Genetic mapping of stripe rust resistance in a geographically diverse barley collection and selected biparental populations.

Barley stripe or yellow rust (BYR) caused by Puccinia striiformis f. sp. hordei (Psh) is a significant constraint to barley production. The disease is best controlled by genetic resistance, which is considered the most economical and sustainable component of integrated disease management. In this study, we assessed the diversity of resistance to Psh in a panel of international barley genotypes (n = 266) under multiple disease environments (Ecuador, India, and Mexico) using genome-wide association studies (GWASs). Four quantitative trait loci (QTLs) (three on chromosome 1H and one on 7H) associated with resistance to Psh were identified. The QTLs were validated by mapping resistance to Psh in five biparental populations, which detected key genomic regions on chromosomes 1H (populations Pompadour/Zhoungdamei, Pompadour/Zug161, and CI9214/Baudin), 3H (Ricardo/Gus), and 7H (Fumai8/Baronesse). The QTL RpshQ.GWA.1H.1 detected by GWAS and RpshQ.Bau.1H detected using biparental mapping populations co-located were the most consistent and stable across environments and are likely the same resistance region. RpshQ.Bau.1H was saturated using population CI9214/Baudin by enriching the target region, which placed the resistance locus between 7.9 and 8.1 Mbp (flanked by markers sun_B1H_03, 0.7 cM proximal to Rpsh_1H and sun_B1H_KASP_02, 3.2 cM distal on 1HS) in the Morex reference genome v.2. A Kompetitive Allele Specific PCR (KASP) marker sun_B1H_KASP_01 that co-segregated for RpshQ.Bau.1H was developed. The marker was validated on 50 Australian barley cultivars, showing well-defined allelic discrimination and presence in six genotypes (Baudin, Fathom, Flagship, Grout, Sakurastar, and Shepherd). This marker can be used for reliable marker-assisted selection and pyramiding of resistance to Psh and in diversifying the genetic base of resistance to stripe rust.

Integrating physiological and multi-omics methods to elucidate heat stress tolerance for sustainable rice production.

Heat stress presents unique challenges compared to other environmental stressors, as predicting crop responses and understanding the mechanisms for heat tolerance are complex tasks. The escalating impact of devastating climate changes heightens the frequency and intensity of heat stresses, posing a noteworthy threat to global agricultural productivity, especially in rice-dependent regions of the developing world. Humidity has been demonstrated to negatively affect rice yields worldwide. Plants have evolved intricate biochemical adaptations, involving intricate interactions among genes, proteins, and metabolites, to counter diverse external signals and ensure their survival. Modern-omics technologies, encompassing transcriptomics, metabolomics, and proteomics, have revolutionized our comprehension of the intricate biochemical and cellular shifts that occur in stressed agricultural plants. Integrating these multi-omics approaches offers a comprehensive view of cellular responses to heat stress and other challenges, surpassing the insights gained from multi-omics analyses. This integration becomes vital in developing heat-tolerant crop varieties, which is crucial in the face of increasingly unpredictable weather patterns. To expedite the development of heat-resistant rice varieties, aiming at sustainability in terms of food production and food security globally, this review consolidates the latest peer-reviewed research highlighting the application of multi-omics strategies.

QTL-seq identifies genomic region associated with the crown root development under Jasmonic acid response.

Rice root system plays a crucial role in plant adaptation under adverse conditions, particularly drought stress. However, the regulatory gene networks that govern rice root development during stress exposure remain largely unexplored. In this study, we applied a QTL sequencing method to identify QTL/gene controlling the crown root development under Jasmonic acid simulation using the Bulk-segregant analysis. Two rice cultivars with contrasting phenotypes from the Vietnamese traditional rice collection were used as parent pairs for crossing. The single-seed descent method was employed to generate an F2 population of progenies. This F2/3 population was further segregated based on root count under JA stress. Pooled DNA from the two extreme groups in this population was sequenced, and SNP indexes across all loci in these pools were calculated. We detected a significant genomic region on chromosome 10, spanned from 20.39-20.50 Mb, where two rice RLKs were located, OsPUB54 and OsPUB58. Receptor-like kinases (RLKs) are pivotal in regulating various aspects of root development in plants, and the U-box E3 ubiquitination ligase class was generally known for its degradation of some protein complexes. Notably, OsPUB54 was strongly induced by JA treatment, suggesting its involvement in the degradation of the Aux/IAA protein complex, thereby influencing crown root initiation. Besides, the Eukaryotic translation initiation of factor 3 subunit L (eIF3l) and the Mitogen-activated protein kinase kinase kinase 37 (MAPKKK 37) proteins identified from SNPs with high score index which suggests their significant roles in the translation initiation process and cellular signaling pathways, respectively. This information suggests several clues of how these candidates are involved in modifying the rice root system under stress conditions.

