從遺傳力到腸菌力：概念及研究進(jìn)展

文超良，孫從佼，楊寧

從遺傳力到腸菌力：概念及研究進(jìn)展

文超良，孫從佼，楊寧

中國(guó)農(nóng)業(yè)大學(xué)動(dòng)物科技學(xué)院，畜禽國(guó)家育種工程實(shí)驗(yàn)室，北京 100193

遺傳力是數(shù)量遺傳學(xué)中衡量性狀遺傳變異的重要參數(shù)之一，對(duì)動(dòng)植物遺傳育種、醫(yī)學(xué)和進(jìn)化生物學(xué)均具有重要意義。自1918年Fisher提出方差組分剖分思想后，遺傳力的分析模型和估計(jì)方法不斷迭代更新。近年來(lái)，一些研究者在研究腸道微生物與宿主表型關(guān)系的熱點(diǎn)問(wèn)題中，引入類似于遺傳力的概念和估計(jì)方法，系統(tǒng)評(píng)估動(dòng)物機(jī)體性狀表現(xiàn)受腸道微生物因素的影響程度，本文將這一參數(shù)(microbiability,2)譯為“腸菌力”。文章簡(jiǎn)要介紹了遺傳力估計(jì)的發(fā)展歷程，概述了腸道菌群與宿主基因組的復(fù)雜關(guān)系，重點(diǎn)闡釋了腸菌力的概念和估計(jì)方法，以期為腸道微生物組塑造宿主表型變異的研究提供一定的借鑒和參考。

遺傳力；腸菌力；關(guān)聯(lián)分析；數(shù)量性狀；方差組分；關(guān)系矩陣

動(dòng)物是由宿主機(jī)體和共棲微生物構(gòu)成的“共生總體(Holobiont)”[1]。宿主性狀的表現(xiàn)既受其自身基因的調(diào)控，又受到“宿主第二基因組”—腸道菌群的影響。在世代傳遞中，宿主的遺傳信息可通過(guò)配子穩(wěn)定遺傳。自1918年英國(guó)統(tǒng)計(jì)學(xué)家和遺傳學(xué)家Fisher[2]提出方差組分剖分思想以來(lái)，科研工作者對(duì)復(fù)雜性狀遺傳規(guī)律的研究，由親緣個(gè)體間表型相似性轉(zhuǎn)變?yōu)檫z傳效應(yīng)的剖分，再到隨機(jī)群體全基因組位點(diǎn)貢獻(xiàn)解析的過(guò)程中，遺傳力(heritability)的概念始終貫穿其中。

與宿主遺傳取得的一系列突破成果相比，腸道微生物與宿主表型聯(lián)系的研究進(jìn)展則緩慢許多。早在1907年，諾貝爾獎(jiǎng)獲得者M(jìn)etchnikoff在《The Prolongation of Life: Optimistic Studies》一書(shū)中最先明確提出腸道微生物產(chǎn)生的毒素是人體衰老、患病的重要原因，通過(guò)調(diào)控腸道菌群可以促進(jìn)健康、延緩衰老[3]。但是由于菌群分離培養(yǎng)和傳統(tǒng)的分子生物學(xué)方法(如DNA指紋技術(shù))的局限性，他的觀點(diǎn)始終未得到主流醫(yī)學(xué)界的關(guān)注和認(rèn)可。近年來(lái)，以二代高通量測(cè)序技術(shù)為主要手段的宏基因組學(xué)(meta-genomics)及其生物信息分析方法[4]廣泛應(yīng)用于動(dòng)物腸道菌群的研究，揭示了動(dòng)物腸道微生物多樣性、結(jié)構(gòu)和功能，腸道微生物組的研究成為微生物學(xué)乃至整個(gè)生物學(xué)最具活力的研究領(lǐng)域之一，新發(fā)現(xiàn)和新理論如雨后春筍，層出不窮。尤其是近年來(lái)各國(guó)學(xué)者將數(shù)量遺傳學(xué)上的概念、理論和方法引入腸道微生物的研究工作中[5~9]，掀起了新一輪的研究熱潮。本文系統(tǒng)介紹了近百年來(lái)宿主遺傳效應(yīng)估計(jì)和腸道菌群效應(yīng)解析，以及宿主與腸道菌群相互關(guān)系(圖1)研究進(jìn)展，并進(jìn)行簡(jiǎn)要討論和展望，以期為該領(lǐng)域的深入研究提供參考。

1 宿主基因組與性狀間的關(guān)系

1.1 遺傳力的定義

遺傳力是一個(gè)基于數(shù)理統(tǒng)計(jì)、主要反映宿主數(shù)量性狀遺傳特征的重要參數(shù)，習(xí)慣上用h表示，該符號(hào)最早是1920年美國(guó)遺傳學(xué)家Wright[10]在豚鼠()斑紋的通徑分析(path analysis)中，用來(lái)表示宿主遺傳因素對(duì)機(jī)體表型的決定程度。一般情況下指狹義遺傳力(narrow sense heritability)，即加性方差(即育種值方差)占據(jù)表型方差的比率，其生物統(tǒng)計(jì)學(xué)概念等同于加性效應(yīng)對(duì)表型值的回歸系數(shù)，或加性效應(yīng)與表型值的相關(guān)系數(shù)的平方[11]。需要強(qiáng)調(diào)的是，世代更迭，只有基因通過(guò)配子進(jìn)行傳遞，因此遺傳力不能真實(shí)反映性狀的傳遞能力，僅說(shuō)明的是群體特定性狀的變異情況[12]。

