Genomic Analysis Research Articles

Exploring microbial diversity in the rhizosphere: a comprehensive review of metagenomic approaches and their applications.

The rhizosphere, the soil region influenced by plant roots, represents a dynamic microenvironment where intricate interactions between plants and microorganisms shape soil health, nutrient cycling, and plant growth. Soil microorganisms are integral players in the transformation of materials, the dynamics of energy flows, and the intricate cycles of biogeochemistry. Considerable research has been dedicated to investigating the abundance, diversity, and intricacies of interactions among different microbes, as well as the relationships between plants and microbes present in the rhizosphere. Metagenomics, a powerful suite of techniques, has emerged as a transformative tool for dissecting the genetic repertoire of complex microbial communities inhabiting the rhizosphere. The review systematically navigates through various metagenomic approaches, ranging from shotgun metagenomics, enabling unbiased analysis of entire microbial genomes, to targeted sequencing of the 16S rRNA gene for taxonomic profiling. Each approach's strengths and limitations are critically evaluated, providing researchers with a nuanced understanding of their applicability in different research contexts. A central focus of the review lies in the practical applications of rhizosphere metagenomics in various fields including agriculture. By decoding the genomic content of rhizospheric microbes, researchers gain insights into their functional roles in nutrient acquisition, disease suppression, and overall plant health. The review also addresses the broader implications of metagenomic studies in advancing our understanding of microbial diversity and community dynamics in the rhizosphere. It serves as a comprehensive guide for researchers, agronomists, and policymakers, offering a roadmap for harnessing metagenomic approaches to unlock the full potential of the rhizosphere microbiome in promoting sustainable agriculture.

Research on the Regulatory Mechanism of Ginseng on the Tumor Microenvironment of Colorectal Cancer based on Network Pharmacology and Bioinformatics Validation.

A network pharmacology study on the biological action of ginseng in the treatment of colorectal cancer (CRC) by regulating the tumor microenvironment (TME). To investigate the potential mechanism of action of ginseng in the treatment of CRC by regulating TME. This research employed network pharmacology, molecular docking techniques, and bioinformatics validation. Firstly, the active ingredients and the corresponding targets of ginseng were retrieved using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), the Traditional Chinese Medicine Integrated Database (TCMID), and the Traditional Chinese Medicine Database@Taiwan (TCM Database@Taiwan). Secondly, the targets related to CRC were retrieved using Genecards, Therapeutic Target Database (TTD), and Online Mendelian Inheritance in Man (OMIM). Tertiary, the targets related to TME were derived from screening the GeneCards and National Center for Biotechnology Information (NCBI)-Gene. Then the common targets of ginseng, CRC, and TME were obtained by Venn diagram. Afterward, the Protein-protein interaction (PPI) network was constructed in the STRING 11.5 database, intersecting targets identified by PPI analysis were introduced into Cytoscape 3.8.2 software cytoHubba plugin, and the final determination of core targets was based on degree value. The OmicShare Tools platform was used to analyze the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the core targets. Autodock and PyMOL were used for molecular docking verification and visual data analysis of docking results. Finally, we verified the core targets by Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases in bioinformatics. A total of 22 active ingredients and 202 targets were identified to be closely related to the TME of CRC. PPI network mapping identified SRC, STAT3, PIK3R1, HSP90AA1, and AKT1 as possible core targets. Go enrichment analysis showed that it was mainly involved in T cell co-stimulation, lymphocyte co-stimulation, growth hormone response, protein input, and other biological processes; KEGG pathway analysis found 123 related signal pathways, including EGFR tyrosine kinase inhibitor resistance, chemokine signaling pathway, VEGF signaling pathway, ErbB signaling pathway, PD-L1 expression and PD-1 checkpoint pathway in cancer, etc. The molecular docking results showed that the main chemical components of ginseng have a stable binding activity to the core targets. The results of the GEPIA database showed that the mRNA levels of PIK3R1 were significantly lowly expressed and HSP90AA1 was significantly highly expressed in CRC tissues. Analysis of the relationship between core target mRNA levels and the pathological stage of CRC showed that the levels of SRC changed significantly with the pathological stage. The HPA database results showed that the expression levels of SRC were increased in CRC tissues, while the expression of STAT3, PIK3R1, HSP90AA1, and AKT1 were decreased in CRC tissues. Ginseng may act on SRC, STAT3, PIK3R1, HSP90AA1, and AKT1 to regulate T cell costimulation, lymphocyte costimulation, growth hormone response, protein input as a molecular mechanism regulating TME for CRC. It reflects the multi-target and multi-pathway role of ginseng in modulating TME for CRC, which provides new ideas to further reveal its pharmacological basis, mechanism of action and new drug design and development.

