Genetic mapping of yield traits using RIL population derived from Fuchuan Dahuasheng and ICG6375 of peanut (<Emphasis Type="Italic">Arachis hypogaea</Emphasis> L.)

The genetic architecture determinants of yield traits in peanut (Arachis hypogaea L.) are poorly understood. In the present study, an effort was made to map quantitative trait loci (QTLs) for yield traits using recombinant inbred lines (RIL). A genetic linkage map was constructed containing 609 loci, covering a total of 1557.48 cM with an average distance of 2.56 cM between adjacent markers. The present map exhibited good collinearity with the physical map of diploid species of Arachis. Ninety-two repeatable QTLs were identified for 11 traits including height of main stem, total branching number, and nine pod- and seed-related traits. Of the 92 QTLs, 15 QTLs were expressed across three environments and 65 QTLs were newly identified. Twelve QTLs for the height of main stem and the pod- and seed-related traits explaining more than 10 % of phenotypic variation showed a great potential for marker-assisted selection in improving these traits. 相似文献   

Quantitative trait loci mapping of yield and related traits using a high-density genetic map of maize

Improving grain yield is the ultimate goal of the maize-breeding programs. In this study, analyses of conditional and unconditional quantitative trait locus (QTL) and epistatic interactions were used to elucidate the genetic architecture of yield and its related traits. A total of 15 traits of a recombinant inbred line population, including yield per plant (YPP), seven ear-related traits, and seven kernel-related traits, were measured in six different environments. Based on the genetic linkage map constructed using 2091 bins as markers, 56 main-effect QTLs for these traits were identified. These QTLs were distributed across eight genomic regions (bin 1.06, bin 4.02/4.05/4.08, bin 5.04, bin 7.04, bin 8.08, and bin 9.04), within the marker intervals of 85.45–6260.66 kb, and the phenotypic variance explained ranging from 5.69 to 11.56 %. One gene (GRMZM2G168229) encoding SBP-box domain protein was located in the small interval of qKRN4-3 and may be involved in patterning of kernel row number. Seventeen conditional QTLs identified for YPP were conditioned on its related traits and explained 6.18–23.15 % of the phenotypic variance. Conditional mapping analysis revealed that qYPP4-1, qYPP6-1, and qYPP8-1 are partially influenced by YPP-related traits at the individual QTL level. Digenic epistatic analysis identified 12 digenic interactions involving 22 loci across the whole genome. In addition, conditional digenic epistatic analysis identified 14 digenic interactions involving 21 loci. This study provides valuable information for understanding the genetic relationship between YPP and related traits and constitutes the first step toward the cloning of the relevant genes.     

Chromosomes A07 and A05 associated with stable and major QTLs for pod weight and size in cultivated peanut (<Emphasis Type="Italic">Arachis hypogaea</Emphasis> L.)

Key message

Co-localized intervals and candidate genes were identified for major and stable QTLs controlling pod weight and size on chromosomes A07 and A05 in an RIL population across four environments.

Abstract

Cultivated peanut (Arachis hypogaea L.) is an important legume crops grown in > 100 countries. Hundred-pod weight (HPW) is an important yield trait in peanut, but its underlying genetic mechanism was not well studied. In this study, a mapping population (Xuhua 13 × Zhonghua 6) with 187 recombinant inbred lines (RILs) was developed to map quantitative trait loci (QTLs) for HPW together with pod length (PL) and pod width (PW) by both unconditional and conditional QTL analyses. A genetic map covering 1756.48 cM was constructed with 817 markers. Additive effects, epistatic interactions, and genotype-by-environment interactions were analyzed using the phenotyping data generated across four environments. Twelve additive QTLs were identified on chromosomes A05, A07, and A08 by unconditional analysis, and five of them (qPLA07, qPLA05.1, qPWA07, qHPWA07.1, and qHPWA05.2) showed major and stable expressions in all environments. Conditional QTL mapping found that PL had stronger influences on HPW than PW. Notably, qHPWA07.1, qPLA07, and qPWA07 that explained 17.93–43.63% of the phenotypic variations of the three traits were co-localized in a 5 cM interval (1.48 Mb in physical map) on chromosome A07 with 147 candidate genes related to catalytic activity and metabolic process. In addition, qHPWA05.2 and qPLA05.1 were co-localized with minor QTL qPWA05.2 to a 1.3 cM genetic interval (280 kb in physical map) on chromosome A05 with 12 candidate genes. This study provides a comprehensive characterization of the genetic components controlling pod weight and size as well as candidate QTLs and genes for improving pod yield in future peanut breeding.

