Identification of QTLs for Yield and Associated Traits in F₂ Population of Rice

Identification of quantitative trait loci (QTLs) controlling yield and yield-related traits in rice was performed in the F₂ mapping population derived from parental rice genotypes DHMAS and K343. A total of 30 QTLs governing nine different traits were identified using the composite interval mapping (CIM) method. Four QTLs were mapped for number of tillers per plant on chromosomes 1 (2 QTLs), 2 and 3; three QTLs for panicle number per plant on chromosomes 1 (2 QTLs) and 3; four QTLs for plant height on chromosomes 2, 4, 5 and 6; one QTL for spikelet density on chromosome 5; four QTLs for spikelet fertility percentage (SFP) on chromosomes 2, 3 and 5 (2 QTLs); two QTLs for grain length on chromosomes 1 and 8; three QTLs for grain width on chromosomes1, 3 and 8; three QTLs for 1000-grain weight (TGW) on chromosomes 1, 4 and 8 and six QTLs for yield per plant (YPP) on chromosomes 2 (3 QTLs), 4, 6 and 8. Most of the QTLs were detected on chromosome 2, so further studies on chromosome 2 could help unlock some new chapters of QTL for this cross of rice variety. Identified QTLs elucidating high phenotypic variance can be used for marker-assisted selection (MAS) breeding. Further, the exploitation of information regarding molecular markers tightly linked to QTLs governing these traits will facilitate future crop improvement strategies in rice.     

Discovering Candidate Chromosomal Regions Linked to Kernel Size-Related Traits via QTL Mapping and Bulked Sample Analysis in Maize

Kernel size-related traits, including kernel length, kernel width, and kernel thickness, are critical components in determining yield and kernel quality in maize (Zea mays L.). Dissecting the phenotypic characteristics of these traits, and discovering the candidate chromosomal regions for these traits, are of potential importance for maize yield and quality improvement. In this study, a total of 139 F2:3 family lines derived from EHel and B73, a distinct line with extremely low ear height (EHel), was used for phenotyping and QTL mapping of three kernel size-related traits, including 10-kernel length (KL), 10-kernel width (KWid), and 10-kernel thickness (KT). The results showed that only one QTL for KWid, i.e., qKWid9 on Chr9, with a phenotypic variation explained (PVE) of 13.4% was detected between SNPs of AX-86298371 and AX-86298372, while no QTLs were detected for KL and KT across all 10 chromosomes. Four bulked groups of family lines, i.e., Groups I to IV, were constructed with F2:3 family lines according to the phenotypic comparisons of KWid between EHel and B73. Among these four groups, Group I possessed a significantly lower KWid than EHel (P = 0.0455), Group II was similar to EHel (P = 0.34), while both Group III and Group IV were statistically higher than EHel (P < 0.05). Besides, except Group IV exhibited a similar KWid to B73 (P = 0.11), KWid of Groups I to III were statistically lower than B73 (P < 0.00). By comparing the bulked genotypes of the four groups to EHel and B73, a stable chromosomal region on Chr9 between SNPs of AX-86298372 to AX-86263154, entirely covered by qKWid9, was identified to link KWid with the positive allele of increasing phenotypic effect to KWid from B73, similar to that of qKWid9. A large amount of enzyme activity and macromolecule binding-related genes were annotated within this chromosomal region, suggesting qKWid9 as a potential QTL for KWid in maize.     

Mapping the genome of Miscanthus sinensis for QTL associated with biomass productivity

In light of rising energy costs, lignocellulosic ethanol has been identified as a renewable alternative to petroleum-based transportation fuels. In an attempt to reach government mandated ethanol production levels, potential plant biofeedstock candidates have been investigated, and cold-tolerant, perennial accessions within the C₄ grass genus Miscanthus have been identified as leading contenders in the Midwestern US. To facilitate the development of improved cultivars through marker-assisted breeding, a quantitative trait locus (QTL) study was conducted on a full-sib, F₁ mapping population segregating for flowering time, height, leaf width, and yield using a genetic map consisting of 846 segregating SNP and SSR markers. This was a 3 year study investigating the genetic architecture underlying traits important to biomass production in a population of 221 progeny from a cross between M. sinensis ‘Grosse Fountaine’ and M. sinensis ‘Undine’ established in the spring of 2010; 72 QTLs with LOD scores above the genome-wide, permuted threshold equivalent to a P-value of 0.05 were identified across 13 traits. Of the 36 QTLs identified in 2011, 22 were detected again the following year. Both the use of spring emergence and vigor rating as a covariate to account for variation related to differences in establishment increased the power to detect QTLs in the 2 year establishment period. Finally, a dry period in the middle of the 2012 growing season suggested that yield declines were due to a decrease in tiller diameter.     

