Construction of a high-density genetic map by specific locus amplified fragment sequencing (SLAF-seq) and its application to Quantitative Trait Loci (QTL) analysis for boll weight in upland cotton (Gossypium hirsutum.)

Drought response revealed by chromatin organization variation and transcriptional regulation in cotton

BACKGROUND

Cotton is a major world cash crop and an important source of natural fiber, oil, and protein. Drought stress is becoming a restrictive factor affecting cotton production. To facilitate the development of drought-tolerant cotton varieties, it is necessary to study the molecular mechanism of drought stress response by exploring key drought-resistant genes and related regulatory factors.

RESULTS

In this study, two cotton varieties, ZY007 (drought-sensitive) and ZY168 (drought-tolerant), showing obvious phenotypic differences under drought stress, were selected. A total of 25,898 drought-induced genes were identified, exhibiting significant enrichment in pathways related to plant stress responses. Under drought induction, At subgenome expression bias was observed at the whole-genome level, which may be due to stronger inhibition of Dt subgenome expression. A gene co-expression module that was significantly associated with drought resistance was identified. About 90% of topologically associating domain (TAD) boundaries were stable, and 6613 TAD variation events were identified between the two varieties under drought. We identified 92 genes in ZY007 and 98 in ZY168 related to chromatin 3D structural variation and induced by drought stress. These genes are closely linked to the cotton response to drought stress through canonical hormone-responsive pathways, modulation of kinase and phosphatase activities, facilitation of calcium ion transport, and other related molecular mechanisms.

CONCLUSIONS

These results lay a foundation for elucidating the molecular mechanism of the cotton drought response and provide important regulatory locus and gene resources for the future molecular breeding of drought-resistant cotton varieties.

An aldehyde dehydrogenase gene, GhALDH7B4_A06, positively regulates fiber strength in upland cotton (Gossypium hirsutum L.)

High fiber strength (FS) premium cotton has significant market demand. Consequently, enhancing FS is a major objective in breeding quality cotton. However, there is a notable lack of known functionally applicable genes that can be targeted for breeding. To address this issue, our study used specific length-amplified fragment sequencing combined with bulk segregant analysis to study FS trait in an F2 population. Subsequently, we integrated these results with previous quantitative trait locus mapping results regarding fiber quality, which used simple sequence repeat markers in F2, F2:3, and recombinant inbred line populations. We identified a stable quantitative trait locus qFSA06 associated with FS located on chromosome A06 (90.74-90.83 Mb). Within this interval, we cloned a gene, GhALDH7B4_A06, which harbored a critical mutation site in coding sequences that is distinct in the two parents of the tested cotton line. In the paternal parent Ji228, the gene is normal and referred to as GhALDH7B4_A06O; however, there is a nonsense mutation in the maternal parent Ji567 that results in premature termination of protein translation, and this gene is designated as truncated GhALDH7B4_A06S. Validation using recombinant inbred lines and gene expression analysis revealed that this mutation site is correlated with cotton FS. Virus-induced gene silencing of GhALDH7B4 in cotton caused significant decreases in FS and fiber micronaire. Conversely, GhALDH7B4_A06O overexpression in Arabidopsis boosted cell wall component contents in the stem. The findings of our study provide a candidate gene for improving cotton fiber quality through molecular breeding.

Genomic and co-expression network analyses reveal candidate genes for oil accumulation based on an introgression population in Upland cotton (Gossypium hirsutum)

KEY MESSAGE

Integrated QTL mapping and WGCNA condense the potential gene regulatory network involved in oil accumulation. A glycosyl hydrolases gene (GhHSD1) for oil biosynthesis was confirmed in Arabidopsis, which will provide useful knowledge to understand the functional mechanism of oil biosynthesis in cotton. Cotton is an economical source of edible oil for the food industry. The genetic mechanism that regulates oil biosynthesis in cottonseeds is essential for the genetic enhancement of oil content (OC). To explore the functional genomics of OC, this study utilized an interspecific backcross inbred line population to dissect the quantitative trait locus (QTL) interlinked with OC. In total, nine OC QTLs were identified, four of which were novel, and each QTL explained 3.62-34.73% of the phenotypic variation of OC. The comprehensive transcript profiling of developing cottonseeds revealed 3,646 core genes differentially expressed in both inbred parents. Functional enrichment analysis determined 43 genes were annotated with oil biosynthesis processes. Implementation of weighted gene co-expression network analysis showed that 803 differential genes had a significant correlation with the OC phenotype. Further integrated analysis identified seven important genes located in OC QTLs. Of which, the GhHSD1 gene located in stable QTL qOC-Dt3-1 exhibited the highest functional linkages with the other network genes. Phylogenetic analysis showed significant evolutionary differences in the HSD1 sequences between oilseed- and starch- crops. Furthermore, the overexpression of GhHSD1 in Arabidopsis yielded almost 6.78% higher seed oil. This study not only uncovers important genetic loci for oil accumulation in cottonseed, but also provides a set of new candidate genes that potentially influence the oil biosynthesis pathway in cottonseed.

Genetic dissection of lint percentage in short-season cotton using combined QTL mapping and RNA-seq

KEY MESSAGE

In total, 17 QTLs for lint percentage in short-season cotton, including three stable QTLs, were detected. Twenty-eight differentially expressed genes located within the stable QTLs were identified, and two genes were validated by qRT-PCR. The breeding and use of short-season cotton have significant values in addressing the question of occupying farmlands with either cotton or cereals. However, the fiber yields of short-season cotton varieties are significantly lower than those of middle- and late-maturing varieties. How to effectively improve the fiber yield of short-season cotton has become a focus of cotton research. Here, a high-density genetic map was constructed using genome resequencing and an RIL population generated from the hybridization of two short-season cotton accessions, Dong3 and Dong4. The map contained 4960 bin markers across the 26 cotton chromosomes and spanned 3971.08 cM, with an average distance of 0.80 cM between adjacent markers. Based on the genetic map, quantitative trait locus (QTL) mapping for lint percentage (LP, %), an important yield component trait, was performed. In total, 17 QTLs for LP, including three stable QTLs, qLP-A02, qLP-D04, and qLP-D12, were detected. Three out of 11 non-redundant QTLs overlapped with previously reported QTLs, whereas the other eight were novel QTLs. A total of 28 differentially expressed genes associated with the three stable QTLs were identified using RNA-seq of ovules and fibers at different seed developmental stages from the parental materials. The two genes, Ghir_A02G017640 and Ghir_A02G018500, may be related to LP as determined by further qRT-PCR validation. This study provides useful information for the genetic dissection of LP and promotes the molecular breeding of short-season cotton.

Construction of the first high-density genetic linkage map and QTL mapping of flavonoid and leaf-size related traits in Epimedium

BACKGROUND

Leaves are the main medicinal organ in Epimedium herbs, and leaf flavonoid content is an important criterion of Epimedium herbs. However, the underlying genes that regulate leaf size and flavonoid content are unclear, which limits the use of breeding for Epimedium development. This study focuses on QTL mapping of flavonoid and leaf-size related traits in Epimedium.

RESULTS

We constructed the first high-density genetic map (HDGM) using 109 F1 hybrids of Epimedium leptorrhizum and Epimedium sagittatum over three years (2019-2021). Using 5,271 single nucleotide polymorphism (SNP) markers, an HDGM with an overall distance of 2,366.07 cM and a mean gap of 0.612 cM was generated by utilizing genotyping by sequencing (GBS) technology. Every year for three years, 46 stable quantitative trait loci (QTLs) for leaf size and flavonoid contents were discovered, including 31 stable loci for Epimedin C (EC), one stable locus for total flavone content (TFC), 12 stable loci for leaf length (LL), and two stable loci for leaf area (LA). For flavonoid content and leaf size, the phenotypic variance explained for these loci varied between 4.00 and 16.80% and 14.95 and 17.34%, respectively.

CONCLUSIONS

Forty-six stable QTLs for leaf size and flavonoid content traits were repeatedly detected over three years. The HDGM and stable QTLs are laying the basis for breeding and gene investigation in Epimedium and will contribute to accelerating the identification of desirable genotypes for Epimedium breeding.

Lint percentage and boll weight QTLs in three excellent upland cotton (Gossypium hirsutum): ZR014121, CCRI60, and EZ60

BACKGROUND

Upland cotton (Gossypium hirsutum L.) is the most economically important species in the cotton genus (Gossypium spp.). Enhancing the cotton yield is a major goal in cotton breeding programs. Lint percentage (LP) and boll weight (BW) are the two most important components of cotton lint yield. The identification of stable and effective quantitative trait loci (QTLs) will aid the molecular breeding of cotton cultivars with high yield.

RESULTS

Genotyping by target sequencing (GBTS) and genome-wide association study (GWAS) with 3VmrMLM were used to identify LP and BW related QTLs from two recombinant inbred line (RIL) populations derived from high lint yield and fiber quality lines (ZR014121, CCRI60 and EZ60). The average call rate of a single locus was 94.35%, and the average call rate of an individual was 92.10% in GBTS. A total of 100 QTLs were identified; 22 of them were overlapping with the reported QTLs, and 78 were novel QTLs. Of the 100 QTLs, 51 QTLs were for LP, and they explained 0.29-9.96% of the phenotypic variation; 49 QTLs were for BW, and they explained 0.41-6.31% of the phenotypic variation. One QTL (qBW-E-A10-1, qBW-C-A10-1) was identified in both populations. Six key QTLs were identified in multiple-environments; three were for LP, and three were for BW. A total of 108 candidate genes were identified in the regions of the six key QTLs. Several candidate genes were positively related to the developments of LP and BW, such as genes involved in gene transcription, protein synthesis, calcium signaling, carbon metabolism, and biosynthesis of secondary metabolites. Seven major candidate genes were predicted to form a co-expression network. Six significantly highly expressed candidate genes of the six QTLs after anthesis were the key genes regulating LP and BW and affecting cotton yield formation.

