遗传学(第3版)(3)
(NEW)刘祖洞《遗传学》(第3版)配套题库【考研真题精选+章节题库】
目 录第一部分 考研真题精选一、选择题二、填空题三、判断题四、名词解释五、问答题第二部分 章节题库第一章 绪论第二章 孟德尔定律第三章 遗传的染色体学说第四章 孟德尔遗传的拓展第五章 遗传的分子基础第六章 性别决定与伴性遗传第七章 连锁交换与连锁分析第八章 细菌和噬菌体的重组和连锁第九章 数量性状遗传第十、十一章 遗传物质的改变第十二章 重组与修复第十三章 细胞质和遗传第十四章 基因组第十五章 基因表达与基因表达调控第十六章 遗传与个体发育第十七章 遗传和进化第一部分 考研真题精选一、选择题1以下哪种性染色体-常染色体套数，会出现雄性果蝇（ ）。
[中山大学2019研]A．XX：AAB．XXY：AAC．XXXA：AAAD．X：AA【答案】D【解析】果蝇的性别由X染色体数目与常染色体组数之比决定，与Y无关。
X：A的比值≥1时发育为雌性，≤0.5发育为雄性。
ABC三项错误，X：A的比值等于1，出现雌性果蝇。
D项，X：A的比值小于1，出现雄性果蝇。
2基因型为aaBbCcDd个体自交后代中，出现aaBbccDd的概率是（ ）。
[湖南农业大学2018研]A．1/4B．1/8C．1/16D．1/32【答案】CaaBbCcDd个体自交，将各基因分开考虑，后代aa的概率为1，【解析】Bb的概率为1/2，cc的概率为1/4，Dd的概率为1/2，因此出现aaBbccDd 的概率为1×1/2×1/4×1/2＝1/16。
3对于拟南芥短径突变，己分离到纯合的品系并获得短径与长径的个体数目分别为62与38，则该突变的外显率为（ ）。
[中山大学2019研]A．0.62B．0.38C．0.613D．0.387【答案】A外显率＝62/（62＋38）＝0.62。
【解析】4细胞减数分裂终变期能产生四体环的是（ ）。
[沈阳农业大学2011研]A．易位纯合体B．易位杂合体C．四分体D．四合体【答案】B易位杂合体是两条非同源染色体间互换片段，另外两条不发生【解析】互换，从而形成十字形结构的四体环。
医学遗传学(第3版)
非编码RNA通过调控基因表达参与多 种生物过程，其异常表达与多种疾病 的发生发展有关，如microRNA与癌 症的关系。
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表观遗传学在疾病诊断和治疗中的应用前景
表观遗传学在疾病诊断中的应用
通过分析特定表观遗传标记，可以实现疾病的早期诊断和预后评估，如利用DNA甲基
化谱对癌症进行分型和预测。
19世纪末至20世纪初，医学遗传学处于萌芽阶段，主要关 注一些明显的遗传性状和单基因遗传病。
中期医学遗传学
20世纪中期，随着DNA双螺旋结构的发现和遗传学理论 的不断完善，医学遗传学开始关注多基因遗传病和染色体 异常等领域。
现代医学遗传学
20世纪末至今，随着人类基因组计划的完成和高通量测序 技术的发展，医学遗传学进入了基因组医学时代，实现了 从单一遗传病研究向复杂疾病研究的转变。
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线粒体DNA的突变与疾病关系
线粒体DNA突变的类型
线粒体DNA突变包括点突变、缺失、插入和重复等类型，其中点突变是最常见的突变类型。
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线粒体DNA突变与疾病的关系
线粒体DNA突变可导致多种疾病，如线粒体肌病、线粒体脑肌病、Leber遗传性视神经病变等。这些疾病通常具有母 系遗传的特点，且病情严重程度与突变类型及比例有关。
治疗手段
对症治疗、康复训练、心理支持等。 对于部分染色体异常遗传病，如唐氏 综合征和威廉姆斯综合征等，目前尚 无根治方法，但通过对症治疗、康复 训练和心理支持等手段，可以改善患 者的生活质量。同时，对于高危人群 进行遗传咨询和产前诊断是预防染色 体异常遗传病的有效措施。
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线粒体遗传与疾病
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遗传学(第3版) 刘祖洞、乔守怡、吴燕华、 赵寿元 高等教育出版社 (2013-01)课后习题答案6
Chapter 6 Circulating Methylated DNA as Biomarkers for Cancer DetectionHongchuan Jin, Yanning Ma, Qi Shen andXian WangAdditional information is available at the end of the chapter/10.5772/514191. IntroductionIn addition to genetic alterations including deletion or point mutations, epigenetic changes such as DNA methylation play an important role in silencing tumor suppressor genes dur‐ing cancer development. By adding a methyl group from S-adenosyl-L-methionine to the cy‐tosine pyrimidine or adenine purine ring, DNA methylation is important to maintain genome structure and regulate gene expression. In mammalian adult tissues, DNA methyla‐tion occurs in CpG dinucleotides that often cluster in the genome as CpG islands in the 5’regulatory regions of the genes. Through recruiting transcriptional co-repressors including methyl-CpG-binding domain proteins (MBDs) and chromatin remodeling proteins like his‐tone deacetylases (HDACs) or impeding the binding of transcriptional activators, DNA methylation could suppress the transcription of many tumor suppressor genes critical to cancer initiation and progression [1-3].More and more results confirmed that cancer is a multi-stage process fuelled by many epige‐netic changes in addition to genetic changes in DNA sequence [4]. Chemical molecules like Trichostatin A (TSA) and 5-aza-2'-deoxycytidine (5-Aza-CdR) targeting epigenetic regula‐tors such as histone modifications and DNMTs (DNA methyltransferases) have been found to inhibit tumor growth both in vitro and in vivo. By reversing the epigenetic silencing of important tumor suppressor genes, an increasing number of epigenetic drugs such as 5-Aza-CdR, 5-Aza-CR and Vorinostat (SAHA) are currently investigated in the clinical trials for cancer treatment as a single drug or in combination with other epigenetic drugs or other ap‐proaches such as chemotherapy and showed very promising activities by offering signifi‐cant clinical benefits to cancer patients [5-13].© 2013 Jin et al.; licensee InTech. This is an open access article distributed under the terms of the CreativeCommons Attribution License (/licenses/by/3.0), which permits unrestricted use,distribution, and reproduction in any medium, provided the original work is properly cited.As one of the major epigenetic changes to inactivate tumor suppressor genes critical to hu‐man cancer development, DNA methylation was recognized as the biomarker for cancer de‐tection or outcome prediction in addition to the identification of novel tumor suppressor genes. DNA mutations will occur randomly in any nucleotides of one particular gene and the comprehensive determination of DNA mutations is thus very difficult and time-consum‐ing. In contrast, aberrant DNA hypermethylation usually takes place in defined CpG Islands within the regulatory region of the genes and it is much more convenient to detect DNA methylation in a quantitatively manner. In addition, DNA methylation can be amplified and is thus easily detectable using PCR-based approaches even when the DNA concentration af‐ter sample extraction is relatively