Pheno2Geno - High-throughput generation of genetic markers and maps from molecular phenotypes for crosses between inbred strains

Background

Genetic markers and maps are instrumental in quantitative trait locus (QTL) mapping in segregating populations. The resolution of QTL localization depends on the number of informative recombinations in the population and how well they are tagged by markers. Larger populations and denser marker maps are better for detecting and locating QTLs. Marker maps that are initially too sparse can be saturated or derived de novo from high-throughput omics data, (e.g. gene expression, protein or metabolite abundance). If these molecular phenotypes are affected by genetic variation due to a major QTL they will show a clear multimodal distribution. Using this information, phenotypes can be converted into genetic markers.

Results

The Pheno2Geno tool uses mixture modeling to select phenotypes and transform them into genetic markers suitable for construction and/or saturation of a genetic map. Pheno2Geno excludes candidate genetic markers that show evidence for multiple possibly epistatically interacting QTL and/or interaction with the environment, in order to provide a set of robust markers for follow-up QTL mapping.We demonstrate the use of Pheno2Geno on gene expression data of 370,000 probes in 148 A. thaliana recombinant inbred lines. Pheno2Geno is able to saturate the existing genetic map, decreasing the average distance between markers from 7.1 cM to 0.89 cM, close to the theoretical limit of 0.68 cM (with 148 individuals we expect a recombination every 100/148=0.68 cM); this pinpointed almost all of the informative recombinations in the population.

Conclusion

The Pheno2Geno package makes use of genome-wide molecular profiling and provides a tool for high-throughput de novo map construction and saturation of existing genetic maps. Processing of the showcase dataset takes less than 30 minutes on an average desktop PC. Pheno2Geno improves QTL mapping results at no additional laboratory cost and with minimum computational effort. Its results are formatted for direct use in R/qtl, the leading R package for QTL studies. Pheno2Geno is freely available on CRAN under “GNU GPL v3”. The Pheno2Geno package as well as the tutorial can also be found at: http://pheno2geno.nl.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0475-6) contains supplementary material, which is available to authorized users.     

不同生长环境下水稻穗伸出度的QTL分析

以十和田/昆明小白谷225个F14家系为作图群体,在云南省弥勒县(正常生长环境)、嵩明县(自然低温胁迫环境)、丽江市(自然低温胁迫环境)等3个试点不同年份共5种不同生长环境下进行了水稻主穗和分蘖穗穗伸出度的异地鉴定,并利用SSR标记对水稻穗伸出度进行了QTL分析。检测结果表明,在5种不同的生长环境下共检测到12个与水稻穗伸出度相关的QTL,分别分布于第1(2个QTLs)、2、4、6(3个QTLs)、7(3个QTLs)、9(2个QTLs)号染色体,对表型的贡献率为3.72%~22.17%。其中与主穗穗伸出度相关的QTL共11个,与分蘖穗穗伸出度相关的QTL共7个,其中6个在主穗和分蘖穗上均检测到。在与主穗穗伸出度相关的11个QTL中,q PE-7-1在4种环境下均被检测到,解释的表型变异为9.49%~22.17%;q PE-1-1、q PE-1-2、q PE-6-1和q PE-9-2 4个QTL在2种环境下均被检测到。在与分蘖穗穗伸出度相关的7个QTL中,q PE-1-2、q PE-7-1和q PE-6-1 3个QTL在2种环境中均被检测到,解释的表型变异率分别为4.35%~12.64%、13.22%~20.89%和11.49%~15.73%。     

烟草品种Beinhart1000-1抗黑胫病基因的QTL定位

为研究烟草黑胫病不同亲本来源的抗性遗传规律,定位抗性基因位点,本研究利用抗黑胫病品种Beinhart1000-1构建了220个F2分离群体。通过病圃接种鉴定和遗传分析,确定Beinhart1000-1对烟草黑胫病的抗性由多基因控制。利用筛选到的70对稳定SSR引物对烟草黑胫病抗性进行了QTL分析,绘制了一张包含14条染色体的遗传连锁图谱,且定位到5个与烟草黑胫病抗性紧密相关的QTLs,分别在2、3、3、6、12号染色体上,其贡献率分别为6.2%、6.0%、6.7%、5.6%和5.1%。此结果使烟草黑胫病抗性研究进一步深入,推进了烟草黑胫病分子标记辅助选择。     

Genetic basis of natural variation in body pigmentation in Drosophila melanogaster

