NetActivity enhances transcriptional signals by combining gene expression into robust gene set activity scores through interpretable autoencoders.

Grouping gene expression into gene set activity scores (GSAS) provides better biological insights than studying individual genes. However, existing gene set projection methods cannot return representative, robust, and interpretable GSAS. We developed NetActivity, a machine learning framework that generates GSAS based on a sparsely-connected autoencoder, where each neuron in the inner layer represents a gene set. We proposed a three-tier training that yielded representative, robust, and interpretable GSAS. NetActivity model was trained with 1518 GO biological processes terms and KEGG pathways and all GTEx samples. NetActivity generates GSAS robust to the initialization parameters and representative of the original transcriptome, and assigned higher importance to more biologically relevant genes. Moreover, NetActivity returns GSAS with a more consistent definition and higher interpretability than GSVA and hipathia, state-of-the-art gene set projection methods. Finally, NetActivity enables combining bulk RNA-seq and microarray datasets in a meta-analysis of prostate cancer progression, highlighting gene sets related to cell division, key for disease progression. When applied to metastatic prostate cancer, gene sets associated with cancer progression were also altered due to drug resistance, while a classical enrichment analysis identified gene sets irrelevant to the phenotype. NetActivity is publicly available in Bioconductor and GitHub.

Structural snapshots of base excision by the cancer-associated variant MutY N146S reveal a retaining mechanism.

DNA glycosylase MutY plays a critical role in suppression of mutations resulted from oxidative damage, as highlighted by cancer-association of the human enzyme. MutY requires a highly conserved catalytic Asp residue for excision of adenines misinserted opposite 8-oxo-7,8-dihydroguanine (OG). A nearby Asn residue hydrogen bonds to the catalytic Asp in structures of MutY and its mutation to Ser is an inherited variant in human MUTYH associated with colorectal cancer. We captured structural snapshots of N146S Geobacillus stearothermophilus MutY bound to DNA containing a substrate, a transition state analog and enzyme-catalyzed abasic site products to provide insight into the base excision mechanism of MutY and the role of Asn. Surprisingly, despite the ability of N146S to excise adenine and purine (P) in vitro, albeit at slow rates, N146S-OG:P complex showed a calcium coordinated to the purine base altering its conformation to inhibit hydrolysis. We obtained crystal structures of N146S Gs MutY bound to its abasic site product by removing the calcium from crystals of N146S-OG:P complex to initiate catalysis in crystallo or by crystallization in the absence of calcium. The product structures of N146S feature enzyme-generated ß-anomer abasic sites that support a retaining mechanism for MutY-catalyzed base excision.

Polymorphic Inversions Underlie the Shared Genetic Susceptibility of Obesity-Related Diseases.

The burden of several common diseases including obesity, diabetes, hypertension, asthma, and depression is increasing in most world populations. However, the mechanisms underlying the numerous epidemiological and genetic correlations among these disorders remain largely unknown. We investigated whether common polymorphic inversions underlie the shared genetic influence of these disorders. We performed an inversion association analysis including 21 inversions and 25 obesity-related traits on a total of 408,898 Europeans and validated the results in 67,299 independent individuals. Seven inversions were associated with multiple diseases while inversions at 8p23.1, 16p11.2, and 11q13.2 were strongly associated with the co-occurrence of obesity with other common diseases. Transcriptome analysis across numerous tissues revealed strong candidate genes for obesity-related traits. Analyses in human pancreatic islets indicated the potential mechanism of inversions in the susceptibility of diabetes by disrupting the cis-regulatory effect of SNPs from their target genes. Our data underscore the role of inversions as major genetic contributors to the joint susceptibility to common complex diseases.

Identifying chromosomal subpopulations based on their recombination histories advances the study of the genetic basis of phenotypic traits.

Recombination is a main source of genetic variability. However, the potential role of the variation generated by recombination in phenotypic traits, including diseases, remains unexplored because there is currently no method to infer chromosomal subpopulations based on recombination pattern differences. We developed recombClust, a method that uses SNP-phased data to detect differences in historic recombination in a chromosome population. We validated our method by performing simulations and by using real data to accurately predict the alleles of well-known recombination modifiers, including common inversions in Drosophila melanogaster and human, and the chromosomes under selective pressure at the lactase locus in humans. We then applied recombClust to the complex human 1q21.1 region, where nonallelic homologous recombination produces deleterious phenotypes. We discovered and validated the presence of two different recombination histories in these regions that significantly associated with the differential expression of ANKRD35 in whole blood and that were in high linkage with variants previously associated with hypertension. By detecting differences in historic recombination, our method opens a way to assess the influence of recombination variation in phenotypic traits.

scoreInvHap: Inversion genotyping for genome-wide association studies.

