利用基因芯片对阉割引起牛生长发育和脂肪沉积变化分子机理的研究
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摘要
本试验首先以同龄、同场的60头国内、外肉牛品种为研究对象,利用超声波活体检测技术采用最小二乘法建立了肉牛宰后肉质性状的预测模型,显示超声波技术不仅可以准确、快速、低成本的检测肉牛背膘厚、眼肌面积和大理石花纹情况,还提供了通过检测活体性状预测宰后性状的可能。
为研究肉牛生长发育和脂肪沉积的分子机制,本试验以西门塔尔牛公牛和阉牛各3头作为试验材料,因为阉割是肉牛生产中常用的技术手段,阉割后肉牛在习性、外观和生长发育过程都发生了很大的改变,这些发展的速度很慢,暗示这些发展是通过基因表达差异的改变进行的,因此采用Affymetix公司的基因芯片技术,研究了二者之间肝脏和脂肪组织的基因表达谱,经过数据分析找到了因阉割引起的生长发育减缓,脂肪沉积速度加快的有关的差异表达基因。并通过荧光定量PCR技术对芯片结果进行验证。
结果如下:
(1)本研究在国内首次建立了超声波技术活体检测技术预测牛肉产量的数学模型:屠宰EMA=30.6032+1.0383×8月龄EMA ,屠宰EMA=8.3520+0.8873×20月龄EMA ;屠宰RIB12=0.3777+0.3470×8月龄RIB12,屠宰RIB12=0.2856+0.4203×20月龄RIB12;高档肉质量=0.3616×8月龄EMA +40.4824×8月龄RIB12+0.065×8月龄体重,高档肉质量=0.6765×8月龄EMA +39.0974×8月龄RIB12,高档肉质量=0.4451×20月龄EMA +1.3847×20月龄RIB12+0.0177×20月龄体重,高档肉质量=0.5621×20月龄EMA +2.7208×20月龄RIB12;后部肉质量=1.1316×8月龄EMA +24.4678×8月龄RIB12+0.0985×8月龄体重,后部肉质量=1.6034×8月龄EMA +22.3924×8月龄RIB12,后部肉质量=0.9869×20月龄EMA -9.5036×20月龄RIB12+0.0148×20月龄体重,后部肉质量=1.0849×20月龄EMA -8.3843×20月龄RIB12;优质肉质量=1.4932×8月龄EMA +64.9502×8月龄RIB12+0.1642×8月龄体重,优质肉质量=2.8384×8月龄EMA +61.4898×8月龄RIB12,优质肉质量=1.4320×20月龄EMA -8.1190×20月龄RIB12+0.0325×20月龄体重,优质肉质量=1.6470×20月龄EMA -5.6636×20月龄RIB12;胴体质量=8.3397×8月龄EMA -204.1618×8月龄RIB12+0.3270×8月龄体重,胴体质量=9.8856×8月龄EMA -198.8285×8月龄RIB12,胴体质量=0.9547×20月龄EMA -93.4699×20月龄RIB12+0.5753×20月龄体重,胴体质量=4.4994×20月龄EMA +7.6870×20月龄RIB12。模型都达到显著水平( p<0.05),可以在实际生产中灵活运用。通过我们实践中测得的牛数据对模型的验证,表明所得模型计算方便,精确度高,具有较强的实用性,提供了从幼龄牛或成年牛预测宰后性状的可能。
(2)对西门塔尔牛公牛和阉牛各5头的生长性状和肉质性状进行分析,发现育肥初公牛和阉牛的生长发育性状(体重、体高、体斜长、胸围和管围)无差异(p>0.05),肥育14个月后公牛体斜长、出栏重、屠宰重、胴体深显著高于阉牛(p<0.05);肉质性状中公牛胴体重、蹄重、前腿肉、脂色、眼肌面积显著高于阉牛,但系膜网膜油、大理石花纹、背膘厚、水分和含钙量显著低于阉牛(p<0.05),且公牛脖肉、里脊和上脑重极显著高于阉牛(p<0.01),结果可以看出,与生长相关的性状阉牛发育较慢,但脂肪沉积速度较公牛快,阉牛肉质性状较公牛好。
(3)随机选取健康无病公牛和阉牛各3头,利用Affymetrix基因芯片对其肝脏组织进行差异表达分析发现,公牛与阉牛相比代表334个基因的362个探针发生转录变化(大于等于2倍或小于等于0.5倍),其有251个已知基因发生转录改变,上调195条、下调56条,它们主要20个参与免疫系统过程、26个参与刺激应答、22个参与发育过程、19个参与多细胞有机过程、9个参与生物粘连生物学过程,多位于胞外区(13个),具有结合功能(77个)。没有分类信息的基因132个。结合关键字方法共获得直接影响生长发育和脂质代谢的基因173个在肝脏中发生转录变化。涉及酶调控功能、结合功能、催化功能、抗氧化剂功能、分子转运功能、结构分子功能、转录因子功能和运输功能。通路分析结果显示阉割后引起生长发育迟缓的机理可能是阉割后雄激素分泌的减少会引起肝脏IGF1上调和IGFBP5转录下调,从而引起胰岛素通路上FBP2和PPARGC1a、肌动蛋白调控通路上ACTG2、BAIAP2、MGC127421、ITGB2和SCIN基因发生转录变化,从而导致肌肉合成速度减慢。并且阉割后引起大量免疫相关基因BOLA-DQA1、BOLA-DQA2、BOLA-DRB13、SELL、JSP.1、EVA1、LRRC25、CD53、LOC783725、FCGR3A发生转录变化,揭示阉割后可能免疫基因的转录变化也影响了生长发育和脂质代谢。
(4)对阉牛和公牛脂肪基因芯片筛选发现,有1925个已知基因发生转录改变,上调103条、下调1822条,它们主要参与代谢过程(406个)、生物调节(176个)、定位(138个)、巨大细胞过程(95个)、刺激应答(91个)、发育过程(89个)、生长(16个)、免疫过程(41个)和生物粘连(38个),多位于细胞器官(301个)、胞外区(64个)和外膜(36个)上,多数为涉及结合功能(524个)、催化功能(326个)和酶调控功能(57个)的基因。经分析推测由于阉割,引起雄性激素和雌性激素代谢途径中的HAD11B1、UGT1A1和HSD基因差异表达,引起激素水平中的LHCGR、PRL、PRLR和GHR转录下调,从而调节ApoE,影响脂类代谢。阉割可能引起脂肪细胞自身分泌LEP基因减少,并且乳糖通路所有基因在转录水平上均发生变化。引起免疫通路中IL2/3和EPO发生变化,从而引起一系列反应,影响蛋白质水解过程。从而影响脂肪沉积过程。
(5)肝脏和脂肪差异表达基因结果各选择了10个代表性基因进行FQ-PCR验证,结果显示除脂肪LEPR基因外所有的基因表达变化趋势与芯片杂交反映的结果一致,基因的表达变化情况符合生理学特征,也从另外一个角度证明本研究筛选的生长发育和脂肪沉积相关基因准确可靠、具有潜在的应用价值。LEPR基因检测结果不符合也证明了选择(0.5,2)作为筛选标准具有实践性,采用倍数法不应任意缩小差异标准。
总之,本研究获得的差异表达基因为今后进一步深入研究牛乃至整个哺乳动物生长发育和脂肪沉积提供了一个有价值而重要的候选基因库。
60 cattle at same age and same factory were used to establish prediction modes of pos slaughter traits by ultrasound measurement in live cattle. The results showed that ultrasound technology can not only accurate, rapid, low-cost testing beef cattle surface fat between the 12th and 13th ribs over the longissimus muscle(RIB12),ribeeye muscle area(EMA) and marbling but also provided the chance to forecast pos slaughter traits by living cattle.
The liver and lipid samples from 3 bull and 3 steer-Simmental cattle were collected to study the growth and fat deposition of molecular mechanisms in Beef cattle by genechip. Castration is a commonly technology used in beef cattle production. the habits, appearance and growth of cattle have taken great changes after emasculation. Such development was very slow suggesting that these developments was through gene expression changes differently. So the genechip technology was used to research the difference gene expression profiling of the liver and adipose tissue to find the growth rate decrease and fat deposition rate increase mechanism in our experiment. The results were verified by fluorescence quantitative PCR.The results were as follows:
(1) The prediction models of pos slaughter traits by ultrasound measurement in live cattle were established first in China:EMA after slaughter =30.6032+1.0383×8Month EMA, EMA after slaughter =8.3520+0.8873×20Month EMA, RIB12 after slaughter =0.3777+0.3470×8Month RIB12, RIB12 after slaughter =0.2856+0.4203×20 MonthRIB12, high-grade meat quality =0.3616×8 Month EMA +40.4824×8 Month RIB12+0.065×8 Months Weight, high-grade meat quality =0.6765×8 Month EMA +39.0974×8 MonthRIB12, high-grade meat quality =0.4451×20Month EMA+1.3847×20Month RIB12+0.0177×20 Month Weight, high-grade meat quality=0.5621×20Month EMA +2.7208×20 Month RIB12, rear meat quality=1.1316×8 Month EMA +24.4678×8 Month RIB12+0.0985×8 Month Weight, rear meat quality =1.6034×8 Month EMA +22.3924×8 Month RIB12, rear meat quality =0.9869×20 Month EMA -9.5036×20 Month RIB12+0.0148×20 Month Weight, rear meat quality =1.0849×20 Month EMA -8.3843×20 MonthRIB12, fine quality meat quality=1.4932×8 Month EMA +64.9502×8 Month RIB12+0.1642×8 Month Weight, fine quality meat quality =2.8384×8 Month EMA +61.4898×8 Month RIB12, fine quality meat quality =1.4320×20 Month EMA -8.1190×20 Month RIB12+0.0325×20 Month Weight, fine quality meat quality =1.6470×20 Month EMA -5.6636×20 Month RIB12, carcass quality=8.3397×8 Month EMA -204.1618×8 Month RIB12+0.3270×8 Month Weight, carcass quality =9.8856×8 Month EMA -198.8285×8 Month RIB12, carcass quality =0.9547×20 Month EMA -93.4699×20 Month RIB12+0.5753×20 Month Weight, carcass quality =4.4994×20 Month EMA +7.6870×20 Month RIB12.It is significant in all models(p<0.05).After demonstration all models could be used flexible in actual production.So the models were convenient, high-precision, greater practicality and could provid the possible to predict the pos slaughter traits from young cattle or adult cattle.
(2) The growth traits and meat traits by 5 bull and 5 steer were analysed the different between them. The results showed that the growth traits(body weight,withers high, diagonal length,heart girth,pastern girth) were no different at 8 month(p>0.05) but the body weight and diagonal length of bull after 14 month breeding were higher than steer(p<0.05). After slaughter, the slaughter weight and naked body depth of bull were higher than steer too(p<0.05). The naked body weight,feet weight,shank weight,fat colour, EMA, and Ca content of bull were higher than steer ,but the retina lipid, marbling, RIB12, water content and Ca content of steer were higher than bull (p<0.05).The chudr weight, tenderloin weight and highrid weight of bull were significant higher than steer(p<0.01).So It can be concluded that the growth rate was decreased but fat depositon rate was increased afer emasculation.
