鸡6个功能基因microRNA靶标区域SNP的生物信息学预测

GDF-8、IGF-I,IGF-III、IGF2R、,IGFBP2和GHR是鸡的重要经济性状候选基因.利用miRanda和Targetscan软件预测6个基因3'UTR潜在的microRNA靶标,并发掘靶标区域SNP位点.结果表明:在6个基因的26个microRNA靶标区域,共检测到125个SNP位点,在靶标及其5'和3'邻接等长侧翼区分别检测到47个,44个和35个SNPs位点,其中12个SNP定位于靶标种子序列互补区.种子序列互补区及其3'侧翼区的SNP位点可能会影响microRNA的调控,导致家禽的表型变异.     

鸡基因组pre-microRNA SNP多态性

为探讨鸡pre-microRNA SNP的多态性及其可能的功能意义, 对鸡471个pre-microRNA区域的SNP位点进行了鉴定和生物信息学分析。结果表明: pre-microRNA的SNP多态性显著地低于其侧翼区(P＜0.01＝, 其种子区SNP变异对pre-microRNA二级结构稳定性的影响高于其他各区; microRNA成熟体SNP可能影响microRNA对靶基因的选择。研究结果提示: pre-microRNA相对于其侧翼区在分子进化过程中受到更大的选择压力; 成熟体SNP可通过影响microRNA加工和靶基因的选择, 改变多种生理过程, 导致鸡种间表型变异。研究结果将为鸡microRNA的进化模式研究及其功能性SNP的鉴定提供参考信息。     

鸡8个功能基因5′-侧翼区与内含子的SNP多样性比较

本研究旨在探讨鸡功能基因5′-侧翼区的单核苷酸多态性(SNP)水平。作者以白来航鸡、隐性白洛克鸡、杏花鸡、丝羽乌骨鸡、固始鸡、红色原鸡为材料,扩增了GH、DDBC1、RIKEN、RASGRP3、IGF1、THRSP、VIP及PRL共8个基因的5′-侧翼区DNA序列。扩增序列全长为8,399bp,SNP的总数为161个,平均每52bp出现一个SNP。8个功能基因5′-侧翼区核苷酸多样性的θ均值和π均值分别为0.00620±0.00110和0.00559±0.00100。比较检验表明,5′-侧翼区的SNP多样性显著低于内含子区域。5′-侧翼区是基因表达的一个重要调控区域,在分子进化和系统发生过程中承受着比内含子区域更大的选择压,其较低的SNP多样性是适应性较好的表现。Tajima检验与Fu和Li检验表明,与鸡繁殖性状显著关联的VIP基因和PRL基因很可能是人工选择或自然选择的目的基因。     

藏鸡诱导型一氧化氮合酶基因低氧适应功能分析

低氧刺激诱导型一氧化氮合酶(Inducible nitric-oxide synthase, iNOS)催化产生NO, 增加血流, 改善组织供氧。文章采用测序和PCR-RFLP技术检测藏鸡及低地鸡iNOS基因编码区、5′侧翼区(2.0 kb片段)序列和3′侧翼序列SNP, 并测定低氧和常氧孵化时鸡胚尿囊绒毛膜组织iNOS基因表达量和酶活力。结果在iNOS基因 5′侧翼区发现一个与低氧适应相关的藏鸡高频率突变SNP位点(-870C→T), 藏鸡该突变的等位基因T频率高于低地鸡种。藏鸡iNOS基因表达量和酶活力在低氧孵化环境中多高于矮小鸡。结果表明藏鸡群体iNOS基因的突变及其低氧表达量的增加是其适应低氧环境的重要基础。     

Cloning of IGF2b 5'Flanking Region and Methylation Analysis of Its GC-rich Sequence in Common Carp (Cyprinus carpio)

