The Gossypium is a model genus for understanding polyploidy and the evolutionary pattern of inheritance. This study aimed to investigate the characteristics of SCPLs in different cotton species and their role in fiber development. A total of 891 genes from one typical monocot and ten dicot species were naturally divided into three classes based on phylogenetic analysis. The SCPL gene family in cotton has undergone intense purifying selection with some functional variation. Segmental duplication and whole genome duplication were shown to be the two main reasons for the increase in the number of genes during cotton evolution. The identification of Gh_SCPL genes exhibiting differential expression in particular tissues or response to environmental stimuli provides a new measure for the in-depth characterization of selected genes of importance. Ga09G1039 was involved in the developmental process of fibers and ovules, and it is significantly different from proteins from other cotton species in terms of phylogenetic, gene structure, conserved protein motifs and tertiary structure. Overexpression of Ga09G1039 significantly increased the length of stem trichomes. Ga09G1039 may be a serine carboxypeptidase protein with hydrolase activity, according to functional region, prokaryotic expression, and western blotting analysis. The results provide a comprehensive overview of the genetic basis of SCPLs in Gossypium and further our knowledge in understanding the key aspects of SCPLs in cotton with their potential role in fiber development and stress resistance.

Considering the personality traits of racehorses (e.g., flightiness, anxiety, and affability) is considered essential to improve training efficiency and decrease accident frequency, especially when retraining for a second career that may involve contact with inexperienced personnel after retiring from racing. Studies on human personality-related genes are frequently conducted; however, such studies are rare in horses because a consistent methodology for personality evaluation is lacking. Using the recently published whole genome variant database of 101 Thoroughbred horses, we compared horse genes orthologous to human genes related to the Big Five personality traits, and identified 18 personality-related candidate genes in horses. These genes include 55 variants that involve non-synonymous substitutions that highly impact the encoded protein. Moreover, we evaluated the allele frequencies and functional impact on the proteins in terms of the difference in molecular weights and hydrophobicity levels between reference and altered amino acids. We identified 15 newly discovered genes that may affect equine personality, but their associations with personality are still unclear. Although more studies are required to compare genetic and behavioral information to validate this approach, it may be useful under limited conditions for personality evaluation.

Uncertainty and controversy exist in the phylogenetic status of the Sciaenidae family because of the limited genetic data availability. In this study, a data set of 69,098 bp, covering 309 shared orthologous genes, was extracted from 18 genomes and 5 transcriptomes of 12 species belonging to the Sciaenidae family and used for phylogenetic analysis. The maximum likelihood (ML) and Bayesian approach (BA) methods were used to reconstruct the phylogenetic trees. The resolved ML and BA trees showed similar topology, thus revealing two major evolutionary lineages within the Sciaenidae family, namely, Western Atlantic (WA) and Eastern Atlantic−Indo−West Pacific (EIP). The WA group included four species belonging to four genera: Cynoscion nebulosus, Equetus punctatus, Sciaenops ocellatus, and Micropogonias undulatus. Meanwhile, the EIP group formed one monophyletic clade, harboring eight species (Argyrosomus regius, A. japonicus, Pennahia anea, Nibea albiflora, Miichthys miiuy, Collichthys lucidus, Larimichthys polyactis, and L. crocea) from six genera. Our results indicated that the Western Atlantic (WA) group was more ancient in the studied species, while the Eastern Atlantic−Indo−West Pacific (EIP) group was a younger group. Within the studied species, the genera Collichthys and Larmichthys were the youngest lineages, and we do not suggest that Collichthys and Larmichthys should be considered as one genus. However, the origin of the Sciaenidae family and problems concerning the basal genus were not resolved because of the lack of genomes. Therefore, further sampling and sequencing efforts are needed.

GF14 proteins are a family of conserved proteins involved in many cellular processes including transport, growth, metabolism, and stress response. However, only few reports are available regarding the 14-3-3 genes in potato. In this study, twelve 14-3-3 genes were detected in the potato genome. Based on their phylogenetic relationships, the StGF14 family members were categorized into two classes. Gene expression analysis demonstrated that StGF14h, StGF14a, and StGF14k had the highest gene expression, induced by abiotic and biotic stresses in all three tissues. The number of exons in 14-3-3 genes ranged from four to seven and most of these genes in the same subfamily had similar exon-intron patterns. The results of our study showed that the conserved motifs are similar in most of the proteins in each group. The intron-exon patterns and the composition of conserved motifs validated the 14-3-3 gene phylogenetic classification. According to the genome distribution results, 14-3-3 genes were located unevenly on the 12 Solanum tuberosum chromosomes. We find out 97 orthologous gene pairs between potato and Arabidopsis as well as 15 paralogous genes among potato genomes. Our results showed that GF-14 genes have an effective role in functional and molecular mechanisms in response to environmental stresses.

