Inclusive Composite Interval Mapping Research Articles

Identification of Quantitative Trait Loci Associated with Seed Quality Traits in Two Early-Maturing Soybean Populations

In Canada, soybean (Glycine max (L.) Merr.) is primarily cultivated in three provinces (Ontario, Quebec, and Manitoba). Canadian breeders want to expand the current cultivation range to more northern agro-environments by developing early-maturing elite lines while maintaining good seed quality traits. To examine quantitative trait loci (QTL) involved in 100-seed weight and seed protein, oil, and fatty acid (oleic, linolenic, and linoleic acids) contents, we generated an early-maturing recombinant inbred line population (QS15544RIL) and an F2:F3 (QS15524F2:F3) population adapted to cultivation zones MGs 00 and 000, and phenotyped them for three and one years, respectively. Using two mapping algorithms (Inclusive composite interval mapping and Genome-wide composite interval mapping), we identified a total of 12 major regions that were either associated with QS15544RIL (five loci), QS15524F2:F3 (four loci), or both (three loci) populations. Of the 12 identified regions, three (RIL_GM12, RIL_GM16, and F2_GM04.2) were not previously identified and might respectively serve as novel sources of regulation for oil content, seed weight, and oleic acid. For the RIL_GM05 locus, we identified two novel variants in Glyma.05G244100/MOTHER OF FT AND TFL1, a gene with a confirmed role in the regulation of oleic and linoleic acid contents. Two of the major loci (RIL_GM04 and RIL_GM16) associated with the 100-seed weight trait and one locus (F2_GM04.2) associated with oleic acid were found to be overlapping three loci (E8-r1, GM16:5,680,173-5,730,237, and E8-r2) involved in early-maturity and/or shorter pod-filling that were previously identified by our group, suggesting possible breeding bottlenecks due to linkage drag or pleiotropic effects.

Dissection of the E8 locus in two early maturing Canadian soybean populations.

Soybean [Glycine max (L.) Merr.] is a short-day crop for which breeders want to expand the cultivation range to more northern agro-environments by introgressing alleles involved in early reproductive traits. To do so, we investigated quantitative trait loci (QTL) and expression quantitative trait loci (eQTL) regions comprised within the E8 locus, a large undeciphered region (~7.0 Mbp to 44.5 Mbp) associated with early maturity located on chromosome GM04. We used a combination of two mapping algorithms, (i) inclusive composite interval mapping (ICIM) and (ii) genome-wide composite interval mapping (GCIM), to identify major and minor regions in two soybean populations (QS15524F2:F3 and QS15544RIL) having fixed E1, E2, E3, and E4 alleles. Using this approach, we identified three main QTL regions with high logarithm of the odds (LODs), phenotypic variation explained (PVE), and additive effects for maturity and pod-filling within the E8 region: GM04:16,974,874-17,152,230 (E8-r1); GM04:35,168,111-37,664,017 (E8-r2); and GM04:41,808,599-42,376,237 (E8-r3). Using a five-step variant analysis pipeline, we identified Protein far-red elongated hypocotyl 3 (Glyma.04G124300; E8-r1), E1-like-a (Glyma.04G156400; E8-r2), Light-harvesting chlorophyll-protein complex I subunit A4 (Glyma.04G167900; E8-r3), and Cycling dof factor 3 (Glyma.04G168300; E8-r3) as the most promising candidate genes for these regions. A combinatorial eQTL mapping approach identified significant regulatory interactions for 13 expression traits (e-traits), including Glyma.04G050200 (Early flowering 3/E6 locus), with the E8-r3 region. Four other important QTL regions close to or encompassing major flowering genes were also detected on chromosomes GM07, GM08, and GM16. In GM07:5,256,305-5,404,971, a missense polymorphism was detected in the candidate gene Glyma.07G058200 (Protein suppressor of PHYA-105). These findings demonstrate that the locus known as E8 is regulated by at least three distinct genomic regions, all of which comprise major flowering genes.

