Presented by Aynalem Haile and Mourad Rekik (ICARDA) at the EIAR-DBARC-ICARDA-ILRI (LIVES)-FAO Training Workshop on Reproduction in Sheep and Goat, Debre Berhan, Ethiopia, 13-15 October 2014
This PowerPoint presentation is from the third webinar in a five part series on Breeding Better Sheep & Goats. The presenter is Susan Schoenian, University of Maryland Extension Sheep & Goat Specialist.
This PowerPoint presentation is from the third webinar in a five part series on Breeding Better Sheep & Goats. The presenter is Susan Schoenian, University of Maryland Extension Sheep & Goat Specialist.
This is the 5th and final presentation in a 5-part webinar series on Breeding Better Sheep & Goats. The presenter is Susan Schoenian, University of Maryland Extension Sheep & Goat Specialist.
Presented by Raphael Mrode, ILRI, at the workshop on Essential Knowledge for Effective Improvement and Dissemination of Genetics in Sheep and Goats, Addis Ababa, Ethiopia, 3–5 November 2020
This PowerPoint is from a seminar originally presented at the 2010 Maryland Sheep & Wool Festival by Susan Schoenian, Sheep & Goat Specialist for University of Maryland Extension.
The presentation is a study material on Bases of Selection - Family selection. It is useful for student fraternity, especially those study genetics and breeding
Major economic traits of cattle and buffalopratee5
Selection and judging of the breeding stocks are the first and foremost steps to start with any breeding programme. For this, a no. of phenotypic and behavioral traits are taken into consideration. Breeding plans for cattle and buffalo should aim to meet the quantitative and qualitative demands of milk and meat in the country. From a practical standpoint, traits with a measurable or at least readily recognizable economic value are generally to be given the most emphasis.The economic traits are typically those that affect either the income obtained or the costs of production. So, a thorough understanding of economic traits of livestock is of utmost importance.
Basis of selection in animal genetics and breeding Dr. Jayesh Vyas
The sources of information based on which the breeding value of the individual is estimated are called as the basis of selection or aids to selection or criteria of selection which are the basis of estimating the breeding value.
The breeding value so obtained is known as estimating breeding value(EBV)or probable breeding value(PBV).
The different selection criteria to estimates the B.V. of an individuals for single trait
Methods of selection in animal genetics and breedingDr. Jayesh Vyas
Simultaneous selection for many traits can be applied based on individuals own performance by adopting any of the procedure of selection.
One may wish to adopt tandem selection or ICL methods or one may evaluate the individuals on the value for each of the traits selected for and then sum of these values to give a total value for all the traits.
The animal with the highest score is then selected.
These procedure are known as methods of selection.
This is the 5th and final presentation in a 5-part webinar series on Breeding Better Sheep & Goats. The presenter is Susan Schoenian, University of Maryland Extension Sheep & Goat Specialist.
Presented by Raphael Mrode, ILRI, at the workshop on Essential Knowledge for Effective Improvement and Dissemination of Genetics in Sheep and Goats, Addis Ababa, Ethiopia, 3–5 November 2020
This PowerPoint is from a seminar originally presented at the 2010 Maryland Sheep & Wool Festival by Susan Schoenian, Sheep & Goat Specialist for University of Maryland Extension.
The presentation is a study material on Bases of Selection - Family selection. It is useful for student fraternity, especially those study genetics and breeding
Major economic traits of cattle and buffalopratee5
Selection and judging of the breeding stocks are the first and foremost steps to start with any breeding programme. For this, a no. of phenotypic and behavioral traits are taken into consideration. Breeding plans for cattle and buffalo should aim to meet the quantitative and qualitative demands of milk and meat in the country. From a practical standpoint, traits with a measurable or at least readily recognizable economic value are generally to be given the most emphasis.The economic traits are typically those that affect either the income obtained or the costs of production. So, a thorough understanding of economic traits of livestock is of utmost importance.
Basis of selection in animal genetics and breeding Dr. Jayesh Vyas
The sources of information based on which the breeding value of the individual is estimated are called as the basis of selection or aids to selection or criteria of selection which are the basis of estimating the breeding value.
The breeding value so obtained is known as estimating breeding value(EBV)or probable breeding value(PBV).
The different selection criteria to estimates the B.V. of an individuals for single trait
Methods of selection in animal genetics and breedingDr. Jayesh Vyas
Simultaneous selection for many traits can be applied based on individuals own performance by adopting any of the procedure of selection.
One may wish to adopt tandem selection or ICL methods or one may evaluate the individuals on the value for each of the traits selected for and then sum of these values to give a total value for all the traits.
The animal with the highest score is then selected.
