Annual report 2007 - North Pacific Marine Science Organization (PICES). Sixteenth meeting, Victoria, Canada, October 26-November 5, 2007

Report of Opening Session (p. 1). Report of Governing Council (p. 15). Report of the Finance and Administration Committee (p. 65). Reports of Science Board and Committees: Science Board Inter-Sessional Meeting (p. 83); Science Board (p. 93); Biological Oceanography Committee (p. 105); Fishery Science Committee (p. 117); Marine Environmental Quality Committee (p. 129); Physical Oceanography and Climate Committee (p. 139); Technical Committee on Data Exchange (p. 145); Technical Committee on Monitoring (p. 153). Reports of Sections, Working and Study Groups: Section on Carbon and Climate (p. 161); Section on Ecology of Harmful Algal Blooms in the North Pacific (p. 167); Working Group 19 on Ecosystem-based Management Science and its Application to the North Pacific (p. 173); Working Group 20 on Evaluations of Climate Change Projections (p. 179); Working Group 21 on Non-indigenous Aquatic Species (p. 183); Study Group to Develop a Strategy for GOOS (p. 193); Study Group on Ecosystem Status Reporting (p. 203); Study Group on Marine Aquaculture and Ranching in the PICES Region (p. 213); Study Group on Scientific Cooperation between PICES and Non-member Countries (p. 225). Reports of the Climate Change and Carrying Capacity Program: Implementation Panel on the CCCC Program (p. 229); CFAME Task Team (p. 235); MODEL Task Team (p. 241). Reports of Advisory Panels: Advisory Panel for a CREAMS/PICES Program in East Asian Marginal Seas (p. 249); Advisory Panel on Continuous Plankton Recorder Survey in the North Pacific (p. 253); Advisory Panel on Iron Fertilization Experiment in the Subarctic Pacific Ocean (p. 255); Advisory Panel on Marine Birds and Mammals (p. 261); Advisory Panel on Micronekton Sampling Inter-calibration Experiment (p. 265). 2007 Review of PICES Publication Program (p. 269). Guidelines for PICES Temporary Expert Groups (p. 297). Summary of Scientific Sessions and Workshops (p. 313). Report of the ICES/PICES Conference for Early Career Scientists (p. 355). Membership (p. 367). Participants (p. 387). PICES Acronyms (p. 413). Acronyms (p. 415).

豌豆β-微管蛋白基因的分离

微管蛋白是在进化过程中最为保守的蛋白质中的一组。高等植物的微管蛋白基因与酵母的微管蛋白基因具有同源性。据此进行了如下实验：从豌豆（A561），大豆（黑农26）苗中提出的核DNA用EcoRI、BamHI和SalI限制性内切酶酶切，经Southern转移与32P标记的酵母β-微管蛋白cDNA进行杂交。从杂交图谱上可以看出豌豆、大豆均有两个拷贝的β-微管蛋白基因。豌豆核DNA经BamHI酶切后的5kb和10kb两个片段从电泳凝胶中回收，插入到puc9质粒中，宿主菌为JM83。然后以酵母β-微管蛋白基因为探针，用菌落原位杂交和Southern斑点杂交的方法筛选出含有豌豆β-微管蛋白基因编码序列的克隆。所克隆到的DNA序列的限制性酶切图谱及序列分析尚有待进一步研究。