Polymorphic inversions contribute to adaptation and phenotypic variation. However, large multi-centric association studies of inversions remain challenging. We present scoreInvHap, a method to genotype inversions from SNP data for genome-wide association studies (GWASs), overcoming important limitations of current methods and outperforming them in accuracy and applicability. scoreInvHap calls individual inversion-genotypes from a similarity score to the SNPs of experimentally validated references. It can be used on different sources of SNP data, including those with low SNP coverage such as exome sequencing, and is easily adaptable to genotype new inversions, either in humans or in other species. We present 20 human inversions that can be reliably and easily genotyped with scoreInvHap to discover their role in complex human traits, and illustrate a first genome-wide association study of experimentally-validated human inversions. scoreInvHap is implemented in R and it is freely available from Bioconductor.

Variability of multi-omics profiles in a population-based child cohort.

BACKGROUND: Multiple omics technologies are increasingly applied to detect early, subtle molecular responses to environmental stressors for future disease risk prevention. However, there is an urgent need for further evaluation of stability and variability of omics profiles in healthy individuals, especially during childhood. METHODS: We aimed to estimate intra-, inter-individual and cohort variability of multi-omics profiles (blood DNA methylation, gene expression, miRNA, proteins and serum and urine metabolites) measured 6 months apart in 156 healthy children from five European countries. We further performed a multi-omics network analysis to establish clusters of co-varying omics features and assessed the contribution of key variables (including biological traits and sample collection parameters) to omics variability. RESULTS: All omics displayed a large range of intra- and inter-individual variability depending on each omics feature, although all presented a highest median intra-individual variability. DNA methylation was the most stable profile (median 37.6% inter-individual variability) while gene expression was the least stable (6.6%). Among the least stable features, we identified 1% cross-omics co-variation between CpGs and metabolites (e.g. glucose and CpGs related to obesity and type 2 diabetes). Explanatory variables, including age and body mass index (BMI), explained up to 9% of serum metabolite variability. CONCLUSIONS: Methylation and targeted serum metabolomics are the most reliable omics to implement in single time-point measurements in large cross-sectional studies. In the case of metabolomics, sample collection and individual traits (e.g. BMI) are important parameters to control for improved comparability, at the study design or analysis stage. This study will be valuable for the design and interpretation of epidemiological studies that aim to link omics signatures to disease, environmental exposures, or both.

Plant organellar DNA polymerases repair double-stranded breaks by microhomology-mediated end-joining.

Double-stranded breaks (DSBs) in plant organelles are repaired via genomic rearrangements characterized by microhomologous repeats. These microhomologous signatures predict the existence of an unidentified enzymatic machinery capable of repairing of DSBs via microhomology-mediated end-joining (MMEJ) in plant organelles. Here, we show that organellar DNA polymerases from Arabidopsis thaliana (AtPolIA and AtPolIB) perform MMEJ using microhomologous sequences as short as six nucleotides. AtPolIs execute MMEJ by virtue of two specialized amino acid insertions located in their thumb subdomains. Single-stranded binding proteins (SSBs) unique to plants, AtWhirly2 and organellar single-stranded binding proteins (AtOSBs), hinder MMEJ, whereas canonical mitochondrial SSBs (AtmtSSB1 and AtmtSSB2) do not interfere with MMEJ. Our data predict that organellar DNA rearrangements by MMEJ are a consequence of a competition for the 3'-OH of a DSBs. If AtWhirlies or AtOSBs gain access to the single-stranded DNA (ssDNA) region of a DSB, the reaction will shift towards high-fidelity routes like homologous recombination. Conversely MMEJ would be favored if AtPolIs or AtmtSSBs interact with the DSB. AtPolIs are not phylogenetically related to metazoan mitochondrial DNA polymerases, and the ability of AtPolIs to execute MMEJ may explain the abundance of DNA rearrangements in plant organelles in comparison to animal mitochondria.

