单细胞微生物基因组学研究

本文介绍了单细胞微生物基因组测序 ,全基因组序列的注释 ,以及基因组进一步研究的主要内容     

Faba bean breeding for resistance against biotic stresses: Towards application of marker technology

Summary Faba beans are adversely affected by numerous fungal diseases leading to a steady reduction in the cultivated area in many countries. Major diseases such as Ascochyta blight (Ascochyta fabae), rust (Uromyces viciae-fabae), chocolate spot (Botrytis fabae), downy mildew (Peornospora viciae) and foot rots (Fusarium spp.) are considered to be the major constraints to the crop. Importantly, broomrape (Orobanche crenata), a very aggressive parasitic angiosperm, is the most damaging and widespread enemy along the Mediterranean basin and Northern Africa. Recent mapping studies have allowed the identification of genes and QTLs controlling resistance to some of these diseases. In case of broomrape, 3 QTLs explained more than 70% of the phenotypic variance of the trait. Concerning Ascochyta, two QTLs located in chromosomes 2 and 3 explained 45% of variation. A second population sharing the susceptible parental line also revealed two QTLs, one of them likely sharing chromosomal location and jointly contributing with a similar percentage of the total phenotypic variance. Finally, several RAPD markers linked to a gene determining hypersensitive resistance to race 1 of the rust fungus U. viciae-fabae have also been reported. The aim of this paper is to review the state of the art of gene technology for genetic improvement of faba bean against several important biotic stresses. Special emphasis is given on the application of marker technology, and Quantitative Trait Loci (QTL) analysis for Marker-Assisted Selection (MAS) in the species. Finally, the potential use of genomic tools to facilitate breeding in the species is discussed. The combined approach should expedite the future development of lines and cultivars with multiple disease resistance, one of the top priorities in faba bean research programs.     

Chickpea molecular breeding: New tools and concepts

Summary Chickpea is a cool season grain legume of exceptionally high nutritive value and most versatile food use. It is mostly grown under rain fed conditions in arid and semi-arid areas around the world. Despite growing demand and high yield potential, chickpea yield is unstable and productivity is stagnant at unacceptably low levels. Major yield increases could be achieved by development and use of cultivars that resist/tolerate abiotic and biotic stresses. In recent years the wide use of early maturing cultivars that escape drought stress led to significant increases in chickpea productivity. In the Mediterranean region, yield could be increased by shifting the sowing date from spring to winter. However, this is hampered by the sensitivity of the crop to low temperatures and the fungal pathogen Ascochyta rabiei. Drought, pod borer (Helicoverpa spp.) and the fungus Fusarium oxysporum additionally reduce harvests there and in other parts of the world. Tolerance to rising salinity will be a future advantage in many regions. Therefore, chickpea breeding focuses on increasing yield by pyramiding genes for resistance/tolerance to the fungi, to pod borer, salinity, cold and drought into elite germplasm. Progress in breeding necessitates a better understanding of the genetics underlying these traits. Marker-assisted selection (MAS) would allow a better targeting of the desired genes. Genetic mapping in chickpea, for a long time hampered by the little variability in chickpea’s genome, is today facilitated by highly polymorphic, co-dominant microsatellite-based markers. Their application for the genetic mapping of traits led to inter-laboratory comparable maps. This paper reviews the current situation of chickpea genome mapping, tagging of genes for ascochyta blight, fusarium wilt resistance and other traits, and requirements for MAS. Conventional breeding strategies to tolerate/avoid drought and chilling effects at flowering time, essential for changing from spring to winter sowing, are described. Recent approaches and future prospects for functional genomics of chickpea are discussed.     

Assessing single-nucleotide polymorphism selection methods for the development of a low-density panel optimized for imputation in South African Drakensberger beef cattle

A major obstacle in applying genomic selection (GS) to uniquely adapted local breeds in less-developed countries has been the cost of genotyping at high densities of single-nucleotide polymorphisms (SNP). Cost reduction can be achieved by imputing genotypes from lower to higher densities. Locally adapted breeds tend to be admixed and exhibit a high degree of genomic heterogeneity thus necessitating the optimization of SNP selection for downstream imputation. The aim of this study was to quantify the achievable imputation accuracy for a sample of 1,135 South African (SA) Drakensberger cattle using several custom-derived lower-density panels varying in both SNP density and how the SNP were selected. From a pool of 120,608 genotyped SNP, subsets of SNP were chosen (1) at random, (2) with even genomic dispersion, (3) by maximizing the mean minor allele frequency (MAF), (4) using a combined score of MAF and linkage disequilibrium (LD), (5) using a partitioning-around-medoids (PAM) algorithm, and finally (6) using a hierarchical LD-based clustering algorithm. Imputation accuracy to higher density improved as SNP density increased; animal-wise imputation accuracy defined as the within-animal correlation between the imputed and actual alleles ranged from 0.625 to 0.990 when 2,500 randomly selected SNP were chosen vs. a range of 0.918 to 0.999 when 50,000 randomly selected SNP were used. At a panel density of 10,000 SNP, the mean (standard deviation) animal-wise allele concordance rate was 0.976 (0.018) vs. 0.982 (0.014) when the worst (i.e., random) as opposed to the best (i.e., combination of MAF and LD) SNP selection strategy was employed. A difference of 0.071 units was observed between the mean correlation-based accuracy of imputed SNP categorized as low (0.01 < MAF ≤ 0.1) vs. high MAF (0.4 < MAF ≤ 0.5). Greater mean imputation accuracy was achieved for SNP located on autosomal extremes when these regions were populated with more SNP. The presented results suggested that genotype imputation can be a practical cost-saving strategy for indigenous breeds such as the SA Drakensberger. Based on the results, a genotyping panel consisting of ~10,000 SNP selected based on a combination of MAF and LD would suffice in achieving a <3% imputation error rate for a breed characterized by genomic admixture on the condition that these SNP are selected based on breed-specific selection criteria.     

