Phenotypes, genotypes and operators in evolutionary computation

B群链球菌对红霉素及克林霉素耐药机制研究何其励;杨维青;张丽华;张丽;王欣;黄娟;陈军剑;郑碧英;张芳成【摘要】目的研究东莞地区孕产妇携带的GBS对大环内酯类的主要耐药表型及对红霉素、克林霉素的耐药机制.方法采用D试验筛查51株孕产妇携带的GBS对大环内酯类耐药表型;采用PCR方法检测GBS红霉素耐药基因ermTR、ermB、mefA/E及克林霉素耐药基因linB,进行基因测序及BLAST序列比对分析.结果 51株GBS经D试验筛查,35株为cMLSB耐药表型,7株为M耐药表型,9株为L耐药表型,未检测到iMLSB耐药表型;PCR检测到ermB 40株、mefA/E 23株、linB5株,未检测到erm TR耐药基因;cMLSB耐药表型中37.14％(13/35)GBS同时检出ermB和mefA/E基因.结论东莞地区孕产妇携带的GBS菌株大环内酯类耐药表型以cMLSB为主;ermB编码的23S rRNA甲基化酶是介导红霉素耐药的主要耐药机制;检测到新型耐药基因linB.东莞地区cMLSB耐药表型高而M耐药表型低,提示克林霉素作为预防和治疗GBS感染的二线药物在该地区可能会受到一定的限制.【期刊名称】《中国抗生素杂志》【年(卷),期】2015(040)002【总页数】4页(P124-127)【关键词】B群链球菌;红霉素;克林霉素;耐药基因【作者】何其励;杨维青;张丽华;张丽;王欣;黄娟;陈军剑;郑碧英;张芳成【作者单位】医学检验研究所临床微生物学教研室,广东医学院,东莞523808;医学检验研究所临床微生物学教研室,广东医学院,东莞523808;东华医院检验科细菌室,东莞523220;东华医院检验科细菌室,东莞523220;医学检验研究所临床微生物学教研室,广东医学院,东莞523808;医学检验研究所临床微生物学教研室,广东医学院,东莞523808;医学检验研究所临床微生物学教研室,广东医学院,东莞523808;医学检验研究所临床微生物学教研室,广东医学院,东莞523808;医学检验研究所临床微生物学教研室,广东医学院,东莞523808【正文语种】中文【中图分类】R378.12B群链球菌(Group B streptococci，GBS)，又称无乳链球菌，可引起新生儿肺炎、脑膜炎、败血症等。

Review Worksheet 11. A diploid organism has 20 chromosomes in its body cells.(1) How many pairs of homologous chromosomes does a body cell of thisorganism have?(2) How many chromatids does a body cell of this organism have at prophaseduring mitosis?(3) How many bivalents would be expected to form during meiosis? How manytetrads?(4) How many chromosomes are expected in each gamete of this organism?(5) How many chromosomes are expected in the zygote of this organism?(6) How many chromosomes does a cell at meiotic prophase I and telophase Ihave in this organism, respectively?2. The genotype of a diploid cell at a gene locus is Aa. “A” allele is dominant to “a” allele.(1) What are the genotypes of the two daughter cells derived from this cell after mitosis?(2) What allele would each of the four haploid cells derived from this cellafter meiosis have?3. A cross between two individuals with the genotype Aabb and Aabb,respectively was made. A is dominant to a and B is dominant to b.(1) What genotypes and phenotypes would be expected in the F1 generation?(2) What are the genotypic and phenotypic ratios in the F1 generation?4. A cross was made between the two genotypes AaBb and AaBb. A is dominant to a and B is dominant to b. The progeny below was obtained from this cross: A-B- 175A-bb 67aaB- 61aabb 21Determine if the ratio of these four phenotypes fit 9:3:3:1 using Chi-squareanalysis.5. Below is a pedigree of a human hereditary trait determined by one gene.(1) Is the shaded controlled by recessive or dominant allele?(2) Is this gene located on an autosome or X-chromosome?(3) Give all possible genotypes of each individual in the pedigree.6. Below is a family tree demonstrating inheritance of ABO blood types. The shaded is a Bombay phenotype. Give all possible phenotypes and genotypes of each individual in the family.7. Match the blood types that are compatible in transfusion.Donor RecipientA AB BAB ABO O8. Explain how you distinguish nuclear inheritance from extranuclear inheritance?Answers:1. (1) 10; (2) 40; (3) 10; (4) 10; (5) 20; (6) 20, 102. (1) Aa, Aa; (2) A, A, a, a3. (1) genotype: AAbb; Aabb; aabb; phenotype: A-bb; aabb(2) genotypic ratio: 1:2:1; phenotypic ratio: 3:14. X2 = 0.91, df=3, p=0.7 > 0.05, fail to reject H0; observed values fit 9:3:3:1ratio.5. (1) recessive;(2) autosome;(3) I-1 aa, I-2 Aa, II-1 Aa, II-2 Aa, II-3 aa, II-4 Aa, II-5 Aa, II-6 Aa,III-1 aa, III-2 Aa or AA, III-3 aa, III-4 Aa or AA, III-5 aa, III-6 Aa or AA6. I-1 I A I B, I-2 I O I O, II-1 I A I O or I B I O (A or B), II-2 I A I O or I B I O (O-Bombay),II-3 I O I O, II-4 I A I O or I B I O (A or B), III-1 I A I O (A)or I B I O (B) or I O I O (O), III-2 I A I O(A)or I B I O (B) or I O I O (O), III-3 I A I O (A)or I B I O (B) or I O I O (O)7. Find answers in your notes.8. Find answers in your notes.。

·病例报道·《中国产前诊断杂志（电子版）》　２０２４年第１６卷第１期产前诊断４６，ＸＸ睾丸型性发育异常胎儿１例并文献复习朱雨英１　吴轲２ （１．衢州市妇幼保健院产前诊断中心，浙江衢州　３２４０００；２．衢州市妇幼保健院产前诊断实验室，浙江衢州　３２４０００）【摘要】　目的　分析４６，ＸＸ睾丸型性发育异常胎儿的基因型与表型，并进行文献复习。

方法　１例超声提示胎儿颈后透明层增厚的孕妇来我院产前诊断中心咨询。

因其符合产前诊断指征，遂行胎儿染色体核型检测、胎儿染色体基因芯片检测。

以“４６，ＸＸ男性综合征”、“产前诊断”、“４６，ＸＸ睾丸型性发育异常”、“ｐｒｅｎａｔａｌｄｉａｇｎｏｓｉｓ”、“４６，ＸＸｍａｌｅｓｙｎｄｒｏｍｅ”、“４６，ＸＸｔｅｓｔｉｃｕｌａｒｄｉｓｏｒｄｅｒｏｆｓｅｘｄｅｖｅｌｏｐｍｅｎｔ”为检索词，检索中国知网、万方数据库、ＰｕｂＭｅｄ数据库（建库至２０２３年２月底），选取产前诊断为４６，ＸＸ睾丸型性发育异常胎儿且临床资料完整的文献进行复习并总结胎儿表型。

结果　胎儿染色体核型正常（４６，ＸＸ），基因芯片提示Ｙｐ１１．３１ ｐ１１．２区域拷贝数为１，大小为３２９９ｋｂ，存在犛犚犢基因，胎儿被诊断为４６，ＸＸ睾丸型性发育异常。

文献检索发现仅报道９例产前诊断为４６，ＸＸ睾丸型发育异常（犛犚犢基因阳性）胎儿，大部分（７０％，７／１０）胎儿孕期无明显异常，其中３／１０的胎儿存在结构异常或超声提示ＮＴ增厚，其中５／１０孕妇存在高龄风险。