Quantitative Trait Loci Mapping for Adult-Plant Stripe Rust Resistance in Chinese Wheat Cultivar Weimai 8

Wheat stripe rust, triggered by Puccinia striiformis f. sp. tritici, is among the most widespread and damaging wheat (Triticum L.) diseases. The development of cultivars harboring adult plant resistance (APR) to stripe rust is a better approach to control the disease. The current study aimed to map APR to stripe rust via the QTL mapping of 165 F2–6 recombinant inbred lines (RILs), derivatives of Weimai 8/Zhengzhou 5389. The collection of phenotypic data for the stripe-rust resistance of both parents and all 165 RILs were conducted at Baoding, Hebei Province, during the 2016–2017 cropping seasons, and at Mianyang, Sichuan Province, during the 2017–2018 and 2018–2019 sowing seasons. The RIL populations and parents were also genotyped with 860 pairs of simple-sequence-repeat (SSR) primers to map APR QTLs to stripe-rust resistant. Moreover, a 55K SNP chip was used for small group bulk segregant analysis conducted to locate the genetic map location and concentration of the SNP markers on the wheat genome. Inclusive composite interval mapping (IciMapping 3.2) software identified four QTLs of stripe-rust resistance on chromosomes 1B, 2AS, 2BS, and 7DS, named QYr.wmy-1B, QYr.wmy-2AS, QYr.wmy-2BS, and QYr.wmy-7DS, which significantly explained 11.56–16.64%, 9.35–12.70%, 7.27–9.95%, and 11.49–15.07% of the phenotypic variation, respectively. All these QTLs were found from the resistant parent, Weimai 8. Meanwhile, the QTLs located on chromosomes 1B and 2AS were found close to Yr18 and Yr9, respectively. Furthermore, the results indicated that QYr.wmy-1B is possibly Yr9 and QYr.wmy-2AS is similar to Yr18 or might be a new QTL, whilst QYr.wmy-2BS and QYr.wmy-7DS were found to be different from previously reported stripe-rust-resistance QTLs and are possibly new QTLs. Overall, the QTLs and their closely associated molecular markers detected in this study could be a great source of input for marker-assisted selection to adult plant stripe-rust resistance in wheat-breeding programs.

Heat Stress-Tolerant Quantitative Trait Loci Identified Using Backcrossed Recombinant Inbred Lines Derived from Intra-Specifically Diverse Aegilops tauschii Accessions

In the face of climate change, bringing more useful alleles and genes from wild relatives of wheat is crucial to develop climate-resilient varieties. We used two populations of backcrossed recombinant inbred lines (BIL1 and BIL2), developed by crossing and backcrossing two intra-specifically diverse Aegilops tauschii accessions from lineage 1 and lineage 2, respectively, with the common wheat cultivar ‘Norin 61′. This study aimed to identify quantitative trait loci (QTLs) associated with heat stress (HS) tolerance. The two BILs were evaluated under heat stress environments in Sudan for phenology, plant height (PH), grain yield (GY), biomass (BIO), harvest index (HI), and thousand-kernel weight (TKW). Grain yield was significantly correlated with BIO and TKW under HS; therefore, the stress tolerance index (STI) was calculated for these traits as well as for GY. A total of 16 heat-tolerant lines were identified based on GY and STI-GY. The QTL analysis performed using inclusive composite interval mapping identified a total of 40 QTLs in BIL1 and 153 QTLs in BIL2 across all environments. We detected 39 QTLs associated with GY-STI, BIO-STI, and TKW-STI in both populations (14 in BIL1 and 25 in BIL2). The QTLs associated with STI were detected on chromosomes 1A, 3A, 5A, 2B, 4B, and all the D-subgenomes. We found that QTLs were detected only under HS for GY on chromosome 5A, TKW on 3B and 5B, PH on 3B and 4B, and grain filling duration on 2B. The higher number of QTLs identified in BIL2 for heat stress tolerance suggests the importance of assessing the effects of intraspecific variation of Ae. tauschii in wheat breeding as it could modulate the heat stress responses/adaptation. Our study provides useful genetic resources for uncovering heat-tolerant QTLs for wheat improvement for heat stress environments.

Identification of stable QTLs and candidate genes associated with plant height and spike length in common wheat

Context Plant height and spike length are important traits with significant impact on the potential yield of wheat. It is essential to dissect their genetic control in order to improve yield potential through breeding. Aims We aimed to identify genomic regions with stable and major-effect quantitative trail loci (QTLs) associated with plant height and spike length in common wheat (Triticum aestivum L.). Methods Three recombinant inbred line (RIL) mapping populations were created by crossing a common parental line, Roshan, with three different cultivars: Sabalan, Falat, and Superhead. The RILs were grown over 3 years at five locations under water-stressed and well-watered conditions. Plant height and spike length were measured during each experiment, and inclusive composite interval mapping was used to analyse the data in both single-and multi-environment analyses. Key results Single-environment analysis detected 32 additive QTLs in the three populations. Three novel, stable and non-epistatic QTLs were identified: qPH1D for plant height in the Sabalan background; and qSL1D and qSL1B.3 for spike length in the Falat and Superhead backgrounds, respectively. Between the flanking markers on chromosomes 1B, 1D and 4B, 191 genes were predicted, 20 of which were identified as potential candidates with roles in wheat plant height and spike-related traits. Conclusions The study identified stable QTLs for plant height and spike length in wheat, providing valuable markers for future breeding programs and enhancing yield potential. Implications These results lay a good foundation for fine mapping of QTLs/genes for molecular marker-assisted breeding in wheat in the future.