圖1 宿主和腸道菌群相互關(guān)系及相關(guān)研究方法

1.2 遺傳力估計(jì)方法

由于遺傳力反映了親屬間的相似程度，傳統(tǒng)數(shù)量遺傳學(xué)通?；谟H緣關(guān)系較近的兩類個(gè)體表型值間的相關(guān)系數(shù)及親緣系數(shù)來(lái)估計(jì)遺傳力(圖2A)[13]。例如子代對(duì)任一親本表型值或中親值的回歸[14]、全同胞或半同胞的相關(guān)性[15]，以及常用于人類性狀的雙胞胎間相似性[16]。

上述經(jīng)典的遺傳力估計(jì)方法雖然計(jì)算較為簡(jiǎn)單，但只能處理系譜關(guān)系簡(jiǎn)單、均衡的資料。對(duì)于系譜關(guān)系復(fù)雜(如多代和跨代)或者非均衡的群體，通過(guò)線性混合模型估計(jì)加性遺傳方差和環(huán)境組分，再利用獲得的方差組分計(jì)算遺傳力則更為有效。1953年美國(guó)數(shù)量遺傳學(xué)家Henderson發(fā)表了題為《Estimation of variance and covariance components》的論文[17]，提出了3種適用于非均衡資料的方差組分估計(jì)方法，引起遺傳學(xué)家和統(tǒng)計(jì)學(xué)家的廣泛關(guān)注。為提高方差組分的估計(jì)準(zhǔn)確性，各國(guó)的遺傳育種工作者及對(duì)此感興趣的統(tǒng)計(jì)學(xué)家進(jìn)行了大量的探索，估計(jì)方法也隨著新理論、新技術(shù)和新工具的不斷涌現(xiàn)而更新和發(fā)展，如約束最大似然法(restricted maximum likeli-hood, REML)[18]、貝葉斯估計(jì)法(Bayesian method)[19]和Gibbs抽樣法[20]等。此后，雖然新方法仍在不斷出現(xiàn)，但是REML法和貝葉斯估計(jì)法已在全球范圍內(nèi)占據(jù)主導(dǎo)地位。

線性模型的理論及其估計(jì)方法在現(xiàn)代數(shù)量遺傳學(xué)中占有十分重要的地位，尤其是動(dòng)物模型，更是畜禽育種、進(jìn)化遺傳學(xué)和人類遺傳學(xué)部分應(yīng)用中的首選模型[12]。傳統(tǒng)上利用線性混合模型估計(jì)遺傳力都是基于系譜記錄完整的群體，因?yàn)槭紫刃枰孟底V信息構(gòu)建分子親緣相關(guān)矩陣(numerator relation-ship matrix，簡(jiǎn)稱A陣)。由于孟德?tīng)柍闃?Mendelian sampling)誤差[21]，基于系譜推斷的個(gè)體間親緣關(guān)系準(zhǔn)確性有限(圖2B)，而且系譜又或多或少地存在錯(cuò)誤記錄；此外，對(duì)于系譜信息不完整或缺失的群體以及隨機(jī)群體，也顯得無(wú)能為力。理論上，親緣關(guān)系較近的個(gè)體，共享的等位基因也更多，由此各國(guó)科研工作者積極嘗試?yán)梅肿訕?biāo)記(如QTL、DNA多態(tài)性等)來(lái)推斷個(gè)體間的親緣關(guān)系[22~24]。1996年Ritland[25]首次利用分子標(biāo)記推斷的個(gè)體間親緣關(guān)系結(jié)合表型相似性估計(jì)自然群體的遺傳力，此后在植物[26]、魚(yú)[27]、哺乳動(dòng)物[28]以及人類群體中[29]得到進(jìn)一步完善和應(yīng)用。

圖2 遺傳力估計(jì)的主要信息來(lái)源

A：基于子代表型值對(duì)親本中親值的回歸估計(jì)遺傳力(根據(jù)參考文獻(xiàn)[12]修改繪制)；B：蛋雞全同胞個(gè)體間的基因組關(guān)系系數(shù)分布(中間虛線為均值線，由于孟德?tīng)柍闃诱`差，全同胞個(gè)體間的親緣系數(shù)可能偏離0.5)；C：基于每條染色體上的SNP估計(jì)每條染色體所能解釋目標(biāo)性狀的遺傳方差。

1.3 全基因組關(guān)聯(lián)分析

1996年，美國(guó)斯坦福醫(yī)學(xué)院Risch等[42]發(fā)現(xiàn)復(fù)雜疾病遺傳學(xué)研究中的關(guān)聯(lián)分析比連鎖分析具有更高的檢測(cè)效力，隨即提出全基因關(guān)聯(lián)分析(genome-wide association study, GWAS)的概念：在整個(gè)基因組范圍內(nèi)篩選與目標(biāo)性狀相關(guān)聯(lián)的分子標(biāo)記。基于測(cè)序和基因分型技術(shù)，2005年Klein等[43]首次報(bào)道了一項(xiàng)有關(guān)年齡相關(guān)性視網(wǎng)膜黃斑變性的GWAS研究。之后，一系列與人類復(fù)雜疾病等相關(guān)表型的GWAS研究被陸續(xù)報(bào)道[44~46]，并且GWAS在畜禽各種重要經(jīng)濟(jì)性狀及復(fù)雜疾病抗性的遺傳研究中也得到了廣泛應(yīng)用[47~49]。GWAS研究為揭示機(jī)體復(fù)雜性狀的遺傳奧秘開(kāi)辟了新的渠道，篩選出大量與目標(biāo)性狀關(guān)聯(lián)的主效和微效基因，并被納入臨床應(yīng)用[50]和遺傳選育[51]。

2 宿主基因組與腸道菌群的關(guān)系

動(dòng)物表型變異除了受宿主自身遺傳因素的影響，腸道內(nèi)棲息的數(shù)量龐大而復(fù)雜的微生物及其代謝產(chǎn)物的作用亦不能小覷，它們通過(guò)腸–肝[52]、腸–腦[53]等調(diào)控軸與宿主免疫疾病[54~56]、營(yíng)養(yǎng)代謝[57~59]和機(jī)體行為[60~62]等諸多方面密切聯(lián)系。腸道菌群究竟是先天遺傳因素主導(dǎo)，還是后天環(huán)境因素驅(qū)動(dòng)？這一直是腸道微生物研究領(lǐng)域的焦點(diǎn)之一。國(guó)內(nèi)外學(xué)者采用各種研究手段和方法，持續(xù)追問(wèn)“nature or nurture?”

