Further QTL mapping for yield component traits using introgression lines in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) under drought field environments

To better understand the underlying mechanisms of agronomic traits related to drought resistance and discover candidate genes or chromosome segments for drought-tolerant rice breeding, a fundamental introgression population, BC₃, derived from the backcross of local upland rice cv. Haogelao (donor parent) and super yield lowland rice cv. Shennong265 (recurrent parent) had been constructed before 2006. Previous quantitative trait locus (QTL) mapping results using 180 and 94 BC₃F_6,7 rice introgression lines (ILs) with 187 and 130 simple sequence repeat (SSR) markers for agronomy and physiology traits under drought in the field have been reported in 2009 and 2012, respectively. In this report, we conducted further QTL mapping for grain yield component traits under water-stressed (WS) and well-watered (WW) field conditions during 3 years (2012, 2013 and 2014). We used 62 SSR markers, 41 of which were newly screened, and 492 BC₄F_2,4 core lines derived from the fourth backcross between D123, an elite drought-tolerant IL (BC₃F₇), and Shennong265. Under WS conditions, a total of 19 QTLs were detected, all of which were associated with the new SSRs. Each QTL was only identified in 1 year and one site except for qPL-12-1 and qPL-5, which additively increased panicle length under drought stress. qPL-12-1 was detected in 2013 between new marker RM1337 and old marker RM3455 (34.39 cM) and was a major QTL with high reliability and 15.36% phenotypic variance. qPL-5 was a minor QTL detected in 2013 and 2014 between new marker RM5693 and old marker RM3476. Two QTLs for plant height (qPHL-3-1 and qPHP-12) were detected under both WS and WW conditions in 1 year and one site. qPHL-3-1, a major QTL from Shennong265 for decreasing plant height of leaf located on chromosome 3 between two new markers, explained 22.57% of phenotypic variation with high reliability under WS conditions. On the contrary, qPHP-12 was a minor QTL for increasing plant height of panicle from Haogelao on chromosome 12. Except for these two QTLs, all other 17 QTLs mapped under WS conditions were not mapped under WW conditions; thus, they were all related to drought tolerance. Thirteen QTLs mapped from Haogelao under WS conditions showed improved drought tolerance. However, a major QTL for delayed heading date from Shennong265, qDHD-12, enhanced drought tolerance, was located on chromosome 12 between new marker RM1337 and old marker RM3455 (11.11 cM), explained 21.84% of phenotypic variance and showed a negative additive effect (shortening delay days under WS compared with WW). Importantly, chromosome 12 was enriched with seven QTLs, five of which, including major qDHD-12, congregated near new marker RM1337. In addition, four of the seven QTLs improved drought resistance and were located between RM1337 and RM3455, including three minor QTLs from Haogelao for thousand kernel weight, tiller number and panicle length, respectively, and the major QTL qDHD-12 from Shennong265. These results strongly suggested that the newly screened RM1337 marker may be used for marker-assisted selection (MAS) in drought-tolerant rice breeding and that there is a pleiotropic gene or cluster of genes linked to drought tolerance. Another major QTL (qTKW-1-2) for increasing thousand kernel weight from Haogelao was also identified under WW conditions. These results are helpful for MAS in rice breeding and drought-resistant gene cloning.     

Genotyping by sequencing of rice interspecific backcross inbred lines identifies QTLs for grain weight and grain length

