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[...]SHOREmap requires a much larger sample size; the NGM studies the genes belongs to the recessive homozygous mutant phenotype; MutMap mainly identifies the single gene‐controlled quality traits; QTL‐seq constructs only two pools showing extreme opposite trait values for a given phenotype in a segregating progeny and maps 1–2 major genes for target trait; GWAS is applicable to natural population with a large sample size and thus its cost is high, and it is also difficult to detect the rare mutations and minor effective genes. [...]we compared the SNP‐index between every two Pool‐seq to map the genomic candidate regions. For the genomic candidate regions with overlapping physical positions on the same chromosome, the intersection regions were selected as the final genomic candidate regions. [...]the regions showing a significant association with anthocyanin biosynthesis‐related genes in rice pericarp are shown in Figure c. Three genomic candidate regions were adjacent to or contained the cloned genes of anthocyanin biosynthesis (Figure c). The number of SNPs in the genomic region nearby Rd was greatly reduced (Figure e). [...]the false‐positive result may be resulted from a decrease in nucleotide polymorphism within this genomic region.

Summary In the last decade, the revolution in sequencing technologies has deeply impacted crop genotyping practice. New methods allowing rapid, high‐throughput genotyping of entire crop populations have proliferated and opened the door to wider use of molecular tools in plant breeding. These new genotyping‐by‐sequencing (GBS) methods include over a dozen reduced‐representation sequencing (RRS) approaches and at least four whole‐genome resequencing (WGR) approaches. The diversity of methods available, each often producing different types of data at different cost, can make selection of the best‐suited method seem a daunting task. We review the most common genotyping methods used today and compare their suitability for linkage mapping, genomewide association studies (GWAS), marker‐assisted and genomic selection and genome assembly and improvement in crops with various genome sizes and complexity. Furthermore, we give an outline of bioinformatics tools for analysis of genotyping data. WGR is well suited to genotyping biparental cross populations with complex, small‐ to moderate‐sized genomes and provides the lowest cost per marker data point. RRS approaches differ in their suitability for various tasks, but demonstrate similar costs per marker data point. These approaches are generally better suited for de novo applications and more cost‐effective when genotyping populations with large genomes or high heterozygosity. We expect that although RRS approaches will remain the most cost‐effective for some time, WGR will become more widespread for crop genotyping as sequencing costs continue to decrease.

Inbreeding depression (reduced fitness of individuals with related parents) has long been a major focus of ecology, evolution, and conservation biology. Despite decades of research, we still have a limited understanding of the strength, underlying genetic mechanisms, and demographic consequences of inbreeding depression in the wild. Studying inbreeding depression in natural populations has been hampered by the inability to precisely measure individual inbreeding. Fortunately, the rapidly increasing availability of high‐throughput sequencing data means it is now feasible to measure the inbreeding of any individual with high precision. Here, we review how genomic data are advancing our understanding of inbreeding depression in the wild. Recent results show that individual inbreeding and inbreeding depression can be measured more precisely with genomic data than via traditional pedigree analysis. Additionally, the availability of genomic data has made it possible to pinpoint loci with large effects contributing to inbreeding depression in wild populations, although this will continue to be a challenging task in many study systems due to low statistical power. Now that reliably measuring individual inbreeding is no longer a limitation, a major focus of future studies should be to more accurately quantify effects of inbreeding depression on population growth and viability.

• Topological cytonuclear discordance is commonly observed in plant phylogenetic and phylogeographic studies, yet few studies have attempted to detect two other forms of cytonuclear discordance (branch length and geographical) and to uncover the causes of the discordance. • We used the whole nuclear and chloroplast genome data from 80 individual Asian butternuts to reveal the pattern and processes of cytonuclear discordance. • Our findings indicate that the chloroplast genome had substantially deeper divergence (branch-length discordance) and a steeper cline in the contact zone (geographic discordance) compared with the nuclear genome. After various hypothesis have been tested, the results suggest that incomplete lineage sorting, positive selection and cytonuclear incompatibility are probably insufficient to explain this pattern. However, isolation-by-distance analysis and gene flow estimation point to a much higher level of gene flow by pollen compared with by seeds, which may have slowed down lineage divergence and mediated wider contact for nuclear genome compared with the chloroplast genome. • Altogether, this study highlights a critical role of sex-biased dispersal in causing discordance between the nuclear and plastid genome of Asian butternuts. Given its ubiquity among plants, asymmetric gene flow should be given a high priority in future studies of cytonuclear discordance.

