This document provides an overview of Chapter 14 from Campbell Biology, Ninth Edition, which discusses Gregor Mendel and his experiments with pea plants that established the basic principles of heredity and genetics. It summarizes Mendel's experimental methods and key findings, including his laws of segregation and independent assortment. It explains how Mendel used controlled crosses and statistical analysis to determine that traits are inherited as discrete units (now known as genes) that segregate and assort independently. Finally, it notes that inheritance patterns are sometimes more complex than predicted by simple Mendelian genetics.
The expression of a single character by the interaction of more than one pair of genes is called the Interaction of genes.
Bateson and Punnet proposed factor hypothesis to explain the Interaction of genes.
The genic interaction is of two types, namely
Non-allelic gene interaction.
Allelic gene interaction.
Basics of Undergraduate/university fellows
Epistasis is a Greek word that means standing over.
BATESON used term epistasis to describe the masking effect in 1909
The term epistasis describes a certain relationship between genes, where an allele of
one gene hides or masks the visible output or phenotype of another gene.
When two different genes which are not alleles, both affect the same character in such
a way that the expression of one masks (inhibits or suppresses) the expression of the
other gene, the phenomenon is said to be epistasis.
The gene that suppresses other gene expression is known as Epistatic gene.
The gene that is suppressed or remain obscure is called Hypostatic gene
The classical phenotypic ratio of 9:3:3:1 F2 ratio becomes modified by epistasis.
This power point presentation is designed to explain deviation of Mendelian dihybrid ratio due to interaction of genes which may be of following types
1.Two gene pairs affecting same character – 9:3:3:1
2.Epistasis, one gene hides effect of other
a) Recessive Epistasis - 9:3:4
b) Dominant epistasis - 12:3:1
3.Complementary genes - 9:7 ( 2 genes responsible for production of a particular phenotype )
4. Duplicate genes – 15:1 ( same effect given by either of two genes )
5. Polymeric gene action - 9:6:1
6. Inhibitory gene action - 13 : 3
Each interaction is typical in itself and ratios obtained are different
The expression of a single character by the interaction of more than one pair of genes is called the Interaction of genes.
Bateson and Punnet proposed factor hypothesis to explain the Interaction of genes.
The genic interaction is of two types, namely
Non-allelic gene interaction.
Allelic gene interaction.
Basics of Undergraduate/university fellows
Epistasis is a Greek word that means standing over.
BATESON used term epistasis to describe the masking effect in 1909
The term epistasis describes a certain relationship between genes, where an allele of
one gene hides or masks the visible output or phenotype of another gene.
When two different genes which are not alleles, both affect the same character in such
a way that the expression of one masks (inhibits or suppresses) the expression of the
other gene, the phenomenon is said to be epistasis.
The gene that suppresses other gene expression is known as Epistatic gene.
The gene that is suppressed or remain obscure is called Hypostatic gene
The classical phenotypic ratio of 9:3:3:1 F2 ratio becomes modified by epistasis.
This power point presentation is designed to explain deviation of Mendelian dihybrid ratio due to interaction of genes which may be of following types
1.Two gene pairs affecting same character – 9:3:3:1
2.Epistasis, one gene hides effect of other
a) Recessive Epistasis - 9:3:4
b) Dominant epistasis - 12:3:1
3.Complementary genes - 9:7 ( 2 genes responsible for production of a particular phenotype )
4. Duplicate genes – 15:1 ( same effect given by either of two genes )
5. Polymeric gene action - 9:6:1
6. Inhibitory gene action - 13 : 3
Each interaction is typical in itself and ratios obtained are different
Gene interaction -Complementary, Supplementary,Dominant Epistasis, Recessive...Nethravathi Siri
Most of the characters of living organisms are controlled/ influenced/ governed by a collaboration of several different genes. • Numerous deviations have been recorded in which different kinds of interactions are possible between the genes.
Epistasis is a Greek word that means standing over .Bateson used it to describe the masking effect in 1909.
An interaction between a pair of loci in which the phenotype effect of one locus depends on the genotype at the second locus.
Genes whose phenotypes are ;
Expressed,epistatic.
Altered or suppressed hypostatic.
It's about for some interactions occurs between two genes and within a gene and how these interactions changed the phenotypic ratios of Mendelian phenotypic ratios.
Gene interactions occur when two or more different genes influence the outcome of a single trait
Epistasis is a phenomenon in which the expression of one gene depends on the presence of one or more modifier genes.
A gene whose phenotype is expressed is called epistatic.
Gene interaction -Complementary, Supplementary,Dominant Epistasis, Recessive...Nethravathi Siri
Most of the characters of living organisms are controlled/ influenced/ governed by a collaboration of several different genes. • Numerous deviations have been recorded in which different kinds of interactions are possible between the genes.
Epistasis is a Greek word that means standing over .Bateson used it to describe the masking effect in 1909.
An interaction between a pair of loci in which the phenotype effect of one locus depends on the genotype at the second locus.
