Biology subjects

Lisi, A.

Publications and source records attributed to Lisi, A..

4 recordsLinked to original sources

bioRxiv2025

CLUES2 Companion: Computational pipelines to estimate, visualize, and date selection on multi-locus sites

SummaryStatistical methods that quantify the selection coefficient associated with alleles provide critical insights into the evolutionary processes underlying organismal adaptation. Among these approaches, CLUES2 was recently developed to estimate selection coefficients for alleles using a statistical framework that captures the maximum amount of information present in genomic data, making it a state-of-the-art method for identifying variation under selection. However, before executing this approach, users first need to apply Relate, a genealogy-based approach, to their data to generate the input files for CLUES2. Moreover, completing this pre-processing step inherently assumes that users have sufficient expertise to successfully run the Relate software. Here, we present the CLUES2 Companion package, which contains user-friendly pipelines that seamlessly apply Relate to multiple sites within a target genomic region and then execute the CLUES2 software to estimate selection coefficients for these sites. CLUES2 Companion also has the capability to present the output of CLUES2 analyses in tabular and graphical formats. In addition, as a new feature, we adapted Relate and CLUES2 to estimate the age of onset of a selective sweep of derived variation, expanding the functionality of our package. ResultsTo demonstrate the utility of our approach, we applied CLUES2 Companion to polymorphisms in the MCM6 gene on Chromosome 2 (including the known variants associated with lactase persistence) in the European Finnish, Middle Eastern Bedouin, and East African Maasai populations from the 1000 Genomes Project, the Human Genome Diversity Project (HGDP), and the haplotype map (HapMap) Project Phase 3, respectively. Our analyses uncovered significant selection coefficient estimates at the persistence-associated T-13910 allele (rs4988235; s = 0.09986, CI: 0.08678 - 0.11294) in the Finnish, the G-13915 allele (rs41380347; s = 0.09981, CI: 0.06515 - 0.13448) in the Bedouin, and the C-14010 allele (rs145946881; s = 0.09981, CI: 0.08799 - 0.11163) in the Maasai, indicative of a classic selective sweep. Furthermore, we inferred the age of onset of selection at these alleles to be 9,100 years ago (CI: 6,552 - 10,612 years ago) in the Finnish, 7,700 years ago (CI: 1,864 - 8,064 years ago) in the Bedouin, and 4,900 years ago (CI: 3,864 - 5,936 years ago) in the Maasai, respectively, which coincide well with other estimates based on genetic and archaeological data. To further validate our dating method, we simulated several datasets containing SNPs with known ages of onset of selection, s estimates, and genomic positions using a selective sweep framework implemented in msprime and then applied CLUES2 Companion to the simulated datasets. Using this approach, CLUES2 Companion produced similar estimates of selection onset as the ones specified in the simulations, corroborating the dependability of our method. Overall, CLUES2 Companion is a versatile package that enables users to efficiently explore, interpret, and report evidence of selection in genomic datasets, complementing the CLUES2 software. Availability and ImplementationCLUES2 Companion is free and open source on GitHub (https://github.com/alisi1989/CLUES2-Companion) and on DropBox (https://www.dropbox.com/scl/fo/m5y6aek0twd1jz9grg4p3/ALxMgIljUJRIZZNQXaGU-OE?rlkey=mbbh36ondftnqg0x07eao57eg&st=9jzsl5um&dl=0). Contactalisi@usc.edu; mc44680@usc.edu

bioinformatics↗

bioRxiv2025

A fluid dynamics-model system for advancing Tissue Engineering and Cancer Research studies: Dynamic Culture with the innovative BioAxFlow Bioreactor

In this study, we test an innovative bioreactor, particularly suitable for tissue engineering applications, named BioAxFlow. Unlike traditional bioreactors, it does not rely on mechanical components to agitate the culture medium, but on the fluid-dynamics generated thanks to the unique geometry of the culture chamber. The flow generated within ensures continuous medium movement, promoting consistent cell exposure to nutrients and growth factors. Using the human osteosarcoma cell line SAOS-2, the bioreactors ability to enhance cell adhesion and proliferation on polylactic acid scaffolds, mimicking bone tissue matrix architecture, is tested. The findings show that the bioreactor significantly improved cell adhesion and growth compared to static cultures, promoting a homogeneous cell distribution across the scaffold surfaces, which is crucial for developing functional tissue constructs. The bioreactor preserves the osteogenic potential of SAOS-2 cells as assessed by the expression of key osteogenic markers. Additionally, it retains the tumorigenic characteristics of SAOS-2 cells, including the expression of pro-angiogenic factors and apoptosis-related genes. These results indicate that the BioAxFlow bioreactor is an effective platform for tissue engineering and cancer research, offering a promising tool for both regenerative medicine applications and drug testing.

bioengineering↗

bioRxiv2024

Polaris: Polarization of ancestral and derived polymorphic alleles for inferences of extended haplotype homozygosity in human populations.