Inheritance of factors and validation of loci linked to the kernel row number in tropical field corn (Zea mays L.)

Sustainable feeding of a growing population with nutritional security in the era of climate change is the leading challenge facing adeveloping nation. Field corn is one of those crops that can help achieve this goal due to its high productivity and wide adaptation. There is scope for further improving field corn productivity by targeting component traits such as kernel row number (KRN). In the present investigation, the kernel row number displayed significant variation as well asa positive correlation with yield and yield component traits under the study. The inheritance of the KRN trait was analyzed using the Wright-Castle estimator and chi-square test in two sets of F2 populations (AH4499 and AH4500) and parental lines (AI 505, AI 541 and AI 542). The analyses by the Wright-Castle estimator revealed that KRN is governed by two effective factors (1.92@ 2) with four contributing alleles in the AH-4499 population and four effective factors (3.93 @ 4) with eight contributing alleles in the AH-4500 population. Further analysis by East’s hypothesis (frequency of recessivehomozygote in F2=1/4n) produced similar results and the Chi-square test (0.01 level of significance) confirmed the non-significant difference between expected and observed recessive frequency in F2sof both the populations. This suggested that KRN is governed at least four genes with eight contributing alleles. In both the F2 populations, F1 value was non-significantly close to the mid-parent value suggesting the additive nature of KRN. Further, Bulked Segregant Analysis was carried out using AH-4500-F2 population having 231 individuals to validate linked loci. Out of 58 flanking SSR markers previously reported for the KRN trait, only nine markers were polymorphic for this population. These linked markers identified two putative QTLs for KRN i.e., qKRN2.1 and qKRN2.2 on chromosome 2 through inclusive composite interval mapping. The genetic distance with closely associated markers, bnlg 1017 was 9 cM for qKRN2.1 with a LOD score of 10.24 and a Proportion of Variance Explained (PVE%) of 16.86. The marker-trait association was further validated using F2:3 population and it was found that the marker bnlg 1017 showed a significant association with the KRN trait. Thus, the marker bnlg 1017 could be used to identify high KRN genotypes for use in breeding programs to enhance the productivity of tropical field corn.

A High-Resolution Linkage Map Construction and QTL Analysis for Morphological Traits in Anthurium (Anthurium andraeanum Linden).

Anthurium andraeanum Linden is a prominent ornamental plant belonging to the family Araceae and is cultivated worldwide. The morphology characteristics are crucial because they significantly impact ornamental values, commercial properties, and the efficiency of space utilization in production. However, only a few related investigations have been conducted in anthurium to date. In this study, an F1 genetic segregation population containing 160 progenies was generated through hybridization between potted and cut anthurium varieties. Fifteen morphological traits were assessed and revealed substantial levels of genetic variation and widespread positive correlation. Based on specific length amplified fragment (SLAF) sequencing technology, 8171 single nucleotide polymorphism (SNP) markers were developed, and the high-density linkage map of 2202.27 cM in length distributed on 15 linkage groups was constructed successfully, with an average distance of 0.30 cM. Using the inclusive composite interval mapping (ICIM) method, 59 QTLs related to 15 key morphological traits were successfully identified, which explained phenotypic variance (PVE) ranging from 6.21% to 17.74%. Thirty-three of those associated with 13 traits were designated as major QTLs with PVE > 10%. These findings offer valuable insights into the genetic basis of quantitative traits and are beneficial for molecular marker-assisted selection (MAS) in anthurium breeding.

Inheritance and molecular mapping of the genomic regions governing seedviability in soybean (Glycine max. L. Merr.)