结论　在产前诊断中，发现４６，ＸＸ睾丸型性发育异常胎儿是极为罕见的。

孕期４６，ＸＸ睾丸型性发育异常胎儿无明显异常；由于ＣＭＡ检测的局限性，部分４６，ＸＸ睾丸型ＤＳＤ胎儿（犛犚犢基因阴性）会被漏诊，这些因素给产前诊断和遗传咨询带来极大的挑战。

【关键词】　４６，ＸＸ睾丸型性发育异常；产前诊断；颈后透明层增厚【中图分类号】　Ｒ７１５．５ 【文献标识码】　Ｂ犇犗犐：１０．１３４７０／ｊ．ｃｎｋｉ．ｃｊｐｄ．２０２４．０１．０１１基金项目：２０２３年衢州市级指导性科技攻关项目（２０２３ＺＤ０８４） 通信作者：吴轲，Ｅｍａｉｌ：７５４２９９０５８＠ｑｑ．ｃｏｍ犘狉犲狀犪狋犪犾犱犻犪犵狀狅狊犻狊狅犳犪犳犲狋狌狊狑犻狋犺４６，犡犡狋犲狊狋犻犮狌犾犪狉犱犻狊狅狉犱犲狉狅犳狊犲狓犱犲狏犲犾狅狆犿犲狀狋犪狀犱犾犻狋犲狉犪狋狌狉犲狉犲狏犻犲狑犣犺狌犢狌狔犻狀犵１，犠狌犓犲２（１．犘狉犲狀犪狋犪犾犇犻犪犵狀狅狊犻狊犆犲狀狋犲狉，犙狌狕犺狅狌犕犪狋犲狉狀犻狋狔犪狀犱犆犺犻犾犱犎犲犪犾狋犺犆犪狉犲犎狅狊狆犻狋犪犾，犙狌狕犺狅狌，犣犺犲犼犻犪狀犵３２４００４，犆犺犻狀犪；２．犔犪犫狅狉犪狋狅狉狔狅犳犘狉犲狀犪狋犪犾犇犻犪犵狀狅狊犻狊，犙狌狕犺狅狌犕犪狋犲狉狀犻狋狔犪狀犱犆犺犻犾犱犎犲犪犾狋犺犆犪狉犲犎狅狊狆犻狋犪犾，犙狌狕犺狅狌，犣犺犲犼犻犪狀犵３２４００４，犆犺犻狀犪）【犃犫狊狋狉犪犮狋】　犗犫犼犲犮狋犻狏犲　Ｔｏａｎａｌｙｚｅｔｈｅｇｅｎｏｔｙｐｅｓａｎｄｐｈｅｎｏｔｙｐｅｓｏｆｔｈｅｆｅｔｕｓｗｉｔｈ４６，ＸＸｔｅｓｔｉｃｕｌａｒｄｉｓｏｒｄｅｒｏｆｓｅｘｄｅｖｅｌｏｐｍｅｎｔａｎｄｒｅｖｉｅｗｒｅｌａｔｅｄｌｉｔｅｒａｔｕｒｅ．犕犲狋犺狅犱狊　Ａｐｒｅｇｎａｎｔｗｏｍａｎｗｉｔｈｉｎｃｒｅａｓｅｄｎｕｃｈａｌｔｒａｎｓｌｕｃｅｎｃｙｃａｍｅｔｏｔｈｅｐｒｅｎａｔａｌｄｉａｇｎｏｓｉｓｃｅｎｔｅｒｆｏｒｇｅｎｅｔｉｃｃｏｕｎｓｅｌｌｉｎｇ．Ｄｕｅｔｏｔｈｅｐｒｅｎａｔａｌｄｉａｇｎｏｓｉｓｉｎｄｉｃａｔｉｏｎｓ，ｆｅｔａｌｃｈｒｏｍｏｓｏｍｅｋａｒｙｏｔｙｐｅａｎｄｃｈｒｏｍｏｓｏｍａｌｍｉｃｒｏａｒｒａｙａｎａｌｙｓｉｓ（ＣＭＡ）ｗｅｒｅｃａｒｒｉｅｄｏｕｔ．Ｔｈｅｌｉｔｅｒａｔｕｒｅｓｅａｒｃｈｗｉｔｈ“ｐｒｅｎａｔａｌｄｉａｇｎｏｓｉｓ”，“４６，ＸＸｍａｌｅｓｙｎｄｒｏｍｅ”，“４６，ＸＸｔｅｓｔｉｃｕｌａｒｄｉｓｏｒｄｅｒｏｆｓｅｘｄｅｖｅｌｏｐｍｅｎｔ”ａｓｋｅｙｗｏｒｄｓｗａｓｃｏｎｄｕｃｔｅｄｏｎＣＮＫＩ（ＣｈｉｎｅｓｅＮａｔｉｏｎａｌＫｎｏｗｌｅｄｇｅＩｎｆｒａｓｔｒｕｃｔｕｒｅ），Ｗａｎｆａｎｇ（Ｃｈｉｎｅｓｅ）ａｎｄＰｕｂＭｅｄ．ＡｌｌｌｉｔｅｒａｔｕｒｅｄａｔａｂａｓｅｓｗｅｒｅｓｅａｒｃｈｅｄｕｐｔｏｔｈｅｅｎｄｏｆＤｅｃｅｍｂｅｒ２０２３．Ｌｉｔｅｒａｔｕｒｅａｂｏｕｔｃｌｉｎｉｃａｌｄａｔａａｎｄｇｅｎｅｔｉｃｆｅａｔｕｒｅｓｏｆｆｅｔｕｓｅｓｗｉｔｈ４６，ＸＸｔｅｓｔｉｃｕｌａｒｄｉｓｏｒｄｅｒｏｆｓｅｘｄｅｖｅｌｏｐｍｅｎｔｗａｓｓｕｍｍａｒｉｚｅｄａｎｄｒｅｖｉｅｗｅｄ．犚犲狊狌犾狋狊　Ｆｅｔａｌｃｈｒｏｍｏｓｏｍｅｋａｒｙｏｔｙｐｅｓｈｏｗｅｄ８５《中国产前诊断杂志（电子版）》　２０２４年第１６卷第１期·病例报道· ４６，ＸＸ；ｆｅｔａｌＣＭＡｉｎｄｉｃａｔｅｄｏｎｅｃｏｐｙｏｆＹｐ１１．３１ ｐ１１．２（３２９９ｋｂ）（犛犚犢ｐｏｓｉｔｉｖｅ）．Ｔｈｅｆｅｔｕｓｗａｓｄｉａｇｎｏｓｅｄｗｉｔｈ４６，ＸＸｔｅｓｔｉｃｕｌａｒｄｉｓｏｒｄｅｒｏｆｓｅｘｄｅｖｅｌｏｐｍｅｎｔ．Ｆｏｒｎｏｗｏｎｌｙｎｉｎｅｃａｓｅｓｗｉｔｈｐｒｅｎａｔａｌｄｉａｇｎｏｓｉｓｏｆ４６，ＸＸｔｅｓｔｉｃｕｌａｒｄｉｓｏｒｄｅｒｏｆｓｅｘｄｅｖｅｌｏｐｍｅｎｔｈａｖｅｂｅｅｎｒｅｐｏｒｔｅｄ．Ｍｏｓｔｃａｓｅｓ（７０％，７／１０）ｄｉｄｎ’ｔｓｈｏｗａｂｎｏｒｍａｌｉｔｉｅｓ，３／１０ｏｆｔｈｅｆｅｔｕｓｅｓｈａｄｓｔｒｕｃｔｕｒａｌａｂｎｏｒｍａｌｉｔｉｅｓａｎｄｉｎｃｒｅａｓｅｄＮＴ，５／１０ｐｒｅｇｎａｎｔｗｏｍｅｎｈａｄｔｈｅｒｉｓｋｏｆａｄｖａｎｃｅｄａｇｅ．犆狅狀犮犾狌狊犻狅狀　Ｔｈｅｃａｓｅｓｗｉｔｈｔｈｅｐｒｅｎａｔａｌｄｉａｇｎｏｓｉｓｏｆ４６，ＸＸｔｅｓｔｉｃｕｌａｒｄｉｓｏｒｄｅｒｏｆｓｅｘｄｅｖｅｌｏｐｍｅｎｔａｒｅｅｘｔｒｅｍｅｌｙｒａｒｅ．Ｍｏｓｔｆｅｔｕｓｅｓｗｉｔｈ４６，ＸＸｔｅｓｔｉｃｕｌａｒｄｉｓｏｒｄｅｒｏｆｓｅｘｄｅｖｅｌｏｐｍｅｎｔｈａｖｅｎｏｏｂｖｉｏｕｓａｂｎｏｒｍａｌｉｔｉｅｓｄｕｒｉｎｇｔｈｅｗｈｏｌｅｇｅｓｔａｔｉｏｎｐｅｒｉｏｄ．ＤｕｅｔｏｔｈｅｌｉｍｉｔａｔｉｏｎｏｆＣＭＡ，ｆｅｔｕｓｅｓｗｉｔｈ４６，ＸＸｔｅｓｔｉｃｕｌａｒＤＳＤ（犛犚犢ｎｅｇａｔｉｖｅ）ｍａｙｂｅｍｉｓｓｅｄｄｉａｇｎｏｓｉｓ．Ｔｈｏｓｅｆａｃｔｏｒｓｐｏｓｅｇｒｅａｔｃｈａｌｌｅｎｇｅｓｆｏｒｐｒｅｎａｔａｌｄｉａｇｎｏｓｉｓａｎｄｇｅｎｅｔｉｃｃｏｕｎｓｅｌｌｉｎｇ．【犓犲狔狑狅狉犱狊】　４６，ＸＸｔｅｓｔｉｃｕｌａｒｄｉｓｏｒｄｅｒｏｆｓｅｘｄｅｖｅｌｏｐｍｅｎｔ；ｐｒｅｎａｔａｌｄｉａｇｎｏｓｉｓ；ｉｎｃｒｅａｓｅｄｎｕｃｈａｌｔｒａｎｓｌｕｃｅｎｃｙ ４６，ＸＸ男性性别逆转综合征（４６，ＸＸｍａｌｅｓｅｘｒｅｖｅｒｓａｌｓｙｎｄｒｏｍｅ），又称ｄｅｌａＣｈａｐｅｌｌｅ综合征，由ｄｅｌａＣｈａｐｅｌｌｅ等于１９６４年首次描述［１］，表现为染色体性别与性腺性别不相符，即患者染色体核型为４６，ＸＸ，而社会性别或第二性征表现为男性。

