Mapping QTLs for improving grain yield using the USDA rice mini-core collection

Yield is the most important and complex trait for genetic improvement in crops, and marker-assisted selection enhances the improvement efficiency. The USDA rice mini-core collection derived from over 18,000 accessions of global origins is an ideal panel for association mapping. We phenotyped 203 O. sativa accessions for 14 agronomic traits and identified 5 that were highly and significantly correlated with grain yield per plant: plant height, plant weight, tillers, panicle length, and kernels/branch. Genotyping with 155 genome-wide molecular markers demonstrated 5 main cluster groups. Linkage disequilibrium (LD) decayed at least 20 cM and marker pairs with significant LD ranged from 4.64 to 6.06% in four main groups. Model comparisons revealed that different dimensions of principal component analysis affected yield and its correlated traits for mapping accuracy, and kinship did not improve the mapping in this collection. Thirty marker–trait associations were highly significant, 4 for yield, 3 for plant height, 6 for plant weight, 9 for tillers, 5 for panicle length and 3 for kernels/branch. Twenty-one markers contributed to the 30 associations, because 8 markers were co-associated with 2 or more traits. Allelic analysis of OSR13, RM471 and RM7003 for their co-associations with yield traits demonstrated that allele 126 bp of RM471 and 108 bp of RM7003 should receive greater attention, because they had the greatest positive effect on yield traits. Tagging the QTLs responsible for multiple yield traits may simultaneously help dissect the complex yield traits and elevate the efficiency to improve grain yield using marker-assisted selection in rice.     

Quantitative trait loci for rice yield-related traits using recombinant inbred lines derived from two diverse cultivars

The thousand-grain weight and spikelets per panicle directly contribute to rice yield. Heading date and plant height also greatly influence the yield. Dissection of genetic bases of yield-related traits would provide tools for yield improvement. In this study, quantitative trait loci (QTL) mapping for spikelets per panicle, thousand-grain weight, heading date and plant height was performed using recombinant inbred lines derived from a cross between two diverse cultivars, Nanyangzhan and Chuan7. In total, 20 QTLs were identified for four traits. They were located to 11 chromosomes except on chromosome 4. Seven and five QTLs were detected for thousand-grain weight and spikelets per panicle, respectively. Four QTLs were identified for both heading date and plant height. About half the QTLs were commonly detected in both years, 2006 and 2007. Six QTLs are being reported for the first time. Two QTL clusters were identified in regions flanked by RM22065 and RM5720 on chromosome 7 and by RM502 and RM264 on chromosome 8, respectively. The parent, Nanyangzhan with heavy thousand-grain weight, carried alleles with increased effects on all seven thousand-grain weight QTL, which explained why there was no transgressive segregation for thousand-grain weight in the population. In contrast, Chuan7 with more spikelets per panicle carried positive alleles at all five spikelets per panicle QTL except qspp5. Further work on distinction between pleiotropic QTL and linked QTL is needed in two yield-related QTL clusters.     

直播条件下水稻6个穗部性状的QTL分析

在大田直播条件下,利用来源于＂Lemont/特青＂的重组自交系群体,对水稻6个穗部性状及其相互间遗传相关的分子基础进行了QTL分析,共检测到19个QTL,各性状QTL数为2～4个,单个QTL贡献率为4%～22%。共检测到3个染色体区段能同时影响多个穗部性状,其中第1染色体RM212-RM104和第2染色体RM263-RM221区段的QTL能同时影响单株产量、每穗颖花数、着粒密度和二次枝梗数中的3个或4个性状,且这2个区段的QTL对各性状的效应方向相同,增效等位基因均来自‘特青’,为各性状间表型正相关提供了重要的遗传解释。第11染色体RG1022附近的QTL对着粒密度的效应值为负,来自‘特青’的等位基因增加性状值,而对穗长的效应值为正,来自‘特青’的等位基因降低性状值,为这2个性状间表型负相关也提供了一定的遗传解释。此外,对水稻穗部性状QTL在多种环境和遗传背景下的稳定表达及其在分子标记辅助育种中的应用进行了讨论。     

