Identification of Selection Signatures in Commercial Asian Rice Subspecies Deciphered Selection Footprints for Four Overrepresented Biological Processes

Abstract BackgroundSelective breeding pressures have led to gradual genomic changes in Asian commercial rice, which have shaped selection footprints on its genome level. Tracing genomic selection footprints might be illuminative for better understanding of recent selection breeding objectives, and how breeding strategies have formed the Asian commercial rice genome. ResultsIn this study, the genotypic information (HDRA 700K) of four Asian commercial rice subspecies including Indica (n=498), Aus (n=187), Temperate japonica (n=241), and Tropical japonica (n=361) were downloaded from Rice Diversity Project database (http://www.ricediversity.org) to detect selection signatures by employing the Z-transformed of fixation index and Tajima’s D test, based on a sliding window approach. Although we could not identify overrepresented genomic regions underlying selection pressure among all aforementioned Asian commercial rice subspecies, interestingly, our findings revealed four overrepresented biological processes underlying selection pressure including proteolysis (GO:0006508), phosphorylation (GO:0016310), protein catabolic process (GO:0030163), and transmembrane transport (GO:0055085) that might be associated with immunity, senescing leaves, transporting, and absorption of ions. ConclusionsThese results can provide knowledge on how breeding efforts shaped the Asian commercial rice subspecies genome, and which genomic regions of these subspecies have been targeted in recent decades.

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Identifying genomic regions and candidate genes selected during the breeding of rice in Vietnam

10.1101/2021.08.04.455072 ◽

2021 ◽

Author(s):

Janet Higgins ◽

Bruno Santos ◽

Tran Dang Khanh ◽

Khuat Huu Trung ◽

Tran Duy Duong ◽

...

Keyword(s):

Candidate Genes ◽

Continuous Improvement ◽

Rice Genome ◽

Selection Signatures ◽

Genome Scanning ◽

Selective Pressures ◽

Rice Landraces ◽

Rich Diversity ◽

Genomic Regions ◽

New Generation

Background and aims: Vietnam harnesses a rich diversity of rice landraces adapted to a broad range of conditions, which constitute a largely untapped source of genetic diversity for the continuous improvement of rice cultivars. We previously identified a strong population structure in Vietnamese rice, which is captured in five Indica and four Japonica subpopulations, including an outlying Indica-5 group. Here, we leveraged on that strong differentiation, and the 672 rice genomes generated, to identify genes within genomic regions putatively selected during domestication and breeding of rice in Vietnam. Methodology: We identified significant distorted patterns in allele frequency (XP-CLR method) and population differentiation scores (FST), resulting from differential selective pressures between native subpopulations, and compared them with QTLs previously identified by GWAS in the same panel. We particularly focused on the outlying Indica-5 subpopulation because of its likely novelty and differential evolution. Results: We identified selection signatures in each of the Vietnamese subpopulations and carried out a comprehensive annotation of the 52 regions selected in Indica-5, which represented 8.1% of the rice genome. We annotated the 4,576 genes in these regions, verified the overlap with QTLs identified in the same diversity panel and the comparison with a FST analysis between subpopulations, to select sixty-five candidate genes as promising breeding targets, several of which harboured alleles with non-synonymous substitutions. Conclusions: Our results highlight genomic differences between traditional Vietnamese landraces, which are likely the product of adaption to multiple environmental conditions and regional culinary preferences in a very diverse country. We also verified the applicability of this genome scanning approach to identify potential regions harbouring novel loci and alleles to breed a new generation of sustainable and resilient rice.

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Selection signatures in two oldest Russian native cattle breeds revealed using high-density single nucleotide polymorphism analysis

PLoS ONE ◽

10.1371/journal.pone.0242200 ◽

2020 ◽

Vol 15 (11) ◽

pp. e0242200

Author(s):

Natalia Anatolievna Zinovieva ◽

Arsen Vladimirovich Dotsev ◽

Alexander Alexandrovich Sermyagin ◽

Tatiana Evgenievna Deniskova ◽

Alexandra Sergeevna Abdelmanova ◽

...