     

Identification and introgression of QTLs implicated in resistance to sorghum downy mildew (Peronosclerospora sorghi (Weston and Uppal) C. G. Shaw) in maize through marker-assisted selection

Sorghum downy mildew caused by Peronosclerospora sorghi is a major disease of maize and resistance is under the control of polygenes which necessitated identification of quantitative-trait loci (QTLs) for initiating marker-assisted introgression of resistant QTLs in elite susceptible inbred lines. In the present study, QTLs for sorghum downy mildew (SDM) resistance in maize were identified based on cosegregation with linked simple sequence repeats in 185 F₂ progeny from a cross between susceptible (CM500-19) and resistant (MAI105) parents. F₃ families were screened in the National Sorghum Downy Mildew Screening Nursery during 2010 and 2011. High heritability was observed for the disease reaction. The final map generated using 87 SSR markers had 10 linkage groups, spanning a length of 1210.3 cM. Although, we used only 87 SSR markers for mapping, the per cent of genome within 20 cM to the nearest marker was 88.5. Three putative QTLs for SDM resistance were located on chromosomes 3 (bin 3.01), 6 (bin 6.01) and 2 (bin 2.02) using composite interval mapping. The locus on chromosome 3 had a major effect and explained up to 12.6% of the phenotypic variation. The other two QTLs on chromosomes 6 and 2 had minor effects with phenotypic variation of 7.1 and 2%. The three QTLs appeared to have additive effects on resistance. The QTLs on chromosomes 3 and 6 were successfully used in the marker-assisted selection programme for introgression of resistance to SDM in eight susceptible maize lines.     

Genetic mapping and QTL analysis for yield and agronomic traits with an F2:3 population derived from a waxy corn × sweet corn cross

We constructed a framework map using SSR markers in the F₂ population derived from a cross between a waxy corn inbred line and a sweet corn inbred line. We constructed a genetic linkage map of the F_2:3 population employing 295 SSR markers on 158 F₂ individuals produced from the cross. The map comprised a total genomic length of 2,626.5 cM in 10 linkage groups and an average distance between markers of 8.9 cM. The number of loci per linkage group ranged from 27 (chr. 5) to 34 (chr. 7). The genetic distance per linkage group ranged from 213.6 cM (chr. 10) to 360.6 cM (chr. 2). Χ ² tests revealed that 254 markers (86.1 %) distributed over all 10 chromosomes exhibited a Mendelian segregation ratio of 1:2:1. A total of 14 quantitative trait loci (QTLs) for days to silking (DTS), plant height (PH), ear height (EH), ear height ratio (ER), ear length (L-ear), and setted ear length (L-sear) were found in the 158 F₂ progeny. They were mapped to chromosomes 1, 2, 3, 7, 8, and 10. Among them, one QTL was associated with DTS, three with PH, six with EH, one with ER, two with L-ear, and one QTL was related to L-sear. In our study, we found that four QTLs: qDTS1, qEH1a, qEH1b, and qPH1, were clustered between umc2390 and umc1603 on chromosome 1. These new QTLs identified by the present study could serve as useful molecular markers in selecting for yield and agronomic traits in maize. The results of this study may improve the identification and characterization of genes responsible for yield and agronomic traits in waxy corn and sweet corn.     

