There is more to tomato fruit colour than candidate carotenoid genes

Determining gene sequences responsible for complex phenotypes has remained a major objective in modern biology. The candidate gene approach is attempting to link, through mapping analysis, sequences that have a known functional role in the measured phenotype with quantitative trait loci (QTL) that are responsible for the studied variation. To explore the potential of the candidate approach for complex traits we conducted a mapping analysis of QTL for the intensity of the red colour of the tomato fruit (mainly lycopene) and for probes associated with the well-characterized carotenoid biosynthesis pathway. Seventy-five tomato introgression lines (ILs), each containing a single homozygous RFLP-defined chromosome segment from the green-fruited species Lycopersicon pennellii delimited 107 marker-defined mapping bins. Three of the bins resolved known qualitative colour mutations for yellow (r) and orange (B and Del) fruits resulting from variation in specific carotenoid biosynthesis genes. Based on trials in different environments, 16 QTL that modified the intensity of the red colour of ripe fruit were assigned to bins. Candidate sequences associated with the carotenoid biosynthesis pathway were mapped to 23 loci. Only five of the QTL co-segregated with the same bins that contained candidate genes - a number that is expected by chance alone. Furthermore, similar map location of a QTL and a candidate is far from a direct causative relationship between a gene and a phenotype. This study highlights the wealth and complexity of the variation present in the genus Lycopersicon that could be employed for basic research and genetic improvement of fruit colour in tomato.     

Simultaneous improvement and genetic dissection of grain yield and its related traits in a backbone parent of hybrid rice (Oryza sativa L.) using selective introgression

Three populations with a total of 125 BC2F3:4 introgression lines (ILs) selected for high yields from three BC2F2 populations were used for genetic dissection of rice yield and its related traits. The progeny testing in replicated phenotyping across two environments and genotyping with 140 polymorphic simple sequence repeat markers allowed the identification of 21 promising ILs that had significantly higher yields than the recurrent parent Shuhui527 (SH527). A total of 94 quantitative trait loci (QTL) were identified using the selective introgression method based on Chi-squared (χ ²) and multi-locus probability tests and the RSTEP-LRT method based on stepwise regression. These QTL were mostly mapped to 12 clusters on seven rice chromosomes. Several important properties of the QTL affecting grain yield (GY) and its related traits were revealed. The first one was the presence of strong and frequent non-random associations between or among QTL that affect low-heritability traits (GY and spikelet number per panicle, SN) in the ILs with high trait values. Second, beneficial alleles at 88.9 % GY and 75 % SN QTL for increased productivity were from the donors, suggesting that direct phenotypic selection for high yield in our introgression breeding program was a powerful way to transfer beneficial alleles at many loci from the donors into SH527. Third, most QTL were in clusters with large effects on multiple traits, which should be the focal points in further investigations and marker-assisted selection in rice. The majority of the QTL identified were expressed only in one of the environments, suggesting that differential expression of QTL in different environments is the primary genetic basis of genotype × environment interaction. Finally, a large variation in both the direction and magnitude of QTL effects was detected for different donor alleles at seven QTL in the same genetic background and environments. This finding suggests the possible presence of functional diversity among the donor alleles at these loci. The promising ILs and QTL identified provide valuable materials and genetic information for further improving the yield potential of SH527, which is a backbone restorer of hybrid rice in China.     