low. Due to such advantages over DNA mutation- or pro‐tein-based biomarkers, DNA methylation-based biomarkers have been intensively investigated in the recent years. A large body of research reports has proved the value of DNA methylations in the prognosis prediction and detection of various cancers. DNAs used for such methylation analyses are usually extracted from tumor tissues harvested after sur‐gical operation or biopsy, thus limiting its wide application as the biomarkers for the early detection or screening of human cancers. Recently, it has been reported that there are certain amount of circulating DNAs in the peripheral blood of cancer patients, providing an ideal source to identify novel biomarkers for non-invasive detection of cancers. Both genetic and epigenetic changes found in the genomic DNAs extracted from primary tumor cells could be detected in the circulating DNAs, indicating that the detection of methylated DNAs in the circulation represents a new direction to develop novel biomarkers for cancer detection or screening in a non-invasive manner.2. Cell free DNA in the circulationAccording to the origin of circulating tumor-related DNA, it could be grouped into circulat‐ing cell free DNA or DNA from cells in the blood such as circulating tumor cells (CTC) in cancer patients (Figure 1).In 1869, the Australian physician Thomas Ashworth observed CTCs in the blood of a cancer patient. Therefore, it was postulated that CTCs were responsible for the tumor metastases in distal sites and should have important prognostic and therapeutic implications [14-16].However, the number of CTCs is very small compared with blood cells. Usually around 1-10CTCs together with several million blood cells could be found in 1 ml of whole blood, mak‐ing the specific and sensitive detection of CTCs very difficult [17-18]. Until recently, technol‐ogies with the requisite sensitivity and reproducibility for CTC detection have been developed to precisely analyze its biological and clinical relevance. The US Food and Drug Administration (FDA) approved the test for determining CTC levels in patients with meta‐static breast cancer in 2004. Currently, it has been expanded to other cancer types such as advanced colorectal cancer and prostate cancer. Although CTCs-counting based test have proven its value in predicting prognosis and monitoring therapeutic effects, the number of CTCs per ml of blood limited its sensitivity greatly [19]. With the development of high-sen‐sitive PCR-based methods, the detection of gene mutations or epigenetic changes such asMethylation - From DNA, RNA and Histones to Diseases and Treatment138DNA methylation within small amount of CTCs could be the next generation of CTC-based test for cancer detection. However, the cost of such tests will be greatly exacerbated, thuslimiting its wide application in the clinic [20-22].Figure 1. Circulating tumor cells and cell free DNA. Circulating Tumor cells (CTC) escape from primary sites and spread into the vessel to form metastases in the distal organs with. Cell free DNAs (cf-DNAs) are released into the circulation from dead cancer cells or proliferating tumor cells. RBC: red blood cell; WBC: white blood cell.Although its origin and biological relevance remains unknown, circulating cell free DNA (cf-DNA) is supposed to be valuable source to identify cancer markers with ideal sensitivity and specificity for non-invasive detection of cancer [23-24]. Early in 1948, two French scientists Mandel and Metais firstly reported the presence of cf-DNAs in human plasma [25]. Such an important discovery has been unnoticed for a long time until cell-free circulating nucleic acid was found to promote the spread and metastasis of crown gall tumor in plants [26]. Subse‐quently, increased level of cf-DNAs was found in patients with various diseases such as lupus erythematosus and rheumatoid arthritis cancer [27-28]. In 1977, Leon et al. reported that higher level of circulating DNA in the plasma of cancer patients when compared to healthy con‐trols. Moreover, greater amounts of cf-DNA were found in the peripheral blood of cancer patients with tumor metastases and cf-DNA levels decreased dramatically after radiothera‐py while persistently high or increasing DNA concentrations were associated with a lack of response to treatment [29], clearly revealing the potential value of cf-DNA as biomarker for cancer detection. Following studies confirmed that cf-DNAs in the plasma contains genetic and epigenetic changes specific to DNAs within the tumor cells from primary tissues, indicat‐ing that tumor specific cf-DNAs are originated from tumor cells rather than lymphocytes reacting towards the disease [30-31]. For example, K-Ras mutation was found in cf-DNA from 17 out of 21 patients with pancreatic adenocarcinoma and mutations were similar in corre‐sponding plasma and tissues samples. Importantly, such DNA alterations were found inCirculating Methylated DNA as Biomarkers