Presented by Raphael Mrode, Julie Ojango, John Gibson and Okeyo Mwai at the 12th World Conference on Animal Production (WCAP), Vancouver, Canada, 5-8 July 2018
Innovative digital technology and genomic approaches to dairy cattle genetic...ILRI
Presented by R. Mrode, J. Ojango, Ekine Chinyere, John Gibson and Okeyo Mwai at the Strategic Interest Research Group Meeting on Genetic Improvement of Livestock II, IITA, Ibadan, 2-3 September 2019
Application of nuclear and genomic technologies for improving livestock produ...ILRI
Presented by Raphael Mrode at the IAEA International Symposium on Sustainable Animal Production and Health—Current Status and Way Forward, Vienna, 28 June-2 July 2021
Draft chicken performance testing protocols: Deliberations with country teams ILRI
Presented by Fasil Getachew, Tadelle Dessie, Jasmine Bruno and Jane Pool at the Second ACGG Program Management Team Meeting, Arusha, 27-28 January 2016
Overview of the Dairy Genetics East Africa (DGEA) projectILRI
Presented by John P. Gibson, Ed Rege, Okeyo Mwai, Julie Ojango at the Dairy Genetics East Africa (DGEA) Project 2013 Grand Challenges Meeting, Rio de Janeiro, Brazil, 28-30 October 2013
Innovative digital technology and genomic approaches to dairy cattle genetic...ILRI
Presented by R. Mrode, J. Ojango, Ekine Chinyere, John Gibson and Okeyo Mwai at the Strategic Interest Research Group Meeting on Genetic Improvement of Livestock II, IITA, Ibadan, 2-3 September 2019
Application of nuclear and genomic technologies for improving livestock produ...ILRI
Presented by Raphael Mrode at the IAEA International Symposium on Sustainable Animal Production and Health—Current Status and Way Forward, Vienna, 28 June-2 July 2021
Draft chicken performance testing protocols: Deliberations with country teams ILRI
Presented by Fasil Getachew, Tadelle Dessie, Jasmine Bruno and Jane Pool at the Second ACGG Program Management Team Meeting, Arusha, 27-28 January 2016
Overview of the Dairy Genetics East Africa (DGEA) projectILRI
Presented by John P. Gibson, Ed Rege, Okeyo Mwai, Julie Ojango at the Dairy Genetics East Africa (DGEA) Project 2013 Grand Challenges Meeting, Rio de Janeiro, Brazil, 28-30 October 2013
Presented by Tesfaye Getachew, Amhara Regional Agricultural Research Institute, at the EIAR/ATA/ICARDA Workshop on small Ruminant Breeding Programs in Ethiopia, Debre Birhan, 17-18 December 2015
Advances in Genomics Research and Molecular Breeding in Dryland Crops through...apaari
Advances in Genomics Research and Molecular Breeding in Dryland Crops through Partnership for Achieving Food and Nutritional Security by Rajeev Varshney, ICRISAT, India
Research Program Genetic Gains (RPGG) Review Meeting 2021: Update on Sequenci...ICRISAT
A range of marker genotyping platforms have been made available to breeders/ researchers from ICRISAT and NARS from all regions. It will be great if CESGB/SISU can be upgraded with new machines. GTD/FB colleagues developing new marker genotyping platforms- mid-density SNP arrays. Therefore, researchers and breeders are encouraged to avail sequencing and genotyping facilities from SISU to accelerate their research and modernize breeding programs.
Small ruminant research and development in Ethiopia ILRI
Presented by Solomon Abegaz (Ethiopian Institute of Agricultural Research) and Solomon Gizaw (LIVES Project, ILRI), at the EIAR/ATA/ICARDA Workshop on small Ruminant Breeding Programs in Ethiopia, Debre Birhan, 17-18 December 2015
This is a presentation from the Canadian Bovine Genomics Workshop held in Calgary, Alberta on Sept.14, 2009.
The workshop was the first step in developing a national bovine genomics strategy for Canada.