Relationships between population densities and niche-centroid distances in North American birds.

Correlational ecological niche models have seen intensive use and exploration as a means of estimating the limits of actual and potential geographic distributions of species, yet their application to explaining geographic abundance patterns has been debated. We developed a detailed test of this latter possibility based on the North American Breeding Bird Survey. Correlations between abundances and niche-centroid distances were mostly negative, as per expectations of niche theory and the abundant niche-centre relationship. The negative relationships were not distributed randomly among species: terrestrial, non-migratory, small-bodied, small-niche-breadth and restricted-range species had the strongest negative associations. Distances to niche centroids as estimated from correlational analyses of presence-only data thus offer a unique means by which to infer geographic abundance patterns, which otherwise are enormously difficult to characterise.

In utero and childhood exposure to tobacco smoke and multi-layer molecular signatures in children.

BACKGROUND: The adverse health effects of early life exposure to tobacco smoking have been widely reported. In spite of this, the underlying molecular mechanisms of in utero and postnatal exposure to tobacco smoke are only partially understood. Here, we aimed to identify multi-layer molecular signatures associated with exposure to tobacco smoke in these two exposure windows. METHODS: We investigated the associations of maternal smoking during pregnancy and childhood secondhand smoke (SHS) exposure with molecular features measured in 1203 European children (mean age 8.1 years) from the Human Early Life Exposome (HELIX) project. Molecular features, covering 4 layers, included blood DNA methylation and gene and miRNA transcription, plasma proteins, and sera and urinary metabolites. RESULTS: Maternal smoking during pregnancy was associated with DNA methylation changes at 18 loci in child blood. DNA methylation at 5 of these loci was related to expression of the nearby genes. However, the expression of these genes themselves was only weakly associated with maternal smoking. Conversely, childhood SHS was not associated with blood DNA methylation or transcription patterns, but with reduced levels of several serum metabolites and with increased plasma PAI1 (plasminogen activator inhibitor-1), a protein that inhibits fibrinolysis. Some of the in utero and childhood smoking-related molecular marks showed dose-response trends, with stronger effects with higher dose or longer duration of the exposure. CONCLUSION: In this first study covering multi-layer molecular features, pregnancy and childhood exposure to tobacco smoke were associated with distinct molecular phenotypes in children. The persistent and dose-dependent changes in the methylome make CpGs good candidates to develop biomarkers of past exposure. Moreover, compared to methylation, the weak association of maternal smoking in pregnancy with gene expression suggests different reversal rates and a methylation-based memory to past exposures. Finally, certain metabolites and protein markers evidenced potential early biological effects of postnatal SHS, such as fibrinolysis.

Common polymorphic inversions at 17q21.31 and 8p23.1 associate with cancer prognosis.

BACKGROUND: Chromosomal inversions are structural genetic variants where a chromosome segment changes its orientation. While sporadic de novo inversions are known genetic risk factors for cancer susceptibility, it is unknown if common polymorphic inversions are also associated with the prognosis of common tumors, as they have been linked to other complex diseases. We studied the association of two well-characterized human inversions at 17q21.31 and 8p23.1 with the prognosis of lung, liver, breast, colorectal, and stomach cancers. RESULTS: Using data from The Cancer Genome Atlas (TCGA), we observed that inv8p23.1 was associated with overall survival in breast cancer and that inv17q21.31 was associated with overall survival in stomach cancer. In the meta-analysis of two independent studies, inv17q21.31 heterozygosity was significantly associated with colorectal disease-free survival. We found that the association was mediated by the de-methylation of cg08283464 and cg03999934, also linked to lower disease-free survival. CONCLUSIONS: Our results suggest that chromosomal inversions are important genetic factors of tumor prognosis, likely affecting changes in methylation patterns.

Epigenome-wide meta-analysis of DNA methylation and childhood asthma.