Molecular diversity, genomic constitution, and QTL mapping of fiber quality by mapped SSRs in introgression lines derived from Gossypium hirsutum?×?G. darwinii Watt

Because the genetic basis of current upland cotton cultivars is narrow, exploring new germplasm resources and discovering novel alleles relevant to important agronomic traits have become two of the most important themes in the field of cotton research. In this study, G. darwinii Watt, a wild cotton species, was crossed with four upland cotton cultivars with desirable traits. A total of 105 introgression lines (ILs) were successfully obtained. By using 310 mapped SSRs evenly distributed across the interspecific linkage map of G. hirsutum?×?G. barbadense, these 105 ILs and their corresponding parents were analyzed. A total of 278 polymorphic loci were detected among the 105 ILs, and the average length of introgression segments accumulated to 333.5?cM, accounting for 6.7?% of the whole genome. These lines included many variations. However, high similarity coefficients existed between lines, even between those derived from different parents. Finally, all the ILs and their upland cotton parents were used for association mapping of fiber quality in three environments. A total of 40 SSRs were found to be associated with five fiber quality indexes (P?相似文献   

Genetic diversity and population structure of a diverse set of rice germplasm for association mapping

Germplasm diversity is the mainstay for crop improvement and genetic dissection of complex traits. Understanding genetic diversity, population structure, and the level and distribution of linkage disequilibrium (LD) in target populations is of great importance and a prerequisite for association mapping. In this study, 100 genome-wide simple sequence repeat (SSR) markers were used to assess genetic diversity, population structure, and LD of 416 rice accessions including landraces, cultivars and breeding lines collected mostly in China. A model-based population structure analysis divided the rice materials into seven subpopulations. 63% of the SSR pairs in these accessions were in LD, which was mostly due to an overall population structure, since the number of locus pairs in LD was reduced sharply within each subpopulation, with the SSR pairs in LD ranging from 5.9 to 22.9%. Among those SSR pairs showing significant LD, the intrachromosomal LD had an average of 25–50 cM in different subpopulations. Analysis of the phenotypic diversity of 25 traits showed that the population structure accounted for an average of 22.4% of phenotypic variation. An example association mapping for starch quality traits using both the candidate gene mapping and genome-wide mapping strategies based on the estimated population structure was conducted. Candidate gene mapping confirmed that the Wx and starch synthase IIa (SSIIa) genes could be identified as strongly associated with apparent amylose content (AAC) and pasting temperature (PT), respectively. More importantly, we revealed that the Wx gene was also strongly associated with PT. In addition to the major genes, we found five and seven SSRs were associated with AAC and PT, respectively, some of which have not been detected in previous linkage mapping studies. The results suggested that the population may be useful for the genome-wide marker–trait association mapping. This new association population has the potential to identify quantitative trait loci (QTL) with small effects, which will aid in dissecting complex traits and in exploiting the rich diversity present in rice germplasm.     

SNPs in stress-responsive rice genes: validation, genotyping, functional relevance and population structure

ABSTRACT: BACKGROUND: Single nucleotide polymorphism (SNP) validation and large-scale genotyping are required to maximize the use of DNA sequence variation and determine the functional relevance of candidate genes for complex stress tolerance traits through genetic association in rice. We used the bead array platform-based Illumina GoldenGate assay to validate and genotype SNPs in a select set of stress-responsive genes to understand their functional relevance and study the population structure in rice. RESULTS: Of the 384 putative SNPs assayed, we successfully validated and genotyped 362 (94.3%). Of these 325 (84.6%) showed polymorphism among the 91 rice genotypes examined. Physical distribution, degree of allele sharing, admixtures and introgression, and amino acid replacement of SNPs in 263 abiotic and 62 biotic stress-responsive genes provided clues for identification and targeted mapping of trait-associated genomic regions. We assessed the functional and adaptive significance of validated SNPs in a set of contrasting drought tolerant upland and sensitive lowland rice genotypes by correlating their allelic variation with amino acid sequence alterations in catalytic domains and three-dimensional secondary protein structure encoded by stress-responsive genes. We found a strong genetic association among SNPs in the nine stress-responsive genes with upland and lowland ecological adaptation. Higher nucleotide diversity was observed in indica accessions compared with other rice sub-populations based on different population genetic parameters. The inferred ancestry of 16% among rice genotypes was derived from admixed populations with the maximum between upland aus and wild Oryza species. CONCLUSIONS: SNPs validated in biotic and abiotic stress-responsive rice genes can be used in association analyses to identify candidate genes and develop functional markers for stress tolerance in rice.     

