Breeding Applications Research Articles

The fecal microbiota of Holstein cows is heritable and genetically correlated to dairy performances.

The fecal microbiota of ruminants constitutes a diversified community that has been phenotypically associated with a variety of host phenotypes, such as production and health. To gain a better understanding of the complex and interconnected factors that drive the fecal bacterial community, we have aimed to estimate the genetic parameters of the diversity and composition of the fecal microbiota, including heritabilities, genetic correlations among taxa, and genetic correlations between fecal microbiota features and host phenotypes. To achieve this, we analyzed a large population of 1,875 Holstein cows originating from 144 French commercial herds and routinely recorded for production, somatic cell score, and fertility traits. Fecal samples were collected from the animals and subjected to 16S rRNA gene sequencing, with reads classified into Amplicon Sequence Variants (ASVs). The estimated α- and β-diversity indices (i.e., Observed Richness, Shannon index, Bray-Curtis and Jaccard dissimilarity matrices) and the abundances of ASVs, genera, families and phyla, normalized by centered-log ratio (CLR), were considered as phenotypes. Genetic parameters were calculated using either univariate or bivariate animal models. Heritabilities estimates, ranging from 0.08 to 0.31 for taxa abundances and β-diversity indices, highlight the influence of the host genetics on the composition of the fecal microbiota. Furthermore, genetic correlations estimated within the microbial community and between microbiota features and host traits reveal the complex networks linking all components of the fecal microbiota together and to their host, thus strengthening the holobiont concept. By estimating the heritabilities of microbiota-associated phenotypes, our study quantifies the impact of the host genetics on the fecal microbiota composition. In addition, genetic correlations between taxonomic groups and between taxa abundances and host performance suggest potential applications for selective breeding to improve host traits or promote a healthier microbiota.

Towards a better understanding of auxin response factors for improving cereal crops

The auxin response factor (ARF) is the key component of phytohormone auxin signal pathway and is crucial in regulating a plurality of functions throughout plant life cycle. Although ARFs’ structure and function have been well studied in Arabidopsis, such knowledge is far from being sufficient for cereal crops, especially wheat, rice and maize. This review is based on a comprehensive retrospection into the studies on ARFs in the three cereal crops, consisting of four parts: (1) characterization of the domains of 23, 25 and 33 ARF family members in wheat, rice and maize, respectively; (2) revision of nomenclatures for previously reported ARFs to the family numbers based on sequence alignment, and summary of ARFs’ functions including the regulation of agronomic traits and response to biotic/abiotic stresses; (3) highlight of general regulatory models for fundamental physiological and reproductive traits from miRNA-ARFs, IAA-ARF-LBD, IAA-ARF-Auxin response gene, and IAA-ARF-ERF (4) prospects to promising future ARF research for anticipated agronomic traits. Hopefully, the review will facilitate the understanding of ARF functions in the three cereal crops and promote its application in molecular breeding for achieving optimal plant architecture, higher yield, and wide adaptability.

CRISPR/Gal4BD-Cas donor adapting systems based on miniaturized Cas proteins for improved gene editing.