CONCLUSIONS

A total of 100 stable QTLs for LP and BW in upland cotton were identified in this study; these QTLs could be used in cotton molecular breeding programs. Putative candidate genes of the six key QTLs were identified; this result provided clues for future studies on the mechanisms of LP and BW developments.

The CCCH-Type Zinc-Finger Protein GhC3H20 Enhances Salt Stress Tolerance in Arabidopsis thaliana and Cotton through ABA Signal Transduction Pathway

The CCCH zinc-finger protein contains a typical C3H-type motif widely existing in plants, and it plays an important role in plant growth, development, and stress responses. In this study, a CCCH zinc-finger gene, GhC3H20, was isolated and thoroughly characterized to regulate salt stress in cotton and Arabidopsis. The expression of GhC3H20 was up-regulated under salt, drought, and ABA treatments. GUS activity was detected in the root, stem, leaves, and flowers of ProGhC3H20::GUS transgenic Arabidopsis. Compared with the control, the GUS activity of ProGhC3H20::GUS transgenic Arabidopsis seedlings under NaCl treatment was stronger. Through the genetic transformation of Arabidopsis, three transgenic lines of 35S-GhC3H20 were obtained. Under NaCl and mannitol treatments, the roots of the transgenic lines were significantly longer than those of the wild-type (WT) Arabidopsis. The leaves of the WT turned yellow and wilted under high-concentration salt treatment at the seedling stage, while the leaves of the transgenic Arabidopsis lines did not. Further investigation showed that compared with the WT, the content of catalase (CAT) in the leaves of the transgenic lines was significantly higher. Therefore, compared with the WT, overexpression of GhC3H20 enhanced the salt stress tolerance of transgenic Arabidopsis. A virus-induced gene silencing (VIGS) experiment showed that compared with the control, the leaves of pYL156-GhC3H20 plants were wilted and dehydrated. The content of chlorophyll in pYL156-GhC3H20 leaves was significantly lower than those of the control. Therefore, silencing of GhC3H20 reduced salt stress tolerance in cotton. Two interacting proteins (GhPP2CA and GhHAB1) of GhC3H20 have been identified through a yeast two-hybrid assay. The expression levels of PP2CA and HAB1 in transgenic Arabidopsis were higher than those in the WT, and pYL156-GhC3H20 had expression levels lower than those in the control. GhPP2CA and GhHAB1 are the key genes involved in the ABA signaling pathway. Taken together, our findings demonstrate that GhC3H20 may interact with GhPP2CA and GhHAB1 to participate in the ABA signaling pathway to enhance salt stress tolerance in cotton.

Quantitative trait locus mapping and identification of candidate genes for resistance to Verticillium wilt in four recombinant inbred line populations of Gossypium hirsutum

Improving resistance to Verticillium wilt is of great significance for achieving high and stable yields of Upland cotton (Gossypium hirsutum). To deeply understand the genetic basis of cotton resistance to Verticillium wilt, Verticillium wilt-resistant Upland Lumianyan 28 and four Verticillium wilt-susceptible Acala cotton cultivars were used to create four recombinant inbred line (RIL) populations of 469 families through nested hybridization. Phenotypic data collected in five stressful environments were used to select resistant and sensitive lines and create a mixed pool of extreme phenotypes for BSA-seq. A total of 8 QTLs associated with Verticillium wilt resistance were identified on 4 chromosomes, of which qVW-A12-5 was detected simultaneously in the RIL populations and in one of the RIL populations and was identified for the first time. According to the sequence comparison and transcriptome analysis of candidate genes in the QTL interval between parents and pools, 4 genes were identified in the qVW-A12-5 interval. qRT-PCR of parental and phenotypically extreme lines revealed that Gh_CPR30 was induced by and may be a candidate gene for resistance to Verticillium wilt in G. hirsutum. Furthermore, VIGS technology revealed that the disease severity index (DSI) of the Gh_CPR30-silenced plants was significantly higher than that of the control. These results indicate that the Gh_CPR30 gene plays an important role in the resistance of G. hirsutum to Verticillium wilt, and the study provides a molecular basis for analyzing the molecular mechanism underlying G. hirsutum resistance to Verticillium wilt.

Construction of a high-resolution genetic map and identification of single nucleotide polymorphism markers relevant to flower stalk height in onion

INTRODUCTION

Onion (Allium cepa L., 2n=16) is an economically and nutritionally important vegetable crop worldwide. Construction of a high-resolution genetic map and map-based gene mining in onion have lagged behind other vegetable crops such as tomato and pepper.

METHODS

In this study, we constructed a high-resolution genetic map of onion using 321 F2 individuals from a cross between two double haploid lines DH-1×DH-17 and employing specific length amplified fragment (SLAF)-seq technology. The genetic map containing 10,584 polymorphic SLAFs with 21,250 single nucleotide polymorphism (SNP) markers and 8 linkage groups was developed for onion, which spanned 928.32 cM, with an average distance of 0.09 cM between adjacent markers.

RESULTS

Using this map, we carried out QTL mapping of Ms locus related to the male-fertile trait and reproduced previous mapping results, which proved that this map was of good quality. Then, four QTLs (located on LG2, LG5, and LG8) were detected for flower stalk height, explaining 26.60% of the phenotypic variance. Among them, we proposed that 20 SLAF markers (in three QTLs) of flower stalk height trait were effective favorable allelic variant markers associated with heterosis.

DISCUSSION

Overall, the genetic map was structured using SLAF-seq based on DH lines, and it is the highest-quality and highest-resolution linkage map of onion to date. It lays a foundation for the fine mapping and candidate gene identification of flower stalk height, and provides new insights into the developmental genetic mechanisms in onion breeding.

Expressed genes and their new alleles identification during fibre elongation reveal the genetic factors underlying improvements of fibre length in cotton

Interspecific breeding in cotton takes advantage of genetic recombination among desirable genes from different parental lines. However, the expression new alleles (ENAs) from crossovers within genic regions and their significance in fibre length (FL) improvement are currently not understood. Here, we generated resequencing genomes of 191 interspecific backcross inbred lines derived from CRI36 (Gossypium hirsutum) × Hai7124 (Gossypium barbadense) and 277 dynamic fibre transcriptomes to identify the ENAs and extremely expressed genes (eGenes) potentially influencing FL, and uncovered the dynamic regulatory network of fibre elongation. Of 35 420 eGenes in developing fibres, 10 366 ENAs were identified and preferentially distributed in chromosomes subtelomeric regions. In total, 1056-1255 ENAs showed transgressive expression in fibres at 5-15 dpa (days post-anthesis) of some BILs, 520 of which were located in FL-quantitative trait locus (QTLs) and GhFLA9 (recombination allele) was identified with a larger effect for FL than GhFLA9 of CRI36 allele. Using ENAs as a type of markers, we identified three novel FL-QTLs. Additionally, 456 extremely eGenes were identified that were preferentially distributed in recombination hotspots. Importantly, 34 of them were significantly associated with FL. Gene expression quantitative trait locus analysis identified 1286, 1089 and 1059 eGenes that were colocalized with the FL trait at 5, 10 and 15 dpa, respectively. Finally, we verified the Ghir_D10G011050 gene linked to fibre elongation by the CRISPR-cas9 system. This study provides the first glimpse into the occurrence, distribution and expression of the developing fibres genes (especially ENAs) in an introgression population, and their possible biological significance in FL.

Detection of Stable Elite Haplotypes and Potential Candidate Genes of Boll Weight Across Multiple Environments via GWAS in Upland Cotton

Boll weight (BW) is a key determinant of yield component traits in cotton, and understanding the genetic mechanism of BW could contribute to the progress of cotton fiber yield. Although many yield-related quantitative trait loci (QTLs) responsible for BW have been determined, knowledge of the genes controlling cotton yield remains limited. Here, association mapping based on 25,169 single-nucleotide polymorphisms (SNPs) and 2,315 insertions/deletions (InDels) was conducted to identify high-quality QTLs responsible for BW in a global collection of 290 diverse accessions, and BW was measured in nine different environments. A total of 19 significant markers were detected, and 225 candidate genes within a 400 kb region (± 200 kb surrounding each locus) were predicted. Of them, two major QTLs with highly phenotypic variation explanation on chromosomes A08 and D13 were identified among multiple environments. Furthermore, we found that two novel candidate genes (Ghir_A08G009110 and Ghir_D13G023010) were associated with BW and that Ghir_D13G023010 was involved in artificial selection during cotton breeding by population genetic analysis. The transcription level analyses showed that these two genes were significantly differentially expressed between high-BW accession and low-BW accession during the ovule development stage. Thus, these results reveal valuable information for clarifying the genetic basics of the control of BW, which are useful for increasing yield by molecular marker-assisted selection (MAS) breeding in cotton.

QTL mapping for growth-related traits by constructing the first genetic linkage map in Simao pine

BACKGROUND

Simao pine is one of the primary economic tree species for resin and timber production in southwest China. The exploitation and utilization of Simao pine are constrained by the relatively lacking of genetic information. Construction a fine genetic linkage map and detecting quantitative trait locis (QTLs) for growth-related traits is a prerequisite section of Simao Pine's molecular breeding program.

