Fundamentals of Genomics and Human Genome Projects Study Notes

Background and Foundation of Modern Genetics

• The completion of the Human Genome Project (HGP) in 2003, followed by subsequent genome-wide studies, initiated a new era in human health and disease management.

• These advancements have led to:

  • Increased accuracy in genetic diagnoses.

  • Enhanced understanding of the pathogenesis of inherited conditions.

  • Development of new and improved treatments.

• Impact on Dentistry: Dental health professionals require a greater understanding of genetics to provide better and more personalized patient care in the modern practice landscape.

The Discovery of the Double Helix (1951-1953)

• Structural Characteristics:

  • The DNA molecule is a double helix with two main grooves: the Major groove and the Minor groove.

  • The diameter of the helix is precisely $2\,\text{nm}$.

  • The distance of one full turn in the helix is $3.4\,\text{nm}$.

  • The vertical distance between individual base pairs is $0.34\,\text{nm}$.

• Chemical Composition and Orientation:

  • DNA strands have an antiparallel orientation: one strand runs in the $5' \rightarrow 3'$ direction, while the complementary strand runs $3' \rightarrow 5'$.

  • Nucleotides consist of a sugar-phosphate (S-P) backbone.

  • Bases are categorized as Purines (Adenine, Guanine) and Pyrimidines (Thymine, Cytosine).

  • Base Pairing rules (Hydrogen bonding):

  • Adenine (A) pairs with Thymine (T) via two hydrogen bonds.

  • Guanine (G) pairs with Cytosine (C) via three hydrogen bonds.

The Human Genome Project (1990-2003)

• The HGP was an international scientific research project designed to:

  • Determine the sequence of nucleotide base pairs in human DNA.

  • Identify and map all genes from both a physical and functional standpoint.

• Conceptual Impact (Francis Collins, 2000):

  • Described as a "history book" of the human species journey.

  • A "shop manual" with a detailed blueprint for building every human cell.

  • A "transformative textbook of medicine" to treat, prevent, and cure disease.

• Sampling and Donors:

  • The project utilized 20 volunteers recruited via the Clinical Genetics Service at Roswell Park Cancer Institute (Buffalo, NY).

  • Participants were at least 18 years old and had not undergone chemotherapy.

  • The sequence is a "mosaic" representation rather than a single individual; it is referred to as a "reference genome."

  • Numerical breakdown of donor contributions: $93\%$ of the HGP sequence came from 11 donors, and $70\%$ came from a single donor.

  • Note on "Normalcy": Some researchers advocated for sequencing a "normal" person first, though this was dismissed as it is impossible to define a biologically "normal" human.

• Publication History:

  • Draft sequences were reported on February 15, 2001, in Nature (representing the government/NIH effort) and February 16, 2001, in Science (representing the private company effort).

Achieving a Complete Human Genome Sequence

• The original project took 13 years to produce a sequence of roughly $3.1\,\text{billion}$ base pairs.

• In April 2022, the Telomere-to-Telomere (T2T) consortium published a truly complete sequence in Science.

• The finalized sequence encompasses $3.05\,\text{billion}$ DNA base pairs.

• Important technical caveats:

  • $0.3\%$ of the sequence might still contain errors.

  • The current complete count includes the X chromosome but excludes the Y chromosome.

  • Counts generally exclude mitochondrial DNA.

  • The final 10% of the genome was considered the most difficult to sequence due to its repetitive nature.

Defining Genetics vs. Genomics

• Genetics:

  • Focuses on single genes one at a time.

  • Acts like a "picture" or "snapshot" of specific hereditary units.

• Genomics:

  • Examines the big picture, viewing all genes and the entire genome as an integrated system.

  • Deals with the fact that not all genes are the same length.

  • Acknowledges that $95\%$ of DNA is non-protein-coding (formerly referred to as "junk DNA").

• Formal definition of Genomics: The sub-discipline devoted to sequencing (ordering bases), mapping (determining positions), and functional analysis of whole-genome sequences.

The 'Omics' Hierarchy and Multiomics

• The biological flow of information involves multiple levels of data:

  • DNA (Genotype): Analyzed via SNPs, CNVs, and Microsatellites using re-sequencing and ChIP-chip.

  • mRNA (Transcriptomics): Involves gene expression, microarrays, and splice junction analysis.

  • Protein (Proteomics): Translation products analyzed via protein arrays, mass spectrometry, and 2D-gel electrophoresis.

  • Metabolite (Metabolomics): Products of cellular processes analyzed via NMR and mass spectrometry.

  • Phenotype (Phenomics): Observations of clinical phenotypes (disease status) and quantitative traits such as Body Mass Index ($BMI$) and blood pressure.

