Discuss the methods Mendel utilized in his research that led to his success in understanding the process of inheritance
The science community ignored the paper, possibly because it was ahead of the ideas of heredity and variation accepted at the time. In the early 1900s, 3 plant biologists finally acknowledged Mendel’s work. Unfortunately, Mendel was not around to receive the recognition as he had died in 1884.
Discuss the methods Mendel utilized in his research that led to his success in understanding the process of inheritance
The science community ignored the paper, possibly because it was ahead of the ideas of heredity and variation accepted at the time. In the early 1900s, 3 plant biologists finally acknowledged Mendel’s work. Unfortunately, Mendel was not around to receive the recognition as he had died in 1884.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
3. Gregor Mendel
Born in 1822 in
Czechoslovakia.
Became a monk at
a monastery in
1843.
Taught biology and
had interests in
statistics.
Also studied at the
University of Vienna
4. Mendel continued
Most famous for his
work with pea plants
Between 1856 and
1863 he grew and
tested over 28,000
pea plants
(That’s what he is
contemplating so
seriously in the
picture)
5. Why Peas?
Easy to grow.
Easily identifiable
traits
Trait – a specific
characteristic
Can work with large
numbers of samples
6. Mendel’s experiments
The first thing Mendel did was
create a “pure” plant or true-
breeding plant.
True breeding – If the parent repeatedly
only produce offspring with the same trait
• For example: A plant
true-breeding for
purple flowers will
always produce
offspring with purple
flowers.
7. Mendel’s experiments
What happens if you cross two
plants which are true-breeding for
contrasting traits???
purple flowers x white flowers
wrinkled seeds x smooth seeds
tall plants x short plants
etc, etc, etc,
8. Mendel’s experiments
He always found the
same pattern
He discovered that
even though one of the
parent plants had white
flowers, ALL of the
offspring had purple
flowers!
True-breeding parents
Hybrids
9. Mendel’s experiments
Mendel repeated this experiment with
other traits, in every case, one trait
“won out”
For example: Purple flower color “won out”
over white flower color. Smooth seed texture
“won out” over wrinkled seed texture.
10. Mendel’s experiments
Mendel called the trait that
“won out” in the offspring
dominant (purple flowers) .
He called the trait that
dissappeared in the offspring
recessive (white flowers) .
11. Mendel’s experiments
What would happen when
Mendel let the offspring self-
pollinate? Was the next
generation true-breeding for
the dominant trait?
Would Mendel continue to see
only purple flowers?
13. From his experiments, Mendel
concluded two things
1. Inheritance is determined by factors
passed on from one generation to
another.
Today these “factors” are called genes, but
Mendel knew nothing about chromosomes,
genes or DNA because there terms hadn’t
been identified yet
Allele – difference forms of a gene
14. From his experiments, Mendel
concluded two things
2. Some alleles are dominant while
other are recessive.
• An organism with a dominant allele for
a trait will always express that allele.
• An organism with a recessive allele for
a trait will express that form only when
the dominant allele is not present.
15. Which led him to create to
“laws” of inheritance
1. The Law of Segregation: Two
factors (alleles) control each
specific characteristic (gene).
These factors (alleles) are
separated during the formation of
gametes (sex cells).
16. Which led him to create to
“laws” of inheritance
2. The Law of Independent
Assortment: Factors (alleles) for
different characteristics (genes) are
distributed to gametes (sex cells)
independently. This means that the
allele for seed texture isn’t
dependent on the allele for plant
height, etc.
17. Probability
The likelihood of a
particular event
occurring.
Can be expressed as a
fraction, percent or ratio.
The more trials performed, the closer
the actual results to the expected
outcomes.
18. Punnett Square
A diagram used to
show the probability
or chances of a
certain trait being
passed from one
generation to
another.
19. Using a Punnett square
1. Gametes are placed above and
to the left of the square
2. Offspring are placed in the
square.
3. Capital letters represent
dominant alleles. (Y)
4. Lower case letters represent
recessive alleles. (y)
20. Punnett square example
In a cross between PP x Pp. What percent of
the offspring would you expect to be purple?
P = purple, p = white One parent goes here
One
parent
goes
here
21. Let’s do another one…
In a cross between Pp x Pp. What percent of
the offspring would you expect to be white?
P = purple, p = white
22. Dominant – allele, which if present, will
ALWAYS be expressed
Represented by a capital letter, usually the first
letter of the dominant trait
Recessive – allele, which will only be
expressed in the absence of a dominant
allele
Represented by a lowercase letter, the same
letter as the dominant trait, just lowercase
For example: Tall is dominant over short,
T = tall, t = short
23. Homozygous = when an organism
has two identical alleles.
YY or yy
Heterozygous = when an organism
has different alleles.
Yy
24. Genotype
The genetic makeup
Symbolized with letters
For example: Tt or TT
Phenotype
Physical appearance of an organism
Description of the trait
For example: Tall, short, purple, white
25. Some exceptions to
Mendel’s principles:
Some alleles are neither
dominant nor recessive.
Many traits are controlled by
more than one gene (polygenic
traits)
26. Incomplete dominance
A situation in which neither allele is
dominant.
When both alleles are present a “new”
phenotype appears that is a blend of
each allele.
Alleles will be represented by capital
letters only.
28. What happens when a
red flower is crossed
with a white flower?
According to
Mendel either
some white and
some red or all
offspring either
red or white.
All are pink
29. Codominance
When two alleles both appear in the
phenotype.
Usually signified using superscripts.
example: color of hair coat in cattle.
crcr = red hairs
cwcw = white hairs
crcw = roan coat (mixture of both colors)
31. Multiple allele
inheritance
When two or more alleles contribute to
the phenotype.
Human blood types: A,B,O and AB
A and B are codominant to each other.
Both A and B are dominant over O.