·论著·《中国产前诊断杂志（电子版）》　２０２０年第１２卷第４期１７９例血红蛋白Ｗｅｓｔｍｅａｄ基因型和表型研究梁凯玲　秦丹卿　黄演林　王继成　梁杰　姚翠泽　杜丽 （广东省妇幼保健院医学遗传中心，广东广州　５１１４４２）【摘要】　目的　分析ＨｂＷｅｓｔｍｅａｄ（ＨｂＷＳ）携带者的血液学特征，探讨携带ＨｂＷＳ突变的不同基因型的表型特点。

方法　回顾性分析在广东省妇幼保健院行地中海贫血（地贫）基因检测后诊断为ＨｂＷＳ携带者的１７９例样本，收集其血常规和血红蛋白电泳相关参数结果，运用ＳＰＳＳ软件进行统计分析。

结果　在检出的１７９例样本中，ＨｂＷＳ杂合子血液学指标基本正常，与静止型α地中海贫血临床表型相吻合；ＨｂＷＳ杂合子合并（ α３．７／）或（ α４．２／）时，平均红细胞血红蛋白量（ｍｅａｎｃｏｒｐｕｓｃｕｌａｒｈｅｍｏｇｌｏｂｉｎ，ＭＣＨ）较单纯的ＨｂＷＳ下降得明显，但其血液学各项指标变化较东南亚缺失型杂合子轻微；ＨｂＷＳ杂合子合并东南亚缺失型α 地贫时，表型类似轻型α 地贫；ＨｂＷＳ杂合子合并轻型β地贫时，表型类似轻型β 地贫。

结论　ＨｂＷＳ无论以杂合子单独存在还是合并α 或β 地贫时，对血液学表型的影响均较小。

【关键词】　血红蛋白Ｗｅｓｔｍｅａｄ；α 地中海贫血；β 地中海贫血；基因型；血液学表型【中图分类号】　Ｒ７１４．５６ 【文献标识码】　Ａ犇犗犐：１０．１３４７０／ｊ．ｃｎｋｉ．ｃｊｐｄ．２０２０．０４．０１１ 通讯作者：杜丽，Ｅ ｍａｉｌ：ｌｉｅｒ２８＠１６３．ｃｏｍ犌犲狀狅狋狔狆犻犮犪狀犱狆犺犲狀狅狋狔狆犻犮狊狋狌犱狔狅犳犺犲犿狅犵犾狅犫犻狀犠犲狊狋犿犲犪犱犻狀１７９犮犪狊犲狊犔犻犪狀犵犓犪犻犾犻狀犵，犙犻狀犇犪狀狇犻狀犵，犎狌犪狀犵犢犪狀犾犻狀，犠犪狀犵犑犻犮犺犲狀犵，犔犻犪狀犵犑犻犲，犢犪狅犆狌犻狕犲，犇狌犔犻犕犲犱犻犮犪犾犌犲狀犲狋犻犮狊犆犲狀狋犲狉，犌狌犪狀犵犱狅狀犵犠狅犿犲狀犪狀犱犆犺犻犾犱狉犲狀犎犲犪犾狋犺犆犪狉犲犎狅狊狆犻狋犪犾，犌狌犪狀犵狕犺狅狌，犌狌犪狀犵犱狅狀犵５１００１０，犆犺犻狀犪犆狅狉狉犲狊狆狅狀犱犻狀犵犪狌狋犺狅狉：犇狌犔犻，犈 犿犪犻犾：犾犻犲狉２８＠１６３．犮狅犿【犃犫狊狋狉犪犮狋】　犗犫犼犲犮狋犻狏犲　ＴｏａｎａｌｙｚｅｔｈｅｈｅｍａｔｏｌｏｇｉｃａｌｃｈａｒａｃｔｅｒｉｓｔｉｃｓｏｆｃａｒｒｉｅｒｓｏｆｈｅｍｏｇｌｏｂｉｎＷｅｓｔｍｅａｄ（ＨｂＷＳ）ａｎｄｉｎｖｅｓｔｉｇａｔｅｔｈｅｐｈｅｎｏｔｙｐｉｃｃｈａｒａｃｔｅｒｉｓｔｉｃｓｏｆｄｉｆｆｅｒｅｎｔｇｅｎｏｔｙｐｅｓｃａｒｒｙｉｎｇＨｂＷＳｍｕｔａｔｉｏｎｓ．犕犲狋犺狅犱狊　Ｒｅｔｒｏｓｐｅｃｔｉｖｅａｎａｌｙｓｉｓｗａｓｐｅｒｆｏｒｍｅｄｏｎ１７９ｓａｍｐｌｅｓｄｉａｇｎｏｓｅｄａｓＨｂＷＳｃａｒｒｉｅｒｓｂｙｔｈａｌａｓｓｅｍｉａｇｅｎｅｔｅｓｔｉｎｏｕｒｈｏｓｐｉｔａｌ．ＴｈｅｄａｔａｏｆｂｌｏｏｄｒｏｕｔｉｎｅｅｘａｍｉｎａｔｉｏｎａｎｄｈｅｍｏｇｌｏｂｉｎｅｌｅｃｔｒｏｐｈｏｒｅｓｉｓｗｅｒｅｃｏｌｌｅｃｔｅｄａｎｄＳＰＳＳｗａｓｕｓｅｄｆｏｒｓｔａｔｉｓｔｉｃａｌａｎａｌｙｓｉｓ．犚犲狊狌犾狋狊　ＴｈｅｈｅｍａｔｏｌｏｇｉｃａｌｉｎｄｅｘｏｆＨｂＷＳｈｅｔｅｒｏｚｙｇｏｔｅａｒｅｂａｓｉｃａｌｌｙｎｏｒｍａｌ，ｗｈｉｃｈｉｓｃｏｎｓｉｓｔｅｎｔｗｉｔｈｓｉｌｅｎｔ（ ｔｈａｌａｓｓｅｍｉａ；ＷｈｅｎＨｂＷＳｈｅｔｅｒｏｚｙｇｏｔｅｓｃｏｍｂｉｎｅｄｗｉｔｈ（ α３．７／）ｏｒ（ α４．２／），ｔｈｅＭＣＨｄｅｃｒｅａｓｅｄｓｉｇｎｉｆｉｃａｎｔｌｙｃｏｍｐａｒｅｄｗｉｔｈＨｂＷＳａｌｏｎｅ，ｗｈｉｌｅｔｈｅｈｅｍａｔｏｌｏｇｉｃａｌｃｈａｎｇｅｓｗｅｒｅｓｌｉｇｈｔｃｏｍｐａｒｅｄｗｉｔｈＳＥＡｈｅｔｅｒｏｚｙｇｏｔｅｓ；ＴｈｅＨｂＷＳｈｅｔｅｒｏｚｙｇｏｔｅｓｃｏ ｅｘｉｓｔｉｎｇｗｉｔｈＳＥＡｄｅｌｅｔｉｏｎｏｎｌｙｓｈｏｗｅｄｔｈｅｐｈｅｎｏｔｙｐｉｃｃｈａｒａｃｔｅｒｉｓｔｉｃｓｏｆｌｉｇｈｔα ｔｈａｌａｓｓｅｍｉａ．ＷｈｅｎＨｂＷＳｈｅｔｅｒｏｚｙｇｏｔｅｓｃｏｍｂｉｎｅｄｗｉｔｈｌｉｇｈｔ（ ｔｈａｌａｓｓｅｍｉａ，ｔｈｅｐｈｅｎｏｔｙｐｅｗａｓｓｉｍｉｌａｒｔｏ（ ｔｈａｌａｓｓｅｍｉａ．犆狅狀犮犾狌狊犻狅狀　ＷｈｅｔｈｅｒＨｂＷＳｈｅｔｅｒｏｚｙｇｏｔｅｓｏｃｃｕｒｒｅｄｉｎｉｓｏｌａｔｉｏｎｏｒｃｏ ｅｘｉｓｔｅｄｗｉｔｈα ｔｈａｌａｓｓｅｍｉａｏｒα ｔｈａｌａｓｓｅｍｉａ，ｔｈｅｅｆｆｅｃｔｏｎｈｅｍａｔｏｌｏｇｉｃｐｈｅｎｏｔｙｐｅｓｉｓｓｍａｌｌ．【犓犲狔狑狅狉犱狊】　ＨｂＷｅｓｔｍｅａｄ；αｔｈａｌａｓｓｅｍｉａ；β＋ｔｈａｌａｓｓｅｍｉａ；Ｇｅｎｏｔｙｐｅ；Ｈｅｍａｔｏｌｏｇｙｐｈｅｎｏｔｙｐｅ α 地中海贫血是由于α珠蛋白基因发生缺失或者突变导致的遗传性溶血性贫血，包括缺失型和非缺失型两类。

