Ryan D. Hernandez

Promoting diversity in the scientific workforce is crucial for harnessing the potential of available talent and ensuring equitable access to Science, Technology, Engineering, Mathematics, and Medicine (STEM-M) careers. We have developed an innovative program called Postbaccalaureate Research Opportunity to Promote Equity in Learning (PROPEL) that provides scientific and career development training for postbaccalaureate scholars from historically excluded backgrounds in STEM-M fields with an interest in pursuing a PhD or MD/PhD degree. Our program is distinct from other postbaccalaureate programs in that scholars are hired by individual labs rather than funded centrally by the program. This funding mechanism removes the idea that central funding is necessary to encourage faculty to train diverse scholars and allows the program to scale dynamically according to the needs of the scientific community. The PROPEL program started in 2020 with six scholars and has since grown to an enrollment of over 100, making it the largest postbaccalaureate program for biomedical research in the country. Here, we describe the program structure and curriculum, our strategy for recruitment, the enrollment trends, the program demographics, metrics of scholar engagement, and outcomes for scholars who completed the program in 2023. Our experience demonstrates the strong demand from both scholars and faculty for programming of this type and describes the feasibility of implementation.

Background Large-scale family pedigrees are commonly used across medical, evolutionary, and forensic genetics. These pedigrees are tools for identifying genetic disorders, tracking evolutionary patterns, and establishing familial relationships via forensic genetic identification. However, there is a lack of software to accurately simulate different pedigree structures along with genomes corresponding to those individuals in a family pedigree. This limits simulation-based evaluations of methods that use pedigrees. Results We have developed a python command-line-based tool called py_ped_sim that facilitates the simulation of pedigree structures and the genomes of individuals in a pedigree. py_ped_sim represents pedigrees as directed acyclic graphs, enabling conversion between standard pedigree formats and integration with the forward population genetic simulator, SLiM. Notably, py_ped_sim allows the simulation of varying numbers of offspring for a set of parents, with the capacity to shift the distribution of sibship sizes over generations. We additionally add simulations for events of misattributed paternity, which offers a way to simulate half-sibling relationships. We validated the accuracy of our software by simulating genomes onto diverse family pedigree structures, showing that the estimated kinship coefficients closely approximated expected values. Conclusions py_ped_sim is a user-friendly and open-source solution for simulating pedigree structures and conducting pedigree genome simulations. It empowers medical, forensic, and evolutionary genetics researchers to gain deeper insights into the dynamics of genetic inheritance and relatedness within families.

Total Parenteral Nutrition (TPN), which uses intravenous administration of nutrients, minerals and vitamins, is essential for sustaining premature infants until they transition to enteral feeds, but there is limited information on metabolomic differences between infants on TPN and enteral feeds. We performed untargeted global metabolomics on urine samples collected between 23–30 days of life from 314 infants born p < 0.05. Of these, 88% were in the direction of higher abundance in the urine of infants on enteral feeds. In a subset of infants in a longitudinal analysis, both concurrent and delayed changes in metabolite levels were observed with the initiation of enteral feeds. These infants had higher concentrations of essential amino acids, lipids, and vitamins, which are necessary for growth and development, suggesting the nutritional benefit of an enteral feeding regimen.

Total Parenteral Nutrition (TPN), which uses intravenous administration of nutrients, minerals and vitamins, is essential in sustaining premature infants until they transition to enteral feeds. There is limited information on metabolomic differences between infants on TPN and enteral feeds. We performed untargeted global metabolomics on urine samples collected between 23-30 days of life from 314 infants born <29 weeks gestational age from the TOLSURF and PROP cohorts. Principal component analysis across all metabolites showed a separation of infants solely on TPN as compared to infants who had transitioned to enteral feeds, indicating global metabolomic differences between infants based on feeding status. Among 913 metabolites that passed quality control filters, 609 varied in abundance between infants on TPN vs enteral feeds at p<0.05. Of these, 88% were in the direction of higher abundance in the urine of infants on enteral feeds. In a subset of infants with longitudinal analysis, both concurrent and delayed changes in metabolite levels were observed with initiation of enteral feeds. Infants on enteral feeds had higher concentrations of essential amino acids, lipids, and vitamins, which are necessary for growth and development, suggesting a nutritional benefit of an enteral feeding regimen.

