Location Of Quantitative Trait Loci Research Articles

Transcriptome-based SNP discovery by GBS and the construction of a genetic map for olive.

Molecular markers located in the genic regions of plants are valuable tools for the identification of candidate genes of economically important traits and consequent use in marker-assisted selection (MAS). In the past, simple sequence repeat markers (SSRs) and single-nucleotide polymorphisms (SNPs) located in expressed sequence tags (ESTs) were developed by sequencing RNA derived from different plant tissues, which involves laborious RNA extraction, mRNA isolation, and cDNA synthesis. In order to develop SNP markers located in olive transcriptomes, we used the recently developed genotyping-by-sequencing (GBS) technique. An analysis was done for 125 olive DNA samples (123 DNA samples from a cross-pollinated F1 mapping population, and two samples from parents). From 45 to 66% of Illumina reads from GBS analysis were aligned to the olive transcriptome. A total of 22,033 transcriptome-based SNP markers were identified, and 3384 of these were mapped in the olive genome. The genetic linkage map constructed in this study consists of 1 cleaved amplified polymorphic sequence (CAPS), 19 SSR, and 3384 transcriptome-based SNP markers. The map covers 3340.8cM of the olive genome in 23 linkage groups, with the length of the linkage groups ranging from 55.6 to 248.7cM. Average map distance between flanking markers was 0.98cM. This genetic linkage map is a saturated genetic map and will be a useful tool for the localization of quantitative trait loci (QTLs) and gene(s) of interest and for the identification of candidate genes for economically important traits.

Association mapping of morphological traits in wild and captive zebra finches: reliable within, but not between populations

Identifying causal genetic variants underlying heritable phenotypic variation is a long-standing goal in evolutionary genetics. We previously identified several quantitative trait loci (QTL) for five morphological traits in a captive population of zebra finches (Taeniopygia guttata) by whole-genome linkage mapping. We here follow up on these studies with the aim to narrow down on the quantitative trait variants (QTN) in one wild and three captive populations. First, we performed an association study using 672 single nucleotide polymorphisms (SNPs) within candidate genes located in the previously identified QTL regions in a sample of 939 wild-caught zebra finches. Then, we validated the most promising SNP-phenotype associations (n=25 SNPs) in 5228 birds from four populations. Genotype-phenotype associations were generally weak in the wild population, where linkage disequilibrium (LD) spans only short genomic distances. In contrast, in captive populations, where LD blocks are large, apparent SNP effects on morphological traits (i.e. associations) were highly repeatable with independent data from the same population. Most of those SNPs also showed significant associations with the same trait in other captive populations, but the direction and magnitude of these effects varied among populations. This suggests that the tested SNPs are not the causal QTN but rather physically linked to them, and that LD between SNPs and causal variants differs between populations due to founder effects. While the identification of QTN remains challenging in nonmodel organisms, we illustrate that it is indeed possible to confirm the location and magnitude of QTL in a population with stable linkage between markers and causal variants.

Individual and combined contributions of the Ren barb1 , Ren barb2 , and Ren barb3 quantitative trait loci to reniform nematode (Rotylenchulus reniformis Linford & Oliveira) resistance in upland cotton (Gossypium hirsutum L.)