RESULTS

In our study, a high-resolution Simao pine genetic map employed specific locus amplified fragment sequencing (SLAF-seq) technology and based on an F₁ pseudo-testcross population has been constructed. There were 11,544 SNPs assigned to 12 linkage groups (LGs), and the total length of the map was 2,062.85 cM with a mean distance of 0.37 cM between markers. According to the phenotypic variation analysis for three consecutive years, a total of seventeen QTLs for four traits were detected. Among 17 QTLs, there were six for plant height (Dh.16.1, Dh16.2, Dh17.1, Dh18.1-3), five for basal diameter (Dbd.17.1-5), four for needle length (Dnl17.1-3, Dnl18.1) and two for needle diameter (Dnd17.1 and Dnd18.1) respectively. These QTLs individually explained phenotypic variance from 11.0-16.3%, and the logarithm of odds (LOD) value ranged from 2.52 to 3.87.

CONCLUSIONS

In our study, a fine genetic map of Simao pine applied the technology of SLAF-seq has been constructed for the first time. Based on the map, a total of 17 QTLs for four growth-related traits were identified. It provides helpful information for genomic studies and marker-assisted selection (MAS) in Simao pine.

Quantitative Trait Loci and Transcriptome Analysis Reveal Genetic Basis of Fiber Quality Traits in CCRI70 RIL Population of Gossypium hirsutum

Upland cotton (Gossypium hirsutum) is widely planted around the world for its natural fiber, and producing high-quality fiber is essential for the textile industry. CCRI70 is a hybrid cotton plant harboring superior yield and fiber quality, whose recombinant inbred line (RIL) population was developed from two upland cotton varieties (sGK156 and 901-001) and were used here to investigate the source of high-quality related alleles. Based on the material of the whole population, a high-density genetic map was constructed using specific locus-amplified fragment sequencing (SLAF-seq). It contained 24,425 single nucleotide polymorphism (SNP) markers, spanning a distance of 4,850.47 centimorgans (cM) over 26 chromosomes with an average marker interval of 0.20 cM. In evaluating three fiber quality traits in nine environments to detect multiple environments stable quantitative trait loci (QTLs), we found 289 QTLs, of which 36 of them were stable QTLs and 18 were novel. Based on the transcriptome analysis for two parents and two RILs, 24,941 unique differentially expressed genes (DEGs) were identified, 473 of which were promising genes. For the fiber strength (FS) QTLs, 320 DEGs were identified, suggesting that pectin synthesis, phenylpropanoid biosynthesis, and plant hormone signaling pathways could influence FS, and several transcription factors may regulate fiber development, such as GAE6, C4H, OMT1, AFR18, EIN3, bZIP44, and GAI. Notably, the marker D13_56413025 in qFS-chr18-4 provides a potential basis for enhancing fiber quality of upland cotton via marker-assisted breeding and gene cloning of important fiber quality traits.

GBS-SNP and SSR based genetic mapping and QTL analysis for drought tolerance in upland cotton

A recombinant inbred line mapping population of intra-species upland cotton was generated from a cross between the drought-tolerant female parent (AS2) and the susceptible male parent (MCU13). A linkage map was constructed deploying 1,116 GBS-based SNPs and public domain-based 782 SSRs spanning a total genetic distance of 28,083.03 cM with an average chromosomal span length of 1,080.12 cM with inter-marker distance of 10.19 cM.A total of 19 quantitative trait loci (QTLs) were identified in nine chromosomes for field drought tolerance traits. Chromosomes 3 and 8 harbored important drought tolerant QTLs for chlorophyll stability index trait while for relative water content trait, three QTLs on chromosome 8 and one QTL each on chromosome 4, 12 were identified. One QTL on each chromosome 8, 5, and 7, and two QTLs on chromosome 15 linking to proline content were identified. For the nitrate reductase activity trait, two QTLs were identified on chromosome 3 and one on each chromosome 8, 13, and 26. To complement our QTL study, a meta-analysis was conducted along with the public domain database and resulted in a consensus map for chromosome 8. Under field drought stress, chromosome 8 harbored a drought tolerance QTL hotspot with two in-house QTLs for chlorophyll stability index (qCSI01, qCSI02) and three public domain QTLs (qLP.FDT_1, qLP.FDT_2, qCC.ST_3). Identified QTL hotspot on chromosome 8 could play a crucial role in exploring abiotic stress-associated genes/alleles for drought trait improvement.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01041-y.

Genome-wide association mapping for agronomic traits in an 8-way Upland cotton MAGIC population by SLAF-seq

One sub-MAGIC population was genotyped using SLAF-seq, and QTLs and candidate genes for agronomic traits were identified in Upland cotton. The agronomic traits of Upland cotton have serious impacts on cotton production, as well as economic benefits. To discover the genetic basis of important agronomic traits in Upland cotton, a subset MAGIC (multi-parent advanced generation inter-cross) population containing 372 lines (SMLs) was selected from an 8-way MAGIC population with 960 lines. The 372 lines and 8 parents were phenotyped in six environments and deeply genotyped by SLAF-seq with 60,495 polymorphic SNPs. The genetic diversity indexes of all SNPs were 0.324 and 0.362 for the parents and MAGIC lines, respectively. The LD decay distance of the SMLs was 600 kb (r² = 0.1). Genome-wide association mapping was performed using 60,495 SNPs and the phenotypic data of the SMLs, and 177 SNPs were identified to be significantly associated with 9 stable agronomic traits in multiple environments. The identified SNPs were divided into 117 QTLs (quantitative trait loci) by LD decay distance, explaining 5.44% to 31.64% of the phenotypic variation. Among the 117 QTLs, 3 QTLs were stable in multiple environments, and 11 QTL regions were proven to have pleiotropism associated with multiple traits. Within QTL regions, 154 genes were preferentially expressed in correlated tissues, and 8 genes with known functions were identified as priori candidate genes. Two genes, GhACT1 and GhGASL3, reported to have clear functions, were, respectively, located in qFE-A05-4 and qFE-D04-3, two stable QTLs for FE. This study revealed the genetic basis of important agronomic traits of Upland cotton, and the results will facilitate molecular breeding in cotton.

Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

BACKGROUND

Spinach (Spinacia oleracea L.) is an important leafy vegetable crop, and leaf-related traits including leaf length, leaf width, and petiole length, are important commercial traits. However, the underlying genes remain unclear. The objective of the study was to conduct QTL mapping of leaf-related traits in spinach.

RESULTS

A BC₁ population was used to construct the linkage map and for QTL mapping of leaf length, leaf width, petiole length, and the ratio of leaf length to width in 2015 and 2019. Two genetic linkage maps were constructed by specific locus amplified fragment sequencing (SLAF-seq), and kompetitive allele specific PCR (KASP) technology, respectively using BC₁ population in 2015. Based on the results of 2015, the specific linkage groups (LG) detected QTLs were generated using BC₁ population in 2019. A total of 13 QTLs were detected for leaf-related traits, only five QTLs being repeatedly detected in multiple years or linkage maps. Interestingly, the major QTLs of leaf length, petiole length, and the ratio of leaf length to width were highly associated with the same SNP markers (KM3102838, KM1360385 and KM2191098). A major QTL of leaf width was mapped on chromosome 1 from 41.470-42.045 Mb. And 44 genes were identified within the region. Based on the GO analysis, these genes were significantly enriched on ribonuclease, lyase activity, phosphodiester bond hydrolysis process, and cell wall component, thus it might change cell size to determine leaves shape.

CONCLUSIONS

Five QTLs for leaf-related traits were repeatedly detected at least two years or linkage maps. The major QTLs of leaf length, petiole length, and the ratio of leaf length to width were mapped on the same loci. And three genes (Spo10792, Spo21018, and Spo21019) were identified as important candidate genes for leaf width.

Genome-wide association analysis reveals quantitative trait loci and candidate genes involved in yield components under multiple field environments in cotton (Gossypium hirsutum)

BACKGROUND

Numerous quantitative trait loci (QTLs) and candidate genes associated with yield-related traits have been identified in cotton by genome-wide association study (GWAS) analysis. However, most of the phenotypic data were from a single or few environments, and the stable loci remained to be validated under multiple field environments.

RESULTS

Here, 242 upland cotton accessions collected from different origins were continuously investigated for phenotypic data of four main yield components, including boll weight (BW) and lint percentage (LP) under 13 field environments, and boll number per plant (BN) and seed index (SI) under 11 environments. Correlation analysis revealed a positive correlation between BN and LP, BW and SI, while SI had a negative correlation with LP and BN. Genetic analysis indicated that LP had the highest heritability estimates of 94.97%, followed by 92.08% for SI, 86.09% for BW, and 72.92% for BN, indicating LP and SI were more suitable traits for genetic improvement. Based on 56,010 high-quality single nucleotide polymorphisms (SNPs) and GWAS analysis, a total of 95 non-redundant QTLs were identified, including 12 of BN, 23 of BW, 45 of LP, and 33 of SI, respectively. Of them, 10 pairs of homologous QTLs were detected between A and D sub-genomes. We also found that 15 co-located QTLs with more than two traits and 12 high-confidence QTLs were detected under more than six environments, respectively. Further, two NET genes (GH_A08G0716 and GH_A08G0783), located in a novel QTL hotspot (qtl24, qtl25 and qlt26) were predominately expressed in early fiber development stages, exhibited significant correlation with LP and SI. The GH_A07G1389 in the stable qtl19 region encoded a tetratricopeptide repeat (TPR)-like superfamily protein and was a homologous gene involved in short fiber mutant ligon lintless-y (Li_y), implying important roles in cotton yield.

CONCLUSIONS

The present study provides a foundation for understanding the regulatory mechanisms of yield components and may enhance yield improvement through molecular breeding in cotton.