两个水稻骨干恢复系重要农艺性状的遗传基础研究

水稻骨干恢复系是指在杂交稻育种中广泛应用的一类恢复系。探明骨干恢复系的遗传基础,发掘其重要农艺性状基因/QTL,对分子标记辅助选择水稻恢复系育种具有重要应用价值。本研究以生产上广泛应用的三系骨干恢复系成恢727和两系骨干恢复系9311为亲本,培育了具有250个系的重组自交系群体。分别在2015年三亚和2016年合肥两个环境下进行了9个重要农艺性状表型和SSR分子标记基因型鉴定,用SAS9.2分析表型数据,用QTL Ici Mapping v4.1进行QTL定位分析。在三亚和合肥两个环境下共检测到39个QTL,三亚检测到16个,分布于第1、2、4、7、8、10、11和12染色体上;合肥检测24个,分布于第1、2、3、7、8、9、10和12染色体上。其中qPH1-1在三亚和合肥两个环境下都能检测到,加性效应分别为-1.75和-2.46。在检测到的39个QTL中,有24个QTL的增效等位基因来自恢复系成恢727,15个QTL的增效等位基因来自9311。共计有26个QTL曾被前人定位,13个属于尚未见文献报道的新QTL。另外,在RM279~RM521、RM336~RM3534、RM25~RM547、RM553~RM160、RM222~RM271区段内检测到5个多效性QTL位点。其中RM25~RM547位点与已经克隆的基因Ghd8位置相近。RM553~RM160位点是一个新的多效性位点,分别控制每穗实粒数、单株产量和结实率,而且效应和表型变异贡献率都较大。其余3个位点在前人的研究中分别有所报道,但其多效性则是在本研究中首次发现。在本研究新发掘到的QTL中,控制穗数的QTL qPN12-1,控制穗长的QTL qPL1-2和qPL10-1,控制总粒数的QTL qSNP2-1和qSNP10-1,控制结实率的QTL qSF3-1,控制千粒重QTL qTGW7-1和控制产量的QTL qGY1-1效应均比较大,解释的表型遗传变异比例也较高。本研究的结果将会为相关性状QTL的精细定位、克隆和育种应用奠定基础。     

Mapping QTLs for Plant Phenology and Production Traits Using Indica Rice (Oryza sativa L.) Lines Adapted to Rainfed Environment

Drought is a major abiotic stress limiting rice production and yield stability in rainfed ecosystems. Identifying quantitative trait loci (QTL) for rice yield and yield components under water limited environments will help to develop drought resilient cultivars using marker assisted breeding (MAB) strategy. A total of 232 recombinant inbred lines of IR62266/Norungan were used to map QTLs for plant phenology and production traits under rainfed condition in target population of environments. A total of 79 QTLs for plant phenology and production traits with phenotypic variation ranging from 4.4 to 72.8% were detected under non-stress and drought stress conditions across two locations. Consistent QTLs for phenology and production traits were detected across experiments and water regimes. The QTL region, RM204-RM197-RM217 on chromosome 6 was linked to days to 50% flowering and grain yield per plant under both rainfed and irrigated conditions. The same genomic region, RM585-RM204-RM197 was also linked to harvest index under rainfed condition with positive alleles from Norungan, a local landrace. QTLs for plant production and drought resistance traits co-located near RM585-RM204-RM197-RM217 region on chromosome 6 in several rice genotypes. Thus with further fine mapping, this region may be useful as a candidate QTL for MAB, map-based cloning of genes and functional genomics studies for rainfed rice improvement.     

水稻籼粳交DH群体收获指数及源库性状的QTL分析

以 1个水稻籼粳交 (圭 6 30 0 2 4 2 8)来源的DH群体为材料 ,利用 1张含有 2 32个标记的RFLP连锁图谱和基于混合线性模型的定位软件QTLMapper1 0对水稻收获指数及生物量、籽粒产量、库容量和株高 5个性状进行QTL分析 ,共检测到 2 1个主效应QTLs和 9对上位性互作位点。其中 ,控制籽粒产量的 3个QTLs合计贡献率为 4 2 % ,LOD值为 7 10 ;这 3个QTLs或者与收获指数的QTL同位 ,或者与生物量的QTL同位 ,且加性效应的方向一致 ,从而揭示了“籽粒产量 =生物量×收获指数”的遗传基础所在。控制收获指数的 4个QTLs合计贡献率为 4 6 % ,LOD值为 10 3;控制生物量的 4个QTLs合计贡献率为 6 4 % ,LOD值为 14 0 9;收获指数的 4个QTLs与生物量的 4个QTLs均不同位。因此 ,通过基因重组 ,可能实现控制收获指数和生物量的增效基因的聚合 ,由此获得收获指数和生物量“双高”的基因型。检测到 5个株高QTLs,其合计贡献率为 6 4 % ,LOD值为 11 6 2 ;其中 ,有 3个效应较小的QTLs与生物量、库容量和 或籽粒产量QTLs同位 ,且同位QTLs的加性效应方向一致 ;未发现株高QTLs与收获指数QTLs的同位性。由此表明 ,株高与“源 流 库”概念中的“源”和“库”在遗传上有一定程度的关联 ,而与“流”无关联。此外还发现 ,在上述同位性QTL     

