2022 Association of Professors of Human and Medical Genetics (APHMG) consensus-based update of the core competencies for undergraduate medical education in genetics and genomics.

PURPOSE: The field of genetics and genomics continues to expand at an unprecedented pace. As scientific knowledge is translated to clinical practice, genomic information is routinely being used in preventive, diagnostic, and therapeutic decision-making across a variety of clinical practice areas. As adoption of genomic medicine further evolves, health professionals will be required to stay abreast of new genetic discoveries and technologies and implementation of these advances within their scope of practice will be indicated. METHODS: The Association of Professors of Human and Medical Genetics previously developed medical school genetics core competencies, last updated in 2013. The competencies were reviewed and updated through a structured approach incorporating a modified Delphi method. RESULTS: The updated Association of Professors of Human and Medical Genetics core competencies are presented. Current revisions include competencies that are concise, specific, and assessable. In addition, they incorporate recent advances in clinical practice and promote equity and inclusion in clinical care. CONCLUSION: The 2022 competencies will serve as a guide for medical school leadership and educators involved in curriculum development, implementation, and assessment. Use of these competencies across the undergraduate medical curricula will foster knowledge, skills, and behaviors required in medical practice across a wide range of specialties.

Two accurate sequence, structure, and phylogenetic template-based RNA alignment systems.

BACKGROUND: The analysis of RNA sequences, once a small niche field for a small collection of scientists whose primary emphasis was the structure and function of a few RNA molecules, has grown most significantly with the realizations that 1) RNA is implicated in many more functions within the cell, and 2) the analysis of ribosomal RNA sequences is revealing more about the microbial ecology within all biological and environmental systems. The accurate and rapid alignment of these RNA sequences is essential to decipher the maximum amount of information from this data. METHODS: Two computer systems that utilize the Gutell lab's RNA Comparative Analysis Database (rCAD) were developed to align sequences to an existing template alignment available at the Gutell lab's Comparative RNA Web (CRW) Site. Multiple dimensions of cross-indexed information are contained within the relational database--rCAD, including sequence alignments, the NCBI phylogenetic tree, and comparative secondary structure information for each aligned sequence. The first program, CRWAlign-1 creates a phylogenetic-based sequence profile for each column in the alignment. The second program, CRWAlign-2 creates a profile based on phylogenetic, secondary structure, and sequence information. Both programs utilize their profiles to align new sequences into the template alignment. RESULTS: The accuracies of the two CRWAlign programs were compared with the best template-based rRNA alignment programs and the best de-novo alignment programs. We have compared our programs with a total of eight alternative alignment methods on different sets of 16S rRNA alignments with sequence percent identities ranging from 50% to 100%. Both CRWAlign programs were superior to these other programs in accuracy and speed. CONCLUSIONS: Both CRWAlign programs can be used to align the very extensive amount of RNA sequencing that is generated due to the rapid next-generation sequencing technology. This latter technology is augmenting the new paradigm that RNA is intimately implicated in a significant number of functions within the cell. In addition, the use of bacterial 16S rRNA sequencing in the identification of the microbiome in many different environmental systems creates a need for rapid and highly accurate alignment of bacterial 16S rRNA sequences.

An Accurate Scalable Template-based Alignment Algorithm.

The rapid determination of nucleic acid sequences is increasing the number of sequences that are available. Inherent in a template or seed alignment is the culmination of structural and functional constraints that are selecting those mutations that are viable during the evolution of the RNA. While we might not understand these structural and functional, template-based alignment programs utilize the patterns of sequence conservation to encapsulate the characteristics of viable RNA sequences that are aligned properly. We have developed a program that utilizes the different dimensions of information in rCAD, a large RNA informatics resource, to establish a profile for each position in an alignment. The most significant include sequence identity and column composition in different phylogenetic taxa. We have compared our methods with a maximum of eight alternative alignment methods on different sets of 16S and 23S rRNA sequences with sequence percent identities ranging from 50% to 100%. The results showed that CRWAlign outperformed the other alignment methods in both speed and accuracy. A web-based alignment server is available at http://www.rna.ccbb.utexas.edu/SAE/2F/CRWAlign.

Statistical potentials for hairpin and internal loops improve the accuracy of the predicted RNA structure.

