RIL Population Research Articles

Integration Linkage Mapping and Comparative Transcriptome Analysis to Dissect the Genetic Basis of Rice Salt Tolerance Associated with the Germination Stage.

Soil salinity poses a serious threat to rice production. The salt tolerance of rice at the germination stage is one of the major determinants of stable stand establishment, which is very important for direct seeding in saline soil. The complexity and polygenic nature of salt tolerance have limited the efficiency of discovering and cloning key genes in rice. In this study, an RIL population with an ultra-high-density genetic map was employed to investigate the salt-tolerant genetic basis in rice, and a total of 20 QTLs were detected, including a major and stable QTL (qRCL3-1). Subsequently, salt-specific DEGs from a comparative transcriptome analysis were overlaid onto annotated genes located on a stable QTL interval, and eight putative candidate genes were further identified. Finally, from the sequence alignment and variant analysis, OsCam1-1 was confirmed to be the most promising candidate gene for regulating salinity tolerance in rice. This study provides important information for elucidating the genetic and molecular basis of rice salt tolerance at the germination stage, and the genes detected here will be useful for improvements in rice salt tolerance.

The Ratio of A400/A1800 Mapping Identifies Chromosomal Regions Containing Known Photoprotection Recovery-Related Genes in Rice

The rice, like other plants, undergoes photoprotection mode by increasing nonphotochemical quenching (NPQ) in high light intensity (> 1200 µmol m− 2s− 1 PPFD), which attenuates photosystem II yield (φPSII) drastically. The plant remains in photoprotection mode even after light intensity becomes not stressful for an extended period. While there are significant differences in the time it takes for photoprotection to recover among different genotypes, its use is limited in plant breeding because measuring the chlorophyll fluorescence parameters in progressive actinic light after dark adaptation takes more than forty-five minutes per genotype. The study finds that instantly measured A400/A1800 ratio by five minutes in flag leaves of 25 diverse genotypes strongly associated with the φPSII400 differences between theoretical and actual, qPd400 and NPQ400 with R2 values 0.74, 0.65 and 0.60, respectively. In two consecutive years, GWAS of A400/A1800 ratio identified the regions with genes reported earlier for plant photoprotection recovery. Additionally, QTL analysis in a RIL population also identified the regions carrying known genes related to photoprotection. Thus, the A400/A1800 ratio can quickly phenotype many plants for easier introgression of the traits in popular cultivars. The identified genotypes, genes, and QTLs can be used to improve yield potential and allele mining.

Inheritance and QTL mapping identified multi-effects loci for fatty acid related traits in peanut (Arachis hypogaea L.)

Peanut (Arachis hypogaea L.) is an important oil and edible protein crop. The fatty acid composition not only influences the quality of peanut oil but also impacts flavor, shelf life, and consumer health. Peanut oil comprises approximately 80% oleic acid (C18:1) and linoleic acid (C18:2), 10% palmitic acid (C16:0), and the remaining 10% includes stearic acid (C18:0), arachidic acid (C20:0), gadoleic acid (C20:1), behenic acid (C22:0), and lignoceric acid (C24:0). To unravel the genetic foundation of fatty acid content and delve into QTL localization, we utilized high-density SNP microarrays for genotyping the RIL population of ‘SunOleic 97R’ × ‘NC94022’. A genetic linkage map was constructed with 3141 SNP markers, covering a total genetic distance of 3051.81 cM. We identified 60 quantitative trait loci (QTLs) associated with fatty acids which distributed in 11 linkage group, with phenotypic variance explained (PVE) ranging from 1.37% to 44.92%. Notably, the QTL qFAT_A05.1 and qFAT_A08.1 are multiple-effect loci contributing to various fatty acid compositions. Moreover, we identified 15 haplotypes for the QTL qFAT_A05.1 and qFAT_A08.1 through genotyping 178 peanut germplasms. Haplotypes analysis in natural population confirmed the closely relationship of the QTLs with the content of oil, oleic acid, lignoceric acid, palmitic acid and behenic acid. This study serves as a valuable reference for selecting improved peanut genotypes with superior oil quality and desirable fatty acid composition.

