Identification of Quantitative Trait Loci Controlling Root Morphological Traits in an Interspecific Soybean Population Using 2D Imagery Data.

Roots are the hidden and most important part of plants. They serve as stabilizers and channels for uptaking water and nutrients and play a crucial role in the growth and development of plants. Here, two-dimensional image data were used to identify quantitative trait loci (QTL) controlling root traits in an interspecific mapping population derived from a cross between wild soybean 'PI366121' and cultivar 'Williams 82'. A total of 2830 single-nucleotide polymorphisms were used for genotyping, constructing genetic linkage maps, and analyzing QTLs. Forty-two QTLs were identified on twelve chromosomes, twelve of which were identified as major QTLs, with a phenotypic variation range of 36.12% to 39.11% and a logarithm of odds value range of 12.01 to 17.35. Two significant QTL regions for the average diameter, root volume, and link average diameter root traits were detected on chromosomes 3 and 13, and both wild and cultivated soybeans contributed positive alleles. Six candidate genes, Glyma.03G027500 (transketolase/glycoaldehyde transferase), Glyma.03G014500 (dehydrogenases), Glyma.13G341500 (leucine-rich repeat receptor-like protein kinase), Glyma.13G341400 (AGC kinase family protein), Glyma.13G331900 (60S ribosomal protein), and Glyma.13G333100 (aquaporin transporter) showed higher expression in root tissues based on publicly available transcriptome data. These results will help breeders improve soybean genetic components and enhance soybean root morphological traits using desirable alleles from wild soybeans.

Identification and map-based cloning of an EMS-induced mutation in wheat gene TaSP1 related to spike architecture.

KEY MESSAGE: A candidate gene TaSP1 related to spike shape was cloned, and the gene-specific marker was developed to efficiently track the superior haplotype in common wheat. Spike shape, an important factor that affects wheat grain yield, is mainly defined by spike length (SPL), spikelet number (SPN), and compactness. Zhoumai32 mutant 1160 (ZM1160), a mutant obtained from ethyl methane sulfonate (EMS) treatment of hexaploid wheat variety Zhoumai32, was used to identify and clone the candidate gene that conditioned the spike shape. Genetic analysis of an F2 population derived from a cross of ZM1160 and Bainong207 suggested that the compact spike shape in ZM1160 was controlled by a single recessive gene, and therefore, the mutated gene was designated as Tasp1. With polymorphic markers identified through bulked segregant analysis (BSA), the gene was mapped to a 2.65-cM interval flanked by markers YZU0852 and MIS46239 on chromosome 7D, corresponding to a 0.42-Mb physical interval of Chinese spring (CS) reference sequences (RefSeq v1.0). To fine map TaSP1, 15 and seven recombinants were, respectively, screened from 1599 and 1903 F3 plants derived from the heterozygous F2 plants. Finally, TaSP1 was delimited to a 21.9 Kb (4,870,562 to 4,892,493 bp) Xmis48123-Xmis48104 interval. Only one high-confidence gene TraesCS7D02G010200 was annotated in this region, which encodes an unknown protein with a putative vWA domain. Quantitative reverse transcription PCR (qRT-PCR) analysis showed that TraesCS7D02G010200 was mainly expressed in the spike. Haplotype analysis of 655 wheat cultivars using the candidate gene-specific marker Xg010200p2 identified a superior haplotype TaSP1b with longer spike and more spikelet number. TaSP1 is beneficial to the improvement in wheat spike shape.

Fine-mapping and validation of the major quantitative trait locus QFlANG-4B for flag leaf angle in wheat.

