Molecular Breeding最新文献

With the rapid development of sequencing technology, the application of genomic prediction has become more and more common in breeding schemes of livestocks and crops. Selecting an appropriate statistical model is of central importance to achieve high prediction accuracy. Recently, machine learning models have been expected to upgrade genomic prediction into a new era. However, the perspective still suffers from lack of evidence that machine learning models can generally outperform the traditional ones on empirical data sets. In this study, we compared two machine learning models based on artificial neural network (ANN) and convolutional neural network (CNN) with four traditional models, including genomic best linear unbiased prediction (GBLUP), Bayesian ridge regression (BRR), BayesA and BayesB, using three published data sets for grain yield in wheat. For each model, we considered two variants: modeling and ignoring the genotype-by-environment ([Formula: see text]) interaction. In the comparison, we considered two strategies of cross-validation: predicting genotypes that have not been evaluated in any environment (CV1) and predicting genotypes that have been tested in other environments (CV2). Our results showed that traditional Bayesian models (BayesA, BayesB, and BRR) outperformed GBLUP, ANN and CNN when considering [Formula: see text] interaction. The accuracies of ANN and CNN were higher than traditional models only in CV1 and when [Formula: see text] interaction was ignored. It was also found that the performance of the two machine learning models was significantly affected by the interaction between the CV strategy and the way of treating the [Formula: see text] interaction, while that of the four traditional models was only influenced by whether the [Formula: see text] interaction was considered or not. Thus, machine learning models can be a powerful complementary to the traditional ones and their superiority may depend on the prediction scenario. Among the two machine learning models, we observed that the accuracy of ANN was higher than CNN in most cases, indicating that it is still challenging to adapt complex machine learning models such as CNN to genomic prediction.

Zucchini (Cucurbita pepo subsp. pepo) stands as an economically vital crop in China. In zucchini breeding, plant architectural patterns and fruit morphological characteristics serve as pivotal traits. In this study, we employed quantitative trait locus (QTL) analysis using recombinant inbred lines (RILs) derived from two distinct inbred lines, JinGL (subsp. ovifera) and HM-S2 (subsp. pepo), in conjunction with a high-density genetic map. Our investigation focused on ten QTLs associated with six horticulturally significant traits, including hypocotyl length (HL), plant height (PH), and four fruit-related traits: fruit length (FL), fruit diameter (FD), fruit shape index (FSI), and fruit weight (FW). The QTLs governing HL and PH were mapped to Chr03/LG10 and named qhl3.1 and qph3.1, respectively. The candidate gene Cp4.1LG10g05910/CpDw for qph3.1 was successfully identified. Additionally, three novel QTLs related to fruit size and shape were discovered. Among them, qfsi8.1/qfl8.1, demarcated by Marker238258 and Marker240069 on Chromosome 08/Linkage group 17 (Chr08/LG17), is a new major QTL regulating the fruit shape of zucchini. Through genomic insertion-deletion (InDel) and qRT-PCR analyses, we predicted genes within the qfsi8.1/qfl8.1 candidate interval, uncovering Cp4.1LG17g02030/CpIAA12 and Cp4.1LG17g02010/CpCalB as potential candidate genes. We developed molecular markers tightly linked to qph3.1 and qfl8.1 and validated them in 171 and 224 Cucurbita pepo germplasms, achieving accuracy rates of 96% and 100%, respectively. This study deepens our understanding of the genetic basis of key traits and provides valuable references for molecular breeding in Cucurbita pepo.

Supplementary information: The online version contains supplementary material available at 10.1007/s11032-025-01592-y.

