Determining the linkage of quantitative trait loci to RFLP markers using extreme phenotypes of recombinant inbreds of soybean (Glycine max L. Merr.)

An experimental test is described for linkages between RFLP markers and quantitative trait loci (QTL). Two hundred and eighty-four F₇-derived recombinant inbred lines (RIL) obtained from crossing the soybean cultivars (Glycine max L. Merr.) Minsoy and Noir 1 were evaluated for maturity, plant height, lodging, and seed yield. RIL exhibiting an extreme phenotype for each trait (earliest and latest plants for maturity, etc.) were selected, and two bulked DNA samples were prepared for each trait. A Southern transfer of the digested bulked DNA was hybridized with restriction fragement length polymorphism (RFLP) probes, and linkages with QTL were established by quantitating the amount of radioactive probe that bound to fragments defining alternative parental RFLP alleles. When an RFLP marker was linked to a QTL, one parental allele predominated in the bulked DNA from a particular phenotype; the other allele was associated with the opposite phenotype. When linkage was absent, radioactivity was associated equally with both alleles for a given phenotype (or with both phenotypes for a given allele). These results confirmed RFLP-QTL associations previously discovered by interval mapping on a smaller segregating population from the same cross. New linkages to QTL were also verified.     

Interval mapping of quantitative trait loci for reproductive,morphological, and seed traits of soybean (Glycine max L.)

Quantitative trait loci (QTL) were mapped in segregating progeny from a cross between two soybean (Glycine max (L.) Merr.) cultivars: Minsoy (PI 27.890) and Noir 1 (PI 290.136). The 15 traits analyzed included reproductive, morphological, and seed traits, seed yield and carbon isotope discrimination ratios (¹³C/¹²C). Genetic variation was detected for all of the traits, and transgressive segregation was a common phenomenon. One hundred and thirty-two linked genetic markers and 24 additional unlinked markers were used to locate QTL by interval mapping and one-way analysis of variance, respectively. Quantitative trait loci controlling 11 of the 15 traits studied were localized to intervals in 6 linkage groups. Quantitative trait loci for developmental and morphological traits (R1, R5, R8, plant height, canopy height, leaf area, etc.) tended to be clustered in three intervals, two of which were also associated with seed yield. Quantitative trait loci for seed oil were separated from all the other QTL. Major QTL for maturity and plant height were linked to RFLP markers R79 (31% variation) and G173 (53% variation). Quantitative trait loci associated with unlinked markers included possible loci for seed protein and weight. Linkage between QTL is discussed in relation to the heritability and genetic correlation of the traits.     

Quantitative trait loci influencing protein and starch concentration in the Illinois Long Term Selection maize strains

A study was initiated to determine the number, chromosomal location, and magnitude of effect of QTL (quantitative trait loci or locus depending on context) controlling protein and starch concentration in the maize (Zea mays L.) kernel. Restriction fragment length polymorphism (RFLP) analysis was performed on 100 F₃ families derived from a cross of two strains, Illinois High Protein (IHP), X Illinois Low Protein (ILP), which had been divergently selected for protein concentration for 76 generations as part of the Illinois Long Term Selection Experiment. These families were analyzed for kernel protein and starch in replicated field trials during 1990 and 1991. A series of 90 genomic and cDNA clones distributed throughout the maize genome were chosen for their ability to detect RFLP between IHP and ILP. These clones were hybridized with DNA extracted from the 100 F₃ families, revealing 100 polymorphic loci. Single factor analysis of variance revealed significant QTL associations of many loci with both protein and starch concentration (P < 0.05 level). Twenty-two loci distributed on 10 chromosome arms were significantly associated with protein concentration, 19 loci on 9 chromosome arms were significantly associated with starch concentration. Sixteen of these loci were significant for both protein and starch concentration. Clusters of 3 or more significant loci were detected on chromosome arms 3L, 5S, and 7L for protein concentration, suggesting the presence of QTL with large effects at these locations. A QTL with large additive effects on protein and starch concentration was detected on chromosome arm 3L. RFLP alleles at this QTL were found to be linked with RFLP alleles at the Shrunken-2 (Sh2) locus, a structural gene encoding the major subunit of the starch synthetic enzyme ADP-glucose pyrophosphorylase. A multiple linear regression model consisting of 6 significant RFLP loci on different chromosomes explained over 64 % of the total variation for kernel protein concentration. Similar results were detected for starch concentration. Thus, several chromosomal regions with large effects may be responsible for a significant portion of the changes in kernel protein and starch concentration in the Illinois Long Term Selection Experiment.     

