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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2022

Genomic demography of world's ethnic groups and their genomic identity between two individuals

All current categorizations of human population, such as ethnicity, ancestry and race, are based on various selections and combinations of subjectively- and/or qualitatively-defined characteristics, such as ancestral lineage/location, cultural/societal norm, language, skin color and other phenotypes and traits perceived by the members within or from outside of the categorized group. Yet, such categorization has been broadly used also in the fields of human genetics, health sciences and medical practices (e.g., 1,2,3), where the observed health characteristics are objectively and quantitatively definable, but the population categorization is not yet available. Here we show the feasibility of deriving a whole-genome-based categorization that is objectively definable and quantitatively measurable. We observe that: (a) the worlds ethnic populations form about 14 genomic groups (GGs); (b) each GG consists of multiple ethnic groups (EGs); and (c) at an individual level, approximately 99.8%, on average, of the whole genome contents are identical between any two individuals regardless of their GGs or EGs.

evolutionary biology↗

bioRxiv2022

Whole genome sequencing of three mesorhizobia isolated from northern Canada to identify genomic adaptations promoting nodulation in cold climates

The N2-fixing symbiosis between rhizobia and legumes is negatively impacted by numerous stresses, including low temperatures. To identify genomic features and biochemical pathways of rhizobia that could foster improved symbiotic function under low temperatures, we isolated and characterized three Mesorhizobium strains from legume nodules collected at two distant northern Canadian sites. Whereas the classical determinants of nodulation and nitrogen fixation are located on the chromosome of most mesorhizobia, whole genome sequencing revealed that these genes are on a large symbiotic megaplasmid in all three of the newly isolated strains. A pangenome-wide association study identified 25 genes putatively associated with mesorhizobia isolated from arctic or subarctic environments, with the genomic location of many of these genes implying a relationship with legume symbiosis. Phylogenetic and sequence analyses of the common nodulation genes revealed alleles that are highly conserved amongst mesorhizobia isolated from northern climates but uncommon in mesorhizobia isolated from similar plant hosts in other climatic regions, suggesting potential functional adaptive differences and the horizontal transfer of these alleles between northern rhizobia. We speculate that nod sequence divergence was driven by climatic factors, and that the encoded proteins may be particularly stable and/or active at low temperatures.

microbiology↗

bioRxiv2022

Genomic Benchmarks: A Collection of Datasets for Genomic Sequence Classification

In this paper, we propose a collection of curated and easily accessible sequence classification datasets in the field of genomics. The proposed collection is based on a combination of novel datasets constructed from the mining of publicly available databases and existing datasets obtained from published articles. The main aim of this effort is to create a repository for shared datasets that will make machine learning for genomics more comparable and reproducible while reducing the over-head of researchers that want to enter the field. The collection currently contains eight datasets that focus on regulatory elements (promoters, enhancers, open chromatin region) from three model organisms: human, mouse, and roundworm. A simple convolution neural network is also included in a repository and can be used as a baseline model. Benchmarks and the baseline model are distributed as the Python package genomic-benchmarks, and the code is available at https://github.com/ML-Bioinfo-CEITEC/genomic_benchmarks.

bioinformatics↗

bioRxiv2022

Whole genome sequencing of a wild yam species Dioscorea tokoro reveals a genomic region associated with sex

Dioscorea tokoro is a wild species distributed in East Asia including Japan. Typical of the genus Dioscorea, D. tokoro is dioecious with male and female flowers borne on separate individuals. To understand its sex determination system and to serve as a model species for population genomics of obligate outcrossing wild species, we set out to determine the whole genome sequence of the species. Here we show 443 Mb genome sequence of D. tokoro distributed over 2,931 contigs that were anchored on 10 linkage groups. Linkage analysis of sex in a segregating F1 family revealed a sex determination locus residing on Pseudochromosome 3 with XY-type male heterogametic sex determination system.

plant biology↗

bioRxiv2022

Leveraging functional genomic annotations and genome coverage to improve polygenic prediction of complex traits within and between ancestries