A Blueberry (Vaccinium L.) Crop Ontology to Enable Standardized Phenotyping for Blueberry Breeding and Research

Breeding programs around the world continually collect data on large numbers of individuals. To be able to combine data collected across regions, years, and experiments, research communities develop standard operating procedures for data collection and measurement. One such method is a crop ontology, or a standardized vocabulary for collecting data on commonly measured traits. The ontology is also computer readable to facilitate the use of data management systems such as databases. Blueberry breeders and researchers across the United States have come together to develop the first standardized crop ontology in blueberry (Vaccinium spp.). We provide an overview and report on the construction of the first blueberry crop ontology and the 178 traits and methods included within. Researchers of Vaccinium species—such as other blueberry species, cranberry, lingonberry, and bilberry—can use the described crop ontology to collect phenotypic data of greater quality and consistency, interoperability, and computer readability. Crop ontologies, as a shared data language, benefit the entire worldwide research community by enabling collaborative meta-analyses that can be used with genomic data for quantitative trait loci, genome-wide association studies, and genomic selection analysis.

A consequential one-night stand: Episodic historical hybridization leads to mitochondrial takeover in sympatric desert ant-eating spiders

Disentangling the genomic intricacies underlying speciation and the causes of discordance between sources of evidence can offer remarkable insights into evolutionary dynamics. The ant-eating spider Zodarion nitidum, found across the Middle East and Egypt, displays yellowish and blackish morphs that co-occur sympatrically. These morphs additionally differ in behavioral and physiological features and show complete pre-mating reproductive isolation. In contrast, they possess similar sexual features and lack distinct differences in their mitochondrial DNA. We analyzed both Z. nitidum morphs and outgroups using genome-wide and additional mitochondrial DNA data. The genomic evidence indicated that Yellow and Black are reciprocally independent lineages without signs of recent admixture. Interestingly, the sister group of Yellow is not Black but Z. luctuosum, a morphologically distinct species. Genomic gene flow analyses pinpointed an asymmetric nuclear introgression event, with Yellow contributing nearly 5 % of its genome to Black roughly 320,000 years ago, intriguingly aligning with the independently estimated origin of the mitochondrial DNA of Black. We conclude that the blackish and yellowish morphs of Z. nitidum are long-diverged distinct species, and that the ancient and modest genomic introgression event registered resulted in a complete mitochondrial takeover of Black by Yellow. This investigation underscores the profound long-term effects that even modest hybridization events can have on the genome of organisms. It also exemplifies the utility of phylogenetic networks for estimating historical events and how integrating independent lines of evidence can increase the reliability of such estimations.

N6‑methyladenosine methyltransferase METTL14 is associated with macrophage polarization in rheumatoid arthritis.

Rheumatoid arthritis (RA) is largely caused by the inflammatory response triggered by macrophage polarization. Through epigenetic reprogramming, the inflammatory state of macrophages can be modified. Macrophage polarization is associated with the RNA epigenetic alteration N6-methyladenosine (m6A) RNA methylation. However, the specific function and underlying mechanisms of m6A methylation in the role of macrophage polarization in RA remain to be elucidated. The mRNA expression levels of m6A methylase genes and signaling pathway components associated with RA macrophages were determined in the present study using reverse-transcription quantitative PCR. Methyltransferase 14 (METTL14) protein expression levels were determined using western blot analysis, and the levels of specific cellular secretion factors were determined using ELISA and flow cytometry. The results of the present study demonstrated that elevated METTL14 expression was associated with joint tenderness, and METTL14 expression was positively correlated with both C-reactive protein and rheumatoid factor expression levels. Moreover, METTL14 exhibited potential in the prediction of visual analogue scale. Pro-inflammatory cytokines (TNF-α) and M1 macrophage markers (CD68+CD86+) were also positively associated with METTL14 expression. The results of the Kyoto Encyclopedia of Genes and Genomes analysis revealed that METTL14 was strongly associated with the MAPK signaling pathway. Notably, JNK and ERK2 exhibited a positive correlation with the M1 macrophage marker, CD68+CD86+, which was positively associated with the pro-inflammatory factor, TNF-α. JNK and ERK2 expression levels were markedly increased in the METTL14 high-expression group, compared with in the low-expression group; however, p38 and ERK1 expression levels were not significantly different between these groups. Collectively, the results of the present study demonstrated that METTL14 expression was significantly increased in the peripheral blood and synovial tissue of patients with RA, highlighting the potential association with both immunoinflammatory markers and clinical symptoms. In addition, it was suggested that METTL14 may exacerbate the downstream inflammatory response, through mediating macrophage polarization via the MAPK pathway.

