Genomic and single-cell analyses reveal genetic signatures of swimming pattern and diapause strategy in jellyfish.

Jellyfish exhibit innovative swimming patterns that contribute to exploring the origins of animal locomotion. However, the genetic and cellular basis of these patterns remains unclear. Herein, we generated chromosome-level genome assemblies of two jellyfish species, Turritopsis rubra and Aurelia coerulea, which exhibit straight and free-swimming patterns, respectively. We observe positive selection of numerous genes involved in statolith formation, hair cell ciliogenesis, ciliary motility, and motor neuron function. The lineage-specific absence of otolith morphogenesis- and ciliary movement-related genes in T. rubra may be associated with homeostatic structural statocyst loss and straight swimming pattern. Notably, single-cell transcriptomic analyses covering key developmental stages reveal the enrichment of diapause-related genes in the cyst during reverse development, suggesting that the sustained diapause state favours the development of new polyps under favourable conditions. This study highlights the complex relationship between genetics, locomotion patterns and survival strategies in jellyfish, thereby providing valuable insights into the evolutionary lineages of movement and adaptation in the animal kingdom.

Genomic surveillance of malaria parasites in an indigenous community in the Peruvian Amazon.

Hard-to-reach communities represent Peru's main challenge for malaria elimination, but information about transmission in these areas is scarce. Here, we assessed Plasmodium vivax (Pv) and P. falciparum (Pf) transmission dynamics, resistance markers, and Pf hrp2/3 deletions in Nueva Jerusalén (NJ), a remote, indigenous community in the Peruvian Amazon with high population mobility. We collected samples from November 2019 to May 2020 by active (ACD) and passive case detection (PCD) in NJ. Parasites were identified with microscopy and PCR. Then, we analyzed a representative set of positive-PCR samples (Pv = 68, Pf = 58) using highly-multiplexed deep sequencing assays (AmpliSeq) and compared NJ parasites with ones from other remote Peruvian areas using population genetics indexes. The ACD intervention did not reduce malaria cases in the short term, and persistent malaria transmission was observed (at least one Pv infection was detected in 96% of the study days). In Nueva Jerusalen, the Pv population had modest genetic diversity (He = 0.27). Pf population had lower diversity (He = 0.08) and presented temporal clustering, one of these clusters linked to an outbreak in February 2020. Moreover, Pv and Pf parasites from NJ exhibited variable levels of differentiation (Pv Fst = 0.07-0.52 and Pf Fst = 0.11-0.58) with parasites from other remote areas. No artemisin resistance mutations but chloroquine (57%) and sulfadoxine-pyrimethamine (35-67%) were detected in NJ's Pf parasites. Moreover, pfhrp2/3 gene deletions were common (32-50% of parasites with one or both genes deleted). The persistent Pv transmission and the detection of a Pf outbreak with parasites genetically distinct from the local ones highlight the need for tailored interventions focusing on mobility patterns and imported infections in remote areas to eliminate malaria in the Peruvian Amazon.

Draft genome assemblies of the ponerine ant Odontoponera transversa and the carpenter ant Camponotus friedae (Hymenoptera: Formicidae).

OBJECTIVES: Ants are ecologically dominant insects in most terrestrial ecosystems, with more than 14,000 extant species in about 340 genera recorded to date. However, genomic resources are still scarce for most species, especially for species endemic in East or Southeast Asia, limiting the study of phylogeny, speciation and adaptation of this evolutionarily successful animal lineage. Here, we assemble and annotate the genomes of Odontoponera transversa and Camponotus friedae, two ant species with a natural distribution in China, to facilitate future study of ant evolution. DATA DESCRIPTION: We obtained a total of 16 Gb and 51 Gb PacBio HiFi data for O. transversa and C. friedae, respectively, which were assembled into the draft genomes of 339 Mb for O. transversa and 233 Mb for C. friedae. Genome assessments by multiple metrics showed good completeness and high accuracy of the two assemblies. Gene annotations assisted by RNA-seq data yielded a comparable number of protein-coding genes in the two genomes (10,892 for O. transversa and 11,296 for C. friedae), while repeat annotations revealed a remarkable difference of repeat content between these two ant species (149.4 Mb for O. transversa versus 49.7 Mb for C. friedae). Besides, complete mitochondrial genomes for the two species were assembled and annotated.

An Overview of Global, Local, and Base-Resolution Methods for the Detection of 5-Hydroxymethylcytosine in Genomic DNA.

