奶牛重要经济性状全基因组关联分析研究进展

产奶性状是奶牛最重要的生产性状, 随着平衡育种理念的提出和发展, 繁殖性状、体型性状、健康性状和长寿性等功能性状也逐渐被重视并纳入育种规划中。鉴定产奶性状和功能性状主效基因或遗传标记并将之应用于奶牛标记辅助选择可望加快遗传进展。随着高密度SNP标记的高通量检测技术的发展, 全基因组关联分析已成为鉴定畜禽重要经济性状基因的重要途径。文章对奶牛产奶性状和功能性状全基因组关联分析研究进展进行综述。     

羊重要性状全基因组关联分析研究进展

全基因组关联分析(genome-wide association study, GWAS)是一种复杂性状功能基因鉴定的分析策略,已成为挖掘畜禽重要经济性状候选基因的重要手段。随着绵羊和山羊基因组完成和公布,以及不同密度的SNP (single nucleotide polymorphism)芯片的推出并进行商业化推广,不仅大大丰富了羊标记辅助选择可利用的分子标记,而且还为开展重要性状的分子机理的探索提供了重要技术支撑。本文主要针对羊角、羊毛、羊奶、生长发育、肉质、繁殖和疾病等重要性状的GWAS研究所用的群体、主要研究方法和研究结果进行了综述,并对GWAS方法研究现状进行了归纳,以期为进一步利用GWAS进行羊的各种性状的遗传基础研究提供参考。     

京海黄鸡体重性状全基因组关联分析

体重性状是肉鸡重要的经济性状。为了寻找可用于京海黄鸡体重性状遗传改良的分子标记及候选基因,本文以400只京海黄鸡核心群母鸡为基础,测定了0~14周龄体重,利用简化基因组测序技术(Specific-locus amplified fragment sequencing, SLAF-seq)对京海黄鸡体重性状进行全基因组关联研究(Genome-wide association stndy, GWAS),筛选与京海黄鸡体重性状相关的SNPs位点。结果共检测到100个与京海黄鸡体重相关的SNPs位点,其中15个位点效应达到全基因组显著水平(P<1.87E-06),85个位点效应达到全基因组潜在显著水平(P<3.73E-05)。通过筛选每个显著SNP周围1 Mb区域内的基因,共找到9个可能的候选基因,其中FAM124A(Family with sequence similarity 124A)、QDPR(Quinoid dihydropteridine reductase)、WDR1(WD repeat domain 1)和SLC2A9(Solute carrier family 2 (facilitated glucose transporter), member 9) 4个基因可能是影响体重性状的重要候选基因。同时还发现,4号染色体75.6~80.7 Mb区域集中了大部分与京海黄鸡中后期体重性状显著相关的SNPs位点,该区域可能是影响京海黄鸡中后期生长体重的重要候选区域。     

干旱胁迫下小麦苗期根系性状的全基因组关联分析

研究小麦根系在干旱逆境下的形态特征和遗传机制是提升小麦抗旱能力并获得稳产的基础。本研究以300份国内外小麦品种（系）为材料,苗期采用PEG-6000模拟干旱胁迫对小麦根系的最长根长、根总长、根表面积、根体积、根平均直径、根尖数、根鲜重和根干重等8个性状进行表型鉴定,结合90K SNP芯片对8个性状的抗旱系数进行全基因组关联分析,并对稳定遗传的显著关联位点进行候选基因的挖掘。研究结果表明,干旱胁迫下小麦品种（系）的根系性状表现出丰富的表型变异,变异系数为0.17～0.58,全基因组多态信息量变异范围为0.01～0.38,LD衰减距离为7 Mb。群体结构分析表明,供试材料分为3个亚群。GWAS分析显示,共检测到与8个根系性状显著关联的41个SNP位点,单个遗传位点可解释3.91%～8.04%的表型变异。同时在两个及两个以上的性状中发现显著关联位点13个,其中Tdurum＿contig71499＿211(5A)、GENE-1743＿858(3B)、Tdurum＿contig28552＿211(5B)3个位点与4～5个性状显著关联,分别能解释遗传变异的4.12%～5.37%、5.77%～6.7...     

