Genomic analysis and phylogenetic characterization of Himalayan snow trout, Schizothorax esocinus based on mitochondrial protein-coding genes.

BACKGROUND: Mitochondrial DNA (mtDNA) has become a significant tool for exploring genetic diversity and delineating evolutionary links across diverse taxa. Within the group of cold-water fish species that are native to the Indian Himalayan region, Schizothorax esocinus holds particular importance due to its ecological significance and is potentially vulnerable to environmental changes. This research aims to clarify the phylogenetic relationships within the Schizothorax genus by utilizing mitochondrial protein-coding genes. METHODS: Standard protocols were followed for the isolation of DNA from S. esocinus. For the amplification of mtDNA, overlapping primers were used, and then subsequent sequencing was performed. The genetic features were investigated by the application of bioinformatic approaches. These approaches covered the evaluation of nucleotide composition, codon usage, selective pressure using nonsynonymous substitution /synonymous substitution (Ka/Ks) ratios, and phylogenetic analysis. RESULTS: The study specifically examined the 13 protein-coding genes of Schizothorax species which belongs to the Schizothoracinae subfamily. Nucleotide composition analysis showed a bias towards A + T content, consistent with other cyprinid fish species, suggesting evolutionary conservation. Relative Synonymous Codon Usage highlighted leucine as the most frequent (5.18%) and cysteine as the least frequent (0.78%) codon. The positive AT-skew and the predominantly negative GC-skew indicated the abundance of A and C. Comparative analysis revealed significant conservation of amino acids in multiple genes. The majority of amino acids were hydrophobic rather than polar. The purifying selection was revealed by the genetic distance and Ka/Ks ratios. Phylogenetic study revealed a significant genetic divergence between S. esocinus and other Schizothorax species with interspecific K2P distances ranging from 0.00 to 8.87%, with an average of 5.76%. CONCLUSION: The present study provides significant contributions to the understanding of mitochondrial genome diversity and genetic evolution mechanisms in Schizothoracinae, hence offering vital insights for the development of conservation initiatives aimed at protecting freshwater fish species.

Molecular diversity of black corals from the Saudi Arabian Red Sea: a first assessment.

Black corals occur as part of benthic assemblages from shallow to deep waters in all oceans. Despite the importance in many benthic ecosystems, where these act as biodiversity aggregators, antipatharians remain poorly studied, with 75% of the known species occurring below recreational SCUBA diving depth limits. Currently, information regarding the diversity and evolutionary history is limited, with most studies focusing on Hawaii and the South Pacific Ocean. Other regions of the world have received less attention, such as the Red Sea, where only two black coral families and four genera have been recorded. We provide the first analysis of the molecular diversity of black corals in the eastern Gulf of Aqaba and the northern and central Saudi Arabian Red Sea, based on a dataset of 161 antipatharian colonies collected down to 627 m deep. Based on specimen morphology, we ascribed our material to 11 genera belonging to 4 of the 7 known Antipatharia families, i.e. Antipathidae, Aphanipathidae, Myriopathidae and Schizopathidae. The genus level phylogeny of three intergenic mitochondrial regions, the trnW-IGR-nad2 (IgrW ), nad5-IGR-nad1 (IgrN ) and cox3-IGR-cox1 was reconstructed including previously published material. Overall, we recovered six molecular clades that included exclusively Red Sea sequences, with the highest diversity occurring at mesophotic depths. This study highlights that diversity of black corals in the Red Sea is much higher than previously known, with seven new generic records, suggesting that this basin may be a hotspot for antipatharian diversity as is known for other taxa. Our results recovered unresolved relationships within the order at the familial and generic levels. This emphasises the urgent need for an integration of genomic-wide data with a re-examination of informative morphological features necessary to revise the systematics of the order at all taxonomic levels.

Thymus algeriensis Boiss. et Reut., a north African endemic plant species: genetic diversity and population structure as assessed by molecular markers, a pioneer step for conservation implications.