(3) 3 healthy disease-free bull and steer were selected randomly to analysis the liver differentially expressed genes by Affymetrix genechip.The results showed that 362 probe , represent 334 gene were changes. There were 251 known gene changed, 195 up, 56 down. They participate in immune system process(20), response to stimulus(26), development process(22), multi-cell organic process(19), biological adhesion(9), more in the extracellular region(13), binding(77)., 132 unclassified. With the keyword method 139 genes were different transcript in liver of growth and lipid metabolism. They were involved in Enzyme regulator activity, binding, catalytic activity, antioxidant activity, molecular transducer activity, structural molecule activity, transcription factor activity and transporter activity. Pathway analysis showed that the mechanism of the emasculation in growth rate decreasing may be related with male hormone secretion reduced after castrated caused liver IGF1 and IGFBP5 transcription down, thus leading to the insulin pathway FBP2 and PPARGC1a, actin regulatory pathway on ACTG2, BAIAP2, MGC127421, ITGB2 and SCIN changes in gene transcription, leading to slow down the speed of muscle synthesis. After castration caused massive immune-related genes BOLA-DQA1, BOLA-DQA2, BOLA-DRB13, SELL, JSP.1, EVA1, LRRC25, CD53, LOC783725, FCGR3A changes in transcription. Revealed the immune gene transcription changes caused by emasculation have also affected the growth and lipid metabolism.
(4) there were 1,925 known gene transcription changes( up 103, down 1,822) using genechip to analysis the different transcription of lipid organ between bull and steer.They mainly involved in metabolic process(406), biological regulation(176),localization(138), multicellular organismal process (95), response to stimulus(91), developmental process (89), growth (16), immune system process (41) and biological adhesion (38). Most of them located in organelle (301), extracellular region(64) and envelope(36), most molecular function were related to binding(524), catalytic activity(326) and the enzyme regulator activity(57). Then it was supposed that the reason due to lipid deposition change after castrate might be the HAD11B1, UGT1A1 and HSD gene expression different in androgen and estrogen metabolism pathway. That caused LHCGR, PRL, PRLR and GHR transcription downturn at hormone levels to regulate ApoE, impact on lipid metabolism. Castration likely to cause fat cells to reduce its own secrete of LEP. All gene of leptin access roads transcription in the level of change. And IL2 / 3 and EPO gene expression were changend in immune pathway, thus leading to a series of reactions, affect protein hydrolysis process. Thus affect fat deposition process.
(5) 10 representative genes in liver and fat were selected to verified the result of genechip by FQ-PCR. The results showed that all genes changed consistent with the result of genechip except LEPR gene.Gene expression changes consistent with the physiological characteristics, From another point of view, this study proved that the growth of screening and fat deposition related genes are accurate and reliable, have potential value. LEPR genes do not meet the test results also proved that the choice (0.5, 2) as a screening standards are practical, using multiples of law should not arbitrarily narrow the differences in standards.
Different expressed genes in the study provided a valuable and important candidate gene pool for the future further in-depth study cattle and even the mammals growth and fat deposition.
为研究肉牛生长发育和脂肪沉积的分子机制,本试验以西门塔尔牛公牛和阉牛各3头作为试验材料,因为阉割是肉牛生产中常用的技术手段,阉割后肉牛在习性、外观和生长发育过程都发生了很大的改变,这些发展的速度很慢,暗示这些发展是通过基因表达差异的改变进行的,因此采用Affymetix公司的基因芯片技术,研究了二者之间肝脏和脂肪组织的基因表达谱,经过数据分析找到了因阉割引起的生长发育减缓,脂肪沉积速度加快的有关的差异表达基因。并通过荧光定量PCR技术对芯片结果进行验证。
结果如下:
(1)本研究在国内首次建立了超声波技术活体检测技术预测牛肉产量的数学模型:屠宰EMA=30.6032+1.0383×8月龄EMA ,屠宰EMA=8.3520+0.8873×20月龄EMA ;屠宰RIB12=0.3777+0.3470×8月龄RIB12,屠宰RIB12=0.2856+0.4203×20月龄RIB12;高档肉质量=0.3616×8月龄EMA +40.4824×8月龄RIB12+0.065×8月龄体重,高档肉质量=0.6765×8月龄EMA +39.0974×8月龄RIB12,高档肉质量=0.4451×20月龄EMA +1.3847×20月龄RIB12+0.0177×20月龄体重,高档肉质量=0.5621×20月龄EMA +2.7208×20月龄RIB12;后部肉质量=1.1316×8月龄EMA +24.4678×8月龄RIB12+0.0985×8月龄体重,后部肉质量=1.6034×8月龄EMA +22.3924×8月龄RIB12,后部肉质量=0.9869×20月龄EMA -9.5036×20月龄RIB12+0.0148×20月龄体重,后部肉质量=1.0849×20月龄EMA -8.3843×20月龄RIB12;优质肉质量=1.4932×8月龄EMA +64.9502×8月龄RIB12+0.1642×8月龄体重,优质肉质量=2.8384×8月龄EMA +61.4898×8月龄RIB12,优质肉质量=1.4320×20月龄EMA -8.1190×20月龄RIB12+0.0325×20月龄体重,优质肉质量=1.6470×20月龄EMA -5.6636×20月龄RIB12;胴体质量=8.3397×8月龄EMA -204.1618×8月龄RIB12+0.3270×8月龄体重,胴体质量=9.8856×8月龄EMA -198.8285×8月龄RIB12,胴体质量=0.9547×20月龄EMA -93.4699×20月龄RIB12+0.5753×20月龄体重,胴体质量=4.4994×20月龄EMA +7.6870×20月龄RIB12。模型都达到显著水平( p<0.05),可以在实际生产中灵活运用。通过我们实践中测得的牛数据对模型的验证,表明所得模型计算方便,精确度高,具有较强的实用性,提供了从幼龄牛或成年牛预测宰后性状的可能。
(2)对西门塔尔牛公牛和阉牛各5头的生长性状和肉质性状进行分析,发现育肥初公牛和阉牛的生长发育性状(体重、体高、体斜长、胸围和管围)无差异(p>0.05),肥育14个月后公牛体斜长、出栏重、屠宰重、胴体深显著高于阉牛(p<0.05);肉质性状中公牛胴体重、蹄重、前腿肉、脂色、眼肌面积显著高于阉牛,但系膜网膜油、大理石花纹、背膘厚、水分和含钙量显著低于阉牛(p<0.05),且公牛脖肉、里脊和上脑重极显著高于阉牛(p<0.01),结果可以看出,与生长相关的性状阉牛发育较慢,但脂肪沉积速度较公牛快,阉牛肉质性状较公牛好。
(3)随机选取健康无病公牛和阉牛各3头,利用Affymetrix基因芯片对其肝脏组织进行差异表达分析发现,公牛与阉牛相比代表334个基因的362个探针发生转录变化(大于等于2倍或小于等于0.5倍),其有251个已知基因发生转录改变,上调195条、下调56条,它们主要20个参与免疫系统过程、26个参与刺激应答、22个参与发育过程、19个参与多细胞有机过程、9个参与生物粘连生物学过程,多位于胞外区(13个),具有结合功能(77个)。没有分类信息的基因132个。结合关键字方法共获得直接影响生长发育和脂质代谢的基因173个在肝脏中发生转录变化。涉及酶调控功能、结合功能、催化功能、抗氧化剂功能、分子转运功能、结构分子功能、转录因子功能和运输功能。通路分析结果显示阉割后引起生长发育迟缓的机理可能是阉割后雄激素分泌的减少会引起肝脏IGF1上调和IGFBP5转录下调,从而引起胰岛素通路上FBP2和PPARGC1a、肌动蛋白调控通路上ACTG2、BAIAP2、MGC127421、ITGB2和SCIN基因发生转录变化,从而导致肌肉合成速度减慢。并且阉割后引起大量免疫相关基因BOLA-DQA1、BOLA-DQA2、BOLA-DRB13、SELL、JSP.1、EVA1、LRRC25、CD53、LOC783725、FCGR3A发生转录变化,揭示阉割后可能免疫基因的转录变化也影响了生长发育和脂质代谢。
(4)对阉牛和公牛脂肪基因芯片筛选发现,有1925个已知基因发生转录改变,上调103条、下调1822条,它们主要参与代谢过程(406个)、生物调节(176个)、定位(138个)、巨大细胞过程(95个)、刺激应答(91个)、发育过程(89个)、生长(16个)、免疫过程(41个)和生物粘连(38个),多位于细胞器官(301个)、胞外区(64个)和外膜(36个)上,多数为涉及结合功能(524个)、催化功能(326个)和酶调控功能(57个)的基因。经分析推测由于阉割,引起雄性激素和雌性激素代谢途径中的HAD11B1、UGT1A1和HSD基因差异表达,引起激素水平中的LHCGR、PRL、PRLR和GHR转录下调,从而调节ApoE,影响脂类代谢。阉割可能引起脂肪细胞自身分泌LEP基因减少,并且乳糖通路所有基因在转录水平上均发生变化。引起免疫通路中IL2/3和EPO发生变化,从而引起一系列反应,影响蛋白质水解过程。从而影响脂肪沉积过程。
(5)肝脏和脂肪差异表达基因结果各选择了10个代表性基因进行FQ-PCR验证,结果显示除脂肪LEPR基因外所有的基因表达变化趋势与芯片杂交反映的结果一致,基因的表达变化情况符合生理学特征,也从另外一个角度证明本研究筛选的生长发育和脂肪沉积相关基因准确可靠、具有潜在的应用价值。LEPR基因检测结果不符合也证明了选择(0.5,2)作为筛选标准具有实践性,采用倍数法不应任意缩小差异标准。
总之,本研究获得的差异表达基因为今后进一步深入研究牛乃至整个哺乳动物生长发育和脂肪沉积提供了一个有价值而重要的候选基因库。
60 cattle at same age and same factory were used to establish prediction modes of pos slaughter traits by ultrasound measurement in live cattle. The results showed that ultrasound technology can not only accurate, rapid, low-cost testing beef cattle surface fat between the 12th and 13th ribs over the longissimus muscle(RIB12),ribeeye muscle area(EMA) and marbling but also provided the chance to forecast pos slaughter traits by living cattle.
The liver and lipid samples from 3 bull and 3 steer-Simmental cattle were collected to study the growth and fat deposition of molecular mechanisms in Beef cattle by genechip. Castration is a commonly technology used in beef cattle production. the habits, appearance and growth of cattle have taken great changes after emasculation. Such development was very slow suggesting that these developments was through gene expression changes differently. So the genechip technology was used to research the difference gene expression profiling of the liver and adipose tissue to find the growth rate decrease and fat deposition rate increase mechanism in our experiment. The results were verified by fluorescence quantitative PCR.The results were as follows:
(1) The prediction models of pos slaughter traits by ultrasound measurement in live cattle were established first in China:EMA after slaughter =30.6032+1.0383×8Month EMA, EMA after slaughter =8.3520+0.8873×20Month EMA, RIB12 after slaughter =0.3777+0.3470×8Month RIB12, RIB12 after slaughter =0.2856+0.4203×20 MonthRIB12, high-grade meat quality =0.3616×8 Month EMA +40.4824×8 Month RIB12+0.065×8 Months Weight, high-grade meat quality =0.6765×8 Month EMA +39.0974×8 MonthRIB12, high-grade meat quality =0.4451×20Month EMA+1.3847×20Month RIB12+0.0177×20 Month Weight, high-grade meat quality=0.5621×20Month EMA +2.7208×20 Month RIB12, rear meat quality=1.1316×8 Month EMA +24.4678×8 Month RIB12+0.0985×8 Month Weight, rear meat quality =1.6034×8 Month EMA +22.3924×8 Month RIB12, rear meat quality =0.9869×20 Month EMA -9.5036×20 Month RIB12+0.0148×20 Month Weight, rear meat quality =1.0849×20 Month EMA -8.3843×20 MonthRIB12, fine quality meat quality=1.4932×8 Month EMA +64.9502×8 Month RIB12+0.1642×8 Month Weight, fine quality meat quality =2.8384×8 Month EMA +61.4898×8 Month RIB12, fine quality meat quality =1.4320×20 Month EMA -8.1190×20 Month RIB12+0.0325×20 Month Weight, fine quality meat quality =1.6470×20 Month EMA -5.6636×20 Month RIB12, carcass quality=8.3397×8 Month EMA -204.1618×8 Month RIB12+0.3270×8 Month Weight, carcass quality =9.8856×8 Month EMA -198.8285×8 Month RIB12, carcass quality =0.9547×20 Month EMA -93.4699×20 Month RIB12+0.5753×20 Month Weight, carcass quality =4.4994×20 Month EMA +7.6870×20 Month RIB12.It is significant in all models(p<0.05).After demonstration all models could be used flexible in actual production.So the models were convenient, high-precision, greater practicality and could provid the possible to predict the pos slaughter traits from young cattle or adult cattle.