收稿日期：２０２１０９０９；修回日期：２０２１１０２８ 基金项目：贵州省科技计划项目重大专项项目（黔科合重大专项字［２０１８］３００２，黔科合重大专项字［２０１６］３０２２）；贵州省公共大数据重点实验室开放课题（２０１７ＢＤＫＦＪＪ００４）；贵州省教育厅青年科技人才成长项目（黔科合ＫＹ字［２０１６］１２４） 作者简介：兰周新（１９９８），男，硕士研究生，主要研究方向为机器学习（ｌｚｘｃ５１１＠１６３．ｃｏｍ）；何庆（１９８２），男（通信作者），副教授，博士，主要研究方向为智能算法、大数据应用．

多策略融合算术优化算法及其工程优化兰周新ａ，ｂ，何　庆ａ，ｂ（贵州大学ａ．大数据与信息工程学院；ｂ．贵州省公共大数据重点实验室，贵阳５５００２５）

摘　要：针对算术优化算法（ＡＯＡ）在搜索过程中容易陷入局部极值点、收敛速度慢以及求解精度低等缺陷，提出一种多策略集成的算术优化算法（ＭＦＡＯＡ）。首先，采用Ｓｏｂｏｌ序列初始化ＡＯＡ种群，增加初始个体的多样性，为算法全局寻优奠定基础；然后，重构数学优化器加速函数（ＭＯＡ），权衡全局搜索与局部开发过程的比重；最后，利用混沌精英突变策略，改善算法过于依赖当前最优解的问题，增强算法跳出局部极值的能力。选用１２个基准函数和部分ＣＥＣ２０１４测试函数进行实验仿真，结果表明ＭＦＡＯＡ在求解精度和收敛速度上均有明显的提升；另外，通过对两个工程实例进行优化，验证了ＭＦＡＯＡ在工程优化问题上的可行性。关键词：算术优化算法；Ｓｏｂｏｌ序列；数学优化器加速函数；混沌精英突变；工程优化中图分类号：ＴＰ１８ 文献标志码：Ａ 文章编号：１００１３６９５（２０２２）０３０１９０７５８０６ｄｏｉ：１０．１９７３４／ｊ．ｉｓｓｎ．１００１３６９５．２０２１．０９．０３５８

Ｍｕｌｔｉｓｔｒａｔｅｇｙｆｕｓｉｏｎａｒｉｔｈｍｅｔｉｃｏｐｔｉｍｉｚａｔｉｏｎａｌｇｏｒｉｔｈｍａｎｄｉｔｓａｐｐｌｉｃａｔｉｏｎｏｆｐｒｏｊｅｃｔｏｐｔｉｍｉｚａｔｉｏｎ