These procedure are known as methods of selection.
Genetic evaluation and best prediction of lactation persistencyJohn B. Cole, Ph.D.
At the same level of production cows with high persistency milk more at the end than the beginning of lactation. Best prediction of persistency is calculated as a function of trait-specific standard lactation curves and the linear regression of a cow’s test day deviations on days in milk.
Effect of climatic variabulity on Indian summer monsoon rainfallSunil Kumar
Monsoon origin theories, Earths atmosphere evolution, climate change, factors of climatic change, climatic variability, how these influencing Indian monsoon rainfall, EL Nino, La Nino, ENSO, Indian ocean dipole, MJO etc
Jennifer Patterson - Improving Efficiencies of Replacement Gilt ManagementJohn Blue
Improving Efficiencies of Replacement Gilt Management - Jennifer Patterson, from the 2018 Allen D. Leman Swine Conference, September 15-18, 2018, St. Paul, Minnesota, USA.
More presentations at http://www.swinecast.com/2018-leman-swine-conference-material
This presentation was given at the Delmarva Small Ruminant Conference All Worms All Day on December 8, 2018, in Keedysville, Maryland. The presenter was Susan Schoenian.
Genetics is the scientific study of genes and heredity of how certain qualities or traits are passed from parents to offspring (National Institute of General Medical Sciences, 2022)
Genetics is the science of heredity and variation.
All animals have a predetermined genotype that they inherit from their parents.
The information in an organism's genes provides a biological blueprint for its appearance, function and survival and largely defines its similarities and differences with other organisms.
The genetics of livestock are therefore a critical factor influencing animal production and health.
However an animal’s genotype can be manipulated by breeding and more advanced scientific technique (genetic engineering and cloning)
Genetic makeup of animals have been manipulated to: improve productivity, increase efficiency, and adaptability.
Successful manipulation of the genetic composition of animals requires a depth understanding of fundamental principles of genetics.
Small ruminant keepers’ knowledge, attitudes and practices towards peste des ...ILRI
Presentation by Guy Ilboudo, Abel Sènabgè Biguezoton, Cheick Abou Kounta Sidibé, Modou Moustapha Lo, Zoë Campbell and Michel Dione at the 6th Peste des Petits Ruminants Global Research and Expertise Networks (PPR-GREN) annual meeting, Bengaluru, India, 28–30 November 2023.
Small ruminant keepers’ knowledge, attitudes and practices towards peste des ...ILRI
Poster by Guy Ilboudo, Abel Sènabgè Biguezoton, Cheick Abou Kounta Sidibé, Modou Moustapha Lo, Zoë Campbell and Michel Dione presented at the 6th Peste des Petits Ruminants Global Research and Expertise Networks (PPR-GREN) annual meeting, Bengaluru, India, 29 November 2023.
A training, certification and marketing scheme for informal dairy vendors in ...ILRI
Presentation by Silvia Alonso, Jef L. Leroy, Emmanuel Muunda, Moira Donahue Angel, Emily Kilonzi, Giordano Palloni, Gideon Kiarie, Paula Dominguez-Salas and Delia Grace at the Micronutrient Forum 6th Global Conference, The Hague, Netherlands, 16 October 2023.
Milk safety and child nutrition impacts of the MoreMilk training, certificati...ILRI
Poster by Silvia Alonso, Emmanuel Muunda, Moira Donahue Angel, Emily Kilonzi, Giordano Palloni, Gideon Kiarie, Paula Dominguez-Salas, Delia Grace and Jef L. Leroy presented at the Micronutrient Forum 6th Global Conference, The Hague, Netherlands, 16 October 2023.
Food safety research in low- and middle-income countriesILRI
Presentation by Hung Nguyen-Viet at the first technical meeting to launch the Food Safety Working Group under the One Health Partnership framework, Hanoi, Vietnam, 28 September 2023
Presentation by Hung Nguyen-Viet at the first technical meeting to launch the Food Safety Working Group under the One Health Partnership framework, Hanoi, Vietnam, 28 September 2023
Reservoirs of pathogenic Leptospira species in UgandaILRI
Presentation by Lordrick Alinaitwe, Martin Wainaina, Salome Dürr, Clovice Kankya, Velma Kivali, James Bugeza, Martin Richter, Kristina Roesel, Annie Cook and Anne Mayer-Scholl at the University of Bern Graduate School for Cellular and Biomedical Sciences Symposium, Bern, Switzerland, 29 June 2023.
Assessing meat microbiological safety and associated handling practices in bu...ILRI
Presentation by Patricia Koech, Winnie Ogutu, Linnet Ochieng, Delia Grace, George Gitao, Lily Bebora, Max Korir, Florence Mutua and Arshnee Moodley at the 8th All Africa Conference on Animal Agriculture, Gaborone, Botswana, 26–29 September 2023.