for Cancer Detection/10.5772/51419139patients with pancreatitis who were diagnosed as pancreatic cancer 5-14 months later, indi‐cating that release of tumor-specific DNA into the circulation is an early event in cancer development and cf-DNA could be used as the biomarkers for early cancer detection [32].Treatment resulted in disappearance of K-Ras mutations in plasma DNA in six of nine pa‐tients. Three patients with a persistently positive K-Ras gene mutation in plasma samples from patients before and after treatment showed early recurrence or progression and pancreatic carcinoma patients with the mutant-type K-ras gene in plasma DNA exhibited a shorter survival time than patients with the wild-type gene, indicating the cf-DNA could be of value in monitoring disease progression or evaluating treatment response [31, 33].Through quantitatively analyzing plasma DNAs from patients with organ transplantation,Lo et al found that the majority of plasma DNAs was released from the hematopoietic sys‐tem. However, donor DNA could be detected in the plasma of recipients suffering from the graft rejection because of the large amount of cell death which promotes the release of donor DNAs into the peripheral blood of the recipients [34]. Therefore, it was postulated that cell-free tumor related DNA could originate from the apoptotic tumor cells since high-rate of apoptosis indeed occurs in primary and metastatic tumor tissues. However, cf-DNA quanti‐ties are significantly reduced in cancer patients after radiotherapy when a great number of tumor cells were believed to undergo apoptotic cell death and cf-DNAs in supernatants of cultured cancer cells increases with cell proliferation rather than apoptosis or necrosis, indi‐cating that proliferating tumor cells could actively release cf-DNA into the tumor microen‐vironment and circulation.In contrast to labile RNAs that were included into the actively secreted exosomes, the nature of cf-DNAs remains to be clarified. As negatively charged molecules, cf-DNA was bound by plasma proteins to escape from endonuclease-mediated degradation. Unfortunately, plasma proteins bound to cf-DNAs was not well characterized yet. Meanwhile, secreted exosomes could remodel microenviroments and promote tumor metastasis since RNAs within exo‐somes especially microRNA with high stability may influence gene expression in neighbor cells. The biological relevance of cf-DNAs remains unknown. DNA was believed to be more structural rather than functional. However, it was supposed that cf-DNA could play a role as vaccine in tumor microenvironment.3. Methods for the detection of methylated DNAIt is unclear so far whether serum or plasma is better for cf-DNA extraction. Although the DNA amount is significantly higher in the serum, the majority of the increase was due to the release of nuclear acids from destroyed blood cells during blood clotting [35]. In addition,the time gap between blooding drawing and DNA extraction as well as the methodologies used for DNA isolation contribute greatly to the amount of cf-DNA harvested. On an aver‐age, around 30 ng cf-DNA could be extracted from one ml of blood sample [36]. Therefore,in order to determine the quantity of potential cf-DNA-based biomarkers precisely and pro‐mote its wide application for cancer detection, it is very important to unify the source asMethylation - From DNA, RNA and Histones to Diseases and Treatment140well as the methodologies for cf-DNA extraction and use various internal controls to adjustpossible inter-laboratory variations.Figure 2. Schematic introductions of various methods for methylation analyses. MSP, BGS and COBRA are based on bisulfite-mediated conversion of unmethylated cytosines into uracils. CpG methylation could block DNA digestion by some restriction enzymes, making it possible to determine methylation status independent of bisulfite treatment by analyzing digestion products. Alternatively, DNA fragments containing methylated CpG sites could be enriched by an‐ti-methylcytosine antibody or methylation binding proteins. Advances in next generation genome sequencing tech‐nology led to the development of noel techniques such as SMRT which can specially analyze 5-methylcytosines with genome wide coverage.In general, the detection of DNA methylation could be bisulfite-dependent or -independent (Figure 2).The chemical reaction of sodium bisulfite with DNA could convert unmethylated cytosine of CpG into uracil or UpG but leave methylated cytosine of CpG unchanged. The following analyses such as methylation-and unmethylation specific polymerase chain reaction (M- and U-SP), bisulfite genome sequencing (BGS) or combined bisulfite restriction analysis (CO‐BRA) could determine the conversion of CpG sites of interest, thus reflecting their methyla‐tion status as methylated or unmethylated [37]. With varied resolution levels, different bisulfite-dependent DNA methylation analysis methods detect the conversion after