Molecular profiling in relation to drought tolerance in advance breeding lines of rice using microsatellite markers

Using agro-morphological characters and microsatellite markers, advance breeding lines of rice were discriminated for their ability to tolerate drought stress at reproductive stage. Experimental materials consisting of 17 advance breeding lines and a check were evaluated in randomized block design with three replications under irrigated condition and drought condition created under rainout shelter during three consecutive years. An analysis of variance revealed significant differences among the genotypes for all the ten agro-morphological characters evaluated under both the conditions across the years. Principal component analysis showed the relative importance of root length, number of tillers per plant, number of grains per panicle, harvest index and grain yield per plant among agro-morphological characters and stress tolerance level, stress susceptibility index, stress tolerance index and drought tolerance efficiency among drought tolerance indices as the important classification variables. Relative mean performance in respect of grain yield as well as drought tolerance indices reflected remarkably greater degree of drought tolerance in 11 advance breeding lines and the check, discriminating them from remaining entries under evaluation. Utilizing a panel of 32 microsatellite primers, selective amplification of targeted genomic regions revealed that the primers RM 72, RM 163, RM 212, RM 225, RM 231, RM 302, RM 327, RM 518, RM 521, RM 555, RM 1349, RM 3549 and RM 5443 were highly informative with greater gene diversity and discrimination ability. Hierarchical cluster analysis based on molecular profiles discriminated the entries into five genotypic groups and drought tolerant entries were accommodated into three distinct groups with remarkably greater efficiency (85.7%). Principal coordinate analysis based two dimensional plots of microsatellites dependent genetic profiles displayed a very close correspondence with the genotypic clustering pattern revealed from a perusal of dendrogram. Sequential exclusion of primers in cluster analysis led to identification of RM 212, RM 231, RM 324, RM 431, RM 521, RM 3549 and RM 6374 as the most useful primers for discrimination of drought tolerant and susceptible lines of rice. Molecular profiling based on these markers can be utilized as efficient tools for discrimination and identification of drought tolerant lines.

     

Genetic mapping of QTLs for sugar-related traits in a RIL population of Sorghum bicolor L. Moench

The productivity of sorghum is mainly determined by quantitative traits such as grain yield and stem sugar-related characteristics. Substantial crop improvement has been achieved by breeding in the last decades. Today, genetic mapping and characterization of quantitative trait loci (QTLs) is considered a valuable tool for trait enhancement. We have investigated QTL associated with the sugar components (Brix, glucose, sucrose, and total sugar content) and sugar-related agronomic traits (flowering date, plant height, stem diameter, tiller number per plant, fresh panicle weight, and estimated juice weight) in four different environments (two locations) using a population of 188 recombinant inbred lines (RILs) from a cross between grain (M71) and sweet sorghum (SS79). A genetic map with 157 AFLP, SSR, and EST-SSR markers was constructed, and several QTLs were detected using composite interval mapping (CIM). Further, additive × additive interaction and QTL × environmental interaction were estimated. CIM identified more than five additive QTLs in most traits explaining a range of 6.0–26.1% of the phenotypic variation. A total of 24 digenic epistatic locus pairs were identified in seven traits, supporting the hypothesis that QTL analysis without considering epistasis can result in biased estimates. QTLs showing multiple effects were identified, where the major QTL on SBI-06 was significantly associated with most of the traits, i.e., flowering date, plant height, Brix, sucrose, and sugar content. Four out of ten traits studied showed a significant QTL × environmental interaction. Our results are an important step toward marker-assisted selection for sugar-related traits and biofuel yield in sorghum.     