The infection of Upland cotton (Gossypium hirsutum L.) by the root parasite Rotylenchulus reniformis Linford & Oliveira, the reniform nematode, results in massive annual yield losses throughout the southeastern United States and portions of Texas. Resistance to reniform nematode was identified in the photoperiodic G. barbadense L. accession GB713. Previous research identified three quantitative trait loci (QTLs) that mediate GB713-derived reniform nematode resistance. Two of the QTLs reside next to each other on chromosome 21 (Ren barb1 and Ren barb2 ) while Ren barb3 was mapped to chromosome 18. In the present study, reniform nematode reproduction and fecundity was measured for eight G. hirsutum near isolines, developed through marker-assisted-selection (MAS), that represented every possible combination of Ren barb QTL genotypes. Our data clearly show that the Ren barb1 –Ren barb2 QTL interval can be resolved to a single QTL locus, i.e., Ren barb2 , that can be selected for in MAS using the BNL3279_106 SSR marker. Reniform nematode resistance equivalent to the GB713 parent was only obtained through combination of Ren barb2 and Ren barb3 ; however, Ren barb2 alone conferred an approximately 71% reduction in eggs gram−1 root compared to the susceptible check. The addition of Ren barb1 to isolines having only Ren barb2 or Ren barb3 did not improve resistance phenotypes. Adult reniform nematode females produced the same number of eggs per egg mass across all lines tested indicating that GB713-derived resistance does not manifest as a reduction in nematode fecundity. These findings streamline cotton MAS breeding programs by reducing the number of reniform nematode resistance loci that require tracking in segregating populations.

Quantitative trait loci (QTL) for reducing aflatoxin accumulation in corn

Aflatoxin produced by Aspergillus flavus in corn poses significant health risks to both humans and livestock. Exploitation of host-plant resistance in breeding programs is a sustainable way to minimize aflatoxin contamination. Identification of quantitative trait loci (QTL) associated with resistance to aflatoxin accumulation in kernels can accelerate development of aflatoxin-resistant corn using marker-assisted selection. An F2:3 mapping population, developed from a cross involving a resistant inbred Mp715 and a susceptible inbred B73, was evaluated in replicated field trials with developing ears artificially inoculated with A. flavus for 2 years to identify QTL for reduced aflatoxin accumulation. Using composite interval mapping, 6 to 7 QTL for aflatoxin content were identified in both years with contribution of individual QTL ranging from <1 to 10% of phenotypic variation. More QTL were detected for husk coverage with phenotypic variance range of <1 to 16% explained by individual QTL. Both B73 and Mp715 alleles at these QTL loci contributed toward resistance. Husk coverage and aflatoxin levels were significantly correlated in both years. Our findings were further supported by overlapping of QTL for husk coverage ratings in four genomic regions on chromosomes 4, 8, and 10, where aflatoxin resistance QTL were reported in previous studies. Since most of the QTL were of low to moderate effects, pyramiding of these QTL may lead to enhanced resistance to aflatoxin accumulation in corn.

Genetic architecture of the maize kernel row number revealed by combining QTL mapping using a high-density genetic map and bulked segregant RNA sequencing.

BackgroundThe maize kernel row number (KRN) is a key component that contributes to grain yield and has high broad-sense heritability (H 2). Quantitative trait locus/loci (QTL) mapping using a high-density genetic map is a powerful approach to detecting loci that are responsible for traits of interest. Bulked segregant ribonucleic acid (RNA) sequencing (BSR-seq) is another rapid and cost-effective strategy to identify QTL. Combining QTL mapping using a high-density genetic map and BSR-seq may dissect comprehensively the genetic architecture underlying the maize KRN.ResultsA panel of 300 F2 individuals derived from inbred lines abe2 and B73 were genotyped using the specific-locus amplified fragment sequencing (SLAF-seq) method. A total of 4,579 high-quality polymorphic SLAF markers were obtained and used to construct a high-density genetic map with a total length of 2,123 centimorgan (cM) and an average distance between adjacent markers of 0.46 cM. Combining the genetic map and KRN of F2 individuals, four QTL (qKRN1, qKRN2, qKRN5, and qKRN8-1) were identified on chromosomes 1, 2, 5, and 8, respectively. The physical intervals of these four QTL ranged from 4.36 Mb for qKRN8-1 to 7.11 Mb for qKRN1 with an average value of 6.08 Mb. Based on high-throughput sequencing of two RNA pools bulked from leaves of plants with extremely high and low KRNs, two QTL were detected on chromosome 8 in the 10–25 Mb (BSR_QTL1) and 60–150 Mb (BSR_QTL2) intervals. According to the physical positions of these QTL, qKRN8-1 was included by BSR_QTL2. In addition, qKRN8-1 was validated using QTL mapping with a recombinant inbred lines population that was derived from inbred lines abe2 and B73.ConclusionsIn this study, we proved that combining QTL mapping using a high-density genetic map and BSR-seq is a powerful and cost-effective approach to comprehensively revealing genetic architecture underlying traits of interest. The QTL for the KRN detected in this study, especially qKRN8-1, can be used for performing fine mapping experiments and marker-assisted selection in maize breeding.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3240-y) contains supplementary material, which is available to authorized users.