We develop a new method, SBayesRC, that integrates GWAS summary statistics with functional genomic annotations to improve polygenic prediction of complex traits. Our method is scalable to whole-genome variant analysis and refines signals from functional annotations by allowing them to affect both causal variant probability and causal effect distribution. We analyse 28 traits in the UK Biobank using [~]7 million common SNPs and 96 annotations. SBayesRC improves prediction accuracy by 14% in European ancestry and by up to 33% in trans-ancestry prediction, compared to the baseline method SBayesR which does not use annotations, and outperforms state-of-the-art methods LDpred-funct, PolyPred-S and PRS-CSx by 12-15%. Investigation of factors affecting prediction accuracy identified a significant interaction between SNP density and annotation information, encouraging future use of whole-genome sequence variants for prediction. Functional partitioning analysis highlights a major contribution of evolutionary constrained regions to prediction accuracy and the largest per-SNP contribution from non-synonymous SNPs.

genetics↗

bioRxiv2022

Profiling of the β-glucosidases identified in the genome of Penicillium funiculosum: Insights from genomics, transcriptomics, proteomics and homology modelling studies

Enzymatic lignocellulosic biomass conversion to bioethanol is dependent on efficient enzyme systems with {beta}-glucosidase as a key component. In this study, we performed in-depth profiling of the various {beta}-glucosidases present in the genome of the hypercellulolytic fungus; Penicillium funiculosum using genomics, transcriptomics, proteomics and molecular dynamics simulation approaches. Of the eight {beta}-glucosidase genes identified in the P. funiculosum genome, three were found to be extracellular, as evidenced by presence of signal peptides and mass spectrometry. Among the three secreted {beta}-glucosidase, two belonged to the GH3 and one belonged to GH1 families. Modelled structures of these proteins predicted a deep and narrow active site for the GH3 {beta}-glucosidases (PfBgl3A and PfBgl3B) and a shallow open active site for the GH1 {beta}-glucosidase (PfBgl1A). The enzymatic assays indicated that P. funiculosum secretome showed high {beta}-glucosidase activities with prominent bands on 4-methylumbelliferyl {beta}-D-glucopyranoside (MUG) zymogram. To understand the contributory effect of each of the three secreted {beta}-glucosidases (PfBgls), the corresponding gene was deleted separately and the effect of the deletion on {beta}-glucosidase activity of the secretome was examined. Although not the most abundant {beta}-glucosidase, PfBgl3A was found to be the most significant one as evidenced by a 42 % reduction in {beta}-glucosidase activity in the {Delta}PfBgl3A strain. To improve the thermostability, two mutants of PfBgl3A were designed with the help of molecular dynamics (MD) simulation and were expressed in Pichia pastoris for evaluation. The PfBgl3A mutant (Mutant A) gave 1.4 fold increase in the half-life (T1/2) of the enzyme at 50{degrees}C. IMPORTANCECommercially available cellulases are majorly produced from Trichoderma reesei. However, external supplementation of the cellulase cocktail from this host with exogenous {beta}-glucosidase is often required to achieve desired optimal saccharification of cellulosic feedstocks. This challenge has led to exploration of other cellulase-producing strains because of the importance of this class of enzymes in the cellulose deconstruction machinery. The non-model hypercellulolytic fungus Penicillium funiculosum has been studied in recent times and identified as a promising source of industrial cellulases. Various genetic interventions targeted at strain improvement for cellulase production have been performed. However, the {beta}-glucosidases of this strain have remained largely understudied. This study, therefore, reports profiling of all the eight {beta}-glucosidases of P. funiculosum via molecular and computational approaches and enhancing thermostability of the most promising {beta}-glucosidase via protein engineering. The results of this study set the background for future engineering strategies to transform the fungus into an industrial workhorse.

microbiology↗

bioRxiv2022

Genomic Distance-based Rapid Uncovering of Microbial Population Structures (GRUMPS): a reference free genomic data cleaning methodology

Accurate datasets are crucial for rigorous large-scale sequence-based analyses such as those performed in phylogenomics and pangenomics. As the volume of available sequence data grows and the quality of these sequences varies, there is a pressing need for reliable methods to swiftly identify and eliminate low-quality and misidentified genomes from datasets prior to analysis. Here we introduce a robust, controlled, computationally efficient method for deriving species-level population structures of bacterial species, regardless of the dataset size. Additionally, our pipeline can classify genomes into their respective species at the genus level. By leveraging this methodology, researchers can rapidly clean datasets encompassing entire bacterial species and examine the sub-species population structures within the provided genomes. These cleaned datasets can subsequently undergo further refinement using a variety of methods to yield sequence sets with varying levels of diversity that faithfully represent entire species. Increasing the efficiency and accuracy of curation of species-level datasets not only enhances the reliability of downstream analyses, but also facilitates a deeper understanding of bacterial population dynamics and evolution.

bioinformatics↗

bioRxiv2023

Whole genome sequencing of Borrelia burgdorferi isolates reveals linked clusters of plasmid-borne accessory genome elements associated with virulence.