QTL mapping for pod quality and yield traits in snap bean (Phaseolus vulgaris L.).

Pod quality and yield traits in snap bean (Phaseolus vulgaris L.) influence consumer preferences, crop adoption by farmers, and the ability of the product to be commercially competitive locally and globally. The objective of the study was to identify the quantitative trait loci (QTL) for pod quality and yield traits in a snap × dry bean recombinant inbred line (RIL) population. A total of 184 F6 RILs derived from a cross between Vanilla (snap bean) and MCM5001 (dry bean) were grown in three field sites in Kenya and one greenhouse environment in Davis, CA, USA. They were genotyped at 5,951 single nucleotide polymorphisms (SNPs), and composite interval mapping was conducted to identify QTL for 16 pod quality and yield traits, including pod wall fiber, pod string, pod size, and harvest metrics. A combined total of 44 QTL were identified in field and greenhouse trials. The QTL for pod quality were identified on chromosomes Pv01, Pv02, Pv03, Pv04, Pv06, and Pv07, and for pod yield were identified on Pv08. Co-localization of QTL was observed for pod quality and yield traits. Some identified QTL overlapped with previously mapped QTL for pod quality and yield traits, with several others identified as novel. The identified QTL can be used in future marker-assisted selection in snap bean.

Genetic analysis of yield components in buckwheat using high-throughput sequencing analysis and wild resource populations.

Fagopyrum tataricum, an important medicinal and edible crop, possesses significant agricultural and economic value. However, the development of buckwheat varieties and yields has been hindered by the delayed breeding progress despite the abundant material resources in China. Current research indicates that quantitative trait loci (QTLs) play a crucial role in controlling plant seed type and yield. To address these limitations, this study constructed recombinant inbred lines (RILs) utilizing both cultivated species and wild buckwheat as raw materials. In total, 84,521 Single Nucleotide Polymorphism (SNP) markers were identified through Genotyping-by-Sequencing (GBS) technology, and high-resolution and high-density SNP genetic maps were developed, which had significant value for QTL mapping, gene cloning and comparative mapping of buckwheat. In this study, we successfully identified 5 QTLs related to thousand grain weight (TGW), 9 for grain length (GL), and 1 for grain width (GW) by combining seed type and TGW data from 202 RIL populations in four different environments, within which one co-located QTL for TGW were discovered on the first chromosome. Transcriptome analysis during different grain development stages revealed 59 significant expression differences between the two materials, which can serve as candidate genes for further investigation into the regulation of grain weight and yield enhancement. The mapped major loci controlling TGW, GL and GW will be valuable for gene cloning and reveal the mechanism underlying grain development and marker-assisted selection in Tartary buckwheat.

Three novel QTLs for FHB resistance identified and mapped in spring wheat PI672538 by bulked segregant analysis of the recombinant inbred line.