The discovery of 5-hydroxymethylcytosine (5hmC) as a common DNA modification in mammalian genomes has ushered in new areas of inquiry regarding the dynamic epigenome. The balance between 5hmC and its precursor, 5-methylcytosine (5mC), has emerged as a determinant of key processes including cell fate specification, and alterations involving these bases have been implicated in the pathogenesis of various diseases. The identification of 5hmC separately from 5mC initially posed a challenge given that legacy epigenetic sequencing technologies could not discriminate between these two most abundant modifications, a significant blind spot considering their potentially functionally opposing roles. The growing interest in 5hmC, as well as in the Ten-Eleven Translocation (TET) family enzymes that catalyze its generation and further oxidation to 5-formylcytosine (5fC) and 5-carboxycytosine (5caC), has spurred the development of versatile methods for 5hmC detection. These methods enable the quantification and localization of 5hmC in diverse biological samples and, in some cases, at the resolution of individual nucleotides. However, navigating this growing toolbox of methods for 5hmC detection can be challenging. Here, we detail existing and emerging methods for the detection, quantification, and localization of 5hmC at global, locus-specific, and base resolution levels. These methods are discussed in the context of their advantages and limitations, with the goal of providing a framework to help guide researchers in choosing the level of resolution and the associated method that could be most suitable for specific needs.

GraphSlimmer: Preserving Read Mappability with the Minimum Number of Variants.

Modern genomic datasets, like those generated under the 1000 Genome Project, contain millions of variants belonging to known haplotypes. Although these datasets are more representative than a single reference sequence and can alleviate issues like reference bias, they are significantly more computationally burdensome to work with, often involving large-indexed genome graph data structures for tasks such as read mapping. The construction, preprocessing, and mapping algorithms can require substantial computational resources depending on the size of these variant sets. Moreover, the accuracy of mapping algorithms has been shown to decrease when working with complete variant sets. Therefore, a drastically reduced set of variants that preserves important properties of the original set is desirable. This work provides a technique for finding a minimal subset of variants S such that for given parameters α and δ, all substrings up to length α in the haplotypes are guaranteed to be still alignable to the appropriate locations with either Hamming or edit distance at most δ, using only S. Our contributions include showing the NP-hardness and inapproximability of these optimization problems and providing Integer Linear Programming (ILP) formulations. Our edit distance ILP formulation carefully decomposes the problem according to variant locations, which allows it to scale to support all of chromosome 22's variants from the 1000 Genome Project. Our experiments also demonstrate a significant reduction in the number of variants. For example, for moderately long reads, e.g., α = 1000, over 75% of the variants can be removed while preserving read mappability with edit distance at most one.

Trematode Genomics and Proteomics.

Trematode infections stand out as one of the frequently overlooked tropical diseases, despite their wide global prevalence and remarkable capacity to parasitize diverse host species and tissues. Furthermore, these parasites hold significant socio-economic, medical, veterinary and agricultural implications. Over the past decades, substantial strides have been taken to bridge the information gap concerning various "omic" tools, such as proteomics and genomics, in this field. In this edition of the book, we highlight recent progress in genomics and proteomics concerning trematodes with a particular focus on the advances made in the past 5 years. Additionally, we present insights into cutting-edge technologies employed in studying trematode biology and shed light on the available resources for exploring the molecular facets of this particular group of parasitic helminths.

Puzzle Hi-C: An accurate scaffolding software.

High-quality, chromosome-scale genomes are essential for genomic analyses. Analyses, including 3D genomics, epigenetics, and comparative genomics rely on a high-quality genome assembly, which is often accomplished with the assistance of Hi-C data. Curation of genomes reveal that current Hi-C-assisted scaffolding algorithms either generate ordering and orientation errors or fail to assemble high-quality chromosome-level scaffolds. Here, we offer the software Puzzle Hi-C, which uses Hi-C reads to accurately assign contigs or scaffolds to chromosomes. Puzzle Hi-C uses the triangle region instead of the square region to count interactions in a Hi-C heatmap. This strategy dramatically diminishes scaffolding interference caused by long-range interactions. This software also introduces a dynamic, triangle window strategy during assembly. Initially small, the window expands with interactions to produce more effective clustering. Puzzle Hi-C outperforms available scaffolding tools.

Classification accuracy of machine learning algorithms for Chinese local cattle breeds using genomic markers.