南瓜矮生基因Bu的比较定位

 以中国南瓜矮生突变体为供体亲本,以印度蔓生南瓜为轮回亲本,构建了BC6F2分离群体。利用黄瓜基因组序列,将南瓜矮生基因Bu比较定位至黄瓜5号染色体,并开发了一个新的PCR标记IF3629,该标记与矮生基因Bu连锁遗传距离为1.0 cM。该标记不仅可以用于分子标记辅助选择育种,而且为Bu基因的克隆奠定了基础。     

基于选择消除分析挖掘豌豆耐冻相关基因

近年来，冬季的低温对豌豆生产造成严重损失。本试验对16 份极端耐冻豌豆和14 份极端冷敏感豌豆的全基因组重测序数据与参考基因组进行比对获得SNP，再基于过滤后的SNP 数据对所有材料进行系统发育树构建、主成分分析、连锁不平衡分析以及选择消除分析等，并依据选择消除分析的群体多样性（θπ）、杂合率（Hp）和群体分化（Fst）三者交集的前5%候选区域，最终筛选获得34 个与豌豆耐冻相关的基因。研究结果为豌豆耐冻品种选育和“冬豆北移”栽培模式提供理论支撑。     

主要蔬菜作物基因组含量统计与比较分析

 基因组含量又称基因组大小或DNA 1C值,是指物种配子染色体组所含DNA的量。基因组含量是比较和进化基因组学研究的基础。为掌握蔬菜基因组含量变化规律,利用植物DNA 1C值数据库和相关文献收集整理了主要蔬菜作物的基因组含量信息,通过统计比较分析得到以下主要结论：（1）流式细胞术（Flow Cytometry,FC）是测定蔬菜基因组含量的最佳方法;（2）睡莲科的莲藕（Nelumbo nucifera）是目前已知的基因组含量最小（0.24 pg）的蔬菜,石蒜科的自然四倍体藠头（Allium chinense）基因组含量最大（32.75 pg）;（3）主要蔬菜种类中,石蒜科（19.08 pg）蔬菜平均基因组含量最高,十字花科（0.78 pg）和葫芦科（0.78 pg）蔬菜最低;（4）多年生和单子叶蔬菜平均基因组含量分别极显著高于非多年生蔬菜和双子叶蔬菜。     

Genomic Sequence and Experimental Tractability of a New Decapod Shrimp Model,Neocaridina denticulata

The speciose Crustacea is the largest subphylum of arthropods on the planet after the Insecta. To date, however, the only publically available sequenced crustacean genome is that of the water flea, Daphnia pulex, a member of the Branchiopoda. While Daphnia is a well-established ecotoxicological model, previous study showed that one-third of genes contained in its genome are lineage-specific and could not be identified in any other metazoan genomes. To better understand the genomic evolution of crustaceans and arthropods, we have sequenced the genome of a novel shrimp model, Neocaridina denticulata, and tested its experimental malleability. A library of 170-bp nominal fragment size was constructed from DNA of a starved single adult and sequenced using the Illumina HiSeq2000 platform. Core eukaryotic genes, the mitochondrial genome, developmental patterning genes (such as Hox) and microRNA processing pathway genes are all present in this animal, suggesting it has not undergone massive genomic loss. Comparison with the published genome of Daphnia pulex has allowed us to reveal 3750 genes that are indeed specific to the lineage containing malacostracans and branchiopods, rather than Daphnia-specific (E-value: 10⁻⁶). We also show the experimental tractability of N. denticulata, which, together with the genomic resources presented here, make it an ideal model for a wide range of further aquacultural, developmental, ecotoxicological, food safety, genetic, hormonal, physiological and reproductive research, allowing better understanding of the evolution of crustaceans and other arthropods.     

基于BLAST与比较基因组学方法计算鉴定青鳉鱼的microRNA前体

microRNA（miRNA）是一类长度为18～25 nt的单链小分子RNA。它可以调控基因的表达调控。通过与目标mRNA的特定位点的结合,从而抑制蛋白质的翻译或诱导该mRNA的降解。目前鱼类miRNA方面以斑马鱼miRNA的研究较多。为发掘另一种鱼类模式生物——青鳉鱼（Oryzias latipes,medeka）的miRNA,利用BLAST同源搜索方法与比较基因组学方法,并根据成熟miRNA的序列保守性以及miRNA前体（premiRNA）的二级结构的特征,对该模式生物的pre-miRNA进行了计算鉴定与分析。通过与miRBase19中已经发布的miRNA进行比较,在青鳉鱼基因组中共找到了56条新序列。设定miRNA基因间距的阈值为5000nt,新发现的与已知的pre-miRNA共形成31个基因簇。同时,这56条新发现的pre-miRNA可以划分到33个已知的基因家族中,并分析了新发现的、保守miRNA的靶标与功能。     

奶牛乳房炎相关基因的功能基因组学研究进展

功能基因组学是在基因组水平上系统、全面的分析基因的功能,主要研究技术有差异显示反转录PCR、表达序列标签、基因表达系列分析、微阵列、RNA干涉、蛋白质组学及生物信息学等。综述了功能基因组学主要研究技术及其在奶牛乳房炎相关基因的表达、抗性候选基因的鉴定、病原菌蛋白质组学、基因治疗等方面的应用研究进展。