SummaryStatistical methods that measure the extent of haplotype homozygosity on chromosomes have been highly informative for identifying episodes of recent selection. For example, the integrated haplotype score (iHS) and the extended haplotype homozygosity (EHH) statistics detect long-range haplotype structure around derived and ancestral alleles indicative of classic and soft selective sweeps, respectively. However, to our knowledge, there are currently no publicly available methods that classify ancestral and derived alleles in genomic datasets for the purpose of quantifying the extent of haplotype homozygosity. Here, we introduce the Polaris package, which polarizes chromosomal variants into ancestral and derived alleles and creates corresponding genetic maps for analysis by selscan and HaploSweep, two versatile haplotype-based programs that perform scans for selection. With the input files generated by Polaris, selscan and/or HaploSweep can produce the appropriate sign (either positive or negative) to outlier iHS statistics, enabling users to distinguish between selection on derived or ancestral alleles. In addition, Polaris can convert the numerical output of these analyses into graphical representations of selective sweeps, increasing the functionality of our software. ResultsTo demonstrate the utility of our approach, we applied the Polaris package to Chromosome 2 in the European Finnish population from the 1000 Genomes Project. More specifically, we examined the regulatory region in intron 13 of MCM6 associated with lactase persistence (i.e., the ability to digest the lactose sugar present in fresh milk), a region of intense interest to human evolutionary geneticists. Our analyses showed that the derived T-13910 allele (a known enhancer for lactase expression), sits on an extended haplotype background in the Finnish consistent with a classic selective sweep model as determined by iHS and EHH statistics calculated by selscan and HaploSweep. Importantly, we were able to immediately identify this target allele under selection based on the information generated by our software. We also explored outlier statistics across Chromosome 2 in two distinct datasets: i) one containing polarized alleles generated with Polaris and ii) the other containing unpolarized alleles in the original phased vcf file. Here, we found a significant excess of outlier statistics (P < 0.00001) in the unpolarized dataset, raising the possibility that a subset of these hits of selection on Chromosome 2 may be false positives. Overall, Polaris is a versatile package that enables users to efficiently explore, interpret, and report signals of recent selection in genomic datasets. Availability and implementationThe Polaris package is free and open source on GitHub (https://github.com/alisi1989/Polaris) and on DropBox (https://www.dropbox.com/scl/fo/mlxizft5267vem9u62qkn/AAnM0qX923zPzQBlPX8iteM?rlkey=uezrp4t2waffpj0nmo1evr320&e=1&st=jaodccws&dl=0)

bioinformatics↗

bioRxiv2023

AncestryGrapher toolkit: Python command-line pipelines to visualize global- and local- ancestry inferences from the RFMix2 software

SummaryAdmixture is a fundamental process that has shaped patterns of genetic variation and the risk for disease in human populations. Here, we introduce the AncestryGrapher toolkit for visualizing inferred global- and local- ancestry by the RFMix v.2 software. Currently, there is no straightforward method to summarize population ancestry results from RFMix analysis. ResultsTo demonstrate the utility of our method, we applied the AncestryGrapher toolkit to the output files of RFMix v.2 to visualize the global and local ancestry of individuals in the Mozabite Berber population from North Africa. Our results showed that the Mozabite Berbers derived their ancestry from the Middle East, Europe, and sub-Saharan Africa (global ancestry). Furthermore, we found that the population origin of ancestry varied considerably along chromosomes. More specifically, we observed variance in ancestry along chromosome 2 (local ancestry), in the genomic region containing the common genetic polymorphisms associated with lactase persistence, a trait known to be under strong positive selection. This finding indicates that the demographic process of admixture has influenced patterns of allelic variation in addition to natural selection. Overall, the AncestryGrapher toolkit facilitates the exploration, interpretation, and reporting of ancestry patterns in human populations. Availability and implementationThe AncestryGrapher toolkit is free and open source on https://github.com/alisi1989/RFmix2-Pipeline-to-plot.

bioinformatics↗