Grain weight and grain length are the most stable components of rice yield and important indicators of consumer preference. Considering the potentials of wild rice and to enhance the rice yields to meet the increasing demands, 185 Backcross Inbred Lines (BILs) in the background of O. sativa ssp. indica cv. PR114, including 63 rufi-BILs derived from O. rufipogon IRGC104433 and 122 glumae-BILs from O. glumaepatula IRGC104387 were evaluated for mapping QTLs for yield and yield component traits using Genotyping by Sequencing (GBS). Phenotypic evaluation of BILs in three seasons spanning two locations revealed significant differences compared with recurrent parent. BILs which did not show significant differences for any trait under investigation, or similar based on pedigree, were excluded from GBS. Some glumae-BILs had to be excluded from mapping QTLs due to less sequence information. A custom designed approach for GBS data analysis identified 3322 informative SNPs in 55 rufi-BILs and 3437 informative SNPs in 79 glumae-BILs. QTL mapping identified one QTL for thousand grain weight (qtgw5.1), two for grain width (qgw5.1, qgw5.2) and one for grain length (qgl7.1) in rufi-BILs. In the glumae-BILs, three QTL for thousand grain weight (qtgw2.1, qtgw3.1, qtgw6.1) and two for grain length (qgl3.1, qgl7.1) were identified. Most of the grain weight and width QTL showed positive additive effect contributed by wild species allele, whereas the grain length QTL showed positive additive effect contributed by recurrent parent allele. Based on their physical position, none of the QTLs were found similar to previously cloned QTLs. QTLs for grain traits identified from low yielding wild relatives of rice reveals their significance in improving further the rice yields and widen the genetic base of cultivated rice.     

Variance components and heritability of traits related to root: shoot biomass allocation and drought tolerance in wheat

Enhanced root growth in plants is fundamental to improve soil water exploration and drought tolerance. Understanding of the variance components and heritability of root biomass allocation is key to design suitable breeding strategies and to enhance the response to selection. This study aimed to determine variance components and heritability of biomass allocation and related traits in 99 genotypes of wheat (Triticum aestivum L.) and one triticale (X. Triticosecale Wittmack) under drought-stressed and non-stressed conditions in the field and greenhouse using a 10?×?10 alpha lattice design. Days to heading (DTH), days to maturity (DTM), number of tillers (NPT), plant height (PH), spike length (SL), shoot and root biomass (SB, RB), root to shoot ratio (RS), thousand kernel weight (TKW) and yield (GY) were recorded. Analyses of variance, variance components, heritability and genetic correlations were computed. Significant (p?<?0.05) genetic and environmental variation were observed for all the traits except for spike length. Drought stress decreased heritability of RS from 47 to 28% and GY from 55 to 17%. The correlations between RS with PH, NPT, SL, SB and GY were weaker under drought-stress (r?≤???0.50; p?<?0.05) compared to non-stressed conditions, suggesting that lower root biomass allocation under drought stress compromises wheat productivity. The negative association between GY and RS (r?=???0.41 and ??0.33; p?<?0.05), low heritability (<?42%) and high environmental variance (>?70%) for RS observed in this population constitute several bottlenecks for improving yield and root mass simultaneously. However, indirect selection for DTH, PH, RB, and TKW, could help optimize RS and simultaneously improve drought tolerance and yield under drought-stressed conditions.     

Genetic dissection of rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) tiller,plant height,and grain yield based on QTL mapping and metaanalysis

Tiller number per plant (TN) and plant height (PH) are important agronomic traits related to grain yield (GY) in rice (Oryza sativa L.). A total of 30 additive quantitative trait loci (A-QTL) and 9 significant additive × environment interaction QTLs (AE-QTL) were detected, while the phenotypic and QTL correlations confirmed the intrinsic relationship of the three traits. These QTLs were integrated with 986 QTLs from previous studies by metaanalysis. Consensus maps contained 7156 markers for a total map length of 1112.71 cM, onto which 863 QTLs were projected; 78 meta-QTLs (MQTLs) covering 11 of the 30 QTLs were detected from the cross between Dongnong422 and Kongyu131 in this study. A total of 705 predicted genes were distributed over the 21 MQTL intervals with physical length <0.3 Mb; 13 of the 21 MQTLs, and 34 candidate genes related to grain yield and plant development, were screened. Five major QTLs, viz. qGY6-2, qPH7-2, qPH6-3, qTN6-1, and qTN7-1, were not detected in the MQTL intervals and could be used as newly discovered QTLs. Candidate genes within these QTL intervals will play a meaningful role in molecular marker-assisted selection and map-based cloning of rice TN, PH, and GY.     

Identification and validation of root length QTLs for water stress resistance in hexaploid wheat (<Emphasis Type="Italic">Titicum aestivum</Emphasis> L.)