Loos of seed viability in soybean (Glycine max L. Merrill, 2n=40) during ambient storage from harvest to the next planting season is a significant barrier for the production of high-quality seeds. The present study includes the inheritance and molecular mapping of the loci linked to seed viability in soybean. For this, five high viable genotypes (>90% germination after one year of storage) viz. EC-1023, EC-105790, G2651, UPSL34, UPSL736 and three poorly viable genotype (<70% germination after one year of storage) viz. MACS-565, PK1243, VLS61 were hybridized in all possible combination. Obtained F1 were advanced separately. Cross EC1023 x VLS61 and their derived F2:3 seeds, were exposed to 72 hours of accelerated ageing (AA) at 41°C and 100% RH, followed by a germination. After AA test, germination % of EC1023 and VL5-61 were 40 and 14, respectively, whereas range of F2:3 seeds were 4.16 to 71.42 %. The seed viability is governed by polygenes or quantitative trait loci (QTL), as evidenced by the continuous distribution of germination % of F2:3 seeds. Parental polymorphism was studied with 506 SSR markers indicated it to 20.35% whereas distribution of the polymorphism was not uniform across the chromosomes; Chr. 15 had 46.15% polymorphism as against 15.78% on Chr. 3 and 4. Through inclusive composite interval mapping 8 QTL for seed viability on Chr. 6, 7, 8, 10, 13 and 17, respectively, were mapped. Two of the eight QTLs appear to be major QTLs, as their PVE percent is greater than 10% and other seems as minor ones. Previously reported markers linked to seed viability were also validated in the parental genotypes, with only Satt538 being able to differentiate the five good and three poor storing genotypes. The genetics of seed viability, as well as the QTLs and markers found in this study, will pave the way for molecular breeding to generate genotypes with improved seed viability.

Mapping of QTLs and meta-QTLs for Heterodera avenae Woll. resistance in common wheat (Triticum aestivum L.)

BackgroundIn hexaploid wheat, quantitative trait loci (QTL) and meta-QTL (MQTL) analyses were conducted to identify genomic regions controlling resistance to cereal cyst nematode (CCN), Heterodera avenae. A mapping population comprising 149 RILs derived from the cross HUW 468 × C 306 was used for composite interval mapping (CIM) and inclusive composite interval mapping (ICIM).ResultsEight main effect QTLs on three chromosomes (1B, 2A and 3A) were identified using two repeat experiments. One of these QTLs was co-localized with a previously reported wheat gene Cre5 for resistance to CCN. Seven important digenic epistatic interactions (PVE = 5% or more) were also identified, each involving one main effect QTL and another novel E-QTL. Using QTLs earlier reported in literature, two meta-QTLs were also identified, which were also used for identification of 57 candidate genes (CGs). Out of these, 29 CGs have high expression in roots and encoded the following proteins having a role in resistance to plant parasitic nematodes (PPNs): (i) NB-ARC,P-loop containing NTP hydrolase, (ii) Protein Kinase, (iii) serine-threonine/tyrosine-PK, (iv) protein with leucine-rich repeat, (v) virus X resistance protein-like, (vi) zinc finger protein, (vii) RING/FYVE/PHD-type, (viii) glycosyl transferase, family 8 (GT8), (ix) rubisco protein with small subunit domain, (x) protein with SANT/Myb domain and (xi) a protein with a homeobox.ConclusionIdentification and selection of resistance loci with additive and epistatic effect along with two MQTL and associated CGs, identified in the present study may prove useful for understanding the molecular basis of resistance against H. avenae in wheat and for marker-assisted selection (MAS) for breeding CCN resistant wheat cultivars.

Novel quantitative trait loci from an interspecific Brassica rapa derivative improve pod shatter resistance in Brassica napus.

Pod shatter is a trait of agricultural relevance that ensures plants dehisce seeds in their native environment and has been subjected to domestication and selection for non-shattering types in several broadacre crops. However, pod shattering causes a significant yield reduction in canola (Brassica napus L.) crops. An interspecific breeding line BC95042 derived from a B. rapa/B. napus cross showed improved pod shatter resistance (up to 12-fold than a shatter-prone B. napus variety). To uncover the genetic basis and improve pod shatter resistance in new varieties, we analysed F2 and F2:3 derived populations from the cross between BC95042 and an advanced breeding line, BC95041, and genotyped with 15,498 DArTseq markers. Through genome scan, interval and inclusive composite interval mapping analyses, we identified seven quantitative trait loci (QTLs) associated with pod rupture energy, a measure for pod shatter resistance or pod strength, and they locate on A02, A03, A05, A09 and C01 chromosomes. Both parental lines contributed alleles for pod shatter resistance. We identified five pairs of significant epistatic QTLs for additive x additive, additive dominance and dominance x dominance interactions between A01/C01, A03/A07, A07/C03, A03/C03, and C01/C02 chromosomes for rupture energy. QTL effects on A03/A07 and A01/C01 were in the repulsion phase. Comparative mapping identified several candidate genes (AG, ABI3, ARF3, BP1, CEL6, FIL, FUL, GA2OX2, IND, LATE, LEUNIG, MAGL15, RPL, QRT2, RGA, SPT and TCP10) underlying main QTL and epistatic QTL interactions for pod shatter resistance. Three QTLs detected on A02, A03, and A09 were near the FUL (FRUITFULL) homologues BnaA03g39820D and BnaA09g05500D. Focusing on the FUL, we investigated putative motifs, sequence variants and the evolutionary rate of its homologues in 373 resequenced B. napus accessions of interest. BnaA09g05500D is subjected to purifying selection as it had a low Ka/Ks ratio compared to other FUL homologues in B. napus. This study provides a valuable resource for genetic improvement for yield through an understanding of the genetic mechanism controlling pod shatter resistance in Brassica species.