Genotype and phenotype associations with drought tolerance in barley tested in North Africa

A review is presented of genetic strategies deployed in a 3-yr project on drought tolerance in barley. Data were collected on genetic, physiological and agronomic traits in non-irrigated and irrigated field trials in Egypt, Morocco and Tunisia. A wide range of barley germplasm (developed from African and European cultivars, adapted landraces and wild barleys) was tested, and positive traits were found in each gene pool. The contrasting environments of the three North African countries had major effects on plant/genotype performance. Genetic effects were also detected, as were genotype × environment interactions. A range of strategies were deployed to investigate the physiology and genetics of quantitative traits associated with field performance. Quantitative trait locus (QTL) analysis was performed using backcross lines, recombinant inbred lines and doubled haploid mapping populations. A detailed genetic map was generated in the Tadmor × (ER/Apm) recombinant inbred lines, an important mapping population specifically developed by ICARDA (Centre for Agricultural Research in Dry Areas) and CIMMYT (International Maize and Wheat Improvement Center) to study drought. Quantitative trait loci (QTLs) for grain yield and other important morphological and physiological traits were also identified in a population of doubled haploids derived from F2BCj plants from a cross between a cultivar and a wild barley accession. Significantly, the wild parental line was found to contribute a number of positive alleles for yield. Effects of major developmental genes could explain many of the responses observed. QTLs were found to cluster around major genes controlling flowering time (sghI), plant stature (sdwI and arie.GP) and ear type (vrsl), and it is highly likely that the associations represent pleiotropic effects. Some QTLs were associated with candidate genes such as dehydrins and rubisco activase. One of the most significant results was the identification and generation of material that out performed the best local standards in the three participating North African countries; the selected lines have now entered local breeding programmes. The strategies adopted provided information on physiological traits, genotypes and genetic markers that could be used for marker-assisted selection. Target QTLs and their associated genetic markers may be deployed in marker assisted selection programmes to match crop phenology to the field environment.     

Linkage between loci of quantitative traits and marker loci: multi-trait analysis with a single marker

An efficient approach to increase the resolution power of linkage analysis between a quantitative trait locus (QTL) and a marker is described in this paper. It is based on a counting of the correlations between the QTs of interest. Such correlations may be caused by the segregation of other genes, environmental effects and physiological limitations. Let a QT locus A/a affect two correlated traits, x and y. Then, within the framework of mixture models, the accuracy of the parameter estimates may be seriously increased, if bivariate densities f _aa(x, y), f _Aa(x, y) and f _AA(x, y) rather than the marginals are considered as the basis for mixture decomposition. The efficiency of the proposed method was demonstrated employing Monte-Carlo simulations. Several types of progeny were considered, including backcross, F₂ and recombinant inbred lines. It was shown that provided the correlation between the traits involved was high enough, a good resolution to the problem is possible even if the QTL groups are strongly overlapping for their marginal densities.     

Quantitative trait analysis of fruit quality in cucumber: QTL detection,confirmation, and comparison with mating-design variation

A cross within C. sativus var. sativus (GY14 x P1432860) and molecular markers were used to determine the number, magnitudes of effect, and overall variation described for genes conditioning the quantitatively inherited traits of length, diameter, seed-cavity size, color, L/D (length/diameter), and S/D (seed-cavity size/diameter). QTL effects were detected with MAPMAKER/QTL using 100 F₃ lines evaluated in a replicated field trial of two harvests over 2 years at one location. Multilocus models were constructed by fixing significant intervals and re-scanning using MAPMAKER/ QTL. Marker inclusion in multilocus models was compared to an ANOVA backward elimination procedure. Generally the same loci were associated with QTLs among the two methods of model construction. Heritabilities of individual QTLs were confirmed by analysis of related backcrosses (67 BC₁P₁ lines and 68 BC₁ P₂ lines). The majority of QTLs were confirmed in at least one backcross population. Pairs of backcrosses allowed overall additive variances and heritabilities to be calculated using a North Carolina Design III (NCIII design) and estimates were compared to overall variances attributable to markers. Heritability estimates using markers were comparable, but generally lower than additive variances estimated by co-variance relationships in the NCIII design. This suggests that neither the number nor the magnitude of QTL effects were overestimated. The utility of backcrosses to confirm individual QTLs and the overall variance described by QTLs is recommended to avoid false positives and over-estimation of effects. The number of QTLs, and/or the proportions of phenotypic variation described by markers and the mating design, agreed with previous reports of heritabilities employing similar germplasm.     

