植物功能基因组研究进展

随着植物基因组计划的深入,植物基因组学研究的重点已经转变为基因组功能的研究,即利用基因组序列的信息和高通量的系统分析技术,在基因组水平研究植物结构和组织与植物功能在细胞、有机体和进化上的关系.对功能基因组学研究的内容、方法以及最新研究进展进行了综述.     

Quantitative Genetics Model as the Unifying Model for Defining Genomic Relationship and Inbreeding Coefficient

The traditional quantitative genetics model was used as the unifying approach to derive six existing and new definitions of genomic additive and dominance relationships. The theoretical differences of these definitions were in the assumptions of equal SNP effects (equivalent to across-SNP standardization), equal SNP variances (equivalent to within-SNP standardization), and expected or sample SNP additive and dominance variances. The six definitions of genomic additive and dominance relationships on average were consistent with the pedigree relationships, but had individual genomic specificity and large variations not observed from pedigree relationships. These large variations may allow finding least related genomes even within the same family for minimizing genomic relatedness among breeding individuals. The six definitions of genomic relationships generally had similar numerical results in genomic best linear unbiased predictions of additive effects (GBLUP) and similar genomic REML (GREML) estimates of additive heritability. Predicted SNP dominance effects and GREML estimates of dominance heritability were similar within definitions assuming equal SNP effects or within definitions assuming equal SNP variance, but had differences between these two groups of definitions. We proposed a new measure of genomic inbreeding coefficient based on parental genomic co-ancestry coefficient and genomic additive correlation as a genomic approach for predicting offspring inbreeding level. This genomic inbreeding coefficient had the highest correlation with pedigree inbreeding coefficient among the four methods evaluated for calculating genomic inbreeding coefficient in a Holstein sample and a swine sample.     

物种形成过程中的分化基因组岛及其形成机制

理解物种形成机制是生态和进化领域的重要任务。得益于测序技术的快速发展, 越来越多研究发现分化种群(亚种、物种)间的基因组常呈现异质性分化景观, 存在分化基因组岛, 这被认为是基因流存在下的歧化选择引起的, 支持基因流存在下的成种假说。然而, 基因渐渗、祖先多态性的差异分选、连锁选择等其他进化过程也可导致分化基因组岛的形成。现有实证研究在解析分化基因组岛的形成机制时, 往往忽略了上述其他进化过程的作用。为此, 本文在辨析分化基因组岛相关概念的基础上, 总结了利用种群基因组数据鉴定分化基因组岛的方法, 对比了不同进化过程形成分化基因组岛的特征, 指出在区分不同机制时联用基因渐渗程度、绝对分化指数(d_XY)、相对节点深度(RND)、重组率等多个指标的必要性, 归纳了物种形成过程中分化基因组岛形成机制解析的研究思路, 并对未来在生殖隔离机制上的深入探索以及实证研究的整合分析等方面进行了展望。     

家畜基因组选择研究进展

近年来,随着基因芯片技术的发展与育种技术的进步,动植物的基因组选择成为研究热点。在家畜育种中,基因组选择凭借其准确性高、世代间隔短和育种成本低等优势被应用于各种经济动物的种畜选择中。本文详细介绍了基因分型技术和基因组育种值估计方法(最小二乘法、RR-BLUP法、GBLUP法、ssGBLUP法、贝叶斯A法、贝叶斯B法等),并对这些育种方法选用的标记范围、准确性以及计算速度进行了比较,总结了我国和其他国家基因组选择在种畜选择中的应用情况及存在的问题,展望了目前国内外在基因组选择上的最新研究动态及进展,以期为其他育种工作者进一步了解基因组选择提供参考。     

Genomic differentiation and patterns of gene flow between two long‐tailed tit species (Aegithalos)

Patterns of heterogeneous genomic differentiation have been well documented between closely related species, with some highly differentiated genomic regions (“genomic differentiation islands”) spread throughout the genome. Differential levels of gene flow are proposed to account for this pattern, as genomic differentiation islands are suggested to be resistant to gene flow. Recent studies have also suggested that genomic differentiation islands could be explained by linked selection acting on genomic regions with low recombination rates. Here, we investigate genomic differentiation and gene‐flow patterns for autosomes using RAD‐seq data between two closely related species of long‐tailed tits (Aegithalos bonvaloti and A. fuliginosus) in both allopatric and contact zone populations. The results confirm recent or ongoing gene flow between these two species. However, there is little evidence that the genomic regions that were found to be highly differentiated between the contact zone populations are resistant to gene flow, suggesting that differential levels of gene flow is not the cause of the heterogeneous genomic differentiation. Linked selection may be the cause of genomic differentiation islands between the allopatric populations with no or very limited gene flow, but this could not account for the heterogeneous genomic differentiation between the contact zone populations, which show evidence of recent or ongoing gene flow.     