Targeted linkage map densification to improve cell wall related QTL detection and interpretation in maize

Several QTLs for cell wall degradability and lignin content were previously detected in the F288 × F271 maize RIL progeny, including a set of major QTLs located in bin 6.06. Unexpectedly, allelic sequencing of genes located around the bin 6.06 QTL positions revealed a monomorphous region, suggesting that these QTLs were likely “ghost” QTLs. Refining the positions of all QTLs detected in this population was thus considered, based on a linkage map densification in most important QTL regions, and in several large still unmarked regions. Re-analysis of data with an improved genetic map (173 markers instead of 108) showed that ghost QTLs located in bin 6.06 were then fractionated over two QTL positions located upstream and downstream of the monomorphic region. The area located upstream of bin 6.06 position carried the major QTLs, which explained from 37 to 59 % of the phenotypic variation for per se values and extended on only 6 cM, corresponding to a physical distance of 2.2 Mbp. Among the 92 genes present in the corresponding area of the B73 maize reference genome, nine could putatively be considered as involved in the formation of the secondary cell wall [bHLH, FKBP, laccase, fasciclin, zinc finger C2H2-type and C3HC4-type (two genes), NF-YB, and WRKY]. In addition, based on the currently improved genetic map, eight QTLs were detected in bin 4.09, while only one QTL was highlighted in the initial investigation. Moreover, significant epistatic interaction effects were shown for all traits between these QTLs located in bin 4.09 and the major QTLs located in bin 6.05. Three genes related to secondary cell wall assembly (ZmMYB42, COV1-like, PAL-like) underlay QTL support intervals in this newly identified bin 4.09 region. The current investigations, even if they were based only on one RIL progeny, illustrated the interest of a targeted marker mapping on a genetic map to improve QTL position.     

Construction of a sequence-based bin map and mapping of QTLs for downy mildew resistance at four developmental stages in Chinese cabbage (<Emphasis Type="Italic">Brassica rapa</Emphasis> L. ssp. <Emphasis Type="Italic">pekinensis</Emphasis>)

Specific-locus amplified fragment sequencing is a high-resolution method for genetic mapping, genotyping, and single nucleotide polymorphism (SNP) marker discovery. Previously, a major QTL for downy mildew resistance, BraDM, was mapped to linkage group A08 in a doubled-haploid population derived from Chinese cabbage lines 91–112 and T12–19. The aim of the present study was to improve the linkage map and identify the genetic factors involved in downy mildew resistance. We detected 53,692 high quality SLAFs, of which 7230 were polymorphic, and 3482 of the polymorphic markers were used in genetic map construction. The final map included 1064 bins on ten linkage groups and was 858.98 cM in length, with an average inter-locus distance of 0.81 cM. We identified six QTLs that are involved in downy mildew resistance. The four major QTLs, sBrDM8, yBrDM8, rBrDM8, and hBrDM8, for resistance at the seedling, young plant, rosette, and heading stages were mapped to A08, and are identical to BraDM. The two minor resistance QTLs, rBrDM6 (A06) and hBrDM4 (A04), were active at the rosette and heading stages. The major QTL sBrDM8 defined a physical interval of ~228 Kb on A08, and a serine/threonine kinase family gene, Bra016457, was identified as the possible candidate gene. We report here the first high-density bin map for Chinese cabbage, which will facilitate mapping QTLs for economically important traits and SNP marker development. Our results also expand knowledge of downy mildew resistance in Chinese cabbage and provide three SNP markers (A08-709, A08-028, and A08-018) that we showed to be effective when used in MAS to breed for downy mildew resistance in B. rapa.     