Targeted precise point editing and knock-in can be achieved by homology-directed repair(HDR) based gene editing strategies in mammalian cells. However, the inefficiency of HDR strategies seriously restricts their application in precision medicine and molecular design breeding. In view of the problem that exogenous donor DNA cannot be efficiently recruited autonomously at double-stranded breaks(DSBs) when using HDR strategies for gene editing, the concept of donor adapting system(DAS) was proposed and the CRISPR/Cas9-Gal4BD DAS was developed previously. Due to the large size of SpCas9 protein, its fusion with the Gal4BD adaptor is inconvenient for protein expression, virus vector packaging and in vivo delivery. In this study, two novel CRISPR/Gal4BD-SlugCas9 and CRISPR/Gal4BD-AsCas12a DASs were further developed, using two miniaturized Cas proteins, namely SlugCas9-HF derived from Staphylococcus lugdunensis and AsCas12a derived from Acidaminococcus sp. Firstly, the SSA reporter assay was used to assess the targeting activity of different Cas-Gal4BD fusions, and the results showed that the fusion of Gal4BD with SlugCas9 and AsCas12a N-terminals had minimal distraction on their activities. Secondly, the HDR efficiency reporter assay was conducted for the functional verification of the two DASs and the corresponding donor patterns were optimized simultaneously. The results demonstrated that the fusion of the Gal4BD adaptor binding sequence at the 5'-end of intent dsDNA template (BS-dsDNA) was better for the CRISPR/Gal4BD-AsCas12a DAS, while for the CRISPR/Gal4BD-SlugCas9 DAS, the dsDNA-BS donor pattern was recommended. Finally, CRISPR/Gal4BD-SlugCas9 DAS was used to achieve gene editing efficiency of 24%, 37% and 31% respectively for EMX1, NUDT5 and AAVS1 gene loci in HEK293T cells, which was significantly increased compared with the controls. In conclusion, this study provides a reference for the subsequent optimization of the donor adapting systems, and expands the gene editing technical toolbox for the researches on animal molecular design breeding.

Mutations in starch BRANCHING ENZYME 2a suppress the traits caused by the loss of ISOAMYLASE1 in barley

Key messageThe hvbe2a mutations restore the starch-deficient phenotype caused by the hvisa1 and hvflo6 mutations in barley endosperm.The genetic interactions among starch biosynthesis genes can be exploited to alter starch properties, but they remain poorly understood due to the various combinations of mutations to be tested. Here, we isolated two novel barley mutants defective in starch BRANCHING ENZYME 2a (hvbe2a-1 and hvbe2a-2) based on the starch granule (SG) morphology. Both hvbe2a mutants showed elongated SGs in the endosperm and increased resistant starch content. hvbe2a-1 had a base change in HvBE2a gene, substituting the amino acid essential for its enzyme activity, while hvbe2a-2 is completely missing HvBE2a due to a chromosomal deletion. Further genetic crosses with barley isoamylase1 mutants (hvisa1) revealed that both hvbe2a mutations could suppress defects in endosperm caused by hvisa1, such as reduction in starch, increase in phytoglycogen, and changes in the glucan chain length distribution. Remarkably, hvbe2a mutations also transformed the endosperm SG morphology from the compound SG caused by hvisa1 to bimodal simple SGs, resembling that of wild-type barley. The suppressive impact was in competition with floury endosperm 6 mutation (hvflo6), which could enhance the phenotype of hvisa1 in the endosperm. In contrast, the compound SG formation induced by the hvflo6 hvisa1 mutation in pollen was not suppressed by hvbe2a mutations. Our findings provide new insights into genetic interactions in the starch biosynthetic pathway, demonstrating how specific genetic alterations can influence starch properties and SG morphology, with potential applications in cereal breeding for desired starch properties.

Exploring Evolutionary Pathways and Abiotic Stress Responses through Genome-Wide Identification and Analysis of the Alternative Oxidase (AOX) Gene Family in Common Oat (Avena sativa).

The alternative oxidase (AOX), a common terminal oxidase in the electron transfer chain (ETC) of plants, plays a crucial role in stress resilience and plant growth and development. Oat (Avena sativa), an important crop with high nutritional value, has not been comprehensively studied regarding the AsAOX gene family. Therefore, this study explored the responses and potential functions of the AsAOX gene family to various abiotic stresses and their potential evolutionary pathways. Additionally, we conducted a genome-wide analysis to explore the evolutionary conservation and divergence of AOX gene families among three Avena species (Avena sativa, Avena insularis, Avena longiglumis) and four Poaceae species (Avena sativa, Oryza sativa, Triticum aestivum, and Brachypodium distachyon). We identified 12 AsAOX, 9 AiAOX, and 4 AlAOX gene family members. Phylogenetic, motif, domain, gene structure, and selective pressure analyses revealed that most AsAOXs, AiAOXs, and AlAOXs are evolutionarily conserved. We also identified 16 AsAOX segmental duplication pairs, suggesting that segmental duplication may have contributed to the expansion of the AsAOX gene family, potentially preserving these genes through subfunctionalization. Chromosome polyploidization, gene structural variations, and gene fragment recombination likely contributed to the evolution and expansion of the AsAOX gene family as well. Additionally, we hypothesize that AsAOX2 may have potential function in resisting wounding and heat stresses, while AsAOX4 could be specifically involved in mitigating wounding stress. AsAOX11 might contribute to resistance against chromium and waterlogging stresses. AsAOX8 may have potential fuction in mitigating ABA-mediated stress. AsAOX12 and AsAOX5 are most likely to have potential function in mitigating salt and drought stresses, respectively. This study elucidates the potential evolutionary pathways of the AsAOXs gene family, explores their responses and potential functions to various abiotic stresses, identifies potential candidate genes for future functional studies, and facilitates molecular breeding applications in A. sativa.