Identification and development of functional markers for purple grain genes in durum wheat (Triticum durum Desf.).

Two allelic variants of Pp-A3 and Pp-B1 were identified in purple durum wheat. Molecular markers at both loci were developed and validated on an independent panel, offering a breakthrough for wheat improvement. Purple wheats are a class of cereals with pigmented kernels of particular interest for their antioxidant and anti-inflammatory properties. Although two complementary loci (Pp-B1 and Pp-A3), responsible for purple pericarp have been pinpointed in bread wheat (Triticum aestivum L.), in durum wheat (Triticum durum Desf.) the causative genes along with functional and non-functional alleles are still unknown. Here, using a quantitative trait loci (QTL) mapping approach on a RIL population derived from purple and non-purple durum wheat genotypes, we identified three major regions on chromosomes 2A, 3A, and 7B explaining the highest phenotypic variation (> 50%). Taking advantage of the Svevo genome, a MYB was reannotated on chromosome 7B and reported as a candidate for Pp-B1. An insertion of ~ 1.6kb within the first exon led to a non-functional allele (TdPpm1b), whereas the functional allele (TdPpm1a) was characterized and released for the first time in durum wheat. Pp-A3 was instead identified as a duplicated gene, of which only one was functional. The promoter sequencing of the functional allele (TdPpb1a) revealed six 261-bp tandem repeats in purple durum wheat, whereas one unit (TdPpb1b) was found in the yellow once. Functional molecular markers at both loci were developed to precisely discriminate purple and not purple genotypes, representing a valuable resource for selecting superior purple durum lines at early growth stages. Overall, our results expand the understanding of the function of MYB and bHLH activators in durum wheat, paving new ways to explore cis-regulatory elements at the promoter level.

Linkage Mapping and Discovery of Candidate Genes for Drought Tolerance in Rice During the Vegetative Growth Period

Drought is a major abiotic stress affecting crop yields. Mapping quantitative trait loci (QTLs) and mining genes for drought tolerance in rice are important for identifying gene functions and targets for molecular breeding. Here, we performed linkage analysis of drought tolerance using a recombinant inbred line population derived from Jileng 1 (drought sensitive) and Milyang 23 (drought tolerant). An ultra-high-density genetic map, previously constructed by our research team using genotype data from whole-genome sequencing, was used in combination with phenotypic data for rice grown under drought stress conditions in the field in 2017–2019. Thirty-nine QTLs related to leaf rolling index and leaf withering degree were identified, and QTLs were found on all chromosomes except chromosomes 6, 10, and 11. qLWD4-1 was detected after 32 days and 46 days of drought stress in 2017 and explained 7.07–8.19% of the phenotypic variation. Two loci, qLRI2-2 and qLWD4-2, were identified after 29, 42, and 57 days of drought stress in 2018. These loci explained 10.59–17.04% and 5.14–5.71% of the phenotypic variation, respectively. There were 281 genes within the QTL interval. Through gene functional annotation and expression analysis, two candidate genes, Os04g0574600 and OsCHR731, were found. Quantitative reverse transcription PCR analysis showed that the expression levels of these genes were significantly higher under drought stress than under normal conditions, indicating positive regulation. Notably, Os04g0574600 was a newly discovered drought tolerance gene. Haplotype analysis showed that the RIL population carried two haplotypes (Hap1 and Hap2) of both genes. Lines carrying Hap2 exhibited significantly or extremely stronger drought tolerance than those carrying Hap1, indicating that Hap2 is an excellent haplotype. Among rice germplasm resources, there were two and three haplotypes of Os04g0574600 and OsCHR731, respectively. A high proportion of local rice resources in Sichuan, Yunnan, Anhui, Guangdong and Fujian provinces had Hap of both genes. In wild rice, 50% of accessions contained Hap1 of Os04g0574600 and 50% carried Hap4; 13.51%, 59.46% and 27.03% of wild rice accessions contained Hap1, Hap2, and Hap3, respectively. Hap2 of Os04g0574600 was found in more indica rice resources than in japonica rice. Therefore, Hap2 has more potential for utilization in future drought tolerance breeding of japonica rice.

