摘 要: 旨在分析小骨山羊群體的遺傳多樣性,為明確其是否為新種質(zhì)資源提供理論依據(jù)。本研究以小骨山羊、河西絨山羊和內(nèi)蒙古絨山羊(阿爾巴斯型)為研究對(duì)象,每個(gè)群體選取20只成年健康母羊,使用SLAF-seq技術(shù)檢測(cè)全基因組范圍內(nèi)核苷酸多態(tài)性(SNPs)。遺傳多樣性通過使用perl編程計(jì)算次要等位基因頻率(MAF)、觀測(cè)雜合度(Ho)、期望雜合度(He)、基因多樣性指數(shù)(Nei)、多態(tài)信息含量(PIC)和香濃維納指數(shù)(SHI);使用PopLDdecay進(jìn)行連鎖不平衡分析(LD);使用VCFtools計(jì)算群體分化指數(shù)(Fst)。通過使用EIGENSOFT進(jìn)行主成分分析(PCA)、MEGA X構(gòu)建NJ樹和ADMIXTURE進(jìn)行群體結(jié)構(gòu)分析。通過使用PLINK計(jì)算IBS距離、使用GCTA計(jì)算親緣關(guān)系并構(gòu)建矩陣。結(jié)果,共檢測(cè)到5 253 776個(gè)SNPs,大部分位于基因間區(qū)。小骨山羊除Ho(0.197)外,其余遺傳多樣性指標(biāo)最高。小骨山羊平均MAF、He、Nei、PIC、SHI分別為0.216、0.302、0.312、0.247、0.466。LD分析表明,小骨山羊r2最高,衰減速度最慢。Fst分析顯示,小骨山羊與河西絨山羊分化水平低(0.043),與內(nèi)蒙古絨山羊(阿爾巴斯型)分化水平中等(0.052)。PCA分析顯示,小骨山羊與河西絨山羊、內(nèi)蒙古絨山羊(阿爾巴斯型)較為聚集,從PC1>0可以將部分小骨山羊與其它群體區(qū)分。NJ樹結(jié)果表明,大部分小骨山羊匯聚為獨(dú)立的一支,其余存在混群現(xiàn)象。群體結(jié)構(gòu)分析顯示,K=1為最佳分群數(shù),小骨山羊有獨(dú)特的遺傳結(jié)構(gòu)。IBS距離矩陣和親緣關(guān)系G矩陣顯示出相同的結(jié)果,3個(gè)群體之間親緣關(guān)系較遠(yuǎn),小骨山羊群體內(nèi)親緣關(guān)系較近。本研究基于SLAF-seq獲得SNPs數(shù)據(jù)分析小骨山羊遺傳多樣性和群體遺傳結(jié)構(gòu)。結(jié)果表明上述結(jié)果提示,小骨山羊與河西絨山羊分化程度低,與內(nèi)蒙古絨山羊(阿爾巴斯型)呈中等分化。小骨山羊的遺傳多樣性相對(duì)其它兩個(gè)群體較高,但是存在選擇壓力和群體規(guī)模小的問題。小骨山羊群體部分個(gè)體間親緣關(guān)系較近,存在近交現(xiàn)象。本研究為小骨山羊的合理開發(fā)利用提供理論依據(jù)。
關(guān)鍵詞: 小骨山羊;種質(zhì)資源;遺傳多樣性;群體遺傳結(jié)構(gòu);簡(jiǎn)化基因組測(cè)序
中圖分類號(hào):
S827.2"""" 文獻(xiàn)標(biāo)志碼:A"""" 文章編號(hào): 0366-6964(2025)03-1170-10
收稿日期:2024-09-18
基金項(xiàng)目:甘肅省2022年農(nóng)業(yè)種質(zhì)資源普查項(xiàng)目(GSCQ-2022-03);農(nóng)業(yè)農(nóng)村部政府購(gòu)買服務(wù)合同項(xiàng)目(19221204);中央財(cái)政農(nóng)業(yè)產(chǎn)業(yè)發(fā)展資金項(xiàng)目“甘肅省羊遺傳資源普查”(CFCAD2023-019)
作者簡(jiǎn)介:王浩宇(2001-),男,甘肅嘉峪關(guān)人,碩士生,主要從事羊生產(chǎn)研究,E-mail: 1415600198@qq.com
*通信作者:馬友記,主要從事羊生產(chǎn)研究,E-mail: yjma@gsau.edu.cn
Population Genetic Diversity and Population Structure Analysis of Small-boned Goat Based
on Specific-Locus Amplified Fragment Sequencing
WANG" Haoyu, MA" Keyan, LI" Taotao, LI" Dengpan, ZHAO" Qing, MA" Youji*
(College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070," China)
Abstract: The aim of this study was to analyze the genetic diversity and population genetic structure of the Small-boned goat population, and to provide a theoretical basis for clarifying whether it is a new germplasm resource. In this study, the Small-boned goats, Hexi cashmere goats and Inner Mongolia cashmere goats (Albas) were used as subjects, 20 adult healthy ewes were selected from each group. DNA was extracted from 5 mL of blood collected from the jugular vein, and Genome-wide nucleotide polymorphisms (SNPs) were detected using the SLAF-seq technique. Genetic diversity was calculated by using perl programming