bisulfite treatment of genomic DNA, which could have certain artificial effects such as incomplete conversion of unmethylated CpG into UpG, leading to high rate of false negative conclusion of DNA methylation status.Recently, some new modifications of cytosine in CpG dinucleotides have been discovered such as 5-hydoxymethylcytosine which was called the sixth base since 5-methylcytosine was named as the fifth base [38]. Generated from the oxidation of 5-methylcytosine by the Tet family of enzymes, 5-hydoxymethylcytosine was first found in bacteriophages and recentlyCirculating Methylated DNA as Biomarkers for Cancer Detection/10.5772/51419141shown to be abundant in human and mouse brains as well as in embryonic stem cells [39-40]. Although the exact relevance of 5-hydoxymethylcytosine in the genome is still not fully clarified, it has been found to regulate gene expression or promote DNA demethyla‐tion. The in vitro synthesized artificial oligonucleotides containing 5-hydoxymethylcyto‐sines can be converted into unmodified cytosines when introduced into mammalian cells,indicating that 5-hydoxymethylcytosine might be one of intermediate products during ac‐tive DNA demethylation [41]. Therefore, the increase of 5-hydoxymethylcytosine might re‐flect the demethylation of CpG dinucleotides. Unfortunately, 5-hydoxymethylcytosines,similar to 5-methylcytosines, appear to be resistant to bisulfite-mediated conversion and PCR could amplify DNA fragments containing 5-hydoxymethylcytosines or 5-methylcyto‐sines with similar efficiency [42-43]. Therefore, bisulfite-dependent methylation analyses could produce false positive results by counting 5-hydoxymethylcytosines into 5-methylcy‐tosines. In addition to 5-hydroxymethylcytosines, some forms of DNA modifications such as the seventh base, 5-formylcytosine and the eighth base, 5-carboxylcytosine, have been found in mammalian cells recently [44-47]. As the products of 5-hydoxymethylcytosine oxidation through TET hydroxylases, both 5-formylcytosine and 5-carboxylcytosine will be read as the uracil after bisulfite conversion, thus making it impossible for bisulfite-dependent analyses to distinguish unmodified cytosines from 5-formylcytosines and 5-carboxylcytosines.Bisulfite independent analyses such as MedIP (methylated DNA immunoprecipitation)could more or less detect DNA methylation specifically. In bisulfite independent analyses, 5-methylcytosines are differentiated from unmethylated cytosine by either enzyme digestion or affinity enrichment. DNA methylation analysis using restriction enzyme digestion is based on the property of some methylation-sensitive and -resistant restriction enzymes such as HpaII and MspI that target CCGG for digestion. HpaII fails to cut it once the second cyto‐sine was methylated while MspI-mediated digestion is not affected by DNA methylation,thus making it possible to determine the methylation status of CpG in the context of CCGG tetranucleotides by analyzing the products of DNAs digested by HpaII and MspI respective‐ly. As a primary method to analyze DNA methylation, it can only determine the methyla‐tion of CpG in the context of CCGG tetranucleotides and will overlook the majority of CpG dinucleotides in the genome.The development of monoclonal antibody specific to 5-methylcytosines revolutionized the analyses of DNA methylation [48-49]. Immunoprecipitated DNA by this antibody could be subject to DNA microarray or even deep sequencing to reveal novel sequences or sites con‐taining 5-methylcytosines [50]. This antibody specifically recognizes 5-methylcytosines but not 5-hydoxymethylcytosines. However, 5-methylcytosines could present not only in CpG dinucleotides but also in CHH or CHG trinucleotides, especially in plants, human embryon‐ic stem cells and probably cancer cells as well. CHH methylation indicates a 5-methylcyto‐sine followed by two nucleotides that may not be guanine and CHG methylation refers to a 5-methylcytosine preceding an adenine, thymine or cytosine base followed by guanine. Such non-CpG DNA methylations were enriched at transposons and repetitive regions, although the exact biological relevance remains unknown. However, antibody against 5-methylcyto‐Methylation - From DNA, RNA and Histones to Diseases and Treatment142sine may precipitate methylated CHH and CHG trinucleotide containing DNA fragments in addition to DNA sequences with methylated CpG sites.DNA methylation functions as the signal for DNA-interacting proteins to maintain genome structure or regulate gene expression. The proteins such as MBD1 (methyl-CpG binding do‐main protein 1), MeCP2 (methyl CpG binding protein 2) and MBD4 (methyl-CpG binding domain protein 4) bind methylated CpG specifically to regulate gene expression [51-52].Therefore, methyl-CpG binding domain could specifically enrich differentially methylated regions (DMRs) of physiological relevance [53]. Similar to MeDIP, MBD capture specifically enrich methylated CpG sites rather