雙胞胎樣本是解析人類基因組塑造腸道菌群的良好模型。早期基于細(xì)胞培養(yǎng)[63]和DNA指紋技術(shù)[64,65]發(fā)現(xiàn)與異卵雙胞胎和無(wú)親緣關(guān)系個(gè)體相比，同卵雙胞胎的糞便微生物結(jié)構(gòu)更為相似。近年來(lái)，Turnbaugh等[66]和Yatsunenko等[67]通過(guò)16S rRNA測(cè)序，在稍大規(guī)模的雙胞胎人群也觀察到這一類似結(jié)果，但未達(dá)到顯著水平，這兩項(xiàng)研究更多的是強(qiáng)調(diào)環(huán)境因素在塑造腸道微生物的關(guān)鍵性作用。腸道經(jīng)歷了從少到多、從簡(jiǎn)單到復(fù)雜、從不穩(wěn)定直至相對(duì)穩(wěn)定的菌群定植過(guò)程[67,68]，但是并不能確定腸道微生物結(jié)構(gòu)的相似性是由于遺傳背景的相似還是由于生活環(huán)境一致所造成的。Xie等[69]對(duì)250對(duì)雙胞胎的糞便樣品進(jìn)行宏基因組測(cè)序，結(jié)果表明人體基因組對(duì)腸道內(nèi)諸多菌群及其潛在功能具有顯著貢獻(xiàn)，且雙胞胎之間，尤其是同卵雙胞胎之間的腸道微生物組成、SNP和功能分類高度相似，但是這種相似性又會(huì)隨著異地居住而逐漸減弱。在小鼠()[70,71]以及雞()[72~74]、豬()[75]、牛()[76~78]和羊()[79,80]等畜禽上，研究者更多的是比較不同品系和品種在相同飼養(yǎng)條件下、或相同品系/品種在不同飼養(yǎng)條件下的腸道微生物的差異；這些研究表明在相同飼養(yǎng)條件下，腸道菌群具有明顯的品種/品系特異性，但飼養(yǎng)環(huán)境的差異又掩蓋了遺傳因素對(duì)腸道菌群的塑造作用。

2010年美國(guó)內(nèi)布拉斯加大學(xué)Beason等[5]提出將腸道微生物作為宿主的復(fù)雜數(shù)量性狀進(jìn)行研究。此后，諸多學(xué)者將腸道菌群豐度、α和β多樣性以及微生物基因功能豐度等視為數(shù)量性狀(稀有的分類群視為二分類性狀)，估計(jì)它們的遺傳力，辨別受宿主遺傳因素調(diào)控的微生物群落，并進(jìn)一步通過(guò)微生物全基因組關(guān)聯(lián)分析(microbial genome-wide asso-ciation study, mGWAS)挖掘?qū)е履c道菌群可遺傳性的宿主遺傳變異。

2.1 腸道菌群的遺傳力

將腸道菌群的遺傳力理解為腸道微生物組成和相對(duì)豐度能夠穩(wěn)定遺傳下去的能力是一種誤解，更為合適的解釋是其反映了宿主遺傳因素對(duì)腸道微生物的影響程度，或親緣個(gè)體間腸道菌群的相似性[81]。通過(guò)對(duì)宿主自身基因組和腸道微生物分別采用基因芯片分型和16S rRNA測(cè)序的方法，Goodrich等[8]于2014年分析了來(lái)自英國(guó)的416對(duì)雙胞胎的糞便樣本，結(jié)果顯示同卵雙胞胎相較異卵雙胞胎和無(wú)親緣個(gè)體具有更加相似的微生物結(jié)構(gòu)，且3組樣本間的相似性距離達(dá)到顯著差異水平；作者進(jìn)一步通過(guò)估計(jì)腸道菌群的遺傳力，鑒定出33個(gè)相對(duì)豐度受到宿主遺傳因素影響的微生物，尤其是對(duì)Christensene-llaceae菌科的估計(jì)值為0.33，該結(jié)果在加拿大(h=0.65)[82]和韓國(guó)人群糞便樣本(h=0.31)[83]中也得到了驗(yàn)證?？紤]到樣本數(shù)量的影響，2016年Goodrich等[84]將雙胞胎數(shù)量提高到1126對(duì)，對(duì)Christen-senellaceae的遺傳力估計(jì)值升至0.42，同時(shí)觀察到更多的可遺傳性微生物(遺傳力大于0.2的菌群比例僅由此前的5.3%增加到8.8%)，這些微生物的相對(duì)豐度在相當(dāng)長(zhǎng)的時(shí)間內(nèi)保持穩(wěn)定，厚壁菌門(Firmi-cutes)和放線菌門(Actinobacteria)具有更多的遺傳屬性，而高豐度的擬桿菌門(Bacteroidetes)呈現(xiàn)較少的可遺傳性；除了估計(jì)分類群的遺傳力外，作者也估計(jì)了α和β多樣性的遺傳力，其中α多樣性也具有一定的遺傳力。同年，Turpin等[82]在加拿大招募了1561名志愿者，估計(jì)了從門至屬水平共計(jì)249種糞便菌群的遺傳力，結(jié)果發(fā)現(xiàn)94種的細(xì)菌類群受宿主遺傳背景的影響，其遺傳力介于0.25~0.66；Lim等[83]基于655名韓國(guó)人體的糞便樣本，估計(jì)了85種不同分類水平下的菌群遺傳力，其中50種菌群具有顯著的遺傳力，并且雙歧桿菌屬()所在的放線菌門(Actinobacteria)的遺傳力達(dá)0.46。