(2) The growth traits and meat traits by 5 bull and 5 steer were analysed the different between them. The results showed that the growth traits(body weight,withers high, diagonal length,heart girth,pastern girth) were no different at 8 month(p>0.05) but the body weight and diagonal length of bull after 14 month breeding were higher than steer(p<0.05). After slaughter, the slaughter weight and naked body depth of bull were higher than steer too(p<0.05). The naked body weight,feet weight,shank weight,fat colour, EMA, and Ca content of bull were higher than steer ,but the retina lipid, marbling, RIB12, water content and Ca content of steer were higher than bull (p<0.05).The chudr weight, tenderloin weight and highrid weight of bull were significant higher than steer(p<0.01).So It can be concluded that the growth rate was decreased but fat depositon rate was increased afer emasculation.
(3) 3 healthy disease-free bull and steer were selected randomly to analysis the liver differentially expressed genes by Affymetrix genechip.The results showed that 362 probe , represent 334 gene were changes. There were 251 known gene changed, 195 up, 56 down. They participate in immune system process(20), response to stimulus(26), development process(22), multi-cell organic process(19), biological adhesion(9), more in the extracellular region(13), binding(77)., 132 unclassified. With the keyword method 139 genes were different transcript in liver of growth and lipid metabolism. They were involved in Enzyme regulator activity, binding, catalytic activity, antioxidant activity, molecular transducer activity, structural molecule activity, transcription factor activity and transporter activity. Pathway analysis showed that the mechanism of the emasculation in growth rate decreasing may be related with male hormone secretion reduced after castrated caused liver IGF1 and IGFBP5 transcription down, thus leading to the insulin pathway FBP2 and PPARGC1a, actin regulatory pathway on ACTG2, BAIAP2, MGC127421, ITGB2 and SCIN changes in gene transcription, leading to slow down the speed of muscle synthesis. After castration caused massive immune-related genes BOLA-DQA1, BOLA-DQA2, BOLA-DRB13, SELL, JSP.1, EVA1, LRRC25, CD53, LOC783725, FCGR3A changes in transcription. Revealed the immune gene transcription changes caused by emasculation have also affected the growth and lipid metabolism.
(4) there were 1,925 known gene transcription changes( up 103, down 1,822) using genechip to analysis the different transcription of lipid organ between bull and steer.They mainly involved in metabolic process(406), biological regulation(176),localization(138), multicellular organismal process (95), response to stimulus(91), developmental process (89), growth (16), immune system process (41) and biological adhesion (38). Most of them located in organelle (301), extracellular region(64) and envelope(36), most molecular function were related to binding(524), catalytic activity(326) and the enzyme regulator activity(57). Then it was supposed that the reason due to lipid deposition change after castrate might be the HAD11B1, UGT1A1 and HSD gene expression different in androgen and estrogen metabolism pathway. That caused LHCGR, PRL, PRLR and GHR transcription downturn at hormone levels to regulate ApoE, impact on lipid metabolism. Castration likely to cause fat cells to reduce its own secrete of LEP. All gene of leptin access roads transcription in the level of change. And IL2 / 3 and EPO gene expression were changend in immune pathway, thus leading to a series of reactions, affect protein hydrolysis process. Thus affect fat deposition process.
(5) 10 representative genes in liver and fat were selected to verified the result of genechip by FQ-PCR. The results showed that all genes changed consistent with the result of genechip except LEPR gene.Gene expression changes consistent with the physiological characteristics, From another point of view, this study proved that the growth of screening and fat deposition related genes are accurate and reliable, have potential value. LEPR genes do not meet the test results also proved that the choice (0.5, 2) as a screening standards are practical, using multiples of law should not arbitrarily narrow the differences in standards.
Different expressed genes in the study provided a valuable and important candidate gene pool for the future further in-depth study cattle and even the mammals growth and fat deposition.
引文
1. 曹红鹤,王雅春,陈幼春.南阳、皮埃蒙特及其杂交牛的血液生化遗传标记与生长性状关系.畜牧兽医学报.1999;30(6):496～503
2. 陈宝生,万学东,夏炎枝等.花生四烯酸改善饱和脂肪酸诱导肝细胞胰岛素抵抗的作用机制.山东医药.2007;47(28):1～3
3. 陈思忠.超声波清洗技术与发展.洗净技术.2004;2(2):7～12.
4. 程志平主编.内分泌生理学.北京: 人民卫生出版社.1984.
5. 崔强,蔡荣,钱程等.一种新的疾病治疗候选基因: SOCS-1.生命科学.2006;18 (3):290～294
6. 邓桂馨.肉牛 CAST 基因和 HFABPL 基因多态性及其与肉品质性状关系的研究 [硕士学位论文]. 北京:中国农业科学院,2003.
7. 丁俊杰,焦正,李中东等.Bootstrap 法验证有限抽样法多元回归模型.中国卫生统计.2004;21 (5 ):289～292
8. 丁世飞,程述汉, 苏本堂.多元模糊回归预测模型及其应用.模糊系统与数学.2000;4:94～98.
9. 杜新宇. 架子牛育肥的技术问题.饲料与畜牧科学.2007;,1:16-18.
10. 冯仁田,张玉民.抑素的研究进展,中国药学杂志.199;28(10):583~585.
11. 傅伟龙,江青艳,刘平祥.神经内分泌生长轴的研究概况及对猪的生长调控研究.中国科学基金.2003;3:151~155.
12. 高腾云,王艳玲,韩正康等.半胱胺对肉牛增重、采食量和血液激素水平的影响.华中农业大学学报.2001;20(3):259~261.
13. 高雪.牛生长发育性状候选基因的分子标记研究[博士学位论文].杨凌:西北农林科技大学,2004.
14. 葛飞.超声波技术的应用现状及发展前景.郑州牧业工程高等专科学校学报.1999;19(1):58～59.
15. 郭芬,李月琴,周天鸿.鞘脂激活蛋白原的研究进展. 中国病理生理杂志 .2006;12: 2485～2488.
16. 郭万库,师守堃,吴常信.肉用动物双肌性状的研究现状. 国外畜牧科技.1999;26,(3):34～38.
17. 郭玮.用基因芯片研究 CLB 处理的猪肪肪组织基因的差异表达[博士学位论文].北京:中国农业大学,2004.
18. 郭燕青.牛 LPL、HSL 基因克隆、SNPs 筛查及其与肉质性状的关联分析. [硕士学位论文].北京:中国农业科学院,2007.
19. 哈珀,罗德韦尔,梅斯著.生理化学评论.北京:科学出版社.1985.
20. 韩正康 , 林玲 . 生长抑素耗竭剂 - 半胱胺促进肉用仔鸡生长的研究 . 畜牧兽医学报 . 1992;23:314～318.
21. 胡宝利.不同年龄秦川牛胴体性状与肉质性状的研究[硕士学位论文].杨凌:西北农林科技大学,2001.
22. 胡晓湘.猪肥胖基因(ob)及其受体(OBR)基因的分子遗传学研究[硕士学位论文]. 北京:中国农业大学,1998.
23. 胡延佳,翦新春.基因芯片数据分析过程:从原始数据到生物意义.生物技术通讯.2007; 18(2) :333～335
24. 黄明,刘冠勇,罗欣.影响肉嫩度因素的探讨.肉类工业.2000;233(11):26～28.
25. 荆志伟,王忠.基因芯片数据分析方法研究进展.生物技术通讯.2007;18(1):144～148.
26. 雷帆,刑东明,孙虹等.肥胖相关生物因子的研究.中国药学杂志.2002;37(1):5～8.
27. 黎敏义,郭文军,刘颖等.调控畜禽繁殖的激素免疫技术.动物医学进展,2005;26 (11) :1～4.
28. 李常绿.应用 DNA 微阵列技术对洛克沙砷处理肉鸡后肝脏和胸肌组织基因表达谱的研究[博士学位论文].北京:中国农业大学,2004.
29. 李加琪,陈赞谋,刘德武等.IGF1 基因对长白×蓝塘猪资源群生产性能的遗传效应分析.遗传学报. 2003;9: 835～839.
30. 李君,赵成义,朱宏等.融雪后梭梭林地土壤水的多尺度空间异质性.中国科学(D).2006;36 (增刊 Ⅱ ): 45～50.
31. 李伟,张书慧, 张倩等.近红外光谱法快速测定土壤碱解氮、速效磷和速效钾含量.农业工程学报.2007;23(1):55～59.
32. 李武峰,许尚忠,曹红鹤等.3 个杂交牛种H -FAB P 基因第二内含子的遗传变异与肉品质性状的相关分析.畜牧兽医学报. 2004;35 (3):252～255.
33. 李雅莉.超声波清洗的原理和实际应用.清洗世界.2006;22(7):31～35.
34. 李瑶主编.基因芯片数据分析与处理.北京:化学工业出版社现代生物技术与医药科技出版中心.2006,7.
35. 林金杏,阎萍,曾宪成.现代牛分子育种及其发展趋势.中国畜牧杂志.2007;(增刊):271~275.
36. 林玲,韩正康,生长抑素耗竭剂-半胱胺促进大鼠、幼兔生长的研究.中国应用生理学杂志.1991;7(4):314~318.
37. 刘波.秦川牛及其杂交后代生长发育性状的分子标记研究[硕士学位论文].杨凌:西北农林科技大学,2004.
38. 刘敬顺,包杰,张豪.猪的活体超声波评估技术与方法.当代畜禽养殖业.2003;10:2～7.
39. 刘伟国,周景义,杨小峰等.天然细胞生长调控因子对原代培养神经细胞生长影响的实验研究.浙江医学.2003;25(1):3～4.
40. 刘忠英.磷脂酶 C-γ1 在大鼠发育过程中 mRNA 表达及其前体 mRNA 剪接的初步谈讨[硕士学位论文].广州:第一军医大学,2004.
41. 马毅,孙超,马勇江等.超声波影像诊断技术在牛繁殖中的应用.黄牛杂志.2000; 26(5):51～54.
42. 秦红灵,高旺盛,李春阳.北方农牧交错带免耕对农田耕层土壤温度的影响.农业工程学报,2007;23(1):40～47.
43. 孙晓清,符卫春,张虎.超声波清洗发展状况.榆林学院学报.2006;16(2):24～25.
44. 孙永巧,刘庆友.牛基因组研究进展.中国牛业科学.2007;33(2):14～19.
45. 滕建军.阉割可提高山羊的生长速度和肉质. 闽东农业科技.1992;3:34.
46. 童伟,许曼音.大鼠垂体细胞 ACTH 分泌的调节控制. 生理学报. 1992;44(4):414～419
47. 涂智杰..基因芯片技术分析前列腺癌发展相关的基因及功能初探[硕士学位论文].厦门:厦门大学,2006.
48. 王盛宗,黄益民,顾云等.环孢素 A,广大霉素和硒制剂对大鼠外周血淋巴细胞分子和基因表达的影响.中国药学杂志.2003;38(3):180～184.
49. 王卫东,陈竹,罗泽志等.仔猪阉割时间对增重的影响.四川农业科技.1988;4:34.
50. 王育慵.超声波原理与现代应用探讨.贵州大学学报(自然科学版).2005;22(3): 287～290.
51. 王永煜,张幼怡.基因芯片数据分析与处理.生物化学与生物物理进展.2003;30(2):321～323.
52. 王志均主编.胃肠激素.北京:科学出版社.1985.