Tiller number is an essential agronomic characteristic that influences barley morphology and yield. A barley low number of tillers mutant CIHO 11,530 exhibits few tillers and in this study, we conducted a genetic analysis of the barley low number of tillers 2 (lnt2) locus. Linkage analysis showed that lnt2 was mapped in an interval of 3.39 cM on chromosome 6HS between the flanking markers SNP1765 and SNP526, explaining 53.06% of the phenotypic variance. The genetic effect of lnt2 was further verified in two other genetic backgrounds, explaining variances of 86.43% and 91.01% in tiller numbers between lines carrying the lnt2 mutant and wild-type alleles, respectively. Furthermore, we constructed a large F₂ population and fine-mapped lnt2. Finally, lnt2 was mapped within a 0.19 cM genetic interval delimited by the tightly linked KASP markers KASP6359 and KASP365, and the physical interval was located at 40.57-42.35 Mb. In this interval, three genes were highly likely lnt2 based on gene annotations, sequence and gene expression analyses. Our research provides valuable information for the map-based cloning of lnt2.

Supplementary information: The online version contains supplementary material available at 10.1007/s11032-025-01589-7.

Capsaicinoids and their low pungent analogs are the important compounds to determine quality of chili pepper fruit in food industrial and medical purposes. Our previous screening for chili pepper bio-resources has shown that the pungent accession 'Charapita' (CH) (Capsicum chinense) has a unique composition with a higher capsinoid content. This study aimed to identify the mutation responsible for the high capsinoid content in CH. QTL analysis was performed using F₂ population between Red Habanero (RH) and CH, and it detected a major QTL on chromosome 3. Further genetic analysis showed that the QTL was narrowed down to approximately 400 kb region, which includes VAMT (vanillin aminotransferase). Allelism test demonstrated that CH possesses a leaky vamt allele. The sequencing analysis revealed that CH-type vamt allele has a unique amino acid substitution (G373E) due to a SNP in exon 15. CH-type vamt decreased pungency by 50%, and increased capsinoid content about three times compared with RH-type. We designated the CH-type allele as vamt ^L3. There was no difference in the expression levels of VAMT or other capsaicinoid biosynthetic genes between RH and CH. The vanillylamine synthesis activity was evaluated with crude extract from placental tissue. It showed that the activity in CH was 30 times less compared with RH. Given that the enzyme activity significantly decreased without transcriptional change, G373E likely reduces VAMT activity, conferring the characteristic composition of capsaicinoids and capsinoids. The novel vamt allele (vamt ^L3) will contribute to manipulate pungency level and capsinoid content in chili pepper breeding.

Supplementary information: The online version contains supplementary material available at 10.1007/s11032-025-01595-9.

Panicle-related traits are important factors affecting the final yield of foxtail millet, and it is imperative to detect their underlying genetic basis. In this study, we constructed a genetic linkage map using the F₂ population crossed by Changsheng07 and Donggu218, two foxtail millet lines with significant differences in panicle-related traits. The genetic linkage map included 159 SSR markers and 37 Indel markers, covering 1545.5 cM, with average distance of 7.89 cM between adjacent markers. Quantitative trait loci (QTL) mapping was conducted by combining the genetic linkage map and the phenotypic data of nine panicle-related traits in F_2:3 families, and a total of 22 QTL were identified, with phenotypic variation explained (PVE) of 0.06-50.14%. Among them, the increased effect alleles of 16 QTL were derived from the parent Changsheng07, and seven QTL (qMPL3.1, qMPL5, qMPW2, qSD5, qTGW5.1, qTGW5.2 and qGL5) were major QTL, which explained the phenotypic variation of 11.41%, 12.78%, 13.75%, 34.81%, 50.14%, 40.28% and 11.32%, respectively. Moreover, 13 of 22 QTL formed four QTL clusters. These results will lay a foundation for the cloning and functional analysis of candidate genes involved in panicle development, and provide a theoretical basis for breeding high yield varieties through molecular marker-assisted selection in foxtail millet.

Supplementary information: The online version contains supplementary material available at 10.1007/s11032-025-01594-w.

