Insights into genetic diversity and phenotypic variations in domestic geese through comprehensive population and pan-genome analysis

Background Domestic goose breeds are descended from either the Swan goose(Anser cygnoides)or the Greylag goose(Anser anser),exhibiting variations in body size,reproductive performance,egg production,feather color,and other phenotypic traits.Constructing a pan-genome facilitates a thorough identification of genetic variations,thereby deepening our comprehension of the molecular mechanisms underlying genetic diversity and phenotypic variability.Results To comprehensively facilitate population genomic and pan-genomic analyses in geese,we embarked on the task of 659 geese whole genome resequencing data and compiling a database of 155 RNA-seq samples.By constructing the pan-genome for geese,we generated non-reference contigs totaling 612 Mb,unveiling a collection of 2,813 novel genes and pinpointing 15,567 core genes,1,324 softcore genes,2,734 shell genes,and 878 cloud genes in goose genomes.Furthermore,we detected an 81.97 Mb genomic region showing signs of genome selection,encompassing the TGFBR2 gene correlated with variations in body weight among geese.Genome-wide association studies utilizing single nucleotide polymorphisms(SNPs)and presence-absence variation revealed significant genomic associations with various goose meat quality,reproductive,and body composition traits.For instance,a gene encoding the SVEP1 protein was linked to carcass oblique length,and a distinct gene-CDS haplotype of the SVEP1 gene exhibited an association with carcass oblique length.Notably,the pan-genome analysis revealed enrichment of variable genes in the“hair follicle maturation”Gene Ontology term,potentially linked to the selection of feather-related traits in geese.A gene presence-absence variation analysis suggested a reduced frequency of genes associated with“regulation of heart contraction”in domesticated geese compared to their wild counterparts.Our study provided novel insights into gene expression features and functions by integrating gene expression patterns across multiple organs and tissues in geese and analyzing population variation.Conclusion This accomplishment originates from the discernment of a multitude of selection signals and candidate genes associated with a wide array of traits,thereby markedly enhancing our understanding of the processes underlying domestication and breeding in geese.Moreover,assembling the pan-genome for geese has yielded a comprehensive apprehension of the goose genome,establishing it as an indispensable asset poised to offer innovative viewpoints and make substantial contributions to future geese breeding initiatives.

The value of community science data to analyze long-term avian trends in understudied regions:The state of birds in Türkiye

Recent studies have revealed concerning declines in bird populations in Europe and other parts of the world.In understudied but biodiverse regions,especially those that are located along key migratory flyways,there is an unmet need to evaluate the status of resident and migratory birdlife for avian conservation ecology.This is especially urgent at a time when recent regional studies have highlighted the scale of the decline of the European and Palearctic avifauna.Rapidly growing community science datasets may help bridge the gaps in our understanding of long-term regional avifaunal trends.In this study,we used eBird data submitted by observers in Türkiye to undertake the first long-term assessment of the state of the country’s birds from 2001 to 2022.We evaluated population trends based on presence-absence data of species to determine if any birds have significantly increased or decreased in the country so far this century.We provide a list of trends for 418 bird species that had large enough sample sizes of eBird observations from Türkiye,and highlight which species have significantly declined or increased.We found that 63 species have significantly declined in detection while 120 have significantly increased during the study period.Our findings provide a baseline for the future monitoring of Türkiye’s birds and help contextualize population changes of birds in Türkiye against those occurring at the continental(Palearctic)scale.Additionally,we include movement classifications for all of the bird species in this study.We also provide a framework to effectively use eBird data to assess long-term avifaunal changes at the country-level in other understudied regions.Finally,we highlight ways in which eBirders in Türkiye and elsewhere can strengthen the quality and value of community ornithology data for population assessments and avian conservation ecology.