Accurate breed classification is required for the conservation and utilization of farm animal genetic resources. Traditional classification methods mainly rely on phenotypic characterization. However, it is difficult to distinguish between the highly similar breeds due to the challenges in qualifying the phenotypic character. Machine learning algorithms show unique advantages in breed classification using genomic information. To evaluate the classification methods for Chinese cattle breeds, this study utilized genomic SNP data from 213 individuals across seven Chinese local breeds and compared the classification accuracies of three feature selection methods (FST value sorting and screening, mRMR, and Relief-F) and three machine learning algorithms (Random Forest, Support Vector Machine, and Naive Bayes). Results showed that: 1) using the FST method to screen more than 1500 SNPs, or using the mRMR algorithm to screen more than 1000 SNPs, the SVM classification algorithm can achieve more than 99.47% classification accuracy; 2) the most effective algorithm was SVM, followed by NB, while the best SNP selection method was FST and mRMR, followed by Relief-F; 3) species misclassification often occurs between breeds with high similarity. This study demonstrates that machine learning classification models combined with genomic data are effective methods for the classification of local cattle breeds, providing a technical basis for the rapid and accurate classification of cattle breeds in China.

Integrating mRNA transcripts and genomic information into genomic prediction.

Genomic prediction has emerged as a pivotal technology for the genetic evaluation of livestock, crops, and for predicting human disease risks. However, classical genomic prediction methods face challenges in incorporating biological prior information such as the genetic regulation mechanisms of traits. This study introduces a novel approach that integrates mRNA transcript information to predict complex trait phenotypes. To evaluate the accuracy of the new method, we utilized a Drosophila population that is widely employed in quantitative genetics researches globally. Results indicate that integrating mRNA transcript data can significantly enhance the genomic prediction accuracy for certain traits, though it does not improve phenotype prediction accuracy for all traits. Compared with GBLUP, the prediction accuracy for olfactory response to dCarvone in male Drosophila increased from 0.256 to 0.274. Similarly, the accuracy for cafe in male Drosophila rose from 0.355 to 0.401. The prediction accuracy for survival_paraquat in male Drosophila is improved from 0.101 to 0.138. In female Drosophila, the accuracy of olfactory response to 1hexanol increased from 0.147 to 0.210. In conclusion, integrating mRNA transcripts can substantially improve genomic prediction accuracy of certain traits by up to 43%, with range of 7% to 43%. Furthermore, for some traits, considering interaction effects along with mRNA transcript integration can lead to even higher prediction accuracy.

Genome-wide analysis of histone modifications can contribute to the identification of candidate cis-regulatory regions in the threespine stickleback fish.

BACKGROUND: Cis-regulatory mutations often underlie phenotypic evolution. However, because identifying the locations of promoters and enhancers in non-coding regions is challenging, we have fewer examples of identified causative cis-regulatory mutations that underlie naturally occurring phenotypic variations than of causative amino acid-altering mutations. Because cis-regulatory elements have epigenetic marks of specific histone modifications, we can detect cis-regulatory elements by mapping and analyzing them. Here, we investigated histone modifications and chromatin accessibility with cleavage under targets and tagmentation (CUT&Tag) and assay for transposase-accessible chromatin-sequencing (ATAC-seq). RESULTS: Using the threespine stickleback (Gasterosteus aculeatus) as a model, we confirmed that the genes for which nearby regions showed active marks, such as H3K4me1, H3K4me3, and high chromatin accessibility, were highly expressed. In contrast, the expression levels of genes for which nearby regions showed repressive marks, such as H3K27me3, were reduced, suggesting that our chromatin analysis protocols overall worked well. Genomic regions with peaks of histone modifications showed higher nucleotide diversity within and between populations. By comparing gene expression in the gills of the marine and stream ecotypes, we identified several insertions and deletions (indels) with transposable element fragments in the candidate cis-regulatory regions. CONCLUSIONS: Thus, mapping and analyzing histone modifications can help identify cis-regulatory elements and accelerate the identification of causative mutations in the non-coding regions underlying naturally occurring phenotypic variations.

SVDF: enhancing structural variation detect from long-read sequencing via automatic filtering strategies.

