A large QTL for fear and anxiety mapped using an F2 cross can be dissected into multiple smaller QTLs

Using chromosome substitution strains (CSS), we previously identified a large quantitative trait locus (QTL) for conditioned fear (CF) on mouse chromosome 10. Here, we used an F₂ cross between CSS‐10 and C57BL/6J (B6) to localize that QTL to distal chromosome 10. That QTL accounted for all the difference between CSS‐10 and B6. We then produced congenic strains to fine‐map that interval. We identified two congenic strains that captured some or all the QTL. The larger congenic strain (Line 1: 122.387121–129.068 Mb; build 37) appeared to account for all the difference between CSS‐10 and B6. The smaller congenic strain (Line 2: 127.277–129.068 Mb) was intermediate between CSS‐10 and B6. We used haplotype mapping followed by quantitative polymerase chain reaction to identify one gene that was differentially expressed in both lines relative to B6 (Rnf41) and one that was differentially expressed between only Line 1 and B6 (Shmt2). These cis‐eQTLs may cause the behavioral QTLs; however, further studies are required to validate these candidate genes. More generally, our observation that a large QTL mapped using CSS and F₂ crosses can be dissected into multiple smaller QTLs shows a weaknesses of two‐stage approaches that seek to use coarse mapping to identify large regions followed by fine‐mapping. Indeed, additional dissection of these congenic strains might result in further subdivision of these QTL regions. Despite these limitations, we have successfully fine‐mapped two QTLs to small regions and identified putative candidate genes, showing that the congenic approach can be effective for fine‐mapping QTLs .     

Theory for identification of marker locus-QTL associations in population by line crosses

The objective of this paper is to present genetic theory demonstrating the conditions under which it should be possible to identify molecular marker-quantitative trait locus (QTL) associations in crosses of random-mating populations to inbreds. Using as an example the cross of a corn (Zea mays L.) population to an inbred, the expected disequilibrium for testcross and per se performance of F₂, F₃, BC₁ (to the inbred) and recombinant inbred generations was derived for cases where a marker allele is linked to an unfavorable QTL allele in the inbred and where the marker allele is linked to a favorable QTL allele in the inbred. Disequilibrium in segregating generations was shown to be a function of disequilibrium in the parent population, the frequency of marker and QTL alleles in the parent population, and the recombination distance between the marker and the QTL. To maximize the opportunity to identify a favorable QTL the following procedures are suggested:

Fine mapping a QTL qCTB7 for cold tolerance at the booting stage on rice chromosome 7 using a near-isogenic line

Low temperature at the booting stage is a serious abiotic stress in rice, and cold tolerance is a complex trait controlled by many quantitative trait loci (QTL). A QTL for cold tolerance at the booting stage in cold-tolerant near-isogenic rice line ZL1929-4 was analyzed. A total of 647 simple sequence repeat (SSR) markers distributed across 12 chromosomes were used to survey for polymorphisms between ZL1929-4 and the cold-sensitive japonica cultivar Towada, and nine were polymorphic. Single marker analysis revealed that markers on chromosome 7 were associated with cold tolerance. By interval mapping using an F₂ population from ZL1929-4 × Towada, a QTL for cold tolerance was detected on the long arm of chromosome 7. The QTL explained 9 and 21% of the phenotypic variances in the F₂ and F₃ generations, respectively. Recombinant plants were screened for two flanking markers, RM182 and RM1132, in an F₂ population with 2,810 plants. Two-step substitution mapping suggested that the QTL was located in a 92-kb interval between markers RI02905 and RM21862. This interval was present in BAC clone AP003804. We designated the QTL as qCTB7 (quantitative trait locus for cold tolerance at the booting stage on chromosome 7), and identified 12 putative candidate genes.     