Insights into the genetic diversity and structure of indigenous ovi-caprine p...ILRI
Presented by Getinet Mekuriaw (Bahir Dar University) and Joram M. Mwacharo (ICARDA), at the EIAR/ATA/ICARDA Workshop on small Ruminant Breeding Programs in Ethiopia, Debre Birhan, 17-18 December 2015
Genetic basis and improvement of reproductive traitsILRI
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
Presented by Shirley Tarawali, Dolapo Enahoro and Catherine Pfeifer (ILRI) at the Expert panel: Food of Animal Origin 2030: Solutions to Consumption Driven Challenges, Global Forum for Food and Agriculture 2018, Berlin, Germany
A platform for testing, delivering, and continuously improving tropically-ada...ILRI
Presented by Tadelle Dessie at the Technology for African Agricultural Transformation (TAAT) Small Ruminants Value Chain Inception Meeting, ILRI, Addis Ababa, 22 June 2018
Resource use efficiency in livestock: Bridging the biotechnology-livestock pr...ExternalEvents
Resource use efficiency in livestock: Bridging the biotechnology-livestock productivity gap in East Africa presentation by Denis Mujibi, Nelson Mandela African Institute for Science and Technology, Arusha, Tanzania
Genomics selection in livestock: ILRI–ICARDA perspectivesILRI
Presented by Raphael Mrode (ILRI), Joram Mwacharo (ICARDA) and Olivier Hanotte (ILRI) at the Workshop on Implementing Genomic Selection in CGIAR Breeding Programs, Montpellier, 10-12 December 2015
Presented by Tesfaye Getachew, Amhara Regional Agricultural Research Institute, at the EIAR/ATA/ICARDA Workshop on small Ruminant Breeding Programs in Ethiopia, Debre Birhan, 17-18 December 2015
Advances in Genomics Research and Molecular Breeding in Dryland Crops through...apaari
Advances in Genomics Research and Molecular Breeding in Dryland Crops through Partnership for Achieving Food and Nutritional Security by Rajeev Varshney, ICRISAT, India
Research Program Genetic Gains (RPGG) Review Meeting 2021: Update on Sequenci...ICRISAT
A range of marker genotyping platforms have been made available to breeders/ researchers from ICRISAT and NARS from all regions. It will be great if CESGB/SISU can be upgraded with new machines. GTD/FB colleagues developing new marker genotyping platforms- mid-density SNP arrays. Therefore, researchers and breeders are encouraged to avail sequencing and genotyping facilities from SISU to accelerate their research and modernize breeding programs.
Small ruminant research and development in Ethiopia ILRI
Presented by Solomon Abegaz (Ethiopian Institute of Agricultural Research) and Solomon Gizaw (LIVES Project, ILRI), at the EIAR/ATA/ICARDA Workshop on small Ruminant Breeding Programs in Ethiopia, Debre Birhan, 17-18 December 2015
This is a presentation from the Canadian Bovine Genomics Workshop held in Calgary, Alberta on Sept.14, 2009.
The workshop was the first step in developing a national bovine genomics strategy for Canada.