KEY MESSAGE: This study precisely mapped and validated a quantitative trait locus (QTL) located on chromosome 4B for flag leaf angle in wheat. Flag leaf angle (FLANG) is closely related to crop architecture and yield. We previously identified the quantitative trait locus (QTL) QFLANG-4B for FLANG on chromosome 4B, located within a 14-cM interval flanked by the markers Xbarc20 and Xzyh357, using a mapping population of recombinant inbred lines (RILs) derived from a cross between Nongda3331 (ND3331) and Zang1817. In this study, we fine-mapped QFLANG-4B and validated its associated genetic effect. We developed a BC3F3 population using ND3331 as the recurrent parent through marker-assisted selection, as well as near-isogenic lines (NILs) by selfing BC3F3 plants carrying different heterozygous segments for the QFLANG-4B region. We obtained eight recombinant types for QFLANG-4B, narrowing its location down to a 5.3-Mb region. This region contained 76 predicted genes, 7 of which we considered to be likely candidate genes for QFLANG-4B. Marker and phenotypic analyses of individual plants from the secondary mapping populations and their progeny revealed that the FLANG of the ND3331 allele is significantly higher than that of the Zang1817 allele in multiple environments. These results not only provide a basis for the map-based cloning of QFLANG-4B, but also indicate that QFLANG-4B has great potential for marker-assisted selection in wheat breeding programs designed to improve plant architecture and yield.

Precision mapping and expression analysis of recessive bacterial blight resistance gene xa-45(t) from Oryza glaberrima.

BACKGROUND: Bacterial blight, caused by Xanthomonas oryzae pv. oryzae (Xoo), is one of the most devastating diseases of rice leading to huge yield losses in Southeast Asia. The recessive resistance gene xa-45(t) from Oryza glaberrima IRGC102600B, mapped on rice chromosome 8, spans 80 Kb with 9 candidate genes on Nipponbare reference genome IRGSP-1.0. The xa-45(t) gene provides durable resistance against all the ten Xanthomonas pathotypes of Northern India, thus aiding in the expansion of recessive bacterial blight resistance gene pool. Punjab Rice PR127, carrying xa-45(t), was released for wider use in breeding programs. This study aims to precisely locate the target gene among the 9 candidates conferring resistance to bacterial blight disease. METHODS AND RESULTS: Sanger sequencing of all nine candidate genes revealed seven SNPs and an Indel between the susceptible parent Pusa 44 and the resistant introgression line IL274. The genotyping with polymorphic markers identified three recombinant breakpoints for LOC_Os08g42370, and LOC_Os08g42400, 15 recombinants for LOC_Os08g423420 and 26 for LOC_Os08g42440 out of 190 individuals. Relative expression analysis across six time intervals (0, 8, 24, 48, 72, and 96 h) after bacterial blight infection showed over expression of LOC_Os08g42410-specific transcripts in IL274 compared to Pusa 44, with a significant 4.46-fold increase observed at 72 h post-inoculation. CONCLUSIONS: The Indel marker at the locus LOC_Os08g42410 was found co-segregating with the phenotype, suggesting its candidacy towards xa-45(t). The transcript abundance assay provides strong evidence for the involvement of LOC_Os08g42410 in the resistance conferred by the bacterial blight gene xa-45(t).

Fine mapping of major QTL qshgd1 for spontaneous haploid genome doubling in maize (Zea mays L.).

KEY MESSAGE: A large-effect QTL was fine mapped, which revealed 79 gene models, with 10 promising candidate genes, along with a novel inversion. In commercial maize breeding, doubled haploid (DH) technology is arguably the most efficient resource for rapidly developing novel, completely homozygous lines. However, the DH strategy, using in vivo haploid induction, currently requires the use of mutagenic agents which can be not only hazardous, but laborious. This study focuses on an alternative approach to develop DH lines-spontaneous haploid genome duplication (SHGD) via naturally restored haploid male fertility (HMF). Inbred lines A427 and Wf9, the former with high HMF and the latter with low HMF, were selected to fine-map a large-effect QTL associated with SHGD-qshgd1. SHGD alleles were derived from A427, with novel haploid recombinant groups having varying levels of the A427 chromosomal region recovered. The chromosomal region of interest is composed of 45 megabases (Mb) of genetic information on chromosome 5. Significant differences between haploid recombinant groups for HMF were identified, signaling the possibility of mapping the QTL more closely. Due to suppression of recombination from the proximity of the centromere, and a newly discovered inversion region, the associated QTL was only confined to a 25 Mb region, within which only a single recombinant was observed among ca. 9,000 BC1 individuals. Nevertheless, 79 gene models were identified within this 25 Mb region. Additionally, 10 promising candidate genes, based on RNA-seq data, are described for future evaluation, while the narrowed down genome region is accessible for straightforward introgression into elite germplasm by BC methods.