普通菜豆抗菜豆象性状的全基因组关联分析

普通菜豆(Phaseolus vulgaris)具有丰富的营养价值, 菜豆象(Acanthoscelides obtectus)是危害菜豆的主要害虫, 利用抗虫种质资源防治菜豆象是最安全且经济有效的方法。该研究利用改良的室内人工接虫方法, 对625份普通菜豆种质资源进行2次菜豆象抗性重复鉴定, 筛选出2份抗性稳定且种子受害率均在10%以下的高抗种质。利用种子受害率和蛀孔总数的表型数据, 基于3 767 432个SNP标记进行全基因组关联分析, 鉴定出15个与种子受害率相关的显著关联遗传位点, 8个与蛀孔总数相关的显著关联位点, 解释了4.54%-5.56%的表型变异。在候选位点筛选出包括编码蛋白酶抑制剂、凝集素和过氧化物酶等在内的20个与抗虫防御相关的候选基因。     

水稻苗期抗稻瘟病基因全基因组关联分析

含抗性基因的水稻品种易被病原菌克服,因此为进一步发掘新的稻瘟病抗性基因,利用水稻多样性群体II(RDP-II)中的470份种质资源,在湖南省桃江县稻瘟病高发区的自然病圃中进行水稻苗期的抗病性鉴定,并通过全基因组关联分析(GWAS)鉴定稻瘟病的抗性相关位点,最终鉴定出25份苗期抗性较好的品种,可作为抗性育种材料.采用混合...     

基于简化基因组测序的大黄鱼耐高温性状全基因组关联分析

利用Illumina HiSeqTM 2500测序平台, 对通过高温胁迫实验筛选得到的20尾耐高温和20尾不耐高温的大黄鱼(Larimichthys crocea)进行了简化基因组测序(SLAF-seq), 每个样本的平均测序深度达到10.26×, 共获得419211个高质量的群体单核苷酸多态性(SNP)位点 。利用TASSEL软件的混合线性模型(MLM)进行全基因组关联分析(GWAS), 共筛选到38个与大黄鱼耐高温性状显著相关的SNP位点(P<2.39E–08)。利用BLAST程序定位每个SNP位点在大黄鱼基因组中的位置, 并分析其周围的功能基因。结果在38个SNPs附近共找到26个已知的功能基因, 这些基因主要与细胞转录、代谢、免疫等功能相关。研究结果可为下一步大黄鱼耐高温分子机制解析及耐高温品种的选育提供参考。     

小麦耐低磷相关性状的全基因组关联分析

通过对小麦耐低磷相关性状进行全基因组关联分析(GWAS,genome-wide association study),挖掘与小麦耐低磷性显著相关的单核苷酸多态性标记(SNP,single nucleotide polymorphism)位点及候选基因,为小麦耐低磷性状的遗传基础和分子机制研究提供理论参考。本试验以198份黄淮麦区小麦品种(系)为试验材料,设置低磷和正常磷营养液水培试验,利用小麦35K芯片对分布于小麦全基因组的11896个SNP,采用Q+K关联模型对小麦耐低磷性相关性状进行关联分析。结果表明,小麦耐低磷性状表现出广泛的表型变异,变异系数为15.65%~26.59%,多态性信息含量(PIC,polymorphic information content)为0.095~0.500。群体结构分析表明,试验所用自然群体可分为2个亚群,GWAS共检测到67个与小麦耐低磷相关性状显著关联的SNP位点(P≤0.001),这些位点分布在除3A、3B和3D以外的18条染色体上,单个SNP位点可解释5.826%~9.552%的表型变异。在这些显著位点中有4个SNP位点同时关联到了2个不同的耐低磷性状。对67个SNP位点进行发掘,筛选到7个可能与小麦耐低磷性有关的候选基因。TraesCS6A02G001000和TraesCS6A02G001100在锌指合成中有重要作用;TraesCS6A02G118100可能为低磷胁迫诱导基因;TraesCS5D02G536400、TraesCS1B02G154200和TraesCS5D02G536500与低磷胁迫相关酶类基因家族有关;TraesCS1D02G231200与植物DUF 538结构域蛋白有关,是植物胁迫相关调控蛋白候选基因。     