Lyme disease is the most common vector-borne disease in North America and Europe. The clinical manifestations of Lyme disease vary based on the genospecies of the infecting Borrelia burgdorferi spirochete, but the microbial genetic elements underlying these associations are not known. Here, we report the whole genome sequence (WGS) and analysis of 299 patient-derived B. burgdorferi sensu stricto (Bbss) isolates from patients in the Eastern and Midwestern US and Central Europe. We develop a WGS-based classification of Bbss isolates, confirm and extend the findings of previous single- and multi-locus typing systems, define the plasmid profiles of human-infectious Bbss isolates, annotate the core and strain-variable surface lipoproteome, and identify loci associated with disseminated infection. A core genome consisting of [~]800 open reading frames and a core set of plasmids consisting of lp17, lp25, lp36, lp28-3, lp28-4, lp54, and cp26 are found in nearly all isolates. Strain-variable (accessory) plasmids and genes correlate strongly with phylogeny. Using genetic association study methods, we identify an accessory genome signature associated with dissemination and define the individual plasmids and genes that make up this signature. Strains within the RST1/WGS A subgroup, particularly a subset marked by the OspC type A genotype, are associated with increased rates of dissemination. OspC type A strains possess a unique constellation of strongly linked genetic changes including the presence of lp56 and lp28-1 plasmids and a cluster of genes that may contribute to their enhanced virulence compared to other genotypes. The patterns of OspC type A strains typify a broader paradigm across Bbss isolates, in which genetic structure is defined by correlated groups of strain-variable genes located predominantly on plasmids, particularly for expression of surface-exposed lipoproteins. These clusters of genes are inherited in blocks through strain-specific patterns of plasmid occupancy and are associated with the probability of invasive infection.

microbiology↗

bioRxiv2023

Human antigen R differentially modulates the translation of SARS-CoV-2 genomic and sub-genomic RNAs

Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) viral RNA associates with different RNA-binding host proteins at each stage of its life cycle. We found sequence dependent binding of one such important protein, human antigen R (HuR) to SARS-CoV-2 5'UTR and studied its potential role in virus life cycle. The knockdown and knockout studies revealed importance of such binding in viral translation. We identified 5'-UTR mutations in SARS-CoV-2 variants of concern that altered the HuR-binding affinity. Interestingly, HuR enhanced non-structural protein translation through the genomic 5'-UTR, by promoting polypyrimidine tract-binding protein binding to the 5'-UTR. However, HuR suppressed the structural protein translation from sub genomic 5UTR. HuR knockout increased the sensitivity to remdesivir treatment by decreasing its half-maximal inhibitory concentration. An antisense oligonucleotide (whose binding site overlapped the HuR-binding site) reduced viral RNA levels in wild-type cells but not HuR-knockout cells. Our results indicate that HuR regulates the balance between SARS-CoV-2 structural and non-structural proteins and guides the infection of viral variants, implying that HuR can potentially be targeted for therapeutic interventions. Author SummaryViruses interacts with various host proteins throughout their life cycle. One significant protein is HuR, an RNA-binding protein that regulates RNA stability and translation. HuR binds to viral RNAs at the 5UTR or 3UTR, impacting their translation and replication. We identified conserved HuR binding sites in the SARS-CoV-2 5UTR across different beta coronaviruses. This binding enhanced the initiation of translation from the genomic 5 UTR, increasing the production of non-structural proteins essential for viral replication. Additionally, we discovered that another host protein, PTB, promotes HuR binding to the viral 5 UTR, facilitating its loading onto ribosomes. Conversely, HuR plays an antagonistic role concerning subgenomic RNAs (sgRNAs), which code for structural proteins, by regulating and limiting their levels. This dual regulation indicates that the virus exploits HuR for its benefit while the host employs it to control viral spread. Targeting HuR may help manipulate the SARS-CoV-2 life cycle. We found that HuR knockout increased sensitivity to the antiviral drug Remdesivir. Using an antisense oligonucleotide to block HuR binding effectively reduced viral RNA levels. Our findings highlight the critical role of HuR in regulating viral protein production and its potential as a therapeutic target.

microbiology↗

bioRxiv2023

A novel interaction between the 5' untranslated region of the Chikungunya virus genome and Musashi RNA binding protein is essential for efficient virus genome replication.