QTL mapping reveals the genetic architecture of loci affecting pre- and post-zygotic isolating barriers in Louisiana Iris

ABSTRACT: BACKGROUND: Hybridization among Louisiana Irises has been well established and the genetic architecture of reproductive isolation is known to affect the potential for and the directionality of introgression between taxa. Here we use co-dominant markers to identify regions where QTL are located both within and between backcross maps to compare the genetic architecture of reproductive isolation and fitness traits across treatments and years. RESULTS: QTL mapping was used to elucidate the genetic architecture of reproductive isolation between Iris fulva and Iris brevicaulis. Homologous co-dominant EST-SSR markers scored in two backcross populations between I. fulva and I. brevicaulis were used to generate genetic linkage maps. These were used as the framework for mapping QTL associated with variation in 11 phenotypic traits likely responsible for reproductive isolation and fitness. QTL were dispersed throughout the genome, with the exception of one region of a single linkage group (LG) where QTL for flowering time, sterility, and fruit production clustered. In most cases, homologous QTL were not identified in both backcross populations, however, homologous QTL for flowering time, number of growth points per rhizome, number of nodes per inflorescence, and number of flowers per node were identified on several linkage groups. CONCLUSION: Two different traits affecting reproductive isolation, flowering time and sterility, exhibit different genetic architectures, with numerous QTL across the Iris genome controlling flowering time and fewer, less distributed QTL affecting sterility. QTL for traits affecting fitness are largely distributed across the genome with occasional overlap, especially on LG 4, where several QTL increasing fitness and decreasing sterility cluster. Given the distribution and effect direction of QTL affecting reproductive isolation and fitness, we have predicted genomic regions where introgression may be more likely to occur (those regions associated with an increase in fitness and unlinked to loci controlling reproductive isolation) and those that are less likely to exhibit introgression (those regions linked to traits decreasing fitness and reproductive isolation).     

Association mapping of grain color,phenolic content,flavonoid content and antioxidant capacity in dehulled rice

Phytochemicals such as phenolics and flavonoids in rice grain are antioxidants that are associated with reduced risk of developing chronic diseases including cardiovascular disease, type-2 diabetes and some cancers. Understanding the genetic basis of these traits is necessary for the improvement of nutritional quality by breeding. Association mapping based on linkage disequilibrium has emerged as a powerful strategy for identifying genes or quantitative trait loci (QTL) underlying complex traits in plants. In this study, genome-wide association mapping using models controlling both population structure (Q) and relative kinship (K) were performed to identify the marker loci/QTLs underlying the naturally occurring variations of grain color and nutritional quality traits in 416 rice germplasm accessions including red and black rice. A total of 41 marker loci were identified for all the traits, and it was confirmed that Ra (i.e., Prp-b for purple pericarp) and Rc (brown pericarp and seed coat) genes were main-effect loci for rice grain color and nutritional quality traits. RM228, RM339, fgr (fragrance gene) and RM316 were important markers associated with most of the traits. Association mapping for the traits of the 361 white or non-pigmented rice accessions (i.e., excluding the red and black rice) revealed a total of 11 markers for four color parameters, and one marker (RM346) for phenolic content. Among them, Wx gene locus was identified for the color parameters of lightness (L*), redness (a*) and hue angle (H ^o). Our study suggested that the markers identified in this study can feasibly be used to improve nutritional quality or health benefit properties of rice by marker-assisted selection if the co-segregations of the marker–trait associations are validated in segregating populations.     

Genetic mapping of QTLs affecting productivity and plant architecture in a full-sib cross from non-inbred parents in Cassava (<Emphasis Type="Italic">Manihot esculenta</Emphasis> Crantz)

An attempt was made to identify quantitative trait loci (QTLs) for several productivity and plant architecture traits in a full-sib progeny of 144 individuals from two non-inbred parents in cassava. A molecular linkage map of this cross constructed previously with over 250 markers was the source of molecular markers. The progeny were grown under field conditions at two locations (Palmira and Quilichao) in Colombia and evaluated in 2 years (1998 and 1999) for architecture and productivity traits. Architecture traits evaluated were plant height (PH), branching height (BH), branching levels (BL), branching index (BI), stem portion with leaves (SPL) and leaf area index (LAI). Productivity traits were those related to total dry matter production and distribution, namely fresh root yield (FRY), fresh shoot yield (FSY), harvest index (HI) and the number of storage roots (NR). Phenotypic evaluation of the traits in this population revealed continuous variation for all traits. Broad-sense heritability estimates, ranged from 36% (for NR) to 94% (for BH). Several significant phenotypic correlations were observed between architecture and productivity traits. Primary QTLs, using the single-QTL model, and secondary QTLs, by a primary QTL interaction model, were detected by interval mapping. A total of 30 primary QTLs and 84 secondary QTLs were detected. We identified 35% of detected QTLs in two or more trials, the other QTLs were environment-specific. These results underscore the significant genotype × environment interactions found for most of the traits. Several genomic segments affecting multiple traits were identified and were in agreement with correlation among traits. All QTLs identified for FRY were found associated with either component traits of productivity or architecture traits. This study suggests that QTLs for plant architecture can be used to improve productivity. However an exhaustive search and analysis of QTLs controlling architecture is required before marker-assisted selection (MAS) for increasing productivity can be initiated.Communicated by H. C. Becker     