Whole genome sequence and comparative genomic analysis of novel Rickettsia koreansis strain CNH17-7 isolated from human.

To determine the genomic feature of novel spotted fever-causing Rickettsia koreansis strain CNH17-7, which is different from R. japonica that is a causative agent for Japanese spotted fever (JSF), and to perform its comparative genomic analysis. Whole genome sequencing (WGS) was performed on R. koreansis strain CNH17-7 by using the Illumina Miseq system. After WGS, assembly and annotation were done by SPAdes. Then, its genomic features were compared with 19 different Rickettsia species. Based on the average nucleotide identity (ANI) value, an unweighted pair group method with an arithmetic mean (UPGMA) dendrogram was generated. Following the dendrogram analysis, pan-and core-genome analysis was performed. Then additional comparative analyses with two genetically closest Rickettsia species were conducted based on gene repertoire. R. koreansis strain CNH17-7 has a chromosome consisting of 1,392,633bp with GC content of 32.4%. The ANI-derived UPGMA showed that R. koreansis strain CNH17-7 is genetically close to R. japonica YH and R. heilongjiangensis 054 but is distinctively differentiated. The ANI value of R. koreansis strain CNH17-7 to R. japonica YH and R. heilongjiangensis 054 are 98.14% and 98.04% respectively, indicating R. koreansis strain CNH17-7 is sufficient to be classified as a new species. Other than ANI, R. koreansis strain CNH17-7 also contains novel CDS and its COG functional category proportion which is distinct compared to R. japonica YH and R. heilongjiangensis 054. We have revealed genomic features of the novel R. koreansis strain CNH17-7. Hence, we propose R. koreansis strain CNH17-7 as new Rickettsia species.

Genomic analysis and mechanisms exploration of a stress tolerance and high-yield pullulan producing strain

Genomic analysis and mechanisms exploration of a stress tolerance and high-yield pullulan producing strain

Miniaturized protein profiling permits targeted signaling pathway analysis in individual circulating tumor cells to improve personalized treatment

BackgroundTraditional genomic profiling and mutation analysis of single cells like Circulating Tumor Cells (CTCs) fails to capture post-translational and functional alterations of proteins, often leading to limited treatment efficacy. To overcome this gap, we developed a miniaturized ‘protein analysis on the single cell level’ workflow—baptized ZeptoCTC. It integrates established technologies for single-cell isolation with sensitive Reverse Phase Protein Array (RPPA) analysis, thus enabling the comprehensive assessment of multiple protein expression and activation in individual CTCs.MethodsThe ZeptoCTC workflow involves several critical steps. Firstly, individual cells are labeled and isolated. This is followed by cell lysis and the printing of true single cell lysate preparations onto a ZeptoChip using a modified micromanipulator, CellCelector™. The printed lysates then undergo fluorescence immunoassay RPPA protein detection using a ZeptoReader. Finally, signal quantification is carried out with Image J software, ensuring precise measurement of multiple protein levels.ResultsThe efficacy of ZeptoCTC was demonstrated through various applications. Initially, it was used for measuring EpCAM protein expression, a standard marker for CTC detection, revealing higher levels in single MCF-7 over MDA-MB-231 tumor cells. Furthermore, in Capivasertib (Akt-inhibitor)-treated MCF-7 single cells, ZeptoCTC detected a 2-fold increase in the pAkt/Akt ratio compared to control cells, and confirmed co-performed bulk-cell western blot analysis results. Notably, when applied to individual CTCs from metastasized breast cancer patients, ZeptoCTC revealed significant differences in protein activation levels, particularly in measured pAkt and pErk levels, compared to patient-matched WBCs. Moreover, it successfully differentiated between CTCs from patients with different Akt1 genotypes, highlighting its potential to determine the activation status of druggable cancer driving proteins for individual and targeted treatment decision making.ConclusionsThe ZeptoCTC workflow represents a valuable tool in single cell cancer research, crucial for personalized medicine. It permits detailed analysis of key proteins and their activation status of targeted, cancer-driven signaling pathways in single cell samples, aiding in understanding tumor response, progression, and treatment efficacy beyond bulk analysis. The method significantly advances clinical investigations in cancer, improving treatment precision and effectiveness. The workflow will be applicable to protein analysis on other types of single cells like relevant in stem cell, neuropathology and hemopoietic cell research.