QTL mapping of grain appearance quality traits and grain weight using a recombinant inbred population in rice (Oryza sativa L.)

Grain appearance quality traits, measured as grain length (GL), grain width (GW), length to width ratio (LWR), grain thickness (GT) and the percentage of grain with chalkiness (PGWC), as well as 1 000-grain weight (TGW), are very important factors that contribute to rice grain quality and yield. To detect quantitative trait loci (QTLs) affecting these traits, we developed a set of recombinant inbred lines (RILs) derived from Gang46B (G46B) and K1075, a G46B introgression line with lower PGWC. Based on a linkage map containing 33 simple sequence repeat (SSR) markers, a total of 15 additive QTLs governing six measured traits were identified on 4 chromosomes across two environments. Of these, the five major QTLs which controlled GW, LWR, GT, PGWC, and TGW, each explaining up to 44.30, 55.29, 62.30, 30.94, and 28.78% of the variation, respectively, were found in the same interval of RM18004–RM18068 on chromosome 5. The G46B alleles contributed to the increase in GW, GT and PGWC at all loci, as well as the increase in TGW at its major QTL locus. Significant interactions between additive QTL and the environment were found at most loci, in which the largest, accounting for 15.06% of variation, was observed between qPGWC-5 and the environment. A total of 15 epistasis QTLs were detected for all the traits, and GL, GW and PGWC had significant epistasis QTLs based on environment interactions with minor effects. These results are valuable for future map-based cloning of the QTLs and the collaborative improvement of G46B in grain appearance quality and yield.

SNP-Based QTL Mapping of 15 Complex Traits in Barley under Rain-Fed and Well-Watered Conditions by a Mixed Modeling Approach.

This study identified single nucleotide polymorphism (SNP) markers associated with 15 complex traits in a breeding population of barley (Hordeum vulgare L.) consisting of 137 recombinant chromosome substitution lines (RCSL), evaluated under contrasting water availability conditions in the Mediterranean climatic region of central Chile. Given that markers showed a very strong segregation distortion, a quantitative trait locus/loci (QTL) mapping mixed model was used to account for the heterogeneity in genetic relatedness between genotypes. Fifty-seven QTL were detected under rain-fed conditions, which accounted for 5–22% of the phenotypic variation. In full irrigation conditions, 84 SNPs were significantly associated with the traits studied, explaining 5–35% of phenotypic variation. Most of the QTL were co-localized on chromosomes 2H and 3H. Environment-specific genomic regions were detected for 12 of the 15 traits scored. Although most QTL-trait associations were environment and trait specific, some important and stable associations were also detected. In full irrigation conditions, a relatively major genomic region was found underlying hectoliter weight (HW), on chromosome 1H, which explained between 27% (SNP 2711-234) and 35% (SNP 1923-265) of the phenotypic variation. Interestingly, the locus 1923-265 was also detected for grain yield at both environmental conditions, accounting for 9 and 18%, in the rain-fed and irrigation conditions, respectively. Analysis of QTL in this breeding population identified significant genomic regions that can be used for marker-assisted selection (MAS) of barley in areas where drought is a significant constraint.

Quantitative Trait Loci and Inter-Organ Partitioning for Essential Metal and Toxic Analogue Accumulation in Barley.