Thorough understanding of the genetic mechanisms governing drought adaptive traits can facilitate drought resistance improvement. This study was conducted to identify chromosome regions harbouring QTLs contributing for water stress resistance in wheat. A RIL mapping population derived from a cross between W7984 (Synthetic) and Opata 85 was phenotyped for root length and root dry weight under water stress and non-stress growing conditions. ANOVA showed highly significant (p ≤ 0.01) variation among the RILs for both traits. Root length and root dry weight showed positive and significant (p ≤ 0.01) phenotypic correlation. Broad sense heritability was 86% for root length under stress and 65% for root dry weight under non-stress conditions. A total of eight root length and five root dry weight QTLs were identified under both water conditions. Root length QTLs Qrln.uwa.1BL, Qrln.uwa.2DS, Qrln.uwa.5AL and Qrln.uwa.6AL combined explained 43% of phenotypic variation under non-stress condition. Opata was the source of favourable alleles for root length QTLs under non-stress condition except for Qrln.uwa.6AL. Four stress specific root length QTLs, Qrls.uwa.1AS, Qrls.uwa.3AL, Qrls.uwa.7BL.1 and Qrls.uwa.7BL.2 jointly explained 47% of phenotypic variation. Synthetic wheat contributed favourable alleles for Qrls.uwa.1AS and Qrls.uwa.3AL. Two stable root dry weight QTLs on chromosomes 4AL and 5AL were consistently found in both water conditions. Three validation populations were developed by crossing cultivars Lang, Yitpi, and Chara with Synthetic W7984 to transfer two of the QTLs identified under stress condition. The F_2.3 and F_3.4 validation lines were phenotyped under the same level of water stress as RILs to examine the effect of these QTLs. There were 13.5 and 14.5% increases in average root length due to the inheritance of Qrls.uwa.1AS and Qrls.uwa.3AL, respectively. The result indicated that closely linked SSR markers Xbarc148 (Qrls.uwa.1AS) and Xgwm391 (Qrls.uwa.3AL) can be incorporated into MAS for water stress improvement in wheat.     

Evaluation of morpho-physiological traits of MRQ74 pyramided lines with drought yield QTLs

Drought regularly affects rainfed lowland and upland rice ecosystems in Malaysia. Three drought yield QTLs, viz qDTY _2.2 , qDTY _3.1 and qDTY _12.1 successfully pyramided into MRQ74 to increase its yield under reproductive stage drought stress (RS). Forty-eight genotypes comprising 39 pyramided lines (PLs) with different qDTYs combinations, four parents including MRQ74 (recipient) and five checks were evaluated for morpho-physiological traits under RS and non-stress (NS). This study aims to determine which traits influenced by individual qDTY and qDTY combinations and to gain better understanding of QTL interactions in enhancing grain yield (GY) under RS. Results showed plant height, number of panicles, root length, root weight, relative water content and 100-grain weight increased while chlorophyll content and GY decreased under RS compared to NS. No significant difference was observed in days to flowering, leaf rolling and grain length between selected PLs and MRQ74 under RS. Six PLs with yield advantage (YA) of 208.17–1751.63 kg ha^?1 compared to MRQ74 in RS but yielded similar to MRQ74 under NS were further selected. Under RS, qDTY class analysis showed qDTY _12.1 individually and combination qDTY _12.1  + ?qDTY _2.2 produced the highest yield of 1521.77 and 1092.30 kg ha^?1 respectively. qDTY _12.1 as single or combination with other qDTY is the best qDTY in stabilizing GY under RS. PL-77 with qDTY _12.1 is the best PL with YA of more than 1100 kg ha^?1 compared to MRQ74 in both RS and NS conditions can be recommended for cultivation in normal and drought-prone areas.     

Phenotypic variation in root architecture traits and their relationship with eco-geographical and agronomic features in a core collection of tetraploid wheat landraces (<Emphasis Type="Italic">Triticum turgidum</Emphasis> L.)