53. 吴桂琴,郑江霞,杨宁.伴性矮小型鸡 GH、GHR 和 IGF-1 基因的表达变化.遗传.2007;29(8): 989～994
54. 席细平,马重芳,王伟.超声波技术应用现状.山西化工.2007;27(1):25～29
55. 肖东,林浩然.半胱胺对草鱼下丘脑—脑垂体组织功孵育中生长激素分泌的影响.动物学报.2003;119(3):600~605.
56. 肖东,林浩然.利用脑—脑垂体—肝脏轴调控鱼类生长.水产科技情报.1999;25(3):99～100.
57. 徐清华.基因芯片技术的研究进展.中国优生与遗传杂志.2007;15(1):13～14.
58. 徐伟,赵亚华,孔洁.血管活性肽研究进展.药物生物技术.2002;9(6):364~368.
59. 许尚忠,魏伍川.肉牛高效生产实用技术.北京:中国农业出版社.2005.5.
60. 颜兴起,郭政,李霞等.利用基因表达谱挖掘差异表达功能类的稳健性.生物信息学.2006;1:5～7.
61. 杨畅,方福德.基因芯片数据分.生命科学.2004;16(2):41～48
62. 杨辉.高密度 Oligo 基因芯片筛选小鼠前脑发育过程中基因表达的研究[博士学位论文].重庆:第三军医大学,2005.
63. 杨晓辉,傅小山.黑白花小公牛阉割肥育试验报告.中国畜牧杂志.1984;8:34.
64. 姚昕,秦文,齐春梅等.花生四烯酸的生理活性及其应用.食品科技.2004;5 :57～59.
65. 袁隆平,辛业芸.希望之光—超级杂交稻.世界农业.2001;10:46.
66. 袁成凌,姚建铭,王文生等.花生四烯酸的研究概况及应用前景.中国生物制品学杂志.2000;13(1):63～64.
67. 昝林森,胡宝利.不同年龄秦川牛胴体性状与肉质性状的研究.国际肉牛生产及科研学术论文集.北京:中国农业出版社,2001.
68. 翟红林,陈兴国,胡之德.相关性分析中的可靠性.大学化学.2004;19(5):51～56.
69. 张瑾.利用 DNA 芯片对盐酸克伦特罗减少猪脂肪积累分子机制的初探[博士学位论文]. 北京:中国农业大学,2005.
70. 张雪朝. 针刺 VD 大鼠海马内新基因筛选、鉴定及其学习记忆相关基因的表达[博士学位论文]. 武汉:湖北中医学院,2002.
71. 赵庆明.微卫星遗传标记与超声波活体测定相结合对肉牛主要产肉性状的研究[硕士学位论文]. 太谷:山西农业大学,2003.
72. 周吕主编.胃肠生理学—基础与临床.北京:科学出版社.1998.
73. 朱安宁,张佳宝,程竹华.轻质土壤水分特征曲线估计的简便方法.土壤通报.2003;34(4):253～258.
74. 朱奇,周国利,郭善利等.鲁西黄牛 calpain 基因 PCR—RFLP 的初步分析.中国畜牧兽医. 2005,(32)8:33～34
75. Aaron G,Matlock,Melinda Sheffield-Moore,et al. Androgens and Skeletal Muscle.Cellscience Reviews. 2005;2(2):1742～8130.
76. Adjaye J, Herwig R, Herrmann D, et al.Cross-species hybridisation of human and bovine orthologous genes on high density cDNA microarrays. BMC Genomics. 2004;5(1):83.
77. Aho AD, McNulty AM, Coussens PM.Enhanced expression of interleukin-1alpha and tumor necrosis factor receptor-associated protein 1 in ileal tissues of cattle infected with Mycobacterium avium subsp. paratuberculosis. Infect Immun. 2003;71(11):6479～6486.
78. Arias P, Pini A, Sanguinetti G, et al. Ultrasound image segmentation with shape priors: application to automatic cattle rib-eye area estimation. IEEE Trans Image Process, 2007;16(6): 1637～1645.
79. Ashburner M,Ball CA,Black JA,et al.Gene ontology:tool for the unification of biology.The Gene Ontology Consortium.Nat Genet,2000;25:25～29
80. Band MR, Olmstead C, Everts RE, et al.A 3800 gene microarray for cattle functional genomics: comparison of gene expression in spleen, placenta, and brain. Anim Biotechnol. 2002;13(1):163～172.
81. Brethour J R. Estimating marbling score in live cattle from ultrasound images using pattern recognition and neural network procedures. J Anim Sci.1994;72: 1425～1432.
82. Brethour J R. Using serial ultrasound measures to generate models of marbling and backfat thicked changes in feedlot cattle. J Anim Sci, 2000;78:2055～2061.
83. Buddle BM, Wedlock DN, Denis M, et al.Identification of immune response correlates for protection against bovine tuberculosis. Vet Immunol Immunopathol. 2005;108(1-2):45～51.
84. Burton JL, Madsen SA, Yao J,et al.An immunogenomics approach to understanding periparturientimmunosuppression and mastitis susceptibility in dairy cows. Acta Vet Scand. 2001;42(3):407～424.
85. Byrne KA, Wang YH, Lehnert SA,et al.Gene expression profiling of muscle tissue in Brahman steers during nutritional restriction. J Anim Sci. 2005;83(1):1～12.
86. Casas E, Keele JW, Shackelford SD, et al.Identification of quantitative trait loci for growth and carcass composition in cattle. Anim Genet. 2004;35(1):2～6.
87. Casas E, White SN, Riley DG, et al. Assessment of single nucleotide polymorphisms in genes residing on chromosomes 14 and 29 for association with carcass composition traits in Bos indicus cattle. J Anim Sci. 2005;83(1):13～19.
88. Casas E, White SN, Wheeler TL, et al.Effects of calpastatin and micro-calpain markers in beef cattle on tenderness traits.J Anim Sci. 2006;84(3):520～525
89. Charlier C, Coppieters W, Farnir F,et al. The mh gene causing double-muscling in cattle maps to bovine Chromosome 2. Mamm Genome. 1995;6(11):788～792.
90. Chen CC, Chang T, Su HY. Characterization of porcine leptin receptor polymorphisms and their association with reproduction and production traits. Anim Biotechnol. 2004;15(1):89～102.
91. Chitko-McKown CG, Fox JM, Miller LC, et al. Gene expression profiling of bovine macrophages in response to Escherichia coli O157:H7 lipopolysaccharide. Dev Comp Immunol. 2004;28(6): 635～645.
92. Corcoran D, Fair T, Park S, Rizos Det al.Suppressed expression of genes involved in transcription and translation in in vitro compared with in vivo cultured bovine embryos. Reproduction. 2006;131(4):651～660.
93. Coussens PM, Colvin CJ, Rosa GJ, et al.Evidence for a novel gene expression program in peripheral blood mononuclear cells from Mycobacterium avium subsp. paratuberculosis-infected cattle. Infect Immun. 2003;71(11):6487～6498
94. Coussens PM, Colvin CJ, Wiersma K, et al.Gene expression profiling of peripheral blood mononuclear cells from cattle infected with Mycobacterium paratuberculosis. Infect Immun. 2002;70(10):5494～5502.
95. Curi RA, Oliveira HN, Silveira AC, et al. Effects of polymorphic microsatellites in the regulatory region of IGF1 and GHR on growth and carcass traits in beef cattle. Anim Genet. 2005;36(1):58～62.
96. Deng M, Liu J, Pelak CN, Lancto CA, et al. MSRegulation of apoptotic pathways in bovine gamma/delta T cells. Vet Immunol Immunopathol. 2005;105(1-2):15～23.
97. Dervis A. M,Gyanendra,Cathy Holding,et al. Pell Insulin-like growth factor-binding protein 5 (Igfbp5) compromises survival, growth, muscle development, and fertility in mice. PNAS.2004;101(12):4314～4319.
98. Di Stasio L, Destefanis G, Brugiapaglia A, et al. Polymorphism of the GHR gene in cattle and relationships with meat production and quality. Anim Genet. 2005;36(2):138～140.
99. Dierkes B, Kriegesmann B, Baumgartner BG, et al.Partial genomic structure of the bovine PIT1 gene and characterization of a HinfI transition polymorphism in exon 6. Anim Genet. 1998;29(5):405.
100. Dode MA, Dufort I, Massicotte L, et al.Quantitative expression of candidate genes for developmental competence in bovine two-cell embryos. Mol Reprod Dev. 2006;73(3):288～297.
101. Donaldson L, Vuocolo T, Gray C, et al.Construction and validation of a Bovine Innate Immune Microarray. BMC Genomics. 2005;6:135.
102. Drmanac R,Labat I,Brukner I, et al. Sequencing of megabase plus DNA by hybridization: theory of the method, Genomics, 1989 ;4: 114～128
103. Editoria.To affinity…… and beyond. Nat Genet, 1996;14(3) :367~370
104. Eisen MB,Patrick OB.DNA array for analysis of gene expression.Methods in enzymology. 1999;303:179～206.
105. El-Sayed A, Hoelker M, Rings F, et al.Large-scale transcriptional analysis of bovine embryo biopsies in relation to pregnancy success after transfer to recipients. Physiol Genomics. 2006;28(1):84～96.
106. Everts RE, Band MR, Liu ZL,et al.A 7872 cDNA microarray and its use in bovine functional genomics. Vet Immunol Immunopathol. 2005;105(3-4):235～245.
107. Flisikowski K, Maj A, Zwierzchowski L, et al. Nucleotide sequence and variation of IGF2 gene exon 6 in Bos taurus and Bos indicus cattle. Anim Biotechnol. 2005;16(2):203～208.
108. Gerbens F, de Koning DJ, Harders FL,et al. The effect of adipocyte and heart fatty acid-binding protein genes on intramuscular fat and backfat content in Meishan crossbred pigs. J Anim Sci. 2000;78(3):552～559.
109. Gossen N, Fietze S, Mosenfechtel S, et al. Relationship between body condition (back fat thickness and body condition scoring) and fertility in dairy cows. Dtsch Tierarztl Wochenschr.2006;; 113(5):171～172, 174～177.
110. Grobet L, Martin LJ, Poncelet D, et al.A deletion in the bovine myostatin gene causes the double-muscled phenotype in cattle. Nat Genet. 1997;17(1):71～74.
111. Grosz MD. Genome-wide scans for QTL affecting carcass traits in Hereford x composite double backcross populations. Journal Animal Science. 2002 ;80(9):2316～2324.
112. Hamlin K E, Green R D, Cundiff L V, et al. Real-time ultrasonic measurement of fat thickness and longissimus muscle area: II. Relationship between real-time ultrasound measures and carcassretail yield. J Anim Sci, 1995;73(6):1725～1734.
113. Hansen C, Fu A, Meng Y, et al.Gene expression profiling of the bovine gastrointestinal tract. Genome. 2004;47(4):639～649
114. Hashizume K, Ishiwata H, Kizaki K,et al.Implantation and placental development in somatic cell clone recipient cows. Cloning Stem Cells. 2002;4(3):197～209.
115. Heiman ML, Yanyun Chen, Laro JF. Leptin participates in the regulation of glucorticoid and growth hormone axes. J.Natr.Biochem. 1998;9:553～559.
116. Heller R A, Schena M, Chaia, et al, 1997, Discovery and analysis of inflammatory disease related genes using cDNA microarray. Proc Natl Acad Sci USA, 94: 2150～2155
117. Herath CB, Ishiwata H, Shiojima S,et al.Developmental aberrations of liver gene expression in bovine fetuses derived from somatic cell nuclear transplantation. Cloning Stem Cells. 2006;8(2):79～95.
118. Herath CB, Shiojima S, Ishiwata H, et al.Pregnancy-associated changes in genome-wide gene expression profiles in the liver of cow throughout pregnancy. Biochem Biophys Res Commun. 2004;313(3):666～680.