Selection of genomic sequences that bind tightly to Ff gene 5 protein: primer-free genomic SELEX

Single-stranded DNA or RNA libraries used in SELEX experiments usually include primer-annealing sequences for PCR amplification. In genomic SELEX, these fixed sequences may form base pairs with the central genomic fragments and interfere with the binding of target molecules to the genomic sequences. In this study, a method has been developed to circumvent these artificial effects. Primer-annealing sequences are removed from the genomic library before selection with the target protein and are then regenerated to allow amplification of the selected genomic fragments. A key step in the regeneration of primer-annealing sequences is to employ thermal cycles of hybridization-extension, using the sequences from unselected pools as templates. The genomic library was derived from the bacteriophage fd, and the gene 5 protein (g5p) from the phage was used as a target protein. After four rounds of primer-free genomic SELEX, most cloned sequences overlapped at a segment within gene 6 of the viral genome. This sequence segment was pyrimidine-rich and contained no stable secondary structures. Compared with a neighboring genomic fragment, a representative sequence from the family of selected sequences had about 23-fold higher g5p-binding affinity. Results from primer-free genomic SELEX were compared with the results from two other genomic SELEX protocols.     

小麦条锈菌大片段基因组DNA的提取方法研究

由条锈菌Puccinia striiformis引致的小麦条锈病是小麦最重要的病害之一。由于其活体寄生的特点,对小麦条锈菌的遗传学和分子生物学研究十分有限,大片段核DNA的提取研究还未见报道。高分子量基因组DNA是开展大片段基因组文库构建、基因组分析以及基因组重建的重要基础,通过系统建立和优化小麦条锈菌大片段基因组DNA的分离方法,成功获得分子量大于1Mb高质量的病菌基因组DNA。     

一种简便高效的酵母基因组提取方法

提取基因组进行检测是酵母研究过程中的必要步骤之一。以毕赤酵母菌株GS115作为研究对象,主要成分为0.2 mol/L醋酸锂和1% SDS的酵母裂解液能高效的裂解酵母细胞壁。与两种酵母基因组提取试剂盒相比,该方法从相同体积的酵母培养液中获得的基因组的量高5倍以上,并且操作简便、快速,能在2 h内完成一次提取过程,极大地缩短了时间。以GS115中的内源AOX基因为目的基因,对提取的基因组进行PCR检测和Southern杂交检测,进一步验证了基因组的质量。因此,本文建立了一种简便、快速、经济而高效的酵母基因提取方法。     

Identification of novel genomic islands associated with small RNAs

Genome evolution in prokaryotes is assisted by integration of gene pools from phages and plasmids. Regions downstream of tRNAs and tmRNAs are considered as hot spots for the integration of these gene pools or genomic islands. Till date, genomic islands have been identified only at tRNA/tmRNA genes in the enterobacterial genomes. Present work reports 10 distinct small RNAs as potent integration sites for genomic islands. A known tool tRNAcc 1.0 has been used to identify genomic islands associated with small RNAs c0362, oxyS, ryaA, rybB, rybD, ryeB, ryeE, rtT, sraE and tmRNA. The coordinates of 25 such small RNA associated genomic islands in three E. coli (strains: CFT073, EDL933 and K12) and Shigella flexneri (strain: 301) genomes are presented. Moreover cross-verification of the genomic sequences encoded within the identified genomic islands in horizontal gene transfer database, GenBank annotation features and atypical sequence compositions support our results. Again, all of the identified 25 genomic integration sites do exhibit genomic block rearrangements with respect to the associated small RNA. Similar to tRNAs/tmRNAs, the downstream regions of the small RNAs are found to be hotspots of integration.     

Examination of Genome Homogeneity in Prokaryotes Using Genomic Signatures

Background

DNA word frequencies, normalized for genomic AT content, are remarkably stable within prokaryotic genomes and are therefore said to reflect a “genomic signature.” The genomic signatures can be used to phylogenetically classify organisms from arbitrary sampled DNA. Genomic signatures can also be used to search for horizontally transferred DNA or DNA regions subjected to special selection forces. Thus, the stability of the genomic signature can be used as a measure of genomic homogeneity. The factors associated with the stability of the genomic signatures are not known, and this motivated us to investigate further. We analyzed the intra-genomic variance of genomic signatures based on AT content normalization (0^th order Markov model) as well as genomic signatures normalized by smaller DNA words (1^st and 2^nd order Markov models) for 636 sequenced prokaryotic genomes. Regression models were fitted, with intra-genomic signature variance as the response variable, to a set of factors representing genomic properties such as genomic AT content, genome size, habitat, phylum, oxygen requirement, optimal growth temperature and oligonucleotide usage variance (OUV, a measure of oligonucleotide usage bias), measured as the variance between genomic tetranucleotide frequencies and Markov chain approximated tetranucleotide frequencies, as predictors.