Genome wide association study of antioxidant activity in pigeonpea germplasm

Pigeonpea (Cajanus cajan L.) is a nutritious crop with antioxidant potential, making it valuable for health supplements and medicinal products. Pigeonpea seed coat possess a rich source of antioxidant properties, particularly in dark colour seed coat varieties. Recently, antioxidant-based drugs for the prevention and treatment of complex diseases have evoked a great deal of research interest in natural antioxidants. We resolved genomic regions by conducted a genome-wide association study (GWAS) using a high-throughput 62 K SNP “CcSNPnks” genic chip to identify SNP markers associated with antioxidant properties in 287 diverse panel of pigeonpea genotypes. Evaluated their antioxidant activity using a spectrophotometric technique based on ferric ion-reducing antioxidant potential (FRAP) and calculated the gallic acid equivalents (GAE) per 100 g of extract. Significant differences in antioxidant activities were found among genotypes, ranging from 3.27 mg in ICPL-13271 to 16.85 mg in UP 9-I for ferric iron-reducing activity. The GWAS identified four distinct marker trait association (MTA) that exhibit a strong correlation with antioxidant properties. We identified significant marker trait associations with chr 2 (AX-165372487), chr 6 (AX-165348296) code for RGA1 protein, chr 10 (AX-165367685) codes for alkaline ceramidase (transcript variant), and chr 11 (AX-165411944) codes for (DL)-glycerol-3-phosphatase 2. The identified protein, RGA1, is involved in reducing ROS accumulation in response to stress by up-regulating the transcription of superoxide dismutases. It suppresses GA-induced vegetative growth and floral initiation. Rapidly degraded in response to GA and involved in fruit and flower development. Furthermore, the population structure analysis identified four distinct sub-populations with admixture types, effectively grouping all genotypes based on their ancestry. Our findings advance the understanding of the genetic underpinning antioxidant concentrations, holding potential for applications in crop breeding and aligning with consumer preferences. This study provides a cornerstone for future research into exploiting marker-assisted breeding to produce pigeonpea cultivars.

Construction and Evaluation of Pepper Core Collection Based on Phenotypic Traits and SSR Markers

To streamline germplasm preservation, enhance resource utilization, and improve breeding efficiency, a core germplasm bank was established using 24 phenotypic traits and DNP markers from 155 pepper resources across various regions. Selection of the optimal core germplasm was based on intra-group retention ratio, overall retention scale, and intra-group stepwise clustering retention. Evaluation of phenotypic trait data for the core germplasm utilized mean, variance, range, and coefficient of variation, with principal component analysis confirming the selection. For molecular evaluation, the core germplasm pre-selection plan was based on SSR clustering, allele retention ratio, and Shannon-Weaver diversity index. This approach resulted in a core germplasm of 41 resources, including 6 var. fasciculatum, 7 var. grossum, 3 var. cerasiorme, 6 var. conoides, and 19 var. longum, representing the maximum phenotypic retention and genetic diversity of the 155 pepper resources. Additionally, a core germplasm of 32 resources was generated based on SSR markers, retaining all 54 polymorphic loci. By integrating phenotypic and molecular core collections, a combined core collection of 57 varieties was developed. This collection achieved a 92.55% phenotype retention ratio and a 100% polymorphism site retention ratio. With a 90% compression ratio, it encapsulates the broad genetic diversity of the original germplasm, serving as a comprehensive resource for further research and breeding applications.