BACKGROUND: Thymus algeriensis Boiss. et Reut. is one of the most widespread North African species of the genus Thymus L. The species is subshrub growing primarily in subtropical biome of Morocco, Algeria, Tunisia and Libya. In Tunisia, the plant species is under high pressure of anthropogenic activities including over-collecting. The assessment of genetic diversity and population structure of T. algeriensis is a pioneer step to retrace its evolutionary history and to perform appropriate conservation strategies of the plant species. METHODS AND RESULTS: Seven wild populations growing, widely, in different bioclimatic zones were selected and analysed using two molecular markers systems. Fifteen Simple Sequence Repeats (SSRs) and fifteen Inter-Simple Sequence Repeats (ISSRs) were used to characterize genetically 140 different genotypes. The results showed a high molecular variation within populations and among the studied genotypes. The intra-populations genetic diversity revealed by SSRs was higher (P = 80.95%, Na = 2.143 and He = 0.364) than that based on ISSRs (P = 78.12%, Na = 1.632, He = 0.265 and I = 0.398). As demonstrated by inbreeding coefficients, a significant level of differentiation and a low level of gene flow were detected among studied populations (FST = 0.161 for SSRs and ΦST = 0.197 for ISSRs). Furthermore, the results of ISSRs marker suggest land strips as barriers in population genetic structure. While SSRs marker reflects a relatively structured bioclimatic patterns of studied populations. The Bayesian analysis showed a specific adaptation of populations to local environments. CONCLUSIONS: The used molecular markers (ISSRs and SSRs) seem to be effective in deciphering genetic polymorphism of Tunisian genotypes of T. algeriensis. Therefore, the genetic structure of the studied genotypes could constitute a starting point for further conservation, characterization and breeding programs.

Discovery of a peculiar insular race of Ravenna nivea (Nire, 1920) (Lepidoptera: Lycaenidae) endemic to Yinggeling Mountain of Hainan, suggesting heterogeneous geological history of mountain formation of the island.

A peculiar population of Ravenna nivea (Nire, 1920) was discovered from the Yinggeling Mountain Mass of central Hainan. Its wing pattern and COI barcode data show considerable distinction from other geographic populations of R. nivea, including that of Bawangling, approximately only 40 km away and also located in Hainan. The p-distance value of the COI barcode between the Yinggeling and Bawangling populations was 1.1%, considerably higher than the value (0.6%) between Bawangling population and populations in eastern China, where the subspecific name howarthi Saigusa, 1993 applies. The population is regarded as a distinct subspecies ngiunmoiae Lo & Hsu, subsp. nov. The distinctness and high degree of COI haplotype diversity of R. nivea found in Hainan and Taiwan suggest continental islands may serve as glacial refugees for the butterfly and other organisms during previous glaciations, and the presence of the relict populations of montane butterflies like R. nivea may provide useful clues towards a better understanding of the geological history of mountain formation within islands.

Rare GPR37L1 Variants Reveal Potential Association between GPR37L1 and Disorders of Anxiety and Migraine.

GPR37L1 is an orphan receptor that couples through heterotrimeric G-proteins to regulate physiological functions. Since its role in humans is not fully defined, we used an unbiased computational approach to assess the clinical significance of rare G-protein-coupled receptor 37-like 1 (GPR37L1) genetic variants found among 51,289 whole-exome sequences from the DiscovEHR cohort. Rare GPR37L1 coding variants were binned according to predicted pathogenicity and analyzed by sequence kernel association testing to reveal significant associations with disease diagnostic codes for epilepsy and migraine, among others. Since associations do not prove causality, rare GPR37L1 variants were functionally analyzed in SK-N-MC cells to evaluate potential signaling differences and pathogenicity. Notably, receptor variants exhibited varying abilities to reduce cAMP levels, activate mitogen-activated protein kinase (MAPK) signaling, and/or upregulate receptor expression in response to the agonist prosaptide (TX14(A)), as compared with the wild-type receptor. In addition to signaling changes, knock-out (KO) of GPR37L1 or expression of certain rare variants altered cellular cholesterol levels, which were also acutely regulated by administration of the agonist TX14(A) via activation of the MAPK pathway. Finally, to simulate the impact of rare nonsense variants found in the large patient cohort, a KO mouse line lacking Gpr37l1 was generated. Although KO animals did not recapitulate an acute migraine phenotype, the loss of this receptor produced sex-specific changes in anxiety-related disorders often seen in chronic migraineurs. Collectively, these observations define the existence of rare GPR37L1 variants associated with neuropsychiatric conditions in the human population and identify the signaling changes contributing to pathological processes.

Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project.

BACKGROUND: A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating. Knowing which tools are most effective remains unclear. To evaluate the performance of computational methods, and to encourage innovation in method development, we designed a Critical Assessment of Genome Interpretation (CAGI) community challenge to place variant prioritization models head-to-head in a real-life clinical diagnostic setting. METHODS: We utilized genome sequencing (GS) data from families sequenced in the Rare Genomes Project (RGP), a direct-to-participant research study on the utility of GS for rare disease diagnosis and gene discovery. Challenge predictors were provided with a dataset of variant calls and phenotype terms from 175 RGP individuals (65 families), including 35 solved training set families with causal variants specified, and 30 unlabeled test set families (14 solved, 16 unsolved). We tasked teams to identify causal variants in as many families as possible. Predictors submitted variant predictions with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on the rank position of causal variants, and the maximum F-measure, based on precision and recall of causal variants across all EPCR values. RESULTS: Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performers recalled causal variants in up to 13 of 14 solved families within the top 5 ranked variants. Newly discovered diagnostic variants were returned to two previously unsolved families following confirmatory RNA sequencing, and two novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant in an unsolved proband with phenotypes consistent with asparagine synthetase deficiency. CONCLUSIONS: Model methodology and performance was highly variable. Models weighing call quality, allele frequency, predicted deleteriousness, segregation, and phenotype were effective in identifying causal variants, and models open to phenotype expansion and non-coding variants were able to capture more difficult diagnoses and discover new diagnoses. Overall, computational models can significantly aid variant prioritization. For use in diagnostics, detailed review and conservative assessment of prioritized variants against established criteria is needed.

Conserved DNA sequence analysis reveals the phylogeography and evolutionary events of Akebia trifoliata in the region across the eastern edge of the Tibetan Plateau and subtropical China.

BACKGROUND: The eastern edge of the Qinghai‒Tibet Plateau (QTP) and subtropical China have various regions where plant species originate and thrive, but these regions have been the focus of very few integrative studies. Here, we elucidated the phylogeographic structure of a continuous and widespread Akebia trifoliata population across these two regions. RESULTS: Sixty-one populations consisting of 391 genotypes were examined to assess population diversity and structure via network distribution analysis, maximum likelihood phylogenetic tree reconstruction, divergence time estimation, demographic history inference, and ancestral area reconstruction of both conserved internal transcribed spacer (ITS) and chloroplast (rps16) DNA sequences. The results showed that the ITS region was more variable than the rps16 region and could be suitable for studying intraspecific phylogeography. The A. trifoliata population displayed high genetic diversity, genetic differentiation and obvious phylogeographical structure, possibly originating on the eastern QTP, expanding during the last glacial-interglacial cycle, diverging in the early Pleistocene and middle Pleistocene, and extensively migrating thereafter. The migration route from west to east along rivers could be largely responsible for the long-distance dispersal of this species, while three main refuges (Qinba Mountains, Nanling Mountains and Yunnan-Guizhou Plateau) with multiple ice shelters facilitated its wide distribution. CONCLUSIONS: Our results suggested that the from west to east long migration accompanying with the minor short reciprocal migration in the south-north direction, and the three main refuges (the Qinba Mountains, Nanling Mountains and Yunnan-Guizhou Plateau) contributed to the extant geographical distribution of A. trifoliata. In addition, this finding also strongly reduced the discrepancy between glacial contraction and postglacial expansion and the in situ survival hypothesis by simultaneously considering the existence of many similar climate-related ecological niches and migration influences.

Genetic divergence accessed with microsatellite markers reflects the time of Crassostrea gigas genetic breeding in Brazil.

The Pacific Oyster was introduced on Santa Catarina Island in 1987, experiencing processes of selection and genetic breeding since then. Such procedures may have led to the establishment of specific strains, given the saltier and warmer conditions of the Atlantic Ocean. This study employed microsatellite markers to compare allelic patterns of oysters cultivated in Santa Catarina, the USA, and Asia. Specific allelic patterns were revealed in the Santa Catarina samples, reflecting the time of selection/breeding of the oyster in this region. This result supports the effectiveness of the selection/breeding procedures and the demand for protection of this commercially important genetic resource.