Characterization of quantitative trait loci (QTLs) in cultivated rice contributing to field resistance to sheath blight (Rhizoctonia solani)

Sheath blight, caused by Rhizoctonia solani, is one of the most important diseases of rice. Despite extensive searches of the rice germ plasm, the major gene(s) which give complete resistance to the fungus have not been identified. However, there is much variation in quantitatively inherited resistance to R. solani, and this type of resistance can offer adequate protection against the pathogen under field conditions. Using 255 F₄ bulked populations from a cross between the susceptible variety Lemont and the resistant variety Teqing, 2 years of field disease evaluation and 113 well-distributed RFLP markers, we identified six quantitative trait loci (QTLs) contributing to resistance to R. solani. These QTLs are located on 6 of the 12 rice chromosomes and collectively explain approximately 60% of the genotypic variation or 47% of the phenotypic variation in the LemontxTeqing cross. One of these resistance QTLs (QSbr4a), which accounted for 6% of the genotypic variation in resistance to R. solani, appeared to be independent of associated morphological traits. The remaining five putative resistance loci (QSbr2a, QSbr3a, QSbr8a, QSbr9a and QSbr12a) all mapped to chromosomal regions also associated with increased plant height, three of which were also associated with QTLs causing later heading. This was consistent with the observation that heading date and plant height accounted for 47% of the genotypic variation in resistance to R. solani in this population. There were also weak associations between resistance to R. solani and leaf width, which were likely due to linkage with a QTL for this trait rather than to a physiological relationship.     

Combined genetic and physiological analysis of a locus contributing to quantitative variation

The natural variation of many traits is controlled by multiple genes, individually referred to as quantitative trait loci (QTL), that interact with the environment to determine the ultimate phenotype of any individual. A QTL has yet to be described molecularly, in part because strategies to systematically identify them are underdeveloped and because the subtle nature of QTLs prevents the application of standard methods of gene identification. Therefore, it will be necessary to develop a systematic approach(es) for the identification of QTLs based upon the numerous positional data now being accumulated through molecular marker analyses. We have characterized a QTL by the following three-step approach: (1) identification of a QTL in complex populations, (2) isolation and genetic mapping of this QTL in near-isogenic lines, and (3) identification of a candidate gene using map position and physiological criteria. Using this approach we have characterized a plant height QTL in maize that maps to chromosome 9 near the centromere. Both map position and physiological criteria suggest the gibberillin biosynthesis gene dwarf3 as a candidate gene for this QTL.     

布氏田鼠肥满度分析和小型兽类肥满度指标K与KWL（重长指标）的比较

通过对两个肥满度指标的理论和生物学意义分析,以及对布氏田鼠肥满度的研究和实际应用的讨论,认为描述动物的肥满度时,重长指标ＫＷＬ优于指标Ｋ。两指标的最大差别是成体的ＫＷＬ值大于幼体,而成体的Ｋ值小于幼体。布氏田鼠肥满度没有性别差异;有异著的年龄差异,成体鼠的肥满度高于幼鼠;有显著的季节变化,鼠种群春季肥满度最高,夏季降低,秋季回升;有显著的年际变化,高数量年的肥满度高于低数量年。     

Mapping QTL for production traits in segregating Piétrain pig populations using genome‐wide association study results of F2 crosses

In this study, genome‐wide association study (GWAS) results of porcine F2 crosses were used to map QTL in outcross Piétrain populations. For this purpose, two F2 crosses (Piétrain × Meishan, n = 304; Piétrain × Wild Boar, n = 291) were genotyped with the PorcineSNP60v2 BeadChip and phenotyped for the dressing yield, carcass length, daily gain and drip loss traits. GWASs were conducted in the pooled F2 cross applying single marker mixed linear models. For the investigated traits, between two and five (in total 15) QTL core regions, spanning 250 segregating SNPs around a significant trait‐associated peak SNP, were identified. The SNPs within the QTL core regions were subsequently tested for trait association in two outcross Piétrain populations consisting of 771 progeny‐tested boars and 210 sows with their own performance records. In the sow (boar) dataset, five (eight) of the 15 mapped QTL were validated. Hence, many QTL mapped in the F2 crosses (with Piétrain as a common founder breed) are still segregating in the current Piétrain breed. This confirms the usefulness of existing F2 crosses for mapping QTL that are still segregating in the recent founder breed generation. The approach utilizes the high power of an F2 cross to map QTL in a breeding population for which it is not guaranteed that they would be found using a GWAS in this population.