Functional genomics

Slide contains the information about functional genomics

1. FUNCTIONAL GENOMICS DEEPALI DASH 02/PP/Ph. D/17 Dept. Of Plant Physiology

2. Genomics is the field of genetics that attempt to understand the content, organisation , function and evolution of genetic information contained in whole genome. GENOMICS Types of genomic s: Structural genomics : Structural Genomics  is a worldwide effort aimed at determining the three-dimensional  structures  of gene products in an efficient and high-throughput mode.  Comparative genomics : Comparative genomics  is a field of biological research in which the  genomic  features of different organisms are compared . The  genomic  features may include the DNA sequence, genes, gene order, regulatory sequences, and other  genomic  structural landmarks Functional genomics : Functional genomics is the worldwide experimental approach to access the function of gene by making use of information and reagent provided by structural genomics. - Hieter & Boguski 1997

3. Functional Genomics Approaches Transcriptomics Proteomics Metabolomics Interactomics Epigenetics Nutrigenomics

4. Functional Genomics Approaches Transcriptomics : Transcriptomics studies measure gene expression at the transcript or RNA level. Proteomics : Proteomics approaches focus on which proteins are expressed in a biological system but may also include studies of protein structure.   Metabolomics : Metabolomics is the study of all metabolites in a biological system Interactomics : Together, transcriptomics , proteomics, metabolomics describe the transcripts, proteins and metabolites of a biological system and expected to provide a complete model of the biological systems being studied.

5. Interactomics , is of specific relevance to agriculture systems, particularly in understanding disease . Interactomics is the study of the molecular interactions and encompasses host– pathogen interactions 5. Epigenetics : Epigenetics studies non-heritable changes in the genome (e.g., DNA methylation and histone modification) that affects observed phenotypes. 6. Nutrigenomics :. Nutrigenomics (or ‘nutritional genomics’) focuses on understanding how diet affects gene expression. Conti…

6. Transcription profiling This is one of the most popular study types, also known as 'expression profiling '. It involves the quantification of gene expression of many genes in cells or tissue samples at the transcription (RNA) level . The quantification can be done by collecting biological samples and extracting RNA (in most cases, total RNA) following a treatment or at fixed time-points in a time-series, thereby creating 'snap-shots' of expression patterns. Branches of Functional Genomics

7. Fig. schematic transcription profiling process

8. Genotyping Genotyping studies are those which identify differences in the DNA sequence ( i.e genotype) of a sample. with the aim of identifying differences in the genotype which may explain the difference in phenotype . Genotyping studies can be designed to identify DNA sequence differences at three levels: Single nucleotide polymorphisms  (SNPs, pronounced ‘snips’): SNP analysis focuses on differences in the DNA sequence at the single nucleotide level. Example:  SNP-profiling of plasma DNA in breast cancer patients

9. Copy number variations  (CNVs): CNVs refer to an increase or decrease in the number of copies of a segment of DNA (e.g. a gene, or a locus-specific DNA repeat element). Each 'copy' can be as short as 50 bases or up to 100 kilo bases. Example:  A genome-wide copy number variant study of suicidal behavior Structural variations : they are an order of magnitude larger than CNVs and often cover megabases of DNA . Example:  Transcription profiling by high throughput sequencing of different maize lines to discover and characterise 'presence-absence variation' in the maize genome Conti…

10. Epigenetic profiling Epigenetics is the study of how biochemical modifications or physical interaction of DNA/chromatin affect gene regulation in a cell. At the DNA level,  methylation  of  CpG dinucleotides  (often located near gene promoters) can be detected by first converting unmethylated cytosines into  uracil using bisulfite , which allows methylated and unmethylated cytosines to be distinguished. . Example : Quantitative sequencing of 5-methylcytosine and 5-hydroxymethylcytosine

11. DNA/RNA-protein interactions Transcription factors, ribosomes and other DNA/RNA-binding proteins can bind to nucleic acid sequences and influence the transcription and translation of genes . The immunoprecipitation technique has also been applied to study protein binding sites on RNA.

12. Meta-analysis Meta-analysis is a branch of functional genomics in which data from pre-existing experiments is combined to create statistically more powerful models of a biological process . This type of analyses has become popular as it allows the identification of subtle events that could not be detected in smaller studies. Functional genomics databases such as  ArrayExpress  and  Expression Atlas  play an important role in these studies as reliable, well annotated sources of functional genomics data. Example :  Genome-wide analysis of over 106,000 individuals identifies 9 neuroticism-associated loci

13. Techniques in Functional Genome Analysis 1.Classical techniques and tools Inserstional mutagenesis : Insertional mutagenesis  is  mutagenesis  of DNA by the  insertion  of one or more bases.  e.g. Transposons and T- DNA tagging Sequence based mutagenesis : It is a molecular biology method that is used to make specific and intentional changes to the DNA  sequence  of a gene. e.g. Physical and chemical mutagenesis Tarrget gene mutagenesis : Homologous recombination  can be used to produce specific mutation in an organism. Vector containing DNA sequence similar to the gene to be modified is introduced to the cell, and by a process of recombination replaces the target gene in the chromosome. e.g. RNAi , Sense and antisense expression

14. 2. Mordern techniques and tools sequence based approaches EST SAGE b. microarray based approaches

15. Expressed sequence tags ESTs are short sequences of cDNA typically 200-400 nucleotides in length. Obtained from either 5’ end or 3’ end of cDNA inserts of cDNA library. DRAWBACKS OF USING E.S.T • Automatically generated without verification thus contain high error rates. • There is often contamination by vector sequence , introns , ribosomal RNA, mitochondrial RNA. • ESTs represent only partial sequences of genes. ADVANTAGES OF E.S.T • Provide a rough estimate of genes that are actively expressed in a genome under a particular physiological condition. • Help in discovering new genes, due to random sequencing of cDNA clones. • EST libraries can be easily generated

16. EST INDEX CONSTRUCTION “A collection of nonredundant and annotated EST sequence is known as gene index construction STEPS INVOLVED Remove vector contaminants masks repeats using Vecscreen Clustering (associates EST sequences with unique genes) Derive consensus sequences results in longer contigs Coding region is defined by excluding introns and 3’- untranslated sequences. coding sequence translated into protein sequence Alignment of these complied ESTs with genomic sequence

17. Microarray based approaches A microarray is a pattern of ssDNA probes which are immobilized on a surface called a chip or a slide . • Microarrays use hybridization to detect a specific DNA or RNA in a sample. • DNA microarray uses a million different probes, f ixed on a solid surface. • Microarray technology evolved from Southern blotting. • To analyze the expression of thousands of genes in single reaction , very quickly and in an efficient manner.

18. Application of Functional Genomics