Chikungunya virus (CHIKV) is a re-emerging, pathogenic alphavirus that is transmitted to humans by Aedes spp. mosquitoes--causing fever and debilitating joint pain, with frequent long-term health implications and high morbidity. The CHIKV replication cycle is poorly understood and specific antiviral therapeutics are lacking. In the current study, we identify host cell Musashi RNA binding protein-2 (MSI-2) as a proviral factor. MSI-2 depletion and small molecule inhibition assays demonstrated that MSI-2 is required for efficient CHIKV genome replication. Depletion of both MSI-2 and MSI-1 homologues was found to synergistically inhibit CHIKV replication, suggesting redundancy in their proviral function. Electromobility shift assay (EMSA) competition studies demonstrated that MSI-2 interacts specifically with an RNA binding motif within the 5 untranslated region (5UTR) of CHIKV and reverse genetic analysis showed that mutation of the binding motif inhibited genome replication and blocked rescue of mutant virus. For the first time, this study identifies the proviral role of MSI RNA binding proteins in the replication of the CHIKV genome, providing important new insight into mechanisms controlling replication of this significant human pathogen and the potential of a novel therapeutic target.

microbiology↗

bioRxiv2023

ORPA: A Fast and Efficient Method for Constructing Genome-Wide Alignments of Organelle Genomes for Phylogenetic Analysis

Creating a multi-gene alignment matrix for phylogenetic analysis using organelle genomes involves aligning single-gene datasets manually, a process that can be time-consuming and prone to errors. The HomBlocks pipeline has been created to eliminate the inaccuracies arising from manual operations. The processing of a large number of sequences, however, remains a time-consuming task. To conquer this challenge, we have developed a speedy and efficient method called ORPA. ORPA quickly generates multiple sequence alignments for whole-genome comparisons by parsing the result files of NCBI BLAST, completing the task in just one minute. With increasing data volume, ORPAs efficiency is even more pronounced, over 300 times faster than HomBlocks in aligning 60 high-plant chloroplast genomes. The tools phylogenetic tree outputs demonstrate equivalent results to HomBlocks, indicating its outstanding efficiency. Due to its speed and accuracy, ORPA can identify species-level evolutionary conflicts, providing valuable insights into evolutionary cognition.

bioinformatics↗

bioRxiv2023

Identification of genome safe harbor loci for human gene therapy based on evolutionary biology and comparative genomics

Gene transfer into CD34+ hematopoietic stem and progenitor cells (HSPCs) involving integrating viral vectors has unpredictable outcomes including potential adverse events like leukemogenesis, resulting from insertional mutagenesis. Therefore, identifying and characterizing genome safe harbor (GSH) sites where exogenous gene material can be safely integrated into adult progenitor and stem cells is critically important for therapeutic gene addition. Here, we present a novel approach to identify new GSH sites based on a proven system of stable transgene insertion: the evolutionarily conserved integration of parvovirus DNA into the germlines of host species. From a dataset of 199 unique endogenous parvovirus (EPV) integration events identified in host species genomes, 102 loci were mapped to the human genome with 17 being experimentally evaluated as GSHs in primary human CD34+ HSPCs. Nine promising GSHs resulted in cells edited using nucleofection alone or in combination with rAAV transduction. Of the nine GSH sites, six edited loci displayed sustained transgene expression in both erythroid and immune phenotypes while three clearly exhibited immune branch specific-regulation. Following this approach, additional GSH sites are likely to emerge from the remaining mapped loci for gene addition in hematopoietic stem and progenitor cells. Since it is unlikely that the GSH-lineage-restricted transgene expression is exclusive to hematopoietic stem cells, this approach extends the options for gene knock-ins while reducing the risks of insertional mutagenesis, unpredictable expression profiles, effects on differentiation, and increasing therapeutic effects.

genetics↗

bioRxiv2023

Comparative Genomics Exploration of Shared lncRNA-coding genes in Human and All Annotated Plant Genomes: Potential Implications for Cancer Research