Keyword(s):

Single Nucleotide Polymorphism ◽

Candidate Genes ◽

High Density ◽

Fixation Index ◽

Nucleotide Polymorphism ◽

Selection Signatures ◽

Single Nucleotide ◽

Cattle Breeds ◽

Native Cattle ◽

Genomic Regions

Native cattle breeds can carry specific signatures of selection reflecting their adaptation to the local environmental conditions and response to the breeding strategy used. In this study, we comprehensively analysed high-density single nucleotide polymorphism (SNP) genotypes to characterise the population structure and detect the selection signatures in Russian native Yaroslavl and Kholmogor dairy cattle breeds, which have been little influenced by introgression with transboundary breeds. Fifty-six samples of pedigree-recorded purebred animals, originating from different breeding farms and representing different sire lines, of the two studied breeds were genotyped using a genome-wide bovine genotyping array (Bovine HD BeadChip). Three statistical analyses—calculation of fixation index (FST) for each SNP for the comparison of the pairs of breeds, hapFLK analysis, and estimation of the runs of homozygosity (ROH) islands shared in more than 50% of animals—were combined for detecting the selection signatures in the genome of the studied cattle breeds. We confirmed nine and six known regions under putative selection in the genomes of Yaroslavl and Kholmogor cattle, respectively; the flanking positions of most of these regions were elucidated. Only two of the selected regions (localised on BTA 14 at 24.4–25.1 Mbp and on BTA 16 at 42.5–43.5 Mb) overlapped in Yaroslavl, Kholmogor and Holstein breeds. In addition, we detected three novel selection sweeps in the genome of Yaroslavl (BTA 4 at 4.74–5.36 Mbp, BTA 15 at 17.80–18.77 Mbp, and BTA 17 at 45.59–45.61 Mbp) and Kholmogor breeds (BTA 12 at 82.40–81.69 Mbp, BTA 15 at 16.04–16.62 Mbp, and BTA 18 at 0.19–1.46 Mbp) by using at least two of the above-mentioned methods. We expanded the list of candidate genes associated with the selected genomic regions and performed their functional annotation. We discussed the possible involvement of the identified candidate genes in artificial selection in connection with the origin and development of the breeds. Our findings on the Yaroslavl and Kholmogor breeds obtained using high-density SNP genotyping and three different statistical methods allowed the detection of novel putative genomic regions and candidate genes that might be under selection. These results might be useful for the sustainable development and conservation of these two oldest Russian native cattle breeds.

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High-resolution Introgressive Region Map Reveals Spatiotemporal Genome Evolution in Asian Rice Domestication

10.1101/829168 ◽

2019 ◽

Author(s):

Hajime Ohyanagi ◽

Kosuke Goto ◽

Sónia Negrão ◽

Rod A. Wing ◽

Mark A. Tester ◽

...

Keyword(s):

Molecular Mechanisms ◽

Rice Genome ◽

Definitive Answer ◽

Asian Rice ◽

Multiple Origins ◽

Genome Wide ◽

Time Calibration ◽

History Of ◽

Genomic Regions ◽

Rice Domestication

AbstractDomestication is anthropogenic evolution that fulfills mankind’s critical food demand. As such, elucidating the molecular mechanisms behind this process promotes the development of future new food resources including crops. With the aim of understanding the long-term domestication process of Asian rice and by employing the Oryza sativa subspecies (indica and japonica) as an Asian rice domestication model, we scrutinized past genomic introgressions between them as traces of domestication. Here we show the genome-wide introgressive region (IR) map of Asian rice, by utilizing 4,587 accession genotypes with a stable outgroup species, particularly at the finest resolution through a machine learning-aided method. The IR map revealed that 14.2% of the rice genome consists of IRs, including both wide IRs (recent) and narrow IRs (ancient). This introgressive landscape with their time calibration indicates that introgression events happened in multiple genomic regions over multiple periods. From the correspondence between our wide IRs and the so-called selective sweep regions, we provide a definitive answer to a long-standing controversy over the evolutionary origin of Asian rice domestication, single or multiple origins: It heavily depends upon which regions you pay attention to, implying that wider genomic regions represent immediate short history of Asian rice domestication as a likely support to the single origin, while its ancient history is interspersed in narrower traces throughout the genome as a possible support to the multiple origin.

