. Our population structure analysis revealed a largely homogenous structure in the Botswana population. Admixture analysis showed elevated components shared between the Botswana population and the Niger-Congo (65.9%), Khoe-San (32.9%), and Europeans (1.1%) ancestries in the population of Botswana. Statistical significance of the mutational burden of deleterious and loss-of-function variants per gene against a null model was estimated. The most deleterious variants were enriched in five genes: ACTRT2 (the Actin Related Protein T2), HOXD12 (homeobox D12), ABCB5 (ATP binding cassette subfamily B member 5), ATP8B4 (ATPase phospholipid transporting 8B4) and ABCC12 (ATP Binding Cassette Subfamily C Member 12). These genes are enriched in the glycolysis and gluconeogenesis (p < 2.84e-6) pathways and therefore, may contribute to the emerging field of immunometabolism in which therapy against HIV-1 infection is being evaluated. Published transcriptomic evidence supports the role of the glycolysis/gluconeogenesis pathways in the regulation of susceptibility to HIV, and that cumulative effects of genetic modifiers in glycolysis/gluconeogenesis pathways may potentially have effects on the expression and clinical variability of HIV-1. Identified genes and pathways provide novel avenues for other interventions, with the potential for informing the design of new therapeutics.

Multiple genome analysis of Candida glabrata clinical isolates renders new insights into genetic diversity and drug resistance determinants.

The emergence of drug resistance significantly hampers the treatment of human infections, including those caused by fungal pathogens such as Candida species. Candida glabrata ranks as the second most common cause of candidiasis worldwide, supported by rapid acquisition of resistance to azole and echinocandin antifungals frequently prompted by single nucleotide polymorphisms (SNPs) in resistance associated genes, such as PDR1 (azole resistance) or FKS1/2 (echinocandin resistance). To determine the frequency of polymorphisms and genome rearrangements as the possible genetic basis of C. glabrata drug resistance, we assessed genomic variation across 94 globally distributed isolates with distinct resistance phenotypes, whose sequence is deposited in GenBank. The genomes of three additional clinical isolates were sequenced, in this study, including two azole resistant strains that did not display Gain-Of-Function (GOF) mutations in the transcription factor encoding gene PDR1. Genomic variations in susceptible isolates were used to screen out variants arising from genome diversity and to identify variants exclusive to resistant isolates. More than half of the azole or echinocandin resistant isolates do not possess exclusive polymorphisms in PDR1 or FKS1/2, respectively, providing evidence of alternative genetic basis of antifungal resistance. We also identified copy number variations consistently affecting a subset of chromosomes. Overall, our analysis of the genomic and phenotypic variation across isolates allowed to pinpoint, in a genome-wide scale, genetic changes enriched specifically in antifungal resistant strains, which provides a first step to identify additional determinants of antifungal resistance. Specifically, regarding the newly sequenced strains, a set of mutations/genes are proposed to underlie the observed unconventional azole resistance phenotype.

Influence of genomic structural variations and nutritional conditions on the emergence of quorum sensing-dependent gene regulation defects in Burkholderia glumae.

Bacteria often change their genetic and physiological traits to survive in harsh environments. To determine whether, in various strains of Burkholderia glumae, genomic diversity is associated with the ability to adapt to ever-changing environments, whole genomes of 44 isolates from different hosts and regions were analyzed. Whole-genome phylogenetic analysis of the 44 isolates revealed six clusters and two divisions. While all isolates possessed chromosomes 1 and 2, strains BGR80S and BGR81S had one chromosome resulting from the merging of the two chromosomes. Upon comparison of genomic structures to the prototype BGR1, inversions, deletions, and rearrangements were found within or between chromosomes 1 and/or 2 in the other isolates. When three isolates-BGR80S, BGR15S, and BGR21S, representing clusters III, IV, and VI, respectively-were grown in Luria-Bertani medium, spontaneous null mutations were identified in qsmR encoding a quorum-sensing master regulator. Six days after subculture, qsmR mutants were found at detectable frequencies in BGR15S and BGR21S, and reached approximately 40% at 8 days after subculture. However, the qsmR mutants appeared 2 days after subculture in BGR80S and dominated the population, reaching almost 80%. No qsmR mutant was detected at detectable frequency in BGR1 or BGR13S. The spontaneous qsmR mutants outcompeted their parental strains in the co-culture. Daily addition of glucose or casamino acids to the batch cultures of BGR80S delayed emergence of qsmR mutants and significantly reduced their incidence. These results indicate that spontaneous qsmR mutations are correlated with genomic structures and nutritional conditions.