Since their discovery in 1990, lncRNAs have been heavily investigated. It is already known that the genomes of plants and animals express large numbers of lncRNAs. In humans, many lncRNA are considered essential players in cancer biology, mainly acting as gene expression regulators in processes like cell proliferation, apoptosis, migration, invasion and stemness. In plants, lncRNAs are involved in vegetative growths, reproduction and stress responses. Yet, in the entirety of the animal and plant kingdoms, the functions and mechanisms of action for the majority of lncRNAs remain largely undiscovered, as do their orthology relationships. The poor conservation of the DNA sequences encoding for these transcripts is hindering the identification of lncRNAs orthologs especially among very distant evolutionary species. In this short study, using an uncomplicated, but creative bioinformatic approach, I searched for sequence homologies between human DNA and 175 annotated plant genomes from NCBI. Using stringent filtering, I found 20 human lncRNA-encoding genes overlapping plant genomic features, including lncRNAs. Evenmore, 3 of these human lncRNA-encoding genes with a potential plant ortholog are reported in multiple databases for lncRNA involved in cancers. This study opens the road for investigating the tumorigenesis in a deep homology context of lncRNAs.

bioinformatics↗

bioRxiv2024

Genome-Wide Association Insights into the Genomic Regions Controlling Oil Production Traits in Acrocomia aculeata (neotropical native palm)

Macauba (Acrocomia aculeata) is a non-domesticated neotropical palm that has been attracting attention for economical use due to its great potential for oil production comparable to the commercially used oil palm (Elaeis guineenses). The discovery of associations between quantitative trait loci and economically important traits represents an advance toward macauba domestication. Pursuing this advance, this study performs single-trait and multi-trait GWAS models to identify candidate genes related to oil production traits in macauba. We randomly selected 201 palms from a natural population and analysed 13 traits related to fruit production, processing, and oil content. Genotyping was performed following the genotyping-by- sequencing protocol. SNP calling was performed using three strategies since macauba doesnt have a reference genome: using i) de novo pipeline, ii) Elaeis guineenses Jacq. reference genome, and iii) transcriptome of Acrocomia aculeata. Single-trait analysis was fitted using five models from GAPIT, while multi-trait analysis was fitted using a multivariate stepwise method implemented in the software TASSEL. Multi-trait analyses were conducted in all pairwise trait combinations. Results showed statistically significant differences in all phenotypic traits studied, and heritability values ranged from 0.63 to 0.95. Gene annotation detected 15 candidate genes in seven traits in the single-trait GWAS and four candidate genes in 10 trait combinations in the multi-trait GWAS. We provide new insights on genomic regions that mapped candidate genes involved in macauba oil production phenotypes. Associated markers to the traits of interest may be valuable resources for the development of marker-assisted selection in macauba for both domestication and pre-breeding purposes.

genetics↗

bioRxiv2024

Whole genome sequencing and comparative genomic studies of Priestia filamentosa JURBA-X for its drought-tolerance, plant-growth promotion, and fluorescent characteristics

Priestia filamentosa JURBA-X is a nonmotile, endospore-forming, and Gram-positive bacterium isolated from a rhizosphere soil sample of groundnut fields in Andhra Pradesh, India, during summer. JURBA-X exhibits chains of filamentous morphology with vibrant yellow fluorescence. It shows tolerance to drought stress, phosphate solubilization, siderophore production, and antibacterial activity. 16s rRNA and single-copy orthologous DNA gyrase subunit B-based phylogenies suggested its closeness with Priestia filamentosa spp., leading to its classification as P. filamentosa JURBA-X. The whole genome was assembled into 5,113,908 bp, distributed across 55 contigs with a GC content of 36.59% and 5,352 protein-coding genes. Genome-genome distance and average nucleotide identity confirmed its designation as a novel strain within P. filamentosa. Assignment of genes/proteins in diverse functions such as drought tolerance, plant growth promotion (PGP), lantibiotics, polyketides, vitamin synthesis, siderophores production, and phosphate solubilization highlight its potential utilization in agriculture as a PGPR and industrial production of antimicrobial agent, vitamins, and biopolymers. Our research concluded that the fluorescence exhibited by JURBA-X is potentially attributed to the production of resistomycin, which might have been horizontally transferred from Streptomyces resistomycificus as inferred by the homology of resistomycin (rem) biosynthesis cluster genes.

microbiology↗

bioRxiv2024

DeepGene: An Efficient Foundation Model for Genomics based on Pan-genome Graph Transformer