在畜禽上，基于16S rRNA測(cè)序數(shù)據(jù)，腸道菌群遺傳力的估計(jì)也得到了廣泛開(kāi)展。2013年，Zhao等[85]利用系譜信息估計(jì)了弗吉尼亞理工大學(xué)體重雙選系肉雞部分糞便菌群的遺傳力，證明肉雞糞便微生物組成受到宿主遺傳背景的影響；隨后，Meng等[86]還分析了腸道菌群的遺傳相關(guān)，并表明一些菌群之間存在顯著的遺傳相關(guān)。Wen等[87]估計(jì)了肉雞十二指腸、空腸、回腸和盲腸4個(gè)腸段以及糞便微生物的SNP遺傳力，發(fā)現(xiàn)可遺傳微生物主要是厚壁菌門(Firmicutes)和變形菌門(Proteobacteria)，但各腸段具有顯著SNP遺傳力的微生物累積豐度均不到3.5%。在反芻動(dòng)物上，Sasson等[88]通過(guò)50K SNP芯片獲取奶牛自身基因組，確定了22個(gè)相對(duì)豐度與能量捕獲的可遺傳瘤胃微生物。Difford等[89]基于系譜信息估計(jì)了750頭荷斯坦奶牛瘤胃細(xì)菌和古菌遺傳力，結(jié)果表明在可操作分類單元(operational taxonomic units, OTUs)上，僅有6%的細(xì)菌和12%的古菌具有顯著的遺傳力；在屬水平上，144個(gè)細(xì)菌屬中只有8個(gè)具有顯著的遺傳力估計(jì)值(0.17~0.25)，此外只有3個(gè)古菌屬具有遺傳力(0.18~0.22)。Li等[90]利用50K SNP芯片對(duì)709頭肉牛進(jìn)行基因分型，估計(jì)了174個(gè)(137個(gè)細(xì)菌，27個(gè)古菌)不同分類水平下的瘤胃微生物SNP遺傳力，發(fā)現(xiàn)56個(gè)細(xì)菌和3個(gè)古菌受到宿主基因組的調(diào)控(h=0.15~0.25)，其中22個(gè)屬于厚壁菌門(Firmicutes)，并且細(xì)菌和古菌一些衡量α和β多樣性的指標(biāo)也呈現(xiàn)一定的遺傳力。Chen等[91]估計(jì)了256頭二花臉豬盲腸微生物和244頭巴馬香豬糞便微生物的SNP遺傳力，共發(fā)現(xiàn)67種盲腸菌群和81種糞便微生物的遺傳力估計(jì)值高于0.15(兩種樣本可遺傳分類群交集數(shù)為31)，其中糞便中的菌種遺傳力達(dá)到0.41，盲腸中的Rumino-coccaceae菌科和菌屬遺傳力達(dá)到0.56。Camarinha-Silva等[92]在207頭皮特蘭母豬上發(fā)現(xiàn)49個(gè)結(jié)腸菌屬中8個(gè)具有顯著的SNP遺傳力(0.32~ 0.57)，其中菌屬的遺傳力為0.33。Lu等[93]在大白豬和長(zhǎng)白豬雜交后代上的研究表明，糞便微生物α多樣性和OTU豐富度在多個(gè)時(shí)間點(diǎn)具有中等的遺傳力。同樣，在鋸齒動(dòng)物上也有腸道菌群遺傳力的相關(guān)報(bào)道[94,95]。

2.2 微生物全基因組關(guān)聯(lián)分析

在人類和動(dòng)物群體中的研究結(jié)論雖然有些差異，但均暗示著一部分腸道菌群受到宿主基因組的影響。因此，科研人員進(jìn)一步通過(guò)mGWAS探討了宿主分子標(biāo)記與腸道微生物的關(guān)聯(lián)。2015年Blekhman等[9]利用人類微生物組計(jì)劃(human microbiome project, HMP)數(shù)據(jù)首次報(bào)道了糞便菌群中的雙歧桿菌屬()與2號(hào)染色體上的乳糖酶(lactase,)基因區(qū)域之間的關(guān)聯(lián)，乳糖不耐受個(gè)體飲用牛奶后，腸道內(nèi)雙歧桿菌的相對(duì)豐度升高，以幫助宿主分解乳糖?；蚺c的關(guān)聯(lián)信號(hào)在英國(guó)雙胞胎群體[84,96]、北美哈特教派信徒[84]、荷蘭[97]、德國(guó)[98]和HMP[99]隊(duì)列得到進(jìn)一步驗(yàn)證，這也是迄今為止mGWAS中報(bào)道最一致的信號(hào)(表1)。

人類mGWAS研究主要依賴于糞便樣品，而畜禽和鋸齒動(dòng)物可以通過(guò)活體或者屠宰取樣，對(duì)糞便以外的其他腸段進(jìn)行mGWAS研究，并且篩選到一些與腸道微生物豐度和組成顯著關(guān)聯(lián)的分子標(biāo)記(表2)。