Cross-species modeling of plant genomes at single nucleotide resolution using a pre-trained DNA language model.

Interpreting function and fitness effects in diverse plant genomes requires transferable models. Language models (LMs) pre-trained on large-scale biological sequences can learn evolutionary conservation and offer cross-species prediction better than supervised models through fine-tuning limited labeled data. We introduce PlantCaduceus, a plant DNA LM based on the Caduceus and Mamba architectures, pre-trained on a curated dataset of 16 Angiosperm genomes. Fine-tuning PlantCaduceus on limited labeled Arabidopsis data for four tasks, including predicting translation initiation/termination sites and splice donor and acceptor sites, demonstrated high transferability to 160 million year diverged maize, outperforming the best existing DNA LM by 1.45 to 7.23-fold. PlantCaduceus is competitive to state-of-the-art protein LMs in terms of deleterious mutation identification, and is threefold better than PhyloP. Additionally, PlantCaduceus successfully identifies well-known causal variants in both Arabidopsis and maize. Overall, PlantCaduceus is a versatile DNA LM that can accelerate plant genomics and crop breeding applications.

Validation of SNP Markers for Diversity Analysis, Quality Control, and Trait Selection in a Biofortified Cassava Population.

A validated marker system is crucial to running an effective genomics-assisted breeding program. We used 36 Kompetitive Allele-Specific PCR (KASP) markers to genotype 376 clones from the biofortified cassava pipeline, and fingerprinted 93 of these clones with DArTseq markers to characterize breeding materials and evaluate their relationships. The discriminating ability of the 36-quality control (QC) KASP and 6602 DArTseq markers was assessed using 92 clones genotyped in both assays. In addition, trait-specific markers were used to determine the presence or absence of target genomic regions. Hierarchical clustering identified two major groups, and the clusters were consistent with the breeding program origins. There was moderate genetic differentiation and a low degree of variation between the identified groups. The general structure of the population was similar using both assays. Nevertheless, KASP markers had poor resolution when it came to differentiating the genotypes by seed sources and overestimated the prevalence of duplicates. The trait-linked markers did not achieve optimal performance as all markers displayed variable levels of false positive and/or false negative. These findings represent the initial step in the application of genomics-assisted breeding for the biofortified cassava pipeline, and will guide the use of genomic selection in the future.

Genome Resequencing for Autotetraploid Rice and Its Closest Relatives Reveals Abundant Variation and High Potential in Rice Breeding.

Polyploid rice and its reverted diploid show rich phenotypic variation and strong heterosis, showing great breeding value. However, the genomic differences among tetraploids, counterpart common diploids, tetraploid-revertant diploids, and hybrid descendants are unclear. In this work, we bred a new excellent two-line hybrid rice variety, Y Liang You Duo Hui 14 (HTRM12), using Haitian tetraploid self-reverted diploid (HTRM2). Furthermore, we comparatively analyzed the important agronomic traits and genome-wide variations of those closest relatives, Haitian diploid (HT2), Haitian tetraploid (HT4), HTRM2, and HTRM12 in detail, based on multiple phenotypic investigations, genome resequencing, and bioinformatics analysis. The results of agronomic traits analysis and genome-wide variation analysis of single nucleotide polymorphism (SNP), insertion-deletion (InDel), and copy number variation (CNV) show that HT4 and HTRM2 had abundant phenotypic and genomic variations compared to HT2. HTRM2 can inherit important traits and variations from HT4. This implies that tetraploid self-reverted diploid has high potential in creating excellent breeding materials and in breeding breakthrough hybrid rice varieties. Our study verifies the feasibility that polyploid rice could be used as a mutation carrier for creating variations and provides genomic information, new breeding materials, and a new way of application for tetraploid rice breeding.