Comparative performance assessment of landslide susceptibility models with presence-only,presenceabsence,and pseudo-absence data

The quality of the data for statistical methods plays an important role in landslide susceptibility mapping.How different data types influence the performance of landslide susceptibility maps is worth studying.The goal of this study was to explore the effects of different data types namely,presence-only(PO),presence-absence(PA),and pseudo-absence(PAs) data,on the predictive capability of landslide susceptibility mapping.This was completed by conducting a case study in the landslide-prone Honghe County in the Yunnan Province of China.A total of 428 landslide PO data points were selected.An equivalent number of nonlandslide locations were generated as PA data by random sampling,and 10,000 sites were uniformly selected at random from each region as PAs data.Three landslide susceptibility models,namely the information value model(IVM),logistic regression(LR) model,and maximum entropy(MaxEnt) model,corresponding to the three data types were investigated.Additionally,the area under the receiver operating characteristic curves(ROC-AUC),seven statistical indices(i.e.accuracy,sensibility,falsepositive rate,specificity,precision,Kappa,and Fmeasure),and a landslide density analysis were used to evaluate model performance regarding landslide susceptibility mapping.Our results indicated that the MaxEnt model using PAs data performed the best and had the highest fitness with the highest ROC-AUC values and statistical indices,followed by the IVM model with only landslide data(PO),and the LR model using PA data.Using PAs data avoided the inherent over-predictive shortcomings of PO data by limiting the predicted area of high-landslide susceptibility.Additionally,the random sampling design of landslide PA data increased the uncertainty of landslide susceptibility mapping and influenced the performance of the model.Therefore,our results suggested that the PAs data sampling provided a useful data type in the absence of high-quality data.Finally,we summarized the principles,advantages,and disadvantages of the three data types to assist with model optimization and the improvement of predicted performance and fitness.

Building a sequence map of the pig pan-genome from multiple de novo assemblies and Hi-C data

Pigs were domesticated independently in the Near East and China,indicating that a single reference genome from one individual is unable to represent the full spectrum of divergent sequences in pigs worldwide.Therefore,12 de novo pig assemblies from Eurasia were compared in this study to identify the missing sequences from the reference genome.As a result,72.5 Mb of nonredundant sequences(~3% of the genome)were found to be absent from the reference genome(Sscrofa11.1)and were defined as pan-sequences.Of the pan-sequences,9.0 Mb were dominant in Chinese pigs,in contrast with their low frequency in European pigs.One sequence dominant in Chinese pigs contained the complete genic region of the tazarotene-induced gene 3(TIG3)gene which is involved in fatty acid metabolism.Using flanking sequences and Hi-C based methods,27.7% of the sequences could be anchored to the reference genome.The supplementation of these sequences could contribute to the accurate interpretation of the 3D chromatin structure.A web-based pan-genome database was further provided to serve as a primary resource for exploration of genetic diversity and promote pig breeding and biomedical research.

Deletion of a Stay-Green Gene Associates with Adaptive Selection in Brassica napus

Chlorophyll levels provide important imrormation about plant growth and physiological plasticity in response to changing environments. The stay-green gene NON-YELLOWING 1 （NYE1） is believed to regu-late chlorophyll degradation during senescence, concomitantly affecting the disassembly of the light- harvesting complex and hence indirectly influencing photosynthesis. We identified Brassica napus acces- sions carrying an NYE1 deletion associated with increased chlorophyll content, and with upregulated expression of light-harvesting complex and photosynthetic reaction center （PSI and PSII） genes. Compar- ative analysis of the seed oil content of accessions with related genetic backgrounds revealed that the B. napus NYE1 gene deletion （bnnyel） affected oil accumulation, and linkage disequilibrium signatures suggested that the locus has been subject to artificial selection by breeding in oilseed B. napus forms. Comparative analysis of haplotype diversity groups （haplogroups） between three different ecotypes of the allopolyploid B. napus and its A-subgenome diploid progenitor, Brassica rapa, indicated that introgres- sion of the bnnyel deletion from Asian B. rapa into winter-type B. napus may have simultaneously improved its adaptation to cooler environments experienced by autumn-sown rapeseed.