ILR I

1. INTRODUCTION Bovine trypanosomosis is a major constraint in animal production and yet there are no available effective control strategies. Farming of trypanotolerant breeds may offer a viable control strategy once genetic mechanisms behind the trait are understood and used to improve it further. Here, we describe the first experiment to test whether previously detected QTLs in an artificially challenged F2 population will hold in an outbred backcross cattle population exposed to the disease in a natural trypanosomosis endemic area. MATERIALS AND METHODS Backcross cattle mapping population was constructed with semen from F1 sires of Boran × N’Dama previously used in F2 population (Hanotte et al., 2003) inseminating several Boran females. The resulting backcross (BC1) progenies, were weaned at age of 8 months, vaccinated against known endemic diseases. The 224 progenies were sampled for blood from which DNA was extracted according to salting out procedure (Sambrook et al., 1989). 8 grandparents, 13 F1 sires and the 224 BC1 progenies were screened using 39 microsatellite markers covering BTA 2, 4, 7, 16 and 17. Selection of markers was from www.cgd.Csiro.au. Allele calling was performed using ABI 3700 genemapper® software. Before and during tsetse challenge, packed cell volume (PCV), body weight and parasitemia were recorded on the experimental animals weekly. All phenotypic data were re-centered and re-scaled and effect of sex was corrected by performing least square analysis of variance. Markers were ordered using Multipoint software (Mester et al., 2003) and single trait-single QTL model within the framework of multiple interval mapping of MULTIQTL® software was used for QTL analysis (http://esti.haifa.ac.il/~poptheor/ , http://www.multiqtl.com & Korol et al., 2001) RESULTS AND DISCUSSION 4 QTLs affecting 3 traits were detected in 3 chromosomes namely chromosome BTA2, BTA7 and BTA16. Two of these QTL significantly affected 2 traits at 10% false discovery rate (FDR) in chromosome BTA7 and BTA2 and the traits affected were’dtr1’ and ‘Newinf’ which were defined as time taken from exposure to the first treatment and new infection (infection after treatment) respectively. The remaining two QTL affected traits, ‘drt1’ and ‘ wR_tr ‘at a FDR of 20% in chromosomes BTA2 and BTA16 respectively, the latter trait being defined as weight recovery post treatment. The traits ‘new inf ‘is related to parasitemia while ‘drt1’ is related to both parasitemia and packed cell volume, PCV. The trait‘wR_tr’ is related to body weight. The proportion of phenotypic variation explained by putative QTL ranged from 8.4 to 11.9% in the three chromosomes where QTL were detected. Power of QTL detection was reported at 0.05p-level after performing 3000 boostrapings and it ranged from 74.8 to 81.8%. Substitution effect (scaled by phenotypic standard deviation) ranged from -0.519 to 0.519. Three of the 4 QTL in chromosomes BTA2, BTA7 and BTA16 controlling parasitemia and PCV (‘newinfe’, ‘pcvDinfec’) and body weight (‘WR_tr’) derived their trypanotolerant alleles from the Boran breed while QTL controlling parasitemia and packed cell volume (‘dtr1) derived its trypanotolerant alleles from the N’Dama breed. The QTL controlling PCV deterioration after infection (‘pcvDinfec’) in chromosomeBTA7 is only significant at p<0.1. Detection of trypanotolerant quantitative trait loci (QTL) in a backcross of (N’Dama x Boran) x Boran under natural tsetse fly challenge, in Narok. S.W. Kenya Table2. QTL detected, Location, p-values, LOD scores, PEV, substitution effects, and power of QTL detection (after using multiple interval mapping, MIM) Position of QTL controlling days to first treatment in chromosome BTA7 in the backcross population Table3. Comparison of QTL effects in the previous F2 and the current BC1 (bolded) populations (shown are traits affected, p-values, type of gene action, PEV and origin of trypanotolerance alleles (*) C.O. Orenge1, C.N. Kimwele2, A. B. Korol5, S. Kemp4, L. K. Munga1, J. P. Gibson6, O.Hanotte3, D.Dereck4, S.Nagda3, G. Murilla1 and M.Soller7 1 Kenya Agricultural Research Institute - Trypanosomiasis Research Centre (KARI-TRC), P.O. Box 362 – 00902, Kikuyu, Kenya 2 Department of Veterinary Anatomy and Physiology, University of Nairobi, P.O. Box 30197-00100, Nairobi, Kenya 3 International Livestock Research Institute (ILRI), P.O. BOX 307907-00100, Nairobi-Kenya 4 School of Biological Sciences, University of Liverpool, Liverpool L69 7ZD, United Kingdom 5 Institute of Evolution, Haifa University, Mount Carmel, 31905 Haifa, Israel 6 The Institute of Genomics and Bioinformatics, University of New England, Armidale, NSW 2351, Australia 7 Hebrew University of Jerusalem, Jerusalem 91904, Israel CONCLUSION The study shows evidence of quantitative trait loci controlling trypanotolerance in a cattle population reared in an area of high tsetse endemicity. There is also a significant contribution of trypanotolerant alleles from the Boran breed. This is consistent with the earlier F2 data, and suggests that a synthetic breed may have a higher trypanotolerance than either the Boran or NDama breeds alone, achievable by using marker assisted selection and introgression breeding programs from the two founder breeds. This will go along way in the improvement of bovine trypanotolerance in the tsetse inhabited zones of Africa. REFERENCES Hanotte, O, Ronin, Y., Agaba, M., Nilsson, P., Gelhaus A., Horstmann, R., Sugimoto, Y., Kemp, S., Gibson, J., Korol, A., Soller, M., Teale, A. (2003). Mapping of quantitative trait loci (QTL) controlling trypanotolerance in a cross of tolerant West African N’Dama and susceptible East African Boran cattle. PNAS 100, 7433- 7448 Korol A., Ronin Y., Itskovich A.M., Peng J., Nevo E. (2001). Enhanced efficiency of QTL mapping analysis based on multivariate complexes of quantitative traits. Genetics, 157: 1789-1803 ILRI INTERNATIONAL LIVESTOCK RESEARCH INSTITUTE