A Genomic Resource for the Development,Improvement, and Exploitation of Sorghum for Bioenergy

With high productivity and stress tolerance, numerous grass genera of the Andropogoneae have emerged as candidates for bioenergy production. To optimize these candidates, research examining the genetic architecture of yield, carbon partitioning, and composition is required to advance breeding objectives. Significant progress has been made developing genetic and genomic resources for Andropogoneae, and advances in comparative and computational genomics have enabled research examining the genetic basis of photosynthesis, carbon partitioning, composition, and sink strength. To provide a pivotal resource aimed at developing a comparative understanding of key bioenergy traits in the Andropogoneae, we have established and characterized an association panel of 390 racially, geographically, and phenotypically diverse Sorghum bicolor accessions with 232,303 genetic markers. Sorghum bicolor was selected because of its genomic simplicity, phenotypic diversity, significant genomic tools, and its agricultural productivity and resilience. We have demonstrated the value of sorghum as a functional model for candidate gene discovery for bioenergy Andropogoneae by performing genome-wide association analysis for two contrasting phenotypes representing key components of structural and non-structural carbohydrates. We identified potential genes, including a cellulase enzyme and a vacuolar transporter, associated with increased non-structural carbohydrates that could lead to bioenergy sorghum improvement. Although our analysis identified genes with potentially clear functions, other candidates did not have assigned functions, suggesting novel molecular mechanisms for carbon partitioning traits. These results, combined with our characterization of phenotypic and genetic diversity and the public accessibility of each accession and genomic data, demonstrate the value of this resource and provide a foundation for future improvement of sorghum and related grasses for bioenergy production.     

银川番茄斑萎病毒的分子鉴定

为明确银川番茄(Lycopersicon esculentum)是否遭受了番茄斑萎病毒(TSWV)的危害, 采用国家标准TSWV RT- PCR检测技术对银川番茄上采集的14份疑似感染TSWV病叶样本进行分子鉴定, 对克隆得到的核衣壳蛋白基因N (Nucleocapsid)序列进行多序列比对和系统进化树分析, 随后对PCR阳性样本进行蛋白检测。结果表明, 14份病叶样本中有8份扩增出长度为394 bp的TSWV N基因序列, 且8条序列完全一致; 获得的银川番茄TSWV分离物与云南番茄、中国莴苣(Lactuca sativa)、中国鸢尾(Iris tectorum)和重庆辣椒(Capsicum annuum) TSWV分离物相对近缘, 与山东、黑龙江和北京等地及国外TSWV分离物相对远缘; 利用TSWV的抗体通过Western blot对8个PCR阳性样本进一步检测, 结果也证实8个阳性样本中存在TSWV感染。该研究首次通过分子鉴定及蛋白检测证明银川番茄上存在TSWV感染, 需要加快抗TSWV番茄品种的选育工作。     

生物信息学分析方法I: 全基因组关联分析概述

全基因组关联分析(GWAS)是动植物复杂性状相关基因定位的常用手段。高通量基因分型技术的应用极大地推动了GWAS的发展。在植物中, 利用GWAS不仅能够以较高的分辨率在全基因组水平鉴定出各种自然群体特定性状相关的基因或区间, 而且可揭示表型变异的遗传架构全景图。目前, 人们利用GWAS分析方法已在拟南芥(Arabidopsis thaliana)、水稻(Oryza sativa)、小麦(Triticum aestivum)、玉米(Zea mays)和大豆(Glycine max)等模式植物和重要农作物品系中发掘出与各种性状显著相关的数量性状座位(QTL)及其候选基因位点, 阐明了这些性状的遗传基础, 并为揭示这些性状背后的分子机理提供候选基因, 也为作物高产优质品种的选育提供了理论依据。该文对GWAS的方法、影响因素及数据分析流程进行了详细描述, 以期为相关研究提供参考。     