玉米、谷子基因转化的研究

本工作用BT基因、PinⅡ基因和bar基因对青饲玉米、谷子进行了基因转化的研究，并且对转基因的受体、转基因的方法、转化后的筛选、检测及植株再生等问题进行了探讨。 玉米胚性细胞系，包括胚性愈伤组织和胚性细胞悬浮系，可作为基因转化的受体，它亦是原生质体培养的关键。玉米的基因型对胚性细胞系的获得有很大的影响。在相同的培养条件下，九个青饲玉米品系都得到了I型愈伤组织，但仅有两个品系(232和235)得到了胚性细胞系(L32和L35)。幼胚的长度及年龄也是影响诱导形成胚性愈伤组织的一个重要因素，最佳胚长是1-1.5mm，最佳胚龄是授粉后10-12天的幼胚。另外，适当提高蔗糖浓度对胚性细胞悬浮系的建立及保持均有好处。 从玉米原生质体培养获得了再生植株．在此基础上用电激法和PEG法将BT基因导入玉米原生体，发现在原生质体培养过程中，同对照相比，第一次细胞分裂及形成愈伤组织的时间往后推移． 诱导玉米I型愈伤组织没有基因型的限制，可以从大多数玉米品系中得到。并且玉米I型愈伤组织具有极强的分化能力．我们将玉米I型愈伤组织作为基因枪法转化的受体，获得了转基因工程植株。目前，尚未见这方面的报道． 基因枪法转化玉米胚性细胞系，得到抗性愈伤组织的效率约为1/40。用直径约3mm的玉米I型愈伤组织块作基因枪法转化受体，转化后经筛选平均每块可得到1-4个抗性愈伤组织系。用PEG和电激法转化玉米原生质体，转化后原生质体再生愈伤组织中，抗性愈伤组织的得率为9.3%和8.9%， 基因枪法适应完整的细胞和组织的转化，可较快得到抗性植株，在玉米基因转化研究中， 为了较快地得到转化植株，用基因枪法较电激法和PEG法更好，在玉米三种基因转化的受体中（原生质体、胚性细胞系和I型愈伤组织），以I型愈伤组织作受体最好，用它作受体可以避免原生质体培养的困难，克服获得胚性细胞系的基因型的限制。 胚性细胞系对抗菌素的耐受性随继代时间增长而增加．I型愈伤组织对抗菌素的耐受性 同愈伤组织块的大小呈正相关。 由于玉米愈伤组织对卡那霉素的本底抗性较高，所以需要用高浓度(800mg/L)的卡那霉 素进行筛选，过高的选择压力对芽的分化有抑制作用．用电激和PEG处理后的原生质体再生的愈伤组织，经卡那霉素筛选出的抗性愈伤组织未能得到再生植株。而对照则得到了再生植株。用PPT和Hyg筛选出的抗性愈伤组织得到了再生植株． 用PCR和Southern杂交对抗性愈伤组织和再生植株进行检测，证明外源基因已整合到 玉米基因组中。得到了携有BT基因、bar基因或PinⅡ基因的愈伤组织或工程植株。 用豫谷一号的幼穗诱导获得了胚性愈伤组织，基因枪转化后，经PPT筛选得到抗性愈伤组织。每个5cm的培养皿内装有谷子胚性愈伤组织约0.5g，经筛选后可得到5-10块抗性愈伤组织，此PPT抗性的愈伤组织用PCR和Southern杂交检测，证明bar基因已整合到了谷子的基因组中。从转化愈伤组织中已分化出了再生植株。

Predicting the distribution of Vibrio vulnificus in Chesapeake Bay

Vibrio vulnificus is a gram-negative pathogenic bacterium endemic to coastal waters worldwide, and a leading cause of seafood related mortality. Because of human health concerns, understanding the ecology of the species and potentially predicting its distribution is of great importance. We evaluated and applied a previously published qPCR assay to water samples (n = 235) collected from the main-stem of the Chesapeake Bay (2007 – 2008) by Maryland and Virginia State water quality monitoring programs. Results confirmed strong relationships between the likelihood of Vibrio vulnificus presence and both temperature and salinity that were used to develop a logistic regression model. The habitat model demonstrated a high degree of concordance (93%), and robustness as subsequent bootstrapping (n=1000) did not change model output (P > 0.05). We forced this empirical habitat model with temperature and salinity predictions generated by a regional hydrodynamic modeling system to demonstrate its utility in future pathogen forecasting efforts in the Chesapeake Bay.