Unit 2 Gene and Its ApplicationText CGene Study Helps Unravel Biology of Alcoholism1 Genomic association studies can help scientists pick out target genes and biological pathways for further investigation, but they are not the end-all tools to explain disease mechanisms.2 A new genomewide association study (GWAS①) has found several mutations linked to increased susceptibility for developing alcohol dependence, bringing scientists a step closer to understanding the complex biological mechanisms of alcohol use disorders.3 Two single nucleotide polymorphisms(SNPs②), both located on the chromosomal region 2p35, had the highest degree of association with alcohol dependence in a relatively homogenous patient population. These SNPs are located near the PECR gene, which encodes an enzyme (peroxisomal trans-2-enoyl-coA reductase) involved in fatty-acid metabolism, particularly when the body’s energy supply is switched from glucose to fat.4 A third SNP with a slightly lower association with alcohol dependence is located within the PECR gene. These three variants are “in strong linkage disequilibrium, or LD, meaning that the same variants at different loci almost always appear togeth er,” Marcella Rietschel, M.D.③, the senior author of the study, told Psychiatric News④. “So it is very likely—but still not certain—that the PECR gene is involved [in alcohol dependence].”5 Rietschel is a professor of genetic epidemiology in psychiatry at the Central Institute of Mental Health Mannheim at the University of Heidelberg⑤, Germany.6 This chromosomal region has been implicated in alcohol dependence in previous research. The PECR gene is expressed most heavily in the liver, but very little in the brain. “As alcohol does not act only on the brain, alcohol dependence can be modulated by many factors whose primary target is not the brain,” Rietschel said. “The best known genetic variants modulating alcohol a ddiction are variants in the genes metabolizing alcohol, like variants in the alcohol dehydrogenase gene clusters.”7 Indeed, this study confirmed several other SNPs associated with alcohol dependence, including those located in the ADH1C gene coding for one of the alcohol-metabolizing alcohol dehydrogenases, as well as the CDH13 gene coding fora cell-adhesion protein known as T-cadherin. Both genes have been implicated in①Genomewide Association Study全基因组关联研究②Single Nucleotide Polymorphisms 单核苷酸多态性③abbr. Medicinae Doctor （[拉丁语] 医学博士(=Doctor of Medicine)）④Psychiatric News is the newspaper of the American Psychiatric Association (APA). It is published on the first and third Fridays of each month. 《精神病学新闻》⑤德国海德堡大学曼海姆中央精神卫生研究所alcohol dependence in previous studies.8 Despite the strong evidence, these variants and their impact on alcohol dependence need to be replicated by additional studies. “The uncertainty is a problem encountered in many GWA studies: A SNP is found to be associated but is not functional itself, so one cannot be sure if this SNP is itself involved in the regulation of genes or if it is only in LD with other causal SNPs, which can be quite far away or even in other genes,” said Rietschel. Since the three top SNPs discovered in this study are close to an d in the PECR gene, “this gene definitely merits further investigation.”9 The researchers first performed a genomic scan for more than 500,000 SNPs, using a sample of 487 alcohol-dependent patients and 1,358 controls. The GWAS identified 121 SNPs that were likely candidates for genetic association.10 The patients selected for the GWAS were German men with a DSM-IV diagnosis of alcohol dependence, whose condition was severe enough to require hospitalization for treatment or prevention of alcohol withdrawal. In addition, the subjects all had an onset of alcohol dependence before age 28; early-onset alcohol dependence has been shown to have a stronger hereditary component. Because alcohol dependence is a multifactorial disorder with multiple phenotypes and genotypes, the researchers narrowed their sampling to clinically similar patients to reduce the heterogeneity.11 Because of the vast number of mutations existing in every person and the large number scanned in a GWAS, scientists face the challenge of weeding out too many potential false-positive“hits,” or variants that appear to be significantly associated with a disease when they are, in fact, random coincidences. To minimize false hits and maximize true disease-associated mutations, strategies such as stringent statistical criteria and replication studies are often used in genetic association studies.12 Here, the researchers used a method called convergent functional genomics. This approach combines gene-expression data from animal models, evidence from human genetic association studies, and findings from human tissues such as brain tissue in autopsies to help prioritize investigation on the most promising candidate genes or the most likely biological pathways. In this study, 19 SNPs were identified after the human GWAS findings were compared with homologous, over-expressed genes in rats that were “alcoholic” strains.13 Armed with 121 candidate SNPs from the GWAS and 19 SNPs derived from convergent functional genomics analysis, the researchers performed a replication study of 1,024 male patients with alcohol dependence and 996 age-matched controls. The replication study confirmed that 15 SNPs have a significant association with alcohol dependence.14 This study was funded by grants from the German government and the European Commission.Source: /content/44/16/25.1.fullWords: 776Words and Expressionsgenomic [ʤi:'nəʊmɪk] adj. of or relating to genome 基因组的；染色体的target gene 目标基因dependence [dɪ'pendəns] n. being abnormally tolerant to and dependent on somethingthat is psychologically or physically habit-forming（毒）瘾，吸毒癖好；药瘾alcohol dependence酒精瘾alcohol use disorders 因酒精使用而导致的障碍nucleotide ['nju:klɪətaɪd] n.a phosphoric ester of a nucleoside; the basic structuralunit of nucleic acids (DNA or RNA) 核苷酸polymorphism [,pɒlɪ'mɔ:fɪzm]n. (biology) the existence of two or more forms ofindividuals within the same animal species(independent of sex differences) 多形性（现象）；多态性degree of association 相关度，关联度disequilibrium [,dɪsɪkwɪ'lɪbrɪəm] n. loss of equilibrium attributable to anunstable situation in which some forcesoutweigh others（尤指经济上的）不平衡，失去平衡，失调，不稳定linkage disequilibrium连锁不平衡express [ɪks'pres]vt. manifest the effects of (a gene or genetic trait) 使（某一基因）在表型中产生有关性状；在表型中表现某一基因的性状（或效应等），使（基因）示性；使（基因）合成特种蛋白dehydrogenase [di:'haɪdrəʤəneɪs] n. 脱氢酶alcohol dehydrogenase醇脱氢酶gene cluster基因簇；一组相同或者相似的基因adhesion protein粘着蛋白cadherin钙黏蛋白genomic scan 基因组扫描hospitalization [,hɒspɪtəlaɪ'zeɪʃən] n. the condition of being treated as a patient ina hospital; a period of time when you areconfined to a hospital送进医院治疗；住院（治疗）；住院期间alcohol withdrawal 戒酒；酒精戒断hereditary [hɪ'redɪtərɪ] adj. tending to occur among members of a family usuallyby heredity遗传的；遗传性的multifactorial[,mʌltɪfæk'tɔ:rɪəl] adj. involving or depending on several factors orcauses (especially pertaining to a condition ordisease resulting from the interaction of manygenes) 多遗传因子的；多种因素的phenotype ['fi:nə,taɪp] n.what an organism looks like as a consequence of theinteraction of its genotype and the environment表现型；表型；显型genotype ['ʤi:nəʊtaɪp] n. a group of organisms sharing a specific geneticconstitution基因型，遗传型heterogeneity [,hetərəʊdʒɪ'niːɪtɪ] n.the quality of being diverse and notcomparable in kind多样性，不均一性；异质性false-positive假阳性的functional genomics功能基因组学homologous [hɒ'mɒləgəs] adj.having the same evolutionary origin but servingdifferent functions同种异体的；相应的，同源的；同系列的，同属列的，同周期的；（细胞、抗血清等）同种的Comprehension ExercisesExercise 1 Multiple ChoicesDirections: Choose the best answer to each of the following questions.1)According to GWAS, how many SNPs are found to have the highest degree ofassociation with alcohol dependence?A)One.B)Two.C)Three.D)Four.2)Which of the following statements is true, according to the text?A)Two single nucleotide polymorphisms (SNPs), both located on thechromosomal region 2p33, had a slightly lower degree of association withalcohol dependence.B)Because of the strong evidence, these SNPs and their impact on alcoholdependence needs no additional studies.C)Because alcohol does not act only on the brain, alcohol dependence can bemodulated by many factors whose primary target is not the brain.D)Armed with 121 candidate SNPs from the GWAS and 19 SNPs derived fromconvergent functional genomics analysis, the researchers performed areplication study of 1358 male patients with alcohol dependence and 487age-matched controls.3)Which gene is helpful to further gene studies, according to a new genomewideassociation study (GWAS)?A)SNPsB)CDH13C)ADH1CD)PECR4)Which of the following strategies or methods is not the one adopted in order tominimize false hits and maximize true disease-associated mutations?A)Stringent statistical criteria.B)Replication studies.C)Convergent functional genomics.D)Genomic scanKey:B-C-D-DExercise 2 True or False StatementsDirections: Read the following statements and decide whether they are true (T) or false (F).（）1)Genomic association studies can explain disease mechanisms because it helps scientists pick out target genes and biological pathways forfurther investigation.（）2) A new genomewide association study (GWAS) has found several mutations related to alcohol dependence.（）3)SNPs which are located near the PECR gene, encode an enzyme (peroxisomal trans-2-enoyl-coA reductase) involved in fatty-acidmetabolism.（）4)The three SNPs which are proved to have degree of association with alcohol dependence are near or within the PECR gene.（）5)Marcella Rietschel believed that it is very likely that the PECR gene is involved in alcohol dependence.（）6)The PECR gene is expressed most heavily in the liver, but very little in the brain.（）7)The best known genetic variants modulating alcohol addiction are variants in the genes metabolizing alcohol, like variants in thedehydrogenase gene clusters.（）8)ADH1C gene is the gene codes for one of the alcohol-metabolizing alcohol dehydrogenases known as T-cadherin.Key:F-T-F-T-T; T-F-FExercise 3 Word-detectingDirections: Find a word in the designated paragraph to complete the sentence.1)ADH1C gene and CDH13 gene have been i in alcohol dependence inprevious studies. (Para. 7)2)The u is a problem encountered in many GWA studies. (Para. 8)3)The patients selected for the GWAS were German men with a DSM-IV diagnosisof alcohol d . (Para. 10)4)Alcohol dependence is a m disorder with multiple phenotypes andgenotypes. (Para. 10)Key:1)implicated2)uncertainty3)dependence4)multifactorialVocabulary ExercisesEnhance your command of medical wordsExercise 1 Word-matchingDirections: Choose the definitions in the right column to match the words in the left column.Key:b-d-a-e-f-g-c-hExercise 2 TranslationDirections: Translate the following terms into Chinese.Key:1) 目标基因2) 酒精瘾3) 使用障碍4) 相关度，关联度5) 连锁不平衡6) 醇脱氢酶7) 基因簇；一组相同或者相似的基因8) 粘着蛋白9) 基因组扫描10) 戒酒；酒精戒断11) 假阳性的12) 功能基因组学Exercise 3 Word-detectingDirections: Find a word in the designated paragraph to complete the sentence.1) The physician should also order and hormonal studies. (Para. 3)2) People with diabetes have too much , or sugar, in their blood. (Para. 3)3) In the absence of an accurate , no basis exists for selecting a treatment.(Para. 10)1) nucleotide 2) polymorphism 3) loci 4) express 5) dehydrogenase 6) cadherin 7) phenotype 8) genotype a) （基因）座位（locus 的复数） b) 核苷酸 c) 表现型；表型；显型 d) 多形性（现象）；多态性 e) 使（基因）示性；使（基因）合成特种蛋白 f) 脱氢酶 g) 钙黏蛋白 h) 基因型，遗传型1) target genes 2) alcohol dependence 3) use disorders 4) degree of association 5) linkage disequilibrium 6) alcohol dehydrogenase 7) gene cluster 8) adhesion protein 9) genomic scan 10) alcohol withdrawal 11) false-positive 12) functional genomics4)Doctor: I can do nothing about your conditi on. I’m afraid it’s . (Para. 10)5)The two loci all have sequence . (Para. 10)6)Translocation occurs when a fragment of one chromosome becomes attached to anon- chromosome. (Para. 12)Key:1)chromosomal2)glucose3)diagnosis4)hereditary5)heterogeneity6)homologousTranslation of the sentences1)还应该进行染色体和激素水平的检查。