Potential interaction between autophagy and auxin during maize leaf senescence

Leaf senescence is important for crop yield as delaying it can increase the average yield. In this study, population genetics and transcriptomic profiling were combined to dissect its genetic basis in maize. To do this, the progenies of an elite maize hybrid Jidan27 and its parental lines Si-287 (early senescence) and Si-144 (stay-green), as well as 173 maize inbred lines were used. We identified two novel loci and their candidate genes, Stg3 (ZmATG18b) and Stg7 (ZmGH3.8), which are predicted to be members of autophagy and auxin pathways, respectively. Genomic variations in the promoter regions of these two genes were detected, and four allelic combinations existed in the examined maize inbred lines. The Stg3Si-144/Stg7Si-144 allelic combination with lower ZmATG18b expression and higher ZmGH3.8 expression could distinctively delay leaf senescence, increase ear weight and the improved hybrid of NIL-Stg3Si-144/Stg7Si-144 × Si-144 significantly reduced ear weight loss under drought stress, while opposite effects were observed in the Stg3Si-287/Stg7Si-287 combination with a higher ZmATG18b expression and lower ZmGH3.8 expression. Thus, we identify a potential interaction between autophagy and auxin which could modulate the timing of maize leaf senescence.

SNP detection and population structure evaluation of Salix gordejevii Y. L. Chang et Skv. in Hunshandake Sandland, Inner Mongolia, China

Single nucleotide polymorphisms (SNPs) are the most abundant and richest form of genomic polymorphism and, hence, are highly favorable markers for genetic map construction and genome-wide association studies. Based on the DNA specific-locus amplified fragment sequencing (SLAF-seq) for large-scale SNP detection, the genetic diversity and population structure of Salix gordejevii Y. L. Chang et Skv., a valuable sand-fixing shrub, was assessed in 199 accessions from 20 populations in Hunshandake Sandland of northern China. A total of 623.15 M reads resulted in 30.49 × sequencing depth on average and a mean Q30 of 95.70%, and 2,287,715 SNPs in 178,509 polymorphic SLAF tags were obtained. By discarding minor allele frequency > 0.05 and integrity > 0.8, a total of 93,600 SNPs were retained for population genetic analyses, which revealed that 199 individuals could be divided into six groups based on cross-validation errors. However, this grouping pattern did not match the geographical distribution, indicating that there is no apparent geographic barrier in the blank areas where S. gordejevii was not distributed in Hunshandake Sandland. In addition, the physical distance of linkage disequilibrium decay in the analyzed S. gordejevii individuals was 18.5 kb when r ² = 0.1. The linkage disequilibrium decay distances for different chromosomes varied from 4.6 kb (chromosome 16) to 37.8 kb (chromosome 3). The obtained SNPs offer suitable marker resources for further genetic and genomic studies and will benefit S. gordejevii breeding programs.

Mapping of a major QTL controlling plant height using a high-density genetic map and QTL-seq methods based on whole-genome resequencing in Brassica napus

Plant height is a crucial element related to plant architecture that influences the seed yield of oilseed rape (Brassica napus L.). In this study, we isolated a natural B. napus mutant, namely a semi-dwarf mutant (sdw-e), which exhibits a 30% reduction in plant height compared with Zhongshuang 11-HP (ZS11-HP). Quantitative trait locus sequencing (QTL-seq) was conducted using two extreme DNA bulks in F₂ populations in Wuchang-2017 derived from ZS11-HP × sdw-e to identify QTLs associated with plant height. The result suggested that two QTL intervals were located on chromosome A10. The F₂ population consisting of 200 individuals in Yangluo-2018 derived from ZS11-HP × sdw-e was used to construct a high-density linkage map using whole-genome resequencing. The high-density linkage map harbored 4323 bin markers and covered a total distance of 2026.52 cM with an average marker interval of 0.47 cM. The major QTL for plant height named qPHA10 was identified on linkage group A10 by interval mapping and composite interval mapping methods. The major QTL qPHA10 was highly consistent with the QTL-seq results. And then, we integrated the variation sites and expression levels of genes in the major QTL interval to predict the candidate genes. Thus, the identified QTL and candidate genes could be used in marker-assisted selection for B. napus breeding in the future.

Specific-Locus Amplified Fragment Sequencing (SLAF-Seq) as High-Throughput SNP Genotyping Methods

Most plant agronomic traits are quantitatively inherited. Identification of quantitative trait loci (QTL) is a challenging target for most scientists and crop breeders as large-scale genotyping is difficult. Molecular marker technology has continuously evolved from hybridization-based technology to PCR-based technology, and finally, sequencing-based high-throughput single-nucleotide polymorphisms (SNPs). High-throughput sequencing technologies can provide strategies for sequence-based SNP genotyping. Here we describe the SLAF-seq that can be applied as the SNP genotyping approach. The high-throughput SNP genotyping methods will prove useful for the construction of high-density genetic maps and identification of QTLs for their deployment in plant breeding and facilitate genome-wide selection (GWS) and genome-wide association studies (GWAS).

Identification and Functional Verification of Cold Tolerance Genes in Spring Maize Seedlings Based on a Genome-Wide Association Study and Quantitative Trait Locus Mapping

Maize (Zea mays L.) is a tropical crop, and low temperature has become one of the main abiotic stresses for maize growth and development, affecting many maize growth processes. The main area of maize production in China, Jilin province, often suffers from varying degrees of cold damage in spring, which seriously affects the quality and yield of maize. In the face of global climate change and food security concerns, discovering cold tolerance genes, developing cold tolerance molecular markers, and creating cold-tolerant germplasm have become urgent for improving maize resilience against these conditions and obtaining an increase in overall yield. In this study, whole-genome sequencing and genotyping by sequencing were used to perform genome-wide association analysis (GWAS) and quantitative trait locus (QTL) mapping of the two populations, respectively. Overall, four single-nucleotide polymorphisms (SNPs) and 12 QTLs were found to be significantly associated with cold tolerance. Through joint analysis, an intersection of GWAS and QTL mapping was found on chromosome 3, on which the Zm00001d002729 gene was identified as a potential factor in cold tolerance. We verified the function of this target gene through overexpression, suppression of expression, and genetic transformation into maize. We found that Zm00001d002729 overexpression resulted in better cold tolerance in this crop. The identification of genes associated with cold tolerance contributes to the clarification of the underlying mechanism of this trait in maize and provides a foundation for the adaptation of maize to colder environments in the future, to ensure food security.

Quantitative Trait Locus Analysis and Identification of Candidate Genes for Micronaire in an Interspecific Backcross Inbred Line Population of Gossypium hirsutum × Gossypium barbadense

Cotton is the most important fiber crop and provides indispensable natural fibers for the textile industry. Micronaire (MIC) is determined by fiber fineness and maturity and is an important component of fiber quality. Gossypium barbadense L. possesses long, strong and fine fibers, while upland cotton (Gossypium hirsutum L.) is high yielding with high MIC and widely cultivated worldwide. To identify quantitative trait loci (QTLs) and candidate genes for MIC in G. barbadense, a population of 250 backcross inbred lines (BILs), developed from an interspecific cross of upland cotton CRI36 × Egyptian cotton (G. barbadense) Hai7124, was evaluated in 9 replicated field tests. Based on a high-density genetic map with 7709 genotyping-by-sequencing (GBS)-based single-nucleotide polymorphism (SNP) markers, 25 MIC QTLs were identified, including 12 previously described QTLs and 13 new QTLs. Importantly, two stable MIC QTLs (qMIC-D03-2 on D03 and qMIC-D08-1 on D08) were identified. Of a total of 338 genes identified within the two QTL regions, eight candidate genes with differential expression between TM-1 and Hai7124 were identified. Our research provides valuable information for improving MIC in cotton breeding.

Identification and Validation of New Stable QTLs for Grain Weight and Size by Multiple Mapping Models in Common Wheat

Improvement of grain weight and size is an important objective for high-yield wheat breeding. In this study, 174 recombinant inbred lines (RILs) derived from the cross between Jing 411 and Hongmangchun 21 were used to construct a high-density genetic map by specific locus amplified fragment sequencing (SLAF-seq). Three mapping methods, including inclusive composite interval mapping (ICIM), genome-wide composite interval mapping (GCIM), and a mixed linear model performed with forward-backward stepwise (NWIM), were used to identify QTLs for thousand grain weight (TGW), grain width (GW), and grain length (GL). In total, we identified 30, 15, and 18 putative QTLs for TGW, GW, and GL that explain 1.1-33.9%, 3.1%-34.2%, and 1.7%-22.8% of the phenotypic variances, respectively. Among these, 19 (63.3%) QTLs for TGW, 10 (66.7%) for GW, and 7 (38.9%) for GL were consistent with those identified by genome-wide association analysis in 192 wheat varieties. Five new stable QTLs, including 3 for TGW (Qtgw.ahau-1B.1, Qtgw.ahau-4B.1, and Qtgw.ahau-4B.2) and 2 for GL (Qgl.ahau-2A.1 and Qgl.ahau-7A.2), were detected by the three aforementioned mapping methods across environments. Subsequently, five cleaved amplified polymorphic sequence (CAPS) markers corresponding to these QTLs were developed and validated in 180 Chinese mini-core wheat accessions. In addition, 19 potential candidate genes for Qtgw.ahau-4B.2 in a 0.31-Mb physical interval were further annotated, of which TraesCS4B02G376400 and TraesCS4B02G376800 encode a plasma membrane H+-ATPase and a serine/threonine-protein kinase, respectively. These new QTLs and CAPS markers will be useful for further marker-assisted selection and map-based cloning of target genes.

Construction of a high-density SNP-based genetic map and identification of fruit-related QTLs and candidate genes in peach [Prunus persica (L.) Batsch]

BACKGROUND

High-density genetic mapping is a valuable tool for mapping loci that control specific traits for perennial fruit trees. Peach is an economically important fruit tree and a model Rosaceae species for genomic and genetic research. In peach, even though many molecular markers, genetic maps and QTL mappings have been reported, further research on the improvement of marker numbers, map densities, QTL accuracy and candidate gene identification is still warranted.