Kernel density estimation of allele frequency including undetected alleles.

Whereas undetected species contribute to estimation of species diversity, undetected alleles have not been used to estimated genetic diversity. Although random sampling guarantees unbiased estimation of allele frequency and genetic diversity measures, using undetected alleles may provide biased but more precise estimators useful for conservation. We newly devised kernel density estimation (KDE) for allele frequency including undetected alleles and tested it in estimation of allele frequency and nucleotide diversity using population generated by coalescent simulation as well as well as real population data. Contrary to expectations, nucleotide diversity estimated by KDE had worse bias and accuracy. Allele frequency estimated by KDE was also worse except when the sample size was small. These might be due to finity of population and/or the curse of dimensionality. In conclusion, KDE of allele frequency does not contribute to genetic diversity estimation.

Phenotypic variation seems not to be associated with the genetic profile in Zygopetalum (Orchidaceae): a case study of a high-elevation rocky complex.

BACKGROUND: Hybridization associated with polyploidy studies is rare in the tropics. The genus Zygopetalum (Orchidaceae) was investigated here as a case study of Neotropical plants. In the rocky highlands of the Ibitipoca State Park (ISP), southeast Brazil, individuals with intermediate colors and forms between the species Z. maculatum and Z. triste were commonly identified. METHODS AND RESULTS: Chromosomal analysis and DNA quantity showed a uniform population. Regardless of the aspects related to the color and shape of floral structures, all individuals showed 2n = 96 chromosomes and an average of 14.05 pg of DNA. Irregularities in meiosis associated with chromosome number and C value suggest the occurrence of polyploidy. The genetic distance estimated using ISSR molecular markers revealed the existence of genetic variability not related to morphological clusters. Morphometric measurements of the flower pieces revealed that Z. maculatum shows higher variation than Z. triste although lacking a defined circumscription. CONCLUSION: The observed variation can be explained by the polyploid and phenotypic plasticity resulting from the interaction of the genotypes with the heterogeneous environments observed in this habitat.

Rare genetic variation in fibronectin 1 (FN1) protects against APOEε4 in Alzheimer's disease.

The risk of developing Alzheimer's disease (AD) significantly increases in individuals carrying the APOEε4 allele. Elderly cognitively healthy individuals with APOEε4 also exist, suggesting the presence of cellular mechanisms that counteract the pathological effects of APOEε4; however, these mechanisms are unknown. We hypothesized that APOEε4 carriers without dementia might carry genetic variations that could protect them from developing APOEε4-mediated AD pathology. To test this, we leveraged whole-genome sequencing (WGS) data in the National Institute on Aging Alzheimer's Disease Family Based Study (NIA-AD FBS), Washington Heights/Inwood Columbia Aging Project (WHICAP), and Estudio Familiar de Influencia Genetica en Alzheimer (EFIGA) cohorts and identified potentially protective variants segregating exclusively among unaffected APOEε4 carriers. In homozygous unaffected carriers above 70 years old, we identified 510 rare coding variants. Pathway analysis of the genes harboring these variants showed significant enrichment in extracellular matrix (ECM)-related processes, suggesting protective effects of functional modifications in ECM proteins. We prioritized two genes that were highly represented in the ECM-related gene ontology terms, (FN1) and collagen type VI alpha 2 chain (COL6A2) and are known to be expressed at the blood-brain barrier (BBB), for postmortem validation and in vivo functional studies. An independent analysis in a large cohort of 7185 APOEε4 homozygous carriers found that rs140926439 variant in FN1 was protective of AD (OR = 0.29; 95% CI [0.11, 0.78], P = 0.014) and delayed age at onset of disease by 3.37 years (95% CI [0.42, 6.32], P = 0.025). The FN1 and COL6A2 protein levels were increased at the BBB in APOEε4 carriers with AD. Brain expression of cognitively unaffected homozygous APOEε4 carriers had significantly lower FN1 deposition and less reactive gliosis compared to homozygous APOEε4 carriers with AD, suggesting that FN1 might be a downstream driver of APOEε4-mediated AD-related pathology and cognitive decline. To validate our findings, we used zebrafish models with loss-of-function (LOF) mutations in fn1b-the ortholog for human FN1. We found that fibronectin LOF reduced gliosis, enhanced gliovascular remodeling, and potentiated the microglial response, suggesting that pathological accumulation of FN1 could impair toxic protein clearance, which is ameliorated with FN1 LOF. Our study suggests that vascular deposition of FN1 is related to the pathogenicity of APOEε4, and LOF variants in FN1 may reduce APOEε4-related AD risk, providing novel clues to potential therapeutic interventions targeting the ECM to mitigate AD risk.