胡萝卜抽薹相关性状全基因组关联分析

【目的】胡萝卜受低温及长日照的影响易发生先期抽薹现象,挖掘与胡萝卜抽薹性状相关联的SNP位点及候选基因,有利于胡萝卜耐抽薹新品种的选育。【方法】以240份胡萝卜种质资源为材料,分别在2021年及2022年调查胡萝卜抽薹(抽薹时间、抽薹率、薹高、抽薹速度)性状,基于质控得到的高质量SNP位点进行抽薹相关性状的GWAS分析。【结果】240份胡萝卜种质资源的抽薹性状具有丰富的遗传多样性,对2年的数据进行分析发现各性状表型均有较大的变异,抽薹率的变异系数最大为144.32%、187.89%,抽薹时间的变异系数同比最小为94.89%和74.63%,BLUE值降低了环境所带来的误差,其变异系数最小为22.53%。相关性分析结果表明,2021年抽薹率与2022年的抽薹性状呈显著正相关,与BLUE值为极显著相关,BLUE值除与2021年的抽薹时间无显著相关外,与其它性状均为极显著相关。GWAS分析共检测到与抽薹性状显著相关的344 个SNP 标记位点,其中有20个多效位点,根据注释信息筛选出29个与抽薹相关的候选基因,主要与光周期途径、春化途径和开花整合子有关。【结论】通过GWAS分析获得多个与抽薹性状相关联的SNP位点,并挖掘到相关候选基因。     

全基因组关联分析的进展与反思

全基因组关联分析(genomewide association study,GWAS)是应用人类基因组中数以百万计的单核苷酸多态性(single nucleotide polymorphism,SNP)为标记进行病例-对照关联分析,以期发现影响复杂性疾病发生的遗传特征的一种新策略。近年来,随着人类基因组计划和基因组单倍体图谱计划的实施,人们已通过GWAS方法发现并鉴定了大量与人类性状或复杂性疾病关联的遗传变异,为进一步了解控制人类复杂性疾病发生的遗传特征提供了重要的线索。然而,由于造成复杂性疾病/性状的因素较多,而且GWAS研究系统较为复杂,因此目前GWAS本身亦存在诸多的问题。本文将从研究方式、研究对象、遗传标记,以及统计分析等方面,探讨GWAS的研究现状以及存在的潜在问题,并展望GWAS今后的发展方向。     

A genome-wide association study of immune response traits in Canadian Holstein cattle

Background

Breeding for enhanced immune response (IR) has been suggested as a tool to improve inherent animal health. Dairy cows with superior antibody-mediated (AMIR) and cell-mediated immune responses (CMIR) have been demonstrated to have a lower occurrence of many diseases including mastitis. Adaptive immune response traits are heritable, and it is, therefore, possible to breed for improved IR, decreasing the occurrence of disease. The objective of this study was to perform genome-wide association studies to determine differences in genetic profiles among Holstein cows classified as High or Low for AMIR and CMIR. From a total of 680 cows with immune response phenotypes, 163 cows for AMIR (81 High and 82 Low) and 140 for CMIR (75 High and 65 Low) were selectively genotyped using the Illumina Bovine SNP50 BeadChip. Results were validated using an unrelated population of 164 Holstein bulls IR phenotyped for AMIR and 146 for CMIR.

Results

A generalized quasi likelihood score method was used to determine single nucleotide polymorphisms (SNP) and chromosomal regions associated with immune response. After applying a 5% chromosomal false discovery rate, 186 SNPs were significantly associated with AMIR. The majority (93%) of significant markers were on chromosome 23, with a similar peak found in the bull population. For CMIR, 21 SNP markers remained significant. Candidate genes within 250,000 base pairs of significant SNPs were identified to determine biological pathways associated with AMIR and CMIR. Various pathways were identified, including the antigen processing and presentation pathway, important in host defense. Candidate genes included those within the bovine Major Histocompatability Complex such as BoLA-DQ, BoLA-DR and the non-classical BoLA-NC1 for AMIR and BoLA-DQ for CMIR, the complement system including C2 and C4 for AMIR and C1q for CMIR, and cytokines including IL-17A, IL17F for AMIR and IL-17RA for CMIR and tumor necrosis factor for both AMIR and CMIR. Additional genes associated with CMIR included galectins 1, 2 and 3, BCL2 and β-defensin.

Conclusions

The significant genetic variation associated with AMIR and CMIR in this study may imply feasibility to include immune response in genomic breeding indices as an approach to improve inherent animal health.     