Quantitative trait locus and haplotype mapping in closely related inbred strains identifies a locus for open field behavior

Quantitative trait locus (QTL) mapping in the mouse typically utilizes inbred strains that exhibit significant genetic and phenotypic diversity. The development of dense SNP panels in a large number of inbred strains has eliminated the need to maximize genetic diversity in QTL studies as plenty of SNP markers are now available for almost any combination of strains. We conducted a QTL mapping experiment using both a backcross (N₂) and an intercross (F₂) between two genetically similar inbred mouse strains: C57BL/6J (B6) and C57L/J (C57). A set of additive QTLs for activity behaviors was identified on Chrs 1, 9, 13, and 15. We also identified additive QTLs for anxiety-related behaviors on Chrs 7, 9, and 16. A QTL on Chr 11 is sex-specific, and we revealed pairwise interactions between QTLs on Chrs 1 and 13 and Chrs 10 and 18. The Chr 9 activity QTL accounts for the largest amount of phenotypic variance and was not present in our recent analysis of a B6 × C58/J (C58) intercross (Bailey et al. in Genes Brain Behav 7:761–769, 2008). To narrow this QTL interval, we used a dense SNP haplotype map with over 7 million real and imputed SNP markers across 74 inbred mouse strains (Szatkiewicz et al. in Mamm Genome 19(3):199–208, 2008). Evaluation of shared and divergent haplotype blocks among B6, C57, and C58 strains narrowed the Chr 9 QTL interval considerably and highlights the utility of QTL mapping in closely related inbred strains.     

Comparative mapping in F2∶3 and F6∶7 generations of quantitative trait loci for grain yield and yield components in maize

This study was conducted to compare maize quantitative trait loci (QTL) detection for grain yield and yield components in F₂₃ and F₆₇ recombinant inbred (RI) lines from the same population. One hundred and eighty-six F₆₇ RIs from a Mo17×H99 population were grown in a replicated field experiment and analyzed at 101 loci detected by restriction fragment length polymorphisms (RFLPs). Single-factor analysis of variance was conducted for each locus-trait combination to identify QTL. For grain yield, 6 QTL were detected accounting for 22% of the phenotypic variation. A total of 63 QTL were identified for the seven grain yield components with alleles from both parents contributing to increased trait values. Several genetic regions were associated with more than one trait, indicating possible linked and/or pleiotropic effects. In a comparison with 150 F₂₃ lines from the same population, the same genetic regions and parental effects were detected across generations despite being evaluated under diverse environmental conditions. Some of the QTL detected in the F₂₃ seem to be dissected into multiple, linked QTL in the F₆₇ generation, indicating better genetic resolution for QTL detection with RIs. Also, genetic effects at QTL are smaller in the F₆₇ generation for all traits.Abbreviations RFLPs Restriction fragment length polymorphisms - QTL quantitative trait loci - RIs recombinant inbreds Journal Paper no. J-16261 of the Iowa Agric and Home Economics Exp Stn Project no. 3134     

Two quantitative trait loci for prepulse inhibition of startle identified on mouse chromosome 16 using chromosome substitution strains

Prepulse inhibition (PPI) of acoustic startle is a genetically complex quantitative phenotype of considerable medical interest due to its impairment in psychiatric disorders such as schizophrenia. To identify quantitative trait loci (QTL) involved in mouse PPI, we studied mouse chromosome substitution strains (CSS) that each carry a homologous chromosome pair from the A/J inbred strain on a host C57BL/6J inbred strain background. We determined that the chromosome 16 substitution strain has elevated PPI compared to C57BL/6J (P = 1.6 x 10(-11)), indicating that chromosome 16 carries one or more PPI genes. QTL mapping using 87 F(2) intercross progeny identified two significant chromosome 16 loci with LODs of 3.9 and 4.7 (significance threshold LOD is 2.3). The QTL were each highly significant independently and do not appear to interact. Sequence variation between B6 and A/J was used to identify strong candidate genes in the QTL regions, some of which have known neuronal functions. In conclusion, we used mouse CSS to rapidly and efficiently identify two significant QTL for PPI on mouse chromosome 16. The regions contain a limited number of strong biological candidate genes that are potential risk genes for psychiatric disorders in which patients have PPI impairments.     