To obtain varieties with root systems adapted to marginal environments it is necessary to search for new genotypes in genetically diverse materials, such as landraces that are more likely to carry novel alleles for different root features. A core collection of ‘durum’ wheat, including three subspecies (dicoccon, turgidum and durum) from contrasting eco-geographical zones, was evaluated for root traits and shoot weight at the seminal root stage. Distinctive rooting phenotypes were characterized within each subspecies, mainly in subsp. durum. Contrasting rooting types, including large roots with shallow distributions, and others with high root numbers were identified. Correlations with climatic traits showed that root shape is more relevant in adaptation to eco-geographical zones in subsp. dicoccon, whereas in subsp. turgidum and durum, which come from warmer and drier areas, both size and shape of roots could have adaptive roles. Root traits with the largest positive effects on certain yield components under limited water conditions included root diameter in subsp. dicoccon, root size in turgidum, and root number in durum. Additionally, shoot weight at the seedling stage had important effects in subsp. turgidum and durum. Twenty-eight marker–trait associations (MTAs) previously identified in this collection for agronomic or quality traits were associated with seminal root traits. Some markers were associated with only one root trait, but others were associated with up to six traits. These MTAs and the genetic variability characterized for root traits in this collection can be exploited in further work to improve drought tolerance and resource capture in wheat.     

Identification of quantitative trait loci associated with drought tolerance traits in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) under PEG and field drought stress

Two recombinant inbred line F₁₀ rice populations (IAPAR-9/Akihikari and IAPAR-9/Liaoyan241) were used to identify quantitative trait loci (QTLs) for ten drought tolerance traits at the budding and early seedling stage under polyethylene glycol-induced drought stress, and two traits of leaf rolling index (LRI) and leaf withering degree (LWD) under field drought stress. The results showed that the drought-tolerance capacity of IAPAR-9 was stronger than that of Akihikari and Liaoyan241. Thirty-four QTLs for 12 drought tolerance traits were detected, and among them, in the IAPAR-9/Akihikari population, qLRI9-1 and qLRI10-1 for LRI were repeatedly detected in RM3600-RM553 on chromosome 9 and in RM6100-RM3773 on chromosome 10, respectively, at two times points of July 31 and August 13 in 2014. The two QTLs are stable against the environmental impact, and qLRI9-1 and qLRI10-1 explained 6.77–13.66% and 5.01–8.32% of the phenotypic variance, respectively, at the two times points. qLWD9-2 for LWD in the IAPAR-9/Liaoyan241 population contributed 8.73% of variation was detected in the same marker interval with the qLRI9-1, and qLRI1-1 for LRI and qLWD1-1 for LWD were located in the same marker interval RM11054-RM5646 on chromosome 1, which contributed 18.82 and 5.78% of phenotype variation respectively. qGV3 for germination vigor and qRGV3 for relative germination vigor at the budding stage were detected in the same marker interval RM426-RM570 on chromosome 3, which explained 14.98 and 16.30% of the observed phenotypic variation respectively, representing major QTLs. The above-mentioned stable or major QTLs regions could be useful for molecular marker assisted selection breeding, fine mapping, and cloning.     

Identification of QTLs controlling low-temperature germinability and cold tolerance at the seedling stage in rice (<Emphasis Type="Italic">Oryza Sativa</Emphasis> L.)

Both low-temperature germinability (LTG) and cold tolerance at the seedling stage (CTS) are important traits for rice. In this study, a rice population of recombinant inbred lines (RILs), derived from the backcross population of a cross between Dongnong422 and Kongyu131, was developed to detect quantitative trait loci (QTL) affecting LTG and CTS by using seed of different storage times. Correlation analysis indicated that there was no significant relationship between LTG and CTS, suggesting that cold tolerance might be genetic differences for LTG and CTS. In total, Twelve and twenty-three major QTLs were detected for LTG and CTS, respectively, which could explain greater than 10% of the phenotypical variation. Eight (qCG12-1, qGI12-1, qGV9-1, qMLIT12-1, qPV6-1, qMDG12-1, qLDWcold10-1, qLFWcold10-1) significant QTLs were mapped for different storage time, it concluded that such QTLs were not affected by environment (storage time) and were closely related QTLs to cold tolerance. One or more QTLs were identified for each trait with some of these QTLs co-locating, qMLIT7-1, qCG7-1, and qGI7-1 for LTG, qLFWcold10-1, and qLDWcold10-1 for CTS with contributions over 15% were mapped common marker interval, respectively, co-location of QTLs for different traits can be an indication that a locus has pleiotropic effects on multiple traits due to a common mechanistic basis. Two lines, RIL128 and RIL73, might be valuable to improve the LTG and CTS through a combination of crosses. The identified QTLs might be applicable to improve the rice cold tolerance by the marker-assisted selection approach.     