RESULTS

A high-density single nucleotide polymorphism (SNP)-based peach linkage map was constructed using specific locus amplified fragment sequencing (SLAF-seq). This genetic map consisted of 7998 SLAF markers, spanning 1098.79 cM with an average distance of 0.17 cM between adjacent markers. A total of 40 QTLs and 885 annotated candidate genes were detected for 10 fruit-related traits, including fruit weight (FW), fruit diameter (FD), percentage of red skin colour (PSC), eating quality (EQ), fruit flavour (FV), red in flesh (RF), red around pit (RP), adherence to pit (AP), fruit development period (FDP) and fruit fibre content (FFC). Eighteen QTLs for soluble solid content (SSC) were identified along LGs 1, 4, 5, and 6 in 2015 and 2016, and 540 genes were annotated in QTL intervals. Thirty-two QTLs for fruit acidity content (FA) were detected on LG1, and 2, 4, 5, 6, and 1232 candidate genes were identified. The expression profiles of 2 candidate genes for SSC and 4 for FA were analysed in parents and their offspring.

CONCLUSIONS

We constructed a high-density genetic map in peach based on SLAF-seq, which may contribute to the identification of important agronomic trait loci. Ninety QTLs for 12 fruit-related traits were identified, most of which overlapped with previous reports, and some new QTLs were obtained. A large number of candidate genes for fruit-related traits were screened and identified. These results may improve our understanding of the genetic control of fruit quality traits and provide useful information in marker-assisted selection for fruit quality in peach breeding programmes.

Novel stable QTLs identification for berry quality traits based on high-density genetic linkage map construction in table grape

BACKGROUND

Aroma, berry firmness and berry shape are three main quality traits in table grape production, and also the important target traits in grapevine breeding. However, the information about their genetic mechanisms is limited, which results in low accuracy and efficiency of quality breeding in grapevine. Mapping and isolation of quantitative trait locus (QTLs) based on the construction of genetic linkage map is a powerful approach to decipher the genetic determinants of complex quantitative traits.

RESULTS

In the present work, a final integrated map consisting of 3411 SLAF markers on 19 linkage groups (LGs) with an average distance of 0.98 cM between adjacent markers was generated using the specific length amplified fragment sequencing (SLAF-seq) technique. A total of 9 significant stable QTLs for Muscat flavor, berry firmness and berry shape were identified on two linkage groups among the hybrids analyzed over three consecutive years from 2016 to 2018. Notably, new stable QTLs for berry firmness and berry shape were found on LG 8 respectively for the first time. Based on biological function and expression profiles of candidate genes in the major QTL regions, 3 genes (VIT_08s0007g00440, VIT_08s0040g02740 and VIT_08s0040g02350) related to berry firmness and 3 genes (VIT_08s0032g01110, VIT_08s0032g01150 and VIT_08s0105g00200) linked to berry shape were highlighted. Overexpression of VIT_08s0032g01110 in transgenic Arabidopsis plants caused the change of pod shape.

CONCLUSIONS

A new high-density genetic map with total 3411 markers was constructed with SLAF-seq technique, and thus enabled the detection of narrow interval QTLs for relevant traits in grapevine. VIT_08s0007g00440, VIT_08s0040g02740 and VIT_08s0040g02350 were found to be related to berry firmness, while VIT_08s0032g01110, VIT_08s0032g01150 and VIT_08s0105g00200 were linked to berry shape.

QTL mapping and transcriptome analysis identify candidate genes regulating pericarp thickness in sweet corn

BACKGROUND

In recent years, the planting area of sweet corn in China has expanded rapidly. Some new varieties with high yields and good adaptabilities have emerged. However, the improvement of edible quality traits, especially through the development of varieties with thin pericarp thickness, has not been achieved to date. Pericarp thickness is a complex trait that is the key factor determining the edible quality of sweet corn. Genetic mapping combined with transcriptome analysis was used to identify candidate genes controlling pericarp thickness.

RESULTS

To identify novel quantitative trait loci (QTLs) for pericarp thickness, a sweet corn BC₄F₃ population of 148 lines was developed using the two sweet corn lines M03 (recurrent parent) and M08 (donor parent). Additionally, a high-density genetic linkage map containing 3876 specific length amplified fragment (SLAF) tags was constructed and used for mapping QTLs for pericarp thickness. Interestingly, 14 QTLs for pericarp thickness were detected, and one stable QTL (qPT10-5) was detected across multiple years, which explained 7.78-35.38% of the phenotypic variation located on chromosome 10 (144,631,242-145,532,401). Forty-two candidate genes were found within the target region of qPT10-5. Moreover, of these 42 genes, five genes (GRMZM2G143402, GRMZM2G143389, GRMZM2G143352, GRMZM6G287947, and AC234202.1_FG004) were differentially expressed between the two parents, as revealed by transcriptome analysis. According to the gene annotation information, three genes might be considered candidates for pericarp thickness. GRMZM2G143352 and GRMZM2G143402 have been annotated as AUX/IAA transcription factor and ZIM transcription factor, respectively, while GRMZM2G143389 has been annotated as FATTY ACID EXPORT 2, chloroplastic.

CONCLUSIONS

This study identified a major QTL and candidate genes that could accelerate breeding for the thin pericarp thickness variety of sweet corn, and these results established the basis for map-based cloning and further functional research.

Construction of a SNP-Based Genetic Map Using SLAF-Seq and QTL Analysis of Morphological Traits in Eggplant

Eggplant (Solanum melongena; 2n = 24) is an economically important fruit crop of the family Solanaceae that was domesticated in India and Southeast Asia. Construction of a high-resolution genetic map and map-based gene mining in eggplant have lagged behind other crops within the family such as tomato and potato. In this study, we conducted high-throughput single nucleotide polymorphism (SNP) discovery in the eggplant genome using specific length amplified fragment (SLAF) sequencing and constructed a high-density genetic map for the quantitative trait locus (QTL) analysis of multiple traits. An interspecific F2 population of 121 individuals was developed from the cross between cultivated eggplant "1836" and the wild relative S. linnaeanum "1809." Genomic DNA extracted from parental lines and the F2 population was subjected to high-throughput SLAF sequencing. A total of 111.74 Gb of data and 487.53 million pair-end reads were generated. A high-resolution genetic map containing 2,122 SNP markers and 12 linkage groups was developed for eggplant, which spanned 1530.75 cM, with an average distance of 0.72 cM between adjacent markers. A total of 19 QTLs were detected for stem height and fruit and leaf morphology traits of eggplant, explaining 4.08-55.23% of the phenotypic variance. These QTLs were distributed on nine linkage groups (LGs), but not on LG2, 4, and 9. The number of SNPs ranged from 2 to 11 within each QTL, and the genetic interval varied from 0.15 to 10.53 cM. Overall, the results establish a foundation for the fine mapping of complex QTLs, candidate gene identification, and marker-assisted selection of favorable alleles in eggplant breeding.

Identification of candidate genes for key fibre-related QTLs and derivation of favourable alleles in Gossypium hirsutum recombinant inbred lines with G. barbadense introgressions

Fine mapping QTLs and identifying candidate genes for cotton fibre-quality and yield traits would be beneficial to cotton breeding. Here, we constructed a high-density genetic map by specific-locus amplified fragment sequencing (SLAF-seq) to identify QTLs associated with fibre-quality and yield traits using 239 recombinant inbred lines (RILs), which was developed from LMY22 (a high-yield Gossypium hirsutumL. cultivar) × LY343 (a superior fibre-quality germplasm with G. barbadenseL. introgressions). The genetic map spanned 3426.57 cM, including 3556 SLAF-based SNPs and 199 SSR marker loci. A total of 104 QTLs, including 67 QTLs for fibre quality and 37 QTLs for yield traits, were identified with phenotypic data collected from 7 environments. Among these, 66 QTLs were co-located in 19 QTL clusters on 12 chromosomes, and 24 QTLs were detected in three or more environments and determined to be stable. We also investigated the genomic components of LY343 and their contributions to fibre-related traits by deep sequencing the whole genome of LY343, and we found that genomic components from G. hirsutum races (which entered LY343 via its G. barbadense parent) contributed more favourable alleles than those from G. barbadense. We further identified six putative candidate genes for stable QTLs, including Gh_A03G1147 (GhPEL6), Gh_D07G1598 (GhCSLC6) and Gh_D13G1921 (GhTBL5) for fibre-length QTLs and Gh_D03G0919 (GhCOBL4), Gh_D09G1659 (GhMYB4) and Gh_D09G1690 (GhMYB85) for lint-percentage QTLs. Our results provide comprehensive insight into the genetic basis of the formation of fibre-related traits and would be helpful for cloning fibre-development-related genes as well as for marker-assisted genetic improvement in cotton.

Construction of a High-Density Genetic Map and Mapping of Firmness in Grapes (Vitis vinifera L.) Based on Whole-Genome Resequencing

Berry firmness is one of the most important quality traits in table grapes. The underlying molecular and genetic mechanisms for berry firmness remain unclear. We constructed a high-density genetic map based on whole-genome resequencing to identify loci associated with berry firmness. The genetic map had 19 linkage groups, including 1662 bin markers (26,039 SNPs), covering 1463.38 cM, and the average inter-marker distance was 0.88 cM. An analysis of berry firmness in the F1 population and both parents for three consecutive years revealed continuous variability in F1, with a distribution close to the normal distribution. Based on the genetic map and phenotypic data, three potentially significant quantitative trait loci (QTLs) related to berry firmness were identified by composite interval mapping. The contribution rate of each QTL ranged from 21.5% to 28.6%. We identified four candidate genes associated with grape firmness, which are related to endoglucanase, abscisic acid (ABA), and transcription factors. A qRT-PCR analysis revealed that the expression of abscisic-aldehyde oxidase-like gene (VIT_18s0041g02410) and endoglucanase 3 gene (VIT_18s0089g00210) in Muscat Hamburg was higher than in Crimson Seedless at the veraison stage, which was consistent with that of parent berry firmness. These results confirmed that VIT_18s0041g02410 and VIT_18s0089g00210 are candidate genes associated with berry firmness.