The concentrations of both essential nutrients and chemically similar toxic analogues accumulated in cereal grains have a major impact on the nutritional quality and safety of crops. Naturally occurring genetic diversity can be exploited for the breeding of improved varieties through introgression lines (ILs). In this study, multi-element analysis was conducted on vegetative leaves, senesced flag leaves and mature grains of a set of 54 ILs of the wild ancestral Hordeum vulgare ssp. spontaneum in the cultivated variety Hordeum vulgare ssp. vulgare cv. Scarlett. Plants were cultivated on an anthropogenically heavy metal-contaminated soil collected in an agricultural field, thus allowing simultaneous localization of quantitative trait loci (QTL) for the accumulation of both essential nutrients and toxic trace elements in barley as a model cereal crop. For accumulation of the micronutrients Fe and Zn and the interfering toxin Cd, we identified 25, 16 and 5 QTL, respectively. By examining the gene content of the introgressions, we associated QTL with candidate genes based on homology to known metal homeostasis genes of Arabidopsis and rice. Global comparative analyses suggested the preferential remobilization of Cu and Fe, over Cd, from the flag leaf to developing grains. Our data identifies grain micronutrient filling as a regulated and nutrient-specific process, which operates differently from vegetative micronutrient homoeostasis. In summary, this study provides novel QTL for micronutrient accumulation in the presence of toxic analogues and supports a higher degree of metal specificity of trace element partitioning during grain filling in barley than previously reported for other cereals.

High-resolution genetic linkage mapping, high-temperature tolerance and growth-related quantitative trait locus (QTL) identification in Marsupenaeus japonicus.

The Kuruma prawn, Marsupenaeus japonicus, is one of the most promising marine invertebrates in the industry in Asia, Europe and Australia. However, the increasing global temperatures result in considerable economic losses in M. japonicus farming. In the present study, to select genetically improved animals for the sustainable development of the Kuruma prawn industry, a high-resolution genetic linkage map and quantitative trait locus (QTL) identification were performed using the RAD technology. The maternal map contained 5849 SNP markers and spanned 3127.23cM, with an average marker interval of 0.535cM. Instead, the paternal map contained 3927 SNP markers and spanned 3326.19cM, with an average marker interval of 0.847cM. The consensus map contained 9289 SNP markers and spanned 3610.90cM, with an average marker interval of 0.388cM and coverage of 99.06% of the genome. The markers were grouped into 41 linkage groups in the maps. Significantly, negative correlation was detected between high-temperature tolerance (UTT) and body weight (BW). The QTL mapping revealed 129 significant QTL loci for UTT and four significant QTL loci for BW at the genome-wide significance threshold. Among these QTLs, 129 overlapped with linked SNPs, and the remaining four were located in regions between contiguous SNPs. They explained the total phenotypic variance ranging from 8.9 to 12.4%. Because of a significantly negative correlation between growth and high-temperature tolerance, we demonstrate that this high-resolution linkage map and QTLs would be useful for further marker-assisted selection in the genetic improvement of M. japonicus.

A remorin gene is implicated in quantitative disease resistance in maize.