Construction of the First High-Density Genetic Linkage Map and Analysis of Quantitative Trait Loci for Growth-Related Traits in <Emphasis Type="Italic">Sinonovacula constricta</Emphasis>

The razor clam (Sinonovacula constricta) is an important aquaculture species, for which a high-density genetic linkage map would play an important role in marker-assisted selection (MAS). In this study, we constructed a high-density genetic map and detected quantitative trait loci (QTLs) for Sinonovacula constricta with an F₁ cross population by using the specific locus amplified fragment sequencing (SLAF-seq) method. A total of 315,553 SLAF markers out of 467.71 Mreads were developed. The final linkage map was composed of 7516 SLAFs (156.60-fold in the parents and 20.80-fold in each F₁ population on average). The total distance of the linkage map was 2383.85 cM, covering 19 linkage groups with an average inter-marker distance of 0.32 cM. The proportion of gaps less than 5.0 cM was on average 96.90%. A total of 16 suggestive QTLs for five growth-related traits (five QTLs for shell height, six QTLs for shell length, three QTLs for shell width, one QTL for total body weight, and one QTL for soft body weight) were identified. These QTLs were distributed on five linkage groups, and the regions showed overlapping on LG9 and LG13. In conclusion, the high-density genetic map and QTLs for S. constricta provide a valuable genetic resource and a basis for MAS.     

Genetic mapping of ovary colour and quantitative trait loci for carotenoid content in the fruit of <Emphasis Type="Italic">Cucurbita maxima</Emphasis> Duchesne

The high content of carotenoids, sugars, dry matter, vitamins and minerals makes the fruit of winter squash (Cucurbita maxima Duchesne) a valuable fresh-market vegetable and an interesting material for the food industry. Due to their nutritional value, long shelf-life and health protective properties, winter squash fruits have gained increased interest from researchers in recent years. Despite these advantages, the genetic and genomic resources available for C. maxima are still limited. The aim of this study was to use the genetic mapping approach to map the ovary colour locus and to identify the quantitative trait loci (QTLs) for high carotenoid content and flesh colour. An F₆ recombinant inbred line (RIL) mapping population was developed and used for evaluations of ovary colour, carotenoid content and fruit flesh colour. SSR markers and DArTseq genotyping-by-sequencing were used to construct an advanced genetic map that consisted of 1824 molecular markers distributed across linkage groups corresponding to 20 chromosomes of C. maxima. Total map length was 2208 cM and the average distance between markers was 1.21 cM. The locus affecting ovary colour was mapped at the end of chromosome 14. The identified QTLs for carotenoid content in the fruit and fruit flesh colour shared locations on chromosomes 2, 4 and 14. QTLs on chromosomes 2 and 4 were the most meaningful. A correlation was clearly confirmed between fruit flesh colour as described by the chroma value and carotenoid content in the fruit. A high-density genetic map of C. maxima with mapped loci for important fruit quality traits is a valuable resource for winter squash improvement programmes.     

Identification of QTL for maize grain yield and kernel-related traits

Grain yield (GY) is one of the most important and complex quantitative traits in maize (Zea mays L.) breeding practice. Quantitative trait loci (QTLs) for GY and three kernel-related traits were detected in a set of recombinant inbred lines (RILs). One hundred and seven simple sequence repeats (SSRs) and 168 insertion/deletion polymorphism markers (Indels) were used to genotype RILs. Eight QTLs were found to be associated with four yield-related traits: GY, 100-kernel weight (HKW), 10-kernel length (KL), and 10-kernel length width (KW). Each QTL explained between 5.96 (qKL2-1) and 13.05 (qKL1-1) per cent of the phenotypic variance. Notably, one common QTL, located at the marker interval between bnlg1893 and chr2-236477 (chromosomal bin 2.09) simultaneously controlled GY and HKW; another common QTL, at bin 2.03 was simultaneously responsible for HKW and KW. Of the QTLs identified, only one pair of significant epistatic interaction involved in chromosomal region at bin 2.03 was detected for HKW; no significant QTL × environment interactions were observed. These results provide the common QTLs and for marker-assisted breeding.     