Insights into the genetic diversity and structure of indigenous ovi-caprine p...ILRI
Presented by Getinet Mekuriaw (Bahir Dar University) and Joram M. Mwacharo (ICARDA), at the EIAR/ATA/ICARDA Workshop on small Ruminant Breeding Programs in Ethiopia, Debre Birhan, 17-18 December 2015
Genetic basis and improvement of reproductive traitsILRI
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
Presented by Shirley Tarawali, Dolapo Enahoro and Catherine Pfeifer (ILRI) at the Expert panel: Food of Animal Origin 2030: Solutions to Consumption Driven Challenges, Global Forum for Food and Agriculture 2018, Berlin, Germany
A platform for testing, delivering, and continuously improving tropically-ada...ILRI
Presented by Tadelle Dessie at the Technology for African Agricultural Transformation (TAAT) Small Ruminants Value Chain Inception Meeting, ILRI, Addis Ababa, 22 June 2018
Resource use efficiency in livestock: Bridging the biotechnology-livestock pr...ExternalEvents
Resource use efficiency in livestock: Bridging the biotechnology-livestock productivity gap in East Africa presentation by Denis Mujibi, Nelson Mandela African Institute for Science and Technology, Arusha, Tanzania
Genomics selection in livestock: ILRI–ICARDA perspectivesILRI
Presented by Raphael Mrode (ILRI), Joram Mwacharo (ICARDA) and Olivier Hanotte (ILRI) at the Workshop on Implementing Genomic Selection in CGIAR Breeding Programs, Montpellier, 10-12 December 2015
The role of reliable data collection systems for improved livestock genetics ...ILRI
Presented by Julie Ojango and Chinyere Ekine-Dzivenu at the Workshop on sustainable development of Burundi's dairy sector--Partners of the regional integrated agricultural development in the great lakes (PRDAIGL) project workshop, Burundi, 2–3 November 2022
Genomic selection in small holder systems: Challenges and opportunitiesILRI
Presented by Raphael Mrode, Julie Ojango and Okeyo Mwai at the Workshop on Animal Genetic Research for Africa (Biosciences for Farming in Africa), Nairobi, 10-11 September 2015
Improving livestock productivity and resilience in Africa: Application of gen...ILRI
Presented by Julie Ojango, Yumi Mingyan, Raphael Mrode and Okeyo Mwai at the Workshop on Animal Genetic Research for Africa (Biosciences for Farming in Africa), Nairobi, 10-11 September 2015
Innovative use of conventional and new technologies to unravel breed options ...ILRI
Presented by J.M.K. Ojango, R. Mrode and A.M. Okeyo at the 1st World Congress on Innovations for Livestock Development: Fostering Innovations for the Livestock Industry, Nakuru, Kenya, 26–30 June 2016
Potential application of lessons from dairy genetics into beef: Lessons from ...ILRI
Presented by Okeyo Mwai, Raphael Mrode, Julie Ojango, Chinyere Ekine-Dzivenu and Gebregziabher Gebreyohannes at the CTLGH-ACIAR Convening workshop, Nairobi, 30 September 2022
Presented by Breeding and genetics (Aynalem Haile and Joram Mwacharo), Reproduction, (Mourad Mourad Rekik) Feed (Jane Wamatu) Health (Solomon Gizaw) and Markets (Girma Tesfahun) at the SmaRT Ethiopia workshop and field day on Small Ruminant Community Based Breeding Program (CBBP), Hosaena, Ethiopia, 27–28 March 2018
Opportunities for improving dairy production in Burundi: Experience from the ...ILRI
Presented by Julie Ojango and Chinyere Ekine-Dzivenu at the Workshop on sustainable development of Burundi's dairy sector--Partners of the regional integrated agricultural development in the great lakes (PRDAIGL) project workshop, Burundi, 2–3 November 2022
An Overview of Genomic Selection and FertilityDAIReXNET
In this webinar, released July 18, 2016, Dr. Hansen joined us to discuss genomic selection as it relates to fertility traits. Learn about single nucleotide polymorphisms (SNPs), the challenges in selecting for reproductive traits, and some of the current work in overcoming those challenges.
Herd recording and farmer education using digital platforms are feasible and...ILRI
Presented by Okeyo A.M., R. Mrode, J. Ojango, J. Gibson, M. Chagunda, Negussie Enyew, E. Kefena, E. Lyatuu, S. Kahumbu and S. Kemp at the Mid-Term Livestock Genetics Flagship Meeting, ILRI, Nairobi, 5-6 September 2017
Genetics and genomic approaches for sustainable dairy cattle improvement in s...ILRI
Presented by Raphael Mrode, Chinyere Ekine-Dzivenu, Julie Ojango and Mwai Okeyo at the ASAS-CSAS Annual Meeting & Trade Show, Oklahoma, USA, 26-30 June 2022
Improving the accuracy of genomic predictions in small holder crossed-bred da...ILRI
Presented by Raphael Mrode, Julie Ojango, John Gibson and Okeyo Mwai at the 7 All Africa Conference on Animal Agriculture (AACAA), Accra , Ghana 29 July– 2 August 2019
Similar to Developing innovative digital technology and genomic approaches to livestock genetic improvement in developing countries (20)
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.