Quantitative disease resistance is used by plant breeders to improve host resistance. We demonstrate a role for a maize remorin ( ZmREM6.3 ) in quantitative resistance against northern leaf blight using high-resolution fine mapping, expression analysis, and mutants. This is the first evidence of a role for remorins in plant-fungal interactions. Quantitative disease resistance (QDR) is important for the development of crop cultivars and is particularly useful when loci also confer multiple disease resistance. Despite its widespread use, the underlying mechanisms of QDR remain largely unknown. In this study, we fine-mapped a known quantitative trait locus (QTL) conditioning disease resistance on chromosome 1 of maize. This locus confers resistance to three foliar diseases: northern leaf blight (NLB), caused by the fungus Setosphaeria turcica; Stewart's wilt, caused by the bacterium Pantoea stewartii; and common rust, caused by the fungus Puccinia sorghi. The Stewart's wilt QTL was confined to a 5.26-Mb interval, while the rust QTL was reduced to an overlapping 2.56-Mb region. We show tight linkage between the NLB QTL locus and the loci conferring resistance to Stewart's wilt and common rust. Pleiotropy cannot be excluded for the Stewart's wilt and the common rust QTL, as they were fine-mapped to overlapping regions. Four positional candidate genes within the 243-kb NLB interval were examined with expression and mutant analysis: a gene with homology to an F-box gene, a remorin gene (ZmREM6.3), a chaperonin gene, and an uncharacterized gene. The F-box gene and ZmREM6.3 were more highly expressed in the resistant line. Transposon tagging mutants were tested for the chaperonin and ZmREM6.3, and the remorin mutant was found to be more susceptible to NLB. The putative F-box is a strong candidate, but mutants were not available to test this gene. Multiple lines of evidence strongly suggest a role for ZmREM6.3 in quantitative disease resistance.

Identification and Fine Mapping of a Soybean Seed Protein QTL from PI 407788A on Chromosome 15

ABSTRACTSoybean [Glycine max (L.) Merr.] is grown primarily as a source of protein and oil. The objectives of this study were to identify soybean seed protein quantitative trait loci (QTL) from the high protein line PI 407788A and to fine map an important QTL for protein on chromosome (chr) 15. The mapping was done in a population of inbred lines developed with one backcross (BC1) using Williams 82 as a recurrent parent and the high protein source PI 407788A as a donor parent. The population was evaluated with genetic markers and for seed protein and oil concentrations in three Illinois locations in 2005 and 2006. The location of the major protein QTL on chr 15 was fine mapped by evaluating six families of lines segregating for sections of the QTL interval in Illinois during 2008. Genetic marker analysis of the BC1 population revealed the locations of significant protein and oil QTL on chr 20 and 15 within regions where QTL for these traits were previously mapped. Fine mapping of the chr 15 QTL placed it in a 535 kb interval between BARCSOYSSR_15_0161 and BARCSOYSSR_15_0194 based on the Glyma.Wm82.a2 assembly. This fine mapping information will be useful in marker‐assisted selection and efforts to clone the QTL.

QTL mapping of seedling traits in cucumber using recombinant inbred lines

AbstractSeedling traits are important for development, flower bud differentiation, fruit production and fruit quality of cucumber (Cucumis sativus L.). In this study, 160 recombinant inbred lines (RILs), derived from crossing wild cucumber inbred line PI 183967 (C. sativus var. hardwickii) with ‘931’ northern China cultivated cucumber inbred line 931, were employed to identify quantitative trait loci (QTLs) of cotyledon length (Cl), cotyledon width (Cw), hypocotyl length (Hl), first true leaf length (Fll), first true leaf width (Flw), aboveground fresh biomass (Afb) and aboveground dry biomass (Adb) at seedling stage. A genetic map including 307 SSR markers was developed which spanned 993.3 cM, with an average genetic distance of 3.23 cM between adjacent markers. 36 QTLs associated with the seven traits were detected on chromosomes 1, 2, 3, 5 and 6 in four environments (spring and autumn of 2012 and 2013), explaining 6.1 to 23.6% of the observed phenotypic variations. Among the 36 QTLs, 21 were responsible for more than 10% of observed phenotypic variations. We obtained 2, 2, 1 and 3 QTL loci for the traits of Fll, Flw, Afw and Adw, respectively. In addition, genes in the genetic region spanned by SSR15321‐SSR07711 on chr. 5 may contribute to Flw, Afw and Adw.

Localization of quantitative trait loci for diapause and other photoperiodically regulated life history traits important in adaptation to seasonally varying environments.