除了估計(jì)菌群遺傳力和進(jìn)行mWGAS研究外，科研人員也發(fā)現(xiàn)基因編輯后的小鼠腸道菌群發(fā)生了顯著改變[105~108]。這些研究證明了宿主遺傳基因型對(duì)腸道微生物的作用，但并未回答宿主遺傳組分和環(huán)境因素對(duì)腸道菌群結(jié)構(gòu)的塑造作用究竟有多強(qiáng)這一核心問(wèn)題。2018年，Rothschild等[96]重新分析了Goodrich等[84]分析的1126對(duì)雙胞胎數(shù)據(jù)，結(jié)果表明人類基因組組分對(duì)腸道微生物組的影響甚微，糞便微生物組的整體可遺傳性僅為1.9%。Wang等[98]對(duì)1812名德國(guó)人群的研究結(jié)果顯示，遺傳因素可解釋微生物組β多樣性變異的10.43%，而僅年齡、BMI、吸煙與否和性別4個(gè)因素的比例可達(dá)14.66%；Zhernakova等[109]通過(guò)問(wèn)卷調(diào)查的方式收集了荷蘭1135名志愿者的飲食、藥物使用等多種可能影響腸道微生物的信息，鑒定出幾個(gè)可影響腸道微生物結(jié)構(gòu)的環(huán)境因子，它們可解釋18.7%的腸道微生物組β多樣性；Rothschild等[96]對(duì)1046名以色列人群的研究顯示，飲食、藥物使用等環(huán)境因素可以解釋20.03%的腸道微生物組結(jié)構(gòu)變異，而宿主遺傳背景與腸道微生物之間沒(méi)有顯著關(guān)聯(lián)。分析宿主親緣關(guān)系與Bray-Curtis相異度相關(guān)性的研究結(jié)果也表明兩者相關(guān)性微弱[87,96,103,110]。

表1 人類腸道m(xù)GWAS相關(guān)研究

表2 畜禽腸道m(xù)GWAS相關(guān)研究

總之，越來(lái)越多的證據(jù)表明宿主遺傳背景對(duì)腸道微生物有影響，但是這種影響對(duì)腸道菌群整體塑造作用是有限的(圖3)。因此，本文認(rèn)為腸道微生物組和宿主基因組應(yīng)該視為不同的實(shí)體，結(jié)合宿主自身遺傳因素，來(lái)分析它們對(duì)宿主生理性狀的影響。

3 腸道菌群與性狀間的關(guān)系

3.1 腸菌力的概念

圖3 宿主遺傳信息與腸道菌群的關(guān)系

A：宿主自身基因型矩陣和腸道菌群豐度矩陣，部分菌群受到宿主基因型的影響；B：利用A圖中的兩個(gè)矩陣構(gòu)建的基因組關(guān)系矩陣和微生物相似矩陣；C：兩兩個(gè)體間基因組關(guān)系系數(shù)與Bray-Curtis相異度的散點(diǎn)圖，兩者相關(guān)性不顯著。

基于腸菌力的估計(jì)值，可以更好的區(qū)分各腸段微生物與目標(biāo)性狀的關(guān)聯(lián)程度，進(jìn)而有針對(duì)性的選擇特定腸段開(kāi)展后續(xù)研究，尤其是對(duì)于可以活體和屠宰取樣的畜禽動(dòng)物，在宏基因組、宏轉(zhuǎn)錄組、宏代謝組和宏蛋白質(zhì)組測(cè)序成本依然偏高情況下，先利用16S rRNA測(cè)序數(shù)據(jù)篩選出重要腸段，之后再采用分辨率更高的宏基因組等手段揭示腸道微生物種群及其代謝物、菌群基因及基因產(chǎn)物對(duì)機(jī)體生理性狀的作用機(jī)制。腸菌力的估計(jì)也為一些傳統(tǒng)研究方法的改進(jìn)提供了依據(jù)，如通過(guò)腸菌力估計(jì)值可以明確禽類盲腸微生物在消化代謝過(guò)程中具有的重要作用，因此去盲腸法測(cè)定消化率并不能有效反映機(jī)體真實(shí)的消化率。

3.2 腸菌力的估計(jì)方法

3.2.1 方差組分法

估計(jì)腸菌力最早的研究可追溯至2013年，澳大利亞的研究者[7]借鑒宿主SNP遺傳力的估計(jì)方法，利用宏基因組測(cè)序得到的重疊群計(jì)數(shù)(contig count)數(shù)據(jù)構(gòu)建微生物組關(guān)系矩陣(metagenomic relation-ship matrix，也有研究使用microbial relationship matrix和bacterial kinship matrix，后文統(tǒng)稱M陣，表4)，接著采用線性混合模型評(píng)估奶牛瘤胃微生物組對(duì)甲烷排放以及人類糞便微生物組對(duì)BMI和IBD的貢獻(xiàn)大小。此后，Difford等[89]采用該方法估計(jì)了750頭荷斯坦奶牛甲烷排放的遺傳力和腸菌力(分別基于系譜信息和16S rRNA測(cè)序)，結(jié)果表明宿主遺傳和瘤胃微生物對(duì)奶牛甲烷排放的效應(yīng)值分別為0.21和0.13，且相互獨(dú)立。2017年，德國(guó)霍恩海姆大學(xué)Camarinha-Silva等[92]利用16S rRNA測(cè)序和Illumina 60K芯片分別分析了207頭皮特蘭母豬結(jié)腸微生物組成和宿主基因型，基于線性混合模型分別估算了日增重、采食量和飼料轉(zhuǎn)化率的微生物效應(yīng)和遺傳效應(yīng)，結(jié)果顯示3個(gè)性狀的遺傳力分別為0.35、0.20和0.23，而腸菌力亦分別可達(dá)0.41、0.33和0.33。與澳大利亞學(xué)者不同的是，后兩項(xiàng)研究使用的是OTU相對(duì)豐度構(gòu)建M陣。