PHENOTYPIC PLASTICITY Functional and Conceptual ApproachesEdited byThomas J. DeWittSamuel M. Scheiner120041Phenotypic Variationfrom Single GenotypesA PrimerTHOMAS J. DEWITTSAMUEL M. SCHEINERThe Breadth of the TopicA plant senses competitors for light and elongates its stem, accepting and elevating the challenge. A zooplankter senses diurnal predators and alters its daily vertical movements.A great breadth of ideas fall under the rubric of phenotypic plasticity, and this book is designed to express that breadth as a broad historical and conceptual review, bringing together a variety of (sometimes conflicting) viewpoints. In this chapter, we set the stage for the rest of the book by reviewing these diverse ideas under an intentionally broad definition of plasticity: environment-dependent phenotype expression. We emphasize the value of combining proximate, ultimate, and historical views. We hope to convey the need to understand how trait values are influenced by the environment, how indi-viduals vary in this ability, and what such variations imply for how organisms live and reproduce.Why Study Phenotypic Plasticity?Phenotypic plasticity, as a paradigm, has broad significance and appeal because it unites perhaps all of biology. Phenotypic plasticity embraces genetics, development, ecology, and evolution and can include physics, physiology, and behavioral science. Although observations of environmentally induced phenotypes were once met blankly or with umbrage (chapter 2), the same observations today provoke biologists to ask how and why plasticity occurs. The change of interest reflects our new understanding that plas-ticity is a powerful means of adaptation. Alternative alleles or their products react dif-12PHENOTYPIC PLASTICITYferently to the environment; those with favorable reactions persist while others go ex-tinct. This mechanism produces flexible organisms that respond to environmental shifts with beneficial phenotypic changes (chapters 8–10).Although the view of plasticity as provider of elaborate adaptations has stimulated a recent boom in research, plasticity also can be a liability for organisms. If a single phe-notype is best in all circumstances, then environmentally induced deviation away from the best phenotype only reduces fitness. For example, Eurosta solidaginis larvae pro-ducing an intermediate gall size on goldenrod plants are least vulnerable to predators (Abrahamson and Weis 1999). Yet the gall size produced by the fly depends on the plant genotype, an aspect of the fly’s environment (Weis and Gorman 1990). Thus, environ-mental influences interfere with a fly’s ability to consistently produce the best gall size. Often genetic changes are required to compensate for maladaptive plastic responses to the environment (i.e., countergradient variation).Even when plasticity can potentially help organisms solve the problem of alterna-tive phenotypic optima in different environments, costs and limits of plasticity may make plasticity suboptimal compared with a compromise level of plasticity that is more eco-nomical (Van Tienderen 1991; reviewed in DeWitt et al. 1998). And once plasticity has evolved, it may obviate the need for alternative adaptations to environmental variation. So, as either adaptation or constraint, or as part of an integrated set of strategies, plas-ticity is a key element in the functioning of organisms in variable environments.Defining PlasticityA common definition of phenotypic plasticity is the environmentally sensitive produc-tion of alternative phenotypes by given genotypes (for a semantic review, see Stearns 1989). This definition leaves considerable flexibility in deciding what types of traits exhibit plasticity, because the word “phenotype” is left for individuals to define for them-selves. Some scientists prefer to restrict the concept of phenotypic plasticity to devel-opmental processes (chapter 5) rather than other labile means of expressing phenotypes, such as physiological or behavioral shifts (chapter 8). Another view holds plasticity to be any environment-dependent gene expression, which can include gene regulatory processes that may have no gross phenotypic effects.The danger of too broad a definition is that all biological processes are to some ex-tent influenced by the environment. Thus, everything falls in the realm of plasticity. We fail to see this as a problem, as long as the point of addressing these diverse phe-nomena as plasticity is to focus on the genotype–environment interaction. Such breadth of scope reinforces the idea that a particular trait value as observed in a given environ-ment always is a special case of a potentially more complex relationship. That is, spe-cific phenotype–environment observations are a fraction of a multidimensional space. This view promotes in our thinking the constant and useful caveat that given phenotype distributions may only apply for the environment in which observation is conducted. Extrapolation beyond given conditions must be justified rather than assumed.Often there is resistance to use of the language and conceptual framework of plastic-ity to describe phenomena outside of development. Is suppression of vertical migration in plankton, based on chemical cues from predators, really plasticity? Yet the wealth of concepts and unique analytical tools in the field of plasticity research might inform tan-PHENOTYPIC VARIATION FROM SINGLE GENOTYPES3 gent fields of inquiry with different traditions. Likewise, these other fields can simi-larly inform mainstream studies in phenotypic plasticity research (e.g., chapters 5, 7, 8, and 11). Thus, each of the following examples, with increasingly liberal definitions of plasticity, can be considered plasticity: (1) development of alternative leaf types in high versus low light, (2) induced chemistry in response to herbivory, (3) production of lac-tase enzymes in bacteria triggered by the presence of lactose, (4) suppression of the vertical migration instinct in zooplankton by chemical cues from fish, (5) production of fever in endotherms upon infections, (6) buildup of muscles with use, and (7) animal learning. We suggest you draw the line where you wish, but be prepared to learn from those who draw their line elsewhere.We also distinguish between this broad definition of plasticity as a trait, and a more narrow scope of evolutionary theory of plasticity (chapter 6). Theories of plasticity evolution all deal, in some fashion, with evolution and adaptation in uncertain environ-ments, where uncertainty can be a function of a variety of ecological and biological mechanisms. Other aspects, such as costs of plasticity, are treated as constraints that are fixed by aspects of the organism’s biology and are external to the evolutionary dynamic. Plasticity as a paradigm for evolutionary studies encompasses a much wider set of ques-tions (chapter 13) than are covered by evolutionary models of plasticity.Environmental or Genetic?Although the definition of plasticity can expand or contract to accommodate various traits, it is important to keep the definition narrow with respect to which aspects of trait variation we refer to as plasticity. Biologists commonly partition total phenotypic vari-ance (V P) into that due to genetic effects (V G) and that due to environmental effects (V E). The equation V P = V G + V E can be found in most introductory biology textbooks. Typi-cal in this gross view is that all deviations from genotype values (= breeding values) are deemed “environmental.” But the environmental component is not accorded any func-tional or breeding value and is not distinguished from developmental or stochastic noise. The recognition of phenotypic plasticity, systematically induced variation attributable to specific environmental states, has allowed us to refine and go beyond the simple di-chotomy (Via and Lande 1985).With recognition of the importance of phenotypic plasticity, we expand the variance partition to V P = V G + V E + V G×E + V errror (Scheiner and Goodnight 1984; Via and Lande 1986), which includes explicit recognition of a systematic environmental effect (V E) and, perhaps more important, a genotype–environment interaction (V G×E). This interac-tion specifies that the environment’s effect is different for some genotypes relative to others (figure 1.1). So persistence of one subset of genotypes over others can change the average effect of the environment. For example, if divergent natural selection fa-vors some genotypes over others based on