QTL Mapping Using RIL Population.

Genetic maps are an excellent tool for the analysis of important traits, the development of which is the result of the combined expression of several genes, enabling the genomic localization of the factors determining them. Such features, characterized by a normal distribution of values, are referred to as quantitative or polygenic. The analysis of their genetic background using a chromosome map is called the mapping of quantitative traits loci (QTL). QTL analysis is a statistical method of determining the genetic association of phenotypic data (trait measurements) with genotypic data (DNA markers assigned to linkage groups).There are numerous tools developed for QTL mapping. This chapter introduces Windows QTL Cartographer with Composite Interval Mapping (CIM) method, which estimates the QTL position by combining interval mapping with multiple regression. The genotypic and phenotypic data used in the exemplary QTL mapping procedure were obtained for the recombinant inbred line (RIL) population of rye. Plant height, assessed in three seasons, was the exemplary trait under study.

Genetic Map Construction Using F2 and RIL/DH Mapping Population.

Genetic mapping is the determination of the position and relative genetic distance between genes or molecular markers in the chromosomes of a particular species. The construction of genetic maps uses data from the genotyping of the mapping population. Among the different mapping populations used, two are relatively common: the F2 and recombinant inbred lines (RILs) obtained as a result of the controlled crossing of genetically diverse parental forms (e.g., inbred lines). Also, the dihaploid (DH) population is often used in plants, but obtaining DHs in different crops, including rye, is very difficult or even impossible. Any molecular marker system can be used for genotyping. Polymorphic markers are used for linkage analysis, differentiating parental forms with segregation in the mapping population, consistent with the appropriate single-gene model. A genetic map is a great source of information on a species and can be an exquisite tool for analyzing important quantitative traits (QT).This chapter presents the procedure of genetic map construction with two different algorithms using the JoinMap5.0 program. First, the Materials section briefly informs about the mapping program, showing how to obtain a mapping population and prepare data for mapping. Finally, the Methods section describes the protocol for the mapping procedure itself.

QTL Analysis for Rice Quality-Related Traits and Fine Mapping of qWCR3.

The quality of rice, evaluated using multiple quality-related traits, is the main determinant of its market competitiveness. In this study, two japonica rice varieties with significant differences in quality-related traits were used as parents to construct two populations, BC3F2 and BC3F2:3, with Kongyu131 (KY131) as the recurrent parent. A genetic linkage map was constructed using the BC3F2 population based on 151 pairs of SSR/InDel polymorphic markers selected between the parents. Grain-shape-related traits (grain length GL, grain width GW, and length-to-width ratio LWR), chalkiness-related traits (white-core rate WCR, white-belly rate WBR, white-back rate BR, and chalkiness rate CR), and amylose content (AC) were investigated in the two populations in 2017 and 2018. Except for BR and CR, the traits showed similar characteristics with a normal distribution in both populations. Genetic linkage analysis was conducted for these quality-related traits, and a total of 37 QTLs were detected in the two populations. Further validation was performed on the newly identified QTLs with larger effects, and three grain shape QTLs and four chalkiness QTLs were successfully validated in different environments. One repeatedly validated QTL, qWCR3, was selected for fine mapping and was successfully narrowed down to a 100 kb region in which only two genes, LOC_0s03g45210 and LOC_0s03g45320, exhibited sequence variations between the parents. Furthermore, the variation of LOC_Os03g45210 leads to a frameshift mutation and premature protein termination. The results of this study provide a theoretical basis for positional cloning of the qWCR3 gene, thus offering new genetic resources for rice quality improvement.

Effect of genotyping errors on linkage map construction based on repeated chip analysis of two recombinant inbred line populations in wheat (Triticum aestivum L.).