Introduction: Fusarium head blight (FHB) has a large influence on both the yield and quality of wheat grain worldwide. Host resistance is the most effective method for controlling FHB, but unfortunately, very few genetic resources on FHB resistance are available; therefore, identifying novel resistance genes or quantitative trait loci (QTLs) is valuable. Methods: Here, a recombinant inbred line (RIL) population containing 451 lines derived from the cross L661/PI672538 was sown in four different environments (2019CZa, 2019CZb, 2021QL and 2021WJ). Results: Five QTLs, consisting of two previously reported QTLs (FhbL693a and FhbL693b) and three new QTLs (FhbL693c, FhbL693d and FhbL693e), were identified. Further investigation revealed that FhbL693b, FhbL693c and FhbL693d could be detected in all four environments, and FhbL693a and FhbL693e were detected only in 2019CZb and 2021WJ, respectively. Among the QTLs, the greatest contribution (10.5%) to the phenotypic variation effect (PVE) was FhbL693d in 2021WJ, while the smallest (1.2%) was FhbL693e and FhbL693a in 2019CZb. The selection of 5Dindel-4 for FhbL693d, 4Aindel-7 for FhbL693c and 3Bindel-24 for FhbL693b decreased the number of damaged spikelets by 2.1, and a new line resistant to FHB named H140-2 was developed by marker-assisted selection (MAS). Discussion: These results could help to further improve FHB resistance in the future.

Modular control of vertebrate axis segmentation in time and space.

How the timing of development is linked to organismal size is a longstanding question. Although numerous studies have reported a correlation of temporal and spatial traits, the developmental or selective constraints underlying this link remain largely unexplored. We address this question by studying the periodic process of embryonic axis segmentation in-vivo in Oryzias fish. Interspecies comparisons reveal that the timing of segmentation correlates to segment, tissue and organismal size. Segment size in turn scales according to tissue and organism size. To probe for underlying causes, we genetically hybridised two closely related species. Quantitative analysis in ~600 phenotypically diverse F2 embryos reveals a decoupling of timing from size control, while spatial scaling is preserved. Using developmental quantitative trait loci (devQTL) mapping we identify distinct genetic loci linked to either the control of segmentation timing or tissue size. This study demonstrates that a developmental constraint mechanism underlies spatial scaling of axis segmentation, while its spatial and temporal control are dissociable modules.

Mapping of dynamic quantitative trait loci for plant height in a RIL population of foxtail millet (Setaria italica L.).

Plant height (PH) is a crucial trait for strengthening lodging resistance and boosting yield in foxtail millet. To identify quantitative trait loci (QTL) and candidate genes associated with PH, we first developed a genetic map using a recombinant inbred line (RIL) population derived from a cross between Aininghuang and Jingu 21. Then, PH phenotyping data and four variations of best linear unbiased prediction (BLUP) were collected from nine environments and three development stages. Next, QTL mapping was conducted using both unconditional and conditional QTL methods. Subsequently, candidate genes were predicted via transcriptome analysis of parental samples at three developmental stages. The results revealed that the genetic map, based on re-sequencing, consisted of 4,360 bin markers spanning 1,016.06 cM with an average genetic distance of 0.23 cM. A total of 19 unconditional QTL, accounting for 5.23%-35.36% of the phenotypic variation explained (PVE), which included 7 major and 4 stable QTL, were identified. Meanwhile, 13 conditional QTL, explaining 5.88%-40.35% of PVE, including 5 major and 3 stable QTL, were discovered. Furthermore, four consistent and stable QTL were identified. Finally, eight candidate genes were predicted through RNA-seq and weighted gene co-expression network analysis (WGCNA). Those findings provide a crucial foundation for understanding the genetic mechanisms underlying PH development and facilitate molecular marker-assisted breeding of ideal plant types in foxtail millet.

A Novel Function of GW5 on Controlling the Early Growth Vigor and its Haplotype Effect on Shoot Dry Weight and Grain Size in Rice (Oryza sativa L.).

Strong early growth vigor is an essential target in both direct seeded rice breeding and high-yielding rice breeding for rice varieties with relatively short growth duration in the double-cropping region. Shoot dry weight (SDW) is one of the important traits associated with early growth vigor, and breeders have been working to improve this trait. Finding stable QTLs or functional genes for SDW is crucial for improving the early growth vigor by implementing molecular breeding in rice. Here, a genome-wide association analysis revealed that the QTL for SDW, qSDW-5, was stably detected in the three cultivation methods commonly used in production practice. Through gene-based haplotype analysis of the annotated genes within the putative region of qSDW-5, and validated by gene expression and knockout transgenic experiments, LOC_Os05g09520, which is identical to the reported GW5/GSE5 controlling grain width (GW) and thousand grain weight (TGW) was identified as the causal gene for qSDW-5. Five main haplotypes of LOC_Os05g09520 were identified in the diverse international rice collection used in this study and their effects on SDW, GW and TGW were analyzed. Phenotypic comparisons of the major haplotypes of LOC_Os05g09520 in the three subpopulations (indica, japonica and aus) revealed the same patterns of wider GW and higher TGW along with higher SDW. Furtherly, the haplotype analysis of 138 rice varieties/lines widely used in southern China showed that 97.8% of the cultivars/lines carry Hap2LOC_Os05g09520. These results not only provide a promising gene source for the molecular breeding of rice varieties with strong early growth vigor, but also elucidate the effect of the LOC_Os05g09520 haplotypes on SDW, GW, and TGW in rice. Importantly, this study provides direct genetic evidence that these three traits are significantly correlated, and suggests a breeding strategy for developing high-yielding and slender grain-shaped indica cultivars with strong early growth vigor.