BACKGROUND: Epigenetic mechanisms, including methylation, can contribute to childhood asthma. Identifying DNA methylation profiles in asthmatic patients can inform disease pathogenesis. OBJECTIVE: We sought to identify differential DNA methylation in newborns and children related to childhood asthma. METHODS: Within the Pregnancy And Childhood Epigenetics consortium, we performed epigenome-wide meta-analyses of school-age asthma in relation to CpG methylation (Illumina450K) in blood measured either in newborns, in prospective analyses, or cross-sectionally in school-aged children. We also identified differentially methylated regions. RESULTS: In newborns (8 cohorts, 668 cases), 9 CpGs (and 35 regions) were differentially methylated (epigenome-wide significance, false discovery rate < 0.05) in relation to asthma development. In a cross-sectional meta-analysis of asthma and methylation in children (9 cohorts, 631 cases), we identified 179 CpGs (false discovery rate < 0.05) and 36 differentially methylated regions. In replication studies of methylation in other tissues, most of the 179 CpGs discovered in blood replicated, despite smaller sample sizes, in studies of nasal respiratory epithelium or eosinophils. Pathway analyses highlighted enrichment for asthma-relevant immune processes and overlap in pathways enriched both in newborns and children. Gene expression correlated with methylation at most loci. Functional annotation supports a regulatory effect on gene expression at many asthma-associated CpGs. Several implicated genes are targets for approved or experimental drugs, including IL5RA and KCNH2. CONCLUSION: Novel loci differentially methylated in newborns represent potential biomarkers of risk of asthma by school age. Cross-sectional associations in children can reflect both risk for and effects of disease. Asthma-related differential methylation in blood in children was substantially replicated in eosinophils and respiratory epithelium.

Sinus lift through the use of a surgical guide: a case report.

AIM: Sinus lift is a common procedure to achieve bone height in the maxillary posterior region. This surgery can be performed through either a lateral or crestal approach. Preoperative planning usually entails CBCT and intraoperative evaluation at the time of surgery. This article presents a case in which a surgical guide was made by digitally planning for the performance of a sinus lift procedure through a lateral approach. CASE PRESENTATION: A 59-year-old partially edentulous female patient underwent sinus lift surgery using a stereolithographic guide designed in NemoStudio software and printed using clear, biocompatible MED610. On the day of surgery, the bone guide was fixed with pins, and the lateral window was made by piezoelectric surgery. There were no intraoperative or postoperative incidents. DISCUSSION: There are very few descriptions in the literature of the use of surgical guides for sinus lift. In this case, the advantages of its use were the precision in the performance of the window, the speed and comfort of access, and the retractor effect of the guide on the flap. The main drawback was the need to raise a wide flap to achieve good settlement of the guide. CONCLUSION: The present case, which presents an innovative technique for the opening of the lateral window in a sinus lift procedure, is interesting for the advancement of computer-guided surgery.

Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: findings from the pregnancy and childhood epigenetics (PACE) consortium.

Pre-pregnancy maternal obesity is associated with adverse offspring outcomes at birth and later in life. Individual studies have shown that epigenetic modifications such as DNA methylation could contribute. Within the Pregnancy and Childhood Epigenetics (PACE) Consortium, we meta-analysed the association between pre-pregnancy maternal BMI and methylation at over 450,000 sites in newborn blood DNA, across 19 cohorts (9,340 mother-newborn pairs). We attempted to infer causality by comparing the effects of maternal versus paternal BMI and incorporating genetic variation. In four additional cohorts (1,817 mother-child pairs), we meta-analysed the association between maternal BMI at the start of pregnancy and blood methylation in adolescents. In newborns, maternal BMI was associated with small (<0.2% per BMI unit (1 kg/m2), P < 1.06 × 10-7) methylation variation at 9,044 sites throughout the genome. Adjustment for estimated cell proportions greatly attenuated the number of significant CpGs to 104, including 86 sites common to the unadjusted model. At 72/86 sites, the direction of the association was the same in newborns and adolescents, suggesting persistence of signals. However, we found evidence for acausal intrauterine effect of maternal BMI on newborn methylation at just 8/86 sites. In conclusion, this well-powered analysis identified robust associations between maternal adiposity and variations in newborn blood DNA methylation, but these small effects may be better explained by genetic or lifestyle factors than a causal intrauterine mechanism. This highlights the need for large-scale collaborative approaches and the application of causal inference techniques in epigenetic epidemiology.

Newborn DNA-methylation, childhood lung function, and the risks of asthma and COPD across the life course.