QTL-seq for rapid identification of candidate genes for flowering time in broccoli × cabbage

Key message

A major QTL controlling early flowering in broccoli × cabbage was identified by marker analysis and next-generation sequencing, corresponding to GRF6 gene conditioning flowering time in Arabidopsis.

Abstract

Flowering is an important agronomic trait for hybrid production in broccoli and cabbage, but the genetic mechanism underlying this process is unknown. In this study, segregation analysis with BC₁P1, BC₁P2, F₂, and F_2:3 populations derived from a cross between two inbred lines “195” (late-flowering) and “93219” (early flowering) suggested that flowering time is a quantitative trait. Next, employing a next-generation sequencing-based whole-genome QTL-seq strategy, we identified a major genomic region harboring a robust flowering time QTL using an F₂ mapping population, designated Ef2.1 on cabbage chromosome 2 for early flowering. Ef2.1 was further validated by indel (insertion or deletion) marker-based classical QTL mapping, explaining 51.5% (LOD = 37.67) and 54.0% (LOD = 40.5) of the phenotypic variation in F₂ and F_2:3 populations, respectively. Combined QTL-seq and classical QTL analysis narrowed down Ef1.1 to a 228-kb genomic region containing 29 genes. A cabbage gene, Bol024659, was identified in this region, which is a homolog of GRF6, a major gene regulating flowering in Arabidopsis, and was designated BolGRF6. qRT-PCR study of the expression level of BolGRF6 revealed significantly higher expression in the early flowering genotypes. Taken together, our results provide support for BolGRF6 as a possible candidate gene for early flowering in the broccoli line 93219. The identified candidate genomic regions and genes may be useful for molecular breeding to improve broccoli and cabbage flowering times.

     

Mapping QTL controlling maize deep-seeding tolerance-related traits and confirmation of a major QTL for mesocotyl length

Deep-seeding tolerant seeds can emerge from deep soil where the moisture is suitable for seed germination. Breeding deep-seeding tolerant cultivars is becoming increasingly important in arid and semi-arid regions. To dissect the quantitative trait loci (QTL) controlling deep-seeding tolerance traits, we selected a tolerant maize inbred line 3681-4 and crossed it with the elite inbred line-X178 to generate an F₂ population and the derivative F_2:3 families. A molecular linkage map composed of 179 molecular markers was constructed, and 25 QTL were detected including 10 QTL for sowing at 10 cm depth and 15 QTL for sowing at 20 cm depth. The QTL analysis results confirmed that deep-seeding tolerance was mainly caused by mesocotyl elongation and also revealed considerable overlap among QTL for different traits. To confirm a major QTL on chromosome 10 for mesocotyl length measured at 20 cm depth, we selected and self-pollinated a BC₃F₂ plant that was heterozygous at the markers around the target QTL and homozygous at other QTL to generate a BC₃F₃ population. We found that this QTL explained more phenotypic variance in the BC₃F₃ population than that in the F₂ population, which laid the foundation for fine mapping and NIL (near-isogenic line) construction.     

Comparative genome-wide mapping versus extreme pool-genotyping and development of diagnostic SNP markers linked to QTL for adult plant resistance to stripe rust in common wheat

Key message

A major stripe rust resistance QTL on chromosome 4BL was localized to a 4.5-Mb interval using comparative QTL mapping methods and validated in 276 wheat genotypes by haplotype analysis.