Seasonally changing environments at high latitudes present great challenges for the reproduction and survival of insects, and photoperiodic cues play an important role in helping them to synchronize their life cycle with prevalent and forthcoming conditions. We have mapped quantitative trait loci (QTL) responsible for the photoperiodic regulation of four life history traits, female reproductive diapause, cold tolerance, egg-to-eclosion development time and juvenile body weight in Drosophila montana strains from different latitudes in Canada and Finland. The F2 progeny of the cross was reared under a single photoperiod (LD cycle 16:8), which the flies from the Canadian population interpret as early summer and the flies from the Finnish population as late summer. The analysis revealed a unique QTL for diapause induction on the X chromosome and several QTL for this and the other measured traits on the 4th chromosome. Flies' cold tolerance, egg-to-eclosion development time and juvenile body weight had several QTL also on the 2nd, 3rd and 5th chromosome, some of the peaks overlapping with each other. These results suggest that while the downstream output of females' photoperiodic diapause response is partly under a different genetic control from that of the other traits in the given day length, all traits also share some QTL, possibly involving genes with pleiotropic effects and/or multiple tightly linked genes. Nonoverlapping QTL detected for some of the traits also suggest that the traits are potentially capable of independent evolution, even though this may be restricted by epistatic interactions and/or correlations and trade-offs between the traits.

Genomic regulation of senescence and innate immunity signaling in the retinal pigment epithelium

The tumor suppressor p53 is a major regulator of genes important for cell cycle arrest, senescence, apoptosis, and innate immunity, and has recently been implicated in retinal aging. In this study we sought to identify the genetic networks that regulate p53 function in the retina using quantitative trait locus (QTL) analysis. First we examined age-associated changes in the activation and expression levels of p53; known p53 target proteins and markers of innate immune system activation in primary retinal pigment epithelial (RPE) cells that were harvested from young and aged human donors. We observed increased expression of p53, activated caspase-1, CDKN1A, CDKN2A (p16INK4a), TLR4, and IFNα in aged primary RPE cell lines. We used the Hamilton Eye Institute (HEI) retinal dataset ( www.genenetwork.org ) to identify genomic loci that modulate expression of genes in the p53 pathway in recombinant inbred BXD mouse strains using a QTL systems biology-based approach. We identified a significant trans-QTL on chromosome 1 (region 172-177 Mb) that regulates the expression of Cdkn1a. Many of the genes in this QTL locus are involved in innate immune responses, including Fc receptors, interferon-inducible family genes, and formin 2. Importantly, we found an age-related increase in FCGR3A and FMN2 and a decrease in IFI16 levels in RPE cultures. There is a complex multigenic innate immunity locus that controls expression of genes in the p53 pathway in the RPE, which may play an important role in modulating age-related changes in the retina.

Multi-location wheat stripe rust QTL analysis: genetic background and epistatic interactions.

Epistasis and genetic background were important influences on expression of stripe rust resistance in two wheat RIL populations, one with resistance conditioned by two major genes and the other conditioned by several minor QTL. Stripe rust is a foliar disease of wheat (Triticum aestivum L.) caused by the air-borne fungus Puccinia striiformis f. sp. tritici and is present in most regions around the world where commercial wheat is grown. Breeding for durable resistance to stripe rust continues to be a priority, but also is a challenge due to the complexity of interactions among resistance genes and to the wide diversity and continuous evolution of the pathogen races. The goal of this study was to detect chromosomal regions for resistance to stripe rust in two winter wheat populations, 'Tubbs'/'NSA-98-0995' (T/N) and 'Einstein'/'Tubbs' (E/T), evaluated across seven environments and mapped with diversity array technology and simple sequence repeat markers covering polymorphic regions of ≈1480 and 1117cM, respectively. Analysis of variance for phenotypic data revealed significant (P<0.01) genotypic differentiation for stripe rust among the recombinant inbred lines. Results for quantitative trait loci/locus (QTL) analysis in the E/T population indicated that two major QTL located in chromosomes 2AS and 6AL, with epistatic interaction between them, were responsible for the main phenotypic response. For the T/N population, eight QTL were identified, with those in chromosomes 2AL and 2BL accounting for the largest percentage of the phenotypic variance.

