Understanding Insulin in the Age of Precision Medicine and Big Data: Under-Explored Nature of Genomics
Insulin is amongst the human genome’s most well-studied genes/proteins due to its connection to metabolic health. Within this article, we review literature and data to build a knowledge base of Insulin (<i>INS</i>) genetics that influence transcription, transcript processing, translation...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
|
| Series: | Biomolecules |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2218-273X/13/2/257 |
| _version_ | 1797622168795742208 |
|---|---|
| author | Taylor W. Cook Amy M. Wilstermann Jackson T. Mitchell Nicholas E. Arnold Surender Rajasekaran Caleb P. Bupp Jeremy W. Prokop |
| author_facet | Taylor W. Cook Amy M. Wilstermann Jackson T. Mitchell Nicholas E. Arnold Surender Rajasekaran Caleb P. Bupp Jeremy W. Prokop |
| author_sort | Taylor W. Cook |
| collection | DOAJ |
| description | Insulin is amongst the human genome’s most well-studied genes/proteins due to its connection to metabolic health. Within this article, we review literature and data to build a knowledge base of Insulin (<i>INS</i>) genetics that influence transcription, transcript processing, translation, hormone maturation, secretion, receptor binding, and metabolism while highlighting the future needs of insulin research. The <i>INS</i> gene region has 2076 unique variants from population genetics. Several variants are found near the transcriptional start site, enhancers, and following the <i>INS</i> transcripts that might influence the readthrough fusion transcript <i>INS–IGF2</i>. This <i>INS–IGF2</i> transcript splice site was confirmed within hundreds of pancreatic RNAseq samples, lacks drift based on human genome sequencing, and has possible elevated expression due to viral regulation within the liver. Moreover, a rare, poorly characterized African population-enriched variant of INS–IGF2 results in a loss of the stop codon. <i>INS</i> transcript UTR variants rs689 and rs3842753, associated with type 1 diabetes, are found in many pancreatic RNAseq datasets with an elevation of the 3′UTR alternatively spliced <i>INS</i> transcript. Finally, by combining literature, evolutionary profiling, and structural biology, we map rare missense variants that influence preproinsulin translation, proinsulin processing, dimer/hexamer secretory storage, receptor activation, and C-peptide detection for quasi-insulin blood measurements. |
| first_indexed | 2024-03-11T09:06:30Z |
| format | Article |
| id | doaj.art-f42c82afc17242ba950f8f97e43dece9 |
| institution | Directory Open Access Journal |
| issn | 2218-273X |
| language | English |
| last_indexed | 2024-03-11T09:06:30Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomolecules |
| spelling | doaj.art-f42c82afc17242ba950f8f97e43dece92023-11-16T19:22:36ZengMDPI AGBiomolecules2218-273X2023-01-0113225710.3390/biom13020257Understanding Insulin in the Age of Precision Medicine and Big Data: Under-Explored Nature of GenomicsTaylor W. Cook0Amy M. Wilstermann1Jackson T. Mitchell2Nicholas E. Arnold3Surender Rajasekaran4Caleb P. Bupp5Jeremy W. Prokop6Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USADepartment of Biology, Calvin University, Grand Rapids, MI 49546, USADepartment of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USADepartment of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USADepartment of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USADepartment of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USADepartment of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USAInsulin is amongst the human genome’s most well-studied genes/proteins due to its connection to metabolic health. Within this article, we review literature and data to build a knowledge base of Insulin (<i>INS</i>) genetics that influence transcription, transcript processing, translation, hormone maturation, secretion, receptor binding, and metabolism while highlighting the future needs of insulin research. The <i>INS</i> gene region has 2076 unique variants from population genetics. Several variants are found near the transcriptional start site, enhancers, and following the <i>INS</i> transcripts that might influence the readthrough fusion transcript <i>INS–IGF2</i>. This <i>INS–IGF2</i> transcript splice site was confirmed within hundreds of pancreatic RNAseq samples, lacks drift based on human genome sequencing, and has possible elevated expression due to viral regulation within the liver. Moreover, a rare, poorly characterized African population-enriched variant of INS–IGF2 results in a loss of the stop codon. <i>INS</i> transcript UTR variants rs689 and rs3842753, associated with type 1 diabetes, are found in many pancreatic RNAseq datasets with an elevation of the 3′UTR alternatively spliced <i>INS</i> transcript. Finally, by combining literature, evolutionary profiling, and structural biology, we map rare missense variants that influence preproinsulin translation, proinsulin processing, dimer/hexamer secretory storage, receptor activation, and C-peptide detection for quasi-insulin blood measurements.https://www.mdpi.com/2218-273X/13/2/257insulingenomic variantsexpressionsplicingprotein foldingprotein processing |
| spellingShingle | Taylor W. Cook Amy M. Wilstermann Jackson T. Mitchell Nicholas E. Arnold Surender Rajasekaran Caleb P. Bupp Jeremy W. Prokop Understanding Insulin in the Age of Precision Medicine and Big Data: Under-Explored Nature of Genomics Biomolecules insulin genomic variants expression splicing protein folding protein processing |
| title | Understanding Insulin in the Age of Precision Medicine and Big Data: Under-Explored Nature of Genomics |
| title_full | Understanding Insulin in the Age of Precision Medicine and Big Data: Under-Explored Nature of Genomics |
| title_fullStr | Understanding Insulin in the Age of Precision Medicine and Big Data: Under-Explored Nature of Genomics |
| title_full_unstemmed | Understanding Insulin in the Age of Precision Medicine and Big Data: Under-Explored Nature of Genomics |
| title_short | Understanding Insulin in the Age of Precision Medicine and Big Data: Under-Explored Nature of Genomics |
| title_sort | understanding insulin in the age of precision medicine and big data under explored nature of genomics |
| topic | insulin genomic variants expression splicing protein folding protein processing |
| url | https://www.mdpi.com/2218-273X/13/2/257 |
| work_keys_str_mv | AT taylorwcook understandinginsulinintheageofprecisionmedicineandbigdataunderexplorednatureofgenomics AT amymwilstermann understandinginsulinintheageofprecisionmedicineandbigdataunderexplorednatureofgenomics AT jacksontmitchell understandinginsulinintheageofprecisionmedicineandbigdataunderexplorednatureofgenomics AT nicholasearnold understandinginsulinintheageofprecisionmedicineandbigdataunderexplorednatureofgenomics AT surenderrajasekaran understandinginsulinintheageofprecisionmedicineandbigdataunderexplorednatureofgenomics AT calebpbupp understandinginsulinintheageofprecisionmedicineandbigdataunderexplorednatureofgenomics AT jeremywprokop understandinginsulinintheageofprecisionmedicineandbigdataunderexplorednatureofgenomics |