Background and Objectives The B cell–depleting anti-CD20 antibody ocrelizumab (OCR) effectively reduces MS disease activity and slows disability progression. Given the role of B cells as antigen-presenting cells, the primary goal of this study was to evaluate the effect of OCR on the T-cell receptor repertoire diversity. Methods To examine whether OCR substantially alters the molecular diversity of the T-cell receptor repertoire, deep immune repertoire sequencing (RepSeq) of CD4⁺ and CD8⁺ T-cell receptor β-chain variable regions was performed on longitudinal blood samples. The IgM and IgG heavy chain variable region repertoire was also analyzed to characterize the residual B-cell repertoire under OCR treatment. Results Peripheral blood samples for RepSeq were obtained from 8 patients with relapsing MS enrolled in the OPERA I trial over a period of up to 39 months. Four patients each were treated with OCR or interferon β1-a during the double-blind period of OPERA I. All patients received OCR during the open-label extension. The diversity of the CD4⁺/CD8⁺ T-cell repertoires remained unaffected in OCR-treated patients. The expected OCR-associated B-cell depletion was mirrored by reduced B-cell receptor diversity in peripheral blood and a shift in immunoglobulin gene usage. Despite deep B-cell depletion, longitudinal persistence of clonally related B-cells was observed. Discussion Our data illustrate that the diversity of CD4⁺/CD8⁺ T-cell receptor repertoires remained unaltered in OCR-treated patients with relapsing MS. Persistence of a highly diverse T-cell repertoire suggests that aspects of adaptive immunity remain intact despite extended anti-CD20 therapy. Trial Registration Information This is a substudy (BE29353) of the OPERA I (WA21092; NCT01247324) trial. Date of registration, November 23, 2010; first patient enrollment, August 31, 2011.

Gauging the spectrum of human mutations: It has become increasing clear that mutation affects phenotypic variation and disease risk across humans. However, there are many different types of mutation. Seplyarskiy et al . applied a matrix factorization method to large human genomic datasets to identify germline mutational processes in an unsupervised manner. From this survey, nine robust mutational components were identified and specific mechanisms generating seven of these processes are proposed from correlations with genomic features. These results confirm and improve upon our understanding of mutational processes and reveal likely mechanisms of mutation in the human genome. —LMZ

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)¹. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

People in the Americas represent a diverse continuum of populations with varying degrees of admixture among African, European, and Amerindigenous ancestries. In the United States, populations with non-European ancestry remain understudied, and thus little is known about the genetic architecture of phenotypic variation in these populations. Using genotype data from the Hispanic Community Health Study/Study of Latinos, we find that Amerindigenous ancestry increased by an average of ~20% spanning 1940s-1990s in Mexican Americans. These patterns result from complex interactions between several population and cultural factors which shaped patterns of genetic variation and influenced the genetic architecture of complex traits in Mexican Americans. We show for height how polygenic risk scores based on summary statistics from a European-based genome-wide association study perform poorly in Mexican Americans. Our findings reveal temporal changes in population structure within Hispanics/Latinos that may influence biomedical traits, demonstrating a need to improve our understanding of admixed populations.

Cutimycin, a thiopeptide antibiotic produced by the skin commensal Cutibacterium acnes , reduces Staphylococcus colonization of human skin hair follicles.

Neutral genetic diversity across the genome is determined by the complex interplay of mutation, demographic history, and natural selection. While the direct action of natural selection is limited to functional loci across the genome, its impact can have effects on nearby neutral loci due to genetic linkage. These effects of selection at linked sites, referred to as genetic hitchhiking and background selection (BGS), are pervasive across natural populations. However, only recently has there been a focus on the joint consequences of demography and selection at linked sites, and some empirical studies have come to apparently contradictory conclusions as to their combined effects. To understand the relationship between demography and selection at linked sites, we conducted an extensive forward simulation study of BGS under a range of demographic models. We found that the relative levels of diversity in BGS and neutral regions vary over time and that the initial dynamics after a population size change are often in the opposite direction of the long-term expected trajectory. Our detailed observations of the temporal dynamics of neutral diversity in the context of selection at linked sites in nonequilibrium populations provide new intuition about why patterns of diversity under BGS vary through time in natural populations and help reconcile previously contradictory observations. Most notably, our results highlight that classical models of BGS are poorly suited for predicting diversity in nonequilibrium populations.