119. Hernández A, Karrow N, Mallard BA.Evaluation of immune responses of cattle as a means to identify high or low responders and use of a human microarray to differentiate gene expression. Genet Sel Evol. 2003;35 Suppl 1:S67～81.
120. Herring W O, Kriese L A, Bertrand J K, et al. Comparison of four real-time ultrasound systems that predict intramuscular fat in beef cattle. J Anim Sci, 1998;76(2):364～370.
121. Herring W O, Miller D C, Bertrand J K, et al. Evaluation of machine, technician, and interpreter effects on ultrasonic measures of backfat and longissimus muscle area in beef cattle. J Anim Sci, 1994;72:2216～2226.
122. Hill EW, O'Gorman GM, Agaba M, et al.Understanding bovine trypanosomiasis and trypanotolerance: the promise of functional genomics. Vet Immunol Immunopathol. 2005;105(3-4):247～258.
123. Honnor RC,DhillinGS,LondosC,et al.cAMP-dependent protein kinase and lopolysis in rat adipocytes.Ⅱ Definition of steady-state relationship with lipolytic and antilipolytic modulators.J Biol Chem.1995;280:1364～1367.
124. Hoyong Chung.Study on the effects of the calpain family of genes on meat tenderness,carcass traits,and growth traints in beef cattle[doctor thesis]. Ohio :The Ohio State University, 2001.
125. Hwang D,Schmott WA,Stephanopoulos G,et al.Determination of minimum sample size and discriminatory expression patterns in microarray data.Bioinformatics.2002;18(9)1184～1193.
126. Ishiwata H, Katsuma S, Kizaki K,et al.Characterization of gene expression profiles in earlybovine pregnancy using a custom cDNA microarray. Mol Reprod Dev. 2003;65(1):9～18.
127. J Pareek R, Wellnitz O, Van Dorp R, et al. Immunorelevant gene expression in LPS-challenged bovine mammary epithelial cells.Appl Genet. 2005;46(2):171～177.
128. Jensen K, Talbot R, Paxton E, et al.Development and validation of a bovine macrophage specific cDNA microarray. BMC Genomics. 2006 1;7:224.
129. Jones KL, King SS, Iqbal MJ.Endophyte-infected tall fescue diet alters gene expression in heifer luteal tissue as revealed by interspecies microarray analysis. Mol Reprod Dev. 2004;67(2):154～161.
130. Kamiński S, Ahman A, Ru?? A, et al.MilkProtChip--a microarray of SNPs in candidate genes associated with milk protein biosynthesis--development and validation. J Appl Genet. 2005;46(1):45～58.
131. Kamiński S, Brym P, Ru?? A, et al.Associations between milk performance traits in Holstein cows and 16 candidate SNPs identified by arrayed primer extension (APEX) microarray. Anim Biotechnol. 2006;17(1):1～11.
132. Kerr MK,Churchill GA.Experimental design for gene expression mocroarrays.Biostatistics. 2001;2:183～201.
133. Kim JJ, Farnir F, Savell J, et al.Detection of quantitative trait loci for growth and beef carcass fatness traits in a cross between Bos taurus (Angus) and Bos indicus (Brahman) cattle. Journal Animal Science. 2003;81(8):1933～1942.
134. Kuemmerle JF, Zhou H. Insulin-like growth factor-binding protein-5 (IGFBP-5) stimulates growth and IGF-I secretion in human intestinal smooth muscle by Ras-dependent activation of p38 MAP kinase and Erk1/2 pathways. J Biol Chem. 2002;277(23):20563～20571.
135. Lee ML,Kuo FC,Whitmore GA,et al.Importance of replication in microarray gene expression studies:statistical methods and evidence from repetitive cDNA hybridization.Proc Natl Acad Sci USA.2000;97(18):9834～9839.
136. Lejen T., Dumitrescu peng T., ROSéS. D,et al. The Role of Different Scinderin Domains in the Control of F-Actin Cytoskeleton during Exocytosis.Annals of the New York Academy of Sciences 2002;971:248-250
137. Li C, Basarab J, Snelling WM, et al. Identification and fine mapping of quantitative trait loci for backfat on bovine chromosomes 2, 5, 6, 19, 21, and 23 in a commercial line of Bos taurus. Journal Animal Science. 2004;82(4):967～972.
138. Lusk J L. Association of single nucleotide polymorphisms in the leptin gene with body weight and backfat growth curve parameters for beef cattle. J Anim Sci, 2007;85(8):1865～1872.
139. Marc Pelletier, José-María Trifarob, M. Eloísa Carbajala, et al. Calcium-Dependent ActinFilament-Severing Protein Scinderin Levels and Localization in Bovine Testis, Epididymis, and Spermatozoa .Biology of Reproduction. 1999;60:1128～1136.
140. Madsen SA, Chang LC, Hickey MC,et al.Microarray analysis of gene expression in blood neutrophils of parturient cows. Physiol Genomics. 2004;16(2):212～221.
141. Mariani TJ,Budhraja V,Mecham BH,et al.A variable fold change threshold determines significance for expression mocroarrays.FASEB-J.2003;17(2):321～323.
142. Marshall A,Hodgson J.DNA chip:An array of possibilities.Nature Biotechol.1998;16(1):27～31
143. Miller M F,Huffman K L,Gilbert S Y,et al.Retail consumer acceptance of beef tenderized with calcium chloride.JAnim Sci.1999;73:2308～2314.
144. Mizoshita K, Takano A, Watanabe T,et al.Identification of a 1.1-Mb region for a carcass weight QTL on bovine Chromosome 14. Mamm Genome. 2005;16(7):532～537.
145. Nino-Soto MI, Nuber UA, Basrur PK, et al.Differences in the pattern of X-linked gene expression between fetal bovine muscle and fibroblast cultures derived from the same muscle biopsies. Cytogenet Genome Res. 2005;111(1):57～64.
146. Ohno S, Im HJ, Knudson CB,et al.oligosaccharide-induced activation of transcription factors in bovine articular chondrocytes. Arthritis Rheum. 2005;52(3):800～809.
147. Page BT, Casas E, Heaton MP, et al.Evaluation of single-nucleotide polymorphisms in CAPN1 for association with meat tenderness in cattle. J Anim Sci. 2002;80(12):3077～3085.
148. Page BT, Casas E, Quaas RL, et al..Association of markers in the bovine CAPN1 gene with meat tenderness in large crossbred populations that sample influential industry sires. J Anim Sci. 2004;82(12):3474～3481.
149. Park YH, Joo YS, Park JY, et al.Characterization of lymphocyte subpopulations and major histocompatibility complex haplotypes of mastitis-resistant and susceptible cows. J Vet Sci. 2004;5(1):29～39.
150. Patel D, Danelishvili L, Yamazaki Y, et al.The ability of Mycobacterium avium subsp. paratuberculosis to enter bovine epithelial cells is influenced by preexposure to a hyperosmolar environment and intracellular passage in bovine mammary epithelial cells. Infect Immun. 2006 ;74(5):2849～2855
151. Pavlidis P,Li Q,Noble WS.The effect of replication on gene expression microarray experiments.Bioinformatics.2003;19(13):1620～1627.
152. Pfister-Genskow M, Myers C, Childs LA,et al.Identification of differentially expressed genes in individual bovine preimplantation embryos produced by nuclear transfer: improper reprogramming of genes required for development. Biol Reprod. 2005;72(3):546～55.
153. Rainard P, Riollet C.Innate immunity of the bovine mammary gland. Vet Res. 2006 ;37(3):369～400.
154. Renaville R, Gengler N, Vrech E, et al.Pit-1 gene polymorphism, milk yield, and conformation traits for Italian Holstein-Friesian bulls. J Dairy Sci. 1997;80(12):3431～3438
155. Reverter A, Byrne KA, Brucet HL,et al.A mixture model-based cluster analysis of DNA microarray gene expression data on Brahman and Brahman composite steers fed high-, medium-, and low-quality diets. J Anim Sci. 2003;81(8):1900～1910.
156. Reverter A, Hudson NJ, Wang Y, et al.A gene coexpression network for bovine skeletal muscle inferred from microarray data. Physiol Genomics. 2006;28(1):76～83.
157. Reverter A, Tier B, Johnston D J, et al. Assessing the efficiency of multiplicative mixed model equations to account for heterogeneous variance across herds in carcass scan traits from beef cattle. J Anim Sci.1997;75:1477～1485.
158. Reverter A, Wang YH, Byrne KA, et al.Joint analysis of multiple cDNA microarray studies via multivariate mixed models applied to genetic improvement of beef cattle. J Anim Sci. 2004;82(12):3430～3439.
159. Rexroad CE, Bennett GL, Stone RT, et al.Comparative mapping of BTA15 and HSA11 including a region containing a QTL for meat tenderness. Mamm Genome. 2001;12(7):561～565.
160. Ripoli MV, Corva P, Giovambattista G.Analysis of a polymorphism in the DGAT1 gene in 14 cattle in 14 cattle breeds through PCR-SSCP methods. Res Vet Sci. 2006;80(3):287～290.
161. Schenkel FS, Miller SP, Jiang Z, et al. Association of a single nucleotide polymorphism in the calpastatin gene with carcass and meat quality traits of beef cattle. J Anim Sci. 2006;84(2):291～299.
162. Schenkel FS, Miller SP, Ye X, et al. Association of single nucleotide polymorphisms in the leptin gene with carcass and meat quality traits of beef cattle. J Anim Sci. 2005;83(9):2009～2020.
163. Schmutz SM, Moker JS, Berryere TG.In situ hybridization of five loci to cattle chromosome 1. Cytogenet Cell Genet. 1998;81(1):51～53
164. Schr?der1 U J, Staufenbiel R. Invited review: methods to determine body fat reserves in the dairy cow with special regard to ultrasonographic measurement of backfat Thickness. J Dairy Sci, 2006; 89(1):1～14.
165. Simmon R,Dobbin K.Experimental design of DNA microarray experiments.Bio Technique. 2003;34:S16.
166. Sirard MA, Dufort I, Vallée M,et al.Potential and limitations of bovine-specific arrays for the analysis of mRNA levels in early development: preliminary analysis using a bovine embryonic array. Reprod Fertil Dev. 2005;17(1-2):47～57
167. Smith SL, Everts RE, Tian XC, et al.Global gene expression profiles reveal significant nuclearreprogramming by the blastocyst stage after cloning. Proc Natl Acad Sci U S A. 2005;102(49):17582～17587.
168. Smith TP, Lopez-Corrales NL, Kappes SM, et al.Myostatin maps to the interval containing the bovine mh locus. Mamm Genome. 1997,8(10):742～744.
169. Somers J, Smith C, Donnison M,et al.Gene expression profiling of individual bovine nuclear transfer blastocysts. Reproduction. 2006;131(6):1073～1084.
170. Stone RT, Casas E, Smith TP, et al. Identification of genetic markers for fat deposition and meat tenderness on bovine chromosome 5: development of a low-density single nucleotide polymorphism map. J Anim Sci. 2005;83(10):2280～2288.
171. Suchyta SP, Sipkovsky S, Halgren RG,et al.Bovine mammary gene expression profiling using a cDNA microarray enhanced for mammary-specific transcripts. Physiol Genomics. 2003;16(1):8～18.
172. Suchyta SP, Sipkovsky S, Kruska R,et al.Development and testing of a high-density cDNA microarray resource for cattle. Physiol Genomics. 2003;15(2):158～64.
173. Tan SH, Reverter A, Wang Y, et al.Gene expression profiling of bovine in vitro adipogenesis using a cDNA microarray. Funct Integr Genomics. 2006;6(3):235～249.
174. Tao W, Mallard B, Karrow N, et al.Construction and application of a bovine immune-endocrine cDNA microarray. Vet Immunol Immunopathol. 2004;101(1-2):1～17.