Assessment and phenotypic identification of millet germplasm (Setaria italica L.) in Liaoning, China.

This study evaluated millet germplasms in Liaoning Province to support the collection, preservation and innovation of millet germplasm resources. The study was conducted from 2018 to 2020, involved the selection of 105 millet germplasm resources from the Germplasm Bank of the Liaoning Academy of Agricultural Sciences (LAAS), the observation and recording of 31 traits, and the application of multivariate analysis methods to assess phenotypic diversity. From the diversity analysis and correlation analysis, it was found that the tested traits had abundant diversity and complex correlations among them. Principal component analysis (PCA) comprehensively analyzed all quantitative traits and extracted seven principal components. Grey relational analysis (GRA) highlighted the varied contributions of different traits to yield. Through systematic cluster analysis (SCA), the resources were categorized into six groups at Euclidean distance of 17.09. K-mean cluster analysis determined the distribution interval and central value of each trait, then identified resources with desirable traits. The results revealed resources that possess characteristics such as upthrow seedling leaves, more tillers and branches, larger and well-formed ears, and lodging resistance prefer to higher grain yield. It was also discovered that the subear internode length (SIL) could be an indicator for maturity selection. Four specific resources, namely, Dungu No. 1, Xiao-li-xiang, Basen Shengu, and Yuhuanggu No. 1, were identified for further breeding and practical applications.

Variation in a Poaceae-conserved fatty acid metabolic gene cluster controls rice yield by regulating male fertility

A wide variety of metabolic gene clusters exist in eukaryotic genomes, but fatty acid metabolic gene clusters have not been discovered. Here, combining with metabolic and phenotypic genome-wide association studies, we identify a major locus containing a six-gene fatty acid metabolic gene cluster on chromosome 3 (FGC3) that controls the cutin monomer hydroxymonoacylglycerols (HMGs) contents and rice yield, possibly through variation in the transcription of FGC3 members. We show that HMGs are sequentially synthesized in the endoplasmic reticulum by OsFAR2, OsKCS11, OsGPAT6, OsCYP704B2 and subsequently transported to the apoplast by OsABCG22 and OsLTPL82. Mutation of FGC3 members reduces HMGs, leading to defective male reproductive development and a significant decrease in yield. OsMADS6 and OsMADS17 directly regulate FGC3 and thus influence male reproduction and yield. FGC3 is conserved in Poaceae and likely formed prior to the divergence of Pharus latifolius. The eukaryotic fatty acid and plant primary metabolic gene cluster we identified show a significant impact on the origin and evolution of Poaceae and has potential for application in hybrid crop breeding.

Maize ZmSRO1e promotes mesocotyl elongation and deep sowing tolerance by inhibiting the activity of ZmbZIP61.

Deep sowing is a traditional method for drought resistance in maize production, and mesocotyl elongation is strongly associated with the ability of maize to germinate from deep soil. However, little is known about the functional genes and mechanisms regulating maize mesocotyl elongation. In the present study, we identified a plant-specific SIMILAR TO RCD-ONE (SRO) protein family member, ZmSRO1e, involved in maize mesocotyl elongation. The expression of ZmSRO1e is strongly inhibited upon transfer from dark to white light. The loss-of-function zmsro1e mutant exhibited a dramatically shorter mesocotyl than the wild-type in both constant light and darkness, while overexpression of ZmSRO1e significantly promoted mesocotyl elongation, indicating that ZmSRO1e positively regulates mesocotyl elongation. We showed that ZmSRO1e physically interacted with ZmbZIP61, an ortholog of Arabidopsis ELONGATED HYPOCOTYL 5 (HY5) and showed a function similar to that of HY5 in regulating photomorphogenesis. We found that ZmSRO1e repressed the transcriptional activity of ZmbZIP61 toward target genes involved in the regulation of cell expansion, such as ZmEXPB4 and ZmEXPB6, by interfering with the binding of ZmbZIP61 to the promoters of target genes. Our results provide a new understanding of the mechanism by which SRO regulates photomorphogenesis and highlight its potential application in deep sowing-resistant breeding.