Quantitative trait locus (QTL) analysis of fruit-quality traits for mandarin breeding in Japan

The improvement of fruit quality is an important objective in citrus breeding. Using an F₁ segregating population from a cross between citrus cultivars ‘Harehime’ (‘E647’—‘Kiyomi’ [Citrus unshiu Marcow. ‘Miyagawa Wase’ × Citrus sinensis (L.) Osbeck ‘Trovita’] × ‘Osceola’—a cultivar of clementine [Citrus clementina hort. ex Tanaka] × ‘Orland’ [Citrus paradisi Macfad. ‘Duncan’ × Citrus tangerina hort. ex Tanaka] × ‘Miyagawa Wase’) and ‘Yoshida’ ponkan (Citrus reticulata Blanco ‘Yoshida’), a SNP-based genetic linkage map was constructed and quantitative trait locus (QTL) mapping of four fruit-quality traits (fruit weight, sugar content, peel puffing, and water rot) was performed. The constructed genetic linkage map of ‘Harehime’ consisted of 442 single nucleotide polymorphisms (SNPs) on 9 linkage groups (LGs) and covered 635.8 cM of the genome, while that of ‘Yoshida’ ponkan consisted of 332 SNPs on 9 LGs and covered 892.9 cM of its genome. We identified four QTLs associated with fruit weight, one QTL associated with sugar content, three QTLs associated with peel puffing, and one QTL associated with water rot. For these QTL regions, we estimated the haplotypes of the crossed parents and verified the founding cultivars that these QTLs were originated from and their inheritance in descendant cultivars using pedigree information. QTLs identified in this study provide useful information for marker-assisted breeding of citrus in Japan.     

Genetic analysis of shoot fresh weight in a cross of wild (<Emphasis Type="Italic">G. soja</Emphasis>) and cultivated (<Emphasis Type="Italic">G. max</Emphasis>) soybean

Shoot fresh weight (SFW) is one of the parameters, used to estimate the total plant biomass yield in soybean. In the present study, a total of 188 F_5:8 recombinant inbred lines (RIL) derived from an interspecific cross of PI 483463 (Glycine soja) and Hutcheson (Glycine max) were investigated for SFW variation in the field for three consecutive years. The parental lines and RILs were phenotyped in the field at the R6 stage by measuring total biomass in kg/plot to identify the QTLs for SFW. Three QTLs qSFW6_1, qSFW15_1, and qSFW19_1 influencing SFW were identified on chromosome 6, 15, and 19, respectively. The QTL qSFW19_1 flanked between the markers BARC-044913-08839 and BARC-029975-06765 was the stable QTL expressed in all the three environments. The phenotypic variation explained by the QTLs across all environments ranged from 6.56 to 21.32 %. The additive effects indicated contribution of alleles from both the parents and additive × environment interaction effects affected the expression of SFW QTL. Screening of the RIL population with additional SSRs from the qSFW19_1 region delimited the QTL between the markers SSR19-1329 and BARC-29975-06765. QTL mapping using bin map detected two QTLs, qSFW19_1A and qSFW19_1B. The QTL qSFW19_1A mapped close to the Dt1 gene locus, which affects stem termination, plant height, and floral initiation in soybean. Potential candidate genes for SFW were pinpointed, and sequence variations within their sequences were detected using high-quality whole-genome resequencing data. The findings in this study could be useful for understanding genetic basis of SFW in soybean.     

Construction of a high-density SNP genetic map in flue-cured tobacco based on SLAF-seq