General combining ability of most yield-related traits had a genetic basis different from their corresponding traits per se in a set of maize introgression lines

Evaluation of combining ability is a crucial process in hybrid breeding, and dissection of the genetic basis of combining ability will facilitate hybrid breeding. In this study, molecular markers significantly associated with general combining ability (GCA) of seven yield-related traits and the traits per se were detected in a set of maize introgression lines (ILs) under three environments. Totally 25 and 31 significant loci for GCA and the traits per se were commonly detected under multiple environments, respectively. Correlation analysis and comparison among these significant loci revealed that the genetic basis of GCA of these yield-related traits was generally different from that of the traits per se except for the trait of ear row number. In addition, GCA of the ILs was positively and significantly correlated to the total relative effects of significant GCA loci in the ILs in general, implying that the GCA loci identified in this study would be useful in molecular breeding. Correlation analysis also showed that the GCA of yield per plant was strongly correlated to the GCA of kernel number per row, ear length and 100-kernel-weight, thus these traits were more important in genetic improvement for GCA. Results in this study would provide useful information for hybrid breeding in maize.     

Characterising functionally important and ecologically meaningful genetic diversity using a candidate gene approach

Over the past two decades the fields of molecular ecology and population genetics have been dominated by the use of putatively neutral DNA markers, primarily to resolve spatio-temporal patterns of genetic variation to inform our understanding of population structure, gene flow and pedigree. Recent emphasis in comparative functional genomics, however, has fuelled a resurgence of interest in functionally important genetic variation that underpins phenotypic traits of adaptive or ecological significance. It may prove a major challenge to transfer genomics information from classical model species to examine functional diversity in non-model species in natural populations, but already multiple gene-targeted candidate loci with major effect on phenotype and fitness have been identified. Here we briefly describe some of the research strategies used for isolating and characterising functional genetic diversity at candidate gene-targeted loci, and illustrate the efficacy of some of these approaches using our own studies on red grouse (Lagopus lagopus scoticus). We then review how candidate gene markers have been used to: (1) quantify genetic diversity among populations to identify those depauperate in genetic diversity and requiring specific management action; (2) identify the strength and mode of selection operating on individuals within natural populations; and (3) understand direct mechanistic links between allelic variation at single genes and variance in individual fitness.     

全基因组关联分析实现水稻粒型自然变异的分子解析

全基因组关联分析(GWAS)近年来被广泛应用于解析生物自然变异的遗传基础。但限于其遗传定位精度, 在水稻(Oryza sativa)遗传学研究中, 该方法尚无法取代传统的图位克隆法在克隆复杂性状调控基因中的作用。近期, 中国科学家在应用GWAS等大数据来克隆控制水稻粒长和粒重等复杂性状的QTL方面取得了新突破。     

Rapid establishment of introgression lines using cytoplasmic male sterility and a restorer gene in Oryza sativa cv. Nipponbare

Quantitative trait locus (QTL) analyses have greatly enhanced our understanding of complex traits in rice (Oryza sativa). In parallel, the development of introgression lines has provided a powerful tool for elucidation of complicated genetic networks and identification of QTL. We recently developed a biotron breeding system that allows rapid indoor cultivation of rice plants. The system, however, has two relatively weak points in its application to marker-assisted breeding in rice: first, variation in generation times among cultivars; second, the low number of seeds produced by crosses. To compensate for these weaknesses, we propose utilizing cytoplasmic male sterility (CMS) and restorer (Rf) lines with a cv. Nipponbare genetic background. Through use of the Nipponbare genetic background, rice generation times of 2 months can be achieved regardless of any differences in the genetic background of the donor rice plant. This CMS–Rf system confers a high yield of hybrid seeds, avoids the need for emasculation and precludes accidental crosses. Our results demonstrate that this new methodology can markedly accelerate many different aspects of rice research, especially in functional genomics. The combination of biotron breeding system, early flowering habit and CMS will be of great value for screening candidate genes associated with QTL and for introducing useful QTL into elite cultivars.     