原发性高血压全基因组关联研究进展

原发性高血压是一种由遗传与环境因素共同导致的复杂疾病,具有高度的遗传异质性。自2007年首个高血压全基因组关联研究(Genome-wide association studies,GWAS)报道以来,许多GWAS相继开展。文章首先对2007年1月至2011年9月期间报道的24篇血压/高血压易感基因的GWAS按人种与染色体位置对其结果进行汇总,经统计位点rs17249754、rs1378942和rs11191548报道频数最多。其次介绍了GWAS方法学的研究进展,包括选择高质量的数量表型和选择多阶段研究设计来增加研究发现阳性关联的机会。统计分析方面,除强调了已经报道过的多重比较和重复(验证)研究等问题外,文章还介绍了通过Meta分析对GWAS数据进行深度发掘,并应用基因型填补法对缺失数据进行填补可以提高全基因组遗传标记的覆盖率的方法。尽管GWAS发现了许多我们未知的基因与疾病表型的关联,为了解高血压的发病机制提供了更多线索,但是目前GWAS发现的血压/高血压相关变异多为对人群血压的影响极其微弱的常见变异。因此今后的研究中可加强深度功能学研究对易感基因精细定位和外显子组测序技术的应用,结合GWAS的成果进行生物信息学通路分析和表观遗传学机制研究等,逐步揭示高血压的遗传机制。     

Genome-wide associations for investigating time-dependent genetic effects for milk production traits in dairy cattle

Phenotypic variation in milk production traits has been described over the course of a lactation as well as between different parities. The objective of this study was to investigate whether variation in production is affected by different loci across lactations. A genome-wide association study (GWAS) using a 50-k SNP chip was conducted in 152 divergent German Holstein Friesian cows to test for association with milk production traits over different lactations. The first four lactations were analysed regarding milk yield, fat, protein, lactose, milk urea nitrogen yield and content as well as somatic cell score. Two approaches were used: (i) Wilmink curve parameters were used to assess the genetic effects over the course of a lactation and (ii) test-day yield deviations (YD) were used as a normative approach for a GWAS. The significant effects were largest for markers affecting curve parameters for which there was a statistical power <0.8 of detection even in this small design. While significant markers for YDs were detected in this study, the power to detect effects of a similar magnitude was only 0.11, suggesting that many loci may have been missed with this approach in the present design. Furthermore, all significant effects were specific for a single lactation, leading to the conclusion that the variance explained by a certain locus changes from lactation to lactation. We confirm the common evidence that most production traits vary in the degree of persistency after the peak as a result of genetic influence.     

Casein haplotypes and their association with milk production traits in the Finnish Ayrshire cattle

Polymorphism of casein genes was studied in half-sib families of artificial insemination bulls of the Finnish Ayrshire dairy breed. Ten grandsires and 300 of their sons were genotyped for the following polymorphisms: α_S1-casein (B, C), β-casein (A¹, A²), the microsatellite within the K-casein gene (ms⁵, ms⁴) and K-casein (A, B, E). Nine different combinations of these alleles, casein haplotypes, were found. Associations between casein haplotypes and milk production traits (milk and protein yield, fat and protein percentage and milking speed) were studied with ordinary least-squares analysis to find a direct effect of the haplotypes or an association within individual grandsire families using the granddaughter design. Estimated breeding values of sons were obtained from cow evaluation by animal model. No direct effect of the casein haplotypes on the traits was found. Within grandsire families, in one out of four families the chromosomal segment characterized by haplotype 3 (B-A²-ms⁴-A) was associated with an increase in milk yield ( P <0.01) and a decrease in fat percentage ( P < 0.01) when contrasted with haplotype 8 (B-A¹-ms⁴-E). The results provide evidence that in the Finnish Ayrshire breed at least one quantitative trait locus affecting the genetic variation in yields traits is segregating linked to either haplotype 3 (B-A²-ms⁴-A) or 8 (B-A¹-ms⁴-E).     

Genome-wide association study reveals five nucleotide sequence variants for carcass traits in beef cattle

Genetic associations of nucleotide sequence variants with carcass traits in beef cattle were investigated using a genome-wide single nucleotide polymorphism (SNP) assay. Three hundred and thirteen Korean cattle were genotyped with the Illumina BovineSNP50 BeadChip, and 39,129 SNPs from 311 animals were analysed for each carcass phenotype after filtering by quality assurance. Five sequence markers were associated with one of the meat quantity or quality traits; rs109593638 on chromosome 3 with marbling score, rs109821175 on chromosome 11 and rs110862496 on chromosome 13 with backfat thickness (BFT), and rs110228023 on chromosome 6 and rs110201414 on chromosome 16 with eye muscle area (EMA) (P < 1.27 × 10(-6) , Bonferonni P < 0.05). The ss96319521 SNP, located within a gene with functions of muscle development, dishevelled homolog 1 (DVL1), would be a desirable candidate marker. Individuals with genotype CC at this gene appeared to have increased both EMA and carcass weight. Fine-mapping would be required to refine each of the five association signals shown in the current study for future application in marker-assisted selection for genetic improvement of beef quality and quantity.     