QTL mapping and identification of corresponding genomic regions for black pod disease resistance to three <Emphasis Type="Italic">Phytophthora</Emphasis> species in <Emphasis Type="Italic">Theobroma cacao</Emphasis> L.

The cacao tree (Theobroma cacao L.) is a species of great importance because cacao beans are the raw material used in the production of chocolate. However, the economic success of cacao is largely limited by important diseases such as black pod, which is responsible for losses of up to 30–40% of the global cacao harvest. The discovery of resistance genes could extensively reduce these losses. Therefore, the aims of this study were to construct an integrated multipoint genetic map, align polymorphisms against the available cacao genome, and identify quantitative trait loci (QTLs) associated with resistance to black pod disease in cacao. The genetic map had a total length of 956.41 cM and included 186 simple sequence repeat (SSR) markers distributed among 10 linkage groups. The physical “in silico” map covered more than 200 Mb of the cacao genome. Based on the mixed model predicted means of Phytophthora evaluation, a total of 6 QTLs were detected for Phytophthora palmivora (1 QTL), Phytophthora citrophthora (1 QTL), and Phytophthora capsici (4 QTLs). Approximately 1.77–3.29% of the phenotypic variation could be explained by the mapped QTLs. Several SSR marker-flanking regions containing mapped QTLs were located in proximity to disease regions. The greatest number of resistance genes was detected in linkage group 6, which provides strong evidence for a QTL. This joint analysis involving multipoint and mixed-model approaches may provide a potentially promising technique for detecting genes resistant to black pod and could be very useful for future studies in cacao breeding.     

Quantitative trait locus analysis for days-to-heading and morphological traits in an RIL population derived from an extremely late flowering F<Subscript>1</Subscript> hybrid of sorghum

The hybrid vigor typical of F₁ cultivars is used to boost biomass production of sorghum (Sorghum bicolor (L.) Moench). The high dry-matter yielding F₁ cultivar Kazetachi uniquely shows extremely late flowering and a long culm, and is greatly different from its parents. We investigated the genetic mechanisms underlying these phenotypes by quantitative trait locus (QTL) analysis of recombinant inbred lines derived from a male-fertile line and a restorer line and grown in 3 years. QTL analysis for six traits (days-to-heading, culm length, culm width, culm number, panicle length, panicle number) revealed that the unique phenotypes of the F₁ plants were controlled by the genetic combination of 12 or more QTLs detected in at least 2 years. Two putative QTLs for days-to-heading (qDH1 on SBI-01 and qDH6 on SBI-06) would strongly affect the other phenotypes because of their co-localization with QTLs for other traits, as supported by significant phenotypic correlations. These QTLs would be useful for understanding the association of plant type with biomass production in sorghum.     

QTL mapping and genetic analysis for maize kernel size and weight in multi-environments