Linkage maps are essential for genetic mapping of phenotypic traits, gene map-based cloning, and marker-assisted selection in breeding applications. Construction of a high-quality saturated map requires high-quality genotypic data on a large number of molecular markers. Errors in genotyping cannot be completely avoided, no matter what platform is used. When genotyping error reaches a threshold level, it will seriously affect the accuracy of the constructed map and the reliability of consequent genetic studies. In this study, repeated genotyping of two recombinant inbred line (RIL) populations derived from crosses Yangxiaomai × Zhongyou 9507 and Jingshuang 16 × Bainong 64 was used to investigate the effect of genotyping errors on linkage map construction. Inconsistent data points between the two replications were regarded as genotyping errors, which were classified into three types. Genotyping errors were treated as missing values, and therefore the non-erroneous data set was generated. Firstly, linkage maps were constructed using the two replicates as well as the non-erroneous data set. Secondly, error correction methods implemented in software packages QTL IciMapping (EC) and Genotype-Corrector (GC) were applied to the two replicates. Linkage maps were therefore constructed based on the corrected genotypes and then compared with those from the non-erroneous data set. Simulation study was performed by considering different levels of genotyping errors to investigate the impact of errors and the accuracy of error correction methods. Results indicated that map length and marker order differed among the two replicates and the non-erroneous data sets in both RIL populations. For both actual and simulated populations, map length was expanded as the increase in error rate, and the correlation coefficient between linkage and physical maps became lower. Map quality can be improved by repeated genotyping and error correction algorithm. When it is impossible to genotype the whole mapping population repeatedly, 30% would be recommended in repeated genotyping. The EC method had a much lower false positive rate than did the GC method under different error rates. This study systematically expounded the impact of genotyping errors on linkage analysis, providing potential guidelines for improving the accuracy of linkage maps in the presence of genotyping errors.

Construction of a high-density genetic map based on large-scale marker development in Coix lacryma-jobi L. using specific-locus amplified fragment sequencing (slaf-seq).

Coix lacryma-jobi L. is one of the most economically and medicinally important corns. This study constructed a high-density genetic linkage map of C. lacryma-jobi based on a cross between the parents 'Qianyi No. 2' × 'Wenyi No. 2' and their F2 progeny through high-throughput sequencing and the construction of a specific-locus amplified fragment (SLAF) library. After pre-processing, 325.49 GB of raw data containing 1628 M reads were obtained. A total of 22,944 high-quality SLAFs were identified, among which 3952 SLAFs and 3646 polymorphic markers met the requirements for the construction of a genetic linkage map. The integrated map contained 3605 high-quality SLAFs, which were grouped into ten genetic linkage groups. The total length of the map was 1620.39 cM, with an average distance of 0.45 cM and an average of 360.5 markers per linkage group. This report presents the first high-density genetic map of C. lacryma-jobi. This map was constructed using an F2 population and SLAF-seq approach, which allows the development of a large number of polymorphic markers in a short period. These results provide a platform for precise gene/quantitative trait locus (QTL) mapping, map-based gene separation, and molecular breeding in C. lacryma-jobi. They also help identify a target gene for tracking, splitting quantitative traits, and estimating the phenotypic effects of each QTL for QTL mapping. They are of great significance for improving the efficiency of discovering and utilizing excellent gene resources of C. lacryma-jobi.

Genetic linkage mapping and quantitative trait locus (QTL) analysis of sweet basil (Ocimum basilicum L.) to identify genomic regions associated with cold tolerance and major volatiles.

