Purpose: Acupuncture is reported to be effective in treating obesity related illnesses, but its mechanism is still unclear. To investigate this mechanism we applied electro-acupuncture (EA) in a mouse model of obesity and used RNA-seq to identify molecular consequences. Methods: Adult male mice (17w) were divided into three groups: Stat5fl/fl, Stat5NKO, Stat5NKO+EA groups, hypothalamus and Epi-WAT mRNA profiles of mice in each group were generated by deep sequencing,using Illumina Hiseq 2000. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. Results: Using an optimized data analysis workflow, we mapped about 25 million sequence reads per sample to the mouse genome (UCSC mm9) and identified transcripts in the Stat5fl/fl, Stat5NKO and Stat5NKO+EA mice with TopHat and Cufflinks workflow respectively. Genes with lower than one FPKM (average fragments per kilobase of transcript per million fragments mapped) were filtered out. Up-regulation and down-regulation were defined as a relative transcription level above Log2 fold change (FC) ≥ |±1| and P value <0.05. Conclusions: Our results provided, for the first time, insight into genomic networks of obesity and their modulation by electro-acupuncture, which in turn reveals potential mechanisms that explain acupuncture-induced weight-loss.

Stat5, Adam7, 9230104L09Rik, Teddm1, 2210415F13Rik, Defb25, Defb30, Spink2, Wfdc10, 5830403L16Rik, Ly6g5b, Mmp7, Hspb7, Hba-a1/a2, Crip1, Ccl6, Krt19, Ccl9, F13a1, Gh
Prl, Lep, Igfals, Plin1, Agpat2, Mogat2, Cidec, AY761185, Cst11, Defb20, Defb28, Defb48, Lcn8, Lcn9, Gpx5, Cst12, Ucp1, Cox7a1, Trfr2, Ptgr1
Gbp1, Fam5b, Dnmt3l, Fmr1, Tuba1a, Sec16b, Rasal2, Etv5, Slc39a8, Tfap2b, Nfe2l3, Faim2, Npc1, Sim1, Dgkg, Enpp1, Grb14, Pter, Mtch2, Gtf3a
Tmem160