About
Rafael Guerrero is an Assistant Professor in the Department of Biological Sciences at North Carolina State University. His primary goal is to create a supportive space that helps lab members accomplish their work effectively. The Guerrero Lab is a data-driven computational research group with strong collaborations in wet-lab and fieldwork. Their research combines theoretical approaches and data analysis, focusing on biological applications of programming and statistics. The lab welcomes prospective members with an interest in these areas, regardless of prior experience. Graduate students interested in joining are encouraged to apply through relevant graduate programs such as Genetics and Genomics Scholars, Biology, Genetics, or Bioinformatics within the Department of Biological Sciences.
Research topics
- Computer Science
- Biology
- Genetics
- Medicine
- Internal medicine
- Bioinformatics
- Computational biology
- Combinatorics
- Mathematics
- Obstetrics
- Theoretical computer science
Selected publications
A polygenic growth score and risk for large for gestational age birth weight
Journal of the Endocrine Society · 2026-02-05 · 1 citations
articleOpen accessAbstract Context Large for gestational age (LGA) birth weight is associated with both short- and long-term health consequences for offspring, and fetal genetics may contribute to risk for LGA birth weight. Objectives We evaluated the relationship between a polygenic growth score (PGS) and LGA birth weight in relation to maternal characteristics. Design A previously developed PGS for LGA birth weight was calculated using offspring DNA. We evaluated the relationship between tertiles of the PGS, maternal body mass index, and glycemia assessed by the 50-gram glucose challenge test on the risk for LGA birth weight using 1-way ANOVA and chi-squared tests as well as a regularized linear model. Participants Nulliparous individuals recruited from 8 clinical sites in the United States. Main Outcome Measures LGA birth weight. Results Infant genotype was available for 3286 individuals. A PGS in the first tertile was associated with a lower risk [adjusted odds ratio (aOR) 0.71, 95% confidence interval (CI) 0.53-0.94], and the third tertile with a higher risk (aOR 1.29, 95% CI 1.02-1.63) for LGA birth weight. The odds of LGA birth weight were highest in those with maternal body mass index (BMI) ≥35 kg/m2 and a PGS of either the second tertile (odds ratio 3.54, 95% CI 1.96-6.38) or third tertile (odds ratio 2.69, 95% CI 1.54-4.71). Conclusion A PGS may assist with identification of those fetuses at increased risk for LGA birth weight, particularly among individuals with a BMI ≥35 kg/m2.
Figshare · 2026-01-01
articleOpen accessSenior authorWe assessed the relationship between a polygenic growth score (PGS) and the risk for large for gestational age (LGA) birth weight in a cohort of nulliparous pregnant individuals in the US. We found that a PGS may assist with identification of those fetuses at increased risk for LGA birth weight, particularly among individuals with a BMI ≥35 kg/m<sup>2</sup>.
Figshare · 2026-01-01
articleOpen accessSenior authorWe assessed the relationship between a polygenic growth score (PGS) and the risk for large for gestational age (LGA) birth weight in a cohort of nulliparous pregnant individuals in the US. We found that a PGS may assist with identification of those fetuses at increased risk for LGA birth weight, particularly among individuals with a BMI ≥35 kg/m<sup>2</sup>.
Proceedings of IMPRS · 2026-03-30
articleOpen accessBackground/Objective: Hypertensive disorders of pregnancy (HDP) are a leading cause of both maternal and neonatal morbidity and mortality worldwide. Predicting which pregnant patients will develop HDP, however, remains a challenge, as existing models often overlook the value of incorporating both behavioral and genetic factors. The objective of this study was to identify predictive factors for HDP, including behavioral, psychosocial, and genetic characteristics not typically included in other models. Methods: We conducted a secondary analysis of the Hoosier Mom Cohort, a prospective observational study of pregnant individuals preferentially recruited to assess predictors for gestational diabetes. Participants completed detailed surveys on behavioral and psychosocial factors, as well as activity and sleep. Biospecimens including maternal blood, urine, and feces, placental biopsies, infant cord blood, and buccal swabs were collected. Genotyping was performed to calculate ancestry-adjusted polygenic risk scores (PRS) for preeclampsia. After identifying variables associated with HDP, a logistic regression was used to assess for independent HDP associations. Models were evaluated with and without PRS, to evaluate the added value of genetic risk in prediction. Results: Among 399 participants with complete outcome data, 121 developed HDP (30.3%). Significant predictors included higher BMI, non-White race, nulliparity, and elevated snoring scores. Preeclampsia PRS tertiles showed no significant association with HDP and did not improve the performance of the regression model. Conclusion and Potential Impact: In addition to high BMI, nulliparity, and self-reported race, snoring scores were independently associated with developing HDP. However, adding PRS did not improve the model. Multidimensional risk factor evaluation and clinical screening are needed to improve early intervention and care for patients with HDP. Key words: polygenic risk score, pregnancy, hypertensive disorders of pregnancy, preeclampsia
bioRxiv (Cold Spring Harbor Laboratory) · 2026-03-31
