Stable Quantitative Trait Loci Research Articles

Identification of genetic loci for flag-leaf-related traits in wheat (Triticum aestivum L.) and their effects on grain yield.

Flag-leaf-related traits including length (FLL), width (FLW), area (FLA), thickness (FLT), and volume (FLV) of flag leaves are the most important determinants of plant architecture and yield in wheat. Understanding the genetic basis of these traits could accelerate the breeding of high yield wheat varieties. In this study, we constructed a doubled haploid (DH) population and analyzed flag-leaf-related traits in five experimental locations/years using the wheat 90K single-nucleotide polymorphism array. It’s worth noting that a novel method was used to measure FLT and FLV easily. Leaf thickness at two-thirds of the leaf length from tip to collar represented the average leaf thickness as measured with freehand sections and was used to calculate the leaf volume. In addition, flag-leaf-related traits showed positive correlations with yield related traits under two different water regimes. A total of 79 quantitative trait loci (QTL) controlling the five traits were detected among all chromosomes except 4D and 5A, explaining 3.09–14.52% of the phenotypic variation. Among them, 15 stable QTL were identified in more than three environments, including two major QTL for FLT, six for FLW, three for FLA, two for FLT and two for FLV. DH lines with positive alleles at both QTL regions had an average FLL (9.90%), FLW (32.87%), FLT (6.62%), FLA (18.47%), and FLV (20.87%) greater than lines with contrasting alleles. QFLT-2B, QFLV-2A, and QFLV-7D were co-located with yield-related traits. The 15 QTL were validated by tightly linked kompetitive allele specific PCR (KASP) markers in a recombinant inbred line (RIL) population derived from a different cross. QFLL-4A, QFLW-4B, QFLA-5D.1, QFLA-7A, QFLA-7D.1, QFLT-2B, QFLT-6A, QFLV-2A, and QFLV-7D are likely novel loci. These results provide a better understanding of the genetic basis underlying flag-leaf-related traits. Also, target regions for fine mapping and marker-assisted selection were identified and these will be valuable for breeding high yielding bread wheat.

Quantitative trait loci identification and breeding value estimation of grain weight-related traits based on a new wheat 50K single nucleotide polymorphism array-derived genetic map.

Mining novel and less utilized thousand grain weight (TGW) related genes are useful for improving wheat yield. In this study, a recombinant inbred line population from a cross between Zhongkemai 138 (ZKM138, high TGW) and Chuanmai 44 (CM44, low TGW) was used to construct a new Wheat 50K SNP array-derived genetic map that spanned 1,936.59 cM and contained 4, 139 markers. Based on this map, ninety-one quantitative trait loci (QTL) were detected for eight grain-related traits in six environments. Among 58 QTLs, whose superior alleles were contributed by ZKM138, QTgw.cib-6A was a noticeable major stable QTL and was also highlighted by bulked segregant analysis with RNA sequencing (BSR-Seq). It had a pyramiding effect on TGW enhancement but no significant trade-off effect on grain number per spike or tiller number, with two other QTLs (QTgw.cib-2A.2 and QTgw.cib-6D), possibly explaining the excellent grain performance of ZKM138. After comparison with known loci, QTgw.cib-6A was deduced to be a novel locus that differed from nearby TaGW2 and TaBT1. Seven simple sequence repeat (SSR) and thirty-nine kompetitive allele-specific PCR (KASP) markers were finally developed to narrow the candidate interval of QTgw.cib-6A to 4.1 Mb. Only six genes in this interval were regarded as the most likely candidate genes. QTgw.cib-6A was further validated in different genetic backgrounds and presented 88.6% transmissibility of the ZKM138-genotype and a 16.4% increase of TGW in ZKM138 derivatives. And the geographic pattern of this locus revealed that its superior allele is present in only 6.47% of 433 Chinese modern wheat varieties, indicating its potential contribution to further high-yield breeding.

Pleiotropic effect analysis and marker development for grain zinc and iron concentrations in spring wheat.