Applicability of SCoT markers in unraveling genetic variation and population structure among sugar beet (Beta vulgaris L.) germplasm.

BACKGROUND: Sugar beet (Beta vulgaris L.) holds significant importance as a crop globally cultivated for sugar production. The genetic diversity present in sugar beet accessions plays a crucial role in crop improvement programs. METHODS AND RESULTS: During the present study, we collected 96 sugar beet accessions from different regions and extracted DNA from their leaves. Genomic DNA was amplified using SCoT primers, and the resulting fragments were separated by gel electrophoresis. The data were analyzed using various genetic diversity indices, and constructed a population STRUCTURE, applied the unweighted pair-group method with arithmetic mean (UPGMA), and conducted Principle Coordinate Analysis (PCoA). The results revealed a high level of genetic diversity among the sugar beet accessions, with 265 bands produced by the 10 SCoT primers used. The percentage of polymorphic bands was 97.60%, indicating substantial genetic variation. The study uncovered significant genetic variation, leading to higher values for overall gene diversity (0.21), genetic distance (0.517), number of effective alleles (1.36), Shannon's information index (0.33), and polymorphism information contents (0.239). The analysis of molecular variance suggested a considerable amount of genetic variation, with 89% existing within the population. Using STRUCTURE and UPGMA analysis, the sugar beet germplasm was divided into two major populations. Structure analysis partitioned the germplasm based on the origin and domestication history of sugar beet, resulting in neighboring countries clustering together. CONCLUSION: The utilization of SCoT markers unveiled a noteworthy degree of genetic variation within the sugar beet germplasm in this study. These findings can be used in future breeding programs with the objective of enhancing both sugar beet yield and quality.

Key variants via the Alzheimer's Disease Sequencing Project whole genome sequence data.

INTRODUCTION: Genome-wide association studies (GWAS) have identified loci associated with Alzheimer's disease (AD) but did not identify specific causal genes or variants within those loci. Analysis of whole genome sequence (WGS) data, which interrogates the entire genome and captures rare variations, may identify causal variants within GWAS loci. METHODS: We performed single common variant association analysis and rare variant aggregate analyses in the pooled population (N cases = 2184, N controls = 2383) and targeted analyses in subpopulations using WGS data from the Alzheimer's Disease Sequencing Project (ADSP). The analyses were restricted to variants within 100 kb of 83 previously identified GWAS lead variants. RESULTS: Seventeen variants were significantly associated with AD within five genomic regions implicating the genes OARD1/NFYA/TREML1, JAZF1, FERMT2, and SLC24A4. KAT8 was implicated by both single variant and rare variant aggregate analyses. DISCUSSION: This study demonstrates the utility of leveraging WGS to gain insights into AD loci identified via GWAS.

Somatic variants as a cause of drug-resistant epilepsy including mesial temporal lobe epilepsy with hippocampal sclerosis.