articleOpen accessSenior authorAbstract Alleles with opposing effects on fitness characters are said to exhibit selectional antagonistic pleiotropy (broadly construed so that effects are not necessarily confined to the same individual). A number of theoretical investigations considered the case where a pair of alleles at a locus influences two fitness components and derived the conditions giving rise to stable polymorphism under various assumptions about the mode of trait-interaction. Strikingly, many of these analyses concluded that the potential for maintaining polymorphism is strongly constrained by the joint influence of two factors: (1) the prevalence of weak selection coefficients over coefficients of large magnitude, and (2) the absence of beneficial dominance reversals (where the deleterious effects of each allele are partially or completely masked in the heterozygous genotype). Consequently, the conclusion that selective polymorphism is unlikely to be maintained by intralocus mechanisms of antagonistic pleiotropy has achieved widespread acceptance. Here we argue that such conclusions do not apply to any of the following models of antagonism: (i) additive trait-interaction, (ii) multiplicative trait-interaction, (iii) bivoltine selection, (iv) soft selection, (v) hard selection, and (vi) sexual antagonism. We demonstrate that the parameter space giving rise to stable allelic variation is quite large throughout, and moreover, the plenitude of suitable parameters neither depends on the strength of selection nor requires dominance reversal. Dominance coefficients associated with stringent conditions for stable polymorphism are shown to be atypical as compared to all feasible parameters, and best regarded as an outcome of adherence to a special relation: dominance with a constant magnitude and direction, which includes the case of additive allelic effects at a locus. Properties of single-locus equilibria (heterozygosity, allele frequency differentiation) are investigated, as well as the contribution of dominance schemes to the genetic variance in fitness characters in populations at multilocus linkage equilibrium. Author summary Allelic variants at a locus with opposing effects on multiple fitness components (antagonistic fitness pleiotropy) have long been appreciated as a possible source of balancing selection. The prevalence of polymorphism owing to this form of natural selection, however, has been doubted on theoretical grounds due to the fact that standard assumptions of genetic models (namely, constant magnitudes for the dominance coefficients) are hardly conducive to the maintenance of polymorphism. The major exception to this conclusion lies with schemes that exhibit dominance reversal (where the direction of dominance for antagonistic alleles flips across fitness components). Here we conduct a geometric analysis of the space of polymorphism-promoting dominance parameters and conclude that the conditions for maintaining balanced alleles is unrestrictive, with non-reversals playing an underappreciated role.
Figshare · 2026-01-25
articleOpen accessSenior authorWe assessed the relationship between a polygenic growth score (PGS) and the risk for large for gestational age (LGA) birth weight in a cohort of nulliparous pregnant individuals in the US. We found that a PGS may assist with identification of those fetuses at increased risk for LGA birth weight, particularly among individuals with a BMI ≥35 kg/m<sup>2</sup>.
Network ontology transcript annotation identifies genetic signals underlying sex determination
Scientific Reports · 2026-04-17
articleOpen accessCannabis sativa L. (marijuana, hemp, cannabis) is an angiosperm species currently evolving sex chromosomes. Genetic mechanisms, primarily an XY chromosome system, dictate cannabis sex expression in dioecious populations. However, sexual expression is also governed by the interplay of hormone regulatory gene networks, influenced by both genetic and environmental factors. Within the species, some populations exhibit dioecy, monoecy, or a gradient of both. Dioecious individuals produce exclusively male or female flowers, while monoecious plants bear both male and female flowers. Remarkably, through interruption of phytohormone signal transduction via abiotic stressors, genetically male or female cannabis are able to produce flowers of the opposite sex. Previous transcriptomic analysis have identified genes associated with masculinization through the application of phytohormone signal disruption using silver thiosulfate treatment. We analyzed transcriptomic data from cannabis treated with colloidal silver to similarly induce masculinization. Using Nota (Network ontology transcript annotation), a multilayer network analysis (Random-Walk-with-Restart) tool, we identified candidate genes involved in sex-determination. Nota and a companion program Jack facilitate multi-layer network analyses, enabling discovery and annotation of gene-trait associations. Our findings highlight Nota’s robust application to enrich the genetic architecture of complex traits, particularly in non-model systems like cannabis, and complex traits such as sex determination. Our analyses identified genes associated with cell wall morphogenesis and embryogenic tissue homeostasis, indicating that silver ion treatment perturbs phytohormone signal transduction through metal ion imbalance. In this reproductive strategy, cannabis is able to make use of its widely investigated sex-determining genetic architecture to navigate transient changes in co-expression and cross-cellular signaling driving embryogenic cell wall re-patterning.