Quantitative Trait Locus (QTLs) Mapping for Quality Traits of Wheat Based on High Density Genetic Map Combined With Bulked Segregant Analysis RNA-seq (BSR-Seq) Indicates That the Basic 7S Globulin Gene Is Related to Falling Number

Numerous quantitative trait loci (QTLs) have been identified for wheat quality; however, most are confined to low-density genetic maps. In this study, based on specific-locus amplified fragment sequencing (SLAF-seq), a high-density genetic map was constructed with 193 recombinant inbred lines derived from Chuanmai 42 and Chuanmai 39. In total, 30 QTLs with phenotypic variance explained (PVE) up to 47.99% were identified for falling number (FN), grain protein content (GPC), grain hardness (GH), and starch pasting properties across three environments. Five NAM genes closely adjacent to QGPC.cib-4A probably have effects on GPC. QGH.cib-5D was the only one detected for GH with high PVE of 33.31-47.99% across the three environments and was assumed to be related to the nearest pina-D1 and pinb-D1genes. Three QTLs were identified for FN in at least two environments, of which QFN.cib-3D had relatively higher PVE of 16.58-25.74%. The positive effect of QFN.cib-3D for high FN was verified in a double-haploid population derived from Chuanmai 42 × Kechengmai 4. The combination of these QTLs has a considerable effect on increasing FN. The transcript levels of Basic 7S globulin and Basic 7S globulin 2 in QFN.cib-3D were significantly different between low FN and high FN bulks, as observed through bulk segregant RNA-seq (BSR). These QTLs and candidate genes based on the high-density genetic map would be beneficial for further understanding of the genetic mechanism of quality traits and molecular breeding of wheat.

Introgression Leads to Genomic Divergence and Responsible for Important Traits in Upland Cotton

Understanding the genetic diversity and population structure of germplasms is essential when selecting parents for crop breeding. The genomic changes that occurred during the domestication and improvement of Upland cotton (Gossypium hirsutum) remains poorly understood. Besides, the available genetic resources from cotton cultivars are limited. By applying restriction site-associated DNA marker sequencing (RAD-seq) technology to 582 tetraploid cotton accessions, we confirmed distinct genomic regions on chromosomes A06 and A08 in Upland cotton cultivar subgroups. Based on the pedigree, reported QTLs, introgression analyses, and genome-wide association study (GWAS), we suggest that these divergent regions might have resulted from the introgression of exotic lineages of G. hirsutum landraces and their wild relatives. These regions were the typical genomic signatures that might be responsible for maturity and fiber quality on chromosome A06 and chromosome A08, respectively. Moreover, these genomic regions are located in the putative pericentromeric regions, implying that their application will be challenging. In the study, based on high-density SNP markers, we reported two genomic signatures on chromosomes A06 and A08, which might originate from the introgression events in the Upland cotton population. Our study provides new insights for understanding the impact of historic introgressions on population divergence and important agronomic traits of modern Upland cotton cultivars.

High-resolution mapping of a major and consensus quantitative trait locus for oil content to a ~ 0.8-Mb region on chromosome A08 in peanut (Arachis hypogaea L.)

KEY MESSAGE: ddRAD-seq-based high-density genetic map comprising 2595 loci identified a major and consensus QTL with a linked marker in a 0.8-Mb physical interval for oil content in peanut. Enhancing oil content is an important breeding objective in peanut. High-resolution mapping of quantitative trait loci (QTLs) with linked markers could facilitate marker-assisted selection in breeding for target traits. In the present study, a recombined inbred line population (Xuhua 13 × Zhonghua 6) was used to construct a genetic map based on double-digest restriction-site-associated DNA sequencing (ddRAD-seq). The resulting high-density genetic map contained 2595 loci, and spanned a length of 2465.62 cM, with an average distance of 0.95 cM/locus. Seven QTLs for oil content were identified on five linkage groups, including the major and stable QTL qOCA08.1 on chromosome A08 with 10.14-27.19% phenotypic variation explained. The physical interval of qOCA08.1 was further delimited to a ~ 0.8-Mb genomic region where two genes affecting oil synthesis had been annotated. The marker SNPOCA08 was developed targeting the SNP loci associated with oil content and validated in peanut cultivars with diverse oil contents. The major and stable QTL identified in the present study could be further dissected for gene discovery. Furthermore, the tightly linked marker for oil content would be useful in marker-assisted breeding in peanut.

Genome-wide quantitative trait loci reveal the genetic basis of cotton fibre quality and yield-related traits in a Gossypium hirsutum recombinant inbred line population

Cotton is widely cultivated globally because it provides natural fibre for the textile industry and human use. To identify quantitative trait loci (QTLs)/genes associated with fibre quality and yield, a recombinant inbred line (RIL) population was developed in upland cotton. A consensus map covering the whole genome was constructed with three types of markers (8295 markers, 5197.17 centimorgans (cM)). Six fibre yield and quality traits were evaluated in 17 environments, and 983 QTLs were identified, 198 of which were stable and mainly distributed on chromosomes 4, 6, 7, 13, 21 and 25. Thirty-seven QTL clusters were identified, in which 92.8% of paired traits with significant medium or high positive correlations had the same QTL additive effect directions, and all of the paired traits with significant medium or high negative correlations had opposite additive effect directions. In total, 1297 genes were discovered in the QTL clusters, 414 of which were expressed in two RNA-Seq data sets. Many genes were discovered, 23 of which were promising candidates. Six important QTL clusters that included both fibre quality and yield traits were identified with opposite additive effect directions, and those on chromosome 13 (qClu-chr13-2) could increase fibre quality but reduce yield; this result was validated in a natural population using three markers. These data could provide information about the genetic basis of cotton fibre quality and yield and help cotton breeders to improve fibre quality and yield simultaneously.

Construction of High-Density Genetic Map and Identification of QTLs Associated with Seed Vigor after Exposure to Artificial Aging Conditions in Sweet Corn Using SLAF-seq

Seed vigor is a key factor that determines the quality of seeds, which is of great significance for agricultural production, with the potential to promote growth and productivity. However, the underlying molecular mechanisms and genetic basis for seed vigor remain unknown. High-density genetic linkage mapping is an effective method for genomic study and quantitative trait loci (QTL) mapping. In this study, a high-density genetic map was constructed from a 148 BC₄F₃ population cross between ‘M03’ and ‘M08’ strains based on specific-locus amplified fragment (SLAF) sequencing. The constructed high-density genetic linkage map (HDGM) included 3876 SNP markers on ten chromosomes covering 2413.25 cM in length, with a mean distance between markers of 0.62 cM. QTL analysis was performed on four sweet corn germination traits that are related to seed vigor under artificial aging conditions. A total of 18 QTLs were identified in two seasons. Interestingly, a stable QTL was detected in two seasons on chromosome 10—termed qGR10—within an interval of 1.37 Mb. Within this interval, combined with gene annotation, we found four candidate genes (GRMZM2G074309, GRMZM2G117319, GRMZM2G465812, and GRMZM2G343519) which may be related to seed vigor after artificial aging.

A high-density genetic map constructed using specific length amplified fragment (SLAF) sequencing and QTL mapping of seed-related traits in sesame (Sesamum indicum L.)

BACKGROUND

Sesame (Sesamum indicum L., 2n = 2x = 26) is an important oilseed crop with high oil content but small seed size. To reveal the genetic loci of the quantitative seed-related traits, we constructed a high-density single nucleotide polymorphism (SNP) linkage map of an F₂ population by using specific length amplified fragment (SLAF) technique and determined the quantitative trait loci (QTLs) of seed-related traits for sesame based on the phenotypes of F₃ progeny.

RESULTS

The genetic map comprised 2159 SNP markers distributed on 13 linkage groups (LGs) and was 2128.51 cM in length, with an average distance of 0.99 cM between adjacent markers. QTL mapping revealed 19 major-effect QTLs with the phenotypic effect (R²) more than 10%, i.e., eight QTLs for seed coat color, nine QTLs for seed size, and two QTLs for 1000-seed weight (TSW), using composite interval mapping method. Particularly, LG04 and LG11 contained collocated QTL regions for the seed coat color and seed size traits, respectively, based on their close or identical locations. In total, 155 candidate genes for seed coat color, 22 for seed size traits, and 54 for TSW were screened and analyzed.

CONCLUSIONS

This report presents the first QTL mapping of seed-related traits in sesame using an F₂ population. The results reveal the location of specific markers associated with seed-related traits in sesame and provide the basis for further seed quality traits research.

QTL identification for seed weight and size based on a high-density SLAF-seq genetic map in peanut (Arachis hypogaea L.)

BACKGROUND

The cultivated peanut is an important oil and cash crop grown worldwide. To meet the growing demand for peanut production each year, genetic studies and enhanced selection efficiency are essential, including linkage mapping, genome-wide association study, bulked-segregant analysis and marker-assisted selection. Specific locus amplified fragment sequencing (SLAF-seq) is a powerful tool for high density genetic map (HDGM) construction and quantitative trait loci (QTLs) mapping. In this study, a HDGM was constructed using SLAF-seq leading to identification of QTL for seed weight and size in peanut.