Abstract

CYMMIT-derived wheat line P10103 was previously identified to have adult plant resistance (APR) to stripe rust in the greenhouse and field. The conventional approach for QTL mapping in common wheat is laborious. Here, we performed QTL detection of APR using a combination of genome-wide scanning and extreme pool-genotyping. SNP-based genetic maps were constructed using the Wheat55 K SNP array to genotype a recombinant inbred line (RIL) population derived from the cross Mingxian 169?×?P10103. Five stable QTL were detected across multiple environments. After comparing SNP profiles from contrasting, extreme DNA pools of RILs six putative QTL were located to approximate chromosome positions. A major QTL on chromosome 4B was identified in F_2:4 contrasting pools from cross Zhengmai 9023?×?P10103. A consensus QTL (LOD?=?26–40, PVE?=?42–55%), named QYr.nwafu-4BL, was defined and localized to a 4.5-Mb interval flanked by SNP markers AX-110963704 and AX-110519862 in chromosome arm 4BL. Based on stripe rust response, marker genotypes, pedigree analysis and mapping data, QYr.nwafu-4BL is likely to be a new APR QTL. The applicability of the SNP-based markers flanking QYr.nwafu-4BL was validated on a diversity panel of 276 wheat lines. The additional minor QTL on chromosomes 4A, 5A, 5B and 6A enhanced the level of resistance conferred by QYr.nwafu-4BL. Marker-assisted pyramiding of QYr.nwafu-4BL and other favorable minor QTL in new wheat cultivars should improve the level of APR to stripe rust.

     

Genetic mapping of a major gene in triticale conferring resistance to bacterial leaf streak

Key message

A major gene conferring resistance to bacterial leaf streak was mapped to chromosome 5R in triticale.

Abstract

Bacterial leaf streak (BLS), caused by Xanthomonas translucens pv. undulosa (Xtu), is an important disease of wheat and triticale around the world. Although resistance to BLS is limited in wheat, several triticale accessions have high levels of resistance. To characterize the genetic basis of this resistance, we developed triticale mapping populations using a resistant accession (Siskiyou) and two susceptible accessions (UC38 and Villax St. Jose). Bulked segregant analysis in an F₂ population derived from the cross of Siskiyou × UC38 led to the identification of a simple sequence repeat (SSR) marker (XSCM138) on chromosome 5R that co-segregated with the resistance gene. The cross of Siskiyou × Villax St. Jose was advanced into an F_2:5 recombinant inbred line population and evaluated for BLS reaction. Genetic linkage maps on this population were assembled with markers generated using genotyping-by-sequencing as well as several SSR markers previously identified on 5R. Quantitative trait locus (QTL) mapping revealed a single major QTL on chromosome 5R, underlined by the same SSR marker as in the Siskiyou × UC38 population. The F₁ hybrids of the two crosses were highly resistant to BLS, indicating that resistance is largely dominant. This work will facilitate introgression of this rye-derived BLS resistance gene into the wheat genome by molecular marker-mediated chromosome engineering.

     

Efficient QTL detection for nonhost resistance in wild lettuce: backcross inbred lines versus F2 population

In plants, several population types [F₂, recombinant inbred lines, backcross inbred lines (BILs), etc.] are used for quantitative trait locus (QTL) analyses. However, dissection of the trait of interest and subsequent confirmation by introgression of QTLs for breeding purposes has not been as successful as that predicted from theoretical calculations. More practical knowledge of different QTL mapping approaches is needed. In this recent study, we describe the detection and mapping of quantitative resistances to downy mildew in a set of 29 BILs of cultivated lettuce (L. sativa) containing genome segments introgressed from wild lettuce (L. saligna). Introgression regions that are associated with quantitative resistance are considered to harbor a QTL. Furthermore, we compare this with results from an already existing F₂ population derived from the same parents. We identified six QTLs in our BIL approach compared to only three in the F₂ approach, while there were two QTLs in common. We performed a simulation study based on our actual data to help us interpret them. This revealed that two newly detected QTLs in the BILs had gone unnoticed in the F₂, due to a combination of recessiveness of the trait and skewed segregation, causing a deficit of the wild species alleles. This study clearly illustrates the added value of extended genetic studies on two different population types (BILs and F₂) to dissect complex genetic traits.     