Principal Findings

Regression analysis revealed that OUV was the most important factor (p<0.001) determining intra-genomic homogeneity as measured using genomic signatures. This means that the less random the oligonucleotide usage is in the sense of higher OUV, the more homogeneous the genome is in terms of the genomic signature. The other factors influencing variance in the genomic signature (p<0.001) were genomic AT content, phylum and oxygen requirement.

Conclusions

Genomic homogeneity in prokaryotes is intimately linked to genomic GC content, oligonucleotide usage bias (OUV) and aerobiosis, while oligonucleotide usage bias (OUV) is associated with genomic GC content, aerobiosis and habitat.     

Functional cell-based uHTS in chemical genomic drug discovery

The availability of genomic information significantly increases the number of potential targets available for drug discovery, although the function of many targets and their relationship to disease is unknown. In a chemical genomic research approach, ultra-high throughput screening (uHTS) of genomic targets takes place early in the drug discovery process, before target validation. Target-selective modulators then provide drug leads and pharmacological research tools to validate target function. Effective implementation of a chemical genomic strategy requires assays that can perform uHTS for large numbers of genomic targets. Cell-based functional assays are capable of the uHTS throughput required for chemical genomic research, and their functional nature provides distinct advantages over ligand-binding assays in the identification of target-selective modulators.     

A genomic island linked to ecotype divergence in Atlantic cod

The genomic architecture underlying ecological divergence and ecological speciation with gene flow is still largely unknown for most organisms. One central question is whether divergence is genome‐wide or localized in ‘genomic mosaics’ during early stages when gene flow is still pronounced. Empirical work has so far been limited, and the relative impacts of gene flow and natural selection on genomic patterns have not been fully explored. Here, we use ecotypes of Atlantic cod to investigate genomic patterns of diversity and population differentiation in a natural system characterized by high gene flow and large effective population sizes, properties which theoretically could restrict divergence in local genomic regions. We identify a genomic region of strong population differentiation, extending over approximately 20 cM, between pairs of migratory and stationary ecotypes examined at two different localities. Furthermore, the region is characterized by markedly reduced levels of genetic diversity in migratory ecotype samples. The results highlight the genomic region, or ‘genomic island’, as potentially associated with ecological divergence and suggest the involvement of a selective sweep. Finally, we also confirm earlier findings of localized genomic differentiation in three other linkage groups associated with divergence among eastern Atlantic populations. Thus, although the underlying mechanisms are still unknown, the results suggest that ‘genomic mosaics’ of differentiation may even be found under high levels of gene flow and that marine fishes may provide insightful model systems for studying and identifying initial targets of selection during ecological divergence.     

Technology-Driven and Evidence-Based Genomic Analysis for Integrated Pediatric and Prenatal Genetics Evaluation

The first decade since the completion of the Human Genome Project has been marked with rapid development of genomic technologies and their immediate clinical applications.Genomic analysis using oligonucleotide array comparative genomic hybridization(aCGH) or single nucleotide polymorphism(SNP) chips has been applied to pediatric patients with developmental and intellectual disabilities(DD/ ID),multiple congenital anomalies(MCA) and autistic spectrum disorders(ASD).Evaluation of analytical and clinical validities of aCGH showed>99%sensitivity and specificity and increased analytical resolution by higher density probe coverage.Reviews of case series, multi-center comparison and large patient-control studies demonstrated a diagnostic yield of 12%—20%;approximately 60%of these abnormalities were recurrent genomic disorders.This pediatric experience has been extended toward prenatal diagnosis.A series of reports indicated approximately 10%of pregnancies with ultrasound-detected structural anomalies and normal cytogenetic findings had genomic abnormalities,and 30%of these abnormalities were syndromic genomic disorders.Evidence-based practice guidelines and standards for implementing genomic analysis and web-delivered knowledge resources for interpreting genomic findings have been established.The progress from this technology-driven and evidence-based genomic analysis provides not only opportunities to dissect disease-causing mechanisms and develop rational therapeutic interventions but also important lessons for integrating genomic sequencing into pediatric and prenatal genetic evaluation.     

Genomic structure and sequence variation of a 3.3-kb repeat DNA element of the kangaroo rat, Dipodomys ordii

The genomic structure and sequence variation of a 3.3-kb repeat DNA element, representing 5% of the genome of the kangaroo rat Dipodomys ordii, has been investigated. Most of the repeats are arranged in tandem arrays of 50 kb or more. Thirteen randomly selected genomic clones have been mapped with twelve restriction enzymes. The frequency of sequence divergence in the genomic clones is 0.5%. The clone maps and the genomic structure studies have permitted the characterization of a number of variant members of the 3.3-kb repeat family. The genomic organization of the repeat resembles that for repeated DNAs found in large tandem arrays or satellites.     