Whole‐genome resequencing (WGRS) of mapping populations has facilitated development of high‐density genetic maps essential for fine mapping and candidate gene discovery for traits of interest in crop species. Leaf spots, including early leaf spot (ELS) and late leaf spot (LLS), and Tomato spotted wilt virus (TSWV) are devastating diseases in peanut causing significant yield loss. We generated WGRS data on a recombinant inbred line population, developed a SNP‐based high‐density genetic map, and conducted fine mapping, candidate gene discovery and marker validation for ELS, LLS and TSWV. The first sequence‐based high‐density map was constructed with 8869 SNPs assigned to 20 linkage groups, representing 20 chromosomes, for the ‘T’ population (Tifrunner × GT‐C20) with a map length of 3120 cM and an average distance of 1.45 cM. The quantitative trait locus (QTL) analysis using high‐density genetic map and multiple season phenotyping data identified 35 main‐effect QTLs with phenotypic variation explained (PVE) from 6.32% to 47.63%. Among major‐effect QTLs mapped, there were two QTLs for ELS on B05 with 47.42% PVE and B03 with 47.38% PVE, two QTLs for LLS on A05 with 47.63% and B03 with 34.03% PVE and one QTL for TSWV on B09 with 40.71% PVE. The epistasis and environment interaction analyses identified significant environmental effects on these traits. The identified QTL regions had disease resistance genes including R‐genes and transcription factors. KASP markers were developed for major QTLs and validated in the population and are ready for further deployment in genomics‐assisted breeding in peanut.

The cultivated [Glycine max (L) Merr.] and wild [Glycine soja Siebold & Zucc.] soybean species comprise wide variation in seed composition traits. Compared to wild soybean, cultivated soybean contains low protein, high oil and high sucrose. In this study, an inter-specific population was derived from a cross between G. max (Williams 82) and G. soja (PI 483460B). This recombinant inbred line (RIL) population of 188 lines was sequenced at 0.3x depth. Based on 91,342 single nucleotide polymorphisms (SNPs), recombination events in RILs were defined, and a high-resolution bin map was developed (4,070 bins). In addition to bin mapping, QTL analysis for protein, oil and sucrose was performed using 3,343 polymorphic SNPs (3K-SNP), derived from Illumina Infinium BeadChip sequencing platform. The QTL regions from both platforms were compared and a significant concordance was observed between bin and 3K-SNP markers. Importantly, the bin map derived from next generation sequencing technology enhanced mapping resolution (from 1325 Kb to 50 Kb). A total of 5, 9 and 4 QTLs were identified for protein, oil and sucrose content, respectively and some of the QTLs coincided with soybean domestication related genomic loci. The major QTL for protein and oil was mapped on Chr. 20 (qPro_20) and suggested negative correlation between oil and protein. In terms of sucrose content, a novel and major QTL was identified on Chr. 8 (qSuc_08) and harbors putative genes involved in sugar transport. In addition, genome-wide association (GWAS) using 91,342 SNPs confirmed the genomic loci derived from QTL mapping. A QTL based haplotype using whole genome resequencing of 106 diverse soybean lines identified unique allelic variation in wild soybean that could be utilized to widen the genetic base in cultivated soybean.

Understanding how populations adapt to their environment is increasingly important to prevent biodiversity loss due to overexploitation and climate change. Here we studied the population structure and genetic basis of local adaptation of Atlantic horse mackerel, a commercially and ecologically important marine fish that has one of the widest distributions in the eastern Atlantic. We analyzed whole‐genome sequencing and environmental data of samples collected from the North Sea to North Africa and the western Mediterranean Sea. Our genomic approach indicated low population structure with a major split between the Mediterranean Sea and the Atlantic Ocean and between locations north and south of mid‐Portugal. Populations from the North Sea are the most genetically distinct in the Atlantic. We discovered that most population structure patterns are driven by a few highly differentiated putatively adaptive loci. Seven loci discriminate the North Sea, two the Mediterranean Sea, and a large putative inversion (9.9 Mb) on chromosome 21 underlines the north–south divide and distinguishes North Africa. A genome–environment association analysis indicates that mean seawater temperature and temperature range, or factors correlated to them, are likely the main environmental drivers of local adaptation. Our genomic data broadly support the current stock divisions, but highlight areas of potential mixing, which require further investigation. Moreover, we demonstrate that as few as 17 highly informative SNPs can genetically discriminate the North Sea and North African samples from neighboring populations. Our study highlights the importance of both, life history and climate‐related selective pressures in shaping population structure patterns in marine fish. It also supports that chromosomal rearrangements play a key role in local adaptation with gene flow. This study provides the basis for more accurate delineation of the horse mackerel stocks and paves the way for improving stock assessments.