Chilling sensitivity is one of the greatest challenges affecting the marketability and profitability of sweet basil (Ocimum basilicum L.) in the US and worldwide. Currently, there are no sweet basils commercially available with significant chilling tolerance and traditional aroma profiles. This study was conducted to identify quantitative trait loci (QTLs) responsible for chilling tolerance and aroma compounds in a biparental mapping population, including the Rutgers advanced breeding line that served as a chilling tolerant parent, 'CB15', the chilling sensitive parent, 'Rutgers Obsession DMR' and 200 F2 individuals. Chilling tolerance was assessed by percent necrosis using machine learning and aroma profiling was evaluated using gas chromatography (GC) mass spectrometry (MS). Single nucleotide polymorphism (SNP) markers were generated from genomic sequences derived from double digestion restriction-site associated DNA sequencing (ddRADseq) and converted to genotype data using a reference genome alignment. A genetic linkage map was constructed and five statistically significant QTLs were identified in response to chilling temperatures with possible interactions between QTLs. The QTL on LG24 (qCH24) demonstrated the largest effect for chilling response and was significant in all three replicates. No QTLs were identified for linalool, as the population did not segregate sufficiently to detect this trait. Two significant QTLs were identified for estragole (also known as methyl chavicol) with only qEST1 on LG1 being significant in the multiple-QTL model (MQM). QEUC26 was identified as a significant QTL for eucalyptol (also known as 1,8-cineole) on LG26. These QTLs may represent key mechanisms for chilling tolerance and aroma in basil, providing critical knowledge for future investigation of these phenotypic traits and molecular breeding.

Genome-wide association study and development of molecular markers for yield and quality traits in peanut (Arachis hypogaea L.).

BACKGROUND: This study aims to decipher the genetic basis governing yield components and quality attributes of peanuts, a critical aspect for advancing molecular breeding techniques. Integrating genotype re-sequencing and phenotypic evaluations of seven yield components and two grain quality traits across four distinct environments allowed for the execution of a genome-wide association study (GWAS). RESULTS: The nine phenotypic traits were all continuous and followed a normal distribution. The broad heritability ranged from 88.09 to 98.08%, and the genotype-environment interaction effects were all significant. There was a highly significant negative correlation between protein content (PC) and oil content (OC). The 10× genome re-sequencing of 199 peanut accessions yielded a total of 631,988 high-quality single nucleotide polymorphisms (SNPs), with 374 significant SNP loci identified in association with the nine traits of interest. Notably, 66 of these pertinent SNPs were detected in multiple environments, and 48 of them were linked to multiple traits of interest. Five loci situated on chromosome 16 (Chr16) exhibited pleiotropic effects on yield traits, accounting for 17.64-32.61% of the observed phenotypic variation. Two loci on Chr08 were found to be strongly associated with protein and oil contents, accounting for 12.86% and 14.06% of their respective phenotypic variations, respectively. Linkage disequilibrium (LD) block analysis of these seven loci unraveled five nonsynonymous variants, leading to the identification of one yield-related candidate gene and two quality-related candidate genes. The correlation between phenotypic variation and SNP loci in these candidate genes was validated by Kompetitive allele-specific PCR (KASP) marker analysis. CONCLUSIONS: Overall, molecular markers were developed for genetic loci associated with yield and quality traits through a GWAS investigation of 199 peanut accessions across four distinct environments. These molecular tools can aid in the development of desirable peanut germplasm with an equilibrium of yield and quality through marker-assisted breeding.

Exploiting genomic tools for genetic dissection and improving the resistance to Fusarium stalk rot in tropical maize.

KEY MESSAGE: A stable genomic region conferring FSR resistance at ~250 Mb on chromosome 1 was identified by GWAS. Genomic prediction has the potential to improve FSR resistance. Fusarium stalk rot (FSR) is a global destructive disease in maize; the efficiency of phenotypic selection for improving FSR resistance was low. Novel genomic tools of genome-wide association study (GWAS) and genomic prediction (GP) provide an opportunity for genetic dissection and improving FSR resistance. In this study, GWAS and GP analyses were performed on 562 tropical maize inbred lines consisting of two populations. In total, 15 SNPs significantly associated with FSR resistance were identified across two populations and the combinedPOP consisting of all 562 inbred lines, with the P-values ranging from 1.99 × 10-7 to 8.27 × 10-13, and the phenotypic variance explained (PVE) values ranging from 0.94 to 8.30%. The genetic effects of the 15 favorable alleles ranged from -4.29 to -14.21% of the FSR severity. One stable genomic region at ~ 250 Mb on chromosome 1 was detected across all populations, and the PVE values of the SNPs detected in this region ranged from 2.16 to 5.18%. Prediction accuracies of FSR severity estimated with the genome-wide SNPs were moderate and ranged from 0.29 to 0.51. By incorporating genotype-by-environment interaction, prediction accuracies were improved between 0.36 and 0.55 in different breeding scenarios. Considering both the genome coverage and the threshold of the P-value of SNPs to select a subset of molecular markers further improved the prediction accuracies. These findings extend the knowledge of exploiting genomic tools for genetic dissection and improving FSR resistance in tropical maize.