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Assessment of genomic changes in a CRISPR/Cas9 Phaeodactylum tricornutum mutant through whole genome resequencing

PeerJ ◽

10.7717/peerj.5507 ◽

2018 ◽

Vol 6 ◽

pp. e5507 ◽

Cited By ~ 8

Author(s):

Monia Teresa Russo ◽

Riccardo Aiese Cigliano ◽

Walter Sanseverino ◽

Maria Immacolata Ferrante

Keyword(s):

Phaeodactylum Tricornutum ◽

Thalassiosira Pseudonana ◽

Model Organisms ◽

Whole Genome ◽

Major Drawback ◽

Genomic Changes ◽

Short Palindromic Repeat ◽

Genome Level ◽

Whole Genome Resequencing ◽

Genomic Regions

The clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 system, co-opted from a bacterial defense natural mechanism, is the cutting edge technology to carry out genome editing in a revolutionary fashion. It has been shown to work in many different model organisms, from human to microbes, including two diatom species, Phaeodactylum tricornutum and Thalassiosira pseudonana. Transforming P. tricornutum by bacterial conjugation, we have performed CRISPR/Cas9-based mutagenesis delivering the nuclease as an episome; this allowed for avoiding unwanted perturbations due to random integration in the genome and for excluding the Cas9 activity when it was no longer required, reducing the probability of obtaining off-target mutations, a major drawback of the technology. Since there are no reports on off-target occurrence at the genome level in microalgae, we performed whole-genome Illumina sequencing and found a number of different unspecific changes in both the wild type and mutant strains, while we did not observe any preferential mutation in the genomic regions in which off-targets were predicted. Our results confirm that the CRISPR/Cas9 technology can be efficiently applied to diatoms, showing that the choice of the conjugation method is advantageous for minimizing unwanted changes in the genome of P. tricornutum.

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Genome-Wide Analyses Identifies Known and New Markers Responsible of Chicken Plumage Color

Animals ◽

10.3390/ani10030493 ◽

2020 ◽

Vol 10 (3) ◽

pp. 493

Author(s):

Salvatore Mastrangelo ◽

Filippo Cendron ◽

Gianluca Sottile ◽

Giovanni Niero ◽

Baldassare Portolano ◽

...

Keyword(s):

Genome Wide Association Study ◽

Snp Array ◽

Fixation Index ◽

Phenotypic Traits ◽

Plumage Color ◽

Phenotypic Marker ◽

Genome Wide ◽

A Genome ◽

The Difference ◽

Genomic Regions

Through the development of the high-throughput genotyping arrays, molecular markers and genes related to phenotypic traits have been identified in livestock species. In poultry, plumage color is an important qualitative trait that can be used as phenotypic marker for breed identification. In order to assess sources of genetic variation related to the Polverara chicken breed plumage colour (black vs. white), we carried out a genome-wide association study (GWAS) and a genome-wide fixation index (FST) scan to uncover the genomic regions involved. A total of 37 animals (17 white and 20 black) were genotyped with the Affymetrix 600 K Chicken single nucleotide polymorphism (SNP) Array. The combination of results from GWAS and FST revealed a total of 40 significant markers distributed on GGA 01, 03, 08, 12 and 21, and located within or near known genes. In addition to the well-known TYR, other candidate genes have been identified in this study, such as GRM5, RAB38 and NOTCH2. All these genes could explain the difference between the two Polverara breeds. Therefore, this study provides the basis for further investigation of the genetic mechanisms involved in plumage color in chicken.

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KRAS Promoter G-Quadruplexes from Sequences of Different Length: A Physicochemical Study

International Journal of Molecular Sciences ◽

10.3390/ijms22010448 ◽

2021 ◽

Vol 22 (1) ◽

pp. 448

Author(s):

Federica D’Aria ◽

Bruno Pagano ◽

Luigi Petraccone ◽

Concetta Giancola

Keyword(s):

Thermodynamic Stability ◽

Drug Targets ◽

Promoter Sequence ◽

Physicochemical Study ◽

Biological Processes ◽

Scanning Calorimetry ◽

Binding Properties ◽

Anticancer Compounds ◽

Nmr Structures ◽

Genomic Regions

DNA G-quadruplexes (G4s) form in relevant genomic regions and intervene in several biological processes, including the modulation of oncogenes expression, and are potential anticancer drug targets. The human KRAS proto-oncogene promoter region contains guanine-rich sequences able to fold into G4 structures. Here, by using circular dichroism and differential scanning calorimetry as complementary physicochemical methodologies, we compared the thermodynamic stability of the G4s formed by a shorter and a longer version of the KRAS promoter sequence, namely 5′-AGGGCGGTGTGGGAATAGGGAA-3′ (KRAS 22RT) and 5′-AGGGCGGTGTGGGAAGAGGGAAGAGGGGGAGG-3′ (KRAS 32R). Our results show that the unfolding mechanism of KRAS 32R is more complex than that of KRAS 22RT. The different thermodynamic stability is discussed based on the recently determined NMR structures. The binding properties of TMPyP4 and BRACO-19, two well-known G4-targeting anticancer compounds, to the KRAS G4s were also investigated. The present physicochemical study aims to help in choosing the best G4 target for potential anticancer drugs.