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.
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.
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.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
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.
The ASGCT Annual Meeting was packed with exciting progress in the field advan...
Developing innovative digital technology and genomic approaches to livestock genetic improvement in developing countries
1. Developing innovative digital technology and genomic approaches to
livestock genetic improvement in developing countries
Raphael Mrode, Julie Ojango, John Gibson and Okeyo Mwai
12th World Conference on Animal Production (WCAP)
Vancouver, Canada, 5-8 July 2018
2. Structure of most genetic Improvement Program in developed
countries
Data
Collection
and storage
(PI)
Analytical tools (PPP)
Breeding Programs or Delivery of
appropriate genetics to farmers
(PI)
Herd management information
Genetic evaluations Farmers
Foreign Genetics
Good Foundation for sustainability or continuous genetic progress
3. Structure of most genetic Improvement Program in developing
countries
Breeding Programs or
Delivery of appropriate
genetics to farmers (PI)
Farmers
Foreign Genetics
Indigenous
breeds or
crosses
No Foundation for sustainability or continuous genetic progress
No Training
No feedback
4. 0
1000
2000
3000
4000
5000
Harsh Poor Good
Yield(l)
Production environment
Indigenous
X-bred
Exotic
Indigenous (non-dairy)
breeds: highly adapted to
harsh conditions; little
potential to increase milk
yield under better
feeding.
Crossbreds: Already exist
in lager numbers &
respond to better feeding
with increased milk yield;
moderately well adapted.
Exotic dairy breeds: very
high genetic potential for
milk yield which is NOT
expressed under the most
favourable conditions;
poorly adapted
Typical low-input
smallholder environment
Success comes from appropriately matching the
genetic potential with production environments,
(physical, management and markets)
5. What Challenges are being addressed by ADGG?
little or no systematic and
sustainable breeding
programs
limited access to the dairy
genetics or breed type that best
suit the different production
systems
Farmers do not have access to
various services, esp. AI & health,
and inputs necessary to support
sustained productivity
improvement
Inadequate access to
input & market
services
access to information or farmer
education and training services
lacking so cant improve herd
productivity and system profitability
6. What is ADGG
Platform for African Dairy Genetic Gains (ADGG) is a multi-country,
multi-institution ILRI-led pioneering proof of concept which is:
developing and testing a multi-country genetic
gains platform that uses on-farm performance
information and basic genomic data for identifying
and proving superior crossbred bulls for AI delivery
and planned natural mating for the benefit of
smallholder farmers in Africa
7. ADGG: Approach and Objectives
Innovative application of existing &
emerging technologies
1. To establish National Dairy Performance Recording Centers
(DPRCs) for herd and cow data collection, synthesis, genetic
evaluation and timely farmer-feedbacks
2. To develop & pilot an ICT platform (FFIP) to capture herd, cow
level & other related data & link it to DPRCs (feeds back key
related herd/cow summaries, dairy extension & market info.
etc.).