Whole-genome sequencing revealed different demographic histories among the Korean endemic hill pigeon (Columba rupestris), rock pigeon (Columba livia var. domestica) and oriental turtle dove (Streptopelia orientalis).

BACKGROUND: The family Columbidae is known as the pigeon family and contains approximately 351 species and 50 genera. Compared to the wealth of biological and genomic information on these Columba livia var. domesteca, information on Columba rupestris and Streptopelia orientalis has been rather limited. The C. rupestris population size is decreasing in Korea. OBJECTIVES: Whole-genome sequencing and identification of population characterization of each species based genome variation on 9 Korean pigeon and dove samples, namely, six hill pigeon (C. rupestris), one rock pigeon (C. livia var. domestica) and two oriental turtle dove (S. orientalis) samples. RESULTS: The whole genome of 9 genotypes were sequenced and mapped to the C. livia reference genome. Sequence alignment showed over 96% identity in C. rupestris and 94% identity in S. orientalis to the reference genome (GenBank assembly accession: GCA_001887795.1). Sequence variations, including single nucleotide polymorphisms (SNPs), insertions and deletions (InDels), and structural variations, revealed that intergenus (Columba vs. Streptopelia) variations were approximately four times higher than intragenus variations (C. livia vs. C. rupestris). Of the two Columba species, C. livia var. domestica is closer to S. orientalis than C. rupestris. Pairwise sequentially Markovian coalescent (PSMC) demographic history analysis revealed that the three species underwent a common population bottleneck between 105 and 120 Kya; since then, the effective population sizes of the rock pigeon and oriental turtle dove have increased. CONCLUSION: The effective population size of the hill pigeon, an Endangered Species of Grade II in Korea, has increased slowly from the second severe bottleneck that occurred approximately 0.5-1.4 × 104 years ago. Our results showed no relationship between copy number variation in the Norrie disease protein (NDP) regulatory regions and plumage color patterns. We report the first comparative analysis of three pigeon genomes.

Guilt by association: EcDNA as a mobile transactivator in cancer.

Extrachromosomal DNA (ecDNA), first described in the 1960s, is emerging as a prevalent but poorly characterized oncogenic alteration in cancer. ecDNA is a reservoir for oncogene amplification and is associated with an aggressive tumor phenotype and poor patient outcome. Despite the long-held knowledge of its existence, little is known about how ecDNA affects tumor cell behavior. Recent data reveal that ecDNA hubs are mobile transcriptional enhancers which can transactivate gene expression through chromatin interactions. Given its prevalence, structural complexity, and unequal segregation into daughter cells, ecDNA can offer selective growth advantages, contribute to intratumor heterogeneity (ITH), and accelerate tumor evolution. Future technology development is expected to transform the current paradigm for studying ecDNA and lead to therapeutic strategies targeting ecDNA vulnerabilities.

The era of 3D and spatial genomics.

Over a decade ago the advent of high-throughput chromosome conformation capture (Hi-C) sparked a new era of 3D genomics. Since then the number of methods for mapping the 3D genome has flourished, enabling an ever-increasing understanding of how DNA is packaged in the nucleus and how the spatiotemporal organization of the genome orchestrates its vital functions. More recently, the next generation of spatial genomics technologies has begun to reveal how genome sequence and 3D genome organization vary between cells in their tissue context. We summarize how the toolkit for charting genome topology has evolved over the past decade and discuss how new technological developments are advancing the field of 3D and spatial genomics.

Predicting Physical Appearance from DNA Data-Towards Genomic Solutions.

The idea of forensic DNA intelligence is to extract from genomic data any information that can help guide the investigation. The clues to the externally visible phenotype are of particular practical importance. The high heritability of the physical phenotype suggests that genetic data can be easily predicted, but this has only become possible with less polygenic traits. The forensic community has developed DNA-based predictive tools by employing a limited number of the most important markers analysed with targeted massive parallel sequencing. The complexity of the genetics of many other appearance phenotypes requires big data coupled with sophisticated machine learning methods to develop accurate genomic predictors. A significant challenge in developing universal genomic predictive methods will be the collection of sufficiently large data sets. These should be created using whole-genome sequencing technology to enable the identification of rare DNA variants implicated in phenotype determination. It is worth noting that the correctness of the forensic sketch generated from the DNA data depends on the inclusion of an age factor. This, however, can be predicted by analysing epigenetic data. An important limitation preventing whole-genome approaches from being commonly used in forensics is the slow progress in the development and implementation of high-throughput, low DNA input sequencing technologies. The example of palaeoanthropology suggests that such methods may possibly be developed in forensics.