Mapping quantitative trait loci for yield,yield components and morphological traits in an advanced backcross population between <Emphasis Type="Italic">Oryza rufipogon</Emphasis> and the <Emphasis Type="Italic">Oryza sativa</Emphasis> cultivar Jefferson

An advanced backcross population between an accession of Oryza rufipogon (IRGC 105491) and the U.S. cultivar Jefferson (Oryza sativa ssp. japonica) was developed to identify quantitative trait loci (QTLs) for yield, yield components and morphological traits. The genetic linkage map generated for this population consisted of 153 SSR and RFLP markers with an average interval size of 10.3 cM. Thirteen traits were examined, nine of which were measured in multiple environments. Seventy-six QTLs above an experiment-wise significance threshold of P<0.01 (corresponding to an interval mapping LOD>3.6 or a composite interval mapping LOD>3.9) were identified. For the traits measured in multiple environments, 47% of the QTLs were detected in at least two environments. The O. rufipogon allele was favorable for 53% of the yield and yield component QTLs, including loci for yield, grains per panicle, panicle length, and grain weight. Morphological traits related to the domestication process and/or weedy characteristics, including plant height, shattering, tiller type and awns, were found clustered on chromosomes 1 and 4. Comparisons to previous studies involving wild x cultivated crosses revealed O. rufipogon alleles with stable effects in multiple genetic backgrounds and environments, several of which have not been detected in studies between Oryza sativa cultivars, indicating potentially novel alleles from O. rufipogon. Some O. rufipogon-derived QTLs, however, were in similar regions as previously reported QTLs from Oryza sativa cultivars, providing evidence for conservation of these QTLs across the Oryza genus. In addition, several QTLs for grain weight, plant height, and flowering time were localized to putative homeologous regions in maize where QTLs for these traits have been previously reported, supporting the hypothesis of functional conservation of QTLs across the grasses.     

Association mapping validates previously identified quantitative trait loci for salt tolerance in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

Salinity is the main abiotic stress that limits rice (Oryza sativa L.) production worldwide. An association mapping project was designed to validate quantitative trait loci (QTLs) in rice associated with Na⁺, K⁺ and Ca⁺⁺ accumulation traits identified in our previous study of linkage mapping. Twenty four varieties/lines of rice were phenotyped for biochemical and yield traits. Among these varieties/lines, two mapping parents, Pokkali and IR-36, of our previous linkage mapping study were also included. For marker-trait assessments, both general linear model (GLM) and mixed linear model (MLM) analyses were performed. Thirteen significant marker-trait associations at P ≤ 0.001 were identified. Associated markers for these marker-trait associations were RM503, RM225, RM152, and RM254 located on chromosomes 3, 6, 8, and 11, respectively. Previously identified QTLs in linkage mapping study for Na⁺ uptake, Ca⁺⁺ uptake, total cations uptake, Ca⁺⁺ uptake ratio, K⁺ uptake ratio, and Na⁺/K⁺ uptake were validated in this study. Heritability values for these traits ranged from 1.00e-05 to 1. Linked markers for these validated QTLs were RM140, RM243, RM203, RM480, RM137, and RM254 located on chromosomes 1, 1, 3, 5, 8, and 11, respectively. These markers will be a valuable resource for marker-assisted breeding (MAB) approach to develop elite salt tolerant rice cultivars. This study demonstrates the potential of association mapping approach to validate previously identified QTLs.     