Development and implementation of nested single-nucleotide polymorphism (SNP) assays for breeding and genetic research applications.

SoySNP50K and SoySNP6K are commonly used for soybean (Glycine max) genotyping. The SoySNP50K assay has been used to genetically analyze the entire USDA Soybean Germplasm Collection, while the SoySNP6K assay, containing a subset of 6000 single-nucleotide polymorphisms (SNPs) from SoySNP50K, has been used for quantitative trait loci mapping of different traits. To meet the needs for genomic selection, selection of parents for crosses, and characterization of breeding populations, especially early selection of ideal offspring from thousands of lines, we developed two assays, SoySNP3K and SoySNP1K, containing 3072 and 1252 SNPs, respectively, based on SoySNP50K and SoySNP6K mark sets. These two assays also contained the trait markers reported or contributed by soybean breeders. The SNPs in the SoySNP3K are a subset from SoySNP6K, while the SNPs in the SoySNP1K are a subset from SoySNP3K. These SNPs were chosen to reduce the SNP number in the large linkage blocks while capturing as much of the haplotype diversity as possible. They are highly polymorphic and of high quality. The mean minor allele frequencies of the SNPs in the southern and northern US elites were 0.25 and 0.27 for SoySNP3K, respectively, and 0.29 and 0.33 for SoySNP1K. The selected SNPs are a valuable source for developing targeted amplicon sequencing assay or beadchip assay in soybean. SoySNP3K and SoySNP1K assays are commercialized by Illumina Inc. and AgriPlex Genomics, respectively. Together with SoySNP50K and SoySNP6K, a series of nested assays with different marker densities will serve as additional low-cost genomic tools for genetic, genomic, and breeding research.

Effects of Different Shelling Methods on Data Variability during Field Screening for Reduced Aflatoxin Contamination in Maize.

Non-genetic variation limits the identification of novel maize germplasm with genetic markers for reduced Aspergillus flavus infection and aflatoxin contamination. Aflatoxin measurements can vary substantially within fields containing the same germplasm following inoculation with A. flavus. While some variation is expected due to microenvironmental differences, components of field screening methodologies may also contribute to variability in collected data. Therefore, the objective of this study is to test the effects of three different shelling methods (whole ear (WE), ear end removal (EER), and inoculation site-surrounding (ISS)) to obtain bulk samples from maize on aflatoxin measurements. Five ears per row of three inbred lines and two hybrids were inoculated with A. flavus, then shelled using the three different methods, and aflatoxin was quantified. Overall, EER and ISS resulted in reduced coefficients of variance (CVs) in comparison to WE for both inbred and hybrid maize lines, with two exceptions. Susceptible B73 showed increased CVs with both EER and ISS compared to WE, and resistant Mp719's EER CVs marginally increased compared to WE. While WE is the standard practice for most breeding programs due to its technical simplicity, EER and ISS may allow for finely phenotyping parental lines for further breeding applications.

A Study on the Functional Identification of Overexpressing Winter Wheat Expansin Gene TaEXPA7-B in Rice under Salt Stress.

Expansin is a cell wall relaxant protein that is common in plants and directly or indirectly participates in the whole process of plant root growth, development and morphogenesis. A well-developed root system helps plants to better absorb water and nutrients from the soil while effectively assisting them in resisting osmotic stress, such as salt stress. In this study, we observed and quantified the morphology of the roots of Arabidopsis overexpressing the TaEXPAs gene obtained by the research group in the early stage of development. We combined the bioinformatics analysis results relating to EXPA genes in five plants and identified TaEXPA7-B, a member of the EXPA family closely related to root development in winter wheat. Subcellular localization analysis of the TaEXPA7-B protein showed that it is located in the plant cell wall. In this study, the TaEXPA7-B gene was overexpressed in rice. The results showed that plant height, root length and the number of lateral roots of rice overexpressing the TaEXPA7-B gene were significantly higher than those of the wild type, and the expression of the TaEXPA7-B gene significantly promoted the growth of lateral root primordium and cortical cells. The plants were treated with 250 mM NaCl solution to simulate salt stress. The results showed that the accumulation of osmotic regulators, cell wall-related substances and the antioxidant enzyme activities of the overexpressed plants were higher than those of the wild type, and they had better salt tolerance. This paper discusses the effects of winter wheat expansins in plant root development and salt stress tolerance and provides a theoretical basis and relevant reference for screening high-quality expansin regulating root development and salt stress resistance in winter wheat and its application in crop molecular breeding.

