Gossypium hirsutum L., or upland cotton, is an important renewable resource for textile fiber. To enhance understanding of the genetic basis of cotton earliness, we constructed an intra-specific recombinant inbred line population (RIL) containing 137 lines, and performed linkage map construction and quantitative trait locus (QTL) mapping. Using restriction-site associated DNA sequencing, a genetic map composed of 6,434 loci, including 6,295 single nucleotide polymorphisms and 139 simple sequence repeat loci, was developed from RIL population. This map spanned 4,071.98 cM, with an average distance of 0.63 cM between adjacent markers. A total of 247 QTLs for six earliness-related traits were detected in 6 consecutive years. In addition, 55 QTL coincidence regions representing more than 60 % of total QTLs were found on 22 chromosomes, which indicated that several earliness-related traits might be simultaneously improved. Fine-mapping of a 2-Mb region on chromosome D3 associated with five stable QTLs between Marker25958 and Marker25963 revealed that lines containing alleles derived from CCRI36 in this region exhibited smaller phenotypes and earlier maturity. One candidate gene (EMF2) was predicted and validated by quantitative real-time PCR in early-, medium- and late-maturing cultivars from 3- to 6-leaf stages, with highest expression level in early-maturing cultivar, CCRI74, lowest expression level in late-maturing cultivar, Bomian1. We developed an SNP-based genetic map, and this map is the first high-density genetic map for short-season cotton and has the potential to provide deeper insights into earliness. Cotton earliness-related QTLs and QTL coincidence regions will provide useful materials for QTL fine mapping, gene positional cloning and MAS. And the gene, EMF2, is promising for further study.

Background: The node of the first fruiting branch (NFFB) is an important precocious trait in cotton. Many studies have been conducted on the localization of quantitative trait loci (QTLs) and genes related to fiber quality and yield, but there has been little attention to traits related to early maturity, especially the NFFB, in cotton. Results: To identify the QTL associated with the NFFB in cotton, a BC₄F₂ population comprising 278 individual plants was constructed. The parents and two DNA bulks for high and low NFFB were whole genome sequenced, and 243.8 Gb of clean nucleotide data were generated. A total of 449,302 polymorphic SNPs and 135,353 Indels between two bulks were identified for QTL-seq. Seventeen QTLs were detected and localized on 11 chromosomes in the cotton genome, among which two QTLs (qNFFB-Dt2–1 and qNFFB-Dt3–3) were located in hotspots. Two candidate genes (GhAPL and GhHDA5) related to the NFFB were identified using quantitative real-time PCR (qRT-PCR) and virus-induced gene silencing (VIGS) experiments in this study. Both genes exhibited higher expression levels in the early-maturing cotton material RIL182 during flower bud differentiation, and the silencing of GhAPL and GhHDA5 delayed the flowering time and increased the NFFB compared to those of VA plants in cotton. Conclusions: Our study preliminarily found that GhAPL and GhHDA5 are related to the early maturity in cotton. The findings provide a basis for the further functional verification of candidate genes related to the NFFB and contribute to the study of early maturity in cotton.

Understanding the genetic basis of the node of the first fruiting branch (NFFB) improves early-maturity cotton breeding. Here we report QTL mapping on 200 F₂ plants and derivative F_2:3 and F_2:4 populations by genotyping by sequencing (GBS). BC₁F₂ population was constructed by backcrossing one F_2:4 line with the maternal parent JF914 and used for BSA-seq for further QTL mapping. A total of 1,305,642 SNPs were developed between the parents by GBS, and 2,907,790 SNPs were detected by BSA-seq. A high-density genetic map was constructed containing 11,488 SNPs and spanning 4,202.12 cM in length. A total of 13 QTL were mapped in the 3 tested populations. JF914 conferred favorable alleles for 11 QTL, and JF173 conferred favorable alleles for the other 2 QTL. Two stable QTL were repeatedly mapped in F_2:3 and F_2:4, including qNFFB-D3-1 and qNFFB-D6-1. Only qNFFB-D3-1 contributed more than 10% of the phenotypic variation. This QTL covered about 24.7 Mb (17,130,008–41,839,226 bp) on chromosome D3. Two regions on D3 (41,779,195–41,836,120 bp, 41,836,768–41,872,287 bp) were found by BSA-seq and covered about 92.4 Kb. This 92.4 Kb region overlapped with the stable QTL qNFFB-D3-1 and contained 8 annotated genes. By qRT-PCR, Ghir_D03G012430 showed a lower expression level from the 1- to 2-leaf stage and a higher expression level from the 3- to 6-leaf stage in the buds of JF173 than that of JF914. Ghir_D03G012390 reached the highest level at the 3- and 5-leaf stages in the buds of JF173 and JF914, respectively. As JF173 has lower NFFB and more early maturity than JF914, these two genes might be important in cell division and differentiation during NFFB formation in the seedling stage. The results of this study will facilitate a better understanding of the genetic basis of NFFB and benefit cotton molecular breeding for improving earliness traits.