Identification of candidate markers associated with agronomic traits in rice using discriminant analysis

Plant genetic mapping strategies routinely utilize marker genotype frequencies obtained from progeny of controlled crosses to declare presence of a quantitative trait locus (QTL) on previously constructed linkage maps. We have evaluated the potential of discriminant analysis (DA), a multivariate statistical procedure, to detect candidate markers associated with agronomic traits among inbred lines of rice (Oryza sativa L.). A total of 218 lines originating from the US and Asia were planted in field plots near Alvin, Texas, in 1996 and 1997. Agronomic data were collected for 12 economically important traits, and DNA profiles of each inbred line were produced using 60 SSR and 114 RFLP markers. Model-based methods revealed population structure among the lines. Marker alleles associated with all traits were identified by DA at high levels of correct percent classification within subpopulations and across all lines. Associated marker alleles pointed to the same and different regions on the rice genetic map when compared to previous QTL mapping experiments. Results from this study suggest that candidate markers associated with agronomic traits can be readily detected among inbred lines of rice using DA combined with other methods described in this report.N. Zhang and Y. Xu contributed equally to work and considered as first authors.Approved for publication by the Director of the Louisiana Agricultural Experiment Station as paper no. 04-14-0335.     

Mapping and characterisation of QTL × E interactions for traits determining grain and stover yield in pearl millet

A mapping population of 104 F(3) lines of pearl millet, derived from a cross between two inbred lines H 77/833-2 x PRLT 2/89-33, was evaluated, as testcrosses on a common tester, for traits determining grain and stover yield in seven different field trials, distributed over 3 years and two seasons. The total genetic variation was partitioned into effects due to season (S), genotype (G), genotype x season interaction (G x S), and genotype x environment-within-season interaction [G x E(S)]. QTLs were determined for traits for their G, G x S, and G x E(S) effects, to assess the magnitude and the nature (cross over/non-crossover) of environmental interaction effects on individual QTLs. QTLs for some traits were associated with G effects only, while others were associated with the effects of both G and G x S and/or G, G x S and G x E(S) effects. The major G x S QTLs detected were for flowering time (on LG 4 and LG 6), and mapped to the same intervals as G x S QTLs for several other traits (including stover yield, harvest index, biomass yield and panicle number m(-2)). All three QTLs detected for grain yield were unaffected by G x S interaction however. All three QTLs for stover yield (mapping on LG 2, LG 4 and LG 6) and one of the three QTLs for grain yield (mapping on LG 4) were also free of QTL x E(S) interactions. The grain yield QTLs that were affected by QTL x E(S) interactions (mapping on LG 2 and LG 6), appeared to be linked to parallel QTL x E(S) interactions of the QTLs for panicle number m(-2) on (LG 2) and of QTLs for both panicle number m(-2) and harvest index (LG 6). In general, QTL x E(S) interactions were more frequently observed for component traits of grain and stover yield, than for grain or stover yield per se.     

Genetic studies of yield contributing traits in Amaranthus

Summary Genetical studies on grain yield and its contributing traits were made in a six parent complete diallel in the F₁ and F₂ generations of one of the most widely grown grain species of grain amaranths (Amaranthus hypochondriacus L.). Graphical analysis indicated that epistasis exists for 1,000-grain weight in the F₁. Grain weight/panicle, yield/plant and harvest index indicated absence of non-allelic gene interaction. The harvest index in the F₁ and F₂ and grain weight/ panicle, 1,000-grain weight, yield/plant in the F₂ appeared to be controlled by overdominance effects. Higher grain yield appeared to be associated with dominant genes. Both additive and non-additive gene effects were responsible for the genetic variation in the diallel population. However, dominance variance was more important than additive variance in grain yield/ plant and harvest index in the F₁ and F₂. For 1,000-grain weight additive genetic variance was more important in the F₁ and non-additive in F₂. There was overdominance of a consistent nature in the two analyses for harvest index in the F₁ and F₂, grain weight/ panicle, 1,000-grain weight and yield/plant in the F₂ and partial dominance for 1,000-grain weight in the F₁.     