RESULTS

A recombinant inbred line (RIL) population was advanced from a cross between a cultivar 'Huayu36' and a germplasm line '6-13' with contrasting seed weight, size and shape. Based on the cultivated peanut genome, a HDGM was constructed with 3866 loci consisting of SLAF-seq and simple sequence repeat (SSR) markers distributed on 20 linkage groups (LGs) covering a total map distance of 1266.87 cM. Phenotypic data of four seed related traits were obtained in four environments, which mostly displayed normal distribution with varied levels of correlation. A total of 27 QTLs for 100 seed weight (100SW), seed length (SL), seed width (SW) and length to width ratio (L/W) were identified on 8 chromosomes, with LOD values of 3.16-31.55 and explaining phenotypic variance (PVE) from 0.74 to 83.23%. Two stable QTL regions were identified on chromosomes 2 and 16, and gene content within these regions provided valuable information for further functional analysis of yield component traits.

CONCLUSIONS

This study represents a new HDGM based on the cultivated peanut genome using SLAF-seq and SSRs. QTL mapping of four seed related traits revealed two stable QTL regions on chromosomes 2 and 16, which not only facilitate fine mapping and cloning these genes, but also provide opportunity for molecular breeding of new peanut cultivars with improved seed weight and size.

Genome-wide characterization of the UDP-glycosyltransferase gene family in upland cotton

Uridine diphosphate (UDP)-glycosyltransferases (UGTs) involved in many metabolic processes are ubiquitous in plants, animals, microorganisms and other organisms and are essential for their growth and development. Upland cotton contains a large number of UGT genes. In this study, we aimed to identify UGT family members in the genome of upland cotton (Gossypium hirsutum L.) and analyze their expression patterns. Bioinformatics methods were used to identify UGT genes from the whole genome of upland cotton (Gossypium hirsutum L. acc. TM-1). Phylogenetic analysis was conducted based on alignment of UGT proteins from upland cotton, and the gene structure, motif and chromosome localization were analyzed for the H subgroup of the UGT family. And the physical and chemical properties and expressions of the genes in the H subgroup of this family were also analyzed. A total of 274 UGT genes were identified from the whole genome of upland cotton and were divided into nine subgroups based on phylogenetic analyses. In subgroup H, 36 genes were distributed on 18 chromosomes. The subfamily genes were simple in the structure, 19 of its members contained two introns, and the others contained only one intron. The qRT-PCR results and transcriptomic data indicated that most of the genes had a wide range of tissue expression characteristics. And the phylogenetic analysis results and expression profiles of these genes revealed tissues and different UGT genes from this crop. Taking RNA-seq, RT-qPCR, and quantitative trait locus (QTL) mapping together, our results suggested that GhUGT6 and GhUGT105 in subgroup H of the GhUGT gene family could be potential candidate genes for cotton yield, and GhUGT16, GhUGT103 might play a vital role in fiber development.

QTL analysis and candidate gene identification for plant height in cotton based on an interspecific backcross inbred line population of Gossypium hirsutum × Gossypium barbadense

We constructed the first high-quality and high-density genetic linkage map for an interspecific BIL population in cotton by specific-locus amplified fragment sequencing for QTL mapping. A novel gene GhPIN3 for plant height was identified in cotton. Ideal plant height (PH) is important for improving lint yield and mechanized harvesting in cotton. Most published genetic studies on cotton have focused on fibre yield and quality traits rather than PH. To facilitate the understanding of the genetic basis in PH, an interspecific backcross inbred line (BIL) population of 250 lines derived from upland cotton (Gossypium hirsutum L.) CRI36 and Egyptian cotton (G. barbadense L.) Hai7124 was used to construct a high-density genetic linkage map for quantitative trait locus (QTL) mapping. The high-density genetic map harboured 7,709 genotyping-by-sequencing (GBS)-based single nucleotide polymorphism (SNP) markers that covered 3,433.24 cM with a mean marker interval of 0.67 cM. In total, ten PH QTLs were identified and each explained 4.27-14.92% of the phenotypic variation, four of which were stable as they were mapped in at least two tests or based on best linear unbiased prediction in seven field tests. Based on functional annotation of orthologues in Arabidopsis and transcriptome data for the genes within the stable QTL regions, GhPIN3 encoding for the hormone auxin efflux carrier protein was identified as a candidate gene located in the stable QTL qPH-Dt1-1 region. A qRT-PCR analysis showed that the expression level of GhPIN3 in apical tissues was significantly higher in four short-statured cotton genotypes than that in four tall-statured cotton genotypes. Virus-induced gene silencing cotton has significantly increased PH when the expression of the GhPIN3 gene was suppressed.

A high density SLAF-seq SNP genetic map and QTL for seed size, oil and protein content in upland cotton

BACKGROUND

Cotton is a leading natural fiber crop. Beyond its fiber, cottonseed is a valuable source of plant protein and oil. Due to the much higher value of cotton fiber, there is less consideration of cottonseed quality despite its potential value. Though some QTL controlling cottonseed quality have been identified, few of them that warrant further study are known. Identifying stable QTL controlling seed size, oil and protein content is necessary for improvement of cottonseed quality.

RESULTS

In this study, a recombinant inbred line (RIL) population was developed from a cross between upland cotton cultivars/lines Yumian 1 and M11. Specific locus amplified fragment sequencing (SLAF-seq) technology was used to construct a genetic map that covered 3353.15 cM with an average distance between consecutive markers of 0.48 cM. The seed index, together with kernel size, oil and protein content were further used to identify QTL. In total, 58 QTL associated with six traits were detected, including 13 stable QTL detected in all three environments and 11 in two environments.

CONCLUSION

A high resolution genetic map including 7033 SNP loci was constructed through specific locus amplified fragment sequencing technology. A total of 13 stable QTL associated with six cottonseed quality traits were detected. These stable QTL have the potential for fine mapping, identifying candidate genes, elaborating molecular mechanisms of cottonseed development, and application in cotton breeding programs.

Fine mapping and molecular characterization of the virescent gene vsp in Upland cotton (Gossypium hirsutum)

The vsp gene was fine mapped to a 353.7-kb region, and a 201-bp deletion that affected chloroplast development and chlorophyll biosynthesis was found in the candidate gene GhPUR4. Virescent mutations can be used as marker traits in heterosis breeding and can also be used to research chloroplast development, chlorophyll biosynthesis and photosynthesis mechanisms. Here, we obtained a light-sensitive virescent mutant, vsp, that has reduced chlorophyll (Chl) content and abnormal chloroplast development. Then, the virescent space (vsp) gene in the vsp mutant was preliminarily mapped to a 38.32-Mb region of chromosome D04 using a high-density SNP genetic map with a total length of 5384.33 cM and 4472 bin markers. Furthermore, the vsp gene was narrowed down to a 353.7-kb region that contains 15 candidate genes using 484 virescent individuals from an F₂ population. Sequence analysis of genes in this region showed that a 201-bp deletion was present in the Gh_D04G1108 (GhPUR4) gene in the vsp mutant. The 201-bp deletion of Gh_D04G1108 caused the deletion of 67 AAs in the GhPUR4 protein. Virus-induced gene silencing (VIGS) of GhPUR4 in normal plants caused reduced GhPUR4 gene expression levels, reduced Chl content, abnormal chloroplast development and virescent true leaves. This study could help us unravel the function of GhPUR4 in chloroplast development and Chl biosynthesis at the early developmental stages of the true leaves in cotton, which could promote the research and application of virescent mutations in cotton heterosis breeding.

Dissecting the genetic basis of fiber quality and yield traits in interspecific backcross populations of Gossypium hirsutum × Gossypium barbadense

Fiber quality and yield are important traits of cotton. Quantitative trait locus (QTL) mapping is a prerequisite for marker-assisted selection (MAS) in cotton breeding. To identify QTLs for fiber quality and yield traits, 4 backcross-generation populations (BC₁F₁, BC₁S₁, BC₂F₁, and BC₃F₀) were developed from an interspecific cross between CCRI36 (Gossypium hirsutum L.) and Hai1 (G. barbadense L.). A total of 153 QTLs for fiber quality and yield traits were identified based on data from the BC₁F₁, BC₁S₁, BC₂F₁ and BC₃F₀ populations in the field and from the BC₂F₁ population in an artificial disease nursery using a high-density genetic linkage map with 2292 marker loci covering 5115.16 centimorgans (cM) from the BC₁F₁ population. These QTLs were located on 24 chromosomes, and each could explain 4.98-19.80% of the observed phenotypic variations. Among the 153 QTLs, 30 were consistent with those identified previously. Specifically, 23 QTLs were stably detected in 2 or 3 environments or generations, 6 of which were consistent with those identified previously and the other 17 of which were stable and novel. Ten QTL clusters for different traits were found and 9 of them were novel, which explained the significant correlations among some phenotypic traits in the populations. The results including these stable or consensus QTLs provide valuable information for marker-assisted selection (MAS) in cotton breeding and will help better understand the genetic basis of fiber quality and yield traits, which can then be used in QTL cloning.

Cumulative and different genetic effects contributed to yield heterosis using maternal and paternal backcross populations in Upland cotton

Heterosis has been utilized in commercial production, but the heterosis mechanism has remained vague. Hybrid cotton is suitable to dissect the heterosis mechanism. In order to explore the genetic basis of heterosis in Upland cotton, we generated paternal and maternal backcross (BC/P and BC/M) populations. Data for yield and yield-component traits were collected over 2 years in three replicated BC/P field trials and four replicated BC/M field trials. At single-locus level, 26 and 27 QTLs were identified in BC/P and BC/M populations, respectively. Six QTLs shared in both BC populations. A total of 27 heterotic loci were detected. Partial dominant and over-dominant QTLs mainly determined yield heterosis in the BC/P and BC/M populations. QTLs for different traits displayed varied genetic effects in two BC populations. Eleven heterotic loci overlapped with QTLs but no common heterotic locus was detected in both BC populations. We resolved the 333 kb (48 genes) and 516 kb (25 genes) physical intervals based on 16 QTL clusters and 35 common QTLs, respectively, in more than one environment or population. We also identified 189 epistatic QTLs and a number of QTL × environment interactions in two BC populations and the corresponding MPH datasets. The results indicated that cumulative effects contributed to yield heterosis in Upland cotton, including epistasis, QTL × environment interaction, additive, partial dominance and over-dominance.