Tobacco (Nicotiana tabacum L., 2n = 48) is an important agronomic crop and model plant. Flue-cured tobacco is the most important type and accounts for approximately 80 % of tobacco production worldwide. The low genetic diversity of flue-cured tobacco impedes the construction of a high-density genetic linkage map using simple sequence repeat (SSR) markers and warrants the exploitation of single nucleotide polymorphic (SNP) markers from genomic regions. In this article, initially using specific locus-amplified fragment sequencing, we discovered 10,891 SNPs that were subsequently used as molecular markers for genetic map construction. Combined with SSR markers, a final high-density genetic map was generated containing 4215 SNPs and 194 SSRs distributed on 24 linkage groups (LGs). The genetic map was 2662.43 cM in length, with an average distance of 0.60 cM between adjacent markers. Furthermore, by mapping the SNP markers to the ancestral genomes of Nicotiana tomentosiformis and Nicotiana sylvestris, a large number of genome rearrangements were identified as occurring after the polyploidization event. Finally, using this novel integrated map and mapping population, two major quantitative trait loci (QTLs) were identified for flue-curing and mapped to the LG6 of tobacco. This is the first report of SNP markers and a SNP-based linkage map being developed in tobacco. The high-density genetic map and QTLs related to tobacco curing will support gene/QTL fine mapping, genome sequence assembly and molecular breeding in tobacco.     

QTL mapping for the paste viscosity characteristics in rice (Oryza sativa L.)

In order to understand the genetic basis of the paste viscosity characteristics (RVA profile, which is tested on the Rapid Visco Analyser) of the rice grain, we mapped QTLs for RVA profile parameters using a DH population derived from a cross between an indica variety, Zai-Ye-Qing 8 (ZYQ8), and a japonica variety, Jing-Xi 17 (JX17). Evidence of genotype-by-environment interaction was found by comparing the mapped QTLs between two locations, Hainan (HN) and Hangzhou (HZ). A total of 20 QTLs for six parameters of the RVA profiles were identified at least one location. Only the waxy locus (wx) located on chromosome 6 was detected significantly at both environments for five traits, i.e. hot paste viscosity (HPV), cool paste viscosity (CPV), breakdown viscosity (BDV), consistency viscosity (CSV) and setback viscosity (SBV). This locus explained 19.5%–63.7% of the total variations at both environments, suggesting that the RVA profiles were mainly controlled by the wx gene. HPV, CPV, BDV, CSV and SBV were also controlled by other QTLs whose effects on the respective parameter were detected only in one environment, while for the peak viscosity (PKV), only 2 QTLs, 1 at HN,the other at HZ, were identified. These results indicate that RVA profiles are obviously affected by environment. Received: 18 July 1999 / Accepted: 27 August 1999     

QTL mapping of mandarin (<Emphasis Type="Italic">Citrus reticulata</Emphasis>) fruit characters using high-throughput SNP markers

Seedlessness, flavor, and color are top priorities for mandarin (Citrus reticulata Blanco) cultivar improvement. Given long juvenility, large tree size, and high breeding cost, marker-assisted selection (MAS) may be an expeditious and economical approach to these challenges. The objectives of this study were to construct high-density mandarin genetic maps and to identify single nucleotide polymorphism (SNP) markers associated with fruit quality traits. Two parental genetic maps were constructed from an F₁ population derived from ‘Fortune’ × ‘Murcott’, two mandarin cultivars with distinct fruit characters, using a 1536-SNP Illumina GoldenGate assay. The map for ‘Fortune’ (FOR) consisted of 189 SNPs spanning 681.07 cM and for ‘Murcott’ (MUR) consisted of 106 SNPs spanning 395.25 cM. Alignment of the SNP sequences to the Clementine (Citrus clementina) genome showed highly conserved synteny between the genetic maps and the genome. A total of 48 fruit quality quantitative trait loci (QTLs) were identified, and ten of them stable over two or more samplings were considered as major QTLs. A cluster of QTLs for flavedo color space values L, a, b, and a/b and juice color space values a and a/b were detected in a single genomic region on linkage group 4. Two carotenoid biosynthetic pathway genes, pds1 and ccd4, were found within this QTL interval. Several SNPs were potentially useful in MAS for these fruit characteristics. QTLs were validated in 13 citrus selections, which may be useful in further validation and tentative MAS in mandarin fruit quality improvement.     

Construction of high-density linkage map and identification of QTLs for resistance to sorghum downy mildew in maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.)