A combination of QTL mapping and genome-wide association study revealed the key gene for husk number in maize.

KEY MESSAGE: Two key genes Zm00001d021232 and Zm00001d048138 were identified by QTL mapping and GWAS. Additionally, they were verified to be significantly associated with maize husk number (HN) using gene-based association study. As a by-product of maize production, maize husk is an important industrial raw material. Husk layer number (HN) is an important trait that affects the yield of maize husk. However, the genetic mechanism underlying HN remains unclear. Herein, a total of 13 quantitative trait loci (QTL) controlling HN were identified in an IBM Syn 10 DH population across different locations. Among these, three QTL were individually repeatedly detected in at least two environments. Meanwhile, 26 unique single nucleotide polymorphisms (SNPs) were detected to be significantly (p < 2.15 × 10-6) associated with HN in an association pool. Of these SNPs, three were simultaneously detected across multiple environments or environments and best linear unbiased prediction (BLUP). We focused on these environment-stable and population-common genetic loci for excavating the candidate genes responsible for maize HN. Finally, 173 initial candidate genes were identified, of which 22 were involved in both multicellular organism development and single-multicellular organism process and thus confirmed as the candidate genes for HN. Gene-based association analyses revealed that the variants in four genes were significantly (p < 0.01/N) correlated with HN, of which Zm00001d021232 and Zm00001d048138 were highly expressed in husks and early developing ears among different maize tissues. Our study contributes to the understanding of genetic and molecular mechanisms of maize husk yield and industrial development in the future.

Expression, Polymorphism, and Potential Functional Sites of the BMPR1A Gene in the Sheep Horn.

Sheep horns are composed of bone and sheaths, and the BMPR1A gene is required for cartilage and osteogenic differentiation. Therefore, the BMPR1A gene may have a function related to the sheep horn, but its relationship with the sheep horn remains unclear. In this study, we first utilized RNA sequencing (RNA-seq) data to investigate the expression of the BMPR1A gene in different tissues and breeds of sheep. Second, whole-genome sequencing (WGS) data were used to explore the functional sites of the BMPR1A gene. Lastly, the allele-specific expression of the BMPR1A gene was explored. Our results indicate that BMPR1A gene expression is significantly higher in the normal horn groups than in the scurred groups. Importantly, this trend is consistent across several sheep breeds. Therefore, this finding suggests that the BMPR1A gene may be related to horn type. A total of 43 Single-Nucleotide Polymorphisms (SNPs) (F-statistics > 0.15) and 10 allele-specific expressions (ASEs) exhibited difference between the large and small horn populations. It is probable that these sites significantly impact the size of sheep horns. Compared to other polled species, we discovered ten amino acid sites that could influence horn presence. By combining RNA-seq and WGS functional loci results, we identified a functional site at position 40574836 on chromosome 25 that is both an SNP and exhibits allele-specific expression. In conclusion, we demonstrated that the BMPR1A gene is associated with horn type and identified some important functional sites which can be used as molecular markers in the breeding of sheep horns.

Potential locus W and candidate gene McPRR2 associated with pericarp pigment accumulation in bitter gourd (Momordica charantia L.) revealed via BSA-seq analysis.