OBJECTIVE: The contribution of somatic variants to epilepsy has recently been demonstrated, particularly in the etiology of malformations of cortical development. The aim of this study was to determine the diagnostic yield of somatic variants in genes that have been previously associated with a somatic or germline epilepsy model, ascertained from resected brain tissue from patients with multidrug-resistant focal epilepsy. METHODS: Forty-two patients were recruited across three categories: (1) malformations of cortical development, (2) mesial temporal lobe epilepsy with hippocampal sclerosis, and (3) nonlesional focal epilepsy. Participants were subdivided based on histopathology of the resected brain. Paired blood- and brain-derived DNA samples were sequenced using high-coverage targeted next generation sequencing to high depth (585× and 1360×, respectively). Variants were identified using Genome Analysis ToolKit (GATK4) MuTect-2 and confirmed using high-coverage Amplicon-EZ sequencing. RESULTS: Sequence data on 41 patients passed quality control. Four somatic variants were validated following amplicon sequencing: within CBL, ALG13, MTOR, and FLNA. The diagnostic yield across 41 patients was 10%, 9% in mesial temporal lobe epilepsy with hippocampal sclerosis and 20% in malformations of cortical development. SIGNIFICANCE: This study provides novel insights into the etiology of mesial temporal lobe epilepsy with hippocampal sclerosis, highlighting a potential pathogenic role of somatic variants in CBL and ALG13. We also report candidate diagnostic somatic variants in FLNA in focal cortical dysplasia, while providing further insight into the importance of MTOR and related genes in focal cortical dysplasia. This work demonstrates the potential molecular diagnostic value of variants in both germline and somatic epilepsy genes.

Explicable prioritization of genetic variants by integration of rule-based and machine learning algorithms for diagnosis of rare Mendelian disorders.

BACKGROUND: In the process of finding the causative variant of rare diseases, accurate assessment and prioritization of genetic variants is essential. Previous variant prioritization tools mainly depend on the in-silico prediction of the pathogenicity of variants, which results in low sensitivity and difficulty in interpreting the prioritization result. In this study, we propose an explainable algorithm for variant prioritization, named 3ASC, with higher sensitivity and ability to annotate evidence used for prioritization. 3ASC annotates each variant with the 28 criteria defined by the ACMG/AMP genome interpretation guidelines and features related to the clinical interpretation of the variants. The system can explain the result based on annotated evidence and feature contributions. RESULTS: We trained various machine learning algorithms using in-house patient data. The performance of variant ranking was assessed using the recall rate of identifying causative variants in the top-ranked variants. The best practice model was a random forest classifier that showed top 1 recall of 85.6% and top 3 recall of 94.4%. The 3ASC annotates the ACMG/AMP criteria for each genetic variant of a patient so that clinical geneticists can interpret the result as in the CAGI6 SickKids challenge. In the challenge, 3ASC identified causal genes for 10 out of 14 patient cases, with evidence of decreased gene expression for 6 cases. Among them, two genes (HDAC8 and CASK) had decreased gene expression profiles confirmed by transcriptome data. CONCLUSIONS: 3ASC can prioritize genetic variants with higher sensitivity compared to previous methods by integrating various features related to clinical interpretation, including features related to false positive risk such as quality control and disease inheritance pattern. The system allows interpretation of each variant based on the ACMG/AMP criteria and feature contribution assessed using explainable AI techniques.

Screening for drought tolerance and genetic diversity of wheat varieties using agronomic and molecular markers.

BACKGROUND: The future predictions for frequent and severe droughts will represent a significant threat to wheat yield and food security. In this context, breeding has proven to be the most efficient approach to enhance wheat productivity in dry environments. METHODS AND RESULTS: In this study, both agronomic and molecular-based approaches were used to evaluate the response of twenty-eight Tunisian wheat varieties to drought stress. The primary objective was to screen these varieties for drought tolerance using molecular and agro-morphological markers. All varieties were significantly affected by drought stress regarding various traits including total dry matter, straw length, flag leaf area, number of senescent leaves, SPAD value, grain yield and grain number. Furthermore, substantial variability in drought-stress tolerance was observed among wheat genotypes. The cluster analysis and principal component analyses confirmed the existence of genotypic variation in growth and yield impairments induced by drought. The stress susceptibility index (SSI) and tolerance index (TOL) proved to be the most effective indices and were strongly correlated with the varying levels of genotypic tolerance. The genotyping evaluation resulted in the amplification of 101 alleles using highly polymorphic 12 SSR markers, showed an average polymorphism of 74%. CONCLUSIONS: Taken together, the combination of agronomic and molecular approaches revealed that Karim, Td7, D117 and Utique are the most drought-tolerant wheat varieties. These varieties are particularly promising candidates for genetic improvements and can be utilized as potential genitors for future breeding programs in arid and semi-arid regions.

Genetic diversity promotes resilience in a mouse model of Alzheimer's disease.