The impact of population structure on genomic prediction in stratified populations

Key message

Impacts of population structure on the evaluation of genomic heritability and prediction were investigated and quantified using high-density markers in diverse panels in rice and maize.

Abstract

Population structure is an important factor affecting estimation of genomic heritability and assessment of genomic prediction in stratified populations. In this study, our first objective was to assess effects of population structure on estimations of genomic heritability using the diversity panels in rice and maize. Results indicate population structure explained 33 and 7.5 % of genomic heritability for rice and maize, respectively, depending on traits, with the remaining heritability explained by within-subpopulation variation. Estimates of within-subpopulation heritability were higher than that derived from quantitative trait loci identified in genome-wide association studies, suggesting 65 % improvement in genetic gains. The second objective was to evaluate effects of population structure on genomic prediction using cross-validation experiments. When population structure exists in both training and validation sets, correcting for population structure led to a significant decrease in accuracy with genomic prediction. In contrast, when prediction was limited to a specific subpopulation, population structure showed little effect on accuracy and within-subpopulation genetic variance dominated predictions. Finally, effects of genomic heritability on genomic prediction were investigated. Accuracies with genomic prediction increased with genomic heritability in both training and validation sets, with the former showing a slightly greater impact. In summary, our results suggest that the population structure contribution to genomic prediction varies based on prediction strategies, and is also affected by the genetic architectures of traits and populations. In practical breeding, these conclusions may be helpful to better understand and utilize the different genetic resources in genomic prediction.     

Accounting for genomic pre-selection in national BLUP evaluations in dairy cattle

Background

In future Best Linear Unbiased Prediction (BLUP) evaluations of dairy cattle, genomic selection of young sires will cause evaluation biases and loss of accuracy once the selected ones get progeny.

Methods

To avoid such bias in the estimation of breeding values, we propose to include information on all genotyped bulls, including the culled ones, in BLUP evaluations. Estimated breeding values based on genomic information were converted into genomic pseudo-performances and then analyzed simultaneously with actual performances. Using simulations based on actual data from the French Holstein population, bias and accuracy of BLUP evaluations were computed for young sires undergoing progeny testing or genomic pre-selection. For bulls pre-selected based on their genomic profile, three different types of information can be included in the BLUP evaluations: (1) data from pre-selected genotyped candidate bulls with actual performances on their daughters, (2) data from bulls with both actual and genomic pseudo-performances, or (3) data from all the genotyped candidates with genomic pseudo-performances. The effects of different levels of heritability, genomic pre-selection intensity and accuracy of genomic evaluation were considered.

Results

Including information from all the genotyped candidates, i.e. genomic pseudo-performances for both selected and culled candidates, removed bias from genetic evaluation and increased accuracy. This approach was effective regardless of the magnitude of the initial bias and as long as the accuracy of the genomic evaluations was sufficiently high.

Conclusions

The proposed method can be easily and quickly implemented in BLUP evaluations at the national level, although some improvement is necessary to more accurately propagate genomic information from genotyped to non-genotyped animals. In addition, it is a convenient method to combine direct genomic, phenotypic and pedigree-based information in a multiple-step procedure.     

DNAdigest and Repositive: Connecting the World of Genomic Data

There is no unified place where genomics researchers can search through all available raw genomic data in a way similar to OMIM for genes or Uniprot for proteins. With the recent increase in the amount of genomic data that is being produced and the ever-growing promises of precision medicine, this is becoming more and more of a problem. DNAdigest is a charity working to promote efficient sharing of human genomic data to improve the outcome of genomic research and diagnostics for the benefit of patients. Repositive, a social enterprise spin-out of DNAdigest, is building an online platform that indexes genomic data stored in repositories and thus enables researchers to search for and access a range of human genomic data sources through a single, easy-to-use interface, free of charge.     

Genomic instability is associated with natural life span variation in Saccharomyces cerevisiae

Increasing genomic instability is associated with aging in eukaryotes, but the connection between genomic instability and natural variation in life span is unknown. We have quantified chronological life span and loss-of-heterozygosity (LOH) in 11 natural isolates of Saccharomyces cerevisiae. We show that genomic instability increases and mitotic asymmetry breaks down during chronological aging. The age-dependent increase of genomic instability generally lags behind the drop of viability and this delay accounts for approximately 50% of the observed natural variation of replicative life span in these yeast isolates. We conclude that the abilities of yeast strains to tolerate genomic instability co-vary with their replicative life spans. To the best of our knowledge, this is the first quantitative evidence that demonstrates a link between genomic instability and natural variation in life span.