Mining Candidate Genes for Leaf Angle in Brassica napus L. by Combining QTL Mapping and RNA Sequencing Analysis.

Leaf angle (LA) is an important trait of plant architecture, and individuals with narrow LA can better capture canopy light under high-density planting, which is beneficial for increasing the overall yield per unit area. To study the genetic basis and molecular regulation mechanism of leaf angle in rapeseed, we carried out a series of experiments. Quantitative trait loci (QTL) mapping was performed using the RIL population, and seven QTLs were identified. Transcriptome analysis showed that the cell wall formation/biogenesis processes and biosynthesis/metabolism of cell wall components were the most enrichment classes. Most differentially expressed genes (DEGs) involved in the synthesis of lignin, xylan, and cellulose showed down-regulated expression in narrow leaf material. Microscopic analysis suggested that the cell size affected by the cell wall in the junction area of the stem and petiole was the main factor in leaf petiole angle (LPA) differences. Combining QTL mapping and RNA sequencing, five promising candidate genes BnaA01G0125600ZS, BnaA01G0135700ZS, BnaA01G0154600ZS, BnaA10G0154200ZS, and BnaC03G0294200ZS were identified in rapeseed, and most of them were involved in cell wall biogenesis and the synthesis/metabolism of cell wall components. The results of QTL, transcriptome analysis, and cytological analysis were highly consistent, collectively revealing that genes related to cell wall function played a crucial role in regulating the LA trait in rapeseed. The study provides further insights into LA traits, and the discovery of new QTLs and candidate genes is highly beneficial for genetic improvement.

Independent genetic factors control floret number and spikelet number in Triticum turgidum ssp.

Wheat grain yield is a complex trait resulting from a trade-off among many distinct components. During wheat evolution, domestication events and then modern breeding have strongly increased the yield potential of wheat plants, by enhancing spike fertility. To address the genetic bases of spike fertility in terms of spikelet number per spike and floret number per spikelet, a population of 110 recombinant inbred lines (RILS) obtained crossing a Triticum turgidum ssp. durum cultivar (Latino) and a T. dicoccum accession (MG5323) was exploited. Being a modern durum and a semi-domesticated genotype, respectively, the two parents differ for spike architecture and fertility, and thus the corresponding RIL population is the ideal genetic material to dissect genetic bases of yield components. The RIL population was phenotyped in four environments. Using a high-density SNP genetic map and taking advantage of several genome sequencing available for Triticeae, a total of 94 QTLs were identified for the eight traits considered; these QTLs were further reduced to 17 groups, based on their genetic and physical co-location. QTLs controlling floret number per spikelet and spikelet number per spike mapped in non-overlapping chromosomal regions, suggesting that independent genetic factors determine these fertility-related traits. The physical intervals of QTL groups were considered for possible co-location with known genes functionally involved in spike fertility traits and with yield-related QTLs previously mapped in tetraploid wheat. The most interesting result concerns a QTL group on chromosome 5B, associated with spikelet number per spike, since it could host genes still uncharacterized for their association to spike fertility. Finally, we identified two different regions where the trade-off between fertility related traits and kernel weight is overcome. Further analyses of these regions could pave the way for a future identification of new genetic loci contributing to fertility traits essential for yield improvement in durum wheat.

Genetic and Physiological Insights into Salt Resistance in Rice through Analysis of Germination, Seedling Traits, and QTL Identification.