鲤(Cyprinus carpio)胰岛素样生长因子2b(insulin-like growth factor 2b,IGF2b)基因为鲤IGF基因家族重要的成员,已有的研究表明5’侧翼区序列对其功能的发挥有重要作用.因此,采用基因组步移法获取5′侧翼区序列,通过亚硫酸盐修饰的方法分析不同品种该区域GC富集区的甲基化状况.本文成功从鲤基因组DNA中获得695 bp的IGF2b 5'侧翼区序列.已获取的IGF2b 5'侧翼区序列经过TFSEARCH分析后发现了多个转录因子结合位点和TATA框,通过BLAST比对发现,鲤IGF2b 5'侧翼区DNA序列与斑马鱼( Danio rerio) IGF2b基因相比,相似性为87％.检测该区域富含GC的序列17个位点,发现建鲤(C.c.var.jian)有2个个体的3个位点出现甲基化,而黄河鲤(C.c.haematopterus)只有1个个体1个位点出现甲基化,这说明2个品种鲤在这个区域出现甲基化修饰的几率低,也验证了这2品种在该基因该区域GC富集区是稳定的.     

已建株鼻咽癌细胞的PLUNC基因启动子区序列多态性分析

目的检测人类标准鼻咽癌细胞中是否存在已知的PLUNC基因启动子-437bp-＋87bp区域的单核苷酸多态性（SNP）。以便进一步探索SNP与鼻咽癌的关系。方法采用PCR产物直接测序的方法,对7株体外培养的鼻咽癌细胞基因组DNA的PLUNC基因启动子区进行序列分析。结果发现7株PLUNC基因的启动子区皆存在已知的3个SNP位点（1888、2128和N2）和未知一个突变位点（N1）,其测观杂合度分别为85．7％、100％、100％和28．6％。其中3个已知SNP位点在筛查的细胞株中均存在T-C的突变,而且SUNE-1鼻咽癌细胞株的1888位点基因型为突变纯合子CC型。结论体外培养的标准鼻咽癌细胞株中存在已知的3个SNP位点（1888、2128和N2）的突变现象,且突变率为100％;1888位点鼻咽癌易患型（CC型）已在体外稳定建株;首次发现启动子-195bp区域N1突变位点。     

鸡8个功能基因5'-侧翼区与内含子的 SNP多样性比较

本研究旨在探讨鸡功能基因5'-侧翼区的单核苷酸多态性(SNP)水平.作者以自来航鸡、隐性白洛克鸡、杏花鸡、丝羽乌骨鸡、固始鸡、红色原鸡为材料,扩增了GH、DDBC1、RIKEN、RASGRP3、IGF1、THRSP、VIP及PRL共8个基因的5'-侧翼区DNA序列.扩增序列全长为8,399 bp,SNP的总数为161个,平均每52 bp出现一个SNP.8个功能基因5'-侧翼区核苷酸多样性的θ均值和π均值分别为0.00620±0.00110和0.00559±0.00100.比较检验表明,5'-侧翼区的SNP多样性显著低于内含子区域.5'-侧翼区是基因表达的一个重要调控区域,在分子进化和系统发生过程中承受着比内含子区域更大的选择压,其较低的SNP多样性是适应性较好的表现.Tajima检验与Fu和Li检验表明,与鸡繁殖性状显著关联的VIP基因和PRL基因很可能是人工选择或自然选择的目的基因.     

山羊MyoD基因家族多态性及与体尺性状的相关性

用PCR-SSCP技术研究了波尔山羊和徐淮山羊2个群体共147个个体MyoD基因家族中3个基因座位的单核苷酸多态性(single nucleotide polymorphism, SNP)。结果表明, 在徐淮白山羊群体中, myf-5基因座发现有3种基因型AA、AB和BB, 波尔山羊均为AA型。在myf-6基因座和myoD 5′侧翼区基因座, 两个山羊群体均检测到了AA和AB型个体。对山羊myf-5、myf-6基因座, myoD 5′侧翼区基因座不同基因型与两品种山羊体尺性状相关分析表明, myf-5基因座对管围和管围指数的效应差异显著(P<0.05)。myf-6基因座对徐淮白山羊体尺性状的效应均不显著(P>0.05), 而对波尔山羊的体高和管围指数效应差异显著(P<0.05)。两个山羊品种myoD 5′侧翼区不同基因型个体的体尺性状差异均不显著。     