CONCLUSIONS: Meta-analysis in wheat for three major quality traits identified 110 meta-QTL (MQTL) with reduced confidence interval (CI). Five GWAS validated MQTL (viz., 1A.1, 1B.2, 3B.4, 5B.2, and 6B.2), each involving more than 20 initial QTL and reduced CI (95%) (< 2 cM), were selected for quality breeding programmes. Functional characterization including candidate gene mining and expression analysis discovered 44 high confidence candidate genes associated with quality traits. A meta-analysis of quantitative trait loci (QTL) associated with dough rheology properties, nutritional traits, and processing quality traits was conducted in wheat. For this purpose, as many as 2458 QTL were collected from 50 interval mapping studies published during 2013-2020. Of the total QTL, 1126 QTL were projected onto the consensus map saturated with 249,603 markers which led to the identification of 110 meta-QTL (MQTL). These MQTL exhibited an 18.84-fold reduction in the average CI compared to the average CI of the initial QTL (ranging from 14.87 to 95.55 cM with an average of 40.35 cM). Of the 110, 108 MQTL were physically anchored to the wheat reference genome, including 51 MQTL verified with marker-trait associations (MTAs) reported from earlier genome-wide association studies. Candidate gene (CG) mining allowed the identification of 2533 unique gene models from the MQTL regions. In-silico expression analysis discovered 439 differentially expressed gene models with > 2 transcripts per million expressions in grains and related tissues, which also included 44 high-confidence CGs involved in the various cellular and biochemical processes related to quality traits. Nine functionally characterized wheat genes associated with grain protein content, high-molecular-weight glutenin, and starch synthase enzymes were also found to be co-localized with some of the MQTL. Synteny analysis between wheat and rice MQTL regions identified 23 wheat MQTL syntenic to 16 rice MQTL associated with quality traits. Furthermore, 64 wheat orthologues of 30 known rice genes were detected in 44 MQTL regions. Markers flanking the MQTL identified in the present study can be used for marker-assisted breeding and as fixed effects in the genomic selection models for improving the prediction accuracy during quality breeding. Wheat orthologues of rice genes and other CGs available from MQTLs can be promising targets for further functional validation and to better understand the molecular mechanism underlying the quality traits in wheat.

Penicillium echinulatum 2HH and Penicillium oxalicum 114-2 are well-known cellulase fungal producers. However, few studies addressing global mechanisms for gene regulation of these two important organisms are available so far. A recent finding that the 2HH wild-type is closely related to P. oxalicum leads to a combined study of these two species. Firstly, we provide a global gene regulatory network for P. echinulatum 2HH and P. oxalicum 114-2, based on TF-TG orthology relationships, considering three related species with well-known regulatory interactions combined with TFBSs prediction. The network was then analyzed in terms of topology, identifying TFs as hubs, and modules. Based on this approach, we explore numerous identified modules, such as the expression of cellulolytic and xylanolytic systems, where XlnR plays a key role in positive regulation of the xylanolytic system. It also regulates positively the cellulolytic system by acting indirectly through the cellodextrin induction system. This remarkable finding suggests that the XlnR-dependent cellulolytic and xylanolytic regulatory systems are probably conserved in both P. echinulatum and P. oxalicum. Finally, we explore the functional congruency on the genes clustered in terms of communities, where the genes related to cellular nitrogen, compound metabolic process and macromolecule metabolic process were the most abundant. Therefore, our approach allows us to confer a degree of accuracy regarding the existence of each inferred interaction.