Identification of QTL for kernel weight and size and analysis of the pentatricopeptide repeat (PPR) gene family in cultivated peanut (Arachis hypogaea L.)

Peanut (Arachis hypogaea L.) is an important oilseed crop worldwide. Improving its yield is crucial for sustainable peanut production to meet increasing food and industrial requirements. Deciphering the genetic control underlying peanut kernel weight and size, which are essential components of peanut yield, would facilitate high-yield breeding. A high-density single nucleotide polymorphism (SNP)-based linkage map was constructed using a recombinant inbred lines (RIL) population derived from a cross between the variety Yuanza9102 and a germplasm accession wt09-0023. Kernel weight and size quantitative trait loci (QTLs) were co-localized to a 0.16 Mb interval on Arahy07 using inclusive composite interval mapping (ICIM). Analysis of SNP, and Insertion or Deletion (INDEL) markers in the QTL interval revealed a gene encoding a pentatricopeptide repeat (PPR) superfamily protein as a candidate closely linked with kernel weight and size in cultivated peanut. Examination of the PPR gene family indicated a high degree of collinearity of PPR genes between A. hypogaea and its diploid progenitors, Arachis duranensis and Arachis ipaensis. The candidate PPR gene, Arahy.JX1V6X, displayed a constitutive expression pattern in developing seeds. These findings lay a foundation for further fine mapping of QTLs related to kernel weight and size, as well as validation of candidate genes in cultivated peanut.

Identification of genetic loci for powdery mildew resistance in bread wheat

AbstractPowdery mildew is a very destructive disease that threatens yield and quality of wheat. In the present study, 262 recombinant inbred lines derived from a cross between Zhongmai 578 (ZM578) with moderate resistance to powdery mildew and Jimai 22 (JM22) with high resistance to powdery mildew in the field were used to map powdery mildew resistance loci using the high‐density Illumina iSelect 50K single‐nucleotide polymorphism array. Three quantitative trait loci (QTLs) on chromosomes 2B, 5B, and 5D were identified by inclusive composite interval mapping, designated as QPm.caas‐2BL.1, QPm.caas‐5BL, and QPm.caas‐5DL, respectively, explaining 5.0%–37.0% of the phenotypic variances. The resistance allele of QPm.caas‐5BL was contributed by ZM578, whereas alleles of QPm.caas‐2BL.1 and QPm.caas‐5DL were from JM22. QPm.caas‐2BL.1, detected in all the six experimental environments, was a major and stable QTL. QPm.caas‐5DL was detected in five of the six environments and is likely to be a new QTL for powdery mildew resistance. The kompetitive allele‐specific PCR (KASP) markers Kpm‐2BL and Kpm‐5DL for QPm.caas‐2BL.1 and QPm.caas‐5DL, respectively, were validated in a diverse panel of 287 cultivars. These KASP markers, tightly linked with the QTLs, can be used for marker‐assisted breeding targeting the improvement of powdery mildew resistance in wheat.

Slow stripe rusting in Chinese wheat Jimai 44 conferred by Yr29 in combination with a major QTL on chromosome arm 6AL.