Summary Moso bamboo (Phyllostachys edulis) known as Mao Zhu (MZ) in Chinese exhibits various forms with distinct morphological characteristics. However, the evolutionary relationship among MZ forms and the mechanisms of culm shape variation are still lacking. Here, the main differences among MZ forms were identified as culm shape variation, which were confirmed by analysing MZ forms (799 bamboo culms) and MZ (458 bamboo culms) populations. To unravel the genetic basis underlying the morphological variations, 20 MZ forms were subjected to whole‐genome resequencing. Further analysis yielded 3 230 107 high‐quality SNPs and uncovered low genetic diversity and high genotype heterozygosity associated with MZ forms' formation. By integrating the SNP data of 427 MZ individuals representing 15 geographic regions, the origins of eight MZ forms were successfully traced using the phylogenetic tree and the identified common heterozygous loci. Meanwhile, transcriptomic analysis was performed using shoots from MZ and its two forms with culm shape variation. The results, combined with genomic analyses, demonstrated that hormone signalling related genes played crucial roles in culm variation. Co‐expression network analysis uncovered genes associated with multiple plant hormone signal transduction, especially auxin and cytokinin were involved in culm shape variation. Furthermore, the regulatory relationships of a specific transcription factor and their target genes associated with auxin and ethylene signalling were validated by yeast one‐hybrid, electrophoretic mobility shift assays, and dual‐luciferase reporter. Overall, this study provides important insights into the culm shape variation formation in bamboo, which facilitates to breed new varieties with novel culms.

The influence of species life history traits and historical demography on contemporary connectivity is still poorly understood. However, these factors partly determine the evolutionary responses of species to anthropogenic landscape alterations. Genetic connectivity and its evolutionary outcomes depend on a variety of spatially dependent evolutionary processes, such as population structure, local adaptation, genetic admixture, and speciation. Over the last years, population genomic studies have been interrogating these processes with increasing resolution, revealing a large diversity of species responses to spatially structured landscapes. In parallel, multispecies meta‐analyses usually based on low‐genome coverage data have provided fundamental insights into the ecological determinants of genetic connectivity, such as the influence of key life history traits on population structure. However, comparative studies still lack a thorough integration of macro‐ and micro‐evolutionary scales to fully realize their potential. Here, I present how a comparative genomics framework may provide a deeper understanding of evolutionary process connectivity. This framework relies on coupling the inference of long‐term demographic and selective history with an assessment of the contemporary consequences of genetic connectivity. Standardizing this approach across several species occupying the same landscape should help understand how spatial environmental heterogeneity has shaped the diversity of historical and contemporary connectivity patterns in different taxa with contrasted life history traits. I will argue that a reasonable amount of genome sequence data can be sufficient to resolve and connect complex macro‐ and micro‐evolutionary histories. Ultimately, implementing this framework in varied taxonomic groups is expected to improve scientific guidelines for conservation and management policies.

Golden pompano (Trachinotus ovatus) is a rapidly growing marine aquaculture species along the southeast coast of China due to its favorable biological traits. However, the relatively short domestication history of marine species compared to terrestrial livestock and crops indicates untapped genetic potential. Therefore, selective breeding in marine aquaculture presents a significant opportunity for genetic improvement. This study aimed to establish a comprehensive genomic prediction to support the selection of new fast‐growing varieties of golden pompano. Body weight was selected as the primary trait for evaluating growth traits. Whole‐genome sequencing was performed on 692 samples, resulting in 4,886,850 high‐quality SNPs after filtering. Three SNP selection strategies were used for evaluating the genomic prediction accuracy, including the Evenly method, GWAS‐based method, and Random method. We addressed the issue of overestimation in the GWAS‐based method. After implementing cross‐validation, the GWAS‐based method demonstrated superior predictive accuracy across most SNP sets. Additionally, six breeding models were evaluated for their performance in genomic prediction, with GBLUP showing higher predictive ability. In terms of SNP density, we determined that 5000 SNPs selected via the Evenly method and 7000 SNPs selected via the GWAS‐based method represent optimal densities for accurately predicting body weight in golden pompano. These findings provide valuable insights for reducing breeding costs while improving selection accuracy, providing a practical strategy for the selection of golden pompano with economically valuable growth traits in aquaculture breeding programs.