A quantitative trait locus for cold tolerance at the booting stage on rice chromosome 8

A quantitative trait locus (QTL) for cold tolerance at the booting stage of a cold-tolerant rice breeding line, Hokkai-PL9, was analyzed. A total of 487 simple sequence repeat (SSR) markers distributed throughout the genome were used to survey for polymorphism between Hokkai-PL9 and a cold-sensitive breeding line, Hokkai287, and 54 markers were polymorphic. Single marker analysis revealed that markers on chromosome 8 are associated with cold tolerance. By interval mapping using an F₂ population between Hokkai-PL9 and Hokkai287, a QTL for cold tolerance was detected on the short arm of chromosome 8. The QTL explains 26.6% of the phenotypic variance, and its additive effect is 11.4%. Substitution mapping suggested that the QTL is located in a 193-kb interval between SSR markers RM5647 and PLA61. We tentatively designated the QTL as qCTB8 (quantitative trait locus for cold tolerance at the booting stage on chromosome 8).     

QTL consistency and meta-analysis for grain yield components in three generations in maize

Grain yield is the most important and complex trait in maize. In this study, a total of 258 F₉ recombinant inbred lines (RIL), derived from a cross between dent corn inbred Dan232 and popcorn inbred N04, were evaluated for eight grain yield components under four environments. Quantitative trait loci (QTL) and their epistatic interactions were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL across three generations (RIL, F_2:3 and BC₂F₂) derived from the same cross. In total, 103 QTL, 42 pairs of epistatic interactions and 16 meta-QTL (mQTL) were detected. Twelve out of 13 QTL with contributions (R ²) over 15% were consistently detected in 3–4 environments (or in combined analysis) and integrated in mQTL. Only q100GW-7-1 was detected in all four environments and in combined analysis. 100qGW-1-1 had the largest R ² (19.3–24.6%) in three environments and in combined analysis. In contrast, 35 QTL for 6 grain yield components were detected in the BC₂F₂ and F_2:3 generations, no common QTL across three generations were located in the same marker intervals. Only 100 grain weight (100GW) QTL on chromosome 5 were located in adjacent marker intervals. Four common QTL were detected across the RIL and F_2:3 generations, and two between the RIL and BC₂F₂ generations. Each of five important mQTL (mQTL7-1, mQTL10-2, mQTL4-1, mQTL5-1 and mQTL1-3) included 7–12 QTL associated with 2–6 traits. In conclusion, we found evidence of strong influence of genetic structure and environment on QTL detection, high consistency of major QTL across environments and generations, and remarkable QTL co-location for grain yield components. Fine mapping for five major QTL (q100GW-1-1, q100GW-7-1, qGWP-4-1, qERN-4-1 and qKR-4-1) and construction of single chromosome segment lines for genetic regions of five mQTL merit further studies and could be put into use in marker-assisted breeding.     

Mapping of new quantitative trait loci for sudden death syndrome and soybean cyst nematode resistance in two soybean populations

Key message

Novel QTL conferring resistance to both the SDS and SCN was detected in two RIL populations. Dual resistant RILs could be used in breeding programs for developing resistant soybean cultivars.

Abstract

Soybean cultivars, susceptible to the fungus Fusarium virguliforme, which causes sudden death syndrome (SDS), and to the soybean cyst nematode (SCN) (Heterodera glycines), suffer yield losses valued over a billion dollars annually. Both pathogens may occur in the same production fields. Planting of cultivars genetically resistant to both pathogens is considered one of the most effective means to control the two pathogens. The objective of the study was to map quantitative trait loci (QTL) underlying SDS and SCN resistances. Two recombinant inbred line (RIL) populations were developed by crossing ‘A95-684043’, a high-yielding maturity group (MG) II line resistant to SCN, with ‘LS94-3207’ and ‘LS98-0582’ of MG IV, resistant to both F. virguliforme and SCN. Two hundred F₇ derived recombinant inbred lines from each population AX19286 (A95-684043 × LS94-3207) and AX19287 (A95-684043 × LS98-0582) were screened for resistance to each pathogen under greenhouse conditions. Five hundred and eighty and 371 SNP markers were used for mapping resistance QTL in each population. In AX19286, one novel SCN resistance QTL was mapped to chromosome 8. In AX19287, one novel SDS resistance QTL was mapped to chromosome 17 and one novel SCN resistance QTL was mapped to chromosome 11. Previously identified additional SDS and SCN resistance QTL were also detected in the study. Lines possessing superior resistance to both pathogens were also identified and could be used as germplasm sources for breeding SDS- and SCN-resistant soybean cultivars.

