Molecular Techniques
Molecular techniques are methods employed in molecular biology, genetics, biochemistry, and biophysics to manipulate and analyze nucleic acids (deoxyribonucleic acid (DNA) and ribonucleic acid (RNA)), protein, and lipids. Techniques in molecular biology are employed to investigate the molecular basis for biological activity. These techniques are used to analyze cellular properties, structures, and chemical reactions, with a focus on how certain molecules regulate cellular reactions and growth.
DNA Fingerprinting and Gel Electrophoresis
The genetic makeup of living organisms is shown by a technique known as DNA fingerprinting. The difference is the satellite region of DNA is shown by this process. Alex Jeffreys has invented the process of DNA fingerprinting in 1985. Any biological samples such as blood, hair, saliva, semen can be used for DNA fingerprinting. DNA fingerprinting is also known as DNA profiling or molecular fingerprinting.
Molecular Markers
A known DNA sequence or gene sequence is present on a chromosome, and it is associated with a specific trait or character. It is mainly used as a genetic marker of the molecular marker. The first genetic map was done in a fruit fly, using genes as the first marker. In two categories, molecular markers are classified, classical marker and a DNA marker. A molecular marker is also known as a genetic marker.
DNA Sequencing
The most important feature of DNA (deoxyribonucleic acid) molecules are nucleotide sequences and the identification of genes and their activities. This the reason why scientists have been working to determine the sequences of pieces of DNA covered under the genomic field. The primary objective of the Human Genome Project was to determine the nucleotide sequence of the entire human nuclear genome. DNA sequencing selectively eliminates the introns leading to only exome sequencing that allows proteins coding.
![Ruminococcaceae (%)
PC2: 9.32% Variance
0.2
0.0
C
-0.40.4
1.00-
Actinobacteria (%)
0.75-
0.50
0.25
-0.2
0.0
Condition
Hothy
Cromar
1000-
0.2
0.4
PC1: 13.8 % Variance
0.00
Healthy
CF
60-
20-
Healthy
CF
Sutterella (%)
Butyricimonas (%)
20
15.
10-
Alpha Diversity (Chao1)
800-
600
400
Healthy
CF
Таха
Acidaminococcus
Clostridium
Tissierellaceae-
Vellonella-
Clostridiaceae-
Fusobacteriaceae-
Fusobacteria-
Fusobacteriales-
Streptococcaceae-
Lactobacillales-
Bacill
Firmicutes
Actinobacteria-
Ruminococcacene
Caprococcus
Christensenellaceae-
Barnesiellaceae-
Alcaligenaceae-
Verrucomicrobia
Down in CF
Up in CF
Verrucomicrobiales-
Verrucomicrobiaceae-
Verrucomicrobiae-
Sutterella-
Cyanobacteria-
Deltaproteobacteria-
Butyricimonas-
Bilophila
Phylum
Bacter
Promobacteria
Funclectora
Actinctontwr
Desulfovibrionaceae-
Desulfovibrionales-
D
Healthy
CF
1.00-
Healthy
CF
Actinobacteria (%)
0.75
0.50-
0.25
-3
0
في
Cynobacteris
log2(Fold Change)
0.00-
Healthy
CF(Other)
CFTR Genotype
CF(df508)
Fig. 2 Differences between cystic fibrosis (CF) and healthy gut mucosal microbiota. a (left) Principal coordinate analysis plot based on Bray-Curtis
distance indicating difference in beta-diversity between CF and healthy gut mucosal microbiome. The axes represent the percentage variance
along the first two principal components and the color of samples indicates their mutation status, ie., Healthy, CF (other), and CF (df508); (right)
Boxplot depicting difference in alpha diversity (Chaol metric) between CF and healthy gut microbiome. b Dotplot showing significantly
differentially abundant OTUS (q value <0.1), where OTUS are grouped by genera along the y-axis and colored by phylum. The x-axis indicates the
log2 fold-change in CF compared to healthy as baseline. c Boxplots indicating the percentage relative abundance of taxa showing differential
abundance between CF and healthy gut microbiome (q value <0.1). d Boxplot depicting gradient-like trend in abundance for Actinobacteria for
three genotypes Healthy, CF (other), and CF (df508)
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