than hydroxymethlated CpG sites. The detailed analysis to compare MeDIP and MBD capture revealed that both enrichment techniques are sensitive enough to identify DMRs in human cancer cells. However, MeDIP enriched more methylat‐ed regions with low CpG densities while MBD capture favors regions of high CpG densities and identifies the greater proportion of CpG islands [49].Recently, the advance of next generation sequencing led to the development of several novel techniques, making it possible to quantitatively analyze DNA methylation at single nucleo‐tide resolution with genome wide coverage. Both the single molecule real time sequencing technology (SMRT) and the single-molecule nanopore DNA sequencing platform could dis‐criminate 5-methylcytosines from other DNA bases including 5-hydroxymethylcytosines even methyladenine independent of bisulfite conversion [54-55]. With many advantages such as less bias during template preparation, lower cost and better accuracy, such new techniques could offer more methods to detect DNA methylation with high specificity and sensitivity in addition to more potential DNA methylation based biomarkers for cancer de‐tection and screening.4. Potential DNA methylation biomarkers for cancer detectionIt has been questioned whether the methylated DNA in the circulation is sensitive to detect cancers early enough for curative resection. However, the development of sensitive detection methods confirmed the potential value of DNA methylation in cancer detection (Table 1).Most of DNA methylation biomarkers are well-known tumor suppressor genes silenced in primary tumor tissues. However, the biomarks do not have to be functional relevant. For ex‐ample, currently well-used biomarkers such as AFP (Alpha-Fetal Protein), PSA (Prostate-specific antigen) and CEA (Carcinoembryonic antigen) are not tumor suppressor genes with important biological functions. Profiling of methylated DNA in the circulation instead of primary tumor tissues with MeDIP or MBD capture or other methylation specific analyses methods would identify more potential biomarks rather than functional important tumor suppressor genes.Circulating Methylated DNA as Biomarkers for Cancer Detection/10.5772/51419143Cancer Markers Sensitivity Specificity Methods Ref.Bladder cancer CDKN2A (ARF) CDKN2A(INK4A)CDKN2A (INK4A)13/27 (48%)2/27 (7%)19/86 (22%)N/AN/A31/31 (100%)MSPMSPMSP[58][59]Breast cancer CDKN2A (INK4A)CDKN2A (INK4A)5/35 (14%)6/43 (14%)N/AN/AMS-AP-PCRMS-AP-PCR[56][57]Colorectal cancerMLH1CDKN2A (INK4A) CDKN2A(INK4A) CDKN2A (INK4A)ALX4CDH4NGFRRUNX3SEPT9TMEFF23/18 (17%)14/52 (27%)13/94 (11%)21/58 (36%)25/30 (83%)32/46 (70%)68/133 (51%)11/17 (65%)92/133 (69%)87/133 (65%)N/A44/44 (100%)N/AN/A36/52 (70%)17/17 (100%)150/179 (84%)10/10 (100%)154/179 (86%)123/179 (69%)MSPMSPMSPMSPMSPMSPMSPMSPMSPMSP[60][61][62][63][64][65][66][67][66]Esophageal cancer APCAPCCDKN2A (INK4A)13/52 (25%)2/32 (6%)7/38 (18%)54/54 (100%)54/54 (100%)N/AMSPMSPMSP[68][69]Gastric cancer CDH1CDKN2A (INK4A)CDKN2B (INK4B)DAPK1GSTP1Panel of five 31/54 (57%)28/54 (52%)30/54 (56%)26/54 (48%)18/54 (15%)45/54 (83%)30/30 (100%)30/30 (100%)30/30 (100%)30/30 (100%)30/30 (100%)30/30 (100%)MSPMSPMSPMSPMSPMSP[70]Head and neck cancer CDKN2A (INK4A)DAPK1MGMTPanel of threeDAPK18/95 (8%)3/95 (3%)14/95 (15%)21/95 (22%)N/AN/AN/AN/AN/AN/AMSPMSPMSPMSPMSP[71][72]Liver cancer CDKN2A (INK4A) CDKN2B(INK4B)13/22 (45%)4/25 (16%)48/48 (100%)35/35 (100%)MSPMSP[73][74]Lung cancer CDKN2A (INK4A)DAPK1GSTP1MGMTPanel of fourCDKN2A (INK4A)APC 3/22 (14%)4/22 (18%)1/22 (5%)4/22 (18%)11/22 (50%)N/A42/89 (47%)N/AN/AN/AN/AN/AN/A50/50 (100%)MSPMSPMSPMSPMSPMSPMSP[75][76][77]Methylation - From DNA, RNA and Histones to Diseases and Treatment 144Cancer Markers Sensitivity Specificity Methods Ref.CDKN2A (INK4A)CDKN2A (INK4A)77/105 (73%)12/35 (34%)N/A15/15 (100%)MSP MSP [78][79]Prostate cancer GSTP1GSTP123/33 (70%)25/69 (36%)22/22 (100%)31/31 (100%)MSP MSP[80][81]Table 1. Methylated DNA biomarkers in the literature.Most of the methods used for methylation biomarkers analyses are still bisulfite dependent.Few reports used MS-AP-PCR (methylation-sensitive arbitrarily primed PCR) which takes the advantage of methylation sensitive restriction endonucleases to distinguish methylated CpG from unmethylated form, although the sensitivity seems to be lower than MSP [56-57].Interestingly, combination of more than one methylated DNA as a methylation panel could great increase the sensitivity for cancer detection without significant reduction of specificity.Unfortunately, most of studies were performed in a retrospective manner. More prospective studies with large sample sizes will be warranted to compare different approaches especial‐ly bisulfite-independent methods in addition to confirm the value of DNA methylation for cancer detection.5. Conclusion and PerspectivesWith the development of the next generation genome sequencing as well as single molecular PCR, it became possible to analyze trace