for minor allele frequency (MAF), observed heterozygosity (Ho), expected heterozygosity (He), Nei diversity index (Nei), polymorphic information content (PIC), and Shannon Wiener index (SHI); PopLDdecay was used for linkage disequilibrium analysis (LD); and VCFtools was used for population differentiation index (Fst). Population genetic structure was illustrated by principal component analysis (PCA) using EIGENSOFT, construction of NJ trees by MEGA X and population structure analysis by ADMIXTURE. Kinship was illustrated by calculating IBS distances using PLINK, calculating kinship using GCTA and constructing matrices. A total of 5 253 776 SNPs were detected, most of which were located in the intergenic region. Small-boned goats had the highest genetic diversity indexes except Ho (0.197). The mean MAF, He, Nei, PIC, and SHI of Small-boned goats were 0.216, 0.302, 0.312, 0.247, and 0.466, respectively. LD analysis showed that Small-boned goats had the highest r2 and the slowest rate of decay. Fst showed that the Small-boned goat had a low level of differentiation from the Hexi cashmere goat (0.043) and a medium level of differentiation from the Inner Mongolian cashmere goat (Albas, 0.052). PCA analysis showed that Small-boned goats were more aggregated with Hexi cashmere goats and Inner Mongolian cashmere goats (Albas), and some of the Small-boned goats could be distinguished from the other groups from PC1gt;0. The results of the NJ-tree showed that the majority of the Small-boned goats converged into independent, and the rest had mixed groups. The population structure analysis showed that K=1 was the optimal number of groups. Small-boned goats had a unique genetic structure. The IBS distance matrix and the kinship G matrix showed the same results, with the 3 groups being more distantly related to each other and more closely related within the Small-boned goat groups. In this study, the genetic diversity and population genetic structure of Small-boned goats were analyzed based on SNPs data obtained by SLAF-seq. The results showed that the Small-boned goat was lowly differentiated from the Hexi cashmere goat and moderately differentiated from the Inner Mongolian cashmere goat (Albas). The genetic diversity of Small-boned goats was higher than that of the other two populations, but there were problems of selection pressure and small population size. Some of the individuals in the Small-boned goat population were closely related to each other, and inbreeding existed. This study provides a theoretical basis for the rational development and utilization of the Small-boned goat.