Wheat (Triticum aestivum L.) is one of the main food crops in the world and a primary source of zinc (Zn) and iron (Fe) in the human body. The genetic mechanisms underlying related traits have been clarified, thereby providing a molecular theoretical foundation for the development of germplasm resources. In this study, a total of 23,536 high-quality DArT markers was used to map quantitative trait loci (QTL) of grain Zn (GZn) and grain Fe (GFe) concentrations in recombinant inbred lines crossed by Avocet/Chilero. A total of 17 QTLs was located on chromosomes 1BL, 2BL, 3BL, 4AL, 4BS, 5AL, 5DL, 6AS, 6BS, 6DS, and 7AS accounting for 0.38-16.62% of the phenotypic variance. QGZn.haust-4AL, QGZn.haust-7AS.1, and QGFe.haust-6BS were detected on chromosomes 4AL, 6BS, and 7AS, accounting for 10.63-16.62% of the phenotypic variance. Four stable QTLs, QGZn.haust-4AL, QGFe.haust-1BL, QGFe.haust-4AL, and QGFe.haust-5DL, were located on chromosomes 1BL, 4AL, and 5DL. Three pleiotropic effects loci for GZn and GFe concentrations were located on chromosomes 1BL, 4AL, and 5DL. Two high-throughput Kompetitive Allele Specific PCR markers were developed by closely linking single-nucleotide polymorphisms on chromosomes 4AL and 5DL, which were validated by a germplasm panel. Therefore, it is the most important that quantitative trait loci and KASP marker for grain zinc and iron concentrations were developed for utilizing in marker-assisted breeding and biofortification of wheat grain in breeding programs.

Genetic dissection of lutein content in common wheat via association and linkage mapping.

Genetic architecture controlling grain lutein content of common wheat was investigated through an integration of genome-wide association study (GWAS) and linkage analysis. Putative candidate genes involved in carotenoid metabolism and regulation were identified, which provide a basis for gene cloning and development of nutrient-enriched wheat varieties through molecular breeding. Lutein, known as 'the eye vitamin', is an important component of wheat nutritional and end-use quality. However, the genetic manipulation of grain lutein content (LUC) in common wheat has not previously been well studied. Here, quantitative trait loci (QTL) associated with the LUC measured by high performance liquid chromatography (HPLC) were first identified by integrating a genome-wide association study (GWAS) and linkage mapping. A Chinese wheat mini-core collection (MCC) of 262 accessions and a doubled haploid (DH) population derived from Jinchun 7 and L1219 were genotyped using the 90K SNP array. A total of 124 significant marker-trait associations (MTAs) on all 21 wheat chromosomes except for 1A, 4D, and 5B that formed 58 QTL were detected. Among them, six stable QTL were identified on chromosomes 2AL, 2DS, 3BL, 3DL, 7AL, and 7BS. Meanwhile, three of the ten QTL identified in the DH population, QLuc.5A.1 and QLuc.5A.2 on chromosome 5AL and QLuc.6A.2 on 6AS, were stable and independently explained 5.58-10.86% of the phenotypic variation. The QLuc.6A.2 region colocalized with two MTAs identified by GWAS. Moreover, 71 carotenoid metabolism-related candidate genes were identified, and the allelic effects were analyzed in the MCC panel based on the 90K array. Results revealed that the genes CYP97A3 (Chr. 6B) and CCD1 (Chr. 5A) were significantly associated with LUC. Additionally, the gene PSY3 (QLuc.5A.1) and several candidate genes involved in the methylerythritol 4-phosphate (MEP) pathways colocalized with stable QTL regions. The present study provides potential targets for future functional gene exploration and molecular breeding in common wheat.

Molecular mapping of quantitative trait loci for 3 husk traits using genotyping by sequencing in maize (Zea mays L.)

The maize (Zea mays L.) husk consists of multiple leaf layers and plays an important role in grain growth and development. Despite significant achievements in physiological and morphological research, few studies have focused on the detection of genetic loci underlying husk-related traits due to the lack of efficient tools. In this study, we constructed an ultra-high-density linkage map using genotyping by sequencing based on a recombinant inbred line population to estimate the genetic variance and heritability of 3 husk traits, i.e. husk length, husk width, and husk layer number in 3 field environments and the combined environment. The 3 husk traits showed broad phenotypic variation and high heritability; the broad-sense heritability (H2) was 0.92, 0.84, and 0.86. Twenty quantitative trait loci were consistently detected more than 1 environment, including 9 for husk length, 6 for husk width, and 5 for husk layer number. These loci were considered as stable quantitative trait loci. Based on the quantitative trait loci mapping in the recombinant inbred line population, qHL6 and qHN4 were detected across all environments and inferred to be reliable and major-effect quantitative trait loci for husk length and husk layer number, respectively. In addition, several predicted candidate genes were identified in the region of qHL6 and qHN4, of which 17 candidate genes potentially play a role in biological processes related to development process and energy metabolism. These results will be as a useful resource for performing functional studies aimed at understanding the molecular pathways involved in husk growth and development.