Variation in Plastome Sizes Accompanied by Evolutionary History in Monogenomic Triticeae (Poaceae: Triticeae).

To investigate the pattern of chloroplast genome variation in Triticeae, we comprehensively analyzed the indels in protein-coding genes and intergenic sequence, gene loss/pseudonization, intron variation, expansion/contraction in inverted repeat regions, and the relationship between sequence characteristics and chloroplast genome size in 34 monogenomic Triticeae plants. Ancestral genome reconstruction suggests that major length variations occurred in four-stem branches of monogenomic Triticeae followed by independent changes in each genus. It was shown that the chloroplast genome sizes of monogenomic Triticeae were highly variable. The chloroplast genome of Pseudoroegneria, Dasypyrum, Lophopyrum, Thinopyrum, Eremopyrum, Agropyron, Australopyrum, and Henradia in Triticeae had evolved toward size reduction largely because of pseudogenes elimination events and length deletion fragments in intergenic. The Aegilops/Triticum complex, Taeniatherum, Secale, Crithopsis, Herteranthelium, and Hordeum in Triticeae had a larger chloroplast genome size. The large size variation in major lineages and their subclades are most likely consequences of adaptive processes since these variations were significantly correlated with divergence time and historical climatic changes. We also found that several intergenic regions, such as petN-trnC and psbE-petL containing unique genetic information, which can be used as important tools to identify the maternal relationship among Triticeae species. Our results contribute to the novel knowledge of plastid genome evolution in Triticeae.

An epistasis and heterogeneity analysis method based on maximum correlation and maximum consistence criteria.

Tumor heterogeneity significantly increases the difficulty of tumor treatment. The same drugs and treatment methods have different effects on different tumor subtypes. Therefore, tumor heterogeneity is one of the main sources of poor prognosis, recurrence and metastasis. At present, there have been some computational methods to study tumor heterogeneity from the level of genome, transcriptome, and histology, but these methods still have certain limitations. In this study, we proposed an epistasis and heterogeneity analysis method based on genomic single nucleotide polymorphism (SNP) data. First of all, a maximum correlation and maximum consistence criteria was designed based on Bayesian network score K2 and information entropy for evaluating genomic epistasis. As the number of SNPs increases, the epistasis combination space increases sharply, resulting in a combination explosion phenomenon. Therefore, we next use an improved genetic algorithm to search the SNP epistatic combination space for identifying potential feasible epistasis solutions. Multiple epistasis solutions represent different pathogenic gene combinations, which may lead to different tumor subtypes, that is, heterogeneity. Finally, the XGBoost classifier is trained with feature SNPs selected that constitute multiple sets of epistatic solutions to verify that considering tumor heterogeneity is beneficial to improve the accuracy of tumor subtype prediction. In order to demonstrate the effectiveness of our method, the power of multiple epistatic recognition and the accuracy of tumor subtype classification measures are evaluated. Extensive simulation results show that our method has better power and prediction accuracy than previous methods.

Identification of Mutation Landscape and Immune Cell Component for Liver Hepatocellular Carcinoma Highlights Potential Therapeutic Targets and Prognostic Markers.

Liver hepatocellular carcinoma (LIHC) is a primary malignancy, and there is a lack of effective treatment for advanced patients. Although numerous studies exist to reveal the carcinogenic mechanism of LIHC, few studies have integrated multi-omics data to systematically analyze pathogenesis and reveal potential therapeutic targets. Here, we integrated genomic variation data and RNA-seq profiles obtained by high-throughput sequencing to define high- and low-genomic instability samples. The mutational landscape was reported, and the advanced patients of LIHC were characterized by high-genomic instability. We found that the tumor microenvironment underwent metabolic reprograming driven by mutations accumulate to satisfy tumor proliferation and invasion. Further, the co-expression network identifies three mutant long non-coding RNAs as potential therapeutic targets, which can promote tumor progression by participating in specific carcinogenic mechanisms. Then, five potential prognostic markers (RP11-502I4.3, SPINK5, CHRM3, SLC5A12, and RP11-467L13.7) were identified by examining the association of genes and patient survival. By characterizing the immune landscape of LIHC, loss of immunogenicity was revealed as a key factor of immune checkpoint suppression. Macrophages were found to be significantly associated with patient risk scores, and high levels of macrophages accelerated patient mortality. In summary, the mutation-driven mechanism and immune landscape of LIHC revealed by this study will serve precision medicine.