Analyzes of genome-wide association follow-up study for calving traits in dairy cattle

ABSTRACT: BACKGROUND: There is often a pronounced disagreement between results obtained from different genome-wide association studies in cattle. There are multiple reasons for this disagreement. Particularly the presence of false positives leads to a need to validate detected QTL before they are optimally incorporated or weighted in selection decisions or further studied for causal gene. In dairy cattle progeny testing scheme new data is routinely accumulated which can be used to validate previously discovered associations. However, the data is not an independent sample and the sample size may not be sufficient to have enough power to validate previous discoveries. Here we compared two strategies to validate previously detected QTL when new data is added from the same study population. We compare analyzing a combined dataset (COMB) including all data presently available to only analyzing a validation dataset (VAL) i.e. a new dataset not previously analyzed as an independent replication. Secondly, we confirm SNP detected in the Reference population (REF) (i.e. previously analyzed dataset consists of older bulls) in the VAL dataset. RESULTS: Clearly the results from the combined (COMB) dataset which had nearly twice the sample size of other two subsets allowed the detection of far more significant associations than the two smaller subsets. The number of significant SNPs in REF (older bulls) was about four times higher compare to VAL (younger bulls) though both had similar sample sizes, 2,219 and 2,039 respectively. A total of 424 SNP-trait combinations on 22 chromosomes showed genome-wide significant association involving 284 unique SNPs in the COMB dataset. In the REF data set 101 associations (73 unique SNPs) and in the VAL 24 associations (18 unique SNPs) were found genome-wide significant.Sixty-eight percent of the SNPs in the REF dataset could be confirmed in the VAL dataset. Out of 469 unique SNPs showing chromosome-wide significant association with calving traits in the REF dataset 321 could be confirmed in the VAL dataset at P < 0.05. CONCLUSIONS: The follow-up study for GWAS in cattle will depend on the aim of the study. If the aim is to discover novel QTL, analyses of the COMB dataset is recommended, while in case of identification of the causal mutation underlying a QTL, confirmation of the discovered SNPs are necessary to avoid following a false positive.     

Analyzes of genome-wide association follow-up study for calving traits in dairy cattle

Background

Genomic islands play an important role in medical, methylation and biological studies. To explore the region, we propose a CpG islands prediction analysis platform for genome sequence exploration (CpGPAP).

Results

CpGPAP is a web-based application that provides a user-friendly interface for predicting CpG islands in genome sequences or in user input sequences. The prediction algorithms supported in CpGPAP include complementary particle swarm optimization (CPSO), a complementary genetic algorithm (CGA) and other methods (CpGPlot, CpGProD and CpGIS) found in the literature. The CpGPAP platform is easy to use and has three main features (1) selection of the prediction algorithm; (2) graphic visualization of results; and (3) application of related tools and dataset downloads. These features allow the user to easily view CpG island results and download the relevant island data. CpGPAP is freely available at http://bio.kuas.edu.tw/CpGPAP/.

Conclusions

The platform's supported algorithms (CPSO and CGA) provide a higher sensitivity and a higher correlation coefficient when compared to CpGPlot, CpGProD, CpGIS, and CpGcluster over an entire chromosome.     

A genome-wide association study of direct gestation length in US Holstein and Italian Brown populations

Direct gestation length influences economically important traits in dairy cattle that are related to birth and peri-natal survival of the calf. The objective of this study was to identify single nucleotide polymorphisms (SNPs) that are significantly associated with direct gestation length through a genome-wide association study. Data used in the analysis included 7,308,194 cow gestation lengths from daughters of 4743 United States Holstein sires in the Cooperative Dairy DNA Repository population and 580,157 gestation lengths from 749 sires in the Italian Brown population. Association analysis included 36,768 and 35,082 SNPs spanning all autosomes for Holstein and Brown Swiss, respectively. Multiple shrinkage Bayesian was employed. Estimates of heritability for both populations were moderate, with values of 0.32 (±0.03) and 0.29 (±0.02) for Holstein and Brown Swiss, respectively. A panel of SNPs was identified, which included SNPs that have significant effects on direct gestation length, of which the strongest candidate region is located on chromosome 18. Two regions not previously linked to direct calving ease and calf survival were identified on chromosome 7 and 28, corresponding to regions that contain genes related to embryonic development and foetal development. SNPs were also identified in regions that have been previously mapped for calving difficulty and longevity. This study identifies target regions for the investigation of direct foetal effects, which are a significant factor in determining the ease of calving.