Whole-genome analysis of hard winter wheat germplasm identifies genomic regions associated with spike and kernel traits.

Genetic dissection of yield component traits including spike and kernel characteristics is essential for the continuous improvement in wheat yield. Genome-wide association studies (GWAS) have been frequently used to identify genetic determinants for spike and kernel-related traits in wheat, though none have been employed in hard winter wheat (HWW) which represents a major class in US wheat acreage. Further, mostof these studies relied on assembled diversity panels instead of adapted breeding lines, limiting the transferability of results to practicalwheat breeding. Here we assembled a population of advanced/elite breeding lines and well-adapted cultivars and evaluated over four environments for phenotypic analysis of spike and kernel traits. GWAS identified 17 significant multi-environment marker-trait associations (MTAs) for various traits, representing 12 putative quantitative trait loci (QTLs), with five QTLs affecting multiple traits. Four of these QTLs mapped on three chromosomes 1A, 5B, and 7A for spike length, number of spikelets per spike (NSPS), and kernel length are likely novel. Further, a highly significant QTL was detected on chromosome 7AS that has not been previously associated with NSPS and putative candidate genes were identified in this region. The allelic frequencies of important quantitative trait nucleotides (QTNs)were deduced in a larger set of 1,124 accessions which revealed the importance of identified MTAs in the US HWW breeding programs. The results from this study could be directly used by thebreeders to select the lines with favorable alleles for making crosses, and reported markers will facilitate marker-assisted selection of stable QTLs for yield components in wheat breeding.

Association mapping of lignin response to Verticillium wilt through an eight-way MAGIC population in Upland cotton

Lignin metabolism plays a pivotal role in plant defense against pathogens and is always positively correlated as a response to pathogen infection. Thus, understanding resistance genes against plant pathogens depends on a genetic analysis of the lignin response. This study used eight Upland cotton lines to construct a multi-parent advanced generation intercross (MAGIC) population (n=280), which exhibited peculiar characteristics from the convergence of various alleles coding for advantageous traits. In order to measure the lignin response to Verticillium wilt (LRVW), the artificial disease nursery (ADN) and rotation nursery (RN) were prepared for MAGIC population planting in four environments. The stem lignin contents were collected, and the LRVW was measured with the lignin value of ADN/RN in each environment, which showed significant variations. We employed 9 323 high-quality single-nucleotide polymorphism (SNP) markers obtained from the Cotton-SNP63K array for genotyping the MAGIC population. The SNPs were distributed through the whole genome with 4.78 SNP/Mb density, ranging from 1.14 (ChrA06) to 10.08 (ChrD08). In addition, a genome-wide association study was performed using a Mixed Linear Model (MLM) for LRVW. Three stable quantitative trait loci (QTLs), qLRVW-A04, qLRVW-A10, and qLRVW-D05, were identified in more than two environments. Two key candidate genes, Ghi_D05G01046 and Ghi_D05G01221, were selected within the QTLs through the combination of variations in the coding sequence, induced expression patterns, and function annotations. Both genes presented nonsynonymous mutations in coding regions and were strongly induced by Verticillium dahliae. Ghi_D05G01046 encodes a leucine-rich extensin (LRx) protein involved in Arabidopsis cell wall biosynthesis and organization. Ghi_D05G01221 encodes a transcriptional co-repressor novel interactor of novel interactor of jasmonic acid ZIM-domain (JAZ–NINJA), which functions in the jasmonic acid (JA) signaling pathway. In summary, the study creates valuable genetic resources for breeding and QTL mapping and opens up a new perspective to uncover the genetic basis of VW resistance in Upland cotton.

Mapping and validation of major and stable QTL for flag leaf size from tetraploid wheat.