2018年，以色列魏茲曼科學(xué)研究所Rothschild等[96]收集了1046名以色列人的身高、BMI、胸圍、臀圍、各血液生化指標(biāo)等12個(gè)復(fù)雜性狀，對(duì)糞便微生物采用了宏基因組和16S兩種測(cè)序手段。基于宏基因組測(cè)序得到的微生物基因檢出與否(0/1)構(gòu)建M陣，將宿主性別、年齡、飲食以及前5個(gè)遺傳主成分作為協(xié)變量，使用GCTA估計(jì)微生物組對(duì)宿主各表型的可釋方差(microbiome-association index, b2)。此外，該研究利用基因芯片對(duì)宿主基因組進(jìn)行分型，提取已公布的與各目標(biāo)性狀相關(guān)的SNP位點(diǎn)，計(jì)算目標(biāo)性狀的多基因風(fēng)險(xiǎn)評(píng)分(polygenic risk score, PRS)，將PRS或者SNP基因型作為協(xié)變量加入線性混合模型中以校正宿主遺傳效應(yīng)的影響，結(jié)果顯示腸道微生物組對(duì)12個(gè)性狀中的8個(gè)具有顯著的影響，并且對(duì)于某些性狀，微生物效應(yīng)大小不亞于遺傳效應(yīng)。該研究還發(fā)現(xiàn)估計(jì)腸菌力所需樣本數(shù)遠(yuǎn)小于遺傳力的樣本需求量。在該研究中，除了利用微生物基因檢出與否構(gòu)建M陣外，作者也嘗試?yán)没蜇S度構(gòu)建M陣，以及基于兩種測(cè)序方式聚類得到的各分類水平下的菌群豐度或檢出與否構(gòu)建M陣。遺憾的是作者并未使用OTU數(shù)據(jù)構(gòu)建M陣，也未對(duì)基于不同數(shù)據(jù)所構(gòu)建的M陣效果進(jìn)行討論，但從該研究公布的數(shù)據(jù)看，由于分類單元信息量過(guò)少，估計(jì)的效果并不理想，而使用基因檢出與否和相對(duì)豐度的估計(jì)效果差異相對(duì)較小。

表3 人類和動(dòng)物上腸菌力估計(jì)的相關(guān)研究

值得注意的是，上述幾項(xiàng)有關(guān)腸菌力估計(jì)的研究?jī)H基于一個(gè)腸段內(nèi)容物。然而，大量的研究表明，由于各腸段間的氧氣含量[114]、pH值[115]和營(yíng)養(yǎng)物質(zhì)可用性[116]存在空間異質(zhì)性，各個(gè)腸段的微生物群落組成、結(jié)構(gòu)和功能亦具有較大的差異[87,117]。此外，宿主自身基因組對(duì)目標(biāo)性狀都具有較大的影響，而在估計(jì)各性狀腸菌力時(shí)，科研人員并沒(méi)有校正宿主遺傳效應(yīng)，或者校正依據(jù)的是公共數(shù)據(jù)庫(kù)中與目標(biāo)性狀相關(guān)聯(lián)的位點(diǎn)，而不是待估群體自身的關(guān)聯(lián)位點(diǎn)。

由此，本課題組以205只黃羽肉雞為研究對(duì)象，對(duì)宿主進(jìn)行全基因組重測(cè)序(whole genomic reseque-ncing, WGS)，通過(guò)全基因組關(guān)聯(lián)分析篩選與腹脂量和腹脂率關(guān)聯(lián)的位點(diǎn)；并對(duì)宿主十二指腸、空腸、回腸、盲腸及糞便微生物進(jìn)行16S rRNA測(cè)序，利用各段OTU相對(duì)豐度數(shù)據(jù)分別構(gòu)建M陣，通過(guò)線性混合模型依次估計(jì)各腸段和糞便的微生物對(duì)腹脂沉積的效應(yīng)[87]。考慮到宿主自身遺傳基礎(chǔ)在腹脂沉積的過(guò)程中發(fā)揮著較大作用，在估計(jì)腸菌力時(shí)，提取與腹脂沉積關(guān)聯(lián)的位點(diǎn)基因型，通過(guò)降維選擇前兩個(gè)主成分以及前5個(gè)遺傳主成分作為協(xié)變量以校正遺傳因素干擾。結(jié)果表明，腹脂量在十二指腸、空腸、回腸、盲腸、糞便的腸菌力依次為：0.24、0.06、0.03、0.21和0.02，腹脂率在5個(gè)部分的腸菌力分別為：0.24、0.10、0、0.20和0.03，這意味著不同腸段的微生物組對(duì)腹脂沉積的貢獻(xiàn)是有差異的，該結(jié)果為研究者選擇腸段開(kāi)展后續(xù)研究提供了重要參考。

綜上所述，方差組分法主要借鑒了SNP遺傳力估計(jì)的方法，通過(guò)線性混合模型求解。方差組分法的核心在于M陣的構(gòu)建，雖然現(xiàn)有的幾篇文獻(xiàn)在M陣構(gòu)建的基本形式一致(公式(1))，但是在選用于構(gòu)建M陣的數(shù)據(jù)類型并不完全一致(圖4)，本文對(duì)其進(jìn)行了系統(tǒng)比較，以期為將來(lái)腸菌力估計(jì)提供參考。

式中，X為×的矩陣，XT為X的轉(zhuǎn)置矩陣，為個(gè)體數(shù)，為檢測(cè)到的OTU(或conting/gene)總數(shù)。X任一元素x為個(gè)體的第個(gè)OTU (或conting/ gene)的標(biāo)準(zhǔn)化的相對(duì)豐度(或標(biāo)準(zhǔn)化的contig計(jì)數(shù)、gene檢出與否)。M陣中個(gè)體和的微生物關(guān)系系數(shù)m計(jì)算公式如表4所示。