genotypic reactions to the environment, then adaptive evolution of plasticity will occur.Finally, a typological dichotomy we must disintegrate involves the question, “Is variation plastic or genetic?” This question is enduring and perennially misleading. The query often reflects the incorrect view of environmental and genetic effects being ex-clusive entities. Besides the obvious fact that genes and environment can interact (G×E variation), plastic responses are underlain by genes even when plasticity exhibits no4PHENOTYPIC PLASTICITYFigure 1.1.A diversity of reaction norms. Mean phenotype and variance in two environments for a family are denoted with circles, and those for another family are denoted with squares. Family means across environments are connected with a line, the reaction norm, to indicate familial identity. Boldface terms adjacent to the panels (G, E, G×E) indicate significant genetic, envi-ronmental, or gene–environment interaction variance, respectively. (A) Flat reaction norms (i.e., no phenotypic plasticity) with consistent genetic differences between families in both environ-ments. (B) Sloped, parallel reaction norms, indicating plasticity and additive genetic variation for trait means but no interaction variance. That is, both genotypes are similarly plastic. (C) Differently sloped reaction norms, indicating genetic variation for plasticity (i.e., interaction vari-ance). Because the overall slope is positive, there is also an effect of environment. Because the marginal mean phenotypes do not differ between families, there is no primary genetic effect (i.e., no genetic main effect). (D) As in C, family marginal means are the same for both families, but the families have opposite reactions to the environment. Therefore, only interaction variance is illustrated here. Asterisks are placed in D to illustrate adaptive optima. Because the family rep-resented by squares would perform better than the other family, and families differ genetically in their degree of plasticity, plasticity would evolve.additive genetic variance. Such responses are still genetic in the sense that they repre-sent a range of reaction that could be subject to modification if suitable mutations arose and were favored by selection. That all organisms in a population have alleles respond-ing similarly to an observed portion of an environmental gradient does not imply the reaction norm is nongenetic. [Conversely, just because a response is plastic still requires that we distinguish between active and passive plasticity (chapter 10).] The number of fingers on human hands is not heritable in the strict sense, yet it would be hard to con-tend that the trait is not genetic. These points may seem obvious, but we frequently seePHENOTYPIC VARIATION FROM SINGLE GENOTYPES5 plasticity cited as being “nongenetic,” a tradition going back at least to Wright (1931). Put another way, such traits are actually perfectly heritable, in the sense that you will express the exact phenotype of your parents. Such traits are not heritable in the breed-ing-value (or evolutionary) sense that the inherited trait distinguishes you from random individuals in the population. Yet there are genetically fixed responses to the environ-ment, genetically fixed plasticity.Therefore, the answer to the question, “Is variation plastic or genetic?” is simple—it’s genetic. Sometimes it is not heritable in the narrow sense (i.e., additive genetic vari-ance), however.Plasticity versus Developmental NoisePhenotypic variation from single genotypes can be produced by phenotypic plasticity or developmental noise. Developmental noise consists of random fluctuations that arise during development that alter the phenotypic product of development (Lynch and Gabriel 1987; Scheiner et al. 1991). The effect of developmental noise on fitness could be good, bad, or neutral. For example, developmental noise is costly under stabilizing selection because organisms cannot consistently produce the optimal phenotype (Yoshimura and Shields 1992; DeWitt and Yoshimura 1998). Conversely, developmental noise can be good in fluctuating environments because genotypes with noisy development have broader environmental tolerance (sensu Lynch and Gabriel 1987), so the geometric mean fitness among generations is increased.Scheiner et al. (1991) raised the question of whether phenotypically plastic geno-types are by necessity “developmentally noisy.” Scheiner et al. (1991) found no clear relationship between developmental noise and plasticity in bristle number, wing length, or thorax length in Drosophila melanogaster. Likewise, DeWitt (1998) failed to find evidence that developmental noise is associated with plasticity for shell shape in a fresh-water snail.In the equation, V P = V G + V E + V G×E + V errror, V E is plasticity and V error is develop-mental (or behavioral, etc.) noise. The designation of “noise” implies only that pheno-typic deviations from a mean are random in direction but not necessarily random in magnitude. For example, in some environments it may be useful to hedge one’s bets by producing variable offspring (Kaplan and Cooper 1984). In such environments, selec-tion favors random phenotypic deviations from a mean, whereas other environments perhaps present strictly stabilizing selection for a mean with no variance. Therefore, it is reasonable to expect interesting evolutionary patterns where both trait means and variances, and potentially higher moments of phenotype distributions (e.g., skewness), vary across environments in an adaptive manner (chapter 7).To illustrate this point, consider the freshwater snail Physa, in which chemical cues from fish induce crush-resistant shells. When fish cues are detected by snails it is cer-tain that fish are present, yet the absence of cues does not always imply the absence of the predator. Thus, noninducing environments (absence of inducing cues) can be in-scrutable (sensu Leon 1993). Inscrutable environments favor bet hedging, so we can expect snails in the noninducing environment to produce a moderate shell shape with greater variance than that produced in the inducing (fish) environment. Empirical data6PHENOTYPIC PLASTICITYmatch this prediction (figure 1.2; T.J.D., unpublished data). Imagine the simultaneous optimization that selection conducts for all these moments along an environmental gra-dient. It is perfectly reasonable to speak both of reaction norms for trait means and of reaction norms for developmental noise (DeWitt and Yoshimura 1998) and potentially higher moments (chapter 7).Genetics or Ecology?There is a point at which the mathematical abstractions about genetic correlations and phenotypic variance components lose intuitive value to ecologists. What do they tell us about the ecology of the organism? Similarly, geneticists may lose interest in studiesFigure 1.2.Reaction norm for shell morphology in the freshwater snail Physa virgata. The re-action norm depicts treatment means and variances of the first canonical axis (from a MANCOVA of partial warp scores; Bookstein 1991). The canonical y-axis describes elongate shells in a noninducing (control) environment and rotund shells in an inducing (bluegill sunfish) environ-ment. Landmarks used in the analysis are indicated in the inset. Shell images illustrate shape differences between treatments magnified 10× using tpsSuper software (Rohlf 2000).PHENOTYPIC VARIATION FROM SINGLE GENOTYPES7 that do not report genetic variation for the traits. We sympathize with both views. It is unfortunate that genetic and functional aspects of plasticity are often studied in isola-tion of one another; quantitative genetic and functional ecology approaches should be complementary. Consider the traits a snail uses to avoid its many predators. One of the traits (growth rate) has high heritability within the environments, but little cor-relation (r G) between environments (DeWitt 1996), which suggests that different genes contribute to the trait in alternative environments (Falconer and Mackay 1996). Al-though this suggestion is a mathematical deduction, the ecology of the animals indi-cates the likely cause. Behavior (hence, behavior genes) seems to determine growth rate in one environment—snails raised with fish perform antipredator behaviors that restrict feeding, so growth suffers (DeWitt 1998; Langerhans and DeWitt 2002). In an environment with an alternative predator, snails reduce allocation to reproduction (determined by a different suite of genes), seemingly to reduce