The flag leaf is an important photosynthetic organ of wheat (Triticum aestivum L.). Appropriate flag leaf size can effectively increase grain yield. In this study, a tetraploid wheat population of recombinant inbred lines (RILs) and a genetic map constructed based on a wheat 55K single-nucleotide polymorphism (SNP) array were used to identify quantitative trait loci (QTL) for flag leaf length (FLL), flag leaf width (FLW), flag leaf area (FLA), and the flag leaf length/width ratio (FLR). A novel and major interval flanked by markers AX-111633224 and AX-109317229 was identified. This interval includes QTL for FLL (QFll.sau-AM-4B.2), for FLW (QFlw.sau-AM-4B.4), for FLA (QFla.sau-AM-4B), and for FLR (QFlr.sau-AM-4B). Based on the genotypes of the closely linked KASP (Kompetitive allele-specific polymerase chain reaction [PCR]) marker (KASP-AX-108756198), QFlw.sau-AM-4B.4 and QFla.sau-AM-4B were successfully verified in two F3 populations with different genetic backgrounds. Genetic associations between flag leaf-related traits and other agronomic traits were detected and analyzed. Four genes in this interval were likely involved in the growth and development of the flag leaf size. In conclusion, this study provides clues for excavating genes related to flag leaf size and breeding variety with ideal plant structure.

Identification of genetic loci conferring seed coat color based on a high-density map in soybean.

Seed coat color is a typical evolutionary trait. Identification of the genetic loci that control seed coat color during the domestication of wild soybean could clarify the genetic variations between cultivated and wild soybean. We used 276 F10 recombinant inbred lines (RILs) from the cross between a cultivated soybean (JY47) and a wild soybean (ZYD00321) as the materials to identify the quantitative trait loci (QTLs) for seed coat color. We constructed a high-density genetic map using re-sequencing technology. The average distance between adjacent markers was 0.31 cM on this map, comprising 9,083 bin markers. We identified two stable QTLs (qSC08 and qSC11) for seed coat color using this map, which, respectively, explained 21.933 and 26.934% of the phenotypic variation. Two candidate genes (CHS3C and CHS4A) in qSC08 were identified according to the parental re-sequencing data and gene function annotations. Five genes (LOC100786658, LOC100801691, LOC100806824, LOC100795475, and LOC100787559) were predicted in the novel QTL qSC11, which, according to gene function annotations, might control seed coat color. This result could facilitate the identification of beneficial genes from wild soybean and provide useful information to clarify the genetic variations for seed coat color in cultivated and wild soybean.

Fine mapping and characterization of a major QTL for grain weight on wheat chromosome arm 5DL.

We fine mapped QTL QTKW.caas-5DL for thousand kernel weight in wheat, predicted candidate genes and developed a breeding-applicable marker. Thousand kernel weight (TKW) is an important yield component trait in wheat, and identification of the underlying genetic loci is helpful for yield improvement. We previously identified a stable quantitative trait locus (QTL) QTKW.caas-5DL for TKW in a Doumai/Shi4185 recombinant inbred line (RIL) population. Here we performed fine mapping of QTKW.caas-5DL using secondary populations derived from 15 heterozygous recombinants and delimited the QTL to an approximate 3.9Mb physical interval from 409.9 to 413.8Mb according to the Chinese Spring (CS) reference genome. Analysis of genomic synteny showed that annotated genes in the physical interval had high collinearity among CS and eight other wheat genomes. Seven genes with sequence variation and/or differential expression between parents were predicted as candidates for QTKW.caas-5DL based on whole-genome resequencing and transcriptome assays. A kompetitive allele-specific PCR (KASP) marker for QTKW.caas-5DL was developed, and genotyping confirmed a significant association with TKW but not with other yield component traits in a panel of elite wheat cultivars. The superior allele of QTKW.caas-5DL was frequent in a panel of cultivars, suggesting that it had undergone positive selection. These findings not only lay a foundation for map-based cloning of QTKW.caas-5DL but also provide an efficient tool for marker-assisted selection.

Stable sorghum grain quality QTL were identified using SC35 × RTx430 mapping population.