Keywords: Small-boned goat; germplasm resources; genetic diversity; population genetic structure; specific-locus amplified fragment sequencing
*Corresponding author:MA Youji, E-mail: yjma@gsau.edu.cn
種質(zhì)資源在農(nóng)業(yè)發(fā)展中有舉足輕重的地位,其不僅對(duì)畜牧業(yè)有40%的貢獻(xiàn)率[1],而且對(duì)培育優(yōu)良品種、提高經(jīng)濟(jì)效益和參與國(guó)際市場(chǎng)競(jìng)爭(zhēng)有深遠(yuǎn)影響[2]。因此充分挖掘、合理利用我國(guó)地方品種對(duì)實(shí)現(xiàn)我國(guó)種質(zhì)資源突破有實(shí)踐意義。2021年在開展第三次全國(guó)畜禽遺傳資源普查中,在蘭州什川大山深處發(fā)現(xiàn)約8 000多只常年放牧、體型明顯偏小、肉質(zhì)優(yōu)良的絨山羊群體,當(dāng)?shù)胤Q小骨山羊。成年小骨山羊公羊體重比河西絨山羊約低20%,比內(nèi)蒙古絨山羊(阿爾巴斯型)約低13%,肉骨比約為7,骨頭重量明顯偏輕。因其飼養(yǎng)環(huán)境較為封閉,小骨山羊群體的遺傳背景尚未有研究。
簡(jiǎn)化基因組測(cè)序(specific-locus amplified fragment sequencing, SLAF-seq)是高通量測(cè)序技術(shù),能獲得分布均勻的單核苷酸多態(tài)性(SNP)標(biāo)記[3]。在評(píng)估群體結(jié)構(gòu)和遺傳多樣性的研究中,相比于微衛(wèi)星標(biāo)記[4-5]和線粒體DNA標(biāo)記[6-7],SNP標(biāo)記擁有密度高、分布廣、多態(tài)性高和遺傳穩(wěn)定等優(yōu)點(diǎn);相比于全基因組重測(cè)序[8-9]和SNP芯片[10-11],SLAF-seq技術(shù)擁有測(cè)序費(fèi)用低、基因組復(fù)雜程度低和測(cè)序深度達(dá)到6×以上時(shí)基因分型準(zhǔn)確等優(yōu)點(diǎn)[3]。SLAF-seq技術(shù)在評(píng)估綿山羊群體遺傳結(jié)構(gòu)和遺傳多樣性的研究領(lǐng)域已有應(yīng)用,Zhou等[12]以分布在四川的5個(gè)綿羊品種為研究對(duì)象,基于SLAF-seq技術(shù)分析其群體結(jié)構(gòu)與遺傳多樣性,發(fā)現(xiàn)賈洛羊與瑪格羊之間遺傳差異相對(duì)較小,為地方綿羊品種的保護(hù)提供理論參考;馬克巖等[13]基于SLAF-seq技術(shù)分析了永登七山羊與周邊飼養(yǎng)的3種綿羊之間的群體結(jié)構(gòu)和遺傳多樣性,為永登七山羊作為新種質(zhì)資源提供理論參考;Ma等[14]基于SLAF-seq技術(shù)分析隴南山羊、波爾山羊和南江黃羊的群體遺傳結(jié)構(gòu)和遺傳多樣性,證實(shí)3個(gè)群體間遺傳差異較大,分化程度較高。
因此本試驗(yàn)的目的是使用SLAF-seq技術(shù)對(duì)小骨山羊、河西絨山羊和內(nèi)蒙古絨山羊(阿爾巴斯型)群體的60只母羊進(jìn)行全基因組范圍內(nèi)SNPs檢測(cè),評(píng)估其遺傳多樣性和群體遺傳結(jié)構(gòu),為鑒定其遺傳背景提供理論依據(jù)。
1 材料與方法
1.1 試驗(yàn)材料
本試驗(yàn)選擇小骨山羊(XG)、河西絨山羊(HXC)和內(nèi)蒙古絨山羊(阿爾巴斯型,IMC)母羊各20只。頸靜脈采血5 mL,用含抗凝劑的采血管收集,記錄樣品編號(hào),24 h內(nèi)帶回實(shí)驗(yàn)室-80 ℃保存,具體采樣信息見表1。