Body pigmentation in insects and other organisms is typically variable within and between species and is often associated with fitness. Regulatory variants with large effects at bab1, t and e affect variation in abdominal pigmentation in several populations of Drosophila melanogaster. Recently, we performed a genome wide association (GWA) analysis of variation in abdominal pigmentation using the inbred, sequenced lines of the Drosophila Genetic Reference Panel (DGRP). We confirmed the large effects of regulatory variants in bab1, t and e; identified 81 additional candidate genes; and validated 17 candidate genes (out of 28 tested) using RNAi knockdown of gene expression and mutant alleles. However, these analyses are imperfect proxies for the effects of segregating variants. Here, we describe the results of an extreme quantitative trait locus (xQTL) GWA analysis of female body pigmentation in an outbred population derived from light and dark DGRP lines. We replicated the effects on pigmentation of 28 genes implicated by the DGRP GWA study, including bab1, t and e and 7 genes previously validated by RNAi and/or mutant analyses. We also identified many additional loci. The genetic architecture of Drosophila pigmentation is complex, with a few major genes and many other loci with smaller effects.     

Genome-wide SNP identification for the construction of a high-resolution genetic map of Japanese flounder (Paralichthys olivaceus): applications to QTL mapping of Vibrio anguillarum disease resistance and comparative genomic analysis

High-resolution genetic maps are essential for fine mapping of complex traits, genome assembly, and comparative genomic analysis. Single-nucleotide polymorphisms (SNPs) are the primary molecular markers used for genetic map construction. In this study, we identified 13,362 SNPs evenly distributed across the Japanese flounder (Paralichthys olivaceus) genome. Of these SNPs, 12,712 high-confidence SNPs were subjected to high-throughput genotyping and assigned to 24 consensus linkage groups (LGs). The total length of the genetic linkage map was 3,497.29 cM with an average distance of 0.47 cM between loci, thereby representing the densest genetic map currently reported for Japanese flounder. Nine positive quantitative trait loci (QTLs) forming two main clusters for Vibrio anguillarum disease resistance were detected. All QTLs could explain 5.1–8.38% of the total phenotypic variation. Synteny analysis of the QTL regions on the genome assembly revealed 12 immune-related genes, among them 4 genes strongly associated with V. anguillarum disease resistance. In addition, 246 genome assembly scaffolds with an average size of 21.79 Mb were anchored onto the LGs; these scaffolds, comprising 522.99 Mb, represented 95.78% of assembled genomic sequences. The mapped assembly scaffolds in Japanese flounder were used for genome synteny analyses against zebrafish (Danio rerio) and medaka (Oryzias latipes). Flounder and medaka were found to possess almost one-to-one synteny, whereas flounder and zebrafish exhibited a multi-syntenic correspondence. The newly developed high-resolution genetic map, which will facilitate QTL mapping, scaffold assembly, and genome synteny analysis of Japanese flounder, marks a milestone in the ongoing genome project for this species.     

Deploying QTL-seq for rapid delineation of a potential candidate gene underlying major trait-associated QTL in chickpea

A rapid high-resolution genome-wide strategy for molecular mapping of major QTL(s)/gene(s) regulating important agronomic traits is vital for in-depth dissection of complex quantitative traits and genetic enhancement in chickpea. The present study for the first time employed a NGS-based whole-genome QTL-seq strategy to identify one major genomic region harbouring a robust 100-seed weight QTL using an intra-specific 221 chickpea mapping population (desi cv. ICC 7184 × desi cv. ICC 15061). The QTL-seq-derived major SW QTL (CaqSW1.1) was further validated by single-nucleotide polymorphism (SNP) and simple sequence repeat (SSR) marker-based traditional QTL mapping (47.6% R² at higher LOD >19). This reflects the reliability and efficacy of QTL-seq as a strategy for rapid genome-wide scanning and fine mapping of major trait regulatory QTLs in chickpea. The use of QTL-seq and classical QTL mapping in combination narrowed down the 1.37 Mb (comprising 177 genes) major SW QTL (CaqSW1.1) region into a 35 kb genomic interval on desi chickpea chromosome 1 containing six genes. One coding SNP (G/A)-carrying constitutive photomorphogenic9 (COP9) signalosome complex subunit 8 (CSN8) gene of these exhibited seed-specific expression, including pronounced differential up-/down-regulation in low and high seed weight mapping parents and homozygous individuals during seed development. The coding SNP mined in this potential seed weight-governing candidate CSN8 gene was found to be present exclusively in all cultivated species/genotypes, but not in any wild species/genotypes of primary, secondary and tertiary gene pools. This indicates the effect of strong artificial and/or natural selection pressure on target SW locus during chickpea domestication. The proposed QTL-seq-driven integrated genome-wide strategy has potential to delineate major candidate gene(s) harbouring a robust trait regulatory QTL rapidly with optimal use of resources. This will further assist us to extrapolate the molecular mechanism underlying complex quantitative traits at a genome-wide scale leading to fast-paced marker-assisted genetic improvement in diverse crop plants, including chickpea.