INTRODUCTION: Alzheimer's disease (AD) is a neurodegenerative disorder with multifactorial etiology, including genetic factors that play a significant role in disease risk and resilience. However, the role of genetic diversity in preclinical AD studies has received limited attention. METHODS: We crossed five Collaborative Cross strains with 5xFAD C57BL/6J female mice to generate F1 mice with and without the 5xFAD transgene. Amyloid plaque pathology, microglial and astrocytic responses, neurofilament light chain levels, and gene expression were assessed at various ages. RESULTS: Genetic diversity significantly impacts AD-related pathology. Hybrid strains showed resistance to amyloid plaque formation and neuronal damage. Transcriptome diversity was maintained across ages and sexes, with observable strain-specific variations in AD-related phenotypes. Comparative gene expression analysis indicated correlations between mouse strains and human AD. DISCUSSION: Increasing genetic diversity promotes resilience to AD-related pathogenesis, relative to an inbred C57BL/6J background, reinforcing the importance of genetic diversity in uncovering resilience in the development of AD. HIGHLIGHTS: Genetic diversity's impact on AD in mice was explored. Diverse F1 mouse strains were used for AD study, via the Collaborative Cross. Strain-specific variations in AD pathology, glia, and transcription were found. Strains resilient to plaque formation and plasma neurofilament light chain (NfL) increases were identified. Correlations with human AD transcriptomics were observed.

Pediatric Beta Blocker Therapy: A Comprehensive Review of Development and Genetic Variation to Guide Precision-Based Therapy in Children, Adolescents, and Young Adults.

Beta adrenergic receptor antagonists, known as beta blockers, are one of the most prescribed medications in both pediatric and adult cardiology. Unfortunately, most of these agents utilized in the pediatric clinical setting are prescribed off-label. Despite regulatory efforts aimed at increasing pediatric drug labeling, a majority of pediatric cardiovascular drug agents continue to lack pediatric-specific data to inform precision dosing for children, adolescents, and young adults. Adding to this complexity is the contribution of development (ontogeny) and genetic variation towards the variability in drug disposition and response. In the absence of current prospective trials, the purpose of this comprehensive review is to illustrate the current knowledge gaps regarding the key drivers of variability in beta blocker drug disposition and response and the opportunities for investigations that will lead to changes in pediatric drug labeling.

Cell subtype-specific effects of genetic variation in the Alzheimer's disease brain.

The relationship between genetic variation and gene expression in brain cell types and subtypes remains understudied. Here, we generated single-nucleus RNA sequencing data from the neocortex of 424 individuals of advanced age; we assessed the effect of genetic variants on RNA expression in cis (cis-expression quantitative trait loci) for seven cell types and 64 cell subtypes using 1.5 million transcriptomes. This effort identified 10,004 eGenes at the cell type level and 8,099 eGenes at the cell subtype level. Many eGenes are only detected within cell subtypes. A new variant influences APOE expression only in microglia and is associated with greater cerebral amyloid angiopathy but not Alzheimer's disease pathology, after adjusting for APOEε4, providing mechanistic insights into both pathologies. Furthermore, only a TMEM106B variant affects the proportion of cell subtypes. Integration of these results with genome-wide association studies highlighted the targeted cell type and probable causal gene within Alzheimer's disease, schizophrenia, educational attainment and Parkinson's disease loci.

A revamped rat reference genome improves the discovery of genetic diversity in laboratory rats.

The seventh iteration of the reference genome assembly for Rattus norvegicus-mRatBN7.2-corrects numerous misplaced segments and reduces base-level errors by approximately 9-fold and increases contiguity by 290-fold compared with its predecessor. Gene annotations are now more complete, improving the mapping precision of genomic, transcriptomic, and proteomics datasets. We jointly analyzed 163 short-read whole-genome sequencing datasets representing 120 laboratory rat strains and substrains using mRatBN7.2. We defined ∼20.0 million sequence variations, of which 18,700 are predicted to potentially impact the function of 6,677 genes. We also generated a new rat genetic map from 1,893 heterogeneous stock rats and annotated transcription start sites and alternative polyadenylation sites. The mRatBN7.2 assembly, along with the extensive analysis of genomic variations among rat strains, enhances our understanding of the rat genome, providing researchers with an expanded resource for studies involving rats.