1.2 DNA提取與簡(jiǎn)化基因組測(cè)序
使用Biomarker Blood/Cell/Tissue DNA Kit試劑盒提取DNA并使用NanoDrop 2000測(cè)定純度,使用Qubit 2.0測(cè)定濃度,瓊脂糖凝膠電泳檢測(cè)基因組DNA的完整性。簡(jiǎn)化基因組測(cè)序由北京百邁客生物科技有限公司完成。以山羊ARS 1.2為參考基因組,最終確定使用Hpy166 II+EcoR V酶切,酶切片段長(zhǎng)度在414~464 bp的序列作為SLAF標(biāo)簽,文庫質(zhì)檢合格后測(cè)序。
1.3 數(shù)據(jù)處理
1.3.1 SNP獲取與注釋
測(cè)序獲得的reads通過BWA[15]與參考基因組比對(duì)后,取GATK(v3.8)[16]和SAMtools(v1.9)[17]獲得的SNPs交集作為可靠數(shù)據(jù)集。利用SnpEff(v3.6c)[18]軟件注釋SNPs在參考基因組上的位置以及變異類型。
1.3.2 群體遺傳多樣性分析
利用perl編程計(jì)算3個(gè)群體遺傳多樣性指標(biāo),包括次要等位基因頻率(MAF)、觀測(cè)雜合度(Ho)、期望雜合度(He)、基因多樣性指數(shù)(Nei)、多態(tài)信息含量(PIC)、香濃維納指數(shù)(SHI)。連鎖不平衡分析(LD)由PopLDdecay(v3.41)軟件計(jì)算完成,連鎖不平衡強(qiáng)度用r2表示。使用VCFtools(v0.1.15)軟件計(jì)算群體分化指數(shù)(Fst)。
1.3.3 群體遺傳結(jié)構(gòu)分析
主成分分析(PCA)通過EIGENSOFT(v6.0)軟件完成[19]。使用MEGA X[20]軟件通過鄰接法(neighbor-joining)構(gòu)建NJ樹,采用kimura 2-parameter模型,bootstrap重復(fù)1 000次。群體結(jié)構(gòu)使用ADMIXTURE(v1.22)[21]軟件進(jìn)行分析,亞群數(shù)目(K值)設(shè)定為1~10,根據(jù)交叉驗(yàn)證錯(cuò)誤率的谷值確定最優(yōu)分群數(shù)。使用GCTA(v1.92.1)[22]軟件估計(jì)親緣關(guān)系。利用PLINK(v1.90)軟件計(jì)算IBS遺傳距離,并構(gòu)建矩陣。
2 結(jié) 果
2.1 SNPs鑒定
共獲得641.85 Mb reads數(shù)據(jù),平均測(cè)序深度為12.05×。測(cè)序獲得的reads平均Q30為95.13%,與參考基因組的比對(duì)率≥70%。共檢測(cè)到5 253 776個(gè)SNPs,SNPs在染色體上的分布如圖1所示。獲得的SNPs有86.41%位于基因間區(qū),CDS區(qū)內(nèi)60.88%的位點(diǎn)為非同義編碼突變(圖2)。
2.2 群體遺傳多樣性分析
3個(gè)群體的He均高于Ho。XG群體的He最高為0.302,Ho最低為0.197。除Ho外,XG群體的其它遺傳多樣性指標(biāo)最高,HXC群體最低。XG、HXC和IMC群體的多態(tài)信息含量均小于0.25(表2)。
LD分析表明,3個(gè)群體的r2隨位點(diǎn)間距離增加而降低,XG群體的r2最高。HXC衰減速度最快,其次是IMC和XG。當(dāng)r2下降至0.1時(shí),XG群體衰減距離最大,其次是IMC和HXC(圖3)。
群體分化指數(shù)見表3,XG與HXC、XG與IMC之間的Fst分別為0.043和0.052;HXC與IMC之間的Fst值最低為0.034。
2.3 群體遺傳結(jié)構(gòu)分析