Understanding the genetic basis of salt resistance in crops is crucial for agricultural productivity. This study investigates the phenotypic and genetic basis of salt stress response in rice (Oryza sativa L.), focusing on germination and seedling traits. Under salt stress conditions, significant differences were observed in seed germination and seedling traits between parental LH99 (Indica rice LuHui 99) and SN265 (japonica rice ShenNong 265). Transgressive segregation was evident within the RIL population, indicating complex genetic interactions. Nine QTLs were detected at germination and seedling stages under salt stress, namely qSGE5 and qSGE7 for seed germination energy (SGE); qSGP7 for seed germination percentage (SGP); qSSH7, qSSH9-1, and qSSH9-2 for seeding height (SSH); qSRN6 for root number (SRN); and qSDW6 and qSDW9 for dry weight (SDW). Among them, qSSH9-1 and qSDW9 were localized in the same interval, derived from the salt-resistant parent SN265. PCA revealed distinct trait patterns under salt stress, captured by six PCs explaining 81.12% of the total variance. PC composite scores were used to localize a QTL associated with early salt resistance in rice qESC9, which was located in the same interval as qSSH9-1 and qSDW9, and was subsequently unified under the name qESC9, an important QTL for early-growth salt tolerance in rice. Correlation analysis also confirmed a relationship between alleles of qESC9 and the resistance to salt, underscoring the critical role this locus plays in the determination of overall salt tolerance in rice. Physiological analyses of extreme phenotype lines highlighted the importance of ion exclusion mechanisms in salt-resistant lines, while salt-susceptible lines exhibited elevated oxidative stress and impaired antioxidant defense, contributing to cellular damage. This comprehensive analysis sheds light on the genetic and physiological mechanisms underlying salt stress response in rice, providing valuable insights for breeding programs aimed at enhancing salt resistance in rice.

Fine mapping of stem rust resistance derived from soft red winter wheat cultivar AGS2000 to an NLR gene cluster on chromosome 6D

The Puccinia graminis f. sp. tritici (Pgt) Ug99-emerging virulent races present a major challenge to global wheat production. To meet present and future needs, new sources of resistance must be found. Identification of markers that allow tracking of resistance genes is needed for deployment strategies to combat highly virulent pathogen races. Field evaluation of a DH population located a QTL for stem rust (Sr) resistance, QSr.nc-6D from the breeding line MD01W28-08-11 to the distal region of chromosome arm 6DS where Sr resistance genes Sr42, SrCad, and SrTmp have been identified. A locus for seedling resistance to Pgt race TTKSK was identified in a DH population and an RIL population derived from the cross AGS2000 × LA95135. The resistant cultivar AGS2000 is in the pedigree of MD01W28-08-11 and our results suggest that it is the source of Sr resistance in this breeding line. We exploited published markers and exome capture data to enrich marker density in a 10 Mb region flanking QSr.nc-6D. Our fine mapping in heterozygous inbred families identified three markers co-segregating with resistance and delimited QSr.nc-6D to a 1.3 Mb region. We further exploited information from other genome assemblies and identified collinear regions of 6DS harboring clusters of NLR genes. Evaluation of KASP assays corresponding to our co-segregating SNP suggests that they can be used to track this Sr resistance in breeding programs. However, our results also underscore the challenges posed in identifying genes underlying resistance in such complex regions in the absence of genome sequence from the resistant genotypes.

Genetic studies for blast disease in a biparental RIL population of pearl millet

Genetic studies for blast disease in a biparental RIL population of pearl millet

Mining for QTL controlling maize low-phosphorus response genes combined with deep resequencing of RIL parental genomes and in silico GWAS analysis.