Pericarp color is a prominent agronomic trait that exerts a significant impact on consumer and breeder preferences. Genetic analysis has revealed that the pericarp color of bitter gourd is a quantitative trait. However, the underlying mechanism for this trait in bitter gourd remains largely unknown. In the present study, we employed bulked segregant analysis (BSA) to identify the candidate genes responsible for bitter gourd pericarp color (specifically, dark green versus white) within F2 segregation populations resulting from the crossing of B07 (dark green pericarp) and A06 (white pericarp). Through genomic variation, genetic mapping, and expression analysis, we identified a candidate gene named McPRR2, which was a homolog of Arabidopsis pseudo response regulator 2 (APRR2) encoded by LOC111023472. Sequence alignment of the candidate gene between the two parental lines revealed a 15-bp nucleotide insertion in the coding region of LOC111023472, leading to a premature stop codon and potentially causing a loss-of-function mutation. qRT-PCR analysis demonstrated that the expression of McPRR2 was significantly higher in B07 compared to A06, and it was primarily expressed in the immature fruit pericarp. Moreover, overexpression of McPRR2 in tomato could enhance the green color of immature fruit pericarp by increasing the chlorophyll content. Consequently, McPRR2 emerged as a strong candidate gene regulating the bitter gourd pericarp color by influencing chlorophyll accumulation. Finally, we developed a molecular marker linked to pericarp color, enabling the identification of genotypes in breeding populations. These findings provided valuable insights into the genetic improvement of bitter gourd pericarp color.

Quantitative trait loci detection for three tiller-related traits and the effects on wheat (Triticum aestivum L.) yields.

KEY MESSAGE: A total of 38 putative additive QTLs and 55 pairwise putative epistatic QTLs for tiller-related traits were reported, and the candidate genes underlying qMtn-KJ-5D, a novel major and stable QTL for maximum tiller number, were characterized. Tiller-related traits play an important role in determining the yield potential of wheat. Therefore, it is important to elucidate the genetic basis for tiller number when attempting to use genetic improvement as a tool for enhancing wheat yields. In this study, a quantitative trait locus (QTL) analysis of three tiller-related traits was performed on the recombinant inbred lines (RILs) of a mapping population, referred to as KJ-RILs, that was derived from a cross between the Kenong 9204 (KN9204) and Jing 411 (J411) lines. A total of 38 putative additive QTLs and 55 pairwise putative epistatic QTLs for spike number per plant (SNPP), maximum tiller number (MTN), and ear-bearing tiller rate (EBTR) were detected in eight different environments. Among these QTLs with additive effects, three major and stable QTLs were first documented herein. Almost all but two pairwise epistatic QTLs showed minor interaction effects accounting for no more than 3.0% of the phenotypic variance. The genetic effects of two colocated major and stable QTLs, i.e., qSnpp-KJ-5D.1 and qMtn-KJ-5D, for yield-related traits were characterized. The breeding selection effect of the beneficial allele for the two QTLs was characterized, and its genetic effects on yield-related traits were evaluated. The candidate genes underlying qMtn-KJ-5D were predicted based on multi-omics data, and TraesKN5D01HG00080 was identified as a likely candidate gene. Overall, our results will help elucidate the genetic architecture of tiller-related traits and can be used to develop novel wheat varieties with high yields.

Identification of QTLs for symbiotic nitrogen fixation and related traits in a soybean recombinant inbred line population.

KEY MESSAGE: The genetic architecture of symbiotic N fixation and related traits was investigated in the field. QTLs were identified for percent N derived from the atmosphere, shoot [N] and C to N ratio. Soybean [Glycine max (L.) Merr.] is cultivated worldwide and is the most abundant source of plant-based protein. Symbiotic N2 fixation (SNF) in legumes such as soybean is of great importance; however, yields may still be limited by N in both high yielding and stressful environments. To better understand the genetic architecture of SNF and facilitate the development of high yielding cultivars and sustainable soybean production in stressful environments, a recombinant inbred line population consisting of 190 lines, developed from a cross between PI 442012A and PI 404199, was evaluated for N derived from the atmosphere (Ndfa), N concentration ([N]), and C to N ratio (C/N) in three environments. Significant genotype, environment and genotype × environment effects were observed for all three traits. A linkage map was constructed containing 3309 single nucleotide polymorphism (SNP) markers. QTL analysis was performed for additive effects of QTLs, QTL × environment interactions, and QTL × QTL interactions. Ten unique additive QTLs were identified across all traits and environments. Of these, two QTLs were detected for Ndfa and eight for C/N. Of the eight QTLs for C/N, four were also detected for [N]. Using QTL × environment analysis, six QTLs were detected, of which five were also identified in the additive QTL analysis. The QTL × QTL analysis identified four unique epistatic interactions. The results of this study may be used for genomic selection and introgression of favorable alleles for increased SNF, [N], and C/N via marker-assisted selection.