amount of DNAs including circulating cell-free DNA. Circulating tumor cells have been proven its value in prognosis predication even ear‐ly detection of various cancers. The analyses of methylated DNAs in the circulating will be the next promising epigenetic biomarkers for cancer detection. As one of the intermediate products of DNA demethylation, 5-hydroxymethlcytosines are resistant to bisulfite conver‐sion. Therefore, it should be carefully to interpret the data of methylation analyses based on bisulfite treatment due to potentially high rate of false positive results. Although some me‐thylated DNAs were found to valuable as a single biomarker for cancer detection, more po‐tential DNA methylations will be found after the wide application of SMRT and other sequencing platforms with high speed, depth and accuracy. DNA methylation signatures in‐cluding a panel of methylated DNAs will show the potential in the early diagnosis or screening and prognosis or therapy response prediction of many cancers. In addition, such DNA methylation biomarkers could be more sensitive and specific for cancer detection when combined with well-used biochemical biomarkers. However, unified methods with gold standards will be warranted to promote the development and clinical application of DNA methylation biomarkers.Circulating Methylated DNA as Biomarkers for Cancer Detection/10.5772/51419145AcknowledgementsThis work was supported by the National Natural Science Foundation of China (81071963;81071652), Program for Innovative Research Team in Science and technology of Zhejiang Province (2010R50046) and Program for Qianjiang Scholarship in Zhejiang Province (2011R10061; 2011R10073).Author detailsHongchuan Jin, Yanning Ma, Qi Shen and Xian Wang **Address all correspondence to: wangx118@Department of Medical Oncology, Laboratory of Cancer Epigenetics, Biomedical Research Center, Sir Runrun Shaw Hospital, Zhejiang University, ChinaReferences[1]Jones, P. A., & Baylin, S. B. (2007). The epigenomics of cancer. Cell , 128, 683-692.[2]Jones, P. A., & Baylin, S. B. (2002). The fundamental role of epigenetic events in can‐cer. Nat Rev Genet , 3, 415-428.[3]Baylin, S. B., Esteller, M., Rountree, M. R., Bachman, K. E., Schuebel, K., & Herman, J.G. (2001). Aberrant patterns of DNA methylation, chromatin formation and gene ex‐pression in cancer. Hum Mol Genet , 10, 687-692.[4]Baylin, S. B., & Herman, J. G. (2000). DNA hypermethylation in tumorigenesis: epige‐netics joins genetics. Trends Genet , 16, 168-174.[5]Oki, Y., & Issa, J. P. (2006). Review: recent clinical trials in epigenetic therapy. Rev Re‐cent Clin Trials , 1, 169-182.[6]Kelly, T. K., De Carvalho, D. D., & Jones, P. A. (2010). Epigenetic modifications astherapeutic targets. Nat Biotechnol , 28, 1069-1078.[7]Ramalingam, S. S., Maitland, M. L., Frankel, P., Argiris, A. E., Koczywas, M., Gitlitz,B., Thomas, S., Espinoza-Delgado, I., Vokes, E. E, Gandara, D. R., & Belani,C. P.(2010). Carboplatin and Paclitaxel in combination with either vorinostat or placebo for first-line therapy of advanced non-small-cell lung cancer. J Clin Oncol , 28, 56-62.[8]Braiteh, F., Soriano, A. O., Garcia-Manero, G., Hong,D., Johnson, MM, Silva Lde, P.,Yang, H., Alexander, S., Wolff, J., & Kurzrock, R. (2008). Phase I study of epigenetic modulation with 5-azacytidine and valproic acid in patients with advanced cancers.Clin Cancer Res , 14, 6296-6301.Methylation - From DNA, RNA and Histones to Diseases and Treatment146/10.5772/51419 [9]Font, P. (2011). Azacitidine for the treatment of patients with acute myeloid leukemiawith 20%-30% blasts and multilineage dysplasia. Adv Ther, 3(28), 1-9.[10]Fu, S., Hu, W., Iyer, R., Kavanagh, J. J., Coleman, R. L., Levenback, C. F., Sood, A. K.,Wolf, J. K., Gershenson, D. M., Markman, M., Hennessy, B. T., Kurzrock, R., & Bast, R. C., Jr. (2011). Phase 1b-2a study to reverse platinum resistance through use of a hypomethylating agent, azacitidine, in patients with platinum-resistant or platinum-refractory epithelial ovarian cancer. Cancer, 117, 1661-1669.[11]Silverman, L. R., Fenaux, P., Mufti, G. J., Santini, V., Hellstrom-Lindberg, E., Gatter‐mann, N., Sanz, G., List, A. F., Gore, S. D., & Seymour, J. F. (2011). Continued azaciti‐dine therapy beyond time of first response improves quality of response in patients with higher-risk myelodysplastic syndromes. Cancer.[12]Sonpavde, G., Aparicio, A. M., Zhan, F., North, B., Delaune, R., Garbo, L. E., Rousey,S. R., Weinstein, R. E., Xiao, L., Boehm, K. A., Asmar, L., Fleming, M. T., Galsky, M.D., Berry, W. R., & Von Hoff, D. D. (2011). Azacitidine favorably modulates PSA ki‐netics correlating with plasma DNA LINE-1 hypomethylation in men with chemo‐naive castration-resistant prostate cancer. Urol Oncol, 29, 682-689.[13]Keating, G. M. (2012). Azacitidine: a review of its use in the management of myelo‐dysplastic syndromes/acute myeloid leukaemia. Drugs, 72, 1111-1136.