Genetic Dissection of Major Rice QTLs for Strong Culms and Fine Mapping of qWS5 for Breeding Application in Transplanted System

BackgroundRice is one of the major staples that feeds about one half of the global populations, and it is important to identify the genetic loci for the traits related to yield improvement. Lodging will cause severe yield loss when it happens, and stem diameter has been characterized as an important trait for lodging resistance. However, most QTLs for stem diameter have not been finely dissected due to their sensitivity to environmental fluctuation.ResultIn this study, we performed QTL analysis for stem diameter using populations derived from Nipponbare (NIP) and strong culm variety YYP1, and confirmed the single and combined effect of three major QTLs by recombinant inbred lines (RILs). Based on the QTL location, we found that qWS5 is a novel QTL not well characterized before. To finely dissect the novel locus, several recombinant heterogeneous inbred families (HIFs) were selected from the RILs for linkage analysis and their derived nearly isogenic lines (NILs) were subjected to detailed trait investigation throughout different years. The HIF-NILs strategy confined the QTL to about 380 kb region supported by repeated genotype and phenotype data, and it lays the foundation for QTL cloning in the future. In addition, introgression of the QTL to an elite japonica variety SD785 was performed by successive backcrossing, and it confirmed the value of qWS5 in increasing stem diameter and other agronomic traits during rice breeding.ConclusionsWe prove that qWS5 is a novel QTL with relatively stable effect for stem diameter and the QTL can be finely mapped to small region by the HIF-NILs strategy. The result will facilitate the improvement of rice lodging resistance by molecular marker assisted selection breeding.

Multiple-trait genomic prediction for swine meat quality traits using gut microbiome features as a correlated trait.

Traits such as meat quality and composition are becoming valuable in modern pork production; however, they are difficult to include in genetic evaluations because of the high phenotyping costs. Combining genomic information with multiple-trait indirect selection with cheaper indicator traits is an alternative for continued cost-effective genetic improvement. Additionally, gut microbiome information is becoming more affordable to measure using targeted rRNA sequencing, and its applications in animal breeding are becoming relevant. In this paper, we investigated the usefulness of microbial information as a correlated trait in selecting meat quality in swine. This study incorporated phenotypic data encompassing marbling, colour, tenderness, loin muscle and backfat depth, along with the characterization of gut (rectal) microbiota through 16S rRNA sequencing at three distinct time points of the animal's growth curve. Genetic progress estimation and cross-validation were employed to evaluate the utility of utilizing host genomic and gut microbiota information for selecting expensive-to-record traits in crossbred individuals. Initial steps involved variance components estimation using multiple-trait models on a training dataset, where the top 25 associated operational taxonomic units (OTU) for each meat quality trait and time point were included. The second step compared the predictive ability of multiple-trait models incorporating different numbers of OTU with single-trait models in a validation set. Results demonstrated the advantage of including genomic information for some traits, while in some instances, gut microbial information proved advantageous, namely, for marbling and pH. The study suggests further investigation into the shared genetic architecture between microbial features and traits, considering microbial data's compositional and high-dimensional nature. This research proposes a straightforward method to enhance swine breeding programs for improving costly-to-record traits like meat quality by incorporating gut microbiome information.