Understanding the genetic control and inheritance of grain quality traits is instrumental in facilitating end-use quality improvement. This study was conducted to identify and map quantitative trait loci (QTL) controlling protein, starch, and amylose content in grain sorghum [Sorghum bicolor (L.) Moench] grown under variable environmental conditions. A recombinant inbred line (RIL) population derived from a cross between RTx430 and SC35 was evaluated in six environments across Hays and Manhattan, KS. Significant variation was observed in genotype, environment, and genotype × environment interaction for all three quality traits. Unlike the RILs, the two parental lines did not show significant differences for these traits. However, significant transgressive segregation was observed for all traits resulting in phenotypic performance extending beyond the two parents. A total of seven protein, 10 starch, and 10 amylose content QTL were identified. Chromosomal regions and phenotypic variation (PVE) of QTL were variable across growing conditions. Quantitative trait loci hotspots for all three traits were detected on chromosomes 1 (115.2-119.2 cM) and 2 (118.2-127.4 cM). Candidate gene analysis indicated that these QTL hotspots were conditioned by several transcription factors, such as Cytochrome P450 and basic helix-loop-helix DNA binding protein, which regulate starch and protein accumulation in the grain. The identified genomic regions and underlying candidate genes provide a starting point for further validation and marker-assisted gene pyramiding to improve sorghum grain quality.

Genetic analysis of adult plant, quantitative resistance to stripe rust in wheat landrace Wudubaijian in multi-environment trials

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most destructive diseases on wheat worldwide. Wudubaijian, a wheat landrace released from Gansu Province in China since 1950, exhibits adult-plant resistance to stripe rust for several decades. To elucidate the genetic basis of stripe rust resistance, Wudubaijian was crossed with the high susceptible cultivar Mingxian 169, and stripe rust tests of both parents and the F2:3 lines were conducted in four environments of Yangling and Tianshui in 2015 and 2016, respectively. The relative area under disease progress curve (rAUDPC) of Mingxian 169/Wudubaijian F2:3 lines showed that the resistance of Wudubaijian was controlled by quantitative trait loci (QTL). Combined with phenotypic data and molecular markers, two stable QTLs were identified in Wudubaijian. QYrwdbj.nwafu-5A with the phenotypic variance of 15.02–40.26% was located between 5AS1–0.40–0.75 and 5AS3–0.75–0.98 of chromosome 5AS, and QYrwdbj.nwafu-2B.1 with the phenotypic variance of 9.54–10.40% was located in the bin C-2BS1–0.53 of chromosome 2BS. Through the location of flanking markers and epistasis analysis, QYrwdbj.nwafu-5A may be a new major QTL that can be used in conjunction with other stripe rust resistance genes (QTLs).

QTLs Controlling Physiological and Morphological Traits of Barley (Hordeum vulgare L.) Seedlings under Salinity, Drought, and Normal Conditions

To identify the genomic regions for the physiological and morphological traits of barley genotypes under normal salinity and drought, a set of 103 recombinant inbred line (RIL) populations, developed between Badia and Kavir crosses, was evaluated under phytotron conditions in a completely randomized design in 2019. Linkage maps were prepared using 152 SSR markers, 72 ISSR, 7 IRAP, 29 CAAT, 27 SCoT, and 15 iPBS alleles. The markers were assigned to seven barley chromosomes and covered 999.29 centimorgans (cM) of the barley genome. In addition, composite interval mapping showed 8, 9, and 26 quantitative trait loci (QTLs) under normal, drought, and salinity stress conditions, respectively. Our results indicate the importance of chromosomes 1, 4, 5, and 7 in salinity stress. These regions were involved in genes controlling stomata length (LR), leaf number (LN), leaf weight (LW), and genetic score (SCR). Three major stable pleiotropic QTLs (i.e., qSCS-1, qRLS-1, and qLNN-1) were associated with SCR, root length (RL), and root number (RN) in both treatments (i.e., normal and salinity), and two major stable pleiotropic QTLs (i.e., qSNN-3 and qLWS-3) associated with the stomata number (SN) and LW appeared to be promising for marker-assisted selection (MAS). Two major-effect QTLs (i.e., SCot8-B-CAAT5-D and HVM54-Bmag0571) on chromosomes 1 and 2 were characterized for their positive allele effect, which can be used to develop barley varieties concerning drought conditions. The new alleles (i.e., qLWS-4a, qSLS-4, qLNS-7b, qSCS-7, and qLNS-7a) identified in this study are useful in pyramiding elite alleles for molecular breeding and marker assisted selection for improving salinity tolerance in barley.