[14]Alix-Panabieres, C., Schwarzenbach, H., & Pantel, K. (2012). Circulating tumor cellsand circulating tumor DNA. Annu Rev Med, 63, 199-215.[15]Zhe, X., Cher, M. L., & Bonfil, R. D. (2011). Circulating tumor cells: finding the needlein the haystack. Am J Cancer Res, 1, 740-751.[16]Fidler, I. J. (2003). The pathogenesis of cancer metastasis: the ‘seed and soil’ hypothe‐sis revisited. Nat Rev Cancer, 3, 453-458.[17]Ghossein, RA, Bhattacharya, S, & Rosai, J. (1999). Molecular detection of micrometa‐stases and circulating tumor cells in solid tumors. Clin Cancer Res, 5, 1950-1960. [18]Pelkey, TJ, Frierson, H. F., Jr, & Bruns, D. E. (1996). Molecular and immunological de‐tection of circulating tumor cells and micrometastases from solid tumors. Clin Chem, 42, 1369-1381.[19]Mocellin, S., Keilholz, U., Rossi, C. R., & Nitti, D. (2006). Circulating tumor cells: the‘leukemic phase’ of solid cancers. Trends Mol Med, 12, 130-139.[20]Chimonidou, M., Strati, A., Tzitzira, A., Sotiropoulou, G., Malamos, N., Georgoulias,V., & Lianidou, E. S. (2011). DNA methylation of tumor suppressor and metastasis suppressor genes in circulating tumor cells. Clin Chem, 57, 1169-1177.[21]Garcia-Olmo, D. C., Gutierrez-Gonzalez, L., Ruiz-Piqueras, R., Picazo, M. G., & Gar‐cia-Olmo, D. (2005). Detection of circulating tumor cells and of tumor DNA in plas‐ma during tumor progression in rats. Cancer Lett, 217, 115-123.。
医学遗传学第三版课件
随着技术的不断进步，医学遗传学将迎来更多的发展机遇和挑战，需要不断 探索和创新。
详细描述
未来，医学遗传学将更加注重疾病的早期诊断和预防，同时需要解决伦理和 法律问题，如基因编辑技
医学遗传学第三版课件
xx年xx月xx日
目录
• 医学遗传学概述 • 人类遗传的细胞与分子基础 • 人类遗传的群体与临床基础 • 医学遗传学的临床应用 • 医学遗传学前沿技术与发展趋势
01
医学遗传学概述
医学遗传学的定义与任务
医学遗传学的定义
医学遗传学是研究人类基因的结构、功能、变异与疾病关系 的科学。
03
医学遗传学研究有助于发现新的疾病基因和治疗靶点，为开发新药和治疗新技 术提供支持。
02
人类遗传的细胞与分子基础
人类细胞的基本结构与功能
细胞膜
维持细胞内外环境稳定，实现细胞与外部环境的 交流和物质交换。
细胞核
包含遗传物质DNA，控制细胞的生长、发育和代 谢。
细胞质
含有多种细胞器，如线粒体、内质网、高尔基体 等，参与蛋白质合成、能量代谢和物质转运等。
基因治疗与基因组编辑技术
基因治疗
利用基因工程技术将正常基因导入到患者细胞中，以纠正或 补偿因基因缺陷引起的疾病。
基因组编辑技术
通过CRISPR-Cas9等基因编辑技术，对人类基因组进行精确 的改造和修复，以治疗某些遗传性疾病。
人类基因组计划及其意义
人类基因组计划
一个旨在确定人类基因组序列的国际性科研项目，它的目标是识别和理解导 致人类健康和疾病的基因。
成熟阶段
进入21世纪，随着基因组学和生物信息学技术 的发展，医学遗传学在疾病预防、诊断和治疗 方面取得了重大突破。
《遗传学》(第3版)(答案合集)刘祖洞乔守怡吴燕华赵寿元
第二章1. 为什么分离现象比显、隐性现象更有重要意义？ 答案：分离现象反映了遗传现象的本质，而且广泛地存在于各生物中，也是孟德尔定律的基础。
显隐性现象是随条件、环境而改变，它不过是一种生理现象，因此从遗传学的角度来说，分离现象更有重要意义。
2. 在番茄中，红果色（R ）对黄果色（r ）是显性，问下列杂交可以产生哪些基因型，哪些表现型，它们的比例如何？（1）RR×rr （2）Rr×rr （3）Rr×Rr （4）Rr×RR （5）rr×rr 答案： (1) (2) (3) (4) (5)3. 下面是紫茉莉的几组杂交，基因型和表型已写明。
问它们产生杂种后代的基因型和表型怎样？（1）Rr×RR （2）rr×Rr （3）Rr×Rr 粉红 红色 白色 粉红 粉红 粉红 答案：(1) (2) (3)4. 在南瓜中，果实的白色（W ）对黄色（w ）是显性，果实盘状（D ）对球状（d ）是显性，这两对基因是自由组合的。
问下列杂交可以产生哪些基因型，哪些表型，它们的比例如何？（1）WWDD×wwdd （2）WwDd×wwdd （3）Wwdd×wwDd （4）Wwdd×WwDd 答案：(1) (2)(3)(4)5. 在豌豆中，蔓茎（T ）对矮茎（t ）是显性，绿豆荚（G ）对黄豆荚（g ）是显性，圆种子（R ）对皱种子（r ）是显性。
现在有下列两种杂交组合，问它们后代的表型如何？Rr 红 Rr rr 红 黄 1∶1 R R Rr rr 1 ∶2∶ 1 红 黄 3 ∶ 1RR Rr 1∶1 全部红 rr黄 RR ∶ Rr 红 粉红 1 ∶ 1 Rr ∶ rr 粉红 白 1 ∶ 1 RR ∶ Rr ∶ rr 红 粉红 白 1 ∶ 2 ∶ 1 WwDd wwDd Wwdd wwdd白盘 黄盘 白球 黄球 1 ∶ 1 ∶ 1 ∶ 1 WWDd WwDd WWdd Wwdd wwDd wwdd 1 ∶ 2 ∶ 1 ∶ 2 ∶ 1 ∶ 1 3(白盘) ∶ 3(白球) ∶1(黄盘)∶1(黄球) WwDd全部白盘WwDd Wwdd wwDd wwdd 白盘 白球 黄盘 黄球 1 ∶ 1 ∶ 1 ∶ 1（1）TTGgRr×ttGgrr （2）TtGgrr×ttGgrr 答案：(1)(2)6. 在番茄中，缺刻叶和马铃薯叶是一对相对性状，显性基因C 控制缺刻叶，基因型cc 是马铃薯叶。
遗传学第三版答案第3章遗传的染色体学说
第三章遗传的染色体学说1 有丝割裂和减数割裂的区别在哪里？从遗传学的角度来看，这两种割裂各有什么意义？那么，无性生殖会发生分离吗？试加以说明。
解：有丝割裂和减数割裂的区别：（1）有丝割裂是体细胞的割裂方式，而减数割裂一样仅存在于生殖细胞中。
（2）有丝割裂DNA复制一次,细胞割裂一次,染色体数由2n-2n，减数割裂DNA复制一次，细胞割裂两次，染色体数由2n-n。
（3）有丝割裂在S期进行DNA合成，然后通过G2期进入有丝割裂期。
减数割裂前DNA 合成时刻较长，合成后当即进入减数割裂，G2期很短或没有。
（4）有丝割裂时每一条染色体独立活动，减数割裂中染色体会发生配对、联会、交叉、互换等。
（5）有丝割裂进行的时刻较短,一样为1-2小时，减数割裂进行时刻长, 例如人的雄性配子减数割裂需24小时，雌配子乃至可长达数年。
有丝割裂的遗传学意义：通过有丝割裂维持了生物个体的正常生长和发育(组织及细胞间遗传组成的一致性)；而且保证了物种的持续性和稳固性(单细胞生物及无性繁衍生物个体间及世代间的遗传组成的一致性)。
减数割裂的遗传学意义：（1）通过减数割裂和受精进程中的染色体数量交替（2n－n－2n），保证了物种世代间染色体数量的稳固性。
（2）在减数割裂进程中，由于同源染色体分开，移向两极是随机的(染色体重组) ，加上同源染色体的互换(染色体片断重组) ，大大增加了配子的种类，从而增加了生物的变异，提高了生物的适应性，为生物的进展进化提供了物质基础。
无性生殖不通过两性生殖细胞的结合，而是由生物体自身的割裂生殖或其体细胞生长发育形成个体进程一样没有和其他个体或结构发生基因交流，自身也不发生减数割裂，因此在正常情形下可不能发生分离，但由于外界环境条件的阻碍通过无性生殖方式产生的个体也有可能会发生变异。
2 水稻正常的孢子体组织，染色体数量是12对，问以下各组织的染色体数量是多少？（1）胚乳；（2）花粉管的管核；（3）胚囊；（4）叶；（5）根端；（6）种子的胚；（7）颖片；解析：（1）胚乳3n＝36（2）花粉管的管核n＝12（3）胚囊8n＝96（4）叶2n＝24（5）根端2n＝24（6）种子的胚2n＝24（7）颖片2n＝243 用基因型Aabb的玉米花粉给基因型AaBb的玉米雌花授粉，你预期下一代胚乳的基因型是什么类型，比例如何？解析：基因型Aabb的花粉产生的雄配子Ab，ab基因型AaBb产生的极核为AB，Ab，aB和ab胚乳基因型为AAABBb，AAAbbb，AaaBBb，Aaabbb，AAaBBb，AAabbb，aaaBBb 和aaabbb，比例相等。
朱军遗传学(第三版)习题答案
学无止境朱军遗传学（第三版）习题答案第三章遗传物质的分子基础1.半保留复制：DNA分子的复制，首先是从它的一端氢键逐渐断开，当双螺旋的一端已拆开为两条单链时，各自可以作为模板，进行氢键的结合，在复制酶系统下，逐步连接起来，各自形成一条新的互补链，与原来的模板单链互相盘旋在一起，两条分开的单链恢复成DNA双分子链结构。
这样，随着DNA分子双螺旋的完全拆开，就逐渐形成了两个新的DNA分子，与原来的完全一样。
这种复制方式成为半保留复制。
冈崎片段：在DNA复制叉中，后随链上合成的DNA不连续小片段称为冈崎片段。
转录：由DNA为模板合成RNA的过程。
RNA的转录有三步：① RNA链的起始；② RNA链的延长；③ RNA链的终止及新链的释放。
翻译：以RNA为模版合成蛋白质的过程即称为遗传信息的翻译过程。
小核RNA：是真核生物转录后加工过程中RNA的剪接体的主要成分，属于一种小分子RNA，可与蛋白质结合构成核酸剪接体。
不均一核RNA：在真核生物中，转录形成的RNA中，含有大量非编码序列，大约只有25%RNA经加工成为mRNA，最后翻译为蛋白质。
因为这种未经加工的前体mRNA 在分子大小上差别很大，所以称为不均一核RNA。
遗传密码：是核酸中核苷酸序列指定蛋白质中氨基酸序列的一种方式，是由三个核苷酸组成的三联体密码。
密码子不能重复利用，无逗号间隔，存在简并现象，具有有序性和通用性，还包含起始密码子和终止密码子。
简并：一个氨基酸由一个以上的三联体密码所决定的现象。
多聚核糖体：一条mRNA分子可以同时结合多个核糖体，形成一串核糖体，成为多聚核糖体。
中心法则：蛋白质合成过程，也就是遗传信息从DNA-mRNA-蛋白质的转录和翻译的过程，以及遗传信息从DNA到DNA的复制过程，这就是生物学的中心法则。