Inheritance studies of SSR and ISSR molecular markers and phylogenetic relationship of rice genotypes resistant to tungro virus

Multivariate analyses were performed using 13 morphological traits and 13 molecular markers (10 SSRs and three ISSRs) to assess the phylogenetic relationship among tungro resistant genotypes. For morphological traits, the genotypes were grouped into six clusters, according to D² statistic and Canonical vector analysis. Plant height, days to flowering, days to maturity, panicle length, number of spikelet per panicle, number of unfilled grain per panicle and yield were important contributors to genetic divergence in 14 rice genotypes. Based on Nei's genetic distance for molecular studies, seven clusters were formed among the tungro resistant and susceptible genotypes. Mantel's test revealed a significant correlation (r = 0.834*) between the morphological and molecular data. To develop high yielding tungro resistant varieties based on both morphological and molecular analyses, crosses could be made with susceptible (BR10 and BR11) genotypes with low yielding but highly resistant genotypes, Sonahidemota, Kumragoir, Nakuchimota, Khaiyamota, Khairymota and Kachamota. The chi-square analysis for seven alleles (RM11, RM17, RM20, RM23, RM80, RM108 and RM531) of SSR and five loci (RY1, MR1, MR2, MR4 and GF5) of three ISSR markers in F₂ population of cross, BR11 × Sonahidemota, showed a good fit to the expected segregation ratio (1:2:1) for a single gene model.     

A mixed model QTL analysis for sugarcane multiple-harvest-location trial data

Sugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane.     

Trait diversity, heritability and genetic advance in selected germplasm lines of tef

The genetic improvement of the Ethiopian cereal, tef, Eragrostis tef (Zucc.) Trotter, depends upon the variability in the indigenous germplasm. A bi-replicated randomized complete block field experiment was, therefore, carried out at Debre Zeit and Alem Tena in Ethiopia during the 1996 main season to study the pheno-morphic and agronomic trait diversity in 320 tef germplasm lines. All of the 17 traits assessed showed substantial (p < or = 0.001) variation among the lines. Genotypes and locations interacted significantly (p < or = 0.05) on 11 of the traits. At about 50% similarity level, the tef lines grouped into six major clusters of nine to 243 lines. Five principal components (PCs) extracted about 71% of the entire variation of the lines. About 28% of the total variance explained by the first PC was due chiefly to variation in main shoot culm length, diameters of the two basal culm internodes, panicle length and grain yield/panicle. About 16% of the whole variance explained by the second PC originated mainly from variation in the length of the first and second basal culm internodes, grain yield/plant, and peduncle length. The third PC accounting for about 12% of the entire variance resulted largely from variation in harvest index and shoot phytomass yield/plant. Across traits, the phenotypic and genotypic coefficients of variation varied in that order from about 2% for grain yield/panicle to 58% for number of fertile tillers/plant, and from less than 1% for diameters of the two basal culm internodes and grain yield/panicle to 35% for panicle length. Estimates of broad sense heritability and genetic advance (as ratio of the mean) were highest for panicle length (71%) and number of fertile tillers/plant (21%), respectively. But both of these were lowest for the second basal culm internode diameter (< 1%). Overall, the study confirmed that tef is a highly versatile crop with broad trait diversity in the germplasm, and this offers ample opportunities for improvement through breeding.     

Identification of QTL for growth- and grain yield-related traits in rice across nine locations of Asia

Rice double-haploid (DH) lines of an indica and japonica cross were grown at nine different locations across four countries in Asia. Genotype-by-environment (G x E) interaction analysis for 11 growth- and grain yield-related traits in nine locations was estimated by AMMI analysis. Maximum G x E interaction was exhibited for fertility percentage number of spikelets and grain yield. Plant height was least affected by environment, and the AMMI model explained a total of 76.2% of the interaction effect. Mean environment was computed by averaging the nine environments and subsequently analyzed with other environments to map quantitative trait loci (QTL). QTL controlling the 11 traits were detected by interval analysis using mapmaker/qtl. A threshold LOD of >/=3.20 was used to identify significant QTL. A total of 126 QTL were identified for the 11 traits across nine locations. Thirty-four QTL common in more than one environment were identified on ten chromosomes. A maximum of 44 QTL were detected for panicle length, and the maximum number of common QTL were detected for days to heading detected. A single locus for plant height (RZ730-RG810) had QTL common in all ten environments, confirming AMMI results that QTL for plant height were affected the least by environment, indicating the stability of the trait. Two QTL were detected for grain yield and 19 for thousand-grain weight in all DH lines. The number of QTL per trait per location ranged from zero to four. Clustering of the QTL for different traits at the same marker intervals was observed for plant height, panicle number, panicle length and spikelet number suggesting that pleiotropism and or tight linkage of different traits could be the possible reason for the congruence of several QTL. The many QTL detected by the same marker interval across environments indicate that QTL for most traits are stable and not essentially affected by environmental factors.