Genetic mapping of QTL for three root-related traits in wheat (Triticum aestivum)

A well-developed root system plays a positive role in wheat yield. Here, we identified quantitative trait loci (QTL) for total root length (TRL), root average diameter (RD) and number of root tips (RTN) based on the previously developed genetic map of a recombinant inbred line (RIL) population in bread wheat and phenotype data from two individual trials. A stable and major QTL, Qtrl-AS-5A for TRL was detected explaining 17.19 to 17.78% of the phenotypic variation. It was physically located at 680.66-683.25 Mb (∼2.59 Mb interval) on chromosome arm 5AL. Two stably expressed QTLs for RD, Qrd-AS-4A and Qrd-AS-6B, were identified. The phenotype variances explained for them were between 5.11 to 5.43% and 17.42 to 22.40%, respectively. They were physically located at 621.74 Mb-621.93 Mb (∼0.19 Mb) on 4AL and 624.01 − 624.78 Mb (∼0.77 Mb) on 6BL, respectively. One unstably expressed QTL for RN was identified only. Genetic analysis suggested that the two major and stably expressed QTLs, Qtrl-AS-5A and Qrd-AS-6B, were not likely associated with plant height and anthesis date. Comparison analysis indicated that they may be novel loci. Several candidate genes which were mainly expressed in roots were also obtained. Collectively, these results provided several major and stably expressed QTLs for root traits and they should have breeding potential.

Genome-Wide Association Analysis Combined With Quantitative Trait Loci Mapping and Dynamic Transcriptome Unveil the Genetic Control of Seed Oil Content in Brassica napus L.

Rapeseed, an allotetraploid oil crop, provides vegetable oil for human consumption. The growing demand for oilseeds has necessitated the development of rapeseed varieties with improved quality. Therefore, a clear understanding of the genetic basis underlying the seed oil content (SOC) is required. In this study, a natural population comprising 204 diverse accessions and recombinant inbred lines (RILs) derived from Brassica napus and Sinapis alba via distant hybridization were collected for genome-wide association analysis (GWAS) and quantitative trait loci (QTL) mapping of the SOC trait, respectively. The variable coefficient of the RIL and natural populations ranged from 7.43 to 10.43% and 8.40 to 10.91%. Then, a high-density linkage map was constructed based on whole genome re-sequencing (WGS); the map harbored 2,799 bin markers and covered a total distance of 1,835.21 cM, with an average marker interval of 0.66 cM. The QTLs for SOC on chromosome A07 were stably detected in both single and multiple environments. Finally, a novel locus qA07.SOC was identified as the major QTL for SOC based on the GWAS and RIL populations. In addition, the RNA-seq results showed that photosynthesis, lipid biosynthesis proteins, fatty acid metabolism, and unsaturated fatty acid biosynthesis were significantly different between the developed seeds of the two parents of the RIL population. By comparing the variation information and expression levels of the syntenic genes within qA07.SOC and its syntenic genomic regions, as well as through haplotype analysis via GWAS, BnaA07.STR18, BnaA07.NRT1, and BnaA07g12880D were predicted as candidate genes in the qA07.SOC interval. These stable QTLs containing candidate genes and haplotypes can potentially provide a reliable basis for marker-assisted selection in B. napus breeding for SOC.

Dynamic Quantitative Trait Loci Mapping for Plant Height in Recombinant Inbred Line Population of Upland Cotton