High-density genetic linkage map construction and QTL mapping of grain shape and size in the wheat population Yanda1817 × Beinong6.

High-density genetic linkage maps are necessary for precisely mapping quantitative trait loci (QTLs) controlling grain shape and size in wheat. By applying the Infinium iSelect 9K SNP assay, we have constructed a high-density genetic linkage map with 269 F 8 recombinant inbred lines (RILs) developed between a Chinese cornerstone wheat breeding parental line Yanda1817 and a high-yielding line Beinong6. The map contains 2431 SNPs and 128 SSR & EST-SSR markers in a total coverage of 3213.2 cM with an average interval of 1.26 cM per marker. Eighty-eight QTLs for thousand-grain weight (TGW), grain length (GL), grain width (GW) and grain thickness (GT) were detected in nine ecological environments (Beijing, Shijiazhuang and Kaifeng) during five years between 2010–2014 by inclusive composite interval mapping (ICIM) (LOD≥2.5). Among which, 17 QTLs for TGW were mapped on chromosomes 1A, 1B, 2A, 2B, 3A, 3B, 3D, 4A, 4D, 5A, 5B and 6B with phenotypic variations ranging from 2.62% to 12.08%. Four stable QTLs for TGW could be detected in five and seven environments, respectively. Thirty-two QTLs for GL were mapped on chromosomes 1B, 1D, 2A, 2B, 2D, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6B, 7A and 7B, with phenotypic variations ranging from 2.62% to 44.39%. QGl.cau-2A.2 can be detected in all the environments with the largest phenotypic variations, indicating that it is a major and stable QTL. For GW, 12 QTLs were identified with phenotypic variations range from 3.69% to 12.30%. We found 27 QTLs for GT with phenotypic variations ranged from 2.55% to 36.42%. In particular, QTL QGt.cau-5A.1 with phenotypic variations of 6.82–23.59% was detected in all the nine environments. Moreover, pleiotropic effects were detected for several QTL loci responsible for grain shape and size that could serve as target regions for fine mapping and marker assisted selection in wheat breeding programs.

Isolation and characterization of novel microsatellite markers from the sika deer (Cervus nippon) genome.

Microsatellite markers are widely and evenly distributed, and are highly polymorphic. Rapid and convenient detection through automated analysis means that microsatellite markers are widely used in the construction of plant and animal genetic maps, in quantitative trait loci localization, marker-assisted selection, identification of genetic relationships, and genetic diversity and phylogenetic tree construction. However, few microsatellite markers remain to be isolated. We used streptavidin magnetic beads to affinity-capture and construct a (CA)n microsatellite DNA-enriched library from sika deer. We selected sequences containing more than six repeats to design primers. Clear bands were selected, which were amplified using non-specific primers following PCR amplification to screen polymorphisms in a group of 65 unrelated sika deer. The positive clone rate reached 82.9% by constructing the enriched library, and we then selected positive clones for sequencing. There were 395 sequences with CA repeats, and the CA repeat number was 4-105. We selected sequences containing more than six repeats to design primers, of which 297 pairs were designed. We next selected clear bands and used non-specific primers to amplify following PCR amplification. In total, 245 pairs of primers were screened. We then selected 50 pairs of primers to randomly screen for polymorphisms. We detected 47 polymorphic and 3 monomorphic loci in 65 unrelated sika deer. These newly isolated and characterized microsatellite loci can be used to construct genetic maps and for lineage testing in deer. In addition, they can be used for comparative genomics between Cervidae species.

Confirming a major QTL and finding additional loci responsible for field resistance to brown spot (Bipolaris oryzae) in rice.