Kernel size and weight are important agronomic traits, as well as crucial traits that influence grain yield in maize. In the present study, 150 F₇ recombinant inbred lines derived from a cross 178×K12 were evaluated for kernel length (KL), kernel width (KW), kernel thickness (KT), and 100-kernel weight (HKW) across seven environments. Natural variations in KL, KW, KT, and HKW were observed in the population. A set of quantitative trait loci (QTLs) for the kernel-related traits were identified by inclusive composite interval mapping method. For the four kernel traits from seven environments and the best linear unbiased prediction data, a total of 52 QTLs were detected, which distributed on all chromosomes except chromosome 6. The LOD values ranged from 2.52 to 8.91, the additive effect from ??2.22 to 1.37, and the range of individually explaining phenotypic variation was from 5.8 to 23.49%. Amongst these QTLs, most were detected only in one or two environments. Three stable QTLs, qKL4-1 at bin 4.07/4.08, qKW4-2 at bin 4.06 and qKT2-1 at bin 2.02/2.03, were identified across at least three environments. Besides, several overlapping QTLs associated with multiple traits were identified. For example, qKW3-1 for KW and qHKW3-1 for HKW were located in the same marker interval at Bin 3.01/3.02. These stable QTLs and overlapping QTLs found in this study will contribute to the understanding of genetic components of grain yield and provide the foundation for molecular marker-assisted breeding in maize.     

QTL analysis of morphological traits and pseudostem pigmentation in bunching onion (<Emphasis Type="Italic">Allium fistulosum</Emphasis>)

Pseudostems of bunching onion (Allium fistulosum L.) show wide variation in morphological traits and skin color. However, despite being one of the most important agronomic traits, molecular studies of bunching onion pseudostems remain limited. In this study, six morphological traits (plant height, leaf length, pseudostem length, leaf width, pseudostem width and number of leaf sheaths) along with pseudostem pigmentation indices were evaluated in two field trials using an F_2:3 population derived from a single F₁ cross between a white single pseudostem (non-tillering) and a red tillering bunching onion. Plant height was highly correlated with both leaf length and pseudostem length, but not the number of leaf sheaths. In contrast, the number of leaf sheaths was significantly negatively correlated with both leaf width and pseudostem width. A total of 27 QTLs for the six morphological traits were detected in 16 regions of 11 linkage groups, with a major QTL for the number of leaf sheaths repeatedly detected on Chr. 8. Meanwhile, two QTLs associated with pseudostem pigmentation were repeatedly detected on linkage groups Chr. 4a and Chr. 5a-2. The latter (qPig5a-2) was considered a major QTL, and its location estimated by marker genotyping of the F₂ population around the qPig5a-2 region as being within a 7.6 cM interval.     

QTL for flag leaf size and their influence on yield-related traits in wheat

Flag leaf-related traits (FLRTs) are determinant traits affecting plant architecture and yield potential in wheat (Triticum aestivum L.). In this study, three related recombinant inbred line (RIL) populations with a common female parent were developed to identify quantitative trait loci (QTL) for flag leaf width (FLW), length (FLL), and area (FLA) in four environments. A total of 31 QTL were detected in four environments. Two QTL for FLL on chromosomes 3B and 4A (QFll-3B and QFll-4A) and one for FLW on chromosome 2A (QFlw-2A) were major stable QTL. Ten QTL clusters (C1–C10) simultaneously controlling FLRTs and yield-related traits (YRTs) were identified. To investigate the genetic relationship between FLRTs and YRTs, correlation analysis was conducted. FLRTs were found to be positively correlated with YRTs especially with kernel weight per spike and kernel number per spike in all the three RIL populations and negatively correlated with spike number per plant. Appropriate flag leaf size could benefit the formation of high yield potential. This study laid a genetic foundation for improving yield potential in wheat molecular breeding programs.     

Identification of QTLs associated with heat tolerance at the heading and flowering stage in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

The ongoing rise in temperatures caused by global climate change is a critical climatic risk factor for rice production, and enhancing rice heat tolerance is an area of particular research interest. A recombinant inbred line (RIL) mapping population was developed from heat sensitive, rice cultivar IAPAR-9 crossed with heat tolerant, Liaoyan241. RIL and parental lines were exposed to high temperature at the heating and flowering stage in experiments in 2014 and 2015. As indicators of heat tolerance, the seed setting rate under natural (NS) and heat stress (HTS) conditions were measured, and the reduction rate of seed set (RRS) was calculated. Quantitative trait loci (QTL) analysis revealed eleven heat tolerance QTLs located on chromosomes 1, 3, 4, 5, and 6. Single QTL contribution rates were 4.75–13.81% and effect values were ? 5.98 to 5.00. Four major QTLs (qNS1, qNS4, qNS6, and qRRS1) were stable detected in different environments in both years. Thirteen QTLs with epistatic interactions and nine QTLs with environmental interactions were also detected. Major QTLs were all involved in epistatic and environmental interactions. Three QTLs from the SSR marker interval RM471 to RM177 region of chromosome 4 (qNS4, qHTS4, and qRRS4) were all involved in epistatic and environmental interactions and contributed to phenotypic variation, indicating that this region constituted a major QTL hotspot. The major QTL for heat tolerance identified in this study will aid in breeding tolerant cultivars and facilitating investigation of the molecular underpinnings of heat tolerance in rice.     