Extensive and comprehensive phenotypic data from a maize RIL population under both low- and normal-Pi treatments were used to conduct QTL mapping. Additionally, we integrated parental resequencing data from the RIL population, GWAS results, and transcriptome data to identify candidate genes associated with low-Pi stress in maize. Phosphorus (Pi) is one of the essential nutrients that greatly affect the maize yield. However, the genes underlying the QTL controlling maize low-Pi response remain largely unknown. In this study, a total of 38 traits at both seedling and maturity stages were evaluated under low- and normal-Pi conditions using a RIL population constructed from X178 (tolerant) and 9782 (sensitive), and most traits varied significantly between low- and normal-Pi treatments. Twenty-nine QTLs specific to low-Pi conditions were identified after excluding those with common intervals under both low- and normal-Pi conditions. Furthermore, 45 additional QTLs were identified based on the index value ((Trait_under_LowPi-Trait_under_NormalPi)/Trait_under_NormalPi) of each trait. These 74 QTLs collectively were classified as Pi-dependent QTLs. Additionally, 39 Pi-dependent QTLs were clustered in nine HotspotQTLs. The Pi-dependent QTL interval contained 19,613 unique genes, 6,999 of which exhibited sequence differences with non-synonymous mutation sites between X178 and 9782. Combined with in silico GWAS results, 277 consistent candidate genes were identified, with 124 genes located within the HotspotQTL intervals. The transcriptome analysis revealed that 21 genes, including the Pi transporter ZmPT7 and the strigolactones pathway-related gene ZmPDR1, exhibited consistent low-Pi stress response patterns across various maize inbred lines or tissues. It is noteworthy that ZmPDR1 in maize roots can be sharply up-regulated by low-Pi stress, suggesting its potential importance as a candidate gene for responding to low-Pi stress through the strigolactones pathway.

Cytogenetic identification and molecular mapping for the wheat-Thinopyrum ponticum introgression line with resistance to Fusarium head blight.

Xinong 511, a new wheat-Thinopyrum ponticum variety with excellent fusarium head blight resistance, the QTLs were mapped to the wheat chromosomes 5B and 7A with named QFhb.nwafu-5B and QFhb.nwafu-7A, respectively. Novel Fusarium head blight (FHB) resistance germplasms and genes are valuable for wheat improvement and breeding efforts. Thinopyrum ponticum, a wild relative of common wheat, is a valuable germplasm of disease resistance for wheat improvement and breeding. Xinong 511 (XN511) is a high-quality wheat variety widely cultivated in the Yellow and Huai Rivers Valley of China with stable FHB-resistance. Through analysis of pedigree materials of the wheat cultivar XN511, we found that the genetic material and FHB resistance from Th. ponticum were transmitted to the introgression line, indicating that the FHB resistance in XN511 likely originates from Th. ponticum. To further explore the genetic basis of FHB resistance in XN511, QTL mapping was conducted using the RILs population of XN511 and the susceptible line Aikang 58 (AK58). Survey with makers closely-linked to Fhb1, Fhb2, Fhb4, Fhb5, and Fhb7, indicated that both XN511 and the susceptible lines do not contain these QTL. Using bulked segregant analysis RNA-seq (BSR-Seq) and newly developed allele-specific PCR (AS-PCR) markers, QTLs in XN511 were successfully located on wheat chromosomes 5B and 7A. These findings are significant for further understanding and utilizing FHB resistance genes in wheat improvement.

High-density genetic map construction and QTL mapping in the sorghum-sudangrass RIL population (M81×Sa)

High-density genetic map construction and QTL mapping in the sorghum-sudangrass RIL population (M81×Sa)

Assessment of the genetic structure of two different tomato breeding populations by Principal Component Analysis

In Plant Breeding, different populations are generated, which frequently represent different gene arrangement from a common selected gene pool. The technique of Principal Component Analysis (PCA) has been widely applied to evaluate the genetic structure of different populations. The objective of this research was to assess PCA for evaluating the genetic structure of two breeding tomato populations, one representing a final step of a breeding program (RIL population) and the other, an initial step (a six basic generations’ population, composed by two homozygous parent, their heterozygous F1 and the segregating F2 and two backcrosses). Both populations were evaluated for phenotypic quantitative traits and population structure was assessed in terms of variances and covariances. PCA was adequate for evaluating differences in genetic structure for evaluated fruit quality traits in both populations.