YrJ44, a more effective slow rusting gene than Yr29, was localized to a 3.5-cM interval between AQP markers AX-109373479 and AX-109563479 on chromosome 6AL. "Slow rusting" (SR) is a type of adult plant resistance (APR) that can provide non-specific durable resistance to stripe rust in wheat. Chinese elite wheat cultivar Jimai 44 (JM44) has maintained SR to stripe rust in China since its release despite exposure to a changing and variable pathogen population. An F2:6 population comprising 295 recombinant inbred lines (RILs) derived from a cross between JM44 and susceptible cultivar Jimai 229 (JM229) was used in genetic analysis of the SR. The RILs and parental lines were evaluated for stripe rust response in five field environments and genotyped using the Affymetrix Wheat55K SNP array and 13 allele-specific quantitative PCR-based (AQP) markers. Two stable QTL on chromosome arms 1BL and 6AL were identified by inclusive composite interval mapping. The 1BL QTL was probably the pleiotropic gene Lr46/Yr29/Sr58. QYr.nwafu-6AL (hereafter named YrJ44), mapped in a 3.5-cM interval between AQP markers AX-109373479 and AX-109563479, was more effective than Yr29 in reducing disease severity and relative area under the disease progress curve (rAUDPC). RILs harboring both YrJ44 and Yr29 displayed levels of SR equal to the resistant parent JM44. The AQP markers linked with YrJ44 were polymorphic and significantly correlated with stripe rust resistance in a panel of 1,019 wheat cultivars and breeding lines. These results suggested that adequate SR resistance can be obtained by combining YrJ44 and Yr29 and the AQP markers can be used in breeding for durable stripe rust resistance.

Consensus linkage map construction and QTL mapping for eight yield-related traits in wheat using BAAFS 90K SNP array

Identification of stable quantitative trait loci (QTL) for yield-related traits across populations and environments is crucial for wheat breeding and genetic studies. Consensus maps also play important roles in wheat genetic and genomic researches. In the present study, a wheat consensus map was constructed using a doubled haploid (DH) population derived from Jinghua 1×Xiaobaidongmai (JX) and an F2 population derived from L43×Shanxibaimai (LS) using BAAFS AFFY wheat 90K single nucleotide polymorphism (SNP) array. A total of 44503 SNP markers were mapped on the constructed consensus map, covering 5437.92 cM across 21 chromosomes. The consensus map showed high collinearity with the individual maps and the wheat reference genome IWGSC RefSeq v2.1. Phenotypic data on eight yield-related traits were collected in the JX population and F2:3 and F2:4 populations of LS in six, two and two environments, respectively, and used for QTL analysis. Inclusive composite interval mapping (ICIM) identified 32 environmentally stable QTL for eight yield-related traits. Among them, four QTL, i.e., QPH.baafs-4B, QKNS.baafs-4B, QTGW.baafs-4B and QSL.baafs-5A.3, were detected across mapping populations and environments, and seven stable QTL i.e., QPH.baafs-2B, QKNS.baafs-3D, QSL.baafs-3D, QKW.baafs-4B, QPH.baafs-5D, QPH.baafs-6A.1 and QSL.baafs-6A, are likely to be new. The physical region of 17.25-44.91 Mb on chromosome 4B was associated with six yield-related traits, which is an important region for wheat yield. The physical region around the dwarfing gene Rht24 contained QTL for KL, KW, SL and TGW, which are either from a pleiotropic effect of Rht24 or closely linked loci. Two hundred and fifty-four promising candidate genes were identified for the stable QTL. Among them, TraesCS5A03G1264300, TraesCS1B03G0624000 and TraesCS6A03G0697000 were particularly noteworthy due to their homologous genes have similar functions for the corresponding traits. The constructed consensus map and the identified QTL along with their candidate genes will facilitate the genetic dissection of wheat yield-related traits and accelerate the development of wheat cultivars with desirable plant morphology and high yield.

KASP mapping of QTLs for yield components using a RIL population in Basmati rice (Oryza sativa L.)

Super Basmati is an elite variety with extra-long grains and superior quality but its yield is severely affected by water stress. Recombinant inbred lines (RILs) developed from the cross of Super Basmati and IR55419-04 (a coarse grained variety with high yield potential) were used to identify and map yield-related quantitative trait loci (QTLs) under normal field conditions. Genotypes for 244 KASP markers were obtained from 188 F9 RILs and a linkage map constructed of 1369.4 cM, with average marker interval of 10.5 cM. Eleven agronomic traits were phenotyped in RILs and parents. Composite interval mapping and inclusive composite interval mapping model identified 21 common QTLs related to nine agronomic traits; of the QTLs identified, twelve mapped at novel positions. LOD scores ranged from 2.51 for number of filled grains (qFG1.1) to 16.8 for plant height (qPH1.1). Four major effect QTLs could explain 20% of variation related for plant height, hundred-grain weight and grain width. Alleles from IR55419-04 improved grain filling, grain weight and grain width, while alleles from Super Basmati contributed to longer grains, panicles and flag leaves. Putative candidate genes were identified for 18 yield-related QTLs. These results validate the use of KASP genotyping for QTL mapping of yield-related traits in a bi-parental segregating population. SNPs in the QTLs identified in this study can be used in marker assisted selection for yield components to improve Basmati rice.