The construction of a maize-teosinte introgression population and quantitative trait loci analysis of their 21 agronomic traits.

Teosinte is a progenitor species of maize (Zea mays ssp. mays) that retains a significant reservoir of genetic resources unaltered via the domestication process. To harness and explore the genetic reservoirs inherent in teosinte, we used the cultivated publicly inbred line H95 and wild species PI566673 (Zea mays ssp. mexicana) to develop a set of introgression lines (ILs), including 366 BC2F5 lines. Using these lines, 12481 high-quality polymorphic homozygous single nucleotide polymorphisms were converted into 2358 bin markers based on Genotyping by Target Sequencing technology. The homozygous introgression ratio in the ILs was approximately 12.1% and the heterozygous introgression ratio was approximately 5.7%. Based on the population phenotypic data across 21 important agronomic traits collected in Sanya and Beijing, 185 and 156 quantitative trait loci (QTLs) were detected in Sanya and Beijing, respectively, with 64 stable QTLs detected in both locations. We detected 12 QTL clusters spanning 10 chromosomes consisting of diverse QTLs related to yield traits such as grain size and weight. In addition, we identified useful materials in the ILs for further gene cloning of related variations. For example, some heterogeneous inbred families with superior genetic purity, shorter target heterozygotes, and some ILs exhibit clear morphological variation associated with plant growth, development, and domestication, manifesting traits such as white stalks, sharp seeds, and cob shattering. In conclusion, our results provide a robust foundation for delving into the genetic reservoirs of teosinte, presenting a wealth of genetic resources and offering insight into the genetic architecture underlying maize agronomic traits.

Analysis of Rice Blast Fungus Genetic Diversity and Identification of a Novel Blast Resistance OsDRq12 Gene.

The rice blast fungus Magnaporthe oryzae poses a significant challenge to maintaining rice production. Developing rice varieties with resistance to this disease is crucial for its effective control. To understand the genetic variability of blast isolates collected between 2015 and 2017, the 27 monogenic rice lines that carry specific resistance genes were used to evaluate blast disease reactions. Based on criteria such as viability, virulence, and reactions to resistance genes, 20 blast isolates were selected as representative strains. To identify novel resistance genes, a quantitative trait locus analysis was carried out utilizing a mixture of the 20 representative rice blast isolates and a rice population derived from crossing the blast-resistant cultivar 'Cheongcheong' with the blast-susceptible cultivar 'Nagdong'. This analysis revealed a significant locus, RM1227-RM1261 on chromosome 12, that is associated with rice blast resistance. Within this locus, 12 disease resistance-associated protein genes were identified. Among them, OsDRq12, a member of the nucleotide-binding, leucine-rich repeat disease resistance family, was chosen as the target gene for additional computational investigation. The findings of this study have significant implications for enhancing rice production and ensuring food security by controlling rice blast and developing resistant rice cultivars.

Identification of QTLs and candidate genes for water-soluble protein content in soybean seeds.