3. To develop low density genomic chip for breed composition
determination & related bull certification systems for
crossbred bulls
11. What data is being collected?
• Milk yield (litres on test-day basis) & milking frequency
• Lactation length (derived)
• Calving interval (derived)
• Birth weight
• Calf/heifer growth (weight for age)
• Survival to different age (derived)
• AFC (derived)
• Lactation number
• Type and incidence of disease, interventions/treatment & costs
• Body condition score on the test –day
• Teat and udder type scores, including disorders
• Behavioral (movement/rumination) tracking in association
estrus detection
• Milk composition (provided for but not being measured now)
• Fat %
• Protein %
• Urea (mg/dl)
• Lactose %
• Somatic cell count (cells/ml)
The above are being used to develop breeding objectives
15. Raw statistics on test-Day milk records from Tanzania
Row Labels
Total number
of TD Records
Avg Test-Day
milk ± SD
Max
TD-Milk
Min TD-
Milk
Number of animals
with TD Records
Arusha 5103 7.27±3.49 25 0.5 1624
Iringa 2322 5.99±2.71 20 0.5 817
Kilimanjaro 5325 6.57±4.06 28 0.5 2050
Mbeya 6377 9.51±4.41 30 1 2260
Morogoro 1 9.00 9 9 1
Njombe 3225 10.06±4.00 28 0.5 1016
Tanga 5837 6.23±3.76 25 0.5 2178
Grand Total 28190 7.64±4.18 30 0.5 9946
16. Data collection - Sustainability
• Several options are being explored
• Training individuals to undertake a bundle of services:
• AI services, supply inputs to farmers and data collection or
verification
• Easy to use phone based ICT tools
• farmers can use to input data. Data is only verified by personnel
providing bundle services occasionally during farm visits.
• well supported with very good feedback that farmers can see
benefits of data collection
17. Characteristics of genomic data in small
holder systems
• Genotyping activities undertaken as a result of research
project or breed associations
• Challenges:
• Number of genotyped animals are few and are mostly females
• Reference are mostly females but a few males in some occasions
• Very difficult to clearly define data sets for validation and
therefore these are created either by random or structured
sampling
• Mostly on cross breeds animals
18. Characteristics of genomic data in small
holder systems
• Opportunities:
• Genotypes on cross breed animals
• Explore novel methods adapted to the data structure
• Plurality of Bayesian methods have been examined
19. Quick wins from genomics in small holder
systems
• With lack of systematic data and pedigree, quick
wins from genotypic data includes
• Reduces the need for accurate pedigree recording as
genomic relationship can easily be computed
• Parentage discovery using SNP data
• Determining breed composition
• Future use in traceability of animal products
20. Experimenting with DGEA data
• Examine genomic prediction using the DGEA small holder data
• Phenotypes were milk yield deviations on 1034 cows (Kenya)
with HD genotypes
• Exotic breeds were Friesian, Holstein, Guernsey, Jersey and
Ayrshires and indigenous breeds : Nellore, Zebu
• Four classes of animals created: cows with > 87.5%, 61−87.5%,
36−60%, and < 36% exotic breed genes.
22. Developing a low density SNP Chip for
breed composition
• Low density snp assay can be developed that gives accurate
estimates of dairy proportion
23. Low density assay for breed composition
• Based on DGEA data
• A low density assay of about 200 SNPs have been
identified for determination of breed composition
• If parentage verification is included, assay expands to
400 SNPs
• Piloting its utilization among farmers for certification
of bulls, heifer and cows.
24. Experimenting with DGEA data
• Non-Bayesian method: GBLUP & SNP-BLUP
• Bayesian methods
• Determine possible levels of accuracy for young bulls of
different breed compositions with no data
25. Current status : Accuracies of genomic
prediction –based on DGEA data
Validation
Population
Validation set Reference Set Accuracy
>87.5% Exotic 297 716 0.41
60 – 87.5%
Exotics
448 565 0.35
50 -33 % Exotics 178 835 0.32
A. Brown,* J. Ojango,† J. Gibson,‡ M. Coffey,* M. Okeyo,† and R.
Mrode*†1
*†
Short communication: Genomic selection in a crossbred cattle
population using data from the Dairy Genetics East Africa Project
26. Looking at other models
GBLUP with G matrix and a dominance matrix (D) :
Multi-trait approach.
Multi-trait GBLUP - proportion of exotic and indigenous genes
as separate effects.
GEBV was computed for each of 9 chromosome regions for
top cows with high exotic or indigenous genes.