time spent in a vul-nerable size class (Crowl and Covich 1990; DeWitt 1998). Thus, we have a functional (and adaptive) basis for understanding the mathematical deduction. This example il-lustrates the sort of multiple-trait, multiple-environment approach that is needed to address plasticity evolution.In many plasticity studies, fitness itself is frequently treated as a trait (e.g., Schmitt 1993; Stratton 1994). Environmental tolerance curves can be thought of as reaction norms for fitness over an environmental gradient. Conversely, reaction norms for fitness can be thought of as parts of environmental tolerance curves. Each view yields insight into the evolutionary ecology of organisms. However, we think that it is more fruitful to focus on individual traits and their reaction norms, not fitness per se, because this allows one to ask questions about plasticity as an adaptation.Plasticity as AdaptationThe ProblemConsider the Olympic hopeful with two performance passions: to be a great sumo wrestler and to be a great pole-vaulter. He has an obvious problem. He needs a large body mass to increase performance in sumo, but large mass is a liability for pole vaulting. Where performance in one environment is inversely related to performance in another, a func-tional trade-off exists. Assuming that performance translates into fitness (Arnold 1992), then the functional trade-off creates divergent natural selection. The theoretical maxi-mum fitness under divergent natural selection is achieved only by expressing the best phenotype in each environment (i.e., “perfect plasticity”). That is, there has to be per-fect phenotype–environment matching for greatest adaptive value. Perfect plasticity is an insuperable strategy. Obviously, such perfection is never actually achieved in nature when the phenotypes diverge greatly. Yet a critical issue in plasticity studies is to de-fine this maximum—to know what the best phenotype is in each environment. Know-ing the functional ecology of an organism, we can adequately assess the degree to which an organism increases its fitness by facultative adjustments to the environment. Once the functional ecology and reaction norms are defined, we can think about the constraints that prevent perfection. Typically, however, this functional approach only proceeds about halfway, as detailed below.8PHENOTYPIC PLASTICITYThe Benefits of PlasticityThe role of phenotypic plasticity in adapting to natural environments has been the focus of considerable work for decades. However, despite the large volume of work in this field (see figure 13.1), adaptive plasticity has not often been documented thoroughly (Scheiner 1993a; Gotthard and Nylin 1995)—but see chapters 8 and 9 for several ex-amples. This problem persists because proof of adaptive plasticity requires analysis of fitness in multiple environments.Consider the following example: Dodson (1988) showed that several cladoceran zooplankton (Daphnia spp.) produce small bodies when raised with fish, and that small size reduced predation risk in the presence of fish. Is the plasticity in body size adaptive plasticity? Probably. However, all that the preceding information tells us about adapta-tion is that small body size is favored in the presence of fish. We cannot make conclu-sions on the adaptive value of plasticity without further information. Three alternatives come to mind:1.Perhaps small size is also favored in the absence of fish. In this case, nonplasticindividuals strictly canalized for small bodies in all environments are more fit thanare plastic types.2.Perhaps there is no selection for body size in the absence of fish, but plasticity ex-hibits costs or limitations that make it a less suitable strategy than always produc-ing small bodies. In this case, less plasticity might be the optimal strategy.3.Perhaps plasticity in antipredator behavior is what is really adaptive, but perform-ing the behaviors results in a correlated response in body size (DeWitt 1998). Inthis scenario, genotypes that are behaviorally responsive to predators survive bet-ter and their small body is merely a by-product.Therefore, to show adaptive plasticity in the face of the first alternative, we have to show the induced phenotype to be adaptive in each environment being considered. Said another way, one must show that the canalized phenotype is inferior in the alternative environment. Examples of one-sided functional ecology are common, where authors demonstrate increased fitness of the induced character state in the inducing environ-ment without testing for higher fitness of the alterative phenotype in other environments (e.g., Appleton and Palmer 1988; Dodson 1989; Parejko and Dodson 1991). Despite this rather stringent litmus test for demonstrating adaptive value, however, the cost of an induced defense is often easy to imagine, and so most cases of one-sided functional ecology are reasonably informative about adaptation. That said, documenting the abso-lute adaptive value of plasticity requires documentation of functional trade-offs, not merely selection within single environments.As for alternative 2, we should be mindful of constraints and actively seek them out. The topic of costs of plasticity recently has been in vogue (reviewed in DeWitt et al. 1998). The current tests for costs (e.g., DeWitt 1998; Scheiner and Berrigan 1998; Donohue et al. 2000; Agrawal 2002; Johansson 2002; Relyea 2002) indicate that costs are certainly not pervasive, and probably are rare.Thus, the major constraint on the evolution of plasticity likely involves limits: logis-tic constraints that prevent the evolution of perfect plasticity. Obviously, lack of ge-netic variation for plasticity may be an important constraint. Yet almost all studies find at least some genetic variation for plasticity (Scheiner 1993a). Other limits are prob-ably more important, at least in the long term. Cue reliability is probably extremelyPHENOTYPIC VARIATION FROM SINGLE GENOTYPES9 important. In the freshwater snails mentioned above, for example, a severe constraint is that the snails cannot tell predatory sunfish from nonpredatory sunfish (Langerhans and DeWitt 2002). The snails therefore end up responding inappropriately to nonpredatory fish. The responses (reduced growth and altered shell shape) are maladaptive because they make snails vulnerable to common alternative predators and limit fecundity. So, research emphases need to shift to include as much (or more) work on limits as is cur-rently being directed to costs.The third alternative, correlations among traits masking the true object of selection, illustrates a topic rarely addressed in plasticity studies. For more general studies of natural selection, this issue was brought to the fore 20 years ago (Lande and Arnold 1983). Recent advances show how these methods can be applied to trait plasticities (Scheiner and Callahan 1999; Scheiner et al. 2000, 2002b). We must consider the entirety of the or-ganism in order to determine patterns of selection and parse functional adaptations.Concluding RemarksA central accomplishment of the Modern Synthesis (Provine 1971) has been the gain of a deep understanding about how natural selection shapes phenotypes. Up to now, that understanding has been confined almost entirely to fixed traits or traits in only a single environment. We are now ready to achieve a similar deep understanding divergent natural selection and the evolution of trait plasticity. To achieve this understanding, we need to understand the nature of plasticity, its evolution, and its effects on diversification. We need to know more about the mechanistic underpinnings of plasticity (chapters 3–5). We need to understand how plasticity is optimized and integrated with other strategies for dealing with variable environments (chapters 6 and 7). We need comprehensive (i.e., two-sided) studies of functional ecology, and we need to address constraints more often than has been common (chapters 9 and 10). We need to define the relevant trait space of plasticity (chapters 8 and 11). Finally, we need to discern how plasticity participates in evolutionary diversification at levels above populations (chapter 12).Central to all these aspirations is not only that we expand among topics studied un-der the rubric of plasticity, but also that we integrate them. Our goals for this book are to present a diverse collection of ideas that embrace the breadth of concepts surround-ing plasticity and to provide a pathway toward that integration.。