Mapping of QTLs associated with yield and related traits under reproductive stage drought stress in rice using SNP linkage map.

Drought stress is a major constraint for rice production worldwide. Reproductive stage drought stress (RSDS) leads to heavy yield losses in rice. The prospecting of new donor cultivars for identification and introgression of QTLs of major effect (Quantitative trait locus) for drought tolerance is crucial for the development of drought-resilient rice varieties. Our study aimed to map QTLs associated with yield and its related traits under RSDS conditions. A saturated linkage map was constructed using 3417 GBS (Genotyping by sequencing) derived SNP (Single nucleotide polymorphism) markers spanning 1924.136cM map length with an average marker density of 0.56cM, in the F3 mapping population raised via cross made between the traditional ahu rice cultivar, Koniahu (drought tolerant) and a high-yielding variety, Disang (drought susceptible). Using the Inclusive composite interval mapping approach, 35 genomic regions governing yield and related traits were identified in pooled data from 198 F3 and F4 segregating lines evaluated for two consecutive seasons under both RSDS and irrigated control conditions. Of the 35 QTLs, 23 QTLs were identified under RSDS with LOD (Logarithm of odds) values ranging between 2.50 and 7.83 and PVE (phenotypic variance explained) values of 2.95-12.42%. Two major QTLs were found to be linked to plant height (qPH1.29) and number of filled grains per panicle (qNOG5.12) under RSDS. Five putative QTLs for grain yield namely, qGY2.00, qGY5.05, qGY6.16, qGY9.19, and qGY10.20 were identified within drought conditions. Fourteen QTL regions having ≤ 10Mb QTL interval size were further analysed for candidate gene identification and a total of 4146 genes were detected out of these 2263 (54.63%) genes were annotated to at least one gene ontology (GO) term. Several QTLs associated with grain yield and yield components and putative candidate genes were identified. The putative QTLs and candidate genes identified could be employed to augment drought resilience in rice after further validation through MAS strategies.

Identification of candidate genes for soybean seed coat-related traits using QTL mapping and GWAS.

Seed coat color is a typical morphological trait that can be used to reveal the evolution of soybean. The study of seed coat color-related traits in soybeans is of great significance for both evolutionary theory and breeding practices. In this study, 180 F10 recombinant inbred lines (RILs) derived from the cross between the yellow-seed coat cultivar Jidou12 (ZDD23040, JD12) and the wild black-seed coat accession Y9 (ZYD02739) were used as materials. Three methods, single-marker analysis (SMA), interval mapping (IM), and inclusive composite interval mapping (ICIM), were used to identify quantitative trait loci (QTLs) controlling seed coat color and seed hilum color. Simultaneously, two genome-wide association study (GWAS) models, the generalized linear model (GLM) and mixed linear model (MLM), were used to jointly identify seed coat color and seed hilum color QTLs in 250 natural populations. By integrating the results from QTL mapping and GWAS analysis, we identified two stable QTLs (qSCC02 and qSCC08) associated with seed coat color and one stable QTL (qSHC08) related to seed hilum color. By combining the results of linkage analysis and association analysis, two stable QTLs (qSCC02, qSCC08) for seed coat color and one stable QTL (qSHC08) for seed hilum color were identified. Upon further investigation using Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, we validated the previous findings that two candidate genes (CHS3C and CHS4A) reside within the qSCC08 region and identified a new QTL, qSCC02. There were a total of 28 candidate genes in the interval, among which Glyma.02G024600, Glyma.02G024700, and Glyma.02G024800 were mapped to the glutathione metabolic pathway, which is related to the transport or accumulation of anthocyanin. We considered the three genes as potential candidate genes for soybean seed coat-related traits. The QTLs and candidate genes detected in this study provide a foundation for further understanding the genetic mechanisms underlying soybean seed coat color and seed hilum color and are of significant value in marker-assisted breeding.

Combined QTL mapping on bi-parental immortalized heterozygous populations to detect the genetic architecture on heterosis.