Regions with highest contribution to GEBV of top cow were
chromosomes 14, 8, 1 and 2 for cows with high exotic genes
chromosome 3,1,10 and 5 for cows with high indigenous
genes
27. Accuracy of genomic prediction
0
0.1
0.2
0.3
0.4
>87.4
61-87.5
36-60
>36
GBLUP GBLUP + Dominance
GBLUP based
on breed
proportion
GBLUP based on
breed proportion
(correlated)
28. Regression Coefficients
GBLUP GBLUP + Dominance
GBLUP based
on breed
proportion
GBLUP based on
breed proportion
(correlated)
0
0.5
1
1.5
2
2.5
3
3.5
4
>87.4
61-87.5
36-60
>36
29. Results from the multi-trait approach are encouraging but we need to
understand it more
Idea is to find the haplotypes or chromosome segments whose origin
can be traced to exotic and indigenous breeds . These can then be fitted
separately
This is being explored by admixture within chromosome in collaboration
with UNE
30. Incorporating genotypes from foreign sires
Li et at 2016 examined the improvement in prediction
reliabilities for 3 production traits from multi-trait SSGBLUP
Brazilian Holsteins that had no genotypes
adding information from Nordic and French
Holstein bulls that had genotypes.
Interbull proofs for foreign countries used as
correlated traits
Some average increases in reliabilities with foreign
information included for bulls were
Milk : 2% ; Fat : 45% and none for protein
31. Other methods explored
• Currently from GBLUP or SNP-BLUP top cows tended to be
dominated with cows of high degree of exotic genes.
• Ideally, you want improve the milk production in cows with
about medium indigenous genes
• This therefore prompted using a weighted G in GBLUP.
• Gwt was computed using SNP effects from BayesA and BayesB
• SNPs effects were from all data, exotic (> 0.65%), indigenous
(<= 0.65%) or combined exotic and indigenous (0.25:0.75)
32. Other methods explored
• Accuracy of predictions only changed for cows with <36%
exotic genes
• Accuracies were 0.12, 0.16 , 0.21 and 0.21 for all data,
exotic, indigenous and combined respectively
• Ranking of indigenous cows in the top 40% increased by 14%
with using SNP effects from indigenous or combined
33. Results cont..
Variable measure At start (2016) Now (2018)
Number genotyped
to inform genomic
selection
0 10000
Genomically
evaluated x-bred
breeding bulls
0 By July 2018
34. Delivery of improved genetics
Carvalheiro (2014) described some business models for
Nellore Cattle in Brazil
One of the models: GEBVs are predicted by multinational
private company and are regarded as intellectual property of
the company
breeders or the breeding programs do not have access to the
genotypes and genomic prediction equations but rely on
company selling GEBVs
35. Delivery of improved genetics
Developed countries
AI - companies and breed societies play major roles in
Developing countries
Farmer cooperatives
National Artificial Insemination Centers (NAIC)
AI usage is low
Bull rankings from Data Centers must be linked to NAIC or
farmer cooperative
Genotyping strategy must ensure key bulls using for natural
mating in villages are part of the evaluation systems
Foreign AI companies should support data collection to
include daughters of their bull
36. • Unstable internet connectivity but
we are able get around it!
• Weak institutions
• Inadequate/not fully supportive
policy to PPR-arrangements
Some Challenges
37. • The proof of concept has been quite
successful and the 1st batch of genomically
evaluated crossbred bulls expected by end
of this year
• Given data structure for smaller , well
adapted methodologies will be needed for
genomic selection and initial results are
encouraging
• In order to benefit from large numbers and
diverse genetic backgrounds, regional
programs is the way to go
Conclusions
38. • Need to collaborate with developed countries
where some of the sires of these cows could be
genotyped
• Parentage discovery
• Genotype by environmental interaction if enough data
• Huge opportunities exist for overlaying
other studies to the ADGG’s framework
with potentially exciting results and
outcomes
Conclusions
39. Dairy Farmers & Farmer
organizations
National/regional
Institutions/govts.
Acknowledgements
The organizers of the Big
Data Conference
40. This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence.
better lives through livestock
ilri.org
ILRI thanks all donors and organizations who globally supported its work through their contributions
to the CGIAR system