175. Tilstone.DNA mocroarray:vital statistics.Nature.2003;424(6949):610～612.
176. Ushizawa K, Herath CB, Kaneyama K, et al.cDNA microarray analysis of bovine embryo gene expression profiles during the pre-implantation period. Reprod Biol Endocrinol. 2004;2:77.
177. Ushizawa K, Takahashi T, Kaneyama K, et al.Gene expression profiles of bovine trophoblastic cell line (BT-1) analyzed by a custom cDNA microarray. J Reprod Dev. 2005;51(2):211～220.
178. Wang YH, Byrne KA, Reverter A, et al.Transcriptional profiling of skeletal muscle tissue from two breeds of cattle. Mamm Genome. 2005;16(3):201～210.
179. Weiss DJ, Evanson OA, Deng M, et al.Sequential patterns of gene expression by bovine monocyte-derived macrophages associated with ingestion of mycobacterial organisms. Microb Pathog. 2004 Oct;37(4):215～224
180. Wu XL, Macneil MD, De S, et al. Evaluation of candidate gene effects for beef backfat via Bayesian model selection.Genetica. 2005;125(1):103～113.
181. Yao J, Burton JL, Saama P, et al.Generation of EST and cDNA microarray resources for the study of bovine immunobiology. Acta Vet Scand. 2001;42(3):391～405.
182. Yao J, Ren X, Ireland JJ, et al.Generation of a bovine oocyte cDNA library and microarray: resources for identification of genes important for follicular development and earlyembryogenesis. Physiol Genomics. 2004;19(1):84～92.
183. Yeung KY, Ruzzo WL. Principal component analysis for clustering gene expression data.Bioinformatics.2001;17:763.
184. Yousef G,Amaar,Garrett R,et al .Insulin-like Growth Factor-binding Protein 5 (IGFBP-5) Interacts with a Four and a Half LIM Protein 2 (FHL2, ).2002;277( 14): 12053～12060.
185. Yu SL, Kim JE, Chung HJ, et al. Molecular cloning and characterization of bovine PRKAG3 gene: structure, expression and single nucleotide polymorphism detection. J Anim Breed Genet. 2005;122(5):294～301.
186. Zhao Q, Davis ME, Hines HC.Associations of polymorphisms in the Pit-1 gene with growth and carcass traits in Angus beef cattle. J Anim Sci. 2004;82(8):2229～2233.
2. 陈宝生,万学东,夏炎枝等.花生四烯酸改善饱和脂肪酸诱导肝细胞胰岛素抵抗的作用机制.山东医药.2007;47(28):1～3
3. 陈思忠.超声波清洗技术与发展.洗净技术.2004;2(2):7～12.
4. 程志平主编.内分泌生理学.北京: 人民卫生出版社.1984.
5. 崔强,蔡荣,钱程等.一种新的疾病治疗候选基因: SOCS-1.生命科学.2006;18 (3):290～294
6. 邓桂馨.肉牛 CAST 基因和 HFABPL 基因多态性及其与肉品质性状关系的研究 [硕士学位论文]. 北京:中国农业科学院,2003.
7. 丁俊杰,焦正,李中东等.Bootstrap 法验证有限抽样法多元回归模型.中国卫生统计.2004;21 (5 ):289～292
8. 丁世飞,程述汉, 苏本堂.多元模糊回归预测模型及其应用.模糊系统与数学.2000;4:94～98.
9. 杜新宇. 架子牛育肥的技术问题.饲料与畜牧科学.2007;,1:16-18.
10. 冯仁田,张玉民.抑素的研究进展,中国药学杂志.199;28(10):583~585.
11. 傅伟龙,江青艳,刘平祥.神经内分泌生长轴的研究概况及对猪的生长调控研究.中国科学基金.2003;3:151~155.
12. 高腾云,王艳玲,韩正康等.半胱胺对肉牛增重、采食量和血液激素水平的影响.华中农业大学学报.2001;20(3):259~261.
13. 高雪.牛生长发育性状候选基因的分子标记研究[博士学位论文].杨凌:西北农林科技大学,2004.
14. 葛飞.超声波技术的应用现状及发展前景.郑州牧业工程高等专科学校学报.1999;19(1):58～59.
15. 郭芬,李月琴,周天鸿.鞘脂激活蛋白原的研究进展. 中国病理生理杂志 .2006;12: 2485～2488.
16. 郭万库,师守堃,吴常信.肉用动物双肌性状的研究现状. 国外畜牧科技.1999;26,(3):34～38.
17. 郭玮.用基因芯片研究 CLB 处理的猪肪肪组织基因的差异表达[博士学位论文].北京:中国农业大学,2004.
18. 郭燕青.牛 LPL、HSL 基因克隆、SNPs 筛查及其与肉质性状的关联分析. [硕士学位论文].北京:中国农业科学院,2007.
19. 哈珀,罗德韦尔,梅斯著.生理化学评论.北京:科学出版社.1985.
20. 韩正康 , 林玲 . 生长抑素耗竭剂 - 半胱胺促进肉用仔鸡生长的研究 . 畜牧兽医学报 . 1992;23:314～318.
21. 胡宝利.不同年龄秦川牛胴体性状与肉质性状的研究[硕士学位论文].杨凌:西北农林科技大学,2001.
22. 胡晓湘.猪肥胖基因(ob)及其受体(OBR)基因的分子遗传学研究[硕士学位论文]. 北京:中国农业大学,1998.
23. 胡延佳,翦新春.基因芯片数据分析过程:从原始数据到生物意义.生物技术通讯.2007; 18(2) :333～335
24. 黄明,刘冠勇,罗欣.影响肉嫩度因素的探讨.肉类工业.2000;233(11):26～28.
25. 荆志伟,王忠.基因芯片数据分析方法研究进展.生物技术通讯.2007;18(1):144～148.
26. 雷帆,刑东明,孙虹等.肥胖相关生物因子的研究.中国药学杂志.2002;37(1):5～8.
27. 黎敏义,郭文军,刘颖等.调控畜禽繁殖的激素免疫技术.动物医学进展,2005;26 (11) :1～4.
28. 李常绿.应用 DNA 微阵列技术对洛克沙砷处理肉鸡后肝脏和胸肌组织基因表达谱的研究[博士学位论文].北京:中国农业大学,2004.
29. 李加琪,陈赞谋,刘德武等.IGF1 基因对长白×蓝塘猪资源群生产性能的遗传效应分析.遗传学报. 2003;9: 835～839.
30. 李君,赵成义,朱宏等.融雪后梭梭林地土壤水的多尺度空间异质性.中国科学(D).2006;36 (增刊 Ⅱ ): 45～50.
31. 李伟,张书慧, 张倩等.近红外光谱法快速测定土壤碱解氮、速效磷和速效钾含量.农业工程学报.2007;23(1):55～59.
32. 李武峰,许尚忠,曹红鹤等.3 个杂交牛种H -FAB P 基因第二内含子的遗传变异与肉品质性状的相关分析.畜牧兽医学报. 2004;35 (3):252～255.
33. 李雅莉.超声波清洗的原理和实际应用.清洗世界.2006;22(7):31～35.
34. 李瑶主编.基因芯片数据分析与处理.北京:化学工业出版社现代生物技术与医药科技出版中心.2006,7.
35. 林金杏,阎萍,曾宪成.现代牛分子育种及其发展趋势.中国畜牧杂志.2007;(增刊):271~275.
36. 林玲,韩正康,生长抑素耗竭剂-半胱胺促进大鼠、幼兔生长的研究.中国应用生理学杂志.1991;7(4):314~318.
37. 刘波.秦川牛及其杂交后代生长发育性状的分子标记研究[硕士学位论文].杨凌:西北农林科技大学,2004.
38. 刘敬顺,包杰,张豪.猪的活体超声波评估技术与方法.当代畜禽养殖业.2003;10:2～7.
39. 刘伟国,周景义,杨小峰等.天然细胞生长调控因子对原代培养神经细胞生长影响的实验研究.浙江医学.2003;25(1):3～4.
40. 刘忠英.磷脂酶 C-γ1 在大鼠发育过程中 mRNA 表达及其前体 mRNA 剪接的初步谈讨[硕士学位论文].广州:第一军医大学,2004.
41. 马毅,孙超,马勇江等.超声波影像诊断技术在牛繁殖中的应用.黄牛杂志.2000; 26(5):51～54.
42. 秦红灵,高旺盛,李春阳.北方农牧交错带免耕对农田耕层土壤温度的影响.农业工程学报,2007;23(1):40～47.
43. 孙晓清,符卫春,张虎.超声波清洗发展状况.榆林学院学报.2006;16(2):24～25.
44. 孙永巧,刘庆友.牛基因组研究进展.中国牛业科学.2007;33(2):14～19.
45. 滕建军.阉割可提高山羊的生长速度和肉质. 闽东农业科技.1992;3:34.
46. 童伟,许曼音.大鼠垂体细胞 ACTH 分泌的调节控制. 生理学报. 1992;44(4):414～419
47. 涂智杰..基因芯片技术分析前列腺癌发展相关的基因及功能初探[硕士学位论文].厦门:厦门大学,2006.
48. 王盛宗,黄益民,顾云等.环孢素 A,广大霉素和硒制剂对大鼠外周血淋巴细胞分子和基因表达的影响.中国药学杂志.2003;38(3):180～184.
49. 王卫东,陈竹,罗泽志等.仔猪阉割时间对增重的影响.四川农业科技.1988;4:34.
50. 王育慵.超声波原理与现代应用探讨.贵州大学学报(自然科学版).2005;22(3): 287～290.
51. 王永煜,张幼怡.基因芯片数据分析与处理.生物化学与生物物理进展.2003;30(2):321～323.
52. 王志均主编.胃肠激素.北京:科学出版社.1985.
53. 吴桂琴,郑江霞,杨宁.伴性矮小型鸡 GH、GHR 和 IGF-1 基因的表达变化.遗传.2007;29(8): 989～994
54. 席细平,马重芳,王伟.超声波技术应用现状.山西化工.2007;27(1):25～29
55. 肖东,林浩然.半胱胺对草鱼下丘脑—脑垂体组织功孵育中生长激素分泌的影响.动物学报.2003;119(3):600~605.
56. 肖东,林浩然.利用脑—脑垂体—肝脏轴调控鱼类生长.水产科技情报.1999;25(3):99～100.
57. 徐清华.基因芯片技术的研究进展.中国优生与遗传杂志.2007;15(1):13～14.
58. 徐伟,赵亚华,孔洁.血管活性肽研究进展.药物生物技术.2002;9(6):364~368.
59. 许尚忠,魏伍川.肉牛高效生产实用技术.北京:中国农业出版社.2005.5.
60. 颜兴起,郭政,李霞等.利用基因表达谱挖掘差异表达功能类的稳健性.生物信息学.2006;1:5～7.
61. 杨畅,方福德.基因芯片数据分.生命科学.2004;16(2):41～48
62. 杨辉.高密度 Oligo 基因芯片筛选小鼠前脑发育过程中基因表达的研究[博士学位论文].重庆:第三军医大学,2005.
63. 杨晓辉,傅小山.黑白花小公牛阉割肥育试验报告.中国畜牧杂志.1984;8:34.
64. 姚昕,秦文,齐春梅等.花生四烯酸的生理活性及其应用.食品科技.2004;5 :57～59.
65. 袁隆平,辛业芸.希望之光—超级杂交稻.世界农业.2001;10:46.
66. 袁成凌,姚建铭,王文生等.花生四烯酸的研究概况及应用前景.中国生物制品学杂志.2000;13(1):63～64.
67. 昝林森,胡宝利.不同年龄秦川牛胴体性状与肉质性状的研究.国际肉牛生产及科研学术论文集.北京:中国农业出版社,2001.
68. 翟红林,陈兴国,胡之德.相关性分析中的可靠性.大学化学.2004;19(5):51～56.
69. 张瑾.利用 DNA 芯片对盐酸克伦特罗减少猪脂肪积累分子机制的初探[博士学位论文]. 北京:中国农业大学,2005.