Mapping of main and hidden epistatic QTL effects in spring wheat population using medium parental FHB resistance

Fusarium head blight (FHB) is a devastating disease lowering the yield and quality of wheat. Intensive use of limited allelic pools critically affects wheat resistance, while advancing pathogenic alleles. This study presents new alleles raised from moderate rather than elite crosses. ‘Parshall’ has indigenous moderate resistance that was crossed with the moderate susceptible ‘Reeder’ and developed the 110 RIL population (noted as PR) that was tested across three states and years in the USA, under open-field and greenhouse conditions. Heading- and FHB-related traits of incidence, severity, and index were assessed. A genetic map (1417 cM) of SNP/DArT markers was generated. Composite interval mapping produced 45 QTL. Permutated LOD assessment identified two consistent QTL (4AL and 4BL) of type I and II resistance. Significant markers at the 4A QTL showed correlation with previous FHB resistance, while at the 4B QTL with pathogen responsive regions. The 1- and 2-D genome scans identified 16 QTL and six pairs of interacting markers for resistance, with additive effects between 0.17% and 2.19%; respectively. Additionally, additive × environment interaction was between 0.04% and 3.18% confirming the high environmental effect. Three pairs of QTL with additive × additive effects between 0.15% and 0.30% were revealed by FHB epistasis. However, the additive × additive environmental interaction at these three loci varied between 0.03% and 1%, confirming the G × E effect on FHB resistance. Hidden heritable epistasis was discovered in PR-population for FHB resistance. PR-alleles will help breeders develop lines mitigating epidemic environments and changeable climates, to boost yield facing hanger, food scarce, and secure worldwide penurious economies.

Screening lentil (Lens culinaris) RIL population for high yield and aluminium toxicity tolerance under acidic field and hydroponic conditions

Screening lentil (Lens culinaris) RIL population for high yield and aluminium toxicity tolerance under acidic field and hydroponic conditions

Genomic Regions and Candidate Genes for Seed Iron and Seed Zinc Accumulation Identified in the Soybean ‘Forrest’ by ‘Williams 82’ RIL Population

Soybean is a major crop in the world and an essential source for minerals, including iron (Fe) and zin (Zn). Deficiency of Fe and Zn in soil and soybean plants result in yield loss and poor seed nutritional qualities. Information on genomic regions and candidate genes controlling seed Fe and Zn accumulation in soybean seed is limited. Therefore, The objective of this research was to identify genetic regions, known as quantitative trait loci (QTL), and candidate genes that control the accumulation of Fe and Zn in soybean mature seeds. A ‘Forrest’ by ‘Williams 82’ (F × W82) recombinant inbred line (RIL) population (n = 306) was used and genotyped using a total of 5405 single nucleotides polymorphism (SNP) markers using Infinium SNP6K BeadChips. A two-year experiment was conducted across two environments: North Carolina in 2018 (NC) and Illinois in 2020 (IL). Only QTL with LOD scores ≥ 2.5, as identified by the composite interval mapping (CIM) method, are reported here. In total, 6 QTL were identified for seed Fe; specifically, 3 QTL (qFe-01-[NC-2018], qFe-02-[NC-2018], and qFe-03-[NC-2018]) were located on chromosomes 1, 2, and 6, respectively, in the NC environment, and 3 QTL (qFe-01-[IL-2020], qFe-02-[IL-2020], and qFe-03-[IL-2020]) were positioned on chromosomes 1, 2, and 12, respectively, in the IL environment. A total of 6 QTL associated with seed Zn were also identified; 4 QTL (qZn-01-[NC-2018]; qZn-02-[NC-2018]; qZn-03-[NC-2018]; and qZn-04-[NC-2018]), respectively on Chr 2, 3, 7, and 19 in NC; and 2 QTL (qZn-01-[IL-2020] and qZn-02-[IL-2020]), respectively, on Chr 5 and 8 in IL. Several functional genes encode Fe- and Zn-proteins, transcription factors, proteins-zinc finger motifs (involved in DNA binding and transcriptional regulation; crosstalk between the regulatory pathways of Zn and Fe transporters) were identified and located within the QTL interval. To our knowledge, and based on the literature available, the QTL identified here on Chr 2 and Chr 6 are novel and were not previously identified. This current research provides a new knowledge of the genetic basis of seed Fe and Zn and the markers associated with QTL. The QTL identified here will contribute to efficient marker assisted selection for higher Fe and Zn content in soybean seeds. The candidate genes and metal-responsive transcription factors may coordinate the expression of both Zn and Fe transporters in response to changes in metal availability, providing new knowledge on minerals uptake and transport mechanisms, allowing for possible genetic engineering application.