目前，通過(guò)宏基因組和擴(kuò)增子兩種測(cè)序方法得到的腸道微生物數(shù)據(jù)都已用于估計(jì)腸菌力，前者分辨率高、獲取的信息量大，不僅能提供菌群群落層面的信息，也能揭示微生物組功能基因信息；而后者成本低廉，分析快速，且能有效避免宿主基因組信息的污染，但這種測(cè)序方式需要經(jīng)過(guò)PCR擴(kuò)增，研究范圍受限于可擴(kuò)增部分序列的物種組成，因此會(huì)遺漏一些菌群信息。由于缺少實(shí)際對(duì)比研究，基于不同測(cè)序方法的腸菌力評(píng)估效果還有待后續(xù)進(jìn)一步探討。

3.2.2 回歸法

除方差組分法外，2015年荷蘭格羅寧根大學(xué)Fu等[118]為估計(jì)腸道微生物組對(duì)人體血脂含量和BMI的貢獻(xiàn)大小，對(duì)荷蘭LifeLines-DEEP項(xiàng)目中893名參與者的糞便微生物進(jìn)行16S rRNA測(cè)序，提出通過(guò)二分類模型(binary model，估計(jì)OTU檢出與否的評(píng)分)和數(shù)量模型(quantitative model，估計(jì)OTU相對(duì)豐度的評(píng)分)分別估計(jì)每個(gè)OTU兩種不同的屬性的風(fēng)險(xiǎn)評(píng)分，再依據(jù)加性模型(additive model)求解每個(gè)個(gè)體所有OTU累加的微生物風(fēng)險(xiǎn)評(píng)分，并將其與個(gè)體表型值相關(guān)系數(shù)的平方(the squared correla-tion coefficient, R2)作為腸道微生物組對(duì)宿主表型的可釋方差。雖然該方法主要借鑒了流行病學(xué)研究中的遺傳風(fēng)險(xiǎn)預(yù)測(cè)模型[119,120]，但其與數(shù)量遺傳學(xué)中狹義遺傳力的估計(jì)(加性效應(yīng)與表型值相關(guān)系數(shù)的平方[11])有相似之處。該方法不涉及M陣的構(gòu)建，先估計(jì)每種OTU效應(yīng)的大小，再計(jì)算個(gè)體OTU累加的總效應(yīng)，最后以O(shè)TU總效應(yīng)與表型值相關(guān)系數(shù)的平方作為腸菌力。該方法為評(píng)估每類OTU效應(yīng)，以及每個(gè)個(gè)體腸道微生物效應(yīng)值提供了重要參考，但尚無(wú)實(shí)際數(shù)據(jù)分析回歸法與方差組分法的估計(jì)效果，其實(shí)際應(yīng)用還需要更深入探索和評(píng)估。

表4 微生物組關(guān)系矩陣構(gòu)建方法比較

圖4 基于高通量測(cè)序微生物組關(guān)系矩陣構(gòu)建流程

3.3 宏基因組關(guān)聯(lián)分析

為了能夠高分辨率的研究腸道微生物組與宿主表型的關(guān)聯(lián)，Qin等[121]借鑒GWAS研究，于2012年提出了宏基因組關(guān)聯(lián)分析(metagenome-wide asso-ciation study, MWAS)的概念和方法。該研究對(duì)345個(gè)中國(guó)參與者的糞便微生物進(jìn)行了兩階段MWAS，共鑒定出約6萬(wàn)個(gè)與Ⅱ型糖尿病相關(guān)的分子標(biāo)記，并從菌種、功能以及微生態(tài)群落詳盡展示了腸道微生物與宿主表型的關(guān)聯(lián)特征。

通過(guò)全集因組鳥(niǎo)槍法測(cè)序，將質(zhì)控后的高質(zhì)量序列拼接成更長(zhǎng)的重疊群，通過(guò)對(duì)重疊群進(jìn)行基因預(yù)測(cè)，去除樣品間高度相似的基因序列，得到高質(zhì)量的非冗余參考基因集；基于來(lái)源于同一菌株基因組的重疊群或基因在不同樣品中應(yīng)具有一致的豐度變化模式，對(duì)宏基因組數(shù)據(jù)進(jìn)行聚類，將物種分辨率提高到菌株水平[122]，這些聚類方法包括建立宏基因組連鎖群(metagenomic linkage group, MLG)[121]、宏基因組基因簇(metagenomic clusters, MGC)[123]和宏基因組物種基因群組(metagenomic species, MGS)[124]。特別是2014年Nielsen等[124]提出的MGS方法，可以在不依賴參考基因集的情況下，將微生物基因組鳥(niǎo)槍法測(cè)序數(shù)據(jù)轉(zhuǎn)化成微生物物種信息。

MWAS不僅能鑒定相對(duì)豐度發(fā)生變化的細(xì)菌種類，基于KEGG、COG和EggNOG等數(shù)據(jù)庫(kù)對(duì)基因序列進(jìn)行功能聚類，還能判斷菌群功能的增強(qiáng)與減弱。原則上MWAS可用于研究微生物組與任何性狀之間的關(guān)聯(lián)，但迄今為止還主要集中在II型糖尿病[121]、肥胖[125]、結(jié)直腸癌[126]以及類風(fēng)濕性關(guān)節(jié)炎[127]等病例對(duì)照設(shè)計(jì)研究上。隨著微生物領(lǐng)組領(lǐng)域的發(fā)展，期待未來(lái)MWAS在復(fù)雜的數(shù)量性狀上能得到廣泛的應(yīng)用。