What makes Candida auris pan-drug resistant? Integrative insights from genomic, transcriptomic, and phenomic analysis of clinical strains resistant to all four major classes of antifungal drugs

ABSTRACT The global epidemic of drug-resistant Candida auris continues unabated. The initial report on pan-drug resistant (PDR) C. auris strains in a hospitalized patient in New York was unprecedented. PDR C. auris showed both known and unique mutations in the prominent gene targets of azoles, amphotericin B, echinocandins, and flucytosine. However, the factors that allow C. auris to acquire pan-drug resistance are not known. Therefore, we conducted a genomic, transcriptomic, and phenomic analysis to better understand PDR C. auris . Among 1,570 genetic variants in drug-resistant C. auris , 299 were unique to PDR strains. The whole-genome sequencing results suggested perturbations in genes associated with nucleotide biosynthesis, mRNA processing, and nuclear export of mRNA. Whole transcriptome sequencing of PDR C. auris revealed two genes to be significantly differentially expressed—a DNA repair protein and DNA replication-dependent chromatin assembly factor 1. Of 59 novel transcripts, 12 transcripts had no known homology. We observed no fitness defects among multi-drug resistant (MDR) and PDR C. auris strains grown in nutrient-deficient or -enriched media at different temperatures. Phenotypic profiling revealed wider adaptability to nitrogenous nutrients and increased utilization of substrates critical in upper glycolysis and tricarboxylic acid cycle. Structural modeling of a 33-amino acid deletion in the gene for uracil phosphoribosyl transferase suggested an alternate route in C. auris to generate uracil monophosphate that does not accommodate 5-fluorouracil as a substrate. Overall, we find evidence of metabolic adaptations in MDR and PDR C. auris in response to antifungal drug lethality without deleterious fitness costs.

Effects of generational low dose-rate 137Cs internal exposure in descendant mice

To quantitatively investigate the effects of chronic low-dose internal exposure to Cesium-137 on DNA damage, carcinogenicity, and offspring over multiple generations. The potential genetic risk in humans was predicted based on next-generation murine mutation rates to confirm the reasonableness of the current Cesium-137 dose limits for food. Cesium-137 (100 Bq/mL) was provided in drinking water to A/J mice, facilitating chronic, low-dose, low-dose-rate internal exposure through sibling mating over 25 generations (G25). The A/J mice were compared with a control strain with the same origin ancestry (no Cesium-137 water) for DNA double-strand breaks (DSBs), oxidative stress, chromosome aberrations, micronucleus test results, whole genome analysis, carcinogenicity, tumor growth rate, and immune competence. Compared to the control group, DNA DSBs and oxidative stress were significantly increased in the Cesium-137 group. However, no significant differences were observed between the groups regarding chromosome aberration, micronuclei, or the whole genome sequence mutation analysis. Although the carcinogenic rate did not differ between the groups, the rate of tumor growth was significantly suppressed in the Cesium-137 group. The anti-tumor cytokine trend in the Cesium-137 group likely contributed to this effect. No pathological or genetic effects were observed in the offspring of mice drinking water containing 100 Bq/mL Cesium-137 after G25. The contribution of low dose-rate radiation to carcinogenicity was not additive but growth-inhibitory. Although the negative data are not conclusive, these findings are deemed highly reliable.