• NIH Multiomics Consortium:

  • Announced Sept 12, 2023.

  • Awarded $50.3\,\text{million}$ over five years.

  • Goal: Use high-throughput molecular assays to generate molecular profiles of disease and non-disease states through integrated data (genomic, epigenomic, transcriptomic, etc.).

The Economics of Genomic Technology

• Sequencing costs have plummeted drastically since 2001.

• Cost Timeline:

  • 2001: Approximately $100\,\text{million}$.

  • 2015: Under $1,000$.

  • 2020: Illumina launched the NovaSeq 6000 v1.5 kit, introducing the "$\$600$ genome."

  • 2024: Ultima Genomics announced high-end sequencers intended to read a genome for as little as "$\$100$."

• Comparison to Moore's Law: While Moore's Law suggests computational power doubles every 12 to 18 months, the drop in sequencing costs has significantly outpaced this trend.

Single Nucleotide Polymorphisms (SNPs) and Haplotypes

• SNPs (Single Nucleotide Polymorphisms):

  • The most important and common type of genetic variation.

  • Consists of single-nucleotide point mutations.

  • Occur approximately every $1,000$ base pairs.

  • Most are biallelic (meaning they have only two possible alleles, such as A or G), though some can have three or four.

  • Serve as markers for disease and help find a "handful" of relevant variants instead of checking the entire genome.

• Haplotypes:

  • Groups of SNPs that are linked (close together on the same chromosome) and inherited together.

  • Examples from population studies include:

  • Haplotype 1: $35\%$

  • Haplotype 2: $30\%$

  • Haplotype 3: $15\%$

  • Haplotype 4: $10\%$

Diversity in Global Genome Projects

• 1000 Genomes Project:

  • Aimed to find common genetic variants with frequencies of at least $1\%$ in populations.

  • Final data set: 2,504 individuals from 26 populations.

• Genome Aggregation Database (gnomAD v3):

  • Contains 76,156 genomes of diverse ancestries.

  • Major represented groups: Non-Finnish European (34,029), African/African American (20,744), Latino/Admixed American (7,647), Finnish (5,316).

• Ancestry Bias in Research:

  • Genome-wide association studies (GWAS) are heavily skewed.

  • European: $78.4\%$

  • Asian: $10.2\%$

  • African: $2\%$

  • Other: $9.4\%$

• Targeted Diversity Projects:

  • African Genome Variation Project: 1,481 individuals from 18 ethno-linguistic groups in sub-Saharan Africa.

  • Nigerian 100K Genome Project: Focuses on 200 ethnic groups and 500 different languages to capture the high genetic diversity in Africa.

Functional and Phenotypic Mapping

• ENCODE Project (Encyclopedia of DNA Elements):

  • Goal: Build a comprehensive "parts list" of functional elements.

  • Includes regulatory elements (promoters, enhancers, repressors/silencers, insulators) that control gene activity.

• NIH Gene Function Initiative (Sept 27, 2022):

  • Goal: Systematically establish the function of every human gene.

  • Current Status: We currently only know the function of approximately $3,000$ out of $20,000$ protein-coding genes.

• Human Phenotype Project (HPP):

  • Focuses on deep phenotyping along the health-disease continuum.

  • Profiling includes longitudinal data: medical history, nutrition, anthropometrics, continuous glucose monitoring, microbiome (gut, vaginal, and oral), and immune profiling.

  • Aims to advance precision medicine by exploring variations in disease susceptibility and aging.

Study Methodologies: GWAS vs. PheWAS

• GWAS (Genome-Wide Association Study):

  • Direction: Trait/Disease $\rightarrow$ Gene Variant.

  • Approach: Starts with a specific disease trait (e.g., cardiovascular disease) in a case-control study and scans markers to find associated variants (e.g., Variant A).

• PheWAS (Phenome-Wide Association Study):

  • Direction: Gene Variant $\rightarrow$ Phenome (all traits).

  • Approach: Starts with a specific gene variant (e.g., Variant A) and looks across the entire phenome to see which diseases or traits (respiratory, cardiovascular, etc.) it correlates with.

Synthetic Genomics

• Researchers in the UK are working toward creating the first synthetic human chromosome.

• Writing large genomes chemically has potentials in:

  • Developing cell therapies for diseased individuals.

  • Creating climate-resistant crops.

  • Transformative understanding of human health.

Questions & Discussion

• Questions for consideration in the field of genomics:

  • How do we synthesize omics data to understand disease?

  • How do we move from phenome data to link it back to the genome?

  • What are the implications of newly synthetic or artificial sequences?

Thought for the Day

• "The meaning of life is to find your gift. The purpose of life is to give it away." (Pablo Picasso)