Identifying QTL–allele system of seed protein content in Chinese soybean landraces for population differentiation studies and optimal cross predictions

Soybean originated in ancient China has been quickly extended globally as a major protein and oil crop. The QTL–allele constitution of seed protein content (SPC) in the Chinese soybean landrace population (CSLRP) was studied using a representative sample composed of 365 accessions tested under multiple environments and analysed under the novel restricted two-stage multi-locus genome-wide association study (RTM-GWAS) procedure based on 29,121 SNPLDB (single nucleotide polymorphism linkage disequilibrium blocks) markers. The SPC varied from 37.51 to 50.46% among accessions, for which 89 QTLs, each with 2–9 alleles in a total of 255 alleles were identified, accounting for 83.16% of the phenotypic variation covering most of the genetic variation (h²?=?84.31%). The QTL–alleles of the 365 landraces were organized into a 255?×?365 QTL–allele matrix as the compact form of SPC genetic constitution in CSLRP. Of the 89 QTLs, 53 showed significantly differentiated allele frequency distribution patterns among geographic eco-regions (sub-populations). There were 32.09% alleles not common among sub-populations but found only in some sub-populations; new allele(s) emerged on some loci in some respective sub-populations, with Eco-region III showing less but Eco-region VI more emergence. The QTL–allele matrix was also used for prediction of optimal crosses for breeding purpose to reach a 99th percentile potential of up to 54.81%, more than the highest accession (50.46%). From the 89 QTLs, 59 SPC candidate genes involving biological processes, cellular components and molecular functions were annotated. Among them, Glyma18g13574 and Glyma20g21370 were inferred as two of the major SPC genes in the whole genome.     

Mapping of QTL associated with waterlogging tolerance and drought resistance during the seedling stage in oilseed rape (Brassica napus)

Soil waterlogging and drought are major environmental stresses that suppress rapeseed (Brassica napus) growth and yield. To identify quantitative trait loci (QTL) associated with waterlogging tolerance and drought resistance at the rapeseed seedling stage, we generated a doubled haploid (DH) population consisting of 150 DH lines from a cross between two B. napus lines, namely, line No2127-17 × 275B F₄ (waterlogging-tolerant and drought-resistant) and line Huyou15 × 5900 F₄ (waterlogging-sensitive and drought-sensitive). A genetic linkage map was constructed using 183 simple sequence repeat and 157 amplified fragment length polymorphism markers for the DH population. Phenotypic data were collected under waterlogging, drought and control conditions, respectively, in two experiments. Five traits (plant height, root length, shoot dry weight, root dry weight and total dry weight) were investigated. QTL associated with the five traits, waterlogging tolerance coefficient (WTC) and drought resistance coefficient (DRC) of all the traits were identified via composite interval mapping, respectively. A total of 28 QTL were resolved for the five traits under control conditions, 26 QTL for the traits under waterlogging stresses and 31 QTL for the traits under drought conditions. Eleven QTL were detected by the WTC, and 19 QTL related to DRC were identified. The results suggest that the genetic bases of both waterlogging tolerance and drought resistance are complex. Some of the QTL for waterlogging tolerance-related traits overlapped with QTL for drought resistance-related traits, indicating that the genetic bases of waterlogging tolerance and drought resistance in the DH population were related in some degree.     