主成分分析中PC1和PC2的貢獻(xiàn)率分別為3.75%和3.04%,圖4A顯示3個(gè)群體不能明顯區(qū)分,XG群體相對(duì)分散。根據(jù)PC1(PC1>0)可將XG群體的17只個(gè)體與HXC和IMC群體區(qū)分。
NJ樹顯示(圖4B),XG群體中有14只個(gè)體聚為獨(dú)立的一支,其余個(gè)體與HXC和IMC群體混群。
群體結(jié)構(gòu)分析發(fā)現(xiàn),當(dāng)K=1時(shí)CV值最小,因此最佳分群數(shù)為K=1(圖4C)。當(dāng)K=2時(shí),部分XG個(gè)體具有獨(dú)立的一類遺傳結(jié)構(gòu),3個(gè)群體含有共同血緣。當(dāng)K=3時(shí),3個(gè)群體各具有獨(dú)立的一支結(jié)構(gòu),可明顯看出部分XG群體有獨(dú)特的一類結(jié)構(gòu)(圖4D)。
2.4 IBS距離矩陣與親緣關(guān)系G矩陣分析
XG與HXC群體之間、XG與IMC群體之間的IBS距離分別為0.718 6~0.738 0(平均值0.727 2±0.003 1)、0.716 6~0.744 0(平均值0.726 0±0.005 3)。XG群體內(nèi)的IBS遺傳距離為0.720 4~0.799 9(平均值0.737 7±0.014 2)。IBS矩陣顯示,3個(gè)群體之間的遺傳距離較遠(yuǎn)。XG群體內(nèi)有14個(gè)個(gè)體遺傳距離較近,親緣關(guān)系較近,位于圖示左上角(圖5A)。G矩陣結(jié)果顯示,3個(gè)群體之間親緣關(guān)系較遠(yuǎn),G矩陣結(jié)果與IBS矩陣結(jié)果一致(圖5B)。
3 討 論
遺傳多樣性是畜禽適應(yīng)各種環(huán)境條件的基礎(chǔ),是生物多樣性的重要組成部分[23],也是培育優(yōu)良品種、提高品種競(jìng)爭(zhēng)力的重要指標(biāo)。雜合度是衡量遺傳多樣性的參數(shù)之一,雜合度與遺傳多樣性呈正相關(guān)關(guān)系。本研究結(jié)果發(fā)現(xiàn),相比于其它地方山羊品種的He和Ho,如牙山黑絨山羊(He:0.326;Ho:0.329)[10]、川中黑山羊(He:0.307;Ho:0.248)[24]、濟(jì)寧青山羊(He:0.418;Ho:0.409)[25]和成都麻羊(He:0.634;Ho:0.577)[26]等,本研究中3個(gè)群體的He和Ho相對(duì)較低。本研究中IMC的He與李亞明[27]的研究結(jié)果相比略高,但是Ho略低;HXC的He和Ho與許麗梅[28]的研究結(jié)果相比低。3個(gè)群體的PIC范圍為0.243~0.247,普遍低于0.25,表明3個(gè)群體處于低度多態(tài)性,普遍低于以微衛(wèi)星為標(biāo)記的研究結(jié)果,推測(cè)可能是使用不同遺傳標(biāo)記導(dǎo)致結(jié)果產(chǎn)生了差異。LD分析可以體現(xiàn)群體受選擇強(qiáng)度和遺傳多樣性,衰減速度越慢,受選擇強(qiáng)度越大,遺傳多樣性越低。本研究發(fā)現(xiàn),XG群體衰減速度最慢,受選擇強(qiáng)度大,遺傳多樣性低,HXC衰減速度最快,受選擇強(qiáng)度小,遺傳多樣性高,該結(jié)果與遺傳多樣性指標(biāo)存在矛盾。結(jié)合IBS距離矩陣和親緣關(guān)系G矩陣與實(shí)地觀察推測(cè)原因是XG群體個(gè)體間親緣關(guān)系較近并且該群體的群體規(guī)模較小,因此產(chǎn)生矛盾。