Construction of a genetic linkage map in Pyropia yezoensis (Bangiales, Rhodophyta) and QTL analysis of several economic traits of blades

Pyropia yezoensis is an economically important seaweed but its molecular genetics is poorly understood. In the present study, we used a doubled haploid (DH) population that was established in our previous work to construct a genetic linkage map of P. yezoensis and analyze the quantitative trait loci (QTLs) of blades. The DH population was genotyped with fluorescent sequence-related amplified polymorphism (SRAP) markers. A chi-square test identified 301 loci with normal segregation (P ≥ 0.01) and 96 loci (24.18%) with low-level skewed segregation (0.001 ≤ P < 0.01). The genetic map was constructed after a total of 92 loci were assembled into three linkage groups (LGs). The map spanned 557.36 cM covering 93.71% of the estimated genome, with a mean interlocus space of 6.23 cM. Kolmogorov-Smirnov test (α = 5%) showed a uniform distribution of the markers along each LG. On the genetic map, 10 QTLs associated with five economic traits of blades were detected. One QTL was for length, one for width, two for fresh weight, two for specific growth rate of length and four for specific growth rate of fresh weight. These QTLs could explain 2.29–7.87% of the trait variations, indicating that their effects were all minor. The results may serve as a framework for future marker-assisted breeding in P. yezoensis.

Development of High-Density SNP Markers and Their Application in Evaluating Genetic Diversity and Population Structure in Elaeis guineensis

High-density single nucleotide polymorphisms (SNPs) are used as highly favored makers to analyze genetic diversity and population structure, to construct high-density genetic maps and provide genotypes for genome-wide association analysis. In order to develop genome-wide SNP markers in oil palm (Elaeis guineensis), single locus amplified fragment sequencing (SLAF-seq) technology was performed in a diversity panel of 200 oil palm individuals and 1,261,501 SNPs were identified with minor allele frequency > 0.05 and integrity > 1. Among them, only 17.81% can be mapped within the genic region and the remaining was located into the intergenic region. A positive correlation was detected between the distribution of SNP markers and retrotransposons [transposable elements (TEs)]. Population structure analysis showed that the 200 individuals of oil palm can be divided into five subgroups based on cross-validation errors. However, the subpopulations divided for the 200 oil palm individuals based on the SNP markers were not accurately related to their geographical origins and 80 oil palm individuals from Malaysia showed highest genetic diversity. In addition, the physical distance of linkage disequilibrium (LD) decay in the analyzed oil palm population was 14.516 kb when r² = 0.1. The LD decay distances for different chromosomes varied from 3.324 (chromosome 15) to 19.983 kb (chromosome 7). Our research provides genome-wide SNPs for future targeted breeding in palm oil.

Co-Expression Network Analysis and Hub Gene Selection for High-Quality Fiber in Upland Cotton (Gossypium hirsutum) Using RNA Sequencing Analysis

Upland cotton (Gossypium hirsutum) is grown for its elite fiber. Understanding differential gene expression patterns during fiber development will help to identify genes associated with fiber quality. In this study, we used two recombinant inbred lines (RILs) differing in fiber quality derived from an intra-hirsutum population to explore expression profiling differences and identify genes associated with high-quality fiber or specific fiber-development stages using RNA sequencing. Overall, 72/27, 1137/1584, 437/393, 1019/184, and 2555/1479 differentially expressed genes were up-/down-regulated in an elite fiber line (L1) relative to a poor-quality fiber line (L2) at 10, 15, 20, 25, and 30 days post-anthesis, respectively. Three-hundred sixty-three differentially expressed genes (DEGs) between two lines were colocalized in fiber strength (FS) quantitative trait loci (QTL). Short Time-series Expression Miner (STEM) analysis discriminated seven expression profiles; gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation were performed to identify difference in function between genes unique to L1 and L2. Co-expression network analysis detected five modules highly associated with specific fiber-development stages, especially for high-quality fiber tissues. The hub genes in each module were identified by weighted gene co-expression network analysis. Hub genes encoding actin 1, Rho GTPase-activating protein with PAK-box, TPX2 protein, bHLH transcription factor, and leucine-rich repeat receptor-like protein kinase were identified. Correlation networks revealed considerable interaction among the hub genes, transcription factors, and other genes.

SLAF-Based Construction of a High-Density Genetic Map and Its Application in QTL Mapping of Carotenoids Content in Citrus Fruit

Carotenoids are important antioxidant components in the human diet. To develop carotenoid-rich agricultural products by genetic intervention, understanding the genetic basis of carotenoids variation is essential. In this study, we constructed a high-density integrated genetic map with 3817 molecular markers using specific locus amplified fragment (SLAF) sequencing from a C. reticulata × P. trifoliata F₁ pseudotestcross population. A total of 17 significant quantitative trait loci (QTLs) distributed on Chromosomes (Chr) 2, 3, 5, 6, and 9 were detected to determine the carotenoid variation in the population. In particular, three QTL colocalizations for multiple carotenoid constituents were observed on Chr 2, 3, and 9, one of which was located on Chr2:34,654,608-35430715 accounted for 20.1-25.4% of the variation of luteoxanthin, auroxanthin, lutein, violaxanthin, and total carotenoid content. Overall, this study provides a genetic foundation for marker-assisted selection (MAS) breeding of nutritionally enhanced citrus fruit.

Fiber Quality Improvement in Upland Cotton (Gossypium hirsutum L.): Quantitative Trait Loci Mapping and Marker Assisted Selection Application

Genetic improvement in fiber quality is one of the main challenges for cotton breeders. Fiber quality traits are controlled by multiple genes and are classified as complex quantitative traits, with a negative relationship with yield potential, so the genetic gain is low in traditional genetic improvement by phenotypic selection. The availability of Gossypium genomic sequences facilitates the development of high-throughput molecular markers, quantitative trait loci (QTL) fine mapping and gene identification, which helps us to validate candidate genes and to use marker assisted selection (MAS) on fiber quality in breeding programs. Based on developments of high density linkage maps, QTLs fine mapping, marker selection and omics, we have performed trait dissection on fiber quality traits in diverse populations of upland cotton. QTL mapping combined with multi-omics approaches such as, RNA sequencing datasets to identify differentially expressed genes have benefited the improvement of fiber quality. In this review, we discuss the application of molecular markers, QTL mapping and MAS for fiber quality improvement in upland cotton.

Identification of Loci and Candidate Genes Responsible for Fiber Length in Upland Cotton (Gossypium hirsutum L.) via Association Mapping and Linkage Analyses

Fiber length (FL) is an important fiber quality trait in cotton. Although many fiber quality quantitative trait loci (QTL) responsible for FL have been identified, most cannot be applied to breeding programs, mainly due to unstable environments or large confidence intervals. In this study, we combined a genome-wide association study (GWAS) and linkage mapping to identify and validate high-quality QTLs responsible for FL. For the GWAS, we developed 93,250 high-quality single-nucleotide polymorphism (SNP) markers based on 355 accessions, and the FL was measured in eight different environments. For the linkage mapping, we constructed an F ₂ population from two extreme accessions. The high-density linkage maps spanned 3,848.29 cM, with an average marker interval of 1.41 cM. In total, 14 and 13 QTLs were identified in the association and linkage mapping analyses, respectively. Most importantly, a major QTL on chromosome D03 identified in both populations explained more than 10% of the phenotypic variation (PV). Furthermore, we found that a sucrose synthesis-related gene (Gh_D03G1338) was associated with FL in this QTL region. The RNA-seq data showed that Gh_D03G1338 was highly expressed during the fiber development stage, and the qRT-PCR analysis showed significant expression differences between the long fiber and short fiber varieties. These results suggest that Gh_D03G1338 may determine cotton fiber elongation by regulating the synthesis of sucrose. Favorable QTLs and candidate genes should be useful for increasing fiber quality in cotton breeding.

A high density SLAF-SNP genetic map and QTL detection for fibre quality traits in Gossypium hirsutum

Background

Upland Cotton (Gossypium hirsutum) is a very important cash crop known for its high quality natural fiber. Recent advances in sequencing technologies provide powerful tools with which to explore the cotton genome for single nucleotide polymorphism marker identification and high density genetic map construction toward more reliable quantitative trait locus mapping.

Results

In the present study, a RIL population was developed by crossing a Chinese high fiber quality cultivar (Yumian 1) and an American high fiber quality line (CA3084), with distinct genetic backgrounds. Specific locus amplified fragment sequencing (SLAF-seq) technology was used to discover SNPs, and a genetic map containing 6254 SNPs was constructed, covering 3141.72 cM with an average distance of 0.5 cM between markers. A total of 95 QTL were detected for fiber quality traits in three environments, explaining 5.5-24.6% of the phenotypic variance. Fifty-five QTL found in multiple environments were considered stable QTL. Nine of the stable QTL were found in all three environments. We identified 14 QTL clusters on 13 chromosomes, each containing one or more stable QTL.

Conclusion

A high-density genetic map of Gossypium hirsutum developed by using specific locus amplified fragment sequencing technology provides detailed mapping of fiber quality QTL, and identification of ‘stable QTL’ found in multiple environments. A marker-rich genetic map provides a foundation for fine mapping, candidate gene identification and marker-assisted selection of favorable alleles at stable QTL in breeding programs.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5294-5) contains supplementary material, which is available to authorized users.