A comparative analysis of planarian genomes reveals regulatory conservation in the face of rapid structural divergence

The planarian Schmidtea mediterranea is being studied as a model species for regeneration, but the assembly of planarian genomes remains challenging. Here, we report a high-quality haplotype-phased, chromosome-scale genome assembly of the sexual S2 strain of S. mediterranea and high-quality chromosome-scale assemblies of its three close relatives, S. polychroa, S. nova, and S. lugubris. Using hybrid gene annotations and optimized ATAC-seq and ChIP-seq protocols for regulatory element annotation, we provide valuable genome resources for the planarian research community and a first comparative perspective on planarian genome evolution. Our analyses reveal substantial divergence in protein-coding sequences and regulatory regions but considerable conservation within promoter and enhancer annotations. We also find frequent retrotransposon-associated chromosomal inversions and interchromosomal translocations within the genus Schmidtea and, remarkably, independent and nearly complete losses of ancestral metazoan synteny in Schmidtea and two other flatworm groups. Overall, our results suggest that platyhelminth genomes can evolve without syntenic constraints.

Characterization of the complete mitogenome of Tiarella polyphylla, commonly known as Asian foamflower: insights into the multi-chromosomes structure and DNA transfers

BackgroundTiarella polyphylla D. Don has been traditionally used to cure asthma and skin eruptions. However, the sequence and the structure of the mitogenome of T. polyphylla remained elusive, limiting the genomic and evolution analysis based on the mitogenome.ResultsUsing a combination of Illumina and Nanopore sequencing reads, we de novo assembled the complete mitogenome of T. polyphylla. In addition to unveiling the major configuration of the T. polyphylla mitogenome was three circular chromosomes with lengths of 430,435 bp, 126,943 bp, and 55,269 bp, we revealed five (R01-R05) and one (R06) repetitive sequence could mediate the intra- and inter-chromosomal recombination, respectively. Furthermore, we identified 208 short and 25 long tandem segments, seven cp-derived mtDNAs, 106 segments of mtDNAs transferred to the nuclear genome, and 653 predicted RNA editing sites. Based on the sequence of the mitogenomes, we obtained the resolved phylogeny of the seven Saxifragales species.ConclusionsThese results presented the mitogenome features and expanded its potential applications in phylogenetics, species identification, and cytoplasmic male sterility (CMS) in the future.

Frequent CHD1 deletions in prostate cancers of African American men is associated with rapid disease progression

We analyzed genomic data from the prostate cancer of African- and European American men to identify differences contributing to racial disparity of outcome. We also performed FISH-based studies of Chromodomain helicase DNA-binding protein 1 (CHD1) loss on prostate cancer tissue microarrays. We created CHD1-deficient prostate cancer cell lines for genomic, drug sensitivity and functional homologous recombination (HR) activity analysis. Subclonal deletion of CHD1 was nearly three times as frequent in prostate tumors of African American than in European American men and it associates with rapid disease progression. CHD1 deletion was not associated with HR deficiency associated mutational signatures or HR deficiency as detected by RAD51 foci formation. This was consistent with the moderate increase of olaparib and talazoparib sensitivity with several CHD1 deficient cell lines showing talazoparib sensitivity in the clinically relevant concentration range. CHD1 loss may contribute to worse disease outcome in African American men.

Trait-based study predicts glycerol/diol dehydratases as a key function of the gut microbiota of hindgut-fermenting carnivores