Soybean represents a vital source of premium plant-based proteins for human nutrition. Importantly, the level of water-soluble protein (WSP) is crucial for determining the overall quality and nutritional value of such crops. Enhancing WSP levels in soybean plants is a high-priority goal in crop improvement. This study aimed to elucidate the genetic basis of WSP content in soybean seeds by identifying quantitative trait loci (QTLs) and set the foundation for subsequent gene cloning and functional analysis. Using 180 F10 recombinant inbred lines generated by crossing the high-protein soybean cultivar JiDou 12 with the wild variety Ye 9, our researcher team mapped the QTLs influencing protein levels, integrating Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene expression profiling to identify candidate genes. During the 2020 and 2022 growing seasons, a standard bell-shaped distribution of protein content trait data was observed in these soybean lines. Eight QTLs affecting protein content were found across eight chromosomes, with LOD scores ranging from 2.59 to 7.30, explaining 4.15-11.74% of the phenotypic variance. Notably, two QTLs were newly discovered, one with a elite allele at qWSPC-15 from Ye 9. The major QTL, qWSPC-19, on chromosome 19 was stable across conditions and contained genes involved in nitrogen metabolism, amino acid biosynthesis, and signaling. Two genes from this QTL, Glyma.19G185700 and Glyma.19G186000, exhibited distinct expression patterns at maturity, highlighting the influence of these genes on protein content. This research revealed eight QTLs for WSP content in soybean seeds and proposed a gene for the key QTL qWSPC-19, laying groundwork for gene isolation and enhanced soybean breeding through the use of molecular markers. These insights are instrumental for developing protein-rich soybean cultivars.

Densification of Genetic Map and Stable Quantitative Trait Locus Analysis for Amino Acid Content of Seed in Soybean (Glycine max L.).

Soybean, a primary vegetable protein source, boasts favorable amino acid profiles; however, its composition still falls short of meeting human nutritional demands. The soybean amino acid content is a quantitative trait controlled by multiple genes. In this study, an F2 population of 186 individual plants derived from the cross between ChangJiangChun2 and JiYu166 served as the mapping population. Based on the previously published genetic map of our lab, we increased the density of the genetic map and constructed a new genetic map containing 518 SSR (simple sequence repeats) markers and 64 InDel (insertion-deletion) markers, with an average distance of 5.27 cm and a total length of 2881.2 cm. The content of eight essential amino acids was evaluated in the F2:5, F2:6, and BLUP (best linear unbiased prediction). A total of 52 QTLs (quantitative trait loci) were identified, and 13 QTL clusters were identified, among which loci02.1 and loci11.1 emerged as stable QTL clusters, exploring candidate genes within these regions. Through GO enrichment and gene annotation, 16 candidate genes associated with soybean essential amino acid content were predicted. This study would lay the foundation for elucidating the regulatory mechanisms of essential amino acid content and contribute to germplasm innovation in soybeans.

QTL Mapping of Yield, Agronomic, and Nitrogen-Related Traits in Barley (Hordeum vulgare L.) under Low Nitrogen and Normal Nitrogen Treatments.

Improving low nitrogen (LN) tolerance in barley (Hordeum vulgare L.) increases global barley yield and quality. In this study, a recombinant inbred line (RIL) population crossed between "Baudin × CN4079" was used to conduct field experiments on twenty traits of barley yield, agronomy, and nitrogen(N)-related traits under LN and normal nitrogen (NN) treatments for two years. This study identified seventeen QTL, comprising eight QTL expressed under both LN and NN treatments, eight LN-specific QTL, and one NN-specific QTL. The localized C2 cluster contained QTL controlling yield, agronomic, and N-related traits. Of the four novel QTL, the expression of the N-related QTL Qstna.sau-5H and Qnhi.sau-5H was unaffected by N treatment. Qtgw.sau-2H for thousand-grain weight, Qph.sau-3H for plant height, Qsl.sau-7H for spike length, and Qal.sau-7H for awn length were identified to be the four stable expression QTL. Correlation studies revealed a significant negative correlation between grain N content and harvest index (p < 0.01). These results are essential for barley marker-assisted selection (MAS) breeding.

Grain albumin content is affected by 1BL/1RS translocation and alters the processing quality of wheat (Triticum aestivum L.).