Identification of combining ability loci for five yield-related traits in maize using a set of testcrosses with introgression lines

Combining ability is essential for hybrid breeding in crops. However, the genetic basis of combining ability remains unclear and has been seldom investigated. Identifying molecular markers associated with this complex trait would help to understand its genetic basis and provide useful information for hybrid breeding in maize. In this study, we identified genetic loci of general combining ability (GCA) and specific combining ability (SCA) for five yield-related traits under three environments using a set of testcrosses with introgression lines (ILs). GCA or SCA of the five yield-related traits of the ILs was estimated by the performance of testcrosses with four testers from different heterotic groups. Genetic correlations between GCA of the traits and the corresponding traits per se were not significant or not strong, suggesting that the genetic basis between them is different. A total of 56 significant loci for GCA and 21 loci for SCA were commonly identified in at least two environments, and only 5 loci were simultaneously controlling GCA and SCA, indicating that the genetic basis of GCA and SCA is different. For all of the traits investigated, positive and significant correlations between the number of GCA loci in the ILs and the performance of the corresponding GCA of the ILs were detected, implying that pyramiding GCA loci would have positive effect on the performance of GCA. Results in this study would be useful for maize hybrid breeding.     

An integrated view of quantitative trait variation using tomato interspecific introgression lines

Resolving natural phenotypic variation into genetic and molecular components is a major objective in biology. Over the past decade, tomato interspecific introgression lines (ILs), each carrying a single 'exotic' chromosome segment from a wild species, have exposed thousands of quantitative trait loci (QTL) affecting plant adaptation, morphology, yield, metabolism, and gene expression. QTL for fruit size and sugar composition were isolated by map-based cloning, while others were successfully implemented in marker-assisted breeding programs. More recently, integrating the multitude of IL-QTL into a single database has unraveled some unifying principles about the architecture of complex traits in plants.     

Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems

The rapid progress in rice genotyping must be matched by advances in phenotyping. A better understanding of genetic variation in rice for drought response, root traits, and practical methods for studying them are needed. In this study, the OryzaSNP set (20 diverse genotypes that have been genotyped for SNP markers) was phenotyped in a range of field and container studies to study the diversity of rice root growth and response to drought. Of the root traits measured across more than 20 root experiments, root dry weight showed the most stable genotypic performance across studies. The environment (E) component had the strongest effect on yield and root traits. We identified genomic regions correlated with root dry weight, percent deep roots, maximum root depth, and grain yield based on a correlation analysis with the phenotypes and aus, indica, or japonica introgression regions using the SNP data. Two genomic regions were identified as hot spots in which root traits and grain yield were co-located; on chromosome 1 (39.7–40.7 Mb) and on chromosome 8 (20.3–21.9 Mb). Across experiments, the soil type/ growth medium showed more correlations with plant growth than the container dimensions. Although the correlations among studies and genetic co-location of root traits from a range of study systems points to their potential utility to represent responses in field studies, the best correlations were observed when the two setups had some similar properties. Due to the co-location of the identified genomic regions (from introgression block analysis) with QTL for a number of previously reported root and drought traits, these regions are good candidates for detailed characterization to contribute to understanding rice improvement for response to drought. This study also highlights the utility of characterizing a small set of 20 genotypes for root growth, drought response, and related genomic regions.     

