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Vision for livestock genetics in Africa
The document discusses the vision for livestock genetics in Africa, emphasizing the need for genetic gain while considering the diverse challenges faced by small-scale producers. Key issues include the impact of diseases like African trypanosomiasis on livestock and the limitations of current control methods such as vector control and vaccine development. It advocates for leveraging advancements in genome editing and data systems to identify and utilize natural genetic variations that improve livestock adaptation and productivity.
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Vision for livestock genetics in Africa
- 1. • Vision forlivestock genetics in Africa • Steve Kemp, ILRI Animal Genetic Research for Africa (Biosciences for Farming in Africa), Nairobi, 10-11 September 2015
- 2. Genetic selection, interactingwith environment, drives ‘improvement’ -1000 0 1000 2000 3000 4000 5000 6000 7000 1950 1960 1970 1980 1990 2000 2010 Year Changeinmilkyield(kg) (Source: http://aipl.arsusda.gov/eval/summary/trend.cfm) Changes in milk yields of US Holstein cows Mean phenotype (P), breeding value (A) and environmental effects (E = A - P). Results relative to 1957 base (mean yield 5859kg). A P E In the industrial world genetics has driven dramatic improvements in productivity • Homogeneous environments (systems, markets, health, regulations, policies…….) • Homogeneous genetics (a handful of well defined breeds) • Superb data recording driving selection schemes
- 3. Achieving genetic gainin developing countries – the same biological rules but different environments We must take account of the realities of small-scale livestock producers. Diversity of: • Environment • Climate • Feeds available • Endemic diseases • Local market context • Infrastructure • Institutions
- 4. Achieving genetic gainin developing countries – the same biological rules but different environments We must take account of the realities of small-scale livestock producers. Diversity of: • Environment • Climate • Feeds available • Endemic diseases • Local market context • Infrastructure • Institutions No data systems to inform selection. No infrastructure to manage selection.
- 5. Genotype data ischeap and easy to obtain. Phenotype data remains a problem. Can we skip a generation of technology? • Fast, light, cheap performance data harvesting. • Cheap sensors, mobile platforms, crowd sensing….. • Simultaneously providing management information to the farmer and performance data to the breeder.
- 6. Diversity of environmentshas created diversity of genetics. Let’s not discard it.
- 7. African Trypanosomiasis • Causedby extracellular protozoan parasites – Trypanosoma • Transmitted between mammals by Tsetse flies (Glossina sp.) • Prevalent in 36 countries of sub-Sahara Africa. In cattle • A chronic debilitating and fatal disease. • A major constraint on livestock and agricultural production in Africa. • Costs US$ 1 billion annually. In human (Human Sleeping Sickness) • Fatal • 60,000 people die every year • Both wild and domestic animals are the major reservoir of the parasites for human infection. African Trypanosomiasis
- 8. Control and Treatmentoptions for African Trypanosomiasis Vector Control (Tsetse Fly) • Using toxic insecticide • Not sustainable • Negative impacts on environment Vaccine • Tryps periodically change the major surface antigen – variant surface glycoprotein (VSG) and evade the host immune system. • More than 2 decades, there is no effective vaccine developed. Drug • Drug toxicity and resistance • Expensive
- 9. New tools allowus to look in new places for sources of variation – including wildlife Comparative gene network and sequence analysis allows to ask new kinds of questions about genomes – eg “what is different about this (group of) species compared to all other mammals” “traditional” linkage mapping requires crosses – so initial discovery is limited to variants within a species Cow NDama KFITRRPSLKTLQEKGLIKDQIFGSPLHTLCEREKSTVPRFVKQCIEAVEK Cow Boran KFITRRPSLKTLQEKGLIKDQIFGSHLHTLCEREKSTVPRFVKQCIEAVEK Human KFISRRPSLKTLQEKGLIKDQIFGSHLHTVCEREHSTVPWFVKQCIEAVEK Pig KFITRRPSLKTLQEKGLIKDQIFGSHLHTVCERENSTVPRFVKQCIEAVEK Chicken KFISRRPSLKTLQEKGLIKDQIFGSHLHLVCEHENSTVPQFVRQCIKAVER Salmon KFISRRPSMKTLQEKGIIKDRVFGCHLLALCEREGTTVPKFVRQCVEAVEK
- 10. Time for anew search for variation underlying tropical adaptation and productivity Identify and make use of the genetics underlying natural variation. There has been no systematic search for the genomic basis of adaptation. Because until now we have had no validation tools and no delivery tools. New Genome Editing tools change the landscape.
- 11. Identify and delivervariants associated with adaptation GenotypingPhenotyping Adapted & productive livestock Genome editing Targeting Data systems Delivery systems
- 12. TLF ApoL-I • Apolipoprotein • Trypanolyticcomponent Hpr • Haptoglobin-related protein • Facilitates the uptake of TLF by trypanosomes via haptoglobin-hemoglobin receptor. ApoL-I released Activated in acidic lysosome Form membrane pores, resulting in ion disregulation and osmotic imbalance Trypanosomes lysis Endocytosed into lysosome by Trypanosomes ApoA-I • Apolipoprotein • Found in all HDL subclasses Killing of Tryps by Trypanosome Lytic Factor (TLF) Flagellar pocket of Tryp
- 13. Complete protection fromTrypanosomes by baboon ApoL-I in transiently transgenic mice 0 20 40 60 80 100 120 140 0 20 40 60 80 100 Vector (N=6) apoL-I + Hpr (N=5) apoL-I (N=5) * * Days post infection • P = < 0.01 • Vector vs. treatment Thomson et al PNAS 2009 106:19509-19514
- 14. Project Strategy Genomic locusof Baboon apoL-I gene Vector construction Validate the construct in transgenic mouse Bovine embryonic fibroblasts (BEF) primary culture Transfection & screening apoL-I Transgenic BEFs Nuclear Transfer Transgenic calves Phenotyping Trypanosome resistant transgenic Boran bull ILRI ILRI Kenya Boran Roslin Institute New York University Michigan State University
- 15. Tumaini A cloned KenyaBoran calf made by SCNT from a Boran embryo fibroblast cell line
- 16.
- 17. The presentation hasa Creative Commons licence. You are free to re-use or distribute this work, provided credit is given to ILRI. better lives through livestock ilri.org http://vimeo.com/74942619 11 minute version Video ‘Developing disease-resistant cattle for Africa’ http://vimeo.com/74940697 3 minute version
Editor's Notes
- #11 Overlay diversity of disease, culture, market access, market demands, policy……..
- #12 Trypanosomes live and multiply extracellularly in blood and tissue fluids Distribution corresponds to the distribution of Tsetse flies
- #13 Antigenic variation is transcriptional switching from one VSG gene to another.
- #14 ‘old fashioned’ genome mapping identified variants – slow and costly. But nowhere to go with it New big data approaches allow us to look in new ways. And now we have genome editing to validate and deliver. TIME FOR A NEW ROUND OF FUNCTIONAL GENOMICS TO UNDERSTAND ADAPTATION