2．答：DNA作为生物的主要遗传物质的间接证据：（1）每个物种不论其大小功能如何，其DNA含量是恒定的。
（2）DNA在代谢上比较稳定。
刘祖洞遗传学第3版配套题库和答案
刘祖洞遗传学第3版配套题库和答案
刘祖洞《遗传学》（第3版）配套题库【考研真题精选＋章节题库】
内容简介
本书是刘祖洞《遗传学》（第3版）教材的学习辅导题库，主要包括以下内容：第一部分为考研真题精选。
本部分精选了中山大学、中国科学院大学等高校近些年的遗传学考研真题，按照题型分类，所有题目都提供答案，大部分题目还提供解析。
通过本部分的学习，可以熟悉考研真题的命题风格和难易程度。
第二部分为章节题库。
结合国内多所知名院校的考研真题和考查重点，根据教材的章目进行编排，精选了典型习题，以供考生强化练习。
•
试看部分内容
•第一部分考研真题精选
•一、选择题
•二、填空题
•三、判断题
•四、名词解释
•五、简答题
•六、论述题
•七、计算与分析题
•第二部分章节题库
•第一章绪论
•第二章孟德尔定律
•第三章遗传的染色体学说
•第四章孟德尔遗传的拓展
•第五章遗传的分子基础
•第六章性别决定与伴性遗传
•第七章连锁交换与连锁分析
•第八章细菌和噬菌体的重组和连锁
•第九章数量性状遗传
•第十章遗传物质的改变（一）——染色体畸变•第十一章遗传物质的改变（二）——基因突变•第十二章重组与修复
•第十三章细胞质和遗传
•第十四章基因组
•第十五章基因表达与基因表达调控•第十六章遗传与个体发育
•第十七章遗传和进化。
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p2[AA]+2pq[Aa)+q2[aa]
子l代群体所产生的A 基因配子和a 基因配子的频率是： A=P2+1/2(2pq)=p2+pq=p(p+q)
a=q2+1/2(2pq)=q2+pq(p+q)
现在来分析子1 代群体婚配。子 1代群体和亲代群体一样有 3 种基因型。这3种基因型的个体在随机婚配的情况下互相婚配的 机会也可由概率乘法定理来推导，见下图。
要运用χ2检验方法。 【例】在我国某大城市随机抽样调查1788人的MN血型，其中397人 M型（LMLM）；861人MN型（LMLN）；530人是N型（LNLN）。请问该
3种基因型及其频率的分布是否符合Hardy-Weinberg平衡定律？
对于这类问题，首先需要从实际所收集的数据中计算LM基因频率（ p）和LN基因频率（q）（表19-2）。
男性群体与女性群体这3种基因型随机婚配共有6种不同的 婚配类型，由上图可写出这6种婚配类型的频率，见下表。 6种婚配类型及其频率
婚配类型 AA x AA AA x Aa Aa x Aa 频 率 婚配类型 AA x aa Aa x aa aa X aa 频 率
p4 2p3q+2p3q=4p3q 4p2q2
能力。
群体遗传学（population genetics）是应用数学和统计学方法研究群体 中的基因及其频率和可能的基因型及其频率以及影响这些频率的选择效应、
突变作用、迁移和遗传漂变作用与群体遗传组成（genetic composition）
的关系，探讨生物微（观）进化（microevolution）的机制。
中的基因型频率保持在上述平衡状态不会改变，这便是理想群体中基因
的遗传行为。
例：用两个等位基因说明Hardy-weinbery定律 雌配子频率 P（A） q(a) P(A) P2(AA) pq(Aa) 雄配子频率 q(a) pq(Aa) q2(aa) 由此可见这种随机婚配子代的基因型和它们的频率是：
q 0 .0001 0 .01
正常基因的频率: 1-0.01=0.99=P 因此,基因型AA的频率: p2=0.992=0.98 Aa为 2pq=2×0.99×0.01≈0.02
（2）伴性基因的遗传平衡
计算X－连锁座位上的基因频率较为复杂。在雌性纯合体中有两个 相同的x－连锁等位基因，而在雌性异合体中也只有一个特定的等位基因, 在所有雄性中只有一个X－连锁等位基因。为了在x－连锁座位上确定等
我们还可以应用 Hardy-Weinberg定律来估计杂合子的频率。
例：尿黑酸尿为常染色体隐性遗传病，约1 000 000儿童中有1个患儿， 其发病率 x=0．000001。 按 Hardy-Weinberg定律：
尿黑酸尿隐性基因频率：
q x 0 .000001英国数学家G.H.Hardy和德国医生W.Weinberg各自
独立地发现的，故称哈迪-温伯格定律（law of HardyWeinberg），亦称哈迪-温伯格平衡（Hardy-Weinberg
equilibrium）。
Hardy—Weinberg Law解释了繁殖如何影响群体的基因和基因型频 率。此定律是群体遗传学的重要理论基石，也是进化理论的基础。 Hardy-Weinberg定律的要点是： ① 在随机交（婚）配下的孟德尔群体中，若没有其他因素（基因突变 、选择、迁移和遗传漂变）的干扰，基因频率不变。 ② 无论群体的起始状况如何，常染色体上的一对等位基因的基因型频 率的平衡由下列二项式的展开式所决定：（pA+qa）2＝p2（AA）+2pq （Aa）+q2（aa），达到平衡的速度只需一个世代的随机交配。 ③ 如果随机交配系统得以保持（这是平衡定律最关键的假设），群体
19.2.2
平衡群体的特征及其应用
已经达到了Hardy-Weinberg平衡的群体，有5个基本 特征，了解平衡群体的性质，有助于运用于遗传咨询和群体 遗传分析（详见e19-1）。
19.2.3 χ2检验抽样群体中的基因型频率的平衡
判断某抽样群体中的基因型频率是否符合Hardy-Weinberg平衡，需
p2q2+p2q2=2p2q2 2pq3+2pq3=4pq3 q4
由此可见，在子2代群体中各种基因型的频率与子1代群体完全相同。我们可 以连续推算后代的基因型频率，结果都一致。所以就这对基因而言，在群体中处 于遗传平衡状态。群体中基因型的相对比例保持不变，都是p2+2pq+q2。这就是 Hardy-Weinberg平衡数学公式，即纯合基因型频率是基因频率的自乘，其系数 是1;杂合基因型的频率是两个有关基因频率的乘积，其系数是2。
（p＋q＋r）2 ＝ p2 ＋2pq＋2pr＋q2 ＋2qr＋r2
则认为这3个复等位基因的6种基因型频率的Hardy- Weinberg平衡 已经建立。 平衡状态下的基因频率可以由基因型频率按下列各式求得：
上述性质可以下列形式表示：
人类的ABO 血型是由复等位基IA ， IB 及i 决定的。设：基因IA 的
•
根据定义，依表19-1的资料分别计算基因型及基因频率：
或根据公式求得：
19.2 Hardy-Weinberg定律
19.2.1 Hardy-Weinberg定律的内容 “在一个大的随机交配的孟德尔群体内，基因型频率同
时在没有选择（ selection） 、没有突变（ mutation） 、
没有迁移（ migration）和遗传漂变（ genetic drift ）发生 的理想条件下，世代相传保持不变。” 此定律是在1908年
例3：AA＝0.25＝P2 p=0.5
( p+q)2= P2+q2+2pq=0.52+ 0.52+2×0.5×0.5＝0.25+0.25+0.5
如果一对等位基因有显性和隐性之分，杂合子的表现型与显性纯合子相同， 这时基因频率和杂合子频率的估计值可利用 Castle-Hardy-Weinberg 平衡的数学 公式得出。 设某一位点有等位基因D和d，纯合隐性基因型dd导致一种隐性遗传病。现在
群体遗传学是生物进化的重要的理论基础。
19.1 群体的遗传组成
19.1.1 孟德尔群体与基因库 （1）群体（population）:
享有一个共同的基因库，并能相互交配的一群个体。
（2）孟德尔式群体（Mendelian population）: 群体内的个体享有共同的基因库，能够相互交配，通过
有性生殖传递基因，可用孟德尔定律进行分析的群体。一个
遗 传 学 (第3版)
第19章 群体遗传与进化
1.群体的遗传组成 2.Hardy-Weinberg定律 3.影响群体遗传平衡的因素 4.自然群体中的遗传变异及其检测 5.物种及物种形成 6.中性突变与分子进化 7.新基因和蛋白质功能的起源 8.人类进化概述
达尔文进化学说有3个重要原则：第一，变异的原则：在任何一个群体 中的不同个体间都存在形态、生理和行为上的差异。第二，遗传的原则：后 代与其亲本的相似性大于与其无关个体的相似性。第三，选择的原则：在特 定的环境下，一些类型的个体总会比另一些类型的个体有更强的生存和繁殖
2 2 2 1)0.05＝3.841（表3-3）
（1.77＜ 3.841）
∴ P>0.05 （0．22 > p >0．10）差异不显著。
表明3种基因型频率符合Hardy-Weinberg平衡定律。 在此χ2检验过程中注意自由度的确定，因为在计算预期 频数时，要应用基因频率p，而它是以样本的实得数据中估 计得来的，因此χ2的自由度又减去1。
计算期望数： np2 = 1788 (0.4628)2 = 1788 0.2142 = 382.96 n2pq = 1788 2 0.4628 0.5372 = 889.05 nq2 = 1788 (0.5372)2 =1788 0.2886 = 515.99
计算得 χ2=1.77，根据自由度df=3-1-1=1，P = 0.05 查X 值表：df ＝1 , X( ∵ Xc <X20.05
2pq 2p 2 q2 q q
即杂合子频率是隐性纯合子患者频率的2／q倍。这意味着在隐性基因频率越来越 小时，杂合子频率对隐性纯合子频率的倍数越高。
例：白化病人具aa基因型，正常人为AA或Aa，假 定在某一群体中白化病人的频率为1/10000，按照 Hardy-weinbery law: 纯合体aa的频率为q2 q2=0.0001
频率为p，IB 基因频率为q，i 基因频率为r。在一个选择、突变、迁移等 因素不起作用的、随机婚配的群体中，ABO 血型及其频率的分布如下表 （表19－4） 。
平衡群体鉴定
• 1. 2. 3. AA 0.5 0.4 0.25
aa = 0.25=q2
Aa / 0.2 0.5
q=0.5
aa 是否平衡 0.5 0.4 0.25 +
最大的孟德尔群体就是一个物种。 （3） 基因库（gene pools）:
有性生殖生物的一个群体中，能进行生殖的所有个体所
携带的全部基因或遗传信息。
19.1.2 基因频率与基因型频率
群体中遗传着的基因及其频率以及可能的基因型及其频率构成了一
个特定群体的遗传组成。研究群体的遗传结构变化的机制是群体遗传学
位基因的数目，我们就得将雌性纯合体的数目乘2加上雌性杂合体数目和
雄性半合体数目然后除以群体中等位基因的总数。确定等位基因总数时 要用2倍的雌体数(因每个雌体都两个X－连锁基因座位)加上一倍的雄体 数(因雄体只有单个X－连锁基因座位)
例如：一对等位基因A、a在X染色体上遗传，在随机交配条件 下，下列情况被认为达到了Hardy-Weinberg平衡，以通常的符 号表示如下：
平衡群体中伴性基因频率的计算要从配子异型的性别入手。 人类的男性伴X基因的频率即为整个群体中该基因的频率。例如， 计算随机婚配人群中红绿色盲基因的频率，即可根据男性中红绿 色盲患者的调查数据来求。若发现色盲患者为7%，即表示qX＝qXX ＝0.07。则可预期有q2XX＝0.072＝0.49%的女性患色盲。这一数字 恰与女性群体中实际调查的发病率0.5%很接近。 运用平衡定律的理论可以作下列预见：对于隐性伴性性状而 言，男性发病率∶女性发病率＝q∶q2。对于伴X显性基因而言， 则有男性发病率∶女性发病率＝p∶（p2+2pq）＝1∶（1+q），可 见女性发病率略高于男性。