Grain albumin is highly nutritious and closely related to the processing quality of wheat. However, few studies have explored the grain albumin content (GAC) in wheat. This study aims to uncover quantitative trait loci (QTLs) linked to wheat GAC by analyzing a doubled haploid (DH) population derived from common wheat cultivars ShanNong23 and ZhouMai17. We detected six QTLs controlling GAC on chromosomes 1B, 5A, and 6D, with individual QTL explaining 5.78% to 22.29% of the GAC variation. The effect of QGac.cau-1B.1 on GAC is attributed to the presence of the 1BL/1RS translocation, indicating that the 1BL/1RS translocation increase of GAC compared with the non-1BL/1RS translocation lines. The higher GAC observed in 1BL/1RS lines could be primarily attributed to the increased accumulation of omega-secalin, omega-gliadin, low molecular weight glutenin subunit and ribosomal protein content. Additionally, we also found that the SDS-sedimentation value of whole wheat flour was decreased by adding albumin solution. These results advance our understanding of the genetic basis of GAC and offer novel perspectives for enhancing wheat quality through genetic enhancements.

Genetics and plasticity of white leaf mark variegation in white clover (Trifolium repens L.).

BACKGROUND AND AIMS: Leaf variegation is common in plants and confers diverse adaptive functions. However, its genetic underpinnings remain largely unresolved; this is particularly true for variegation that arises through modified leaf tissue structure that affects light reflection. White clover is naturally polymorphic for structure-based white leaf mark variegation. It therefore provides a useful system to examine the genetic basis of this phenotype, and to assess potential costs to photosynthetic efficiency resulting from modified leaf structures. This study sought to map the loci controlling the white leaf mark in white clover and evaluate the relationship between white leaf mark, leaf thickness, and photosynthetic efficiency. METHODS: We generated a high-density genetic linkage map from an F3 mapping population, employing reference genome-based SNP markers. White leaf mark was quantified through detailed phenotypic evaluations alongside leaf thickness to test how tissue thickness may affect the variegation phenotype. Quantitative trait locus (QTL) mapping was performed to characterize their genetic bases. Photosynthetic efficiency measurements were used to test for physiological trade-offs between variegation and photosynthetic output. KEY RESULTS: The V locus, a major gene responsible for the white leaf mark polymorphism, was mapped to the distal end of chromosome 5, and several modifier loci were also mapped that contribute additively to variegation intensity. The presence and intensity of white leaf mark was associated with greater leaf thickness; however, increased variegation did not detectably affect photosynthetic efficiency. CONCLUSIONS: We have successfully mapped the major locus governing the white leaf mark in white clover, along with several modifier loci, revealing a complex basis for this structure-based variegation. The apparent absence of compromised photosynthesis in variegated leaves challenges the notion that variegation creates fitness trade-offs between photosynthetic efficiency and other adaptive functions. This finding suggests that other factors may maintain the white leaf mark polymorphism in white clover.

Single- and multiple-trait quantitative trait locus analyses for seed oil and protein contents of soybean populations with advanced breeding line background.

Soybean seed oil and protein contents are negatively correlated, posing challenges to enhance both traits simultaneously. Previous studies have identified numerous oil and protein QTLs via single-trait QTL analysis. Multiple-trait QTL methods were shown to be superior but have not been applied to seed oil and protein contents. Our study aimed to evaluate the effectiveness of single- and multiple-trait multiple interval mapping (ST-MIM and MT-MIM, respectively) for these traits using three recombinant inbred line populations from advanced breeding line crosses tested in four environments. Using original and simulated data, we found that MT-MIM did not outperform ST-MIM for our traits with high heritability (H2 > 0.84). Empirically, MT-MIM confirmed only five out of the seven QTLs detected by ST-MIM, indicating single-trait analysis was sufficient for these traits. All QTLs exerted opposite effects on oil and protein contents with varying protein-to-oil additive effect ratios (-0.4 to -4.8). We calculated the economic impact of the allelic variations via estimated processed values (EPV) using the National Oilseed Processors Association (NOPA) and High Yield + Quality (HY + Q) methods. Oil-increasing alleles had positive effects on both EPVNOPA and EPVHY+Q when the protein-to-oil ratio was low (-0.4 to -0.7). However, when the ratio was high (-4.1 to -4.8), oil-increasing alleles increased EPVNOPA and decreased EPVHY+Q, which penalizes low protein meal. In conclusion, single-trait QTL analysis is adequately effective for high heritability traits like seed oil and protein contents. Additionally, the populations' elite pedigrees and varying protein-to-oil ratios provide potential lines for further yield assessment and direct integration into breeding programs. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-024-01489-2.