70. 张雪朝. 针刺 VD 大鼠海马内新基因筛选、鉴定及其学习记忆相关基因的表达[博士学位论文]. 武汉:湖北中医学院,2002.
71. 赵庆明.微卫星遗传标记与超声波活体测定相结合对肉牛主要产肉性状的研究[硕士学位论文]. 太谷:山西农业大学,2003.
72. 周吕主编.胃肠生理学—基础与临床.北京:科学出版社.1998.
73. 朱安宁,张佳宝,程竹华.轻质土壤水分特征曲线估计的简便方法.土壤通报.2003;34(4):253～258.
74. 朱奇,周国利,郭善利等.鲁西黄牛 calpain 基因 PCR—RFLP 的初步分析.中国畜牧兽医. 2005,(32)8:33～34
75. Aaron G,Matlock,Melinda Sheffield-Moore,et al. Androgens and Skeletal Muscle.Cellscience Reviews. 2005;2(2):1742～8130.
76. Adjaye J, Herwig R, Herrmann D, et al.Cross-species hybridisation of human and bovine orthologous genes on high density cDNA microarrays. BMC Genomics. 2004;5(1):83.
77. Aho AD, McNulty AM, Coussens PM.Enhanced expression of interleukin-1alpha and tumor necrosis factor receptor-associated protein 1 in ileal tissues of cattle infected with Mycobacterium avium subsp. paratuberculosis. Infect Immun. 2003;71(11):6479～6486.
78. Arias P, Pini A, Sanguinetti G, et al. Ultrasound image segmentation with shape priors: application to automatic cattle rib-eye area estimation. IEEE Trans Image Process, 2007;16(6): 1637～1645.
79. Ashburner M,Ball CA,Black JA,et al.Gene ontology:tool for the unification of biology.The Gene Ontology Consortium.Nat Genet,2000;25:25～29
80. Band MR, Olmstead C, Everts RE, et al.A 3800 gene microarray for cattle functional genomics: comparison of gene expression in spleen, placenta, and brain. Anim Biotechnol. 2002;13(1):163～172.
81. Brethour J R. Estimating marbling score in live cattle from ultrasound images using pattern recognition and neural network procedures. J Anim Sci.1994;72: 1425～1432.
82. Brethour J R. Using serial ultrasound measures to generate models of marbling and backfat thicked changes in feedlot cattle. J Anim Sci, 2000;78:2055～2061.
83. Buddle BM, Wedlock DN, Denis M, et al.Identification of immune response correlates for protection against bovine tuberculosis. Vet Immunol Immunopathol. 2005;108(1-2):45～51.
84. Burton JL, Madsen SA, Yao J,et al.An immunogenomics approach to understanding periparturientimmunosuppression and mastitis susceptibility in dairy cows. Acta Vet Scand. 2001;42(3):407～424.
85. Byrne KA, Wang YH, Lehnert SA,et al.Gene expression profiling of muscle tissue in Brahman steers during nutritional restriction. J Anim Sci. 2005;83(1):1～12.
86. Casas E, Keele JW, Shackelford SD, et al.Identification of quantitative trait loci for growth and carcass composition in cattle. Anim Genet. 2004;35(1):2～6.
87. Casas E, White SN, Riley DG, et al. Assessment of single nucleotide polymorphisms in genes residing on chromosomes 14 and 29 for association with carcass composition traits in Bos indicus cattle. J Anim Sci. 2005;83(1):13～19.
88. Casas E, White SN, Wheeler TL, et al.Effects of calpastatin and micro-calpain markers in beef cattle on tenderness traits.J Anim Sci. 2006;84(3):520～525
89. Charlier C, Coppieters W, Farnir F,et al. The mh gene causing double-muscling in cattle maps to bovine Chromosome 2. Mamm Genome. 1995;6(11):788～792.
90. Chen CC, Chang T, Su HY. Characterization of porcine leptin receptor polymorphisms and their association with reproduction and production traits. Anim Biotechnol. 2004;15(1):89～102.
91. Chitko-McKown CG, Fox JM, Miller LC, et al. Gene expression profiling of bovine macrophages in response to Escherichia coli O157:H7 lipopolysaccharide. Dev Comp Immunol. 2004;28(6): 635～645.
92. Corcoran D, Fair T, Park S, Rizos Det al.Suppressed expression of genes involved in transcription and translation in in vitro compared with in vivo cultured bovine embryos. Reproduction. 2006;131(4):651～660.
93. Coussens PM, Colvin CJ, Rosa GJ, et al.Evidence for a novel gene expression program in peripheral blood mononuclear cells from Mycobacterium avium subsp. paratuberculosis-infected cattle. Infect Immun. 2003;71(11):6487～6498
94. Coussens PM, Colvin CJ, Wiersma K, et al.Gene expression profiling of peripheral blood mononuclear cells from cattle infected with Mycobacterium paratuberculosis. Infect Immun. 2002;70(10):5494～5502.
95. Curi RA, Oliveira HN, Silveira AC, et al. Effects of polymorphic microsatellites in the regulatory region of IGF1 and GHR on growth and carcass traits in beef cattle. Anim Genet. 2005;36(1):58～62.
96. Deng M, Liu J, Pelak CN, Lancto CA, et al. MSRegulation of apoptotic pathways in bovine gamma/delta T cells. Vet Immunol Immunopathol. 2005;105(1-2):15～23.
97. Dervis A. M,Gyanendra,Cathy Holding,et al. Pell Insulin-like growth factor-binding protein 5 (Igfbp5) compromises survival, growth, muscle development, and fertility in mice. PNAS.2004;101(12):4314～4319.
98. Di Stasio L, Destefanis G, Brugiapaglia A, et al. Polymorphism of the GHR gene in cattle and relationships with meat production and quality. Anim Genet. 2005;36(2):138～140.
99. Dierkes B, Kriegesmann B, Baumgartner BG, et al.Partial genomic structure of the bovine PIT1 gene and characterization of a HinfI transition polymorphism in exon 6. Anim Genet. 1998;29(5):405.
100. Dode MA, Dufort I, Massicotte L, et al.Quantitative expression of candidate genes for developmental competence in bovine two-cell embryos. Mol Reprod Dev. 2006;73(3):288～297.
101. Donaldson L, Vuocolo T, Gray C, et al.Construction and validation of a Bovine Innate Immune Microarray. BMC Genomics. 2005;6:135.
102. Drmanac R,Labat I,Brukner I, et al. Sequencing of megabase plus DNA by hybridization: theory of the method, Genomics, 1989 ;4: 114～128
103. Editoria.To affinity…… and beyond. Nat Genet, 1996;14(3) :367~370
104. Eisen MB,Patrick OB.DNA array for analysis of gene expression.Methods in enzymology. 1999;303:179～206.
105. El-Sayed A, Hoelker M, Rings F, et al.Large-scale transcriptional analysis of bovine embryo biopsies in relation to pregnancy success after transfer to recipients. Physiol Genomics. 2006;28(1):84～96.
106. Everts RE, Band MR, Liu ZL,et al.A 7872 cDNA microarray and its use in bovine functional genomics. Vet Immunol Immunopathol. 2005;105(3-4):235～245.
107. Flisikowski K, Maj A, Zwierzchowski L, et al. Nucleotide sequence and variation of IGF2 gene exon 6 in Bos taurus and Bos indicus cattle. Anim Biotechnol. 2005;16(2):203～208.
108. Gerbens F, de Koning DJ, Harders FL,et al. The effect of adipocyte and heart fatty acid-binding protein genes on intramuscular fat and backfat content in Meishan crossbred pigs. J Anim Sci. 2000;78(3):552～559.
109. Gossen N, Fietze S, Mosenfechtel S, et al. Relationship between body condition (back fat thickness and body condition scoring) and fertility in dairy cows. Dtsch Tierarztl Wochenschr.2006;; 113(5):171～172, 174～177.
110. Grobet L, Martin LJ, Poncelet D, et al.A deletion in the bovine myostatin gene causes the double-muscled phenotype in cattle. Nat Genet. 1997;17(1):71～74.
111. Grosz MD. Genome-wide scans for QTL affecting carcass traits in Hereford x composite double backcross populations. Journal Animal Science. 2002 ;80(9):2316～2324.
112. Hamlin K E, Green R D, Cundiff L V, et al. Real-time ultrasonic measurement of fat thickness and longissimus muscle area: II. Relationship between real-time ultrasound measures and carcassretail yield. J Anim Sci, 1995;73(6):1725～1734.
113. Hansen C, Fu A, Meng Y, et al.Gene expression profiling of the bovine gastrointestinal tract. Genome. 2004;47(4):639～649
114. Hashizume K, Ishiwata H, Kizaki K,et al.Implantation and placental development in somatic cell clone recipient cows. Cloning Stem Cells. 2002;4(3):197～209.
115. Heiman ML, Yanyun Chen, Laro JF. Leptin participates in the regulation of glucorticoid and growth hormone axes. J.Natr.Biochem. 1998;9:553～559.
116. Heller R A, Schena M, Chaia, et al, 1997, Discovery and analysis of inflammatory disease related genes using cDNA microarray. Proc Natl Acad Sci USA, 94: 2150～2155
117. Herath CB, Ishiwata H, Shiojima S,et al.Developmental aberrations of liver gene expression in bovine fetuses derived from somatic cell nuclear transplantation. Cloning Stem Cells. 2006;8(2):79～95.
118. Herath CB, Shiojima S, Ishiwata H, et al.Pregnancy-associated changes in genome-wide gene expression profiles in the liver of cow throughout pregnancy. Biochem Biophys Res Commun. 2004;313(3):666～680.
119. Hernández A, Karrow N, Mallard BA.Evaluation of immune responses of cattle as a means to identify high or low responders and use of a human microarray to differentiate gene expression. Genet Sel Evol. 2003;35 Suppl 1:S67～81.
120. Herring W O, Kriese L A, Bertrand J K, et al. Comparison of four real-time ultrasound systems that predict intramuscular fat in beef cattle. J Anim Sci, 1998;76(2):364～370.
121. Herring W O, Miller D C, Bertrand J K, et al. Evaluation of machine, technician, and interpreter effects on ultrasonic measures of backfat and longissimus muscle area in beef cattle. J Anim Sci, 1994;72:2216～2226.
122. Hill EW, O'Gorman GM, Agaba M, et al.Understanding bovine trypanosomiasis and trypanotolerance: the promise of functional genomics. Vet Immunol Immunopathol. 2005;105(3-4):247～258.
123. Honnor RC,DhillinGS,LondosC,et al.cAMP-dependent protein kinase and lopolysis in rat adipocytes.Ⅱ Definition of steady-state relationship with lipolytic and antilipolytic modulators.J Biol Chem.1995;280:1364～1367.
124. Hoyong Chung.Study on the effects of the calpain family of genes on meat tenderness,carcass traits,and growth traints in beef cattle[doctor thesis]. Ohio :The Ohio State University, 2001.
125. Hwang D,Schmott WA,Stephanopoulos G,et al.Determination of minimum sample size and discriminatory expression patterns in microarray data.Bioinformatics.2002;18(9)1184～1193.
126. Ishiwata H, Katsuma S, Kizaki K,et al.Characterization of gene expression profiles in earlybovine pregnancy using a custom cDNA microarray. Mol Reprod Dev. 2003;65(1):9～18.
127. J Pareek R, Wellnitz O, Van Dorp R, et al. Immunorelevant gene expression in LPS-challenged bovine mammary epithelial cells.Appl Genet. 2005;46(2):171～177.
128. Jensen K, Talbot R, Paxton E, et al.Development and validation of a bovine macrophage specific cDNA microarray. BMC Genomics. 2006 1;7:224.
129. Jones KL, King SS, Iqbal MJ.Endophyte-infected tall fescue diet alters gene expression in heifer luteal tissue as revealed by interspecies microarray analysis. Mol Reprod Dev. 2004;67(2):154～161.