Brown spot is a devastating rice disease. Quantitative resistance has been observed in local varieties (e.g., ‘Tadukan’), but no economically useful resistant variety has been bred. Using quantitative trait locus (QTL) analysis of recombinant inbred lines (RILs) from ‘Tadukan’ (resistant) × ‘Hinohikari’ (susceptible), we previously found three QTLs (qBS2, qBS9, and qBS11) that conferred resistance in seedlings in a greenhouse. To confirm their effect, the parents and later generations of RILs were transplanted into paddy fields where brown spot severely occurred. Three new resistance QTLs (qBSfR1, qBSfR4, and qBSfR11) were detected on chromosomes 1, 4, and 11, respectively. The ‘Tadukan’ alleles at qBSfR1 and qBSfR11 and the ‘Hinohikari’ allele at qBSfR4 increased resistance. The major QTL qBSfR11 coincided with qBS11 from the previous study, whereas qBSfR1 and qBSfR4 were new but neither qBS2 nor qBS9 were detected. To verify the qBSfR1 and qBSfR11 ‘Tadukan’ resistance alleles, near-isogenic lines (NILs) with one or both QTLs in a susceptible background (‘Koshihikari’) were evaluated under field conditions. NILs with qBSfR11 acquired significant field resistance; those with qBSfR1 did not. This confirms the effectiveness of qBSfR11. Genetic markers flanking qBSfR11 will be powerful tools for marker-assisted selection to improve brown spot resistance.

Genetic mapping of QTL for maize weevil resistance in a RIL population of tropical maize.

A tropical RIL maize population was subjected to phenotypic and genotypic analysis for maize weevil resistance during four seasons, and three main genomic areas were detected as main QTLs. The maize weevil (Sitophilus zeamais) (MW) is a common and important pest of stored maize (Zea mays) worldwide, especially in tropical areas. Quantitative trait loci (QTLs) associated with the MW have been analyzed previously in an F2 maize population. In this work, new germplasm-based F6 recombinant inbred line (RIL) families, derived from the cross of Population 84 and Kilima, were analyzed using insect bioassays during four seasons. The parameters analyzed for MW resistance were grain weight losses (GWL), adult progeny (AP), and flour production (FP). Composite interval mapping identified a total of 15 QTLs for MW parameters located on six chromosomes, explaining between 14 and 51 % of phenotypic variation (σ p (2) ) and 27 and 81 % of genotypic variation (σ g (2) ). The QTL obtained for GWL was located in bin 2.05, which explained 15 % of σ p (2) . For AP and FP, the QTLs were located on regions 1.09 and 2.05, explaining 7 and 15 % of σ p (2) , respectively. Comparative analysis between F2 and F6 families showed similarities in QTL localization; three main regions were co-localized in chromosomes 4.08, 10.04, and 10.07, where no resistance-associated genes have been reported previously. These regions could be used for a marker-assisted selection in breeding programs for MW resistance in tropical maize.

Genetic Dissection of QTL Associated with Grain Yield in Diverse Environments

Wheat (Triticum aestivum L.) breeding programs strive to increase grain yield; however, the progress is hampered due to its quantitative inheritance, low heritability, and confounding environmental effects. In the present study, a winter wheat population of 159 recombinant inbred lines (RILs) was evaluated in six trials under rainfed, terminal drought, and fully-irrigated conditions, over four years. Quantitative trait locus/loci (QTL) mapping was conducted for grain yield main effect (GY) and the genotype × environment interaction (GEI) effect. A total of 17 QTL were associated with GY and 13 QTL associated with GEI, and nine QTL were mapped in the flanking chromosomal regions for both GY and GEI. One major QTL Q.Gy.ui-1B.2, explaining up to 22% of grain yield, was identified in all six trials. Besides the additive effect of QTL associated with GY, interactions among QTL (QTL × QTL interaction), QTL × environment, and QTL × QTL × environment were also observed. When combining the interaction effects, QTL Q.Gy.ui-1B.2 along with other QTL explained up to 52% of the variation in grain yield over the six trials. This study suggests that QTL mapping of complex traits such as grain yield should include interaction effects of QTL and environments in marker-assisted selection.