RNA is directly associated with a growing number of functions within the cell. The accurate prediction of different RNA higher-order structures from their nucleic acid sequences will provide insight into their functions and molecular mechanics. We have been determining statistical potentials for a collection of structural elements that is larger than the number of structural elements determined with experimentally determined energy values. The experimentally derived free energies and the statistical potentials for canonical base-pair stacks are analogous, demonstrating that statistical potentials derived from comparative data can be used as an alternative energetic parameter. A new computational infrastructure-RNA Comparative Analysis Database (rCAD)-that utilizes a relational database was developed to manipulate and analyze very large sequence alignments and secondary-structure data sets. Using rCAD, we determined a richer set of energetic parameters for RNA fundamental structural elements including hairpin and internal loops. A new version of RNAfold was developed to utilize these statistical potentials. Overall, these new statistical potentials for hairpin and internal loops integrated into the new version of RNAfold demonstrated significant improvements in the prediction accuracy of RNA secondary structure.

Correlation of RNA secondary structure statistics with thermodynamic stability and applications to folding.

The accurate prediction of the secondary and tertiary structure of an RNA with different folding algorithms is dependent on several factors, including the energy functions. However, an RNA higher-order structure cannot be predicted accurately from its sequence based on a limited set of energy parameters. The inter- and intramolecular forces between this RNA and other small molecules and macromolecules, in addition to other factors in the cell such as pH, ionic strength, and temperature, influence the complex dynamics associated with transition of a single stranded RNA to its secondary and tertiary structure. Since all of the factors that affect the formation of an RNAs 3D structure cannot be determined experimentally, statistically derived potential energy has been used in the prediction of protein structure. In the current work, we evaluate the statistical free energy of various secondary structure motifs, including base-pair stacks, hairpin loops, and internal loops, using their statistical frequency obtained from the comparative analysis of more than 50,000 RNA sequences stored in the RNA Comparative Analysis Database (rCAD) at the Comparative RNA Web (CRW) Site. Statistical energy was computed from the structural statistics for several datasets. While the statistical energy for a base-pair stack correlates with experimentally derived free energy values, suggesting a Boltzmann-like distribution, variation is observed between different molecules and their location on the phylogenetic tree of life. Our statistical energy values calculated for several structural elements were utilized in the Mfold RNA-folding algorithm. The combined statistical energy values for base-pair stacks, hairpins and internal loop flanks result in a significant improvement in the accuracy of secondary structure prediction; the hairpin flanks contribute the most.

Gestational ethanol exposure disrupts the expression of FGF8 and Sonic hedgehog during limb patterning.

BACKGROUND: Ethanol is known to induce a wide variety of gestational anomalies, including skeletal malformations. Gestational ethanol exposure in mice has been shown to induce postaxial digit loss (ectrodactyly). How ethanol induces limb malformations is not understood. To better understand how ethanol effects limb development, we have utilized a transgenic line of mice that expresses beta-galactosidase in the apical ectodermal ridge (AER) of the limbs throughout gestation. METHODS: Pregnant female mice were injected with 2.9, 3.4, or 3.9 gm/kg ethanol at E9.3 and E9.5; embryos were isolated at E11.25, stained for beta-galactosidase activity, and evaluated for AER defects. Based upon the pattern of defects seen, expression of FGF8 in the AER and Sonic hedgehog in the postaxial mesoderm was evaluated by in situ hybridization. RESULTS: Two distinct phenotypes were seen in response to ethanol that were dose dependent. At 2.9 gm/kg ethanol, the most prevalent phenotype was a mislocalization of the AER to regions both dorsal and ventral to the midline. A higher dosage of 3.4 gm/kg ethanol did not increase the mislocalization phenotype, but resulted in a higher frequency of postaxial loss of the AER and associated mesenchymal tissue. The highest dosage utilized (3.9 gm/kg) resulted in a high frequency of both preaxial and postaxial loss of the AER. Through in situ hybridization, we found that ethanol exposure resulted in a concomitant reduction in FGF8 expression in the AER and Sonic hedgehog expression from the zone of polarizing activity (ZPA). CONCLUSIONS: We propose a model where ethanol disrupts the AER/ZPA positive feedback loop to induce postaxial malformations. Preaxial malformations seen at higher ethanol dosage suggest FGF8 as a critical target of ethanol in producing limb defects.