甘南牦牛(Bos grunniens)FBXO32基因突变及其与胴体和肉质性状关联分析

为了分析甘南牦牛(Bos grunniens)肌肉萎缩盒蛋白32(F-box protein 32,FBXO32)基因的单核苷酸多态性(single nucleotide polymorphism, SNP)位点,以及基因型与胴体和肉质性状间的相关性,本研究以593头甘南牦牛为研究对象,采用混池测序和竞争性等位基因特异性PCR(kompetitive allele specific PCR, KASP)技术,检测了甘南牦牛FBXO32基因突变位点及基因型,分析了基因型与甘南牦牛胴体及肉质性状的相关性。结果表明,从甘南牦牛FBXO32基因检测到7个SNP位点,分别是位于5′UTR区的SNP1(g.267A>C)、外显子1区的SNP2(g.326G>T)、外显子8区的SNP3(g.31231G>C),以及3′UTR区的SNP4(g.31352G>A)、 SNP5(g.31424C>T)、 SNP6(g.31503A>C)和SNP7(g.31504A>G)。其中,SNP1、 SNP4、 SNP5、 SNP6与肌肉嫩度显著相关(P<0.05), ...     

奶牛乳铁蛋白基因5′侧翼区PCR-SSCP多态性分析

采用PCR-SSCP技术,对奶牛乳铁蛋白基因5′侧翼区1122bp序列进行多态性分析.在该区所划分的5个亚片段上,发现Blf 5′-1(227bp),Blf 5′-3(175bp)和Blf 5′-5(293bp)3个DNA片段存在多态.进一步对这3个片段进行测序分析,在Blf 5′-1序列中,发现位于转录起始位点上游-926和-915位分别有G→A及T→G点突变;在Blf 5′-3片段中,-478位存在G的插入;Blf 5′-5位点上,发生-28位的C颠换为A和 33位的G颠换为C两处突变.利用TFSEARCH (ver.1.3)软件对乳铁蛋白基因5′侧翼区潜在调控元件及蛋白质结合位点进行了预测,结果显示5′侧翼区的突变引起了蛋白质结合因子的变化.     

A genome-wide association study of seed protein and oil content in soybean

Background

Association analysis is an alternative to conventional family-based methods to detect the location of gene(s) or quantitative trait loci (QTL) and provides relatively high resolution in terms of defining the genome position of a gene or QTL. Seed protein and oil concentration are quantitative traits which are determined by the interaction among many genes with small to moderate genetic effects and their interaction with the environment. In this study, a genome-wide association study (GWAS) was performed to identify quantitative trait loci (QTL) controlling seed protein and oil concentration in 298 soybean germplasm accessions exhibiting a wide range of seed protein and oil content.

Results

A total of 55,159 single nucleotide polymorphisms (SNPs) were genotyped using various methods including Illumina Infinium and GoldenGate assays and 31,954 markers with minor allele frequency >0.10 were used to estimate linkage disequilibrium (LD) in heterochromatic and euchromatic regions. In euchromatic regions, the mean LD (r ² ) rapidly declined to 0.2 within 360 Kbp, whereas the mean LD declined to 0.2 at 9,600 Kbp in heterochromatic regions. The GWAS results identified 40 SNPs in 17 different genomic regions significantly associated with seed protein. Of these, the five SNPs with the highest associations and seven adjacent SNPs were located in the 27.6-30.0 Mbp region of Gm20. A major seed protein QTL has been previously mapped to the same location and potential candidate genes have recently been identified in this region. The GWAS results also detected 25 SNPs in 13 different genomic regions associated with seed oil. Of these markers, seven SNPs had a significant association with both protein and oil.

Conclusions

This research indicated that GWAS not only identified most of the previously reported QTL controlling seed protein and oil, but also resulted in narrower genomic regions than the regions reported as containing these QTL. The narrower GWAS-defined genome regions will allow more precise marker-assisted allele selection and will expedite positional cloning of the causal gene(s).     