     

Rapid identification of an adult plant stripe rust resistance gene in hexaploid wheat by high-throughput SNP array genotyping of pooled extremes

Key message

High-throughput SNP array analysis of pooled extreme phenotypes in a segregating population by KASP marker genotyping permitted rapid, cost-effective location of a stripe rust resistance QTL in wheat.

Abstract

German wheat cultivar “Friedrichswerther” has exhibited high levels of adult plant resistance (APR) to stripe rust in field environments for many years. F_2:3 lines and F₆ recombinant inbred line (RILs) populations derived from a cross between Friedrichswerther and susceptible landrace Mingxian 169 were evaluated in the field in 2013, 2016 and 2017. Illumina 90K iSelect SNP arrays were used to genotype bulked extreme pools and parents; 286 of 1135 polymorphic SNPs were identified on chromosome 6B. Kompetitive Allele-Specific PCR (KASP) markers were used to verify the chromosome region associated with the resistance locus. A linkage map was constructed with 18 KASP-SNP markers, and a major effect QTL was identified within a 1.4 cM interval flanked by KASP markers IWB71602 and IWB55937 in the region 6BL3-0-0.36. The QTL, named QYr.nwafu-6BL, was stable across environments, and explained average 54.4 and 47.8% of the total phenotypic variation in F_2:3 lines and F₆ RILs, respectively. On the basis of marker genotypes, pedigree analysis and relative genetic distance QYr.nwafu-6BL is likely to be a new APR QTL. Combined high-throughput SNP array genotyping of pooled extremes and validation by KASP assays lowers sequencing costs compared to genome-wide association studies with SNP arrays, and more importantly, permits rapid isolation of major effect QTL in hexaploid wheat as well as improving accuracy of mapping in the QTL region. QYr.nwafu-6BL with flanking KASP markers developed and verified in a subset of 236 diverse lines can be used in marker-assisted selection to improve stripe rust resistance in breeding programs.

     

RFLP mapping of the sugary enhancer1 gene in maize

RFLP marker data from an F₂₃ population derived from a cross between a sugary1 (su1) and a sugary enhancer1 (su1, sel) inbred were used to construct a genetic linkage map of maize. This map includes 93 segregating marker loci distributed throughout the maize genome, providing a saturated linkage map that is suitable for linkage analysis with quantitative trait loci (QTL). This population, which has been immortalized in the form of sibbed F₂₃ families, was derived from each of the 214 F₂ plants and along with probe data are available to the scientific community. QTL analysis for kernel sucrose (the primary form of sugar) concentration at 20 days after pollination (DAP) uncovered the segregation of seven major QTL influencing sucrose concentration; a locus linked to umc36a described the greatest proportion of the variation (24.7%). Since maltose concentration has previously been reported to be associated with the se1 phenotype, an analysis of probe associations with maltose concentration at 40 DAP was also conducted. The highly significant association of umc36a with maltose and sucrose concentrations provided evidence that this probe is linked to se1. Phenotypic evaluation for the se1 genotype in each F₂₃ family enabled us to map the gene 12.1 cM distal to umc36a. In contrast to previous work where se1 was reported to be located on chromosome four, our data strongly suggest that the sugary enhancer1 locus maps on the the distal portion of the long arm of chromosome 2 in the maize genome.     

How replicable are mRNA expression QTL?