分析群體遺傳結(jié)構(gòu)對(duì)合理利用種質(zhì)資源有重要的理論意義[29]。Fst用以衡量品種分化程度,由高到低分別為0.15~0.25、0.05~0.15和0~0.05,當(dāng)值小于0.05時(shí)群體分化程度低[30],同時(shí)Fst值較低也是基因交流的表現(xiàn)[31]。Machov等[32]研究發(fā)現(xiàn),同一地區(qū)的綿羊品種之間存在基因交流,導(dǎo)致Fst值較低。O’Brien等[33]通過PCA與Fst關(guān)聯(lián)分析發(fā)現(xiàn),愛爾蘭和蘇格蘭黑頭羊之間的分化程度較低,原因是雜交改良后存在基因交流。Wang等[34]調(diào)查提出,通過雜交實(shí)現(xiàn)羊絨產(chǎn)量的提高可能導(dǎo)致絨山羊品種間遺傳關(guān)系更加密切。本研究中,河西絨山羊樣本來自甘肅省張掖市,內(nèi)蒙古絨山羊(阿爾巴斯型)樣本來自內(nèi)蒙古自治區(qū)鄂爾多斯市,兩地直線距離為804 km。群體結(jié)構(gòu)分析顯示,K=3時(shí)IMC與HXC部分個(gè)體祖先成分組成相似,IMC-2、7、17、3、18清晰表示出HXC與IMC之間存在血統(tǒng)交流。因此推測(cè),河西絨山羊與內(nèi)蒙古絨山羊(阿爾巴斯型)群體分化程度低的原因是人為導(dǎo)致的基因交流。
本研究共通過3種方法綜合分析XG、HXC和IMC的群體遺傳結(jié)構(gòu),包括PCA、NJ樹和群體結(jié)構(gòu)分析。PCA可以用于探究不同個(gè)體間的遺傳關(guān)系,更容易觀察和解釋遺傳變異的分布情況?;赟NPs獲得的PCA結(jié)果可視化程度相對(duì)較好[35]。本研究的PCA結(jié)果顯示,3個(gè)群體不能明顯區(qū)分。根據(jù)PC1能看出XG群體內(nèi)個(gè)體間呈現(xiàn)分散分布,表明存在一定程度的遺傳差異[36]。NJ樹能夠展示物種之間的親緣關(guān)系,輔助了解物種的共同祖先和進(jìn)化等信息[37]。NJ樹結(jié)果顯示,3個(gè)群體存在混群現(xiàn)象,XG群體內(nèi)存在相對(duì)獨(dú)立的一支。本研究中NJ樹基于IBS遺傳距離進(jìn)行構(gòu)建,結(jié)合NJ樹與群體結(jié)構(gòu)分析結(jié)果,群體結(jié)構(gòu)分析用于檢測(cè)不同群體或個(gè)體之間的遺傳成分和遺傳比例[38],何亮宏等[39]在使用ADMIXTURE分析夏彭陽縣利木贊牛群體結(jié)構(gòu)時(shí)發(fā)現(xiàn)其血統(tǒng)主要有3部分,以普通牛血統(tǒng)為主,有不同程度的東亞普通牛及中國(guó)瘤牛血統(tǒng)的滲入。徐媛等[40]研究發(fā)現(xiàn),北歐馬有其獨(dú)特的祖先成分,歐美高度選育的馬血統(tǒng)較為純凈,幾乎全為紅色。在本研究中,K=2~4時(shí)發(fā)現(xiàn)XG群體中始終存在與HXC、IMC不同的血統(tǒng)。當(dāng)K=3時(shí),與進(jìn)化樹結(jié)果相對(duì)應(yīng),XG-14、XG-6、XG-13血統(tǒng)的比例為40.31%、44.73%、63.20%,在群體結(jié)構(gòu)分析中表現(xiàn)為紅色比例增加,從XG-20開始增加至全紅色。因此推測(cè),XG特殊的祖先成分占比增加,遺傳距離增加逐漸形成相對(duì)獨(dú)立分支。
4 結(jié) 論
本研究利用SLAF-seq分析了小骨山羊群體遺傳多樣性和群體遺傳結(jié)構(gòu)。結(jié)果表明,小骨山羊與河西絨山羊遺傳分化水平低,與內(nèi)蒙古絨山羊(阿爾巴斯型)分化水平中等。小骨山羊的遺傳多樣性相對(duì)其它兩個(gè)群體較高,但是存在選擇壓力和群體規(guī)模小的問題。
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(編輯 郭云雁)