Exploring a Bayesian sparse factor model-based strategy for the genetic analysis of thousands of mid-infrared spectra traits for animal breeding

With the rapid development of animal phenomics and deep phenotyping, we can obtain thousands of traditional (but also molecular) phenotypes per individual. However, there is still a lack of exploration regarding how to handle this huge amount of data in the context of animal breeding, presenting a challenge that we are likely to encounter more and more in the future. This study aimed to (1) explore the use of the mega-scale linear mixed model (MegaLMM), a factor model-based approach that is able to simultaneously estimate (co)variance components and genetic parameters in the context of thousands of milk traits, hereafter called thousand-trait (TT) models; (2) compare the phenotype values and genomic breeding value (u) predictions for focal traits (i.e., traits that are targeted for prediction, compared with secondary traits that are helping to evaluate), from single-trait (ST) and TT models, respectively; (3) propose a new approximate method of GEBV (U) prediction with TT models and MegaLMM. We used a total of 3,421 milk mid-infrared (MIR) spectra wavepoints (called secondary traits) and 3 focal traits (average fat percentage [AFP], average methane production [ACH4], and average SCS [ASCS]) collected on 3,302 first-parity Holstein cows. The 3,421 milk MIR wavepoint traits were composed of 311 wavepoints in 11 classes (months in lactation). Genotyping information of 564,439 SNPs was available for all animals and was used to calculate the genomic relationship matrix. The MegaLMM was implemented in the framework of the Bayesian sparse factor model and solved through Gibbs sampling (Markov chain Monte Carlo). The heritabilities of the studied 3,421 milk MIR wavepoints gradually increased and then decreased in units of 311 wavepoints throughout the lactation. The genetic and phenotypic correlations between the first 311 wavepoints and the other 3,110 wavepoints were low. The accuracies of phenotype predictions from the ST model were lower than those from the TT model for AFP (0.51 vs. 0.93), ACH4 (0.30 vs. 0.86), and ASCS (0.14 vs. 0.33). The same trend was observed for the accuracies of u predictions for AFP (0.59 vs. 0.86), ACH4 (0.47 vs. 0.78), and ASCS (0.39 vs. 0.59). The average correlation between U predicted from the TT model and the new approximate method was 0.90. The new approximate method used for estimating U in MegaLMM will enhance the suitability of MegaLMM for applications in animal breeding. This study conducted an initial investigation into the application of thousands of traits in animal breeding and showed that the TT model is beneficial for the prediction of focal traits (phenotype and breeding values), especially for difficult-to-measure traits (e.g., ACH4).

Genome-Wide Association Analysis Identified Quantitative Trait Loci (QTLs) Underlying Drought-Related Traits in Cultivated Peanut (Arachis hypogaea L.).

Drought is a destructive abiotic stress that affects all critical stages of peanut growth such as emergence, flowering, pegging, and pod filling. The development of a drought-tolerant variety is a sustainable strategy for long-term peanut production. The U.S. mini-core peanut germplasm collection was evaluated for drought tolerance to the middle-season drought treatment phenotyping for pod weight, pod count, relative water content (RWC), specific leaf area (SLA), leaf dry matter content (LDMC), and drought rating. A genome-wide association study (GWAS) was performed to identify minor and major QTLs. A total of 144 QTLs were identified, including 18 significant QTLs in proximity to 317 candidate genes. Ten significant QTLs on linkage groups (LGs) A03, A05, A06, A07, A08, B04, B05, B06, B09, and B10 were associated with pod weight and pod count. RWC stages 1 and 2 were correlated with pod weight, pod count, and drought rating. Six significant QTLs on LGs A04, A07, B03, and B04 were associated with RWC stages 1 and 2. Drought rating was negatively correlated with pod yield and pod count and was associated with a significant QTL on LG A06. Many QTLs identified in this research are novel for the evaluated traits, with verification that the pod weight shared a significant QTL on chromosome B06 identified in other research. Identified SNP markers and the associated candidate genes provide a resource for molecular marker development. Verification of candidate genes surrounding significant QTLs will facilitate the application of marker-assisted peanut breeding for drought tolerance.