Background: African animal trypanosomiasis (AAT) caused by tsetse fly-transmitted protozoa of the genus Trypanosoma is a major constraint on livestock and agricultural production in Africa and is among the top ten global cattle diseases impacting on the poor. Here we show that a functional genomics approach can be used to identify temporal changes in host peripheral blood mononuclear cell (PBMC) gene expression due to disease progression. We also show that major gene expression differences exist between cattle from trypanotolerant and trypanosusceptible breeds. Using bovine long oligonucleotide microarrays and real time quantitative reverse transcription PCR (qRT-PCR) validation we analysed PBMC gene expression in naïve trypanotolerant and trypanosusceptible cattle experimentally challenged with Trypanosoma congolense across a 34-day infection time course. Results: Trypanotolerant N’Dama cattle displayed a rapid and distinct transcriptional response to infection, with a ten-fold higher number of genes differentially expressed at day 14 post infection compared to trypanosusceptible Boran cattle. These analyses identified coordinated temporal gene expression changes for both breeds in responses to trypanosome infection. In addition, a panel of genes were identified that showed pronounced differences in gene expression between the two breeds, which may underlie the phenomena of trypanotolerance and trypanosusceptibility. Gene ontology (GO) analysis demonstrate that the products of these genes may contribute to increased mitochondrial mRNA translational efficiency, a more pronounced B cell response, an elevated activation status and a heightened response to stress in trypanotolerant cattle. Conclusions: This study has revealed an extensive and diverse range of cellular processes that are altered temporally in response to trypanosome infection in African cattle. Results indicate that the trypanotolerant N’Dama cattle respond more rapidly and with a greater magnitude to infection compared to the trypanosusceptible Boran cattle. Specifically, a subset of the genes analyzed by qRT-PCR, which display significant breed differences, could collectively contribute to the trypanotolerance trait in N’Dama. Overall design: Animals and experimental infection The work presented here is based on an experimental infection that was previously described. Briefly, eight Boran (B. indicus, trypanosusceptible) and eight N’Dama (B. taurus, trypanotolerant) female cattle, aged between 19-28 months, were raised together at the International Livestock Research Institute (ILRI) farm at Kapiti Plains Estate, Kenya in an area free from trypanosomiasis. The cattle were each experimentally infected with the T. congolense clone IL1180, which was delivered via the bites of eight infected tsetse flies [Ref. G. morsitans morsitans] Blood collection, PBMC isolation and RNA extraction and purification Peripheral blood (200 ml) was collected before infection and at 14, 21, 25, 29 and 34 dpi in heparanized syringes. These time points were chosen to coincide with the first wave of parasitaemia. Peripheral blood mononuclear cells (PBMC) were isolated using Percoll™ gradients (GE Healthcare, www.gehealthcare.com) and previously described methods, washed with sterile PBS and stored immediately at -80°C in Tri-reagent (Molecular Research Center, Inc, www.mrcgene.com). Total RNA was extracted with chloroform and precipitated with isopropanol. Each sample was further DNase-treated with RQ1 RNase-free DNase (Promega Corp., www.promega.com) and purified using the RNeasy® mini kit (Qiagen, www.qiagen.com). RNA quality and quantity was subsequently assessed using the 18S/28S ratio and RNA integrity number (RIN) on an Agilent Bioanalyzer with the RNA 6000 Nano LabChip® kit (Agilent Technologies, Inc., www.agilent.com). The bovine long oligo (BLO) microarray The NCBI GEO platform accession for the BLO microarray is GPL3810. The BLO microarray platform has 17,328 spot features representing approximately 7,920 predicted bovine mRNA’s spotted in duplicate supplemented with positive (GAPDH, RPL19, RPLP2, 28S RNA, 60S RNA, PPIA, ACTB, PGK1, B2M and GUSB), negative and artificial control sequences spotted multiple times. The oligonucleotides (70-mers) were designed and synthesized commercially by Operon Biotechnologies (Operon Biotechnologies, Inc., www.operon.com). The oligonucleotides were designed to the The Institute for Genomic Research (TIGR) tentative consensus (TC) sequences (release October 5th 2004). cDNA conversion, labelling and hybridization to bovine long oligonucleotide microarrays Labelled cDNA was generated using the SuperScript™ Plus Direct cDNA labelling System (Invitrogen Corp., www.invitrogen.com) according to the manufacturers’ instructions. Briefly, 8 µg of sample RNA was labelled with Alexa Fluor® 555 and 10 µg of common reference RNA (CRR) was labelled with Alexa Fluor® 647. A common reference RNA pool was generated by combing equal quantities of all samples in the study, which included RNA from pre- and post-infection time points. Labelled samples were purified using the purification module included with the SuperScript™ Plus Direct cDNA labelling System, combined and supplemented with approximately 60-70 µl SlideHyb Glass Hybridization Buffer #3 (Ambion Inc., www.ambion.com) to a final probe volume of 100 µl. Probes were hybridized to bovine long oligonucleotide (BLO) microarrays, using an automated HS400 hybridization station (Tecan UK Ltd., www.tecan.com) with the following optimized protocol; WASH: 75°C, Runs 1, Wash 10 s, Soak 20 s; PROBE INJECTION: 85°C; Denaturation: 95°C, 2 mins; HYBRIDISATION: 42°C – 4 hrs; 35°C – 4 hrs; 30°C – 4 hrs; agitation frequency medium, WASH: 37°C, Runs 2, Wash 10 s, Soak 20 s; 25°C, Runs 2, Wash 15 s, Soak 30 s; 25°C, Runs 2, Wash 20 s, Soak 40 s and SLIDE DRYING: 25°C for 2 mins. Data collection, normalization, quality control and statistical analysis Microarrays were scanned using a GenePix® 4000B scanner (Molecular Devices Corp., www.moleculardevices.com). The microarray hybridizations represented 5-8 animals of each breed at all of the time points (0, 14, 21, 25, 29 and 34 dpi) where the CRR served as the reference sample in each case (for a total of 88 slides). Spot features where foreground was less than background plus two standard deviations were flagged as lowly expressed. The linear models for microarray data (LIMMA) package in Bioconductor was used to identify differential gene expression. Background correction was performed according to the robust multichip average (RMA) method. An intensity-based normalization method was employed: within microarray print-tip dependent locally weighted scatterplot smoothing (LOWESS) normalization, followed by between microarray quantile normalization.