Plant height (PH) is a key plant architecture trait for improving the biological productivity of cotton. Ideal PH of cotton is conducive to lodging resistance and mechanized harvesting. To detect quantitative trait loci (QTL) and candidate genes of PH in cotton, a genetic map was constructed with a recombinant inbred line (RIL) population of upland cotton. PH phenotype data under nine environments and three best linear unbiased predictions (BLUPs) were used for QTL analyses. Based on restriction-site-associated DNA sequence (RAD-seq), the genetic map contained 5,850 single-nucleotide polymorphism (SNP) markers, covering 2,747.12 cM with an average genetic distance of 0.47 cM. Thirty-seven unconditional QTL explaining 1.03–12.50% of phenotypic variance, including four major QTL and seven stable QTL, were identified. Twenty-eight conditional QTL explaining 3.27–28.87% of phenotypic variance, including 1 major QTL, were identified. Importantly, five QTL, including 4 stable QTL, were both unconditional and conditional QTL. Among the 60 PH QTL (including 39 newly identified), none of them were involved in the whole period of PH growth, indicating that QTL related to cotton PH development have dynamic expression characteristics. Based on the functional annotation of Arabidopsis homologous genes and transcriptome data of upland cotton TM-1, 14 candidate genes were predicted within 10 QTL. Our research provides valuable information for understanding the genetic mechanism of PH development, which also increases the economic production of cotton.

Genetic basis of heterosis in a common wheat cross withstrong-heterosis

<p indent="0mm">Heterosis refers to the phenomenon that a heterozygous hybrid exhibits superior performances over its parents, which has been suggested as a solution to overcome yield stagnation of wheat. However, the molecular basis of wheat heterosis is still poorly understood. We have previously found that a cross derived from the winter common wheat Nongda3338 (ND3338) and Jingdong 6 (JD6) showed strong mid-parent heteroses on plant height (PH) and thousand grain weight (TGW). In this study, we further aimed to investigate the genetic underpinnings of PH and TGW using an “immortalized F₂” (IF₂) derived from the ND3338/JD6 doubled haploid (DH) population. The PH and TGW of DH and IF₂ populations were evaluated across two different environments, and the mid-parent heterosis value (HV) was used to measure heterosis. The direction and magnitude of HV greatly varied between PH and TGW across the environments. A two-way analysis of variance (ANOVA) was performed for PH and TGW in the IF₂ population, revealing that genetic variation was the main source, despite the significant variations found from the environments and genotype by environment interaction. The broad sense heritability of PH and TGW in IF₂ population was 94.05% and 88.14%, respectively. Pearson’s correlation coefficients of PH, TGW, HV_PH and HV_TGW in the IF₂ population were estimated based on the best linear unbiased prediction (BLUP) values of two environments, showing that PH was significantly positively correlated with TGW and HV_TGW, TGW was significantly positively correlated with HV_TGW and negatively correlated with HV_PH, while HV_PH had a strong positive correlation with HV_TGW. The genotypes of the IF₂ population were deduced from corresponding DH parents. Based on the inclusive composite interval mapping method, quantitative trait locus (QTL) mapping was separately conducted with PH, TGW, HV_PH and HV_TGW using the QTL IciMapping software. We identified a total of 32 and 25 QTL that exhibited additive, dominant and overdominant pattern associated with PH and TGW, which accounted for 0.54%–36.05% and 0.87%–25.78% of the variance, respectively. Consistent with the results found in the ND3338/JD6 DH population, major and stable QTL on chromosomes 2D (<italic>QPh</italic>.<italic>2D</italic>.<italic>1</italic> and <italic>QTgw</italic>.<italic>2D</italic>), 4B (<italic>QPh</italic>.<italic>4B</italic>.<italic>1</italic> and <italic>QTgw</italic>.<italic>4B</italic>.<italic>1</italic>) and 4D (<italic>QPh</italic>.<italic>4D </italic>and <italic>QTgw</italic>.<italic>4D</italic>) that were coincident with the dwarfing genes <italic>Rht1</italic>, <italic>Rht2</italic> and <italic>Rht8</italic> were detected, suggesting that the IF₂ population design is feasible and reliable for identifying the genetic components of heterosis. Furthermore, 13 QTL for HV_PH and 15 QTL for HV_TGW were identified, of which most of these loci exhibited overdominant pattern. However, only few of the QTL controlling PH and TGW were overlapped with those controlling HV_PH and HV_TGW, suggesting potentially different genetic mechanisms between phenotypic traits and heterosis. In addition, epistasis analysis for PH and TGW revealed that four types of digenic interactions, including additive by additive (AA), additive by dominance (AD), dominance by additive (DA) and dominance by dominance (DD), were involved in the genetic basis of hybrid performance and heterosis in the IF₂ population. Notably, the DD-oriented QTL with the greatest interactive effects possessed the highest frequency. Overall, this study provides strong evidence for supporting the classical genetic hypotheses of heterosis (dominance, overdominance, and epistasis) with an IF₂ population, establishing the foundation to develop and select crosses with strong heterosis.