Phenotypic Activation to Discover Biological Pathways and Kinase Substrates

Observing the effects of gene perturbation on cells or organisms has long been a standard strategy in biological research. We developed a genome-wide gene overexpression library as a new tool for large-scale functional analysis in budding yeast. Previous large-scale genetic studies have focused on applications of the deletion mutant collection, which has arguably revolutionized the functional characterization of yeast genes. While extremely powerful, deletion mutant experiments are generally limited to the characterization of loss-of-function phenotypes. We have explored the potential for using the Synthetic Genetic Array (SGA) method, a platform for high-throughput genetic analysis, with a genome-wide “overexpression array”, in which each strain on the array overexpresses a unique yeast gene. The overexpression array enables gain-of-function phenotypes to be examined on a large scale, providing a unique insight into gene function and a novel source of reagents for the global mapping of genetic networks and functional relationships amongst genes and pathways. Understanding the molecular bases of overexpression phenotypes should also shed new light on the nature of genetic dominance.     

Development of Oryza rufipogon and O. sativa Introgression Lines and Assessment for Yield-related Quantitative Trait Loci

Introgression lines population was effectively used in mapping quantitative trait loci （QTLs）, identifying favorable genes, discovering hidden genetic variation, evaluating the action or interaction of QTLs in multiple conditions and providing the favorable experimental materials for plant breeding and genetic research. In this study, an advanced backcross and consecutive selfing strategy was used to develop introgression lines （ILs）, which derived from an accession of Oryza rufipogon Griff. collected from Yuanjiang County, Yunnan Province of China, as the donor, and an elite indica cultivar Teqing （O. sativa L.）, as the recipient. Introgression segments from O. rufipogon were screened using 179 polymorphic simple sequence repeats （SSR） markers in the genome of each IL. Introgressed segments carried by the introgression lines population contained 120 ILs covering the whole O. rufipogon genome. The mean number of homozygous O. rufipogon segments per introgression line was about 3.88. The average length of introgressed segments was approximate 25.5 cM, and about 20.8% of these segments had sizes less than 10 cM. The genome of each IL harbored the chromosomal fragments of O. rufipogon ranging from 0.54% to 23.7%, with an overall average of 5.79%. At each locus, the ratio of substitution of O. rufipogon alleles had a range of 1.67-9.33, with an average of 5.50. A wide range of alterations in morphological and yield-related traits were also found in the introgression lines population. Using single-point analysis, a total of 37 putative QTLs for yield and yield components were detected at two sites with 7%-20% explaining the phenotypic variance. Nineteen QTLs （51.4%） were detected at both sites, and the alleles from O. rufipogon at fifteen loci （40.5%） improved the yield and yield components in the Teqing background. These O. rufipogon-O, sativa introgression lines will serve as genetic materials for identifying and using favorable genes from common wild rice.     

Localization of Canine Brachycephaly Using an Across Breed Mapping Approach

The domestic dog, Canis familiaris, exhibits profound phenotypic diversity and is an ideal model organism for the genetic dissection of simple and complex traits. However, some of the most interesting phenotypes are fixed in particular breeds and are therefore less tractable to genetic analysis using classical segregation-based mapping approaches. We implemented an across breed mapping approach using a moderately dense SNP array, a low number of animals and breeds carefully selected for the phenotypes of interest to identify genetic variants responsible for breed-defining characteristics. Using a modest number of affected (10–30) and control (20–60) samples from multiple breeds, the correct chromosomal assignment was identified in a proof of concept experiment using three previously defined loci; hyperuricosuria, white spotting and chondrodysplasia. Genome-wide association was performed in a similar manner for one of the most striking morphological traits in dogs: brachycephalic head type. Although candidate gene approaches based on comparable phenotypes in mice and humans have been utilized for this trait, the causative gene has remained elusive using this method. Samples from nine affected breeds and thirteen control breeds identified strong genome-wide associations for brachycephalic head type on Cfa 1. Two independent datasets identified the same genomic region. Levels of relative heterozygosity in the associated region indicate that it has been subjected to a selective sweep, consistent with it being a breed defining morphological characteristic. Genotyping additional dogs in the region confirmed the association. To date, the genetic structure of dog breeds has primarily been exploited for genome wide association for segregating traits. These results demonstrate that non-segregating traits under strong selection are equally tractable to genetic analysis using small sample numbers.