Stability of <Emphasis Type="Italic">Solanum aethiopicum</Emphasis> Shum accessions under varied water deficit stress levels and identification of pertinent breeding traits for resistance to water shortage

Drought is a major constraint to productivity of Solanum aethiopicum ‘Shum’ group due to loss in market and nutrient value of stressed plants. This study evaluated S. aethiopicum Shum group accessions to identify genotypes (G) that excel across moisture deficit stress levels (WLs). A split-plot arrangement composed of four WLs and twenty accessions of S. aethiopicum as main plot and sub-plot factors, respectively, was implemented in a screenhouse, and repeated for two experiments. In each experiment, there was a highly significant effect of at least two WLs on mean performance among at least two accessions for most of the traits at p < 0.05. Further, very highly significant WL × G interactions were obtained for leaf relative water content (LRWC), leaves per plant (LPP) and plant height (PH), and non-significant for leaf blade length and leaf blade width. The order of priority as breeding traits for stability superiority across WLs was suggested as LRWC > PH > LPP. Consequently, based on LRWC, the most superiorly stable accessions were identified as accession 160 followed by accessions 145, 137, 108P and 184G while the least stable ones were identified as accessions 163G, 141, 163 and 108. The broad sense heritability (H ²) for each of the three recommended traits for drought resistance breeding was above 0.9 thus supportive for a good response to selection. Drought stress negatively affected the performance of S. aethiopicum Shum group but the exhibited variation allowed for selection of superiorly stable genotypes.     

Evaluation of end use quality and root traits in wheat cultivars associated with 1RS.1BL translocation

1RS.1BL translocation in wheat, exploited for its multiple disease resistance (Lr26, Yr9, Sr31 and Pm8), has  maintained significance due to its agronomical advantages. However, this translocation exhibits serious defects in dough quality due to the presence of Sec-1 loci on 1RS arm. In the present investigation micro SDS sedimentation test (MST), high molecular weight glutenin subunits (HMWGS) and bread making analysis of 26 genotypes were studied along with their root phenotyping in the field and under hydroponic culture system. The MST values showed that genotypes having Sec-1 loci had low MST values but in the presence of Glu-D1 (5?+?10) with Glu-B1 (7?+?9) and (7?+?8) they had high MST values, thus overcoming the negative effects of secalin on dough quality. The loaf volume showed positive correlation with MST values of the genotypes. The translocation of 1RS arm led to higher root biomass and longer root length than Pavon 76 without 1RS. Better root traits in recombinant 1RS 44:38 and 1B?+?38 than Pavon 1RS.1BL suggested the role of negative epistatic effects between different QTL regions in 1RS arm. The results suggest that it should be possible to harness the useful alleles associated with good dough quality, better root traits, high yield and stress tolerance with or without secalin.     

Dynamic QTL analysis and validation for plant height using maternal and paternal backcrossing populations in Upland cotton

Plant height determines plant biomass yield, harvest index and economic yield. We analyzed quantitative trait loci (QTL) and gene action controlling plant height. We generated the maternal and paternal testcrossing (TC/M and TC/P) populations based on a recombinant inbred line population. Data for plant height at t1, t2, t3, t4 or t5 stages were collected over 2 years from 3 TC/M field trials and 2 TC/P field trials. At single-locus level, 32 QTLs at five stages and 24 conditional QTLs at four intervals were detected, and 14 QTLs shared in different years or populations or stages. Plant height displayed dynamic characteristics through expression of QTLs. A total of 21 novel QTLs were detected and 11 QTLs validated the previous results. And 19 QTLs explained over 10% of phenotypic variation, such as qPH-Chr9-2, qPH-Chr19-4 and qPH-Chr22-4. The region of NAU5330-NAU1269 on chromosome 19 may be a desired target for genetic improvement of plant height in Upland cotton. In addition, five and eight heterotic loci were identified in TC/M and TC/P populations, respectively. Additive, partial dominance and overdominance effects were observed in both TC populations. We also identified 43 epistatic QTLs and QTLs by environment interactions by inclusive composite interval mapping method. Taken together, additive, partial dominance and overdominance effects together with epistasis explained the genetic basis of plant height in Upland cotton.