Comparative genetic analysis of a wheat seed dormancy QTL with rice and <Emphasis Type="Italic">Brachypodium</Emphasis> identifies candidate genes for ABA perception and calcium signaling

Wheat preharvest sprouting (PHS) occurs when seed germinates on the plant before harvest resulting in reduced grain quality. In wheat, PHS susceptibility is correlated with low levels of seed dormancy. A previous mapping of quantitative trait loci (QTL) revealed a major PHS/seed dormancy QTL, QPhs.cnl-2B.1, located on wheat chromosome 2B. A comparative genetic study with the related grass species rice (Oryza sativa L.) and Brachypodium distachyon at the homologous region to the QPhs.cnl-2B.1 interval was used to identify the candidate genes for marker development and subsequent fine mapping. Expressed sequence tags and a comparative mapping were used to design 278 primer pairs, of which 22 produced polymorphic amplicons that mapped to the group 2 chromosomes. Fourteen mapped to chromosome 2B, and ten were located in the QTL interval. A comparative analysis revealed good macrocollinearity between the PHS interval and 3 million base pair (mb) region on rice chromosomes 7 and 3, and a 2.7-mb region on Brachypodium Bd1. The comparative intervals in rice were found to contain three previously identified rice seed dormancy QTL. Further analyses of the interval in rice identified genes that are known to play a role in seed dormancy, including a homologue for the putative Arabidopsis ABA receptor ABAR/GUN5. Additional candidate genes involved in calcium signaling were identified and were placed in a functional protein association network that includes additional proteins critical for ABA signaling and germination. This study provides promising candidate genes for seed dormancy in both wheat and rice as well as excellent molecular markers for further comparative and fine mapping.     

Genetic polymorphisms and microRNAs: new direction in molecular epidemiology of solid cancer

MicroRNAs (miRNAs) are small non-coding RNAs, which regulate gene expression. Single nucleotide polymorphisms (SNPs) may occur in miRNA biogenesis pathway genes, primary miRNA, pre-miRNA or a mature miRNA sequence. Such polymorphisms may be functional with respect to biogenesis and actions of mature miRNA. Specific SNPs were identified in predicted miRNA target sites within 3' untranslated regions of mRNAs. These SNPs have a potential to affect the efficiency of miRNA binding to the target sites or can create or disrupt binding sites. Resulting gene dysregulation may involve changes in phenotype and may eventually prove critical for the susceptibility to cancer and its onset as well as for estimates of prognosis and therapy response. In this review, we provide a comprehensive list of potentially functional miRNA-related SNPs and summarize their importance as candidate cancer biomarkers.     

Genome-wide association study for candidate genes controlling seed yield and its components in rapeseed (Brassica napus subsp. napus)

Genetic improvement of seed yield per plant (SY) is one of the major objectives in Brassica napus breeding programme. SY, being a complex quantitative trait is directly and indirectly influenced by yield-component traits such as siliqua length (SL), number of seeds per siliqua (NSS), and thousand seed weight (TSW). Therefore, concurrent improvement in SL, NSS and TSW can lead to higher SY in B. napus. This study was conducted to identify significant SNPs and putative candidate genes governing SY and its component traits (SL, NSS, TSW). All these traits were evaluated in a diverse set of 200 genotypes representing diversity from wide geographical locations. Of these, a set of 125 genotypes were chosen based on pedigree diversity and multi-location trait variation for genotyping by sequencing (GBS). Best linear unbiased predictors (BLUPs) of all the traits were used for genome-wide association study (GWAS) with 85,126 SNPs obtained from GBS. A total of 16, 18, 27 and 18 SNPs were found to be significantly associated for SL, NSS, TSW and SY respectively. Based on linkage disequilibrium decay analysis, 150 kb genomic region flanking the SNP was used for the identification of underlying candidate genes for each test trait. Important candidate genes involved in phytohormone signaling (WAT1, OSR1, ARR8, CKX1, REM7, REM9, BG1) and seed storage proteins (Cruciferin) were found to have significant influence on seed weight and yield. Genes involved in sexual reproduction and fertilization (PERK7, PERK13, PRK3, GATA15, NFD6) were found to determine the number of seeds per siliqua. Several genes found in this study namely ATS3A, CKX1, SPL2, SPL6, SPL9, WAT1 showed pleiotropic effect with yield component traits. Significant SNPs and putative candidate genes identified for SL, NSS, TSW and SY could be used in marker-assisted breeding for improvement of crop yield in B. napus. Genotypes identified with high SL, NSS, TSW and SY could serve as donors in crop improvement programs in B. napus.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12298-021-01060-9.