Ecological factors associated with abundance and distribution of mosquito vec...ILRI
Poster by Max Korir, Joel Lutomiah and Bernard Bett presented the 8th All Africa Conference on Animal Agriculture, Gaborone, Botswana, 26–29 September 2023.
Practices and drivers of antibiotic use in Kenyan smallholder dairy farmsILRI
Poster by Lydiah Kisoo, Dishon M. Muloi, Walter Oguta, Daisy Ronoh, Lynn Kirwa, James Akoko, Eric Fèvre, Arshnee Moodley and Lillian Wambua presented at Tropentag 2023, Berlin, Germany, 20–22 September 2023.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
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.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Genetic basis and improvement of reproductive traits
1. Genetic basis and improvement of
reproductive traits
Aynalem Haile and Mourad Rekik (ICARDA)
EIAR-DBARC-ICARDA-ILRI (LIVES)-FAO Training on
Reproduction in Sheep and Goat, Debre Berhan,
Ethiopia, 13-15 October 2014
2. Reproduction: is a complex composite trait
influenced by many components including puberty,
ovulation, estrus, fertilization, embryo
implantation, pregnancy, parturition, lactation, and
mothering ability.
Breeding and Reproduction---Objectives
• Improved lamb production
• More lambs per lambing
• More frequent lambing
• Increased percent of total sheep nos.
• Reducing death losses
3. The production systems
• Crop-livestock systems where genetic interventions can
make a difference
• Pastoral & semi-pastoral systems in which adaptation is
critical
3
4. • Crop-livestock systems
– Medium to high potential areas
– Individual/family enterprises
– Limited land
– Medium to high productivity breeds
• Pastoral & semi-pastoral systems
– Large herds/flocks
– Dictates of climate
– Mobility
– Indigenous breeds
– Strong community values
4
5. Scenarios
• Fluctuation and poor
quality of the feeding
resources
• Insufficient health
care
• Poor housing
conditions
• Fragile economic
asset
Reproduction is
adversely affected
6. Consequences for reproduction
Sheep and goat breeds of arid and semi arid zones are often late-maturing
animals, have a delayed puberty, shorter production life-time
later than in more favourable natural conditions.
Productive outputs are limited, within other causes, by long
anoestrus periods and low fertility and prolificacy.
Furthermore, in utero undernutrition, a very common event when
pregnant dams are inadequately fed under arid and semi arid
conditions, contributes to a reduced reproductive fitness of the
progeny
7. Large genetic differences
Between species
• Goats are more strict
seasonal breeders than sheep
• Goats are in average more
prolific than sheep
Within breed variability
Between breeds
• Late maturing vs. early
maturing breeds
• Existence of natural prolific
strains
8. Characteristics of the reproductive traits to
be improved
• Economically important (fertility, litter size vs.
return to oestrus)
• Expression at the individual level (litter size vs.
Prolificacy)
• Easiness of measure (litter size vs. ovulation rate)
• Cost of measure
• Existence of variability !!!!!!
9. Factors affecting reproduction in the
ewe
• Heredity
• Age
• Photoperiod (seasonal)
• Temperature and humidity
• Nutrition and Exercise
• Parturition and lactation
• Disease and parasites
• Fertility of & assoc. with the ram
10. Factors affecting the reproduction in
the Ram
• Breeding soundness exam
• Palpation of the testicles, epididymis, and
penis and visual appraisal of feet, legs, eyes
and jaws.
• Semen evaluation
• Disease prevention
• Heat stress
11. Desirable traits for accelerated
lambing
• Ewes can breed year round
• Ewes that can mate while lactacting
• Ewes that have a good lambing rate (ie
twinning)
• Sires that produce a desirable market lamb
and have the libido and fertility for conception
year round
12. Genetic effects
• Although component traits of reproduction are
under the influence of many genes, a limited number
of major genes associated with separate components
of reproduction have been reported in sheep
• Expressions of the genetic effects on reproduction
are affected by numerous environmental factors such
as season, climatic conditions, management, health,
nutrition, ram to ewe breeding ratio, age of ewe, and
ram libido and fertility. Because genetic and
environmental factors interact, genetic improvement
of reproduction is very complicated.
13. • Selection for a single component of reproduction
such as ovulation rate, litter size at birth or number
of lambs weaned has commonly been practiced.
However, selection for a single component of a
composite trait does not always result in an overall
improvement of a complex trait such as reproduction
• The relevance of the different reproductive traits is
not the same and also differs among species.