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46 Footprints of Selection in Angus and Hanwoo Beef Cattle Using Imputed Whole Genome Sequence Data

Journal of Animal Science ◽

10.1093/jas/skab235.042 ◽

2021 ◽

Vol 99 (Supplement_3) ◽

pp. 25-25

Author(s):

Muhammad Yasir Nawaz ◽

Rodrigo Pelicioni Savegnago ◽

Cedric Gondro

Keyword(s):

Beef Cattle ◽

Genome Sequence ◽

Sequence Data ◽

Whole Genome Sequence ◽

Fixation Index ◽

Whole Genome ◽

Extended Haplotype Homozygosity ◽

Extended Haplotype ◽

Genome Sequence Data ◽

Genomic Regions

Abstract In this study, we detected genome wide footprints of selection in Hanwoo and Angus beef cattle using different allele frequency and haplotype-based methods based on imputed whole genome sequence data. Our dataset included 13,202 Angus and 10,437 Hanwoo animals with 10,057,633 and 13,241,550 imputed SNPs, respectively. A subset of data with 6,873,624 common SNPs between the two populations was used to estimate signatures of selection parameters, both within (runs of homozygosity and extended haplotype homozygosity) and between (allele fixation index, extended haplotype homozygosity) the breeds in order to infer evidence of selection. We observed that correlations between various measures of selection ranged between 0.01 to 0.42. Assuming these parameters were complementary to each other, we combined them into a composite selection signal to identify regions under selection in both beef breeds. The composite signal was based on the average of fractional ranks of individual selection measures for every SNP. We identified some selection signatures that were common between the breeds while others were independent. We also observed that more genomic regions were selected in Angus as compared to Hanwoo. Candidate genes within significant genomic regions may help explain mechanisms of adaptation, domestication history and loci for important traits in Angus and Hanwoo cattle. In the future, we will use the top SNPs under selection for genomic prediction of carcass traits in both breeds.

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149 Integration of Selection Signatures Analyses and Weighted Single-step GWAS to Prioritize Candidate Genes for Body Conformation Traits in Pigs

Journal of Animal Science ◽

10.1093/jas/skab235.138 ◽

2021 ◽

Vol 99 (Supplement_3) ◽

pp. 76-77

Author(s):

Seyed Milad Vahedi ◽

Siavash Salek Ardestani ◽

Duy Ngoc Do ◽

Karim Karimi ◽

Younes Miar

Keyword(s):

Candidate Genes ◽

Complex Traits ◽

Body Height ◽

Single Step ◽

Fixation Index ◽

Nucleotide Polymorphisms ◽

Selection Signatures ◽

Body Conformation ◽

Yorkshire Pigs ◽

Estimated Breeding Values

Abstract Body conformation traits such as body height (BH) and body length (BL) have been included in the swine industry’s selection criteria. The objective of this study was to identify the quantitative trait loci (QTLs) and candidate genes for pig conformation traits using an integration of selection signatures analyses and weighted single-step GWAS (WssGWAS). Body measurement records of 5,593 Yorkshire pigs of which 598 animals were genotyped with Illumina 50K panel were used. Estimated breeding values (EBVs) for BH and BL were computed using univariate animal models. Genotyped animals were grouped into top 5% and bottom 5% based on their EBVs, and selection signatures analyses were performed using fixation index (Fst), FLK, hapFLK, and Rsb statistics, which were then combined as a Mahalanobis distance (Md) framework. The WssGWAS was conducted to detect the single nucleotide polymorphisms (SNPs) associated with the studied traits. The top 1% SNPs (n=530) from Md distribution that overlapped with the top 1% SNPs from WssGWAS (n = 530) were used to detect the candidate genes. A total of 31 and six overlapped SNPs were found to be associated with BH and BL, respectively. Several candidate genes were identified for BH (PARVA, DCDC1, SYT1, CASTOR2, RGSL1, RGS8, RBMS3, TGFBR2, and HS6ST1) and BL (SNTB1, AK7, PAPOLA, KSR1, CHODL, and BMP2), explaining 2.58% and 0.42% of the trait’s genetic variation, respectively. Our results indicated that integrating data from the signatures of selection tests with WssGWAS could help elucidate genomic regions underlying complex traits.