Purpose/aim of the study: To conduct a survey spectrum of the PITX2, FOXC1, and PRDM5 genes to reveal genotype–phenotype correlations in a cohort of Southeastern Chinese patients with Axenfeld–Rieger syndrome (ARS). Materials and methods: A total of 20 probands with ARS were recruited in Southeast China. All patients underwent full ocular and systemic examinations. Sanger sequencing was used to analyze all coding regions of and regions adjacent to PITX2, FOXC1, and PRDM5 and 13 upstream regulatory elements of PITX2. Multiplex ligation-dependent probe amplification was performed to detect gross insertions and deletions in PITX2 and FOXC1. Quantitative polymerase chain reaction was used to detect copy number variations in regulatory elements of PITX2. A bioinformatics analysis was conducted to evaluate the pathogenicity of variants. Results: Eleven mutations, including eight novel mutations, were identified in PITX2. Seven of the mutations were truncations. A genotype–phenotype correlation analysis showed that 81.8% (9/11) of patients with mutations in PITX2 developed glaucoma before reaching 10 years old. The proportion of patients without detected mutations was only 33.3% (3/9, P = 0.0399). In patient G1399, ultrasound biomicroscopy revealed that the left eye exhibited a phenotype similar to aniridia with complete angle closure and a remaining stub of iris tissue. Conclusion: This is the first genetic study of a cohort of Southeastern Chinese patients with ARS. Eight novel mutations were detected, expanding the mutation spectrum of PITX2. PITX2 may be a major candidate gene for ARS in Southeastern Chinese patients. Truncations may be the primary mutation type in PITX2. Glaucoma onset may be earlier in patients with mutations in PITX2 than in those without mutations in PITX2 and FOXC1. A block of the anterior chamber angle by the end of the iris might represent the main factor influencing the development of glaucoma in ARS patients with an asymmetric aniridia phenotype.

Cotton is the most important natural fiber-producing crop globally. High-quality fiber and early maturity are equally important breeding goals in the cotton industry. However, it remains challenging to synchronously improve these traits through conventional breeding techniques. To identify additional genetic information relating to fiber quality and early maturity, 11 phenotypic traits for the F₂ and F₃ generations were tested, and quantitative trait loci (QTL) mapping was performed. Candidate genes were analyzed using published RNA-seq datasets and qRT-PCR assays. All 11 tested traits showed bi-directional transgressive segregation, and most traits followed an approximately normal distribution. Overall, significant positive and significant negative correlations were observed among these traits. During cotton breeding, varieties with strong boll-setting ability can be selected from early-maturing materials that have high-quality fiber. A total of 102 QTLs were mapped, including 4 major and 3 stable QTLs. qFL-D13-1 was mapped in both the F₂ and F₃ generations, achieving a 3.94% to 11.39% contribution rate to the phenotypic variation. Three genes located in the QTL regions were identified based on their high expression levels in the three evaluated RNA-seq datasets. Ghir_A04G014830.1, covered by qHNFFB-A4-1 and qFU-A4-1, encoded ACLA-1. Ghir_D13G015010.1, encoding VTC2, and Ghir_D13G016670.1, encoding GA2OX1, were in the stable QTL qFL-D13-1 region. The qRT-PCR results suggested that these three genes may be involved in regulating seed development, fiber initiation, and fiber elongation. Overall, these findings contribute additional information for the breeding of high-yield, high fiber quality, and early-maturity varieties, as well as serve as a foundation for research on the underlying molecular mechanisms.