Sorghum downy mildew (SDM), caused by obligate biotrophic fungi Peronosclerospora sorghi, is an economically important disease of maize. The genetics of resistance was reported to be polygenic thereby necessitating identification of QTLs for resistance to SDM to initiate effective marker-assisted selection programs. During post-rainy and winter season of 2012, 645 F_2:3 progeny families from the cross CML153 (susceptible) × CML226 (resistant) were screened for their reaction to SDM. Characterization of QTLs affecting resistance to SDM was undertaken using the genetic linkage map with 319 polymorphic SSR and SNP marker loci and the phenotypic data of F_2:3 families. Three QTLs conferring resistance to SDM were consistently identified on chromosomes 2, 3 and 6 in both seasons. The resistant parent CML226 contributed all the QTL alleles conferring resistance to SDM. The major QTL located on chromosome 2 explained 38.68% of total phenotypic variation in the combined analysis with a LOD score of 9.12. All the three QTL showed partially dominant gene effects in combined analysis. The detection of more than one QTL supports the hypothesis that quantitative genes control resistance to P. sorghi. The generation was advanced to F₆ using markers linked to major QTLs on chromosomes 2 and 3 to derive 33 SDM resistant maize inbred lines.     

QTL mapping for yield and photosynthetic related traits under different water regimes in wheat

The improvement for drought tolerance requires understanding of the genetic control of wheat (Triticum aestivum L.) reaction to drought. In this study, a set of 131 recombinant inbred lines of wheat were investigated under well-watered (WW) and drought stress (DS) environments across 2 years to map quantitative trait loci (QTLs) for yield and physiological traits. A total of 225 QTLs were detected, including 32 non-environment-specific loci that were significant in both DS and WW, one drought-specific locus and two watering-specific loci. Three consistently-expressed QTLs (QTkw-3A.2, QTss-1A, and QScn-7A.1) were identified in at least three environments and the QTkw-1D.1 was significant in DS across the 2 years. By unconditional and conditional QTL analysis, spike number per plant and kernel number per spike were more important than thousand-kernel weight for grain yield (GY) at the given genetic background. Meta-analysis identified 67 meta-QTLs that contained QTLs for at least two traits. High frequency co-location of QTLs was found among either the spike-related traits or the six physiological traits. Four photosynthesis traits (CHL, LWUE, P _N, and C _i) were co-located with GY and/or yield components on various MQTLs. The results provided QTLs that warrant further study for drought tolerance breeding and are helpful for understanding the genetic basis of drought tolerance and the genetic contribution of yield components to GY at individual QTL level in wheat.     

Genetic mapping of local adaptation along the altitudinal gradient in <Emphasis Type="Italic">Abies sachalinensis</Emphasis>

Understanding the genetic bases of local adaptation in dominant conifer species is critical in predicting the impacts of rapid climate change on forest ecosystems. However, the genetic basis of adaptation is not yet fully understood due to the huge and complex genomes of conifers and the unavailability to date of suitable crossing material. In this study, we constructed a linkage map for Abies sachalinensis (2n = 24) and investigated quantitative trait loci (QTLs) associated with local adaptation along an altitudinal gradient. A segregating population of 239 seedlings was produced from a cross between two F₁ hybrids (high-altitude × low-altitude genotypes). QTL mapping of phenological and growth traits was performed using a pseudo-testcross strategy with linkage maps based on 1251 single-nucleotide polymorphism (SNP) and three simple sequence repeat (SSR) markers. Two maps consisting of 12 linkage groups with an average marker interval of ca. 3 cM were constructed for each parent. The total lengths of the maps were 1861 and 1949 cM. A permutation test identified four significant QTLs and 11 additional suggestive QTLs, with high logarithm of odds (LOD) scores (> 3.0). This is the first highly saturated linkage map produced for Abies taxa. Our results suggest that spring bud phenology is controlled by several QTLs with moderate effects. The use of the mapping population created by crossing two hybrids (high × low altitude genotypes) and numerous SNP markers enabled us to investigate the genetic basis of adaptive traits in conifer species.     