Applying quantitative trait analysis methods to genome-wide microarray-derived mRNA expression phenotypes in segregating populations is a valuable tool in the attempt to link high-level traits to their molecular causes. The massive multiple-testing issues involved in analyzing these data make the correct level of confidence to place in mRNA abundance quantitative trait loci (QTL) a difficult problem. We use a unique resource to directly test mRNA abundance QTL replicability in mice: paired recombinant inbred (RI) and F₂ data sets derived from C57BL/6J (B6) and DBA/2J (D2) inbred strains and phenotyped using the same Affymetrix arrays. We have one forebrain and one striatum data set pair. We describe QTL replication at varying stringencies in these data. For instance, 78% of mRNA expression QTL (eQTL) with genome-wide adjusted p ≤ 0.0001 in RI data replicate at a genome-wide adjusted p < 0.05 or better. Replicated QTL are disproportionately putatively cis-acting, and approximately 75% have higher apparent expression levels associated with B6 genotypes, which may be partly due to probe set generation using B6 sequence. Finally, we note that while trans-acting QTL do not replicate well between data sets in general, at least one cluster of trans-acting QTL on distal Chr 1 is notably preserved between data sets.     

Mapping diabetes QTL in an intercross derived from a congenic strain of the Brown Norway and Goto-Kakizaki rats

Genetic studies in experimental crosses derived from the inbred Goto-Kakizaki (GK) rat model of spontaneous diabetes mellitus have identified quantitative trait loci (QTL) for diabetes phenotypes in a large region of rat Chromosome (RNO) 1. To test the impact of GK variants on QTL statistical and biological features, we combined genetic and physiologic studies in a cohort of F₂ hybrids derived from a QTL substitution congenic strain (QTLSCS) carrying a 110-cM GK haplotype of RNO1 introgressed onto the genetic background of the Brown Norway (BN) strain. Glucose intolerance and altered insulin secretion in QTLSCS rats when compared with BN controls were consistent with original QTL features in a GK × BN F₂ cross. Segregating GK alleles in the QTLSCS F₂ cross account for most of these phenotypic differences between QTLSCS and BN rats. However, significant QTL for diabetes traits in both the QTLSCS and GK × BN F₂ cohorts account for a similar small proportion of their variance. Comparing results from these experimental systems provides indirect estimates of the contribution of genetic interactions and environmental factors to QTL architecture as well as locus and biological targets for future post-QTL mapping studies in congenic substrains. Electronic Supplementary Material Electronic Supplementary material is available for this article at and accessible for authorised users. Stephan C. Collins and Robert H. Wallis contributed equally to this work.     

Genetic mapping revealed two loci for soybean aphid resistance in PI 567301B

The soybean aphid (Aphis glycines Matsumura) is the most damaging insect pest of soybean [Glycine max (L.) Merr.] in North America. New soybean aphid biotypes have been evolving quickly and at least three confirmed biotypes have been reported in USA. These biotypes are capable of defeating most known aphid resistant soybean genes indicating the need for identification of new genes. Plant Introduction (PI) 567301B was earlier identified to have antixenosis resistance against biotype 1 and 2 of the soybean aphid. Two hundred and three F_7:9 recombinant inbred lines (RILs) developed from a cross of soybean aphid susceptible cultivar Wyandot and resistant PI 567301B were used for mapping aphid resistance genes using the quantitative trait loci (QTL) mapping approach. A subset of 94 RILs and 516 polymorphic SNP makers were used to construct a genome-wide molecular linkage map. Two candidate QTL regions for aphid resistance were identified on this linkage map. Fine mapping of the QTL regions was conducted with SSR markers using all 203 RILs. A major gene on chromosome 13 was mapped near the previously identified Rag2 gene. However, an earlier study revealed that the detached leaves of PI 567301B had no resistance against the soybean aphids while the detached leaves of PI 243540 (source of Rag2) maintained aphid resistance. These results and the earlier finding that PI 243540 showed antibiosis resistance and PI 567301B showed antixenosis type resistance, indicating that the aphid resistances in the two PIs are not controlled by the same gene. Thus, we have mapped a new gene near the Rag2 locus for soybean aphid resistance that should be useful in breeding for new aphid-resistant soybean cultivars. Molecular markers closely linked to this gene are available for marker-assisted breeding. Also, the minor locus found on chromosome 8 represents the first reported soybean aphid-resistant locus on this chromosome.