Fine mapping and candidate gene analysis of qSRC3 controlling the silk color in maize (Zea mays L.).

KEY MESSAGE: Fine mapping of the maize QTL qSRC3, responsible for red silk, uncovered the candidate gene ZmMYB20, which encodes an R2R3-MYB transcription factor, has light-sensitive expression, and putatively regulates genes expression associated with anthocyanin biosynthesis. Colorless silk is a key characteristic contributing to the visual quality of fresh corn intended for market distribution. Nonetheless, the identification of Mendelian trait loci and associated genes that control silk color has been scarce. In this study, a F2 population arising from the hybridization of the single-segment substitution line qSRC3MT1 with red silk, carrying an introgressed allele from teosinte (Zea mays ssp. mexicana), and the recurrent maize inbred line Mo17, characterized by light green silk, was utilized for fine mapping. We found that the red silk trait is controlled by a semi-dominant genetic locus known as qSRC3, and its expression is susceptible to light-mediated inhibition. Moreover, qSRC3 explained 68.78% of the phenotypic variance and was delimited to a 133.2 kb region, which includes three genes. Subsequent expression analyses revealed that ZmMYB20 (Zm00001d039700), which encodes an R2R3-MYB transcription factor, was the key candidate gene within qSRC3. Yeast one-hybrid and dual-luciferase reporter assays provided evidence that ZmMYB20 suppresses the expression of two crucial anthocyanin biosynthesis genes, namely ZmF3H and ZmUFGT, by directly binding to their respective promoter regions. Our findings underscore the significance of light-inhibited ZmMYB20 in orchestrating the spatial and temporal regulation of anthocyanin biosynthesis. These results advance the production of colorless silk in fresh corn, responding to the misconception that fresh corn with withered colored silk is not fresh and providing valuable genetic resources for the improvement of sweet and waxy maize.

Construction of Genetic Map and QTL Mapping for Seed Size and Quality Traits in Soybean (Glycine max L.).

Soybean (Glycine max L.) is the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean yield and quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) mapping for yield and quality traits, as well as for the identification of mining-related candidate genes, is of great significance for the molecular breeding and understanding the genetic mechanism. In this study, 186 individual plants of the F2 generation derived from crosses between Changjiangchun 2 and Yushuxian 2 were selected as the mapping population to construct a molecular genetic linkage map. A genetic map containing 445 SSR markers with an average distance of 5.3 cM and a total length of 2375.6 cM was obtained. Based on constructed genetic map, 11 traits including hundred-seed weight (HSW), seed length (SL), seed width (SW), seed length-to-width ratio (SLW), oil content (OIL), protein content (PRO), oleic acid (OA), linoleic acid (LA), linolenic acid (LNA), palmitic acid (PA), stearic acid (SA) of yield and quality were detected by the multiple- d size traits and 113 QTLs related to quality were detected by the multiple QTL model (MQM) mapping method across generations F2, F2:3, F2:4, and F2:5. A total of 71 QTLs related to seed size traits and 113 QTLs related to quality traits were obtained in four generations. With those QTLs, 19 clusters for seed size traits and 20 QTL clusters for quality traits were summarized. Two promising clusters, one related to seed size traits and the other to quality traits, have been identified. The cluster associated with seed size traits spans from position 27876712 to 29009783 on Chromosome 16, while the cluster linked to quality traits spans from position 12575403 to 13875138 on Chromosome 6. Within these intervals, a reference genome of William82 was used for gene searching. A total of 36 candidate genes that may be involved in the regulation of soybean seed size and quality were screened by gene functional annotation and GO enrichment analysis. The results will lay the theoretical and technical foundation for molecularly assisted breeding in soybean.