Decoding the language of DNA sequences is a fundamental problem in genome research. Mainstream pre-trained models like DNABERT-2 and Nucleotide Transformer have demonstrated remarkable achievements across a spectrum of DNA analysis tasks. Yet, these models still face the pivotal challenge of (1) genetic language diversity, or the capability to capture genetic variations across individuals or populations in the foundation models; (2) model efficiency, specifically how to enhance performance at scalable costs for large-scale genetic foundational models; (3) length extrapolation, or the ability to accurately interpret sequences ranging from short to long within a unified model framework. In response, we introduce DeepGene, a model leveraging Pan-genome and Minigraph representations to encompass the broad diversity of genetic language. DeepGene employs the rotary position embedding to improve the length extrapolation in various genetic analysis tasks. On the 28 tasks in Genome Understanding Evaluation, DeepGene reaches the top position in 9 tasks, second in 5, and achieves the overall best score. DeepGene outperforms other cutting-edge models for its compact model size and superior efficiency in processing sequences of varying lengths. The datasets and source code of DeepGene are available at GitHub (https://github.com/wds-seu/DeepGene).

bioinformatics↗

bioRxiv2024

Comprehensive analysis of microbial content in whole-genome sequencing samples from The Cancer Genome Atlas project

In recent years, a growing number of publications have reported the presence of microbial species in human tumors and of mixtures of microbes that appear to be highly specific to different cancer types. Our recent re-analysis of data from three cancer types revealed that technical errors have caused erroneous reports of numerous microbial species found in sequencing data from The Cancer Genome Atlas (TCGA) project. Here we have expanded our analysis to cover all 5,734 whole-genome sequencing (WGS) data sets currently available from TCGA, covering 25 distinct types of cancer. We analyzed the microbial content using updated computational methods and databases, and compared our results to those from two major recent studies that focused on bacteria, viruses, and fungi in cancer. Our results expand upon and reinforce our recent findings, which showed that the presence of microbes is far smaller than had been previously reported, and that many species identified in TCGA data are either not present at all, or are known contaminants rather than microbes residing within tumors. As part of this expanded analysis, and to help others avoid being misled by flawed data, we have released a dataset that contains detailed read counts for bacteria, viruses, archaea, and fungi detected in all 5,734 TCGA samples, which can serve as a public reference for future investigations. One-sentence summaryAnalysis of microbial content in 5,734 whole-genome sequencing samples from TCGA yields a comprehensive new resource for investigating the role of microbes in cancer.

cancer biology↗

bioRxiv2024

Large-Scale Genome-Wide Optimization and Prediction of the Cre Recombinase System for Precise Genome Manipulation in Mice

The Cre-Lox recombination system is a powerful tool in mouse genetics, offering spatial-temporal control over gene expression and facilitating the large-scale generation of conditional knockout mice. Its versatility also extends to other research models, such as rats, pigs, and zebrafish. However, the Cre-Lox technology presents a set of challenges that includes high costs, a time-intensive process, and the occurrence of unpredictable recombination events, which can lead to unexpected phenotypic outcomes. To better understand factors affecting recombination, we embarked on a systematic and genome-wide analysis of Cre-mediated recombination in mice. To ensure uniformity and reproducibility, we generated 11 novel strains with conditional alleles at the ROSA26 locus, utilizing a single inbred mouse strain background, C57BL/6J. We examined several factors influencing Cre-recombination, including the inter-loxP distance, mutant loxP sites, the zygosity of the conditional alleles, chromosomal location, and the age of the breeders. We discovered that the selection of the Cre-driver strain profoundly impacts recombination efficiency. We also found that successful and complete recombination is best achieved when loxP sites are spaced between 1 to 4 kb apart, with mutant loxP sites facilitating recombination at distances of 1 to 3 kb. Furthermore, we demonstrate that complete recombination does not occur at an inter-loxP distance of [≥] 15 kb with wildtype loxP sites, nor at a distance of [≥] 7 kb with mutant lox71/66 sites. Interestingly, the age of the Cre-driver mouse at the time of breeding emerged as a critical factor in recombination efficiency, with best results observed between 8 and 20 weeks old. Moreover, crossing heterozygous floxed alleles with the Cre-driver strain resulted in more efficient recombination than using homozygous floxed alleles. Lastly, maintaining an inter-loxP distance of 4 kb or less ensures efficient recombination of the conditional allele, regardless of the chromosomal location. While CRISPR/Cas has revolutionized genome editing in mice, Cre-Lox technology remains a cornerstone for the generation of sophisticated alleles and for precise control of gene expression in mice. The knowledge gained here will enable investigators to select a Cre-Lox approach that is most efficient for their desired outcome in the generation of both germline and non-germline mouse models of human disease, thereby reducing time and cost of Cre-Lox technology-mediated genome modification.

genetics↗