Natural variation of HTH5 from wild rice, Oryza rufipogon Griff., is involved in conferring high-temperature tolerance at the heading stage.

SummaryGlobal warming is a major abiotic stress factor, which limit rice production. Exploiting the genetic basis of the natural variation in heat resistance at different reproductive stages among diverse exotic Oryza germplasms can help breeding heat‐resistant rice cultivars. Here, we identified a stable quantitative trait locus (QTL) for heat tolerance at the heading stage on chromosome 5 (qHTH5) in O. rufipogon Griff. The corresponding gene, HTH5, pertains to the pyridoxal phosphate‐binding protein PLPBP (formerly called PROSC) family, which is predicted to encode pyridoxal phosphate homeostasis protein (PLPHP) localized to the mitochondrion. Overexpression of HTH5 increased the seed‐setting rate of rice plants under heat stress at the heading stage, whereas suppression of HTH5 resulted in greater susceptibility to heat stress. Further investigation indicated that HTH5 reduces reactive oxygen species accumulation at high temperatures by increasing the heat‐induced pyridoxal 5'‐phosphate (PLP) content. Moreover, we found that two SNPs located in the HTH5 promoter region are involved with its expression level and associated with heat tolerance diversity. These findings suggest that the novel gene HTH5 might have great potential value for heightening rice tolerance to heat stress to the on‐going threat of global warming.

A major and stable QTL for wheat spikelet number per spike validated in different genetic backgrounds

The spikelet number per spike (SNS) contributes greatly to grain yield in wheat. Identifying various genes that control wheat SNS is vital for yield improvement. This study used a recombinant inbred line population genotyped by the Wheat55K single-nucleotide polymorphism array to identify two major and stably expressed quantitative trait loci (QTLs) for SNS. One of them (QSns.sau-2SY-2D.1) was reported previously, while the other (QSns.sau-2SY-7A) was newly detected and further analyzed in this study. QSns.sau-2SY-7A had a high LOD value ranging from 4.46 to 16.00 and explained 10.21–40.78% of the phenotypic variances. QSns.sau-2SY-7A was flanked by the markers AX-110518554 and AX-110094527 in a 4.75-cM interval on chromosome arm 7AL. The contributions and interactions of both major QTLs were further analyzed and discussed. The effect of QSns.sau-2SY-7A was successfully validated by developing a tightly linked kompetitive allele specific PCR marker in an F2:3 population and a panel of 101 high-generation breeding wheat lines. Furthermore, several genes including the previously reported WHEAT ORTHOLOG OF APO1 (WAPO1), an ortholog of the rice gene ABERRANT PANICLE ORGANIZATION 1 (APO1) related to SNS, were predicted in the interval of QSns.sau-2SY-7A. In summary, these results revealed the genetic basis of the multi-spikelet genotype of wheat line 20828 and will facilitate subsequent fine mapping and breeding utilization of the major QTLs.

Genetic Mapping and QTL Analysis of Stigma Color in Melon (Cucumis melo L.).

Melon is an important Cucurbitaceae crop. Field observations had shown that the green stigmas of melon are more attractive to pollinators than yellow stigmas. In this study, F2 and F2:3 populations obtained by crossing MR-1 (green stigma) and M4-7 (yellow stigma) were used for genetic analysis and mapping. A genetic map of 1,802.49 cm was constructed with 116 cleaved amplified polymorphism sequence (CAPS) markers. Two stable quantitative trait loci (QTLs) linked to the trait of stigma color were identified on chromosomes 2 (SC2.1) and 8 (SC8.1), respectively. An expanded F2 population was used to narrow down the confidence regions of SC2.1 and SC8.1. As a result, SC2.1 was further mapped to a 3.6 cm region between CAPS markers S2M3 and S2B1-3, explaining 9.40% phenotypic variation. SC8.1 was mapped to a 3.7-cm region between CAPS markers S8E7 and S8H-1, explaining 25.92% phenotypic variation. This study broadens our understanding of the mechanisms of stigma color regulation and will be of benefit to the breeding of melon.