Exploring Evolutionary Adaptations and Genomic Advancements to Improve Heat Tolerance in Chickens.

Climate change poses a significant threat to the poultry industry, especially in hot climates that adversely affect chicken growth, development, and productivity through heat stress. This literature review evaluates the evolutionary background of chickens with the specific genetic characteristics that can help chickens to cope with hot conditions. Both natural selection and human interventions have influenced the genetic characteristics of the breeds used in the current poultry production system. The domestication of chickens from the Red junglefowl (Gallus gallus) has resulted in the development of various breeds with distinct genetic differences. Over the past few years, deliberate breeding for desirable traits (such as meat production and egg quality) in chickens has resulted in the emergence of various economically valuable breeds. However, this selective breeding has also caused a decrease in the genetic diversity of chickens, making them more susceptible to environmental stressors like heat stress. Consequently, the chicken breeds currently in use may possess a limited ability to adapt to challenging conditions, such as extreme heat. This review focuses on evaluating potential genes and pathways responsible for heat tolerance, including heat shock response, antioxidant defense systems, immune function, and cellular homeostasis. This article will also discuss the physiological and behavioral responses of chicken varieties that exhibit genetic resistance to heat, such as the naked neck and dwarf traits in different indigenous chickens. This article intends to review the current genomic findings related to heat tolerance in chickens that used methods such as the genome-wide association study (GWAS) and quantitative trait loci (QTL) mapping, offering valuable insights for the sustainability of poultry in the face of global warming.

Modeling QTL-by-environment interactions for multi-parent populations.

Multi-parent populations (MPPs) are attractive for genetic and breeding studies because they combine genetic diversity with an easy-to-control population structure. Most methods for mapping QTLs in MPPs focus on the detection of QTLs in single environments. Little attention has been given to mapping QTLs in multienvironment trials (METs) and to detecting and modeling QTL-by-environment interactions (QEIs). We present mixed model approaches for the detection and modeling of consistent versus environment-dependent QTLs, i.e., QTL-by-environment interaction (QEI). QTL effects are assumed to be normally distributed with variances expressing consistency or dependence on environments and families. The entries of the corresponding design matrices are functions of identity-by-descent (IBD) probabilities between parents and offspring and follow from the parental origin of offspring DNA. A polygenic effect is added to the models to account for background genetic variation. We illustrate the wide applicability of our method by analyzing several public MPP datasets with observations from METs. The examples include diallel, nested association mapping (NAM), and multi-parent advanced inter-cross (MAGIC) populations. The results of our approach compare favorably with those of previous studies that used tailored methods.

Research advances on the hard seededness trait of soybean and the underlying regulatory mechanisms.

Soybean is one of the world's most economically significant crops and is widely utilized as an essential source of vegetable protein and edible oil. Cultivated soybean is domesticated from its annual counterpart, wild soybean, which is considered valuable germplasm for soybean breeding. However, wild soybean accessions generally produce seeds with impermeable coats, a trait known as hard seededness (HS), which is beneficial for long-term seed survival but is undesirable for the uniform water absorption and germination of seeds, thus limiting the utilization of wild soybeans in breeding. In addition, moderate HS can isolate the embryo from the surrounding environment and is thus beneficial for long-term seed storage and germplasm preservation. The HS trait is primarily associated with the structure and chemical composition of the seed coat. Moreover, its development is also influenced by various environmental conditions, such as water and temperature. Genetic analysis has revealed that HS of soybean is a complex quantitative trait controlled by multiple genes or minor quantitative trait loci (QTL), with many QTLs and several causal genes currently identified. Investigating the physiological and molecular mechanisms underlying this trait is crucial for soybean breeding, production, and food processing. For this article, the literature was reviewed and condensed to create a well-rounded picture of the current understanding of internal and external factors, QTLs, causal genes, and the regulatory mechanisms related to the HS of soybean, with the aim of providing reference for future research and utilization of this trait.