Quantitative trait locus mapping under irrigated and drought treatments based on a novel genetic linkage map in mungbean (<Emphasis Type="Italic">Vigna radiata</Emphasis> L.)

Key message

A novel genetic linkage map was constructed using SSR markers and stable QTLs were identified for six drought tolerance related-traits using single-environment analysis under irrigation and drought treatments.

Abstract

Mungbean (Vigna radiata L.) is one of the most important leguminous food crops. However, mungbean production is seriously constrained by drought. Isolation of drought-responsive genetic elements and marker-assisted selection breeding will benefit from the detection of quantitative trait locus (QTLs) for traits related to drought tolerance. In this study, we developed a full-coverage genetic linkage map based on simple sequence repeat (SSR) markers using a recombinant inbred line (RIL) population derived from an intra-specific cross between two drought-resistant varieties. This novel map was anchored with 313 markers. The total map length was 1010.18 cM across 11 linkage groups, covering the entire genome of mungbean with a saturation of one marker every 3.23 cM. We subsequently detected 58 QTLs for plant height (PH), maximum leaf area (MLA), biomass (BM), relative water content, days to first flowering, and seed yield (Yield) and 5 for the drought tolerance index of 3 traits in irrigated and drought environments at 2 locations. Thirty-eight of these QTLs were consistently detected two or more times at similar linkage positions. Notably, qPH5A and qMLA2A were consistently identified in marker intervals from GMES5773 to MUS128 in LG05 and from Mchr11-34 to the HAAS_VR_1812 region in LG02 in four environments, contributing 6.40–20.06% and 6.97–7.94% of the observed phenotypic variation, respectively. None of these QTLs shared loci with previously identified drought-related loci from mungbean. The results of these analyses might facilitate the isolation of drought-related genes and help to clarify the mechanism of drought tolerance in mungbean.

     

Identification and genetic mapping for <Emphasis Type="Italic">rht-DM</Emphasis>, a dominant dwarfing gene in mutant semi-dwarf maize using QTL-seq approach

Semi-dwarfism is an agronomically important trait in breeding for stable high yields and for resistance to damage by wind and rain (lodging resistance). Many QTLs and genes causing dwarf phenotype have been found in maize. However, because of the yield loss associated with these QTLs and genes, they have been difficult to use in breeding for dwarf stature in maize. Therefore, it is important to find the new dwarfing genes or materials without undesirable characters. The objectives of this study were: (1) to figure out the inheritance of semi-dwarfism in mutants; (2) mapping dwarfing gene or QTL. Maize inbred lines ‘18599’ and ‘DM173’, which is the dwarf mutant derived from the maize inbred line ‘173’ through ⁶⁰Co-γ ray irradiation. F₂ and BC₁F₁ population were used for genetic analysis. Whole genome resequencing-based technology (QTL-seq) were performed to map dwarfing gene and figured out the SNP markers in predicted region using dwarf bulk and tall bulk from F₂ population. Based on the polymorphic SNP markers from QTL-seq, we were fine-mapping the dwarfing gene using F₂ population. In F₂ population, 398 were dwarf plants and 135 were tall plants. Results of χ² tests indicated that the ratio of dwarf plants to tall plants was fitted to 3:1 ratio. Furthermore, the χ² tests of BC₁F₁ population showed that the ratio was fitted to 1:1 ratio. Based on QTL-seq, the dwarfing gene was located at the region from 111.07 to 124.56 Mb of chromosome 9, and we named it rht-DM. Using traditional QTL mapping with SNP markers, the rht-DM was narrowed down to 400 kb region between SNP-21 and SNP-24. The two SNPs were located at 0.43 and 0.11 cM. Segregation analysis of F₂ and BC₁F₁ indicated that the dwarfing gene was likely a dominant gene. This dwarfing gene was located in the region between 115.02 and 115.42 Mb on chromosome 9.