From bi-parental pure-inbred lines (PIL), immortalized backcross (i.e., IB1 and IB2, representing the two directions of backcrossing) and F2 (i.e., IF2) populations can be developed. These populations are suitable for genetic studies on heterosis, due to the present of both homozygous and heterozygous genotypes, and in the meantime allow repeated phenotyping trials across multiple locations and years. In this study, we developed a combined approach of quantitative trait locus (QTL) mapping, when some or all of the four immortalized populations (i.e., PIL, IB1, IB2, and IF2) are available. To estimate the additive and dominant effects simultaneously and accurately, suitable transformations are made on phenotypic values from different populations. When IB1 and IB2 are present, summation and subtraction are used. When IF2 and PIL are available, mid-parental values and mid-parental heterosis are used. One-dimensional genomic scanning is performed to detect the additive and dominant QTLs, based on the algorithm of inclusive composite interval mapping (ICIM). The proposed approach was applied to one IF2 population together with PIL in maize, and identified ten QTLs on ear length, showing varied degrees of dominance. Simulation studies indicated the proposed approach is similar to or better than individual population mapping by QTL detection power, false discovery rate (FDR), and estimated QTL position and effects.

Molecular dissection of connected rice populations revealed important genomic regions for agronomic and biofortification traits.

Breeding staple crops with increased micronutrient concentration is a sustainable approach to address micronutrient malnutrition. We carried out Multi-Cross QTL analysis and Inclusive Composite Interval Mapping for 11 agronomic, yield and biofortification traits using four connected RILs populations of rice. Overall, MC-156 QTLs were detected for agronomic (115) and biofortification (41) traits, which were higher in number but smaller in effects compared to single population analysis. The MC-QTL analysis was able to detect important QTLs viz: qZn5.2, qFe7.1, qGY10.1, qDF7.1, qPH1.1, qNT4.1, qPT4.1, qPL1.2, qTGW5.1, qGL3.1 , and qGW6.1 , which can be used in rice genomics assisted breeding. A major QTL (qZn5.2 ) for grain Zn concentration has been detected on chromosome 5 that accounted for 13% of R2. In all, 26 QTL clusters were identified on different chromosomes. qPH6.1 epistatically interacted with qZn5.1 and qGY6.2 . Most of QTLs were co-located with functionally related candidate genes indicating the accuracy of QTL mapping. The genomic region of qZn5.2 was co-located with putative genes such as OsZIP5, OsZIP9, and LOC_OS05G40490 that are involved in Zn uptake. These genes included polymorphic functional SNPs, and their promoter regions were enriched with cis-regulatory elements involved in plant growth and development, and biotic and abiotic stress tolerance. Major effect QTL identified for biofortification and agronomic traits can be utilized in breeding for Zn biofortified rice varieties.

QTL Analysis of Yield and End-Use Quality Traits in Texas Hard Red Winter Wheat

Genetic dissection of complex traits by quantitative trait locus (QTL) analysis permits the understanding of the genotypic effects of QTL, interactions between QTLs, and QTL-by-environment interactions in wheat. This study aimed to identify the QTL linked to yield, its components, end-use quality traits including kernel, flour, and dough rheology, and related agronomic traits under dryland and irrigated conditions. A mapping population of 179 F2:6 recombinant inbred lines (RILs) derived from ‘TAM 111’/‘TX05A001822’ was evaluated for these traits to investigate their genetic stability and phenotypic plasticity using 2658 single nucleotide polymorphisms (SNPs) with 35 linkage groups. Traits associated with chromosome regions were detected for individual and across-environment QTL by inclusive composite interval mapping. A total of 30 QTL regions were identified, including 14 consistent QTLs mapped on 11 chromosomes and six pleiotropic QTLs mapped on 5 chromosomes. Three consistent QTLs in chromosomes 1A, 3B, and 6D might be novel. Three major QTLs with both consistent and pleiotropic effects were co-localized with known genes. The first QTL for dough mixing properties was physically clustered around Glu-D1 and had an phenotypic variation explained (PVE) up to 31.3%. The second QTL for kernel-related traits was physically close to the TaCWI-4A (cell wall invertase) gene, which influences the thousand kernel weight, heading date, and harvest index, with a PVE of up to 12.3%. The third QTL, which was colocalized with the TaCWI-5D gene for kernel traits, was identified with a PVE of 6.7%. Epistasis was also detected, but major QTLs were not involved in significant epistasis or interactions with environmental effects. The current study provided new information that is useful for enhanced wheat breeding, which will benefit from the deployment of the favorable alleles for end-use quality, yield, and other agronomic traits in wheat-breeding programs through marker-assisted selection.