4 結(jié)語(yǔ)與展望

歷經(jīng)百年的發(fā)展和累積，遺傳力的估計(jì)方法不斷改進(jìn)、豐富和完善。將遺傳效應(yīng)的分析模型和統(tǒng)計(jì)方法引入腸道微生物的研究中，為腸道微生物、宿主基因組和宿主表型特征的關(guān)系研究提供了全新的思路。盡管在該方向上取得了顯著的進(jìn)展，但尚處于早期階段，仍然具有挑戰(zhàn)，主要表現(xiàn)在5個(gè)方面：(1)腸菌力的準(zhǔn)確評(píng)估，以及宿主基因組與腸道菌群互作機(jī)制的解析，都需要足夠的樣本量，與人類上的研究相比，畜禽上的相關(guān)研究所使用的樣本數(shù)量相對(duì)較少，在測(cè)序成本以“超摩爾定律”的速度不斷下降的同時(shí)，應(yīng)適當(dāng)擴(kuò)大分析的樣本含量，以增強(qiáng)結(jié)果的可靠性；(2)不管是宏基因組測(cè)序還是擴(kuò)增子測(cè)序，通過(guò)序列相似度進(jìn)行聚類，都存在歸類不準(zhǔn)確的現(xiàn)象，進(jìn)而導(dǎo)致定量的偏差；(3)腸道微生物組是一個(gè)復(fù)雜的多維結(jié)構(gòu)，基于兩種測(cè)序數(shù)據(jù)計(jì)算腸道菌群的遺傳力、鑒定與菌群顯著關(guān)聯(lián)的分子標(biāo)記和評(píng)估腸菌力時(shí)，是否需要考慮微生物之間的互作關(guān)系，以及對(duì)數(shù)據(jù)進(jìn)行質(zhì)控過(guò)濾的條件還有待進(jìn)一步探討；(4)目前對(duì)OTU、重疊群或基因等數(shù)據(jù)的屬性尚無(wú)統(tǒng)一標(biāo)準(zhǔn)，應(yīng)該將其視為二分類屬性(0/1)，還是連續(xù)變異，亦或是將兩者同時(shí)納入考慮，它們的估計(jì)效果又是否有差異亦有待深入論證； (5)尤為重要的一點(diǎn)是，腸道微生物對(duì)外界環(huán)境因素高度敏感，外源環(huán)境因素可能會(huì)掩蓋宿主遺傳變異對(duì)腸道菌群的影響，并且也會(huì)造成腸菌力評(píng)估和MWAS結(jié)果偏差。

隨著測(cè)序技術(shù)的快速發(fā)展，微生物組分析技術(shù)、工具和高質(zhì)量的參考數(shù)據(jù)庫(kù)將升級(jí)換代，隨之而來(lái)的腸道微生物分析所需要的數(shù)據(jù)量、深度和精度將不再成為瓶頸。受回歸法估計(jì)腸菌力的啟示，或許未來(lái)人們可以像估計(jì)SNP效應(yīng)值一樣，估計(jì)OTU、重疊群或微生物基因的效應(yīng)值，以確定哪一類菌群的哪一簇基因與目標(biāo)性狀關(guān)系更為緊密；同時(shí)將微生物效應(yīng)值作為協(xié)變量加入到模型中以提高遺傳評(píng)估的準(zhǔn)確性，如在人類疾病預(yù)測(cè)上，綜合考慮PRS和微生物效應(yīng)可更為準(zhǔn)確的預(yù)測(cè)疾病易感風(fēng)險(xiǎn)。但如何在mGWAS、腸菌力評(píng)估和MWAS過(guò)程中調(diào)整環(huán)境因素的影響是一大挑戰(zhàn)，我們期待結(jié)合數(shù)量遺傳學(xué)的最新理論和方法，腸菌力的估計(jì)會(huì)被進(jìn)一步完善，并將取得更多、更有影響的創(chuàng)新和突破。

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The concepts and research progress: from heritability to microbiability

Chaoliang Wen, Congjiao Sun, Ning Yang

Heritability, one of the central quantitative genetic parameters, is critically important to measure the genetic variation of traits, especially in the studies of the response to selection in evolutionary biology and agriculture, and the prediction of disease risks in medicine. The statistical model and method for estimating heritability have been continually developed and improved, since the genetic variance components was first proposed by Fisher in 1918. Recently, the term “microbiability” (2), an analogous concept and estimated method to heritability, was introduced in gut microbiome research for evaluating the effect of entire microbiota on a host phenotype. In this review, we summarize the progress of statistical methods in the heritability estimation, as well as the current state of gut microbiome associations with the host genome, with a particular focus on the concept and estimated methods of microbiability. Our review will provide a reference for the future study of host phenotypic variation that can be inferred by the gut microbiota.

heritability; microbiability; association study; quantitative trait; variance component; relationship matrix

2019-05-13;

2019-09-23

國(guó)家自然科學(xué)基金項(xiàng)目(編號(hào)：31930105)，國(guó)家現(xiàn)代農(nóng)業(yè)(蛋雞)產(chǎn)業(yè)技術(shù)體系專項(xiàng)資金(編號(hào)：CARS-40)和教育部長(zhǎng)江學(xué)者及創(chuàng)新團(tuán)隊(duì)發(fā)展計(jì)劃(編號(hào)：IRT_15R62)資助[Supported by the National Natural Science Foundation of China (No. 31930105), Programs for Changjiang Scholars and Innovative Research in Universities (No. IRT_15R62) and China Agriculture Research Systems (No. CARS_40)]

文超良，博士研究生，專業(yè)方向：動(dòng)物遺傳育種與繁殖。E-mail: clwen@cau.edu.cn

楊寧，博士，教授，研究方向：家禽分子遺傳與育種。E-mail: nyang@cau.edu.cn

10.16288/j.yczz.19-130

2019/11/7 15:22:05

*：文獻(xiàn)按發(fā)表時(shí)間從先到后排序。

URI: http://kns.cnki.net/kcms/detail/11.1913.R.20191107.1206.004.html

(責(zé)任編委: 李輝)