Structural variation (SV) is an important form of genomic variation that influences gene function and expression by altering the structure of the genome. Although long-read data have been proven to better characterize SVs, SVs detected from noisy long-read data still include a considerable portion of false-positive calls. To accurately detect SVs in long-read data, we present SVDF, a method that employs a learning-based noise filtering strategy and an SV signature-adaptive clustering algorithm, for effectively reducing the likelihood of false-positive events. Benchmarking results from multiple orthogonal experiments demonstrate that, across different sequencing platforms and depths, SVDF achieves higher calling accuracy for each sample compared to several existing general SV calling tools. We believe that, with its meticulous and sensitive SV detection capability, SVDF can bring new opportunities and advancements to cutting-edge genomic research.

Comparative genomics of Tn6411 transposons carrying the blaIMP-1 gene in Pseudomonas aeruginosa.

We aimed to determine the molecular characteristics of carbapenem-resistant Pseudomonas aeruginosa strains 18081308 and 18083286, which were isolated from the urine and the sputum of two Chinese patients, respectively. Additionally, we conducted a comparative analysis between Tn6411 carrying blaIMP-1 in strain 18083286 and transposons from the same family available in GenBank. Bacterial genome sequencing was carried out on strains 18081308 and 18083286 to obtain their whole genome sequence. Average nucleotide identity (ANI) was used for their precise species identification. Serotyping and multilocus sequence typing were performed. Furthermore, the acquired drug resistance genes of these strains were identified. The carbapenem-resistant P. aeruginosa strains isolated in the present study were of sequence type ST865 and serotype O6. They all carried the same resistance genes (aacC2, tmrB, and blaIMP-1). Tn6411, a Tn7-like transposon carrying blaIMP-1, was found in strain 18083286 by single molecule real time (SMRT) sequencing. We also identified the presence of this transposon sequence in other chromosomes of P. aeruginosa and plasmids carried by Acinetobacter spp. in GenBank, indicating the necessity for heightening attention to the potential transferability of this transposon.

Circulating tumor extracellular vesicles to monitor metastatic prostate cancer genomics and transcriptomic evolution.

Extracellular vesicles (EVs) secreted by tumors are abundant in plasma, but their potential for interrogating the molecular features of tumors through multi-omic profiling remains widely unexplored. Genomic and transcriptomic profiling of circulating EV-DNA and EV-RNA isolated from in vitro and in vivo models of metastatic prostate cancer (mPC) reveal a high contribution of tumor material to EV-loaded DNA/RNA, validating the findings in two cohorts of longitudinal plasma samples collected from patients during androgen receptor signaling inhibitor (ARSI) or taxane-based therapy. EV-DNA genomic features recapitulate matched-patient biopsies and circulating tumor DNA (ctDNA) and associate with clinical progression. We develop a novel approach to enable transcriptomic profiling of EV-RNA (RExCuE). We report how the transcriptome of circulating EVs is enriched for tumor-associated transcripts, captures certain patient and tumor features, and reflects on-therapy tumor adaptation changes. Altogether, we show that EV profiling enables longitudinal transcriptomic and genomic profiling of mPC in liquid biopsy.

Unraveling genomic features and phylogenomics through the analysis of three Mexican endemic Myotis genomes.

Background: Genomic resource development for non-model organisms is rapidly progressing, seeking to uncover molecular mechanisms and evolutionary adaptations enabling thriving in diverse environments. Limited genomic data for bat species hinder insights into their evolutionary processes, particularly within the diverse Myotis genus of the Vespertilionidae family. In Mexico, 15 Myotis species exist, with three-M. vivesi, M. findleyi, and M. planiceps-being endemic and of conservation concern. Methods: We obtained samples of Myotis vivesi, M. findleyi, and M. planiceps for genomic analysis. Each of three genomic DNA was extracted, sequenced, and assembled. The scaffolding was carried out utilizing the M. yumanensis genome via a genome-referenced approach within the ntJoin program. GapCloser was employed to fill gaps. Repeat elements were characterized, and gene prediction was done via ab initio and homology methods with MAKER pipeline. Functional annotation involved InterproScan, BLASTp, and KEGG. Non-coding RNAs were annotated with INFERNAL, and tRNAscan-SE. Orthologous genes were clustered using Orthofinder, and a phylogenomic tree was reconstructed using IQ-TREE. Results: We present genome assemblies of these endemic species using Illumina NovaSeq 6000, each exceeding 2.0 Gb, with over 90% representing single-copy genes according to BUSCO analyses. Transposable elements, including LINEs and SINEs, constitute over 30% of each genome. Helitrons, consistent with Vespertilionids, were identified. Values around 20,000 genes from each of the three assemblies were derived from gene annotation and their correlation with specific functions. Comparative analysis of orthologs among eight Myotis species revealed 20,820 groups, with 4,789 being single copy orthogroups. Non-coding RNA elements were annotated. Phylogenomic tree analysis supported evolutionary chiropterans' relationships. These resources contribute significantly to understanding gene evolution, diversification patterns, and aiding conservation efforts for these endangered bat species.