RATIONALE: We aimed to identify differentially methylated regions (DMRs) in cord blood DNA associated with childhood lung function, asthma and chronic obstructive pulmonary disease (COPD) across the life course. METHODS: We meta-analysed epigenome-wide data of 1688 children from five cohorts to identify cord blood DMRs and their annotated genes, in relation to forced expiratory volume in 1 s (FEV1), FEV1/forced vital capacity (FVC) ratio and forced expiratory flow at 75% of FVC at ages 7-13 years. Identified DMRs were explored for associations with childhood asthma, adult lung function and COPD, gene expression and involvement in biological processes. RESULTS: We identified 59 DMRs associated with childhood lung function, of which 18 were associated with childhood asthma and nine with COPD in adulthood. Genes annotated to the top 10 identified DMRs were HOXA5, PAOX, LINC00602, ABCA7, PER3, CLCA1, VENTX, NUDT12, PTPRN2 and TCL1A. Differential gene expression in blood was observed for 32 DMRs in childhood and 18 in adulthood. Genes related with 16 identified DMRs were associated with respiratory developmental or pathogenic pathways. INTERPRETATION: Our findings suggest that the epigenetic status of the newborn affects respiratory health and disease across the life course.

Redundancy analysis allows improved detection of methylation changes in large genomic regions.

BACKGROUND: DNA methylation is an epigenetic process that regulates gene expression. Methylation can be modified by environmental exposures and changes in the methylation patterns have been associated with diseases. Methylation microarrays measure methylation levels at more than 450,000 CpGs in a single experiment, and the most common analysis strategy is to perform a single probe analysis to find methylation probes associated with the outcome of interest. However, methylation changes usually occur at the regional level: for example, genomic structural variants can affect methylation patterns in regions up to several megabases in length. Existing DMR methods provide lists of Differentially Methylated Regions (DMRs) of up to only few kilobases in length, and cannot check if a target region is differentially methylated. Therefore, these methods are not suitable to evaluate methylation changes in large regions. To address these limitations, we developed a new DMR approach based on redundancy analysis (RDA) that assesses whether a target region is differentially methylated. RESULTS: Using simulated and real datasets, we compared our approach to three common DMR detection methods (Bumphunter, blockFinder, and DMRcate). We found that Bumphunter underestimated methylation changes and blockFinder showed poor performance. DMRcate showed poor power in the simulated datasets and low specificity in the real data analysis. Our method showed very high performance in all simulation settings, even with small sample sizes and subtle methylation changes, while controlling type I error. Other advantages of our method are: 1) it estimates the degree of association between the DMR and the outcome; 2) it can analyze a targeted or region of interest; and 3) it can evaluate the simultaneous effects of different variables. The proposed methodology is implemented in MEAL, a Bioconductor package designed to facilitate the analysis of methylation data. CONCLUSIONS: We propose a multivariate approach to decipher whether an outcome of interest alters the methylation pattern of a region of interest. The method is designed to analyze large target genomic regions and outperforms the three most popular methods for detecting DMRs. Our method can evaluate factors with more than two levels or the simultaneous effect of more than one continuous variable, which is not possible with the state-of-the-art methods.

MultiDataSet: an R package for encapsulating multiple data sets with application to omic data integration.

BACKGROUND: Reduction in the cost of genomic assays has generated large amounts of biomedical-related data. As a result, current studies perform multiple experiments in the same subjects. While Bioconductor's methods and classes implemented in different packages manage individual experiments, there is not a standard class to properly manage different omic datasets from the same subjects. In addition, most R/Bioconductor packages that have been designed to integrate and visualize biological data often use basic data structures with no clear general methods, such as subsetting or selecting samples. RESULTS: To cover this need, we have developed MultiDataSet, a new R class based on Bioconductor standards, designed to encapsulate multiple data sets. MultiDataSet deals with the usual difficulties of managing multiple and non-complete data sets while offering a simple and general way of subsetting features and selecting samples. We illustrate the use of MultiDataSet in three common situations: 1) performing integration analysis with third party packages; 2) creating new methods and functions for omic data integration; 3) encapsulating new unimplemented data from any biological experiment. CONCLUSIONS: MultiDataSet is a suitable class for data integration under R and Bioconductor framework.

[Epidemiological panorama of venomous snake bites in the state of Yucatan, Mexico (2003-2012)]. / Panorama epidemiológico de las mordeduras por serpiente venenosa en el estado de Yucatán, México (2003-2012).