medRxiv · 2025-11-04
preprintOpen accessAbstract Background Large for gestational age birth weight is associated with both short- and long-term health consequences for offspring, and fetal genetics may contribute to risk for large for gestational age birth weight. Objectives We evaluated the relationship between a polygenic growth score and the risk for large gestational age birth weight. We also delineated the between the polygenic growth score and risk for large for gestational age birth weight in relation to maternal glycemia and body mass index, both of which are established risk factors for large for gestational age birth weight. Study design This is a secondary analysis of a prospective multicenter cohort study in which nulliparous individuals were recruited from eight clinical sites in the United States. A subset of infants (n = 3865) with DNA available were genotyped, and a previously developed polygenic growth score for large for gestational age birth weight was calculated. We evaluated the relationship between tertiles of the polygenic growth score, maternal body mass index, and glycemia assessed by the 50-gram glucose challenge test on the risk for large for gestational age birth weight using one-way ANOVA and Chi-squared tests as well as a regularized linear model. Results Of the 3,865 individuals with infant genotype available, 3,286 (84.9%) were included in this analysis. A polygenic growth score in the first tertile was associated with a lower risk for large for gestational age (OR 0.71, 95% CI 0.53-0.94), while a polygenic growth score in the third tertile was associated with a higher risk for large for gestational age birth weight (OR 1.29, 95% CI 1.02-1.63). Maternal body mass index was more strongly associated with the risk for large for gestational birth weight than maternal glycemia. The odds of large for gestational age birth weight were significantly higher with a maternal body mass index ≥35 kg/m 2 and a PGS of either the second tertile (OR 3.54, 95% CI 1.96-6.38) or third tertile (OR 2.69, 95% CI 1.54-4.71). Conclusions The polygenic growth score has a modest ability to identify fetuses at higher or lower risk for Large for gestational age birth weight in a multiracial cohort from the United States. Polygenic growth score could assist with identification of those fetuses at increased risk for LGA birth weight among individuals with a BMI ≥35 kg/m 2 , which may allow for targeted interventions such as dietary and lifestyle modifications to optimize the in-utero environment.
A network perspective on the evolution of hybrid incompatibilities
bioRxiv (Cold Spring Harbor Laboratory) · 2025-07-15 · 1 citations
preprintOpen accessSenior authorCorrespondingAbstract Theory predicts that hybrid incompatibilities accumulate faster than linearly with genetic divergence, a phenomenon known as the snowball effect. While this prediction is mathematically robust under simplifying assumptions, accumulating evidence suggests that the structure of gene interaction networks can alter both the rate and organization of incompatibility evolution. Here, we extend classic DMI models with a network approach, equating the assumptions of the Orr model with a complete graph of gene interactions. We simulate the evolution of hybrid incompatibilities under different gene interaction networks and evaluate the effects of network density, topology, and substitution model. We find that network density strongly governs the rate of DMI accumulation, particularly under models permitting multiple substitutions per locus, while network topology shapes the agglomeration of incompatibilities into large, connected clusters. Substitution rate heterogeneity, especially when anti-correlated with node degree, further suppresses both accumulation and clustering. These results highlight that while the snowball effect remains qualitatively valid, the structure and evolution of the incompatibility network exhibit nontrivial departures from previous expectations, with implications for observable quantities in empirical systems. Our findings underscore the importance of incorporating genomic architecture and network constraints into models of speciation.
2025-02-27
preprintOpen accessnot-yet-known not-yet-known not-yet-known unknown Objective: Maternal genotypes may be useful to customize fetal growth assessment, but generalizability across diverse racial and ancestral groups remains uncertain. We assessed the generalizability of a genetic risk score for birth weight (GRS BW), derived from European ancestry participants, within a diverse U.S. cohort. Design: Secondary analysis of a prospective observational cohort of nulliparous patients. Setting: Eight U.S. recruitment centers. Population or Sample: Participants in the parent study with available maternal DNA. Methods: We used log-linear modeling to test the association of maternal GRS BW with fetal weight. We then assessed the robustness of the association by self-identified race and genetically predicted continental ancestry (GPA) groups. Main Outcome Measures: Association between GRS BW and fetal weight. Results: Among 8,147 eligible participants, GRS BW was associated with fetal weight (p<0.001). Across self-identified racial groups, the association was significant in White (p=0.007) and multiracial (p=0.03) groups but not in Black, Asian, or unknown race groups (p>0.09 for all). Among GPA groups, the association was significant among European (p=0.001) and American (p=0.02) ancestry groups but not African, East or South Asian, or unknown ancestry (p>0.05 for all). Conclusions: This GRS BW is not generalizable across races, highlighting the need for globally representative genetic discovery cohorts.
Recent grants
Computational tools and quantitative analyses of genome structure evolution
NIH · $1.5M · 2022–2027
Frequent coauthors
- 28 shared
C. Brandon Ogbunugafor
Yale University
- 26 shared
Matthew W. Hahn
- 22 shared
David M. Haas
- 14 shared
Predrag Radivojac
Northeastern University
- 12 shared
Samuel V. Scarpino
Northeastern University
- 10 shared
Uma M. Reddy
Cornell University
- 10 shared
Judith H. Chung
UC Irvine Health
- 10 shared
Robert M. Silver
University of Utah
Labs
Not provided
Education
- 2013
PhD Biology, Integrative Biology
University of Texas at Austin
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