BackgroundMicrobial pdu and cob-cbi-hem gene clusters encode the key enzyme glycerol/diol dehydratase (PduCDE), which mediates the transformation of dietary nutrients glycerol and 1,2-propanediol (1,2-PD) to a variety of metabolites, and enzymes for cobalamin synthesis, a co-factor and shared good of microbial communities. It was the aim of this study to relate pdu as a multipurpose functional trait to environmental conditions and microbial community composition. We collected fecal samples from wild animal species living in captivity with different gut physiology and diet (n = 55, in total 104 samples), determined occurrence and diversity of pdu and cob-cbi-hem using a novel approach combining metagenomics with quantification of metabolic and genetic biomarkers, and conducted in vitro fermentations to test for trait-based activity.ResultsFecal levels of the glycerol transformation product 1,3-propanediol (1,3-PD) were higher in hindgut than foregut fermenters. Gene-based analyses indicated that pduC harboring taxa are common feature of captive wild animal fecal microbiota that occur more frequently and at higher abundance in hindgut fermenters. Phylogenetic analysis of genomes reconstructed from metagenomic sequences identified captive wild animal fecal microbiota as taxonomically rich with a total of 4150 species and > 1800 novel species but pointed at only 56 species that at least partially harbored pdu and cbi-cob-hem. While taxonomic diversity was highest in fecal samples of foregut-fermenting herbivores, higher pduC abundance and higher diversity of pdu/cbi-cob-hem related to higher potential for glycerol and 1,2-PD utilization of the less diverse microbiota of hindgut-fermenting carnivores in vitro.ConclusionOur approach combining metabolite and gene biomarker analysis with metagenomics and phenotypic characterization identified Pdu as a common function of fecal microbiota of captive wild animals shared by few taxa and stratified the potential of fecal microbiota for glycerol/1,2-PD utilization and cobalamin synthesis depending on diet and physiology of the host. This trait-based study suggests that the ability to utilize glycerol/1,2-PD is a key function of hindgut-fermenting carnivores, which does not relate to overall community diversity but links to the potential for cobalamin formation.5QUW1NVLR3PN1Ur7W1hKTuVideo

Whole genome sequences of 135 “Candidatus Liberibacter asiaticus” strains from China

“Candidatus Liberibacter asiaticus” (CLas) is a phloem-limited alpha-proteobacteria causing Citrus Huanglongbing, the destructive disease currently threatening global citrus industry. Genomic analyses of CLas provide insights into its evolution and biology. Here, we sequenced and assembled whole genomes of 135 CLas strains originally from 20 citrus cultivars collected at ten citrus-growing provinces in China. The resulting dataset comprised 135 CLas genomes ranging from 1,221,309 bp to 1,308,521 bp, with an average coverage of 675X. Prophage typing showed that 44 strains contained Type 1 prophage, 89 strains contained Type 2 prophage, 44 strains contained Type 3 prophage, and 34 of them contained more than one type of prophage/phage. The SNP calling identified a total of 5,090 SNPs. Genome-based phylogenetic analysis revealed two major clades among CLas strains, with Clade I dominated by CLas strains containing Type 1 prophage (79/95) and Clade II dominated by CLas strains containing Type 1 or Type 3 prophage (80/95). This CLas genome dataset provides valuable resources for studying genetic diversity and evolutionary pattern of CLas strains.

Comparative Genomics Analysis of the Populus Epidermal Pattern Factor (EPF) Family Revealed Their Regulatory Effects in Populus euphratica Stomatal Development

Drought stress seriously threatens plant growth. The improvement of plant water use efficiency (WUE) and drought tolerance through stomatal regulation is an effective strategy for coping with water shortages. Epidermal patterning factor (EPF)/EPF-like (EPFL) family proteins regulate stomatal formation and development in plants and thus contribute to plant stress adaptation. Here, our analysis revealed the presence of 14 PeEPF members in the Populus euphratica genome, which exhibited a relatively conserved gene structure with 1–3 introns. Subcellular localisation prediction revealed that 9 PeEPF members were distributed in the chloroplasts of P. euphratica, and 5 were located extracellularly. Phylogenetic analysis indicated that PeEPFs can be divided into three clades, with genes within the same clade revealing a relatively conserved structure. Furthermore, we observed the evolutionary conservation of PeEPFs and AtEPF/EPFLs in certain domains, which suggests their conserved function. The analysis of cis-acting elements suggested the possible involvement of PeEPFs in plant response to multiple hormones. Transcriptomic analysis revealed considerable changes in the expression level of PeEPFs during treatment with polyethylene glycol and abscisic acid. The overexpression of PeEPF2 resulted in low stomatal density in transgenetic lines. These findings provide a basis for gaining insights into the function of PeEPFs in response to abiotic stress.