Genes whose phenotypes are ;
Expressed,epistatic.
Altered or suppressed hypostatic.
It's about for some interactions occurs between two genes and within a gene and how these interactions changed the phenotypic ratios of Mendelian phenotypic ratios.
Gene interactions occur when two or more different genes influence the outcome of a single trait
Epistasis is a phenomenon in which the expression of one gene depends on the presence of one or more modifier genes.
A gene whose phenotype is expressed is called epistatic.
KEY CONCEPTS
14.1 Mendel used the scientific approach to identify two laws of inheritance
14.2 Probability laws govern Mendelian inheritance
14.3 Inheritance patterns are often more complex than predicted by simple Mendelian genetics
14.4 Many human traits follow Mendelian patterns of
inheritance
The idea of chromosomal Linkage. It starts with understanding the Mendel's law of segregation and Independent assortment and later discusses why certain traits does not follows 9:3:3:1 ratio as in Mendel's law of Independent assortment. Also briefly covers the Genetic mapping and phenotypic mapping unit.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
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Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
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Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
27. Figure 14.5-2
P Generation
Appearance:
Purple flowers White flowers
Genetic makeup:
pp
PP
p
Gametes:
P
F1 Generation
Appearance:
Genetic makeup:
Gametes:
Purple flowers
Pp
1
1
/2 p
/2 P
28. Figure 14.5-3
P Generation
Appearance:
Purple flowers White flowers
Genetic makeup:
pp
PP
p
Gametes:
P
F1 Generation
Appearance:
Genetic makeup:
Gametes:
Purple flowers
Pp
1
1
/2 p
/2 P
Sperm from F1 (Pp) plant
F2 Generation
Eggs from
F1 (Pp) plant
P
p
PP
Pp
Pp
pp
P
p
3
:1
33. Figure 14.7
TECHNIQUE
Dominant phenotype,
unknown genotype:
PP or Pp?
Predictions
If purple-flowered
parent is PP
Sperm
p
p
Recessive phenotype,
known genotype:
pp
P
P
Pp
Eggs
If purple-flowered
parent is Pp
Sperm
p
p
or
Pp
Pp
P
Pp
pp
Eggs
pp
p
Pp
Pp
RESULTS
or
All offspring purple
/2 offspring purple and
1
/2 offspring white
1
36. Figure 14.8
EXPERIMENT
YYRR
P Generation
yyrr
Gametes YR
yr
F1 Generation
Predictions
YyRr
Hypothesis of
dependent assortment
Hypothesis of
independent assortment
Sperm
or
Predicted
offspring of
F2 generation
/4 YR
1
Sperm
/2 yr
/2 YR
/4 Yr
1
1
/4 yR
/4 yr
1
1
1
1
/4 YR
YYRR
YYRr
YyRR
YyRr
YYRr
YYrr
YyRr
Yyrr
YyRR
YyRr
yyRR
yyRr
YyRr
Yyrr
yyRr
yyrr
/2 YR
1
YyRr
YYRR
Eggs
1
/4 Yr
Eggs
/2 yr
1
YyRr
/4
yyrr
1
/4 yR
/4
3
1
1
Phenotypic ratio 3:1
/4 yr
9
/16
/16
3
3
/16
/16
1
Phenotypic ratio 9:3:3:1
RESULTS
315
108
101
32
Phenotypic ratio approximately 9:3:3:1
40. Figure 14.9
×
Rr
Segregation of
alleles into eggs
Rr
Segregation of
alleles into sperm
Sperm
/2
1
R
/2
/4
Eggs
1
r
/2
r
R
R
1
1
r
R
R
1
/2
1
/4
r
r
R
r
/4
1
/4
1
56. Figure 14.11
(a) The three alleles for the ABO blood groups and their
carbohydrates
Allele
Carbohydrate
IA
IB
i
none
B
A
(b) Blood group genotypes and phenotypes
Genotype
IAIA or IAi
IBIB or IBi
IAIB
ii
A
B
AB
O
Red blood cell
appearance
Phenotype
(blood group)
97. Figure 14.UN03
Relationship among
alleles of a single gene
Complete dominance
of one allele
Description
Heterozygous phenotype
same as that of homozygous dominant
Incomplete dominance Heterozygous phenotype
intermediate between
of either allele
the two homozygous
phenotypes
Codominance
Both phenotypes
expressed in
heterozygotes
Example
PP
Pp
CRCR CRCW CWCW
IAIB
Multiple alleles
In the whole population, ABO blood group alleles
some genes have more
IA, IB, i
than two alleles
Pleiotropy
One gene is able to affect Sickle-cell disease
multiple phenotypic
characters
98. Figure 14.UN04
Relationship among
two or more genes
Epistasis
Description
The phenotypic
expression of one
gene affects that
of another
Example
BbEe
BE
BbEe
bE
Be
be
BE
bE
Be
be
9
Polygenic inheritance
A single phenotypic
character is affected
by two or more genes
AaBbCc
:3
:4
AaBbCc