Rapeseed pods are prone to dehiscence, resulting in yield loss at maturity. In the present study, we investigated the shatter resistance index (SRI) of 280 doubled haploid (DH) lines derived from a cross between ZS11 (susceptible line) and R11 (resistant line). Based on the phenotypic data obtained from four environments and a high-density genetic map, a significant QTL (qSRI.A06) for shatter resistance on A06 chromosome were stably detected. This locus explained 4.80% - 15.00% of the phenotypic variation and the peak position covered a 664 Kb region. The effect of qSRI.A06 was verified in BC₃F₂ and BC₃F₃ populations and delimited in a 90.8 Kb region comprising 11 genes. Out of these genes, a differencially expressed gene, BnaA06g27900D, was identified to be involved in cell wall development by comparative transcriptome analysis. Regional association revealed four SNP/Indel variations in the promoter associated with pod shattering resistance. The highest Indels A06-41975887 showed suggestive association with SRI (p = 8.80E-06) with a TG allele variation. The stable locus qSRI.A06 and the candidate gene BnaA06g27900D will be helpful for understanding the resistance mechanism and improving shatter resistance in rapeseed.

Supplementary information: The online version contains supplementary material available at 10.1007/s11032-025-01590-0.

Cytoplasmic male sterility (CMS) caused by mitochondrial genome alterations in flowering plants plays a crucial role in hybrid breeding systems. In pear (Pyrus spp.), pollenless phenotypes have been consistently observed in progeny. However, the genetic basis and inheritance mechanisms of male sterility in pears remain poorly understood. To investigate the inheritance mode, we performed segregation analysis in four F₁ populations derived from crosses using a cultivar carrying CMS-type cytoplasm as the maternal parent. The observed male sterility segregation ratios confirmed a maternal inheritance pattern consistent with the CMS model and suggested differential effects of nuclear fertility restorer genes from various pollen parents. We analyzed whole-genome sequencing data from four pear accessions, identifying an 860 bp mitochondrial DNA sequence associated with male-sterile individuals. This sequence was located near cox3 and apt8, commonly co-located with CMS loci in other plant species. Within this region, we identified orf206, a chimeric open reading frame composed of 113 bp from nad3 in Pyrus betulifolia and 403 bp from atp9-1 of Malus × domestica. The predicted protein encoded by orf206 contained three transmembrane domains, which are typical features of CMS-associated proteins. Our results demonstrate that male sterility in pears is maternally inherited and support orf206 as a strong candidate gene for CMS induction. Furthermore, we developed an InDel marker (CBpMtid03 and CBpMtid07) targeting the CMS-specific mitochondrial sequence enabling the efficient identification of CMS individuals in breeding programs. These findings provide insights into the molecular mechanisms underlying pollen sterility in pears and facilitate marker-assisted selection in pear breeding.

Supplementary information: The online version contains supplementary material available at 10.1007/s11032-025-01591-z.

Soybean [Glycine max (L.) Merr.] seed morphology markedly influences yield, productivity, and nutritional value. However, assessing quantitative traits remains challenging due to their complexity and strong genotype-by-environment interactions. In this study, a high-throughput phenotyping (HTP) system was used to evaluate 13 image-based traits and a hundred-seed weight in a soybean mutant diversity pool (MDP) comprising 192 genotypes. All traits exhibited significant variations within the mutant diversity pool across multiple environments. Correlation analysis revealed strong positive and negative correlations among the traits regarding seed size, shape, color, and weight. Genome-wide association studies (GWAS) were conducted using 37,249 single nucleotide polymorphisms (SNPs) generated through genotype-by-sequencing (GBS) to uncover the genetic architecture of seed-related traits. The image-based GWAS identified 79 significant quantitative trait nucleotides (QTNs) that were simultaneously detected under all environments. Notably, five novel pleiotropic QTNs were consistently mapped to chromosomes 7, 10, 15, 18, and 20, each associated with a specific candidate gene. These genes exhibited marked expression differences during the seed developmental stages between the wild-type cultivar and its mutant. The HTP-integrated GBS demonstrates a powerful approach for precise trait dissection and genomic selection. These findings provide critical insights into the genetic architecture underlying desirable seed morphology and offer valuable tools for advancing precision soybean breeding.

Supplementary information: The online version contains supplementary material available at 10.1007/s11032-025-01584-y.