Genomic analysis of Brucella isolates from animals and humans, Türkiye, 2010 to 2020

Genomic analysis of Brucella isolates from animals and humans, Türkiye, 2010 to 2020

Artificial Intelligence in Cancer: A SWOT Analysis

Cancer, a collection of maladies that has undergone extensive examination over centuries, remains a formidable challenge. Despite the array of available pharmacological and therapeutic interventions, the intricate molecular dynamics and heterogeneity of cancer continue to challenge the scientific community. Artificial Intelligence (AI) emerges as a promising avenue, offering the potential for expedited, precise diagnostics devoid of human expertise. Additionally, AI facilitates the tailoring of patient-specific therapeutic strategies targeting various facets of cancer, spanning macroscopic to microscopic levels. Nonetheless, it is imperative to scrutinize the potential benefits and limitations of AI technologies in this context. This review undertakes a comprehensive Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis of AI's application in cancer. An extensive compilation of AI applications encompasses predictive modeling, diagnostic capabilities, prognostic assessments, and personalized therapeutic modalities, spanning genomic analyses to individualized treatment regimens. The synthesis of evidence suggests that the advantages of AI outweigh its drawbacks; nevertheless, obstacles to its widespread integration persist.

Generative Haplotype Prediction Outperforms Statistical Methods for Small Variant Detection in NGS Data

Abstract Motivation Detection of germline variants in next-generation sequencing data is an essential component of modern genomics analysis. Variant detection tools typically rely on statistical algorithms such as de Bruijn graphs or Hidden Markov Models, and are often coupled with heuristic techniques and thresholds to maximize accuracy. Despite significant progress in recent years, current methods still generate thousands of false positive detections in a typical human whole genome, creating a significant manual review burden. Results We introduce a new approach that replaces the handcrafted statistical techniques of previous methods with a single deep generative model. Using a standard transformer-based encoder and double-decoder architecture, our model learns to construct diploid germline haplotypes in a generative fashion identical to modern Large Language Models (LLMs). We train our model on 37 Whole Genome Sequences (WGS) from Genome-in-a-Bottle samples, and demonstrate that our method learns to produce accurate haplotypes with correct phase and genotype for all classes of small variants. We compare our method, called Jenever, to FreeBayes, GATK HaplotypeCaller, Clair3 and DeepVariant, and demonstrate that our method has superior overall accuracy compared to other methods. At F1-maximizing quality thresholds, our model delivers the highest sensitivity, precision, and the fewest genotyping errors for insertion and deletion variants. For single nucleotide variants our model demonstrates the highest sensitivity but at somewhat lower precision, and achieves the highest overall F1 score among all callers we tested. Availability and Implementation Jenever is implemented as a python-based command line tool. Source code is available at https://github.com/ARUP-NGS/jenever/

Genetic and genomic analysis of reproduction traits in holstein cattle using SNP chip data and imputed sequence level genotypes

BackgroundReproductive performance plays an important role in animal welfare, health and profitability in animal husbandry and breeding. It is well established that there is a negative correlation between performance and reproduction in dairy cattle. This relationship is being increasingly considered in breeding programs. By elucidating the genetic architecture of underlying reproduction traits, it will be possible to make a more detailed contribution to this. Our study followed two approaches to elucidate this area; in a first part, variance components were estimated for 14 different calving and fertility traits, and then genome-wide association studies were performed for 13 reproduction traits on imputed sequence-level genotypes with subsequent enrichment analyses.ResultsVariance components analyses showed a low to moderate heritability (h2) for the traits analysed, ranging from 0.014 for endometritis up to 0.271 for stillbirth, indicating variable degrees of variation within the reproduction traits. For genome-wide association studies, we were able to detect genome-wide significant association signals for nine out of 13 analysed traits after Bonferroni correction on chromosome 6, 18 and the X chromosome. In total, we detected over 2700 associated SNPs encircling more than 90 different genes using the imputed whole-genome sequence data. Functional associations were reviewed so far known and potential candidate regions in the proximity of reproduction events were hypothesised.ConclusionOur results confirm previous findings of other authors in a comprehensive cohort including 13 different traits at the same time. Additionally, we identified new candidate genes involved in dairy cattle reproduction and made initial suggestions regarding their potential impact, with special regard to the X chromosome as a putative information source for further research. This work can make a contribution to reveal the genetic architecture of reproduction traits in context of trait specific interactions.