Identification and analysis of novel recessive alleles for Tan1 and Tan2 in sorghum.

The identification and analysis of allelic variation are important bases for crop diversity research, trait domestication and molecular marker development. Grain tannin content is a very important quality trait in sorghum. Higher tannin levels in sorghum grains are usually required when breeding varieties resistant to bird damage or those used for brewing liquor. Non-tannin-producing or low-tannin-producing sorghum accessions are commonly used for food and forage. Tan1 and Tan2, two important cloned genes, regulate tannin biosynthesis in sorghum, and mutations in one or two genes will result in low or no tannin content in sorghum grains. Even if sorghum accessions contain dominant Tan1 and Tan2, the tannin contents are distributed from low to high, and there must be other new alleles of the known regulatory genes or new unknown genes contributing to tannin production. The two parents 8R306 and 8R191 did not have any known recessive alleles for Tan1 and Tan2, and it was speculated that they probably both had dominant Tan1 and Tan2 genotypes. However, the phenotypes of two parents were different; 8R306 had tannins and 8R191 had non-tannins in the grains, so these two parents were constructed as a RIL population. Bulked segregant analysis (BSA) was used to determine other new alleles of Tan1 and Tan2 or new Tannin locus. Tan1 and Tan2 full-length sequences and tannin contents were detected in wild sorghum resources, landraces and cultivars. We identified two novel recessive tan1-d and tan1-e alleles and four recessive Tan2 alleles, named as tan2-d, tan2-e, tan2-f, and tan2-g. These recessive alleles led to loss of function of Tan1 and Tan2, and low or no tannin content in sorghum grains. The loss-of-function alleles of tan1-e and tan2-e were only found in Chinese landraces, and other alleles were found in landraces and cultivars grown all around the world. tan1-a and tan1-b were detected in foreign landraces, Chinese cultivars and foreign cultivars, but not in Chinese landraces. These results implied that Tan1 and Tan2 recessive alleles had different geographically distribution in the worldwide, but not all recessive alleles had been used in breeding. The discovery of these new alleles provided new germplasm resources for breeding sorghum cultivars for food and feed, and for developing molecular markers for low-tannin or non-tannin cultivar-assisted breeding in sorghum.

Genetic Mapping for Leaf Shape and Leaf Size in Non-Heading Chinese Cabbage by a RIL Population

Leaves are the predominant photosynthetic and edible organs in non-heading Chinese cabbage (Brassica campestris ssp. chinensis, NHCC), contributing significantly to yield, appearance, and desirability to consumers. However, the genetic basis of leaf shape and size in non-heading Chinese cabbage remains unclear. In this study, we developed a RIL population using ‘Maertou’, with slender leaves and narrow petioles, and ‘Suzhouqing’, with oval leaves and wide petioles, to construct a genetic linkage map and detect QTLs. To obtain stable and reliable QTLs, the 11 leaf-related traits, including the leaf length, leaf width, and fresh weight of the lamina and petiole and the thickness of petiole was observed on two locations—while the leaf shape, petiole shape, index of lamina/petiole length, and index of petiole fresh weight were calculated based on 7 leaf-related traits. QTL mapping illustrated that a total of 27 QTLs for leaf-related traits were preliminarily detected. The candidate genes were annotated and several genes involved in leaf development and leaf shape appeared in the overlapping regions of multiple loci, such as KRP2, GRF4, ARGOS, and SAUR9. This study lays the foundation for further exploration of the genetic mechanisms and development of effective molecular markers for leaf shape and size in NHCC.

QTL mapping for heading date and plant height using a RIL population in rice in different photoperiod environments

QTL mapping for heading date and plant height using a RIL population in rice in different photoperiod environments