130. Kamiński S, Ahman A, Ru?? A, et al.MilkProtChip--a microarray of SNPs in candidate genes associated with milk protein biosynthesis--development and validation. J Appl Genet. 2005;46(1):45～58.
131. Kamiński S, Brym P, Ru?? A, et al.Associations between milk performance traits in Holstein cows and 16 candidate SNPs identified by arrayed primer extension (APEX) microarray. Anim Biotechnol. 2006;17(1):1～11.
132. Kerr MK,Churchill GA.Experimental design for gene expression mocroarrays.Biostatistics. 2001;2:183～201.
133. Kim JJ, Farnir F, Savell J, et al.Detection of quantitative trait loci for growth and beef carcass fatness traits in a cross between Bos taurus (Angus) and Bos indicus (Brahman) cattle. Journal Animal Science. 2003;81(8):1933～1942.
134. Kuemmerle JF, Zhou H. Insulin-like growth factor-binding protein-5 (IGFBP-5) stimulates growth and IGF-I secretion in human intestinal smooth muscle by Ras-dependent activation of p38 MAP kinase and Erk1/2 pathways. J Biol Chem. 2002;277(23):20563～20571.
135. Lee ML,Kuo FC,Whitmore GA,et al.Importance of replication in microarray gene expression studies:statistical methods and evidence from repetitive cDNA hybridization.Proc Natl Acad Sci USA.2000;97(18):9834～9839.
136. Lejen T., Dumitrescu peng T., ROSéS. D,et al. The Role of Different Scinderin Domains in the Control of F-Actin Cytoskeleton during Exocytosis.Annals of the New York Academy of Sciences 2002;971:248-250
137. Li C, Basarab J, Snelling WM, et al. Identification and fine mapping of quantitative trait loci for backfat on bovine chromosomes 2, 5, 6, 19, 21, and 23 in a commercial line of Bos taurus. Journal Animal Science. 2004;82(4):967～972.
138. Lusk J L. Association of single nucleotide polymorphisms in the leptin gene with body weight and backfat growth curve parameters for beef cattle. J Anim Sci, 2007;85(8):1865～1872.
139. Marc Pelletier, José-María Trifarob, M. Eloísa Carbajala, et al. Calcium-Dependent ActinFilament-Severing Protein Scinderin Levels and Localization in Bovine Testis, Epididymis, and Spermatozoa .Biology of Reproduction. 1999;60:1128～1136.
140. Madsen SA, Chang LC, Hickey MC,et al.Microarray analysis of gene expression in blood neutrophils of parturient cows. Physiol Genomics. 2004;16(2):212～221.
141. Mariani TJ,Budhraja V,Mecham BH,et al.A variable fold change threshold determines significance for expression mocroarrays.FASEB-J.2003;17(2):321～323.
142. Marshall A,Hodgson J.DNA chip:An array of possibilities.Nature Biotechol.1998;16(1):27～31
143. Miller M F,Huffman K L,Gilbert S Y,et al.Retail consumer acceptance of beef tenderized with calcium chloride.JAnim Sci.1999;73:2308～2314.
144. Mizoshita K, Takano A, Watanabe T,et al.Identification of a 1.1-Mb region for a carcass weight QTL on bovine Chromosome 14. Mamm Genome. 2005;16(7):532～537.
145. Nino-Soto MI, Nuber UA, Basrur PK, et al.Differences in the pattern of X-linked gene expression between fetal bovine muscle and fibroblast cultures derived from the same muscle biopsies. Cytogenet Genome Res. 2005;111(1):57～64.
146. Ohno S, Im HJ, Knudson CB,et al.oligosaccharide-induced activation of transcription factors in bovine articular chondrocytes. Arthritis Rheum. 2005;52(3):800～809.
147. Page BT, Casas E, Heaton MP, et al.Evaluation of single-nucleotide polymorphisms in CAPN1 for association with meat tenderness in cattle. J Anim Sci. 2002;80(12):3077～3085.
148. Page BT, Casas E, Quaas RL, et al..Association of markers in the bovine CAPN1 gene with meat tenderness in large crossbred populations that sample influential industry sires. J Anim Sci. 2004;82(12):3474～3481.
149. Park YH, Joo YS, Park JY, et al.Characterization of lymphocyte subpopulations and major histocompatibility complex haplotypes of mastitis-resistant and susceptible cows. J Vet Sci. 2004;5(1):29～39.
150. Patel D, Danelishvili L, Yamazaki Y, et al.The ability of Mycobacterium avium subsp. paratuberculosis to enter bovine epithelial cells is influenced by preexposure to a hyperosmolar environment and intracellular passage in bovine mammary epithelial cells. Infect Immun. 2006 ;74(5):2849～2855
151. Pavlidis P,Li Q,Noble WS.The effect of replication on gene expression microarray experiments.Bioinformatics.2003;19(13):1620～1627.
152. Pfister-Genskow M, Myers C, Childs LA,et al.Identification of differentially expressed genes in individual bovine preimplantation embryos produced by nuclear transfer: improper reprogramming of genes required for development. Biol Reprod. 2005;72(3):546～55.
153. Rainard P, Riollet C.Innate immunity of the bovine mammary gland. Vet Res. 2006 ;37(3):369～400.
154. Renaville R, Gengler N, Vrech E, et al.Pit-1 gene polymorphism, milk yield, and conformation traits for Italian Holstein-Friesian bulls. J Dairy Sci. 1997;80(12):3431～3438
155. Reverter A, Byrne KA, Brucet HL,et al.A mixture model-based cluster analysis of DNA microarray gene expression data on Brahman and Brahman composite steers fed high-, medium-, and low-quality diets. J Anim Sci. 2003;81(8):1900～1910.
156. Reverter A, Hudson NJ, Wang Y, et al.A gene coexpression network for bovine skeletal muscle inferred from microarray data. Physiol Genomics. 2006;28(1):76～83.
157. Reverter A, Tier B, Johnston D J, et al. Assessing the efficiency of multiplicative mixed model equations to account for heterogeneous variance across herds in carcass scan traits from beef cattle. J Anim Sci.1997;75:1477～1485.
158. Reverter A, Wang YH, Byrne KA, et al.Joint analysis of multiple cDNA microarray studies via multivariate mixed models applied to genetic improvement of beef cattle. J Anim Sci. 2004;82(12):3430～3439.
159. Rexroad CE, Bennett GL, Stone RT, et al.Comparative mapping of BTA15 and HSA11 including a region containing a QTL for meat tenderness. Mamm Genome. 2001;12(7):561～565.
160. Ripoli MV, Corva P, Giovambattista G.Analysis of a polymorphism in the DGAT1 gene in 14 cattle in 14 cattle breeds through PCR-SSCP methods. Res Vet Sci. 2006;80(3):287～290.
161. Schenkel FS, Miller SP, Jiang Z, et al. Association of a single nucleotide polymorphism in the calpastatin gene with carcass and meat quality traits of beef cattle. J Anim Sci. 2006;84(2):291～299.
162. Schenkel FS, Miller SP, Ye X, et al. Association of single nucleotide polymorphisms in the leptin gene with carcass and meat quality traits of beef cattle. J Anim Sci. 2005;83(9):2009～2020.
163. Schmutz SM, Moker JS, Berryere TG.In situ hybridization of five loci to cattle chromosome 1. Cytogenet Cell Genet. 1998;81(1):51～53
164. Schr?der1 U J, Staufenbiel R. Invited review: methods to determine body fat reserves in the dairy cow with special regard to ultrasonographic measurement of backfat Thickness. J Dairy Sci, 2006; 89(1):1～14.
165. Simmon R,Dobbin K.Experimental design of DNA microarray experiments.Bio Technique. 2003;34:S16.
166. Sirard MA, Dufort I, Vallée M,et al.Potential and limitations of bovine-specific arrays for the analysis of mRNA levels in early development: preliminary analysis using a bovine embryonic array. Reprod Fertil Dev. 2005;17(1-2):47～57
167. Smith SL, Everts RE, Tian XC, et al.Global gene expression profiles reveal significant nuclearreprogramming by the blastocyst stage after cloning. Proc Natl Acad Sci U S A. 2005;102(49):17582～17587.
168. Smith TP, Lopez-Corrales NL, Kappes SM, et al.Myostatin maps to the interval containing the bovine mh locus. Mamm Genome. 1997,8(10):742～744.
169. Somers J, Smith C, Donnison M,et al.Gene expression profiling of individual bovine nuclear transfer blastocysts. Reproduction. 2006;131(6):1073～1084.
170. Stone RT, Casas E, Smith TP, et al. Identification of genetic markers for fat deposition and meat tenderness on bovine chromosome 5: development of a low-density single nucleotide polymorphism map. J Anim Sci. 2005;83(10):2280～2288.
171. Suchyta SP, Sipkovsky S, Halgren RG,et al.Bovine mammary gene expression profiling using a cDNA microarray enhanced for mammary-specific transcripts. Physiol Genomics. 2003;16(1):8～18.
172. Suchyta SP, Sipkovsky S, Kruska R,et al.Development and testing of a high-density cDNA microarray resource for cattle. Physiol Genomics. 2003;15(2):158～64.
173. Tan SH, Reverter A, Wang Y, et al.Gene expression profiling of bovine in vitro adipogenesis using a cDNA microarray. Funct Integr Genomics. 2006;6(3):235～249.
174. Tao W, Mallard B, Karrow N, et al.Construction and application of a bovine immune-endocrine cDNA microarray. Vet Immunol Immunopathol. 2004;101(1-2):1～17.
175. Tilstone.DNA mocroarray:vital statistics.Nature.2003;424(6949):610～612.
176. Ushizawa K, Herath CB, Kaneyama K, et al.cDNA microarray analysis of bovine embryo gene expression profiles during the pre-implantation period. Reprod Biol Endocrinol. 2004;2:77.
177. Ushizawa K, Takahashi T, Kaneyama K, et al.Gene expression profiles of bovine trophoblastic cell line (BT-1) analyzed by a custom cDNA microarray. J Reprod Dev. 2005;51(2):211～220.
178. Wang YH, Byrne KA, Reverter A, et al.Transcriptional profiling of skeletal muscle tissue from two breeds of cattle. Mamm Genome. 2005;16(3):201～210.
179. Weiss DJ, Evanson OA, Deng M, et al.Sequential patterns of gene expression by bovine monocyte-derived macrophages associated with ingestion of mycobacterial organisms. Microb Pathog. 2004 Oct;37(4):215～224
180. Wu XL, Macneil MD, De S, et al. Evaluation of candidate gene effects for beef backfat via Bayesian model selection.Genetica. 2005;125(1):103～113.
181. Yao J, Burton JL, Saama P, et al.Generation of EST and cDNA microarray resources for the study of bovine immunobiology. Acta Vet Scand. 2001;42(3):391～405.
182. Yao J, Ren X, Ireland JJ, et al.Generation of a bovine oocyte cDNA library and microarray: resources for identification of genes important for follicular development and earlyembryogenesis. Physiol Genomics. 2004;19(1):84～92.
183. Yeung KY, Ruzzo WL. Principal component analysis for clustering gene expression data.Bioinformatics.2001;17:763.
184. Yousef G,Amaar,Garrett R,et al .Insulin-like Growth Factor-binding Protein 5 (IGFBP-5) Interacts with a Four and a Half LIM Protein 2 (FHL2, ).2002;277( 14): 12053～12060.
185. Yu SL, Kim JE, Chung HJ, et al. Molecular cloning and characterization of bovine PRKAG3 gene: structure, expression and single nucleotide polymorphism detection. J Anim Breed Genet. 2005;122(5):294～301.
186. Zhao Q, Davis ME, Hines HC.Associations of polymorphisms in the Pit-1 gene with growth and carcass traits in Angus beef cattle. J Anim Sci. 2004;82(8):2229～2233.