• In meat sheep production, litter size and days to
lambing are two of the most important traits
14. Sex Expression
Mainly in females
• Age at puberty
• Age at first lambing
• Fertility
• Litter size at lambing
• Litter size at weaning
• Lambing interval
• Productive lifetime
Little attention in males
• Scrotal diameter???
• Libido and sexual
aggressiveness???
15. Heredity basis of reproductive traits
• For most breeds,
reproductive traits are
quantitative traits:
progress is obtained by
transmission of the
additive effects of genes
• In some breeds or
strains, litter size is
influenced by major
genes: alleles
polymorphism in some
known genes
(≈ Mendelian trait)
17. 2 categories of genetic effects
• Due to the effect of random halving of the genome, we have 2
fundamentally different categories of genetic effects:
• Effects that come into play by mating an individual to a random
sample of the population and are effective as the average of the
offspring (= additive effects).
• Effects determined by specific combination of gametes in a
particular individual, but not the offspring (= dominance and
epistatic effects).
17
18. Splitting the genetic effect
g = ga + do + ep
• ga = "additive" gene effect (relevant for breeding value)
– ga is the part of g, which comes into effect when the individual
is mated to a representative sample of the population in the
average of its offspring.
• do = "dominance effect"
– do is the part of g, not explained by ga and due to interactions
of alleles of the same locus within a particular individual.
• ep = "epistatic effect"
– ep is the part of g, not explained by ga or do and due to
interactions of alleles of different loci within a particular
individual.
18
19. Concept of heritability h2
Heritability is the proportion of variation in a phenotype (trait,
performance) that is thought to be caused by genetic variation
among individuals. The remaining variation is usually
attributed to environmental factors. A measure of
the degree to which the variance in the distribution of
a phenotype is due to genetic causes.
- h2 < 10%: low heritability, low genetic progress by direct
selection
- 10% < h2 < 30% : moderate heritability, slow genetic progress
by direct selection
- h2 > 30% : high heritability, significant progress by direct
selection
20. Estimates of heritability for basic and
composite traits (Rosati, 2002)
Conception Rate 0,06
Number of lambs born 0,10
Number of lambs born alive 0,05
Number of lambs alive at weaning 0,01
Litter mean weight per lamb born (kg) 0,13
Litter mean weignt per lamb weaned (kg) 0,15
Number of lambs born per ewe exposed 0,09
Number of lambs weaned per ewe exposed 0,07
Total litter weight at birth (kg) 0,4
Total litter weight at weaning (kg) 0,17
Total litter weight born per ewe exposed (kg) 0,13
Total litter weight weaned per ewe exposed (kg) 0,11
Lamb survival at weaning (%) 0,12
21. Major genes affecting litter size
1. The BMPR 1B (Bone Morphogenetic Protein Receptor
type 1B) gene has been mapped to sheep chromosome 6
(“hyperprolific phenotype” of the Booroola sheep,
Assaf??)
2. The BMP15 (Bone Morphogenetic Protein 15) gene, has
been mapped to sheep chromosome X (Rasa Aragonesa,
Lacaune, Galway)
3. The sheep GDF9 (Growth Differentiation Factor 9) gene
maps to chromosome
22. The challenge
• Regarding genetic improvement, available work has mainly
focused on phenotypic selection, rather than using
information on specific genetic factors (genotypic information)
affecting these traits.
• Nevertheless, reproductive traits are characterized by low
heritabilities and a complex genetic basis and are thus difficult
to improve using traditional selection methods.
• Moreover, these traits are recordable only in one sex and late
in the animal’s life.
• These limitations have led to a growing interest in the
identification and characterization of specific genes and
genomic regions implicated in the variability and regulation of
reproductive processes.
24. Modern Breeding Structures
Breeders
Commercial flocks,
community or base
Breeders
Multipliers
Base flocks
Gene flow (males)
Mueller, 2008
24
25. No breeding structures
– Occurs in low input systems
– Difficult for the breeder to detect the best animals with
high precision
– Difficult to organize a stratified mating in his flock
– Less chance for gene inflow
– Mating is at random within the flock
– Genetic progress is slow, if any
– Difficult to follow
25
26. Nucleus Breeding Structure
Nucleus
Base
Females Males
“Open” to gene flow
in any direction
Mueller, 2008 26
27. Centralized and dispersed nucleus
central
nucleus
dispersed
nucleus
Participating flocks Participating flocks
Mueller, 2008 27
29. The higher the dissemination, the higher
should be the BV and its accuracy
Records
BLUP analyses
Records on
relatives
30%
60%
90%
Genomic
100%
Visual
Random
0%
Performance test
Progeny test
BLP analyses
Sophistication of selection system
Selection accuracy