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148 Multiple Dysregulated Novel Pathways and Genes in Aleutian Mink Disease Revealed by Selection Signatures and Gene Network Analyses Using Whole-genome Sequence Data

Journal of Animal Science ◽

10.1093/jas/skab235.137 ◽

2021 ◽

Vol 99 (Supplement_3) ◽

pp. 76-76

Author(s):

Seyed Milad Vahedi ◽

Karim Karimi ◽

Siavash Salek Ardestani ◽

Younes Miar

Keyword(s):

Sequence Data ◽

American Mink ◽

Enrichment Analysis ◽

Whole Genome Sequence ◽

Fixation Index ◽

Pathway Enrichment Analysis ◽

Whole Genome ◽

Nucleotide Polymorphisms ◽

Network Analyses ◽

Genome Level

Abstract Aleutian disease (AD) is a chronic persistent infection in domestic mink caused by Aleutian mink disease virus (AMDV). Female mink’s fertility and pelt quality depression are the main reasons for the AD’s negative economic impacts on the mink industry. A total number of 79 American mink from the Canadian Center for Fur Animal Research at Dalhousie University (Truro, NS, Canada) were classified based on the results of counter immunoelectrophoresis (CIEP) tests into two groups of positive (n = 48) and negative (n = 31). Whole-genome sequences comprising 4,176 scaffolds and 8,039,737 single nucleotide polymorphisms (SNPs) were used to trace the selection footprints for response to AMDV infection at the genome level. Window-based fixation index (Fst) and nucleotide diversity (θπ) statistics were estimated to compare positive and negative animals’ genomes. The overlapped top 1% genomic windows between two statistics were considered as potential regions underlying selection pressures. A total of 98 genomic regions harboring 33 candidate genes were detected as selective signals. Most of the identified genes were involved in the development and functions of immune system (PPP3CA, SMAP2, TNFRSF21, SKIL, and AKIRIN2), musculoskeletal system (COL9A2, PPP1R9A, ANK2, AKAP9, and STRIT1), nervous system (ASCL1, ZFP69B, SLC25A27, MCF2, and SLC7A14), reproductive system (CAMK2D, GJB7, SSMEM1, C6orf163), liver (PAH and DPYD), and lung (SLC35A1). Gene-expression network analysis showed the interactions among 27 identified genes. Moreover, pathway enrichment analysis of the constructed genes network revealed significant oxytocin (KEGG: hsa04921) and GnRH signaling (KEGG: hsa04912) pathways, which are likely to be impaired by AMDV leading to dams’ fecundity reduction. These results provided a perspective to the genetic architecture of response to AD in American mink and novel insight into the pathogenesis of AMDV.

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Detection and evaluation of selection signatures in sheep

Pesquisa Agropecuária Brasileira ◽

10.1590/s0100-204x2018000500001 ◽

2018 ◽

Vol 53 (5) ◽

pp. 527-539 ◽

Cited By ~ 2

Author(s):

Tiago do Prado Paim ◽

Patrícia Ianella ◽

Samuel Rezende Paiva ◽

Alexandre Rodrigues Caetano ◽

Concepta Margaret McManus Pimentel

Keyword(s):

Statistical Methods ◽

Phenotypic Diversity ◽

Selection Process ◽

Genomic Data ◽

Research Field ◽

Economic Traits ◽

Selection Signatures ◽

Important Species ◽

Challenges And Opportunities ◽

Genomic Regions

Abstract: The recent development of genome-wide single nucleotide polymorphism (SNP) arrays made it possible to carry out several studies with different species. The selection process can increase or reduce allelic (or genic) frequencies at specific loci in the genome, besides dragging neighboring alleles in the chromosome. This way, genomic regions with increased frequencies of specific alleles are formed, caracterizing selection signatures or selective sweeps. The detection of these signatures is important to characterize genetic resources, as well as to identify genes or regions involved in the control and expression of important production and economic traits. Sheep are an important species for theses studies as they are dispersed worldwide and have great phenotypic diversity. Due to the large amounts of genomic data generated, specific statistical methods and softwares are necessary for the detection of selection signatures. Therefore, the objectives of this review are to address the main statistical methods and softwares currently used for the analysis of genomic data and the identification of selection signatures; to describe the results of recent works published on selection signatures in sheep; and to discuss some challenges and opportunities in this research field.

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