BACKGROUND: DELLAs play key roles in plant gibberellin signaling pathways and are generally important in plant development and growth. However, DELLAs in many plant taxa have not yet been systematically analyzed.
RESULTS: In our study, we searched for DELLA genes across 58 green plant genomes and found 181 DELLAs. Structure analysis showed some DELLA domains do not contain \"D-E-L-L-A\" sequences and instead contain similar domains, including DGLLA and DSLLH domains. \"VHYNP\" motifs in plant DELLAs comprise 23 types of sequences, while some DELLAs did not contain GRAS domains. In grape, we found that the DELLA protein GSVIVT01015465001 contains an F-box domain, while apple DELLA proteins MDP0000220512 and MDP0000403162 contain a WW domain and a BCIP domain, respectively. These DELLAs can be divided into 22 homologous groups and 17 orthologous groups, and 35 paralogous genes were identified. In total, 35 positively selected genes (PSGs) and 121 negatively selected genes (NSGs) were found among DELLAs based on selective pressure analysis, with an average Ks of NSGs that was significantly higher than that of PSGs (P < 0.05). Among the paralogous groups, CBI and Fop were significantly positively correlated with GC, GC1, GC2, GC12, and GC3, while CAI was significantly positively correlated with GC, GC1, GC12, and GC. The paralogous groups with ω values exceeding 1 had significantly higher Ka values. We also found some paralogous groups with ω values exceeding 1 that differed in their motifs.
CONCLUSIONS: This study provides helpful insights into the evolution of DELLA genes and offers exciting opportunities for the investigation of DELLA functions in different plants.

Small heat shock proteins (sHSPs) are important modulators of insect survival. Previous research revealed that there is only one orthologous cluster of shsps in insects. Here, we identified another novel orthologous cluster of shsps in insects by comparative analysis. Multiple stress experiments and function investigation of Tchsp21.8a belonging to this orthologous cluster and seven species-specific shsps were performed in the stored-grain pest Tribolium castaneum. The results indicated that expression of Tchsp21.8a showed weak responses to different stresses. However, expressions of most species-specific shsps exhibited hyper-responses to heat stress, and expressions of all species-specific shsps displayed diverse responses during other stresses to protect beetles in a cooperative manner. Additionally, Tchsp21.8a and species-specific Tcshsp19.7 played important roles in the development of T. castaneum, and all Tcshsps had a certain impact on the fecundity. Our work created a comprehensive reliable scaffold of insect shsps that can further provide instructive insights to pest bio-control.

Circular RNAs (circRNAs) are a new type of intracellular regulator that have been widely identified in animals and plants by high-throughput sequencing. However, there are still few functional studies on circRNAs in plants. To better understand maize circRNAs and their potential functions, we identified 1199 circRNAs in maize from RiboMinus RNA-Seq transcriptome data, and found distinct features of splicing site selection bias, longer flanking introns, and miniature inverted-repeat transposable element (MITE) insertions in flanking introns in maize circRNAs compared to other plant circRNAs. In total, 31 and 36 orthologous circRNAs were identified in rice and maize, respectively, but the orthologous parental genes could not produce orthologous circRNAs, mostly because of long-sequence insertions/deletions at flanking introns and approximately 24.3% of them contained MITE sequences. The majority of maize circRNAs showed high diversity of expression under different treatments and/or in different genetic backgrounds, implying that circRNAs could be involved in various regulatory networks. Twenty-six ecircRNAs were predicted to contain one or more target mimics, and 229 circRNAs had high coding potential, indicating that circRNAs could perform peptide-encoding functions in plants. These results will broaden understanding of the roles of circRNAs in plants and support further functional work on maize.

Essential proteins have vital functions, when they are destroyed in cells, the cells will die or stop reproducing. Therefore, it is very important to identify essential proteins from a large number of other proteins. Due to the time-consuming, expensive, and inefficient process in biological experimental methods, computational methods become more and more popular to recognize them. In the early stages, these methods mainly rely on protein-protein interaction (PPI) information, which limits their discovery capacities. Researchers find novel methods by fusing multi-information to improve prediction accuracy. According to these features, essential proteins are more important and conservative in the evolution process, their neighbors in PPI networks are usually likely to be essential, there are many false positives in PPI data, whether a protein is essential can be assessed by the importance of a protein itself, the relevance of neighbors and the reliability of PPIs. The importance of neighbors and the reliability of PPIs can be further integrated into neighborhood feature. In the study, orthologous information, edge-clustering coefficient and gene expression information are used to measure the importance of a protein itself, the importance of the neighbors and the reliability of PPIs, respectively. Then, a novel expanded POC model, E_POC, is proposed to fuse the above information to discover essential proteins, a weighted PPI network is constructed. The proteins ranked high according to their weights are treated as candidate essential proteins. This novel method is named as E_POC. E_POC outperforms the existing classical methods on S. cerevisiae and E. coli data.