No information has been yet published on the epidemiological panorama of snakebite in the state of Yucatan. The aim of this study was to evaluate the geographic and temporal patterns of this problem in the state. Snakebite data was obtained from the Program of Zoonosis of the Health Services of Yucatan between 2003 and 2012. A total of 821 snakebite cases and an incidence of 41.9 accidents/100,000 inhabitants were recorded during this period. The annual average cases and incidence were 82.1 and 4.1 (bites/100,000 inhabitants), respectively. The highest number of snakebites occurred in 2005, while in 2003 the lowest number was recorded. Geographically, we observed a great disparity between municipalities, some of them reaching very high levels of incidence. This geographical variation may reflect the distribution and abundance of venomous snakes on one hand, and human population densities and their activities on the other. This study will help health authorities to know preliminarily the magnitude of snakebites in Yucatan and improving strategies to mitigate it.

[Temporal and geographical analysis of snakebite envenoming in Veracruz, Mexico (2003-2012)]. / Análisis temporal y geográfico del envenenamiento por mordedura de serpiente en Veracruz, México (2003-2012).

Through the period 2003-2012, a temporal and geographical analysis was performed to characterize the snakebite envenoming in the state of Veracruz. Bite records were obtained during this decade and the incidence rate per year was estimated in order to evaluate its spatial and temporal distribution. Furthermore, a smoothed rate of snakebites was calculated per municipality. Snakebite rates have remained constant over time, in spite of fluctuations, which suggest that better prevention strategies are necessary to reduce this phenomenon. Municipalities with the highest smoothed rate are located in the northern portion of the state.

Exploring the causes underlying the latitudinal variation in range sizes: Evidence for Rapoport's rule in spiny lizards (genus Sceloporus).

Species' range size is a fundamental unit of analysis in biodiversity research, given its association with extinction risk and species richness. One of its most notable patterns is its positive relationship with latitude, which has been considered an ecogeographical rule called Rapoport's rule. Despite this rule being confirmed for various taxonomic groups, its validity has been widely discussed and several taxa still lack a formal assessment. Different hypotheses have been proposed to explain their potential mechanisms, with those related to temperature and elevational being the most supported thus far. In this study, we employed two level of analyses (cross-species and assemblage) to investigate the validity of Rapoport's rule in spiny lizards (genus Sceloporus). Additionally, we evaluated four environmental-related hypotheses (minimum temperature, temperature variability, temperature stability since the last glacial maximum, and elevation) posed to explain such pattern, contrasting our results to those patterns expected under a null model of range position. Our results provided support for Rapoport's rule at both levels of analyses, contrasting with null expectations. Consistently, minimum temperature and elevation were the most relevant variables explaining the spatial variation in range size. At the cross-species level, our null simulations revealed that both variables deviated significantly from random expectations. Conversely, at the assemblage level, none of the variables were statistically different from the expected relationships. We discussed the implication of our findings in relation to the ecology and evolution of spiny lizards.

Niche position and niche breadth effects on population abundances: A case study of New World Warblers (Parulidae).

Species abundance patterns are influenced by a myriad of factors, including habitat availability and ecological niche characteristics. However, the evidence concerning the specific impact factors such as niche position and niche breadth on mean and maximum abundances in vertebrates at a broad geographical scale remains inconclusive. In this study, we investigated the influence of niche position and breadth on the abundance of 47 species of birds belonging to the Parulidae family, commonly known as New World Warblers. We obtained data on abundance and presence records spanning the reproductive distribution of these species and employed the outlying mean index analysis to calculate niche position and niche breadth. We assessed the relationship between abundance metrics and niche descriptors using phylogenetic regressions to account for the non-independence resulting from phylogenetic ancestry. Initially, we developed individual models for each predictor and subsequently formulated a multi-predictor model encompassing niche position, niche breadth, and their interaction. Our findings revealed a negative relationship between niche position and both mean and maximum abundance, while niche breadth exhibited a positive relationship with these niche characteristics. Notably, the results of the multi-predictor models indicated that niche position exerted the most substantial influence on both mean and maximum abundance. Additionally, the interaction between niche position and niche breadth had the most positive and significant contribution to mean population abundance. This study underscores the need for future research in other vertebrates to delve into the mechanisms underlying these patterns. Such endeavors will not only enhance our understanding of ecological dynamics but also equip us with predictive capabilities to anticipate population responses to environmental changes effectively.