Exploring the cobia (Rachycentron canadum) genome: unveiling putative male heterogametic regions and identification of sex-specific markers.

BACKGROUND: Cobia (Rachycentron canadum) is the only member of the Rachycentridae family and exhibits considerable sexual dimorphism in growth rate. Sex determination in teleosts has been a long-standing basic biological question, and the molecular mechanisms of sex determination/differentiation in cobia are completely unknown. RESULTS: Here, we reported 2 high-quality, chromosome-level annotated male and female cobia genomes with assembly sizes of 586.51 Mb (contig/scaffold N50: 86.0 kb/24.3 Mb) and 583.88 Mb (79.9 kb/22.5 Mb), respectively. Synteny inference among perciform genomes revealed that cobia and the remora Echeneis naucrates were sister groups. Further, whole-genome resequencing of 31 males and 60 females, genome-wide association study, and sequencing depth analysis identified 3 short male-specific regions within a 10.7-kb continuous genomic region on male chromosome 18, which hinted at an undifferentiated sex chromosome system with a putative XX/XY mode of sex determination in cobia. Importantly, the only 2 genes within/between the male-specific regions, epoxide hydrolase 1 (ephx1, renamed cephx1y) and transcription factor 24 (tcf24, renamed ctcf24y), showed testis-specific/biased gene expression, whereas their counterparts cephx1x and ctf24x, located in female chromosome 18, were similarly expressed in both sexes. In addition, male-specific PCR targeting the cephx1y gene revealed that this genomic feature is conserved in cobia populations from Panama, Brazil, Australia, and Japan. CONCLUSION: The first comprehensive genomic survey presented here is a valuable resource for future studies on cobia population structure and dynamics, conservation, and evolutionary history. Furthermore, it establishes evidence of putative male heterogametic regions with 2 genes playing a potential role in the sex determination of the species, and it provides further support for the rapid evolution of sex-determining mechanisms in teleost fish.

Comparative genomic analysis and optimization of astaxanthin production of Rhodotorula paludigena TL35-5 and Rhodotorula sampaioana PL61-2.

Astaxanthin is a powerful antioxidant known to enhance skin, cardiovascular, eye, and brain health. In this study, the genome insights and astaxanthin production of two newly isolated astaxanthin-producing yeasts (TL35-5 and PL61-2) were evaluated and compared. Based on their phenotypic and genotypic characteristics, TL35-5 and PL61-2 were identified as basidiomycetous yeasts belonging to Rhodotorula paludigena and Rhodotorula sampaioana, respectively. To optimize astaxanthin production, the effects of cultural medium composition and cultivation conditions were examined. The optimal conditions for astaxanthin production in R. paludigena TL35-5 involved cultivation in AP medium containing 10 g/L glucose as the sole carbon source, supplemented with 1.92 g/L potassium nitrate, pH 6.5, and incubation at 20°C for 3 days with shaking at 200 rpm. For R. sampaioana PL61-2, the optimal medium composition for astaxanthin production consisted of AP medium with 40 g/L glucose, supplemented with 0.67 g/L urea, pH 7.5, and the fermentation was carried out at 20°C for 3 days with agitating at 200 rpm. Under their optimal conditions, R. paludigena TL35-5 and R. sampaioana PL61-2 gave the highest astaxanthin yields of 3.689 ± 0.031 and 4.680 ± 0.019 mg/L, respectively. The genome of TL35-5 was 20,982,417 bp in length, with a GC content of 64.20%. A total of 6,789 protein-encoding genes were predicted. Similarly, the genome of PL61-2 was 21,374,169 bp long, with a GC content of 64.88%. It contained 6,802 predicted protein-encoding genes. Furthermore, all essential genes involved in astaxanthin biosynthesis, including CrtE, CrtYB, CrtI, CrtS, and CrtR, were identified in both R. paludigena TL35-5 and R. sampaioana PL61-2, providing evidence for their ability to produce astaxanthin.

Genomic and Epigenomic Biomarkers of Immune Checkpoint Immunotherapy Response in Melanoma: Current and Future Perspectives.

Immune checkpoint inhibitors (ICIs) demonstrate durable responses, long-term survival benefits, and improved outcomes in cancer patients compared to chemotherapy. However, the majority of cancer patients do not respond to ICIs, and a high proportion of those patients who do respond to ICI therapy develop innate or acquired resistance to ICIs, limiting their clinical utility. The most studied predictive tissue biomarkers for ICI response are PD-L1 immunohistochemical expression, DNA mismatch repair deficiency, and tumour mutation burden, although these are weak predictors of ICI response. The identification of better predictive biomarkers remains an important goal to improve the identification of patients who would benefit from ICIs. Here, we review established and emerging biomarkers of ICI response, focusing on epigenomic and genomic alterations in cancer patients, which have the potential to help guide single-agent ICI immunotherapy or ICI immunotherapy in combination with other ICI immunotherapies or agents. We briefly review the current status of ICI response biomarkers, including investigational biomarkers, and we present insights into several emerging and promising epigenomic biomarker candidates, including current knowledge gaps in the context of ICI immunotherapy response in melanoma patients.

De Novo Hybrid Assembly Unveils Multi-Chromosomal Mitochondrial Genomes in Ludwigia Species, Highlighting Genomic Recombination, Gene Transfer, and RNA Editing Events.

Biological invasions have been identified as the fifth cause of biodiversity loss, and their subsequent dispersal represents a major ecological challenge. The aquatic invasive species Ludwigia grandiflora subsp. hexapetala (Lgh) and Ludwigia peploides subsp. montevidensis (Lpm) are largely distributed in aquatic environments in North America and in Europe. However, they also present worrying terrestrial forms that are able to colonize wet meadows. To comprehend the mechanisms of the terrestrial adaptation of Lgh and Lpm, it is necessary to develop their genomic resources, which are currently poorly documented. We performed de novo assembly of the mitogenomes of Lgh and Lpm through hybrid assemblies, combining short reads (SR) and/or long reads (LR) before annotating both mitogenomes. We successfully assembled the mitogenomes of Lgh and Lpm into two circular molecules each, resulting in a combined total length of 711,578 bp and 722,518 bp, respectively. Notably, both the Lgh and Lpm molecules contained plastome-origin sequences, comprising 7.8% of the mitochondrial genome length. Additionally, we identified recombinations that were mediated by large repeats, suggesting the presence of multiple alternative conformations. In conclusion, our study presents the first high-quality mitogenomes of Lpm and Lgh, which are the only ones in the Myrtales order found as two circular molecules.

Exploring Molecular Mechanisms and Biomarkers in COPD: An Overview of Current Advancements and Perspectives.

Chronic obstructive pulmonary disease (COPD) plays a significant role in global morbidity and mortality rates, typified by progressive airflow restriction and lingering respiratory symptoms. Recent explorations in molecular biology have illuminated the complex mechanisms underpinning COPD pathogenesis, providing critical insights into disease progression, exacerbations, and potential therapeutic interventions. This review delivers a thorough examination of the latest progress in molecular research related to COPD, involving fundamental molecular pathways, biomarkers, therapeutic targets, and cutting-edge technologies. Key areas of focus include the roles of inflammation, oxidative stress, and protease-antiprotease imbalances, alongside genetic and epigenetic factors contributing to COPD susceptibility and heterogeneity. Additionally, advancements in omics technologies-such as genomics, transcriptomics, proteomics, and metabolomics-offer new avenues for comprehensive molecular profiling, aiding in the discovery of novel biomarkers and therapeutic targets. Comprehending the molecular foundation of COPD carries substantial potential for the creation of tailored treatment strategies and the enhancement of patient outcomes. By integrating molecular insights into clinical practice, there is a promising pathway towards personalized medicine approaches that can improve the diagnosis, treatment, and overall management of COPD, ultimately reducing its global burden.

Functional Genomics in Psoriasis.

Psoriasis is an autoimmune cutaneous condition that significantly impacts quality of life and represents a burden on society due to its prevalence. Genome-wide association studies (GWASs) have pinpointed several psoriasis-related risk loci, underlining the disease's complexity. Functional genomics is paramount to unveiling the role of such loci in psoriasis and disentangling its complex nature. In this review, we aim to elucidate the main findings in this field and integrate our discussion with gold-standard techniques in molecular biology-i.e., Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-and high-throughput technologies. These tools